diff --git a/.gitignore b/.gitignore index aa864ef66..f63879c28 100644 --- a/.gitignore +++ b/.gitignore @@ -168,6 +168,7 @@ framework/contrib/asio/ *.cpr *.cpa-* *.cpr-* +*_cp/ # Ignore petsc arch petsc/arch-*/* @@ -245,3 +246,9 @@ doc/content/verification_and_validation/figures/val-2g_environment_history.png doc/content/examples/figures/fuel_cycle_*.png doc/content/source/interfacekernels/figures/YHx_PCT_*.png doc/content/source/interfacekernels/figures/ZrCoHx_PCT_*.png + +# temporary testharness_time files +*.testharness_time + +# val-2c PSS results +test/tests/val-2c/val-2c_pss_results_short diff --git a/AGENTS.md b/AGENTS.md index 2b6042569..535168001 100644 --- a/AGENTS.md +++ b/AGENTS.md @@ -1,7 +1,7 @@ # AGENTS.md ## Environment -- Use the MOOSE conda environment (`conda activate moose`) +- Ask the user if you need to load a MOOSE conda environment, and if so, what the name of the conda environment is - If `./tmap8-opt` or `run_tests` throws an error, stop and ask the user - Pre-commit hooks handle all formatting and input file validation on every `git commit` — do not invoke `clang-format`, `black`, or `hit format` manually - `moose/framework/contrib/hit/hit check .i` is available to validate input files during development — use it before committing diff --git a/doc/content/agent/200/rollout-2026-03-27T11-05-04-019d3078-9ee5-78f0-838a-4a4a79175713.jsonl b/doc/content/agent/200/rollout-2026-03-27T11-05-04-019d3078-9ee5-78f0-838a-4a4a79175713.jsonl new file mode 100644 index 000000000..c2c863a78 --- /dev/null +++ b/doc/content/agent/200/rollout-2026-03-27T11-05-04-019d3078-9ee5-78f0-838a-4a4a79175713.jsonl @@ -0,0 +1,186 @@ +{"timestamp":"2026-03-27T18:05:37.594Z","type":"session_meta","payload":{"id":"019d3078-9ee5-78f0-838a-4a4a79175713","timestamp":"2026-03-27T18:05:04.614Z","cwd":"/Users/lindad/projects/TMAP8","originator":"codex_cli_rs","cli_version":"0.106.0","source":"cli","model_provider":"openai","base_instructions":{"text":"You are Codex, a coding agent based on GPT-5. You and the user share the same workspace and collaborate to achieve the user's goals.\n\n# Personality\n\nYou are a deeply pragmatic, effective software engineer. You take engineering quality seriously, and collaboration comes through as direct, factual statements. You communicate efficiently, keeping the user clearly informed about ongoing actions without unnecessary detail.\n\n## Values\nYou are guided by these core values:\n- Clarity: You communicate reasoning explicitly and concretely, so decisions and tradeoffs are easy to evaluate upfront.\n- Pragmatism: You keep the end goal and momentum in mind, focusing on what will actually work and move things forward to achieve the user's goal.\n- Rigor: You expect technical arguments to be coherent and defensible, and you surface gaps or weak assumptions politely with emphasis on creating clarity and moving the task forward.\n\n## Interaction Style\nYou communicate concisely and respectfully, focusing on the task at hand. You always prioritize actionable guidance, clearly stating assumptions, environment prerequisites, and next steps. Unless explicitly asked, you avoid excessively verbose explanations about your work.\n\nYou avoid cheerleading, motivational language, or artificial reassurance, or any kind of fluff. You don't comment on user requests, positively or negatively, unless there is reason for escalation. You don't feel like you need to fill the space with words, you stay concise and communicate what is necessary for user collaboration - not more, not less.\n\n## Escalation\nYou may challenge the user to raise their technical bar, but you never patronize or dismiss their concerns. When presenting an alternative approach or solution to the user, you explain the reasoning behind the approach, so your thoughts are demonstrably correct. You maintain a pragmatic mindset when discussing these tradeoffs, and so are willing to work with the user after concerns have been noted.\n\n\n# General\nAs an expert coding agent, your primary focus is writing code, answering questions, and helping the user complete their task in the current environment. You build context by examining the codebase first without making assumptions or jumping to conclusions. You think through the nuances of the code you encounter, and embody the mentality of a skilled senior software engineer.\n\n- When searching for text or files, prefer using `rg` or `rg --files` respectively because `rg` is much faster than alternatives like `grep`. (If the `rg` command is not found, then use alternatives.)\n- Parallelize tool calls whenever possible - especially file reads, such as `cat`, `rg`, `sed`, `ls`, `git show`, `nl`, `wc`. Use `multi_tool_use.parallel` to parallelize tool calls and only this. Never chain together bash commands with separators like `echo \"====\";` as this renders to the user poorly.\n\n## Editing constraints\n\n- Default to ASCII when editing or creating files. Only introduce non-ASCII or other Unicode characters when there is a clear justification and the file already uses them.\n- Add succinct code comments that explain what is going on if code is not self-explanatory. You should not add comments like \"Assigns the value to the variable\", but a brief comment might be useful ahead of a complex code block that the user would otherwise have to spend time parsing out. Usage of these comments should be rare.\n- Always use apply_patch for manual code edits. Do not use cat or any other commands when creating or editing files. Formatting commands or bulk edits don't need to be done with apply_patch.\n- Do not use Python to read/write files when a simple shell command or apply_patch would suffice.\n- You may be in a dirty git worktree.\n * NEVER revert existing changes you did not make unless explicitly requested, since these changes were made by the user.\n * If asked to make a commit or code edits and there are unrelated changes to your work or changes that you didn't make in those files, don't revert those changes.\n * If the changes are in files you've touched recently, you should read carefully and understand how you can work with the changes rather than reverting them.\n * If the changes are in unrelated files, just ignore them and don't revert them.\n- Do not amend a commit unless explicitly requested to do so.\n- While you are working, you might notice unexpected changes that you didn't make. It's likely the user made them, or were autogenerated. If they directly conflict with your current task, stop and ask the user how they would like to proceed. Otherwise, focus on the task at hand.\n- **NEVER** use destructive commands like `git reset --hard` or `git checkout --` unless specifically requested or approved by the user.\n- You struggle using the git interactive console. **ALWAYS** prefer using non-interactive git commands.\n\n## Special user requests\n\n- If the user makes a simple request (such as asking for the time) which you can fulfill by running a terminal command (such as `date`), you should do so.\n- If the user asks for a \"review\", default to a code review mindset: prioritise identifying bugs, risks, behavioural regressions, and missing tests. Findings must be the primary focus of the response - keep summaries or overviews brief and only after enumerating the issues. Present findings first (ordered by severity with file/line references), follow with open questions or assumptions, and offer a change-summary only as a secondary detail. If no findings are discovered, state that explicitly and mention any residual risks or testing gaps.\n\n## Autonomy and persistence\nPersist until the task is fully handled end-to-end within the current turn whenever feasible: do not stop at analysis or partial fixes; carry changes through implementation, verification, and a clear explanation of outcomes unless the user explicitly pauses or redirects you.\n\nUnless the user explicitly asks for a plan, asks a question about the code, is brainstorming potential solutions, or some other intent that makes it clear that code should not be written, assume the user wants you to make code changes or run tools to solve the user's problem. In these cases, it's bad to output your proposed solution in a message, you should go ahead and actually implement the change. If you encounter challenges or blockers, you should attempt to resolve them yourself.\n\n## Frontend tasks\n\nWhen doing frontend design tasks, avoid collapsing into \"AI slop\" or safe, average-looking layouts.\nAim for interfaces that feel intentional, bold, and a bit surprising.\n- Typography: Use expressive, purposeful fonts and avoid default stacks (Inter, Roboto, Arial, system).\n- Color & Look: Choose a clear visual direction; define CSS variables; avoid purple-on-white defaults. No purple bias or dark mode bias.\n- Motion: Use a few meaningful animations (page-load, staggered reveals) instead of generic micro-motions.\n- Background: Don't rely on flat, single-color backgrounds; use gradients, shapes, or subtle patterns to build atmosphere.\n- Ensure the page loads properly on both desktop and mobile\n- For React code, prefer modern patterns including useEffectEvent, startTransition, and useDeferredValue when appropriate if used by the team. Do not add useMemo/useCallback by default unless already used; follow the repo's React Compiler guidance.\n- Overall: Avoid boilerplate layouts and interchangeable UI patterns. Vary themes, type families, and visual languages across outputs.\n\nException: If working within an existing website or design system, preserve the established patterns, structure, and visual language.\n\n# Working with the user\n\nYou interact with the user through a terminal. You have 2 ways of communicating with the users:\n- Share intermediary updates in `commentary` channel. \n- After you have completed all your work, send a message to the `final` channel.\nYou are producing plain text that will later be styled by the program you run in. Formatting should make results easy to scan, but not feel mechanical. Use judgment to decide how much structure adds value. Follow the formatting rules exactly.\n\n## Formatting rules\n\n- You may format with GitHub-flavored Markdown.\n- Structure your answer if necessary, the complexity of the answer should match the task. If the task is simple, your answer should be a one-liner. Order sections from general to specific to supporting.\n- Never use nested bullets. Keep lists flat (single level). If you need hierarchy, split into separate lists or sections or if you use : just include the line you might usually render using a nested bullet immediately after it. For numbered lists, only use the `1. 2. 3.` style markers (with a period), never `1)`.\n- Headers are optional, only use them when you think they are necessary. If you do use them, use short Title Case (1-3 words) wrapped in **…**. Don't add a blank line.\n- Use monospace commands/paths/env vars/code ids, inline examples, and literal keyword bullets by wrapping them in backticks.\n- Code samples or multi-line snippets should be wrapped in fenced code blocks. Include an info string as often as possible.\n- File References: When referencing files in your response follow the below rules:\n * Use markdown links (not inline code) for clickable file paths.\n * Each reference should have a stand alone path. Even if it's the same file.\n * For clickable/openable file references, the path target must be an absolute filesystem path. Labels may be short (for example, `[app.ts](/abs/path/app.ts)`).\n * Optionally include line/column (1‑based): :line[:column] or #Lline[Ccolumn] (column defaults to 1).\n * Do not use URIs like file://, vscode://, or https://.\n * Do not provide range of lines\n- Don’t use emojis or em dashes unless explicitly instructed.\n\n## Final answer instructions\n\nAlways favor conciseness in your final answer - you should usually avoid long-winded explanations and focus only on the most important details. For casual chit-chat, just chat. For simple or single-file tasks, prefer 1-2 short paragraphs plus an optional short verification line. Do not default to bullets. On simple tasks, prose is usually better than a list, and if there are only one or two concrete changes you should almost always keep the close-out fully in prose.\n\nOn larger tasks, use at most 2-3 high-level sections when helpful. Each section can be a short paragraph or a few flat bullets. Prefer grouping by major change area or user-facing outcome, not by file or edit inventory. If the answer starts turning into a changelog, compress it: cut file-by-file detail, repeated framing, low-signal recap, and optional follow-up ideas before cutting outcome, verification, or real risks. Only dive deeper into one aspect of the code change if it's especially complex, important, or if the users asks about it. This also holds true for PR explanations, codebase walkthroughs, or architectural decisions: provide a high-level walkthrough unless specifically asked and cap answers at 2-3 sections.\n\nRequirements for your final answer:\n- Prefer short paragraphs by default.\n- When explaining something, optimize for fast, high-level comprehension rather than completeness-by-default.\n- Use lists only when the content is inherently list-shaped: enumerating distinct items, steps, options, categories, comparisons, ideas. Do not use lists for opinions or straightforward explanations that would read more naturally as prose. If a short paragraph can answer the question more compactly, prefer prose over bullets or multiple sections.\n- Do not turn simple explanations into outlines or taxonomies unless the user asks for depth. If a list is used, each bullet should be a complete standalone point.\n- Do not begin responses with conversational interjections or meta commentary. Avoid openers such as acknowledgements (“Done —”, “Got it”, “Great question, ”, \"You're right to call that out\") or framing phrases.\n- The user does not see command execution outputs. When asked to show the output of a command (e.g. `git show`), relay the important details in your answer or summarize the key lines so the user understands the result.\n- Never tell the user to \"save/copy this file\", the user is on the same machine and has access to the same files as you have.\n- If the user asks for a code explanation, include code references as appropriate.\n- If you weren't able to do something, for example run tests, tell the user.\n- Never use nested bullets. Keep lists flat (single level). If you need hierarchy, split into separate lists or sections or if you use : just include the line you might usually render using a nested bullet immediately after it. For numbered lists, only use the `1. 2. 3.` style markers (with a period), never `1)`.\n- Never overwhelm the user with answers that are over 50-70 lines long; provide the highest-signal context instead of describing everything exhaustively.\n\n## Intermediary updates \n\n- Intermediary updates go to the `commentary` channel.\n- User updates are short updates while you are working, they are NOT final answers.\n- You use 1-2 sentence user updates to communicated progress and new information to the user as you are doing work. \n- Do not begin responses with conversational interjections or meta commentary. Avoid openers such as acknowledgements (“Done —”, “Got it”, “Great question, ”) or framing phrases.\n- Before exploring or doing substantial work, you start with a user update acknowledging the request and explaining your first step. You should include your understanding of the user request and explain what you will do. Avoid commenting on the request or using starters such at \"Got it -\" or \"Understood -\" etc.\n- You provide user updates frequently, every 30s.\n- When exploring, e.g. searching, reading files you provide user updates as you go, explaining what context you are gathering and what you've learned. Vary your sentence structure when providing these updates to avoid sounding repetitive - in particular, don't start each sentence the same way.\n- When working for a while, keep updates informative and varied, but stay concise.\n- After you have sufficient context, and the work is substantial you provide a longer plan (this is the only user update that may be longer than 2 sentences and can contain formatting).\n- Before performing file edits of any kind, you provide updates explaining what edits you are making.\n- As you are thinking, you very frequently provide updates even if not taking any actions, informing the user of your progress. You interrupt your thinking and send multiple updates in a row if thinking for more than 100 words.\n- Tone of your updates MUST match your personality.\n"},"git":{"commit_hash":"d997bd404cecd8d2de36f38e55b037f7f126acab","branch":"try-some-regularization","repository_url":"git@github.com:lindsayad/TMAP8.git"}}} +{"timestamp":"2026-03-27T18:05:37.595Z","type":"response_item","payload":{"type":"message","role":"developer","content":[{"type":"input_text","text":"\nFilesystem sandboxing defines which files can be read or written. `sandbox_mode` is `workspace-write`: The sandbox permits reading files, and editing files in `cwd` and `writable_roots`. Editing files in other directories requires approval. Network access is restricted.\n# Escalation Requests\n\nCommands are run outside the sandbox if they are approved by the user, or match an existing rule that allows it to run unrestricted. The command string is split into independent command segments at shell control operators, including but not limited to:\n\n- Pipes: |\n- Logical operators: &&, ||\n- Command separators: ;\n- Subshell boundaries: (...), $(...)\n\nEach resulting segment is evaluated independently for sandbox restrictions and approval requirements.\n\nExample:\n\ngit pull | tee output.txt\n\nThis is treated as two command segments:\n\n[\"git\", \"pull\"]\n\n[\"tee\", \"output.txt\"]\n\n## How to request escalation\n\nIMPORTANT: To request approval to execute a command that will require escalated privileges:\n\n- Provide the `sandbox_permissions` parameter with the value `\"require_escalated\"`\n- Include a short question asking the user if they want to allow the action in `justification` parameter. e.g. \"Do you want to download and install dependencies for this project?\"\n- Optionally suggest a `prefix_rule` - this will be shown to the user with an option to persist the rule approval for future sessions.\n\nIf you run a command that is important to solving the user's query, but it fails because of sandboxing, rerun the command with \"require_escalated\". ALWAYS proceed to use the `justification` parameter - do not message the user before requesting approval for the command.\n\n## When to request escalation\n\nWhile commands are running inside the sandbox, here are some scenarios that will require escalation outside the sandbox:\n\n- You need to run a command that writes to a directory that requires it (e.g. running tests that write to /var)\n- You need to run a GUI app (e.g., open/xdg-open/osascript) to open browsers or files.\n- If you run a command that is important to solving the user's query, but it fails because of sandboxing, rerun the command with `require_escalated`. ALWAYS proceed to use the `sandbox_permissions` and `justification` parameters. do not message the user before requesting approval for the command.\n- You are about to take a potentially destructive action such as an `rm` or `git reset` that the user did not explicitly ask for.\n- Be judicious with escalating, but if completing the user's request requires it, you should do so - don't try and circumvent approvals by using other tools.\n\n## prefix_rule guidance\n\nWhen choosing a `prefix_rule`, request one that will allow you to fulfill similar requests from the user in the future without re-requesting escalation. It should be categorical and reasonably scoped to similar capabilities. You should rarely pass the entire command into `prefix_rule`.\n\n### Banned prefix_rules \nAvoid requesting overly broad prefixes that the user would be ill-advised to approve. For example, do not request [\"python3\"], [\"python\", \"-\"], or other similar prefixes.\nNEVER provide a prefix_rule argument for destructive commands like rm.\nNEVER provide a prefix_rule if your command uses a heredoc or herestring. \n\n### Examples\nGood examples of prefixes:\n- [\"npm\", \"run\", \"dev\"]\n- [\"gh\", \"pr\", \"check\"]\n- [\"pytest\"]\n- [\"cargo\", \"test\"]\n\n\n## Approved command prefixes\nThe following prefix rules have already been approved: - [\"git\", \"add\"]\n- [\"git\", \"commit\"]\n- [\"mpiexec\", \"-n\"]\n- [\"./tmap8-opt\", \"-i\"]\n- [\"./tmap8-devel\", \"-i\"]\n- [\"/bin/bash\", \"scripts/build_tmap8_devel.sh\"]\n- [\"./test/moose_test-dbg\", \"--show-capabilities\"]\n- [\"/bin/bash\", \"scripts/run_tests_val_2f_dimensionless.sh\"]\n- [\"/bin/bash\", \"scripts/run_val_2f_dimensionless_light.sh\"]\n- [\"/bin/bash\", \"scripts/run_val_2f_dimensionless_light_charge.sh\"]\n- [\"/bin/bash\", \"scripts/run_tests_val_2f_dimensionless_parallel.sh\"]\n- [\"/bin/bash\", \"scripts/run_val_2f_dimensionless_first_step_svd.sh\"]\n- [\"/bin/bash\", \"scripts/run_val_2f_dimensionless_light_scheduled.sh\"]\n- [\"git\", \"commit\", \"--amend\"]\n- [\"/bin/bash\", \"-lc\", \"rg -n \\\"VIRS|virs|VIRS\\\" \\\"$HOME/projects/moose/petsc\\\"\"]\n- [\"/bin/bash\", \"-lc\", \"sed -n '1,260p' \\\"$HOME/projects/moose/petsc/src/snes/impls/vi/vi.c\\\"\"]\n- [\"cp\", \"test/tests/val-2f/val-2f_light_out.e\", \"test/tests/val-2f/gold/val-2f_light_out.e\"]\n- [\"cp\", \"test/tests/val-2f/val-2f_light_out.csv\", \"test/tests/val-2f/gold/val-2f_light_out.csv\"]\n- [\"/bin/bash\", \"-lc\", \"sed -n '1,260p' \\\"$HOME/projects/moose/petsc/src/snes/impls/vi/rs/virs.c\\\"\"]\n- [\"/bin/bash\", \"-lc\", \"sed -n '260,520p' \\\"$HOME/projects/moose/petsc/src/snes/impls/vi/rs/virs.c\\\"\"]\n- [\"/bin/bash\", \"-lc\", \"sed -n '520,780p' \\\"$HOME/projects/moose/petsc/src/snes/impls/vi/rs/virs.c\\\"\"]\n- [\"/bin/bash\", \"-lc\", \"sed -n '1,220p' \\\"$HOME/projects/moose/petsc/src/snes/impls/vi/rs/virsimpl.h\\\"\"]\n- [\"/bin/bash\", \"-lc\", \"sed -n '1,260p' \\\"$HOME/projects/moose/petsc/src/snes/linesearch/interface/linesearch.c\\\"\"]\n- [\"/bin/bash\", \"-lc\", \"sed -n '1,260p' \\\"$HOME/projects/moose/petsc/src/snes/linesearch/impls/bt/linesearchbt.c\\\"\"]\n- [\"/bin/bash\", \"-lc\", \"/bin/bash scripts/run_val_2f_dimensionless_light_scheduled.sh > /tmp/val2f_sched.log 2>&1\"]\n- [\"/bin/bash\", \"-lc\", \"source \\\"$HOME/miniforge/etc/profile.d/conda.sh\\\" && conda activate moose-mpich && make -j8\"]\n- [\"/bin/bash\", \"-lc\", \"sed -n '260,420p' \\\"$HOME/projects/moose/petsc/src/snes/linesearch/impls/bt/linesearchbt.c\\\"\"]\n- [\"/bin/bash\", \"-lc\", \"/bin/bash scripts/run_val_2f_dimensionless_scheduled_svd.sh 1 > /tmp/val2f_svd_step1.log 2>&1\"]\n- [\"/bin/bash\", \"-lc\", \"/bin/bash scripts/run_val_2f_dimensionless_scheduled_svd.sh 272 > /tmp/val2f_svd_full.log 2>&1\"]\n- [\"/bin/bash\", \"-lc\", \"/bin/bash scripts/run_val_2f_dimensionless_light_scheduled.sh > /tmp/val2f_sched_regularized.log 2>&1\"]\n- [\"/bin/bash\", \"-lc\", \"rg -n \\\"SNESLineSearch.*VIRS|SNESLINESEARCHVIRS|SNESLineSearchApply_VIRS\\\" \\\"$HOME/projects/moose/petsc\\\"\"]\n- [\"/bin/bash\", \"-lc\", \"source \\\"$HOME/miniforge/etc/profile.d/conda.sh\\\" && conda activate moose-mpich && ./run_tests -j 1 --re 'val-2f_light_csv$'\"]\n- [\"/bin/bash\", \"-lc\", \"source \\\"$HOME/miniforge/etc/profile.d/conda.sh\\\" && conda activate moose-mpich && CXXFLAGS='-std=c++20' METHOD=dbg make -j16\"]\n- [\"/bin/bash\", \"-lc\", \"source \\\"$HOME/miniforge/etc/profile.d/conda.sh\\\" && conda activate moose-mpich && ./run_tests -j 1 --re 'val-2f_light_(csv|exodus)$'\"]\n- [\"/bin/bash\", \"-lc\", \"source \\\"$HOME/miniforge/etc/profile.d/conda.sh\\\" && conda activate moose-mpich && CXXFLAGS='-std=c++20' METHOD=dbg make -j16 moose_test-dbg\"]\n- [\"/bin/bash\", \"-lc\", \"source \\\"$HOME/miniforge/etc/profile.d/conda.sh\\\" && conda activate moose-mpich && ./run_tests -j 1 --dbg --re 'mms-kokkos-diffusion-2d-orthogonal'\"]\n- [\"/bin/bash\", \"-lc\", \"source \\\"$HOME/miniforge/etc/profile.d/conda.sh\\\" && conda activate moose-mpich && ./run_tests --dbg --re \\\"kokkos.*linearfvkernels\\\" --ignore-capability=method\"]\n- [\"/bin/bash\", \"-lc\", \"source \\\"$HOME/miniforge/etc/profile.d/conda.sh\\\" && conda activate moose-mpich && ./moose_test-dbg -i tests/kokkos/linearfvkernels/diffusion/kokkos_diffusion-2d.i\"]\n- [\"/bin/bash\", \"-lc\", \"rg -n \\\"LineSearch|project|Projection|bound|VecPointwiseMin|VecPointwiseMax|SNESVIProject|inactive|active\\\" \\\"$HOME/projects/moose/petsc/src/snes/impls/vi/rs/virs.c\\\"\"]\n- [\"/bin/bash\", \"-lc\", \"source \\\"$HOME/miniforge/etc/profile.d/conda.sh\\\" && conda activate moose-mpich && ./run_tests -j 1 --re 'ver-1d_trapping_limited(_ad_scaled_coupled_time|_scaled_trap_equation)?$'\"]\n- [\"/bin/bash\", \"-lc\", \"source \\\"$HOME/miniforge/etc/profile.d/conda.sh\\\" && conda activate moose-mpich && ./run_tests -j 1 --re 'physics/more_species_on_component|ver-1d_trapping_limited(_ad_scaled_coupled_time)?$'\"]\n- [\"/bin/bash\", \"-lc\", \"source \\\"$HOME/miniforge/etc/profile.d/conda.sh\\\" && conda activate moose-mpich && lldb --batch -o run -o bt -- ./moose_test-dbg -i tests/kokkos/linearfvkernels/diffusion/kokkos_diffusion-2d.i\"]\n- [\"/bin/bash\", \"-lc\", \"source \\\"$HOME/miniforge/etc/profile.d/conda.sh\\\" && conda activate moose-mpich && lldb ./moose_test-dbg -o 'settings set -- target.run-args -i tests/kokkos/linearfvkernels/diffusion/kokkos_diffusion-2d.i'\"]\n- [\"/bin/bash\", \"-lc\", \"source \\\"$HOME/miniforge/etc/profile.d/conda.sh\\\" && conda activate moose-mpich && lldb --batch -o 'break set -E c++' -o run -o bt -- ./moose_test-dbg -i tests/kokkos/linearfvkernels/diffusion/kokkos_diffusion-2d.i\"]\n- [...\n[Some commands were truncated]\n The writable roots are `/Users/lindad/projects/TMAP8`, `/tmp`, `/var/folders/_4/0z2qtsqd0_v_cld9r500s5wj8h3w_z/T`.\n"}]}} +{"timestamp":"2026-03-27T18:05:37.596Z","type":"response_item","payload":{"type":"message","role":"user","content":[{"type":"input_text","text":"# AGENTS.md instructions for /Users/lindad/projects/TMAP8\n\n\n# AGENTS.md\n\n## Environment\n- Ask the user if you need to load a MOOSE conda environment, and if so, what the name of the conda environment is\n- If `./tmap8-opt` or `run_tests` throws an error, stop and ask the user\n- Pre-commit hooks handle all formatting and input file validation on every `git commit` — do not invoke `clang-format`, `black`, or `hit format` manually\n- `moose/framework/contrib/hit/hit check .i` is available to validate input files during development — use it before committing\n\n## Before writing any code or input file\n- Browse `doc/content/` to understand documentation standards and existing patterns before starting work\n- Before writing a new C++ class, look through existing MOOSE classes in the codebase to confirm expected syntax and patterns\n- Documentation in `doc/content/` may not accurately reflect current code behavior — once you identify a class to use in an input file, find its C++ implementation and read it to confirm the class does what you expect before writing the input file\n\n## C++ code\n- Every new class requires a MOOSE TestHarness test in `test/tests/` before committing\n- Every new class requires a MooseDocs page following existing TMAP8 doc structure\n- Never hardcode physical parameters — first check if it is already defined in `doc/content/source/utils/TMAP8PhysicalConstants`, and if not available, expose everything through `addParam`\n- Code is unit-agnostic; units live in input files only\n\n## Input files\n- Before writing an input file, look through existing MOOSE and TMAP8 classes to confirm object names and parameter syntax\n- Use `moose/framework/contrib/hit/hit check .i` to validate before committing\n- Use `./tmap8-opt -i .i` to run input files\n- Write parameter values in the units the reference source used; use the MOOSE units system for conversion — the units system is self-documenting and does not require inline comments\n- State the unit system at the top of every input file in a comment block\n\n## Testing\n- Run tests only when `.C`, `.h`, or `test/tests/` files change\n- Run only the affected module: `./run_tests -j --re `\n\n## Session log\n- Every session must be associated with a GitHub issue on `idaholab/TMAP8`; ask the user for the issue number at the start of the session if one is not provided, or create one if the user instructs you to\n- **SQA requirement:** When creating a GitHub issue with `gh`, you must use the appropriate template from `.github/ISSUE_TEMPLATE/`; read the available templates first, select the one that fits (e.g. `bug-report.md` for bugs, `feature-request.md` for new features or tasks), and populate all sections in the template body — passing a bare description without following the template structure is not acceptable\n- Before committing, copy the current session's `.jsonl` file into `doc/content/agent//`. For Claude Code sessions the file is the most recently modified `.jsonl` under `~/.claude/projects//`; for Codex sessions check the equivalent Codex session directory. Do not remove old session files already in that directory — append the new one alongside them.\n\n## Committing\n- Commit at minimum after: every input file that successfully runs, every test that passes or fails, and every new class added\n- If a test or run failed, commit the failure state first (include the full error message in the commit body), then commit the fix separately\n- Every commit must reference the associated GitHub issue (e.g. `Refs #` or `Closes #` as appropriate) in the commit message\n- **Every commit must include an updated copy of the session `.jsonl`** — before staging, copy the current session file from `~/.claude/projects//.jsonl` to `doc/content/agent//` and stage it; this is a critical SQA requirement. Do not remove session files already present in that directory — if multiple Claude/Codex sessions contribute to the same branch and issue, all session files must be kept.\n- Every commit must include these trailers:\n```\nRefs #\nAI-assisted: true\nAI-model: \nAI-version: \nCo-Authored-By: \n```\n\n## Pull requests\n- If the linked issue already contains a complete Reason/Design/Impact description, the PR body should contain only the closing reference (e.g. `Closes #`) — do not duplicate the issue content or leave template sections empty\n- If the PR introduces physics/modeling decisions, non-obvious AI reasoning, or tests not described in the issue, add those as a short addendum below the issue reference\n- Never merge autonomously\n\n## Never do\n- Modify existing passing tests without explicit user instruction\n- Modify the build system without explicit user instruction\n- Make physics modeling decisions without flagging them to the user\n- Suppress or bypass test failures\n\n\n## Skills\nA skill is a set of local instructions to follow that is stored in a `SKILL.md` file. Below is the list of skills that can be used. Each entry includes a name, description, and file path so you can open the source for full instructions when using a specific skill.\n### Available skills\n- openai-docs: Use when the user asks how to build with OpenAI products or APIs and needs up-to-date official documentation with citations, help choosing the latest model for a use case, or explicit GPT-5.4 upgrade and prompt-upgrade guidance; prioritize OpenAI docs MCP tools, use bundled references only as helper context, and restrict any fallback browsing to official OpenAI domains. (file: /Users/lindad/.codex/skills/.system/openai-docs/SKILL.md)\n- plugin-creator: Create and scaffold plugin directories for Codex with a required `.codex-plugin/plugin.json`, optional plugin folders/files, and baseline placeholders you can edit before publishing or testing. Use when Codex needs to create a new local plugin, add optional plugin structure, or generate or update repo-root `.agents/plugins/marketplace.json` entries for plugin ordering and availability metadata. (file: /Users/lindad/.codex/skills/.system/plugin-creator/SKILL.md)\n- skill-creator: Guide for creating effective skills. This skill should be used when users want to create a new skill (or update an existing skill) that extends Codex's capabilities with specialized knowledge, workflows, or tool integrations. (file: /Users/lindad/.codex/skills/.system/skill-creator/SKILL.md)\n- skill-installer: Install Codex skills into $CODEX_HOME/skills from a curated list or a GitHub repo path. Use when a user asks to list installable skills, install a curated skill, or install a skill from another repo (including private repos). (file: /Users/lindad/.codex/skills/.system/skill-installer/SKILL.md)\n### How to use skills\n- Discovery: The list above is the skills available in this session (name + description + file path). Skill bodies live on disk at the listed paths.\n- Trigger rules: If the user names a skill (with `$SkillName` or plain text) OR the task clearly matches a skill's description shown above, you must use that skill for that turn. Multiple mentions mean use them all. Do not carry skills across turns unless re-mentioned.\n- Missing/blocked: If a named skill isn't in the list or the path can't be read, say so briefly and continue with the best fallback.\n- How to use a skill (progressive disclosure):\n 1) After deciding to use a skill, open its `SKILL.md`. Read only enough to follow the workflow.\n 2) When `SKILL.md` references relative paths (e.g., `scripts/foo.py`), resolve them relative to the skill directory listed above first, and only consider other paths if needed.\n 3) If `SKILL.md` points to extra folders such as `references/`, load only the specific files needed for the request; don't bulk-load everything.\n 4) If `scripts/` exist, prefer running or patching them instead of retyping large code blocks.\n 5) If `assets/` or templates exist, reuse them instead of recreating from scratch.\n- Coordination and sequencing:\n - If multiple skills apply, choose the minimal set that covers the request and state the order you'll use them.\n - Announce which skill(s) you're using and why (one short line). If you skip an obvious skill, say why.\n- Context hygiene:\n - Keep context small: summarize long sections instead of pasting them; only load extra files when needed.\n - Avoid deep reference-chasing: prefer opening only files directly linked from `SKILL.md` unless you're blocked.\n - When variants exist (frameworks, providers, domains), pick only the relevant reference file(s) and note that choice.\n- Safety and fallback: If a skill can't be applied cleanly (missing files, unclear instructions), state the issue, pick the next-best approach, and continue.\n"},{"type":"input_text","text":"\n /Users/lindad/projects/TMAP8\n bash\n"}]}} +{"timestamp":"2026-03-27T18:05:37.601Z","type":"event_msg","payload":{"type":"task_started","turn_id":"019d3079-1f59-7a90-b02b-926b44d14497","model_context_window":258400,"collaboration_mode_kind":"default"}} +{"timestamp":"2026-03-27T18:05:37.603Z","type":"response_item","payload":{"type":"message","role":"developer","content":[{"type":"input_text","text":"# Collaboration Mode: Default\n\nYou are now in Default mode. Any previous instructions for other modes (e.g. Plan mode) are no longer active.\n\nYour active mode changes only when new developer instructions with a different `...` change it; user requests or tool descriptions do not change mode by themselves. Known mode names are Default and Plan.\n\n## request_user_input availability\n\nThe `request_user_input` tool is unavailable in Default mode. If you call it while in Default mode, it will return an error.\n\nIn Default mode, strongly prefer making reasonable assumptions and executing the user's request rather than stopping to ask questions. If you absolutely must ask a question because the answer cannot be discovered from local context and a reasonable assumption would be risky, ask the user directly with a concise plain-text question. Never write a multiple choice question as a textual assistant message.\n"}]}} +{"timestamp":"2026-03-27T18:05:37.607Z","type":"response_item","payload":{"type":"message","role":"user","content":[{"type":"input_text","text":"Please remove/replace all non-ascii characters introduced since commit 7d1a0b5b"}]}} +{"timestamp":"2026-03-27T18:05:37.609Z","type":"event_msg","payload":{"type":"user_message","message":"Please remove/replace all non-ascii characters introduced since commit 7d1a0b5b","images":[],"local_images":[],"text_elements":[]}} +{"timestamp":"2026-03-27T18:05:37.613Z","type":"turn_context","payload":{"turn_id":"019d3079-1f59-7a90-b02b-926b44d14497","cwd":"/Users/lindad/projects/TMAP8","approval_policy":"on-request","sandbox_policy":{"type":"workspace-write","network_access":false,"exclude_tmpdir_env_var":false,"exclude_slash_tmp":false},"model":"gpt-5.4","personality":"pragmatic","collaboration_mode":{"mode":"default","settings":{"model":"gpt-5.4","reasoning_effort":"medium","developer_instructions":"# Collaboration Mode: Default\n\nYou are now in Default mode. Any previous instructions for other modes (e.g. Plan mode) are no longer active.\n\nYour active mode changes only when new developer instructions with a different `...` change it; user requests or tool descriptions do not change mode by themselves. Known mode names are Default and Plan.\n\n## request_user_input availability\n\nThe `request_user_input` tool is unavailable in Default mode. If you call it while in Default mode, it will return an error.\n\nIn Default mode, strongly prefer making reasonable assumptions and executing the user's request rather than stopping to ask questions. If you absolutely must ask a question because the answer cannot be discovered from local context and a reasonable assumption would be risky, ask the user directly with a concise plain-text question. Never write a multiple choice question as a textual assistant message.\n"}},"effort":"medium","summary":"auto","user_instructions":"# AGENTS.md\n\n## Environment\n- Ask the user if you need to load a MOOSE conda environment, and if so, what the name of the conda environment is\n- If `./tmap8-opt` or `run_tests` throws an error, stop and ask the user\n- Pre-commit hooks handle all formatting and input file validation on every `git commit` — do not invoke `clang-format`, `black`, or `hit format` manually\n- `moose/framework/contrib/hit/hit check .i` is available to validate input files during development — use it before committing\n\n## Before writing any code or input file\n- Browse `doc/content/` to understand documentation standards and existing patterns before starting work\n- Before writing a new C++ class, look through existing MOOSE classes in the codebase to confirm expected syntax and patterns\n- Documentation in `doc/content/` may not accurately reflect current code behavior — once you identify a class to use in an input file, find its C++ implementation and read it to confirm the class does what you expect before writing the input file\n\n## C++ code\n- Every new class requires a MOOSE TestHarness test in `test/tests/` before committing\n- Every new class requires a MooseDocs page following existing TMAP8 doc structure\n- Never hardcode physical parameters — first check if it is already defined in `doc/content/source/utils/TMAP8PhysicalConstants`, and if not available, expose everything through `addParam`\n- Code is unit-agnostic; units live in input files only\n\n## Input files\n- Before writing an input file, look through existing MOOSE and TMAP8 classes to confirm object names and parameter syntax\n- Use `moose/framework/contrib/hit/hit check .i` to validate before committing\n- Use `./tmap8-opt -i .i` to run input files\n- Write parameter values in the units the reference source used; use the MOOSE units system for conversion — the units system is self-documenting and does not require inline comments\n- State the unit system at the top of every input file in a comment block\n\n## Testing\n- Run tests only when `.C`, `.h`, or `test/tests/` files change\n- Run only the affected module: `./run_tests -j --re `\n\n## Session log\n- Every session must be associated with a GitHub issue on `idaholab/TMAP8`; ask the user for the issue number at the start of the session if one is not provided, or create one if the user instructs you to\n- **SQA requirement:** When creating a GitHub issue with `gh`, you must use the appropriate template from `.github/ISSUE_TEMPLATE/`; read the available templates first, select the one that fits (e.g. `bug-report.md` for bugs, `feature-request.md` for new features or tasks), and populate all sections in the template body — passing a bare description without following the template structure is not acceptable\n- Before committing, copy the current session's `.jsonl` file into `doc/content/agent//`. For Claude Code sessions the file is the most recently modified `.jsonl` under `~/.claude/projects//`; for Codex sessions check the equivalent Codex session directory. Do not remove old session files already in that directory — append the new one alongside them.\n\n## Committing\n- Commit at minimum after: every input file that successfully runs, every test that passes or fails, and every new class added\n- If a test or run failed, commit the failure state first (include the full error message in the commit body), then commit the fix separately\n- Every commit must reference the associated GitHub issue (e.g. `Refs #` or `Closes #` as appropriate) in the commit message\n- **Every commit must include an updated copy of the session `.jsonl`** — before staging, copy the current session file from `~/.claude/projects//.jsonl` to `doc/content/agent//` and stage it; this is a critical SQA requirement. Do not remove session files already present in that directory — if multiple Claude/Codex sessions contribute to the same branch and issue, all session files must be kept.\n- Every commit must include these trailers:\n```\nRefs #\nAI-assisted: true\nAI-model: \nAI-version: \nCo-Authored-By: \n```\n\n## Pull requests\n- If the linked issue already contains a complete Reason/Design/Impact description, the PR body should contain only the closing reference (e.g. `Closes #`) — do not duplicate the issue content or leave template sections empty\n- If the PR introduces physics/modeling decisions, non-obvious AI reasoning, or tests not described in the issue, add those as a short addendum below the issue reference\n- Never merge autonomously\n\n## Never do\n- Modify existing passing tests without explicit user instruction\n- Modify the build system without explicit user instruction\n- Make physics modeling decisions without flagging them to the user\n- Suppress or bypass test failures\n\n\n## Skills\nA skill is a set of local instructions to follow that is stored in a `SKILL.md` file. Below is the list of skills that can be used. Each entry includes a name, description, and file path so you can open the source for full instructions when using a specific skill.\n### Available skills\n- openai-docs: Use when the user asks how to build with OpenAI products or APIs and needs up-to-date official documentation with citations, help choosing the latest model for a use case, or explicit GPT-5.4 upgrade and prompt-upgrade guidance; prioritize OpenAI docs MCP tools, use bundled references only as helper context, and restrict any fallback browsing to official OpenAI domains. (file: /Users/lindad/.codex/skills/.system/openai-docs/SKILL.md)\n- plugin-creator: Create and scaffold plugin directories for Codex with a required `.codex-plugin/plugin.json`, optional plugin folders/files, and baseline placeholders you can edit before publishing or testing. Use when Codex needs to create a new local plugin, add optional plugin structure, or generate or update repo-root `.agents/plugins/marketplace.json` entries for plugin ordering and availability metadata. (file: /Users/lindad/.codex/skills/.system/plugin-creator/SKILL.md)\n- skill-creator: Guide for creating effective skills. This skill should be used when users want to create a new skill (or update an existing skill) that extends Codex's capabilities with specialized knowledge, workflows, or tool integrations. (file: /Users/lindad/.codex/skills/.system/skill-creator/SKILL.md)\n- skill-installer: Install Codex skills into $CODEX_HOME/skills from a curated list or a GitHub repo path. Use when a user asks to list installable skills, install a curated skill, or install a skill from another repo (including private repos). (file: /Users/lindad/.codex/skills/.system/skill-installer/SKILL.md)\n### How to use skills\n- Discovery: The list above is the skills available in this session (name + description + file path). Skill bodies live on disk at the listed paths.\n- Trigger rules: If the user names a skill (with `$SkillName` or plain text) OR the task clearly matches a skill's description shown above, you must use that skill for that turn. Multiple mentions mean use them all. Do not carry skills across turns unless re-mentioned.\n- Missing/blocked: If a named skill isn't in the list or the path can't be read, say so briefly and continue with the best fallback.\n- How to use a skill (progressive disclosure):\n 1) After deciding to use a skill, open its `SKILL.md`. Read only enough to follow the workflow.\n 2) When `SKILL.md` references relative paths (e.g., `scripts/foo.py`), resolve them relative to the skill directory listed above first, and only consider other paths if needed.\n 3) If `SKILL.md` points to extra folders such as `references/`, load only the specific files needed for the request; don't bulk-load everything.\n 4) If `scripts/` exist, prefer running or patching them instead of retyping large code blocks.\n 5) If `assets/` or templates exist, reuse them instead of recreating from scratch.\n- Coordination and sequencing:\n - If multiple skills apply, choose the minimal set that covers the request and state the order you'll use them.\n - Announce which skill(s) you're using and why (one short line). If you skip an obvious skill, say why.\n- Context hygiene:\n - Keep context small: summarize long sections instead of pasting them; only load extra files when needed.\n - Avoid deep reference-chasing: prefer opening only files directly linked from `SKILL.md` unless you're blocked.\n - When variants exist (frameworks, providers, domains), pick only the relevant reference file(s) and note that choice.\n- Safety and fallback: If a skill can't be applied cleanly (missing files, unclear instructions), state the issue, pick the next-best approach, and continue.","truncation_policy":{"mode":"tokens","limit":10000}}} +{"timestamp":"2026-03-27T18:05:37.770Z","type":"event_msg","payload":{"type":"token_count","info":null,"rate_limits":{"limit_id":"codex","limit_name":null,"primary":{"used_percent":13.0,"window_minutes":300,"resets_at":1774643092},"secondary":{"used_percent":26.0,"window_minutes":10080,"resets_at":1774905636},"credits":null,"plan_type":"enterprise"}}} +{"timestamp":"2026-03-27T18:05:42.250Z","type":"event_msg","payload":{"type":"agent_reasoning","text":"**Inspecting git diff**\n\nI need to check the git diff since the last commit to look for any non-ASCII characters in the changed files. I'll also ask for the issue number at the beginning if it hasn't been provided—it's required before I start substantial work, after all. Before making any code edits, I should browse the documentation to ensure I’m following the content standards per AGENTS. Since this is a simple code edit, I might not need conda, so I'll ask a concise question."}} +{"timestamp":"2026-03-27T18:05:42.251Z","type":"response_item","payload":{"type":"reasoning","summary":[{"type":"summary_text","text":"**Inspecting git diff**\n\nI need to check the git diff since the last commit to look for any non-ASCII characters in the changed files. I'll also ask for the issue number at the beginning if it hasn't been provided—it's required before I start substantial work, after all. Before making any code edits, I should browse the documentation to ensure I’m following the content standards per AGENTS. Since this is a simple code edit, I might not need conda, so I'll ask a concise question."}],"content":null,"encrypted_content":"gAAAAABpxsb2jNW_f4hGrjnuJhHsqYUqJe9Shi7P6Dicd5l3lYs7BfCk1lhwb5JZW8fqCGZILZClpJAmqgoK29R5x_RQevhp-5sCRiC7GpfjEWHj-oQ3IEReU8yWZOvVXWm6LTyYrUVu_eP9-Q8d9Y5UEQZmIFNwNc06Ew6mzvhq9eJlYwO6ezE0v2Y2qhAuXam8BQ_GdsMxBOSGuTbk68G0ZxpsXMbZ5tJaWeVFslAOLOOCOr_Vv21DdZAKKI8F9l6r9erUwmrGbyYRv_uIdnqGc2Ss02DcqqsMTsv5VPml9uFe0HWIgyQ51m0W-ZKcDaG6yR1-vLP6qma8NTvWXuYd8rF2rYYRCEflmbVKiODWZOQPnk5bGWH6M2SYQuyyqfm1_9neuqBZX7j0TdOKth8-KzeidAkr0kgbRfvab7moYeeR5VFFi70orYhjm9tSq3CqB8Vj0djuHNdI9FSPy3_2KBwnYkshP4bd41LOh-1n1vG1JzS9Qy2ep3_Ur9A-NR5Ql6xduqBBZYL9MIEqRTlsAuScHnqQegTqe5Bv9EMc9-HeQF02ut71baG2gYrLueU1Z_XlcujCD3xtkdCgd2K3YXEqTXHZBlm0Eu9HXy29R1txnbCaSmRho1FRNyj_hssnrxiKnBJQyrdhN_1C_24MJStbr1scigEYd2qnPWnR7ShyhHisddrR5Lcq2Jw23DjygU2tUuArYC8LqzemWU2aCG3j2hhaS6_smG-NqxyXcFDNgP6bvzmUH3JFs84_QBPbzK9hZbEqTnweow6kL4Uec41rhYrHcOBsSZGWIab8MBakJ7e36N2eFAkWMvXhxDpPNS0VH0kdVSgXMUYQePfzYlDcjo8YsgFDqPr1COHA8LqJRzYwiDT1a9iLgACECb3g92nknK-JAJ40B_Wl6eUitKKQ1e_YVEYCOXm2tX-8gb1KMAg4PuGIWduECm1jb6_SEmZUDKBmWl4AYrl_e8rzUFHg605TEYfoTtUMJyvpbgN9JInI-MYeP4--_zIK_fhZyzSF3J2EeiVnp_WcrUqNXvTLzFjey5QNEMVdUuuvBfNYzXPDN2pS9wtsU-NtDzgFrV_g_afLSU5EAxihdAa48xrF75IPnAA8SD988gmwkffl9R4AGZV14m7MhDBRL6oleVh-hU5_X-gSEHGegAOBQ5nRAvbVXPfV_ol-2wXL0JE7XQIYBmN1gNeKqnuSzxlz1dhfSDr8H1THKoAYHr2qHzJpRviRwt1ww8pmT0dzvCqU_4fMLZRv9BdFFdIeBKxTarbGskwkzw7O1fF-AvggZX2O0A7LH-_lf6JsN8NctJWliYlw6DjfK44DQOxdREiDKCGVTX4hI8Nzxq-MN8bDCKlk2fvdlfj22a7GRS34HO_cMAfU0DQD0LOG9ORCG-5aegRGS4d0"}} +{"timestamp":"2026-03-27T18:05:42.327Z","type":"event_msg","payload":{"type":"agent_message","message":"I need the GitHub issue number for this session before I make changes. After that I’ll inspect the diff since `7d1a0b5b`, identify any non-ASCII characters added after that commit, and replace them with ASCII-safe text.","phase":"commentary"}} +{"timestamp":"2026-03-27T18:05:42.327Z","type":"response_item","payload":{"type":"message","role":"assistant","content":[{"type":"output_text","text":"I need the GitHub issue number for this session before I make changes. After that I’ll inspect the diff since `7d1a0b5b`, identify any non-ASCII characters added after that commit, and replace them with ASCII-safe text."}],"phase":"commentary"}} +{"timestamp":"2026-03-27T18:05:42.399Z","type":"event_msg","payload":{"type":"agent_message","message":"I need the GitHub issue number for this session before I make changes. After that I’ll inspect the diff since `7d1a0b5b`, identify any non-ASCII characters added after that commit, and replace them with ASCII-safe text.","phase":"final_answer"}} +{"timestamp":"2026-03-27T18:05:42.399Z","type":"response_item","payload":{"type":"message","role":"assistant","content":[{"type":"output_text","text":"I need the GitHub issue number for this session before I make changes. After that I’ll inspect the diff since `7d1a0b5b`, identify any non-ASCII characters added after that commit, and replace them with ASCII-safe text."}],"phase":"final_answer"}} +{"timestamp":"2026-03-27T18:05:42.415Z","type":"event_msg","payload":{"type":"token_count","info":{"total_token_usage":{"input_tokens":11883,"cached_input_tokens":6528,"output_tokens":203,"reasoning_output_tokens":86,"total_tokens":12086},"last_token_usage":{"input_tokens":11883,"cached_input_tokens":6528,"output_tokens":203,"reasoning_output_tokens":86,"total_tokens":12086},"model_context_window":258400},"rate_limits":{"limit_id":"codex","limit_name":null,"primary":{"used_percent":13.0,"window_minutes":300,"resets_at":1774643092},"secondary":{"used_percent":26.0,"window_minutes":10080,"resets_at":1774905636},"credits":null,"plan_type":"enterprise"}}} +{"timestamp":"2026-03-27T18:05:42.415Z","type":"event_msg","payload":{"type":"task_complete","turn_id":"019d3079-1f59-7a90-b02b-926b44d14497","last_agent_message":"I need the GitHub issue number for this session before I make changes. After that I’ll inspect the diff since `7d1a0b5b`, identify any non-ASCII characters added after that commit, and replace them with ASCII-safe text."}} +{"timestamp":"2026-03-27T18:05:45.574Z","type":"event_msg","payload":{"type":"task_started","turn_id":"019d3079-3ee6-7c93-a382-6cbfe9cff7d7","model_context_window":258400,"collaboration_mode_kind":"default"}} +{"timestamp":"2026-03-27T18:05:45.574Z","type":"response_item","payload":{"type":"message","role":"user","content":[{"type":"input_text","text":"200"}]}} +{"timestamp":"2026-03-27T18:05:45.575Z","type":"event_msg","payload":{"type":"user_message","message":"200","images":[],"local_images":[],"text_elements":[]}} +{"timestamp":"2026-03-27T18:05:45.575Z","type":"turn_context","payload":{"turn_id":"019d3079-3ee6-7c93-a382-6cbfe9cff7d7","cwd":"/Users/lindad/projects/TMAP8","approval_policy":"on-request","sandbox_policy":{"type":"workspace-write","network_access":false,"exclude_tmpdir_env_var":false,"exclude_slash_tmp":false},"model":"gpt-5.4","personality":"pragmatic","collaboration_mode":{"mode":"default","settings":{"model":"gpt-5.4","reasoning_effort":"medium","developer_instructions":"# Collaboration Mode: Default\n\nYou are now in Default mode. Any previous instructions for other modes (e.g. Plan mode) are no longer active.\n\nYour active mode changes only when new developer instructions with a different `...` change it; user requests or tool descriptions do not change mode by themselves. Known mode names are Default and Plan.\n\n## request_user_input availability\n\nThe `request_user_input` tool is unavailable in Default mode. If you call it while in Default mode, it will return an error.\n\nIn Default mode, strongly prefer making reasonable assumptions and executing the user's request rather than stopping to ask questions. If you absolutely must ask a question because the answer cannot be discovered from local context and a reasonable assumption would be risky, ask the user directly with a concise plain-text question. Never write a multiple choice question as a textual assistant message.\n"}},"effort":"medium","summary":"auto","user_instructions":"# AGENTS.md\n\n## Environment\n- Ask the user if you need to load a MOOSE conda environment, and if so, what the name of the conda environment is\n- If `./tmap8-opt` or `run_tests` throws an error, stop and ask the user\n- Pre-commit hooks handle all formatting and input file validation on every `git commit` — do not invoke `clang-format`, `black`, or `hit format` manually\n- `moose/framework/contrib/hit/hit check .i` is available to validate input files during development — use it before committing\n\n## Before writing any code or input file\n- Browse `doc/content/` to understand documentation standards and existing patterns before starting work\n- Before writing a new C++ class, look through existing MOOSE classes in the codebase to confirm expected syntax and patterns\n- Documentation in `doc/content/` may not accurately reflect current code behavior — once you identify a class to use in an input file, find its C++ implementation and read it to confirm the class does what you expect before writing the input file\n\n## C++ code\n- Every new class requires a MOOSE TestHarness test in `test/tests/` before committing\n- Every new class requires a MooseDocs page following existing TMAP8 doc structure\n- Never hardcode physical parameters — first check if it is already defined in `doc/content/source/utils/TMAP8PhysicalConstants`, and if not available, expose everything through `addParam`\n- Code is unit-agnostic; units live in input files only\n\n## Input files\n- Before writing an input file, look through existing MOOSE and TMAP8 classes to confirm object names and parameter syntax\n- Use `moose/framework/contrib/hit/hit check .i` to validate before committing\n- Use `./tmap8-opt -i .i` to run input files\n- Write parameter values in the units the reference source used; use the MOOSE units system for conversion — the units system is self-documenting and does not require inline comments\n- State the unit system at the top of every input file in a comment block\n\n## Testing\n- Run tests only when `.C`, `.h`, or `test/tests/` files change\n- Run only the affected module: `./run_tests -j --re `\n\n## Session log\n- Every session must be associated with a GitHub issue on `idaholab/TMAP8`; ask the user for the issue number at the start of the session if one is not provided, or create one if the user instructs you to\n- **SQA requirement:** When creating a GitHub issue with `gh`, you must use the appropriate template from `.github/ISSUE_TEMPLATE/`; read the available templates first, select the one that fits (e.g. `bug-report.md` for bugs, `feature-request.md` for new features or tasks), and populate all sections in the template body — passing a bare description without following the template structure is not acceptable\n- Before committing, copy the current session's `.jsonl` file into `doc/content/agent//`. For Claude Code sessions the file is the most recently modified `.jsonl` under `~/.claude/projects//`; for Codex sessions check the equivalent Codex session directory. Do not remove old session files already in that directory — append the new one alongside them.\n\n## Committing\n- Commit at minimum after: every input file that successfully runs, every test that passes or fails, and every new class added\n- If a test or run failed, commit the failure state first (include the full error message in the commit body), then commit the fix separately\n- Every commit must reference the associated GitHub issue (e.g. `Refs #` or `Closes #` as appropriate) in the commit message\n- **Every commit must include an updated copy of the session `.jsonl`** — before staging, copy the current session file from `~/.claude/projects//.jsonl` to `doc/content/agent//` and stage it; this is a critical SQA requirement. Do not remove session files already present in that directory — if multiple Claude/Codex sessions contribute to the same branch and issue, all session files must be kept.\n- Every commit must include these trailers:\n```\nRefs #\nAI-assisted: true\nAI-model: \nAI-version: \nCo-Authored-By: \n```\n\n## Pull requests\n- If the linked issue already contains a complete Reason/Design/Impact description, the PR body should contain only the closing reference (e.g. `Closes #`) — do not duplicate the issue content or leave template sections empty\n- If the PR introduces physics/modeling decisions, non-obvious AI reasoning, or tests not described in the issue, add those as a short addendum below the issue reference\n- Never merge autonomously\n\n## Never do\n- Modify existing passing tests without explicit user instruction\n- Modify the build system without explicit user instruction\n- Make physics modeling decisions without flagging them to the user\n- Suppress or bypass test failures\n\n\n## Skills\nA skill is a set of local instructions to follow that is stored in a `SKILL.md` file. Below is the list of skills that can be used. Each entry includes a name, description, and file path so you can open the source for full instructions when using a specific skill.\n### Available skills\n- openai-docs: Use when the user asks how to build with OpenAI products or APIs and needs up-to-date official documentation with citations, help choosing the latest model for a use case, or explicit GPT-5.4 upgrade and prompt-upgrade guidance; prioritize OpenAI docs MCP tools, use bundled references only as helper context, and restrict any fallback browsing to official OpenAI domains. (file: /Users/lindad/.codex/skills/.system/openai-docs/SKILL.md)\n- plugin-creator: Create and scaffold plugin directories for Codex with a required `.codex-plugin/plugin.json`, optional plugin folders/files, and baseline placeholders you can edit before publishing or testing. Use when Codex needs to create a new local plugin, add optional plugin structure, or generate or update repo-root `.agents/plugins/marketplace.json` entries for plugin ordering and availability metadata. (file: /Users/lindad/.codex/skills/.system/plugin-creator/SKILL.md)\n- skill-creator: Guide for creating effective skills. This skill should be used when users want to create a new skill (or update an existing skill) that extends Codex's capabilities with specialized knowledge, workflows, or tool integrations. (file: /Users/lindad/.codex/skills/.system/skill-creator/SKILL.md)\n- skill-installer: Install Codex skills into $CODEX_HOME/skills from a curated list or a GitHub repo path. Use when a user asks to list installable skills, install a curated skill, or install a skill from another repo (including private repos). (file: /Users/lindad/.codex/skills/.system/skill-installer/SKILL.md)\n### How to use skills\n- Discovery: The list above is the skills available in this session (name + description + file path). Skill bodies live on disk at the listed paths.\n- Trigger rules: If the user names a skill (with `$SkillName` or plain text) OR the task clearly matches a skill's description shown above, you must use that skill for that turn. Multiple mentions mean use them all. Do not carry skills across turns unless re-mentioned.\n- Missing/blocked: If a named skill isn't in the list or the path can't be read, say so briefly and continue with the best fallback.\n- How to use a skill (progressive disclosure):\n 1) After deciding to use a skill, open its `SKILL.md`. Read only enough to follow the workflow.\n 2) When `SKILL.md` references relative paths (e.g., `scripts/foo.py`), resolve them relative to the skill directory listed above first, and only consider other paths if needed.\n 3) If `SKILL.md` points to extra folders such as `references/`, load only the specific files needed for the request; don't bulk-load everything.\n 4) If `scripts/` exist, prefer running or patching them instead of retyping large code blocks.\n 5) If `assets/` or templates exist, reuse them instead of recreating from scratch.\n- Coordination and sequencing:\n - If multiple skills apply, choose the minimal set that covers the request and state the order you'll use them.\n - Announce which skill(s) you're using and why (one short line). If you skip an obvious skill, say why.\n- Context hygiene:\n - Keep context small: summarize long sections instead of pasting them; only load extra files when needed.\n - Avoid deep reference-chasing: prefer opening only files directly linked from `SKILL.md` unless you're blocked.\n - When variants exist (frameworks, providers, domains), pick only the relevant reference file(s) and note that choice.\n- Safety and fallback: If a skill can't be applied cleanly (missing files, unclear instructions), state the issue, pick the next-best approach, and continue.","truncation_policy":{"mode":"tokens","limit":10000}}} +{"timestamp":"2026-03-27T18:05:45.707Z","type":"event_msg","payload":{"type":"token_count","info":{"total_token_usage":{"input_tokens":11883,"cached_input_tokens":6528,"output_tokens":203,"reasoning_output_tokens":86,"total_tokens":12086},"last_token_usage":{"input_tokens":11883,"cached_input_tokens":6528,"output_tokens":203,"reasoning_output_tokens":86,"total_tokens":12086},"model_context_window":258400},"rate_limits":{"limit_id":"codex","limit_name":null,"primary":{"used_percent":15.0,"window_minutes":300,"resets_at":1774643092},"secondary":{"used_percent":27.0,"window_minutes":10080,"resets_at":1774905636},"credits":null,"plan_type":"enterprise"}}} +{"timestamp":"2026-03-27T18:05:49.111Z","type":"event_msg","payload":{"type":"agent_reasoning","text":"**Inspecting necessary updates**\n\nI need to start by updating the commentary and then inspect the current state. It’s crucial for me to browse the documentation and content before diving into any coding tasks related to AGENTS. It seems like I might just need to edit some files, possibly the documentation. So, I'll get that inspection underway to see exactly what needs attention!"}} +{"timestamp":"2026-03-27T18:05:49.111Z","type":"response_item","payload":{"type":"reasoning","summary":[{"type":"summary_text","text":"**Inspecting necessary updates**\n\nI need to start by updating the commentary and then inspect the current state. It’s crucial for me to browse the documentation and content before diving into any coding tasks related to AGENTS. It seems like I might just need to edit some files, possibly the documentation. So, I'll get that inspection underway to see exactly what needs attention!"}],"content":null,"encrypted_content":"gAAAAABpxsb97h3q7lz8aKCWyJ8mnYLoSiXhzzWM0i6R8u86BP8vdW-Ya2m8tPIR_WnnWuxpCX6RB74BX7XD81SE1E04MFKrfDqqfCxN5znlqKbC042wdDDMkxJLqJzEBQRe7JE-4Zr7pIPK8RflZK9TtlmfTS6gZoDxbS8hVvA0lR9EdSLZ00D-V3b7RvsLSklX5dwSdW-wN2NPjGQgIAoekVXMUojGVkkVpMcjsSn9Bhb98-pJ9mMVOac5nbSU9xSz8rmvijh6UI-1ileUPk4cKssAXJZuW9mxkeIfdf34lk9wTB5E2YUmr-IalxS4LVEMvFzlEK5PoiMLvPlDgh-c6hMO2zD32EUg0gloDdfmugdMuFzEWJ7DqEjHPrWSC2Ip-2QLhpSK7PxdlFMuDnQDU7rqA5rQedCW9l83B8jxVD1Z5Y4xSDhmZABBfGXcUcyMf1XwQ5JOPRK3h6-fqoKdlZYslCurT6qWc50NpIka0YWJH4eM-Lczza48zb4F7bFjTWxXg6rFP_XITFi7NFrmTGZ-kjIrLo77z3h9Qp5wqJYsbVKsM5N0gvJRGCMLp6gz6zjlIZcY4Y768_PPA5jmtHvOngvNqFmZqcH1gdgjLNcD5c5tLKifpiXp805GswaQQvxCh0dcsUrJ3h9Erbcn45Lx2coZe5PbbtbP8fXuCHJDMfqOwC0m86CaqUnZ-txt9njRGyLulGEYPHTskZ1y1t5LyQbh2ASke7U9JXAtwc9fi5fWtrDKwa7mfa9mr6432c63tpvINe3xLXNEY3t-AemylO-8FBnUfcxauc3oEgTiY1XJRd7cgWbLymgDC7TZmTpFtPwKR4I_aFlN68HXbAp2e9CubaJJ-fbX_FiqTZLqFf4X2wVwQpsU0bVZRpprMWDnHtUSm7st0XVhLbJjrBAowTtupVeoK2RnOMsQhXmbLUCW0wes86tQFHBqAaUh3w5bGNrrURdFmKumunsao0CUFriFtkIDqVX5oo2rXOM54FgBPBL0MnBZwU0vHIb8HyeQ15wyYVOGVCl4XAEd1MCoKLPoeA=="}} +{"timestamp":"2026-03-27T18:05:50.977Z","type":"event_msg","payload":{"type":"agent_message","message":"Issue is `#200`. I’m checking the repo state and the changes since `7d1a0b5b`, and I’ll scan `doc/content/` first to stay aligned with the repo’s documentation conventions before editing anything.","phase":"commentary"}} +{"timestamp":"2026-03-27T18:05:50.977Z","type":"response_item","payload":{"type":"message","role":"assistant","content":[{"type":"output_text","text":"Issue is `#200`. I’m checking the repo state and the changes since `7d1a0b5b`, and I’ll scan `doc/content/` first to stay aligned with the repo’s documentation conventions before editing anything."}],"phase":"commentary"}} +{"timestamp":"2026-03-27T18:05:50.977Z","type":"response_item","payload":{"type":"function_call","name":"exec_command","arguments":"{\"cmd\":\"rg --files doc/content | head -n 40\",\"workdir\":\"/Users/lindad/projects/TMAP8\",\"max_output_tokens\":4000,\"yield_time_ms\":1000}","call_id":"call_noJJs1BQZglQBbnkfl70OzVo"}} +{"timestamp":"2026-03-27T18:05:50.977Z","type":"response_item","payload":{"type":"function_call","name":"exec_command","arguments":"{\"cmd\":\"git status --short\",\"workdir\":\"/Users/lindad/projects/TMAP8\",\"max_output_tokens\":2000,\"yield_time_ms\":1000}","call_id":"call_YtTDMPVXrCqS9BhNUSOXSm8o"}} +{"timestamp":"2026-03-27T18:05:50.977Z","type":"response_item","payload":{"type":"function_call","name":"exec_command","arguments":"{\"cmd\":\"git diff --name-only 7d1a0b5b..HEAD\",\"workdir\":\"/Users/lindad/projects/TMAP8\",\"max_output_tokens\":4000,\"yield_time_ms\":1000}","call_id":"call_5b64KUinUhenEK8a1DayD5e7"}} +{"timestamp":"2026-03-27T18:05:51.041Z","type":"event_msg","payload":{"type":"token_count","info":{"total_token_usage":{"input_tokens":23888,"cached_input_tokens":13568,"output_tokens":468,"reasoning_output_tokens":122,"total_tokens":24356},"last_token_usage":{"input_tokens":12005,"cached_input_tokens":7040,"output_tokens":265,"reasoning_output_tokens":36,"total_tokens":12270},"model_context_window":258400},"rate_limits":{"limit_id":"codex","limit_name":null,"primary":{"used_percent":15.0,"window_minutes":300,"resets_at":1774643092},"secondary":{"used_percent":27.0,"window_minutes":10080,"resets_at":1774905636},"credits":null,"plan_type":"enterprise"}}} +{"timestamp":"2026-03-27T18:05:51.220Z","type":"response_item","payload":{"type":"function_call_output","call_id":"call_noJJs1BQZglQBbnkfl70OzVo","output":"Chunk ID: 5e21df\nWall time: 0.0520 seconds\nProcess exited with code 0\nOriginal token count: 425\nOutput:\ndoc/content/index.md\ndoc/content/publications.md\ndoc/content/theory_manual.md\ndoc/content/citing_tmap8.md\ndoc/content/bib/articles_using_tmap8.bib\ndoc/content/bib/tmap8.bib\ndoc/content/bib/proceedings_using_tmap8.bib\ndoc/content/syntax/physical_constants_alert.md\ndoc/content/verification_and_validation/ver-1c.md\ndoc/content/verification_and_validation/val-2g.md\ndoc/content/verification_and_validation/ver-1g.md\ndoc/content/verification_and_validation/val-2c.md\ndoc/content/verification_and_validation/val-2b.md\ndoc/content/verification_and_validation/verification_and_validation_standards.md\ndoc/content/verification_and_validation/ver-1b.md\ndoc/content/verification_and_validation/val-2f.md\ndoc/content/verification_and_validation/ver-1kc-2.md\ndoc/content/verification_and_validation/ver-1dd.md\ndoc/content/verification_and_validation/ver-1ic.md\ndoc/content/sqa/tmap8_srs.md\ndoc/content/sqa/tmap8_far.md\ndoc/content/sqa/tmap8_scs.md\ndoc/content/sqa/tmap8_sll.md\ndoc/content/sqa/tmap8_cci.md\ndoc/content/sqa/tmap8_sdd.md\ndoc/content/sqa/index.md\ndoc/content/sqa/user_manual.md\ndoc/content/sqa/tmap8_vvr.md\ndoc/content/sqa/tmap8_stp.md\ndoc/content/sqa/tmap8_rtm.md\ndoc/content/source/kernels/ADMatCoupledDefectAnnihilation.md\ndoc/content/source/kernels/ScaledCoupledTimeDerivative.md\ndoc/content/source/kernels/ADMatReactionFlexible.md\ndoc/content/verification_and_validation/ver-1ia.md\ndoc/content/verification_and_validation/ver-1fb.md\ndoc/content/verification_and_validation/ver-1gc.md\ndoc/content/verification_and_validation/ver-1kc-1.md\ndoc/content/verification_and_validation/ver-1kd.md\ndoc/content/verification_and_validation/ver-1fc.md\ndoc/content/verification_and_validation/ver-1dc.md\n"}} +{"timestamp":"2026-03-27T18:05:52.083Z","type":"response_item","payload":{"type":"function_call_output","call_id":"call_YtTDMPVXrCqS9BhNUSOXSm8o","output":"Chunk ID: 1b722f\nWall time: 0.9428 seconds\nProcess exited with code 0\nOriginal token count: 14\nOutput:\n M moose\n?? test/tests/val-2c/val-2c_pss_results_short/\n"}} +{"timestamp":"2026-03-27T18:05:52.083Z","type":"response_item","payload":{"type":"function_call_output","call_id":"call_5b64KUinUhenEK8a1DayD5e7","output":"Chunk ID: 8c3ed9\nWall time: 0.0536 seconds\nProcess exited with code 0\nOriginal token count: 717\nOutput:\n.gitignore\nAGENTS.md\ndoc/content/source/kernels/ScaledCoupledTimeDerivative.md\ndoc/content/source/nodal_kernels/ReleasingNodalKernelDimensionless.md\ndoc/content/source/nodal_kernels/TrappingNodalKernelDimensionless.md\ndoc/content/verification_and_validation/val-2c.md\ninclude/nodal_kernels/ReleasingNodalKernelDimensionless.h\ninclude/nodal_kernels/TrappingNodalKernelDimensionless.h\ninclude/physics/SpeciesTrappingPhysics.h\nmoose\nscripts/build_tmap8_devel.sh\nscripts/compute_val_2f_dimensionless_reference.py\nscripts/extract_time_sequence_from_csv.py\nscripts/run_tests_val_2f_dimensionless.sh\nscripts/run_tests_val_2f_dimensionless_parallel.sh\nscripts/run_val_2f_dimensionless_light_charge.sh\nscripts/run_val_2f_dimensionless_light_scheduled.sh\nscripts/run_val_2f_dimensionless_scheduled_svd.sh\nsrc/kernels/ScaledCoupledTimeDerivative.C\nsrc/nodal_kernels/ReleasingNodalKernelDimensionless.C\nsrc/nodal_kernels/TrappingNodalKernelDimensionless.C\nsrc/physics/SpeciesTrappingPhysics.C\ntest/tests/actioncomponents/exceptions/tests\ntest/tests/physics/exceptions/tests\ntest/tests/physics/more_species_on_component/gold/species_trapping_dimensionless_other_trap_out.csv\ntest/tests/physics/more_species_on_component/species_trapping_dimensionless_other_trap.i\ntest/tests/physics/more_species_on_component/tests\ntest/tests/val-2c/gold/val-2c_delay_calibrated_out.csv\ntest/tests/val-2c/gold/val-2c_delay_csv.csv\ntest/tests/val-2c/gold/val-2c_delay_out.e\ntest/tests/val-2c/gold/val-2c_immediate_injection_csv.csv\ntest/tests/val-2c/gold/val-2c_immediate_injection_out.e\ntest/tests/val-2c/gold/val-2c_pss_results_short/val-2c_pss_main_short_out.json\ntest/tests/val-2c/tests\ntest/tests/val-2c/val-2c_base.i\ntest/tests/val-2c/val-2c_delay.params\ntest/tests/val-2c/val-2c_exodus.exodiff\ntest/tests/val-2c/val-2c_immediate_injection.i\ntest/tests/val-2f/gold/val-2f_light_out.csv\ntest/tests/val-2f/gold/val-2f_light_out.e\ntest/tests/val-2f/gold/val-2f_out.csv\ntest/tests/val-2f/gold/val-2f_out.e\ntest/tests/val-2f/gold/val-2f_out_inf_recombination.csv\ntest/tests/val-2f/parameters_val-2f.params\ntest/tests/val-2f/test_val_2f_rmspe.py\ntest/tests/val-2f/tests\ntest/tests/val-2f/val-2f.i\ntest/tests/val-2f/val-2f_trapping_1.i\ntest/tests/val-2f/val-2f_trapping_2.i\ntest/tests/val-2f/val-2f_trapping_3.i\ntest/tests/val-2f/val-2f_trapping_4.i\ntest/tests/val-2f/val-2f_trapping_5.i\ntest/tests/val-2f/val-2f_trapping_intrinsic.i\ntest/tests/yttrium_hydrogen_system/YHx_PCT.i\ntest/tests/yttrium_hydrogen_system/gold/YHx_PCT_T1173_P1e3_out.csv\ntest/tests/yttrium_hydrogen_system/gold/YHx_PCT_T1173_P1e4_out.csv\ntest/tests/yttrium_hydrogen_system/gold/YHx_PCT_T1173_P5e4_out.csv\ntest/tests/yttrium_hydrogen_system/gold/YHx_PCT_T1273_P3e3_out.csv\ntest/tests/yttrium_hydrogen_system/gold/YHx_PCT_out.csv\ntest/tests/yttrium_hydrogen_system/gold/YHx_PCT_out.e\ntest/tests/yttrium_hydrogen_system/tests\n"}} +{"timestamp":"2026-03-27T18:05:52.083Z","type":"turn_context","payload":{"turn_id":"019d3079-3ee6-7c93-a382-6cbfe9cff7d7","cwd":"/Users/lindad/projects/TMAP8","approval_policy":"on-request","sandbox_policy":{"type":"workspace-write","network_access":false,"exclude_tmpdir_env_var":false,"exclude_slash_tmp":false},"model":"gpt-5.4","personality":"pragmatic","collaboration_mode":{"mode":"default","settings":{"model":"gpt-5.4","reasoning_effort":"medium","developer_instructions":"# Collaboration Mode: Default\n\nYou are now in Default mode. Any previous instructions for other modes (e.g. Plan mode) are no longer active.\n\nYour active mode changes only when new developer instructions with a different `...` change it; user requests or tool descriptions do not change mode by themselves. Known mode names are Default and Plan.\n\n## request_user_input availability\n\nThe `request_user_input` tool is unavailable in Default mode. If you call it while in Default mode, it will return an error.\n\nIn Default mode, strongly prefer making reasonable assumptions and executing the user's request rather than stopping to ask questions. If you absolutely must ask a question because the answer cannot be discovered from local context and a reasonable assumption would be risky, ask the user directly with a concise plain-text question. Never write a multiple choice question as a textual assistant message.\n"}},"effort":"medium","summary":"auto","user_instructions":"# AGENTS.md\n\n## Environment\n- Ask the user if you need to load a MOOSE conda environment, and if so, what the name of the conda environment is\n- If `./tmap8-opt` or `run_tests` throws an error, stop and ask the user\n- Pre-commit hooks handle all formatting and input file validation on every `git commit` — do not invoke `clang-format`, `black`, or `hit format` manually\n- `moose/framework/contrib/hit/hit check .i` is available to validate input files during development — use it before committing\n\n## Before writing any code or input file\n- Browse `doc/content/` to understand documentation standards and existing patterns before starting work\n- Before writing a new C++ class, look through existing MOOSE classes in the codebase to confirm expected syntax and patterns\n- Documentation in `doc/content/` may not accurately reflect current code behavior — once you identify a class to use in an input file, find its C++ implementation and read it to confirm the class does what you expect before writing the input file\n\n## C++ code\n- Every new class requires a MOOSE TestHarness test in `test/tests/` before committing\n- Every new class requires a MooseDocs page following existing TMAP8 doc structure\n- Never hardcode physical parameters — first check if it is already defined in `doc/content/source/utils/TMAP8PhysicalConstants`, and if not available, expose everything through `addParam`\n- Code is unit-agnostic; units live in input files only\n\n## Input files\n- Before writing an input file, look through existing MOOSE and TMAP8 classes to confirm object names and parameter syntax\n- Use `moose/framework/contrib/hit/hit check .i` to validate before committing\n- Use `./tmap8-opt -i .i` to run input files\n- Write parameter values in the units the reference source used; use the MOOSE units system for conversion — the units system is self-documenting and does not require inline comments\n- State the unit system at the top of every input file in a comment block\n\n## Testing\n- Run tests only when `.C`, `.h`, or `test/tests/` files change\n- Run only the affected module: `./run_tests -j --re `\n\n## Session log\n- Every session must be associated with a GitHub issue on `idaholab/TMAP8`; ask the user for the issue number at the start of the session if one is not provided, or create one if the user instructs you to\n- **SQA requirement:** When creating a GitHub issue with `gh`, you must use the appropriate template from `.github/ISSUE_TEMPLATE/`; read the available templates first, select the one that fits (e.g. `bug-report.md` for bugs, `feature-request.md` for new features or tasks), and populate all sections in the template body — passing a bare description without following the template structure is not acceptable\n- Before committing, copy the current session's `.jsonl` file into `doc/content/agent//`. For Claude Code sessions the file is the most recently modified `.jsonl` under `~/.claude/projects//`; for Codex sessions check the equivalent Codex session directory. Do not remove old session files already in that directory — append the new one alongside them.\n\n## Committing\n- Commit at minimum after: every input file that successfully runs, every test that passes or fails, and every new class added\n- If a test or run failed, commit the failure state first (include the full error message in the commit body), then commit the fix separately\n- Every commit must reference the associated GitHub issue (e.g. `Refs #` or `Closes #` as appropriate) in the commit message\n- **Every commit must include an updated copy of the session `.jsonl`** — before staging, copy the current session file from `~/.claude/projects//.jsonl` to `doc/content/agent//` and stage it; this is a critical SQA requirement. Do not remove session files already present in that directory — if multiple Claude/Codex sessions contribute to the same branch and issue, all session files must be kept.\n- Every commit must include these trailers:\n```\nRefs #\nAI-assisted: true\nAI-model: \nAI-version: \nCo-Authored-By: \n```\n\n## Pull requests\n- If the linked issue already contains a complete Reason/Design/Impact description, the PR body should contain only the closing reference (e.g. `Closes #`) — do not duplicate the issue content or leave template sections empty\n- If the PR introduces physics/modeling decisions, non-obvious AI reasoning, or tests not described in the issue, add those as a short addendum below the issue reference\n- Never merge autonomously\n\n## Never do\n- Modify existing passing tests without explicit user instruction\n- Modify the build system without explicit user instruction\n- Make physics modeling decisions without flagging them to the user\n- Suppress or bypass test failures\n\n\n## Skills\nA skill is a set of local instructions to follow that is stored in a `SKILL.md` file. Below is the list of skills that can be used. Each entry includes a name, description, and file path so you can open the source for full instructions when using a specific skill.\n### Available skills\n- openai-docs: Use when the user asks how to build with OpenAI products or APIs and needs up-to-date official documentation with citations, help choosing the latest model for a use case, or explicit GPT-5.4 upgrade and prompt-upgrade guidance; prioritize OpenAI docs MCP tools, use bundled references only as helper context, and restrict any fallback browsing to official OpenAI domains. (file: /Users/lindad/.codex/skills/.system/openai-docs/SKILL.md)\n- plugin-creator: Create and scaffold plugin directories for Codex with a required `.codex-plugin/plugin.json`, optional plugin folders/files, and baseline placeholders you can edit before publishing or testing. Use when Codex needs to create a new local plugin, add optional plugin structure, or generate or update repo-root `.agents/plugins/marketplace.json` entries for plugin ordering and availability metadata. (file: /Users/lindad/.codex/skills/.system/plugin-creator/SKILL.md)\n- skill-creator: Guide for creating effective skills. This skill should be used when users want to create a new skill (or update an existing skill) that extends Codex's capabilities with specialized knowledge, workflows, or tool integrations. (file: /Users/lindad/.codex/skills/.system/skill-creator/SKILL.md)\n- skill-installer: Install Codex skills into $CODEX_HOME/skills from a curated list or a GitHub repo path. Use when a user asks to list installable skills, install a curated skill, or install a skill from another repo (including private repos). (file: /Users/lindad/.codex/skills/.system/skill-installer/SKILL.md)\n### How to use skills\n- Discovery: The list above is the skills available in this session (name + description + file path). Skill bodies live on disk at the listed paths.\n- Trigger rules: If the user names a skill (with `$SkillName` or plain text) OR the task clearly matches a skill's description shown above, you must use that skill for that turn. Multiple mentions mean use them all. Do not carry skills across turns unless re-mentioned.\n- Missing/blocked: If a named skill isn't in the list or the path can't be read, say so briefly and continue with the best fallback.\n- How to use a skill (progressive disclosure):\n 1) After deciding to use a skill, open its `SKILL.md`. Read only enough to follow the workflow.\n 2) When `SKILL.md` references relative paths (e.g., `scripts/foo.py`), resolve them relative to the skill directory listed above first, and only consider other paths if needed.\n 3) If `SKILL.md` points to extra folders such as `references/`, load only the specific files needed for the request; don't bulk-load everything.\n 4) If `scripts/` exist, prefer running or patching them instead of retyping large code blocks.\n 5) If `assets/` or templates exist, reuse them instead of recreating from scratch.\n- Coordination and sequencing:\n - If multiple skills apply, choose the minimal set that covers the request and state the order you'll use them.\n - Announce which skill(s) you're using and why (one short line). If you skip an obvious skill, say why.\n- Context hygiene:\n - Keep context small: summarize long sections instead of pasting them; only load extra files when needed.\n - Avoid deep reference-chasing: prefer opening only files directly linked from `SKILL.md` unless you're blocked.\n - When variants exist (frameworks, providers, domains), pick only the relevant reference file(s) and note that choice.\n- Safety and fallback: If a skill can't be applied cleanly (missing files, unclear instructions), state the issue, pick the next-best approach, and continue.","truncation_policy":{"mode":"tokens","limit":10000}}} +{"timestamp":"2026-03-27T18:05:57.505Z","type":"event_msg","payload":{"type":"agent_reasoning","text":"**Checking non-ASCII characters**\n\nI need to find non-ASCII characters introduced since a certain commit. My first thought is to consider using `git diff` to review all changed files. I probably only need to focus on characters introduced in the added lines. Maybe I can also use a Perl command or a regex with `rg` to check for any non-ASCII characters in those changed files. Let's run through this and see what we find!"}} +{"timestamp":"2026-03-27T18:05:57.505Z","type":"response_item","payload":{"type":"reasoning","summary":[{"type":"summary_text","text":"**Checking non-ASCII characters**\n\nI need to find non-ASCII characters introduced since a certain commit. My first thought is to consider using `git diff` to review all changed files. I probably only need to focus on characters introduced in the added lines. Maybe I can also use a Perl command or a regex with `rg` to check for any non-ASCII characters in those changed files. Let's run through this and see what we find!"}],"content":null,"encrypted_content":"gAAAAABpxscFbYDXBmfiv6Boy6PU9NsrhwwA2I1HGeyEAvYWvvNL9qZsYp1H_w7BIPCdxukaYXusCJ6JNvqpQiF3-x21G7Mk00RoL1Wxj-4WJRwhbMUjMAwEAK5w2PU1rM0y2Tra0GEIiLryMk6rbejonrNDGHsTS7iWrLvJpU1VzFS0FpMPt_M-t2ghpYF4I-xay_OzVU-ZbtUZd2ubxGiYxTZeMRd-CZctAREEDWGMdzqVaM2A1hM0aAwC9wJ0QYWZTsYrLclj0AmL_8ZeBWg80k-i6BlJlaZsRuo9NDps-errLkCNpB7LkyK_ba1BdB9gsB8T0ob4wPGNvBSmpBYCXwERfFO1qXJGDXw6LPjjXvViSyrhgI1OK-2JlMrcGBZg9175n4YkKm5OirpGC2cV5pgXxGehN5SCWo2Gi-UUc8my_1kdIszwTVgWvKvRPFa1Z9s5rFHWDG3PM_05krRNX_jwYSbA_gxTx6U-xn3tmCJfr8OEpdXAdJ2bCVuObgAgZg0N4aC0iINj4KIHftpqDQDn7c6wcPlW316hQjRylqfiQPoURG02xwxZxpV6Kt9dFPd8vN-R_XJJYUrl1ygf03P_gaxhsevdUIS7gqtYvDSnPniu_uQMSBtc7HlTNxmwzfaCx7-rUG5U5Dr9QzGe7zWNS_xF8aSaYDZu9Tq9DTAIBGx7uO72hnFOn5ujBlPCOO_sWf-UuIVICtrusJV9GxvUsNGYGhwY7ix1efz2FR4Ry8yNi-I2dvkiNO6BuFPmb01eszCuRKClp5gYU54KrRpzf0HckzmjJw-JPzhW6juH1lOwLnv5FZR5d2pCmJhzZv3B5ZioUKYH2vwK8atZBE9PB4VJ4kKZXbww4zHywJ2pvUliQycqEdesVdgo7ArEskdDpkz-ud5-TASXgRDitLda17o2G5vkgdFcO3y2wSVatcY_KAEaT-_H4HUwNkIv7dnQrv6Gc46pwDZH6MqEJTUAzBrWElMN0Dp_Sr4-F_yzAfsdDeItVve310ob6nHSPYbsqExgyVD98UdTwA60PJM483jvWWOJMteCAWC1hQh9CVBta-JSRxCeVbOjEH0SYRVoidVzVqolxs15FpgqI5k5i88GMnd_s_ZgHwxTidKjN-SsIzLu_A-q0rerZsodMr9VJ6QR"}} +{"timestamp":"2026-03-27T18:06:00.431Z","type":"event_msg","payload":{"type":"agent_message","message":"I have the changed file set. Next I’m isolating actual non-ASCII characters introduced after `7d1a0b5b` so I only touch relevant lines and avoid unrelated worktree changes.","phase":"commentary"}} +{"timestamp":"2026-03-27T18:06:00.431Z","type":"response_item","payload":{"type":"message","role":"assistant","content":[{"type":"output_text","text":"I have the changed file set. Next I’m isolating actual non-ASCII characters introduced after `7d1a0b5b` so I only touch relevant lines and avoid unrelated worktree changes."}],"phase":"commentary"}} +{"timestamp":"2026-03-27T18:06:00.431Z","type":"response_item","payload":{"type":"function_call","name":"exec_command","arguments":"{\"cmd\":\"git diff --unified=0 7d1a0b5b..HEAD -- . ':(exclude)moose' | rg -n \\\"^\\\\+.*[^\\\\x00-\\\\x7F]\\\"\",\"workdir\":\"/Users/lindad/projects/TMAP8\",\"max_output_tokens\":8000,\"yield_time_ms\":1000}","call_id":"call_d0cB00nMcc8ytPgGTk6G5n5q"}} +{"timestamp":"2026-03-27T18:06:00.432Z","type":"response_item","payload":{"type":"function_call","name":"exec_command","arguments":"{\"cmd\":\"git diff --name-only 7d1a0b5b..HEAD -- . ':(exclude)moose' | while read -r f; do rg -n --pcre2 \\\"[^\\\\x00-\\\\x7F]\\\" \\\"$f\\\" && printf \\\"\\\\n\\\"; done\",\"workdir\":\"/Users/lindad/projects/TMAP8\",\"max_output_tokens\":8000,\"yield_time_ms\":1000}","call_id":"call_D9z45ClySs5qrO3EMm70WpAP"}} +{"timestamp":"2026-03-27T18:06:00.595Z","type":"event_msg","payload":{"type":"token_count","info":{"total_token_usage":{"input_tokens":37718,"cached_input_tokens":25728,"output_tokens":791,"reasoning_output_tokens":184,"total_tokens":38509},"last_token_usage":{"input_tokens":13830,"cached_input_tokens":12160,"output_tokens":323,"reasoning_output_tokens":62,"total_tokens":14153},"model_context_window":258400},"rate_limits":{"limit_id":"codex","limit_name":null,"primary":{"used_percent":15.0,"window_minutes":300,"resets_at":1774643092},"secondary":{"used_percent":27.0,"window_minutes":10080,"resets_at":1774905636},"credits":null,"plan_type":"enterprise"}}} +{"timestamp":"2026-03-27T18:06:00.661Z","type":"response_item","payload":{"type":"function_call_output","call_id":"call_d0cB00nMcc8ytPgGTk6G5n5q","output":"Chunk ID: fc3bc1\nWall time: 0.0718 seconds\nProcess exited with code 0\nOriginal token count: 586\nOutput:\n142:+ * Ĉ_t = C_t / C_t_ref.\n145:+ * R = +k_r_hat · exp(-E_r / T) · Ĉ_t\n147:+ * where k_r_hat = t_ref · α_r.\n149:+ * This is trivially dimensionless (O(k_r_hat)) because Ĉ_t is O(1).\n198:+ * Ĉ_t = C_t / C_t_ref, where C_t_ref is the trap concentration reference scale.\n201:+ * R = -k_t_hat · exp(-E_t / T) · ((N·Ct0 - C_t_ref·Ĉ_t - Σ_j C_t_j) / C_t_ref) · Ĉ_m\n204:+ * - Ĉ_t = dimensionless variable (this kernel's variable), O(1)\n205:+ * - Ĉ_m = dimensionless mobile concentration. The coupled variable may be either physical\n207:+ * - C_t_j = C_t_ref_j * Ĉ_t_j, other trap species (dimensionless variable + reference, optional)\n209:+ * - k_t_hat = t_ref · α_t · C_m_ref / N\n229:+ /// C_t_ref: reference concentration for THIS trap (used to convert Ĉ_t back to physical)\n234:+ /// Dimensionless concentrations of other trap types (Ĉ_t_j = C_t_j / C_t_ref_j)\n236:+ /// Reference concentrations C_t_ref_j for each other trap, to convert Ĉ_t_j → physical C_t_j\n568:+ \"Ĉ_t = C_t / C_t_ref. \"\n569:+ \"The residual R = +k_r_hat · exp(-E_r / T) · Ĉ_t is naturally O(k_r_hat) \"\n570:+ \"because Ĉ_t is O(1). No equation scaling is applied.\");\n630:+ \"Ĉ_t = C_t / C_t_ref. \"\n644:+ \"Typically set to N * Ct0_max. The variable stores Ĉ_t = C_t / C_t_ref.\");\n649:+ \"Dimensionless trapped-concentration variables (Ĉ_t_j = C_t_j / C_t_ref_j) \"\n655:+ \"other_trapped_concentration_variables, used to convert Ĉ_t_j back to physical C_t_j \"\n710:+ // N * Ct0(x) - C_t_ref * Ĉ_t - sum_j C_t_ref_j * Ĉ_t_j\n734:+ // Other traps: dimensionless Ĉ_t_j, multiplied by C_t_ref_j to get physical units\n742:+ // This trap: variable is dimensionless Ĉ_t, multiply by C_t_ref to get physical\n747:+ // Mobile concentration in dimensionless form Ĉ_m\n1054:+ // Time derivative — plain TimeDerivativeNodalKernel suffices for both paths:\n1055:+ // • dimensionless path: variable IS Ĉ_t (O(1)), so dĈ_t/dt is correct as-is\n1056:+ // • physical path: variable IS C_t, no per-row scaling is applied here\n1126:+ // dimensionless kernel can convert Ĉ_t_j → physical C_t_j.\n1170:+ // Dimensionless path: add (C_t_ref_i / C_m_ref) * dĈ_t_i/dt.\n31442:+# (from nondimensionalizing ∂C_t/∂t = alpha_t/N * C_m * (N*Ct0 - C_t))\n"}} +{"timestamp":"2026-03-27T18:06:01.589Z","type":"response_item","payload":{"type":"function_call_output","call_id":"call_D9z45ClySs5qrO3EMm70WpAP","output":"Chunk ID: 9e6b40\nWall time: 1.0007 seconds\nProcess running with session ID 47234\nOriginal token count: 1256\nOutput:\n6:- Pre-commit hooks handle all formatting and input file validation on every `git commit` — do not invoke `clang-format`, `black`, or `hit format` manually\n7:- `moose/framework/contrib/hit/hit check .i` is available to validate input files during development — use it before committing\n12:- Documentation in `doc/content/` may not accurately reflect current code behavior — once you identify a class to use in an input file, find its C++ implementation and read it to confirm the class does what you expect before writing the input file\n17:- Never hardcode physical parameters — first check if it is already defined in `doc/content/source/utils/TMAP8PhysicalConstants`, and if not available, expose everything through `addParam`\n24:- Write parameter values in the units the reference source used; use the MOOSE units system for conversion — the units system is self-documenting and does not require inline comments\n33:- **SQA requirement:** When creating a GitHub issue with `gh`, you must use the appropriate template from `.github/ISSUE_TEMPLATE/`; read the available templates first, select the one that fits (e.g. `bug-report.md` for bugs, `feature-request.md` for new features or tasks), and populate all sections in the template body — passing a bare description without following the template structure is not acceptable\n34:- Before committing, copy the current session's `.jsonl` file into `doc/content/agent//`. For Claude Code sessions the file is the most recently modified `.jsonl` under `~/.claude/projects//`; for Codex sessions check the equivalent Codex session directory. Do not remove old session files already in that directory — append the new one alongside them.\n40:- **Every commit must include an updated copy of the session `.jsonl`** — before staging, copy the current session file from `~/.claude/projects//.jsonl` to `doc/content/agent//` and stage it; this is a critical SQA requirement. Do not remove session files already present in that directory — if multiple Claude/Codex sessions contribute to the same branch and issue, all session files must be kept.\n51:- If the linked issue already contains a complete Reason/Design/Impact description, the PR body should contain only the closing reference (e.g. `Closes #`) — do not duplicate the issue content or leave template sections empty\n\n15: * Ĉ_t = C_t / C_t_ref.\n18: * R = +k_r_hat · exp(-E_r / T) · Ĉ_t\n20: * where k_r_hat = t_ref · α_r.\n22: * This is trivially dimensionless (O(k_r_hat)) because Ĉ_t is O(1).\n\n26: * Ĉ_t = C_t / C_t_ref, where C_t_ref is the trap concentration reference scale.\n29: * R = -k_t_hat · exp(-E_t / T) · ((N·Ct0 - C_t_ref·Ĉ_t - Σ_j C_t_j) / C_t_ref) · Ĉ_m\n32: * - Ĉ_t = dimensionless variable (this kernel's variable), O(1)\n33: * - Ĉ_m = dimensionless mobile concentration. The coupled variable may be either physical\n35: * - C_t_j = C_t_ref_j * Ĉ_t_j, other trap species (dimensionless variable + reference, optional)\n37: * - k_t_hat = t_ref · α_t · C_m_ref / N\n57: /// C_t_ref: reference concentration for THIS trap (used to convert Ĉ_t back to physical)\n62: /// Dimensionless concentrations of other trap types (Ĉ_t_j = C_t_j / C_t_ref_j)\n64: /// Reference concentrations C_t_ref_j for each other trap, to convert Ĉ_t_j → physical C_t_j\n\n19: \"Ĉ_t = C_t / C_t_ref. \"\n20: \"The residual R = +k_r_hat · exp(-E_r / T) · Ĉ_t is naturally O(k_r_hat) \"\n21: \"because Ĉ_t is O(1). No equation scaling is applied.\");\n\n20: \"Ĉ_t = C_t / C_t_ref. \"\n34: \"Typically set to N * Ct0_max. The variable stores Ĉ_t = C_t / C_t_ref.\");\n39: \"Dimensionless trapped-concentration variables (Ĉ_t_j = C_t_j / C_t_ref_j) \"\n45: \"other_trapped_concentration_variables, used to convert Ĉ_t_j back to physical C_t_j \"\n100: // N * Ct0(x) - C_t_ref * Ĉ_t - sum_j C_t_ref_j * Ĉ_t_j\n124: // Other traps: dimensionless Ĉ_t_j, multiplied by C_t_ref_j to get physical units\n132: // This trap: variable is dimensionless Ĉ_t, multiply by C_t_ref to get physical\n137: // Mobile concentration in dimensionless form Ĉ_m\n\n536: // Time derivative — plain TimeDerivativeNodalKernel suffices for both paths:\n537: // • dimensionless path: variable IS Ĉ_t (O(1)), so dĈ_t/dt is correct as-is\n538: // • physical path: variable IS C_t, no per-row scaling is applied here\n603: // dimensionless kernel can convert Ĉ_t_j → physical C_t_j.\n644: // Dimensionless path: add (C_t_ref_i / C_m_ref) * dĈ_t_i/dt.\n\nbinary file matches (found \"\\0\" byte around offset 4)\n\nbinary file matches (found \"\\0\" byte around offset 4)\n\nbinary file matches (found \"\\0\" byte around offset 4)\n\nrg: test/tests/val-2f/gold/val-2f_out.e: IO error for operation on test/tests/val-2f/gold/val-2f_out.e: No such file or directory (os error 2)\n164:# (from nondimensionalizing ∂C_t/∂t = alpha_t/N * C_m * (N*Ct0 - C_t))\n\n"}} +{"timestamp":"2026-03-27T18:06:01.590Z","type":"turn_context","payload":{"turn_id":"019d3079-3ee6-7c93-a382-6cbfe9cff7d7","cwd":"/Users/lindad/projects/TMAP8","approval_policy":"on-request","sandbox_policy":{"type":"workspace-write","network_access":false,"exclude_tmpdir_env_var":false,"exclude_slash_tmp":false},"model":"gpt-5.4","personality":"pragmatic","collaboration_mode":{"mode":"default","settings":{"model":"gpt-5.4","reasoning_effort":"medium","developer_instructions":"# Collaboration Mode: Default\n\nYou are now in Default mode. Any previous instructions for other modes (e.g. Plan mode) are no longer active.\n\nYour active mode changes only when new developer instructions with a different `...` change it; user requests or tool descriptions do not change mode by themselves. Known mode names are Default and Plan.\n\n## request_user_input availability\n\nThe `request_user_input` tool is unavailable in Default mode. If you call it while in Default mode, it will return an error.\n\nIn Default mode, strongly prefer making reasonable assumptions and executing the user's request rather than stopping to ask questions. If you absolutely must ask a question because the answer cannot be discovered from local context and a reasonable assumption would be risky, ask the user directly with a concise plain-text question. Never write a multiple choice question as a textual assistant message.\n"}},"effort":"medium","summary":"auto","user_instructions":"# AGENTS.md\n\n## Environment\n- Ask the user if you need to load a MOOSE conda environment, and if so, what the name of the conda environment is\n- If `./tmap8-opt` or `run_tests` throws an error, stop and ask the user\n- Pre-commit hooks handle all formatting and input file validation on every `git commit` — do not invoke `clang-format`, `black`, or `hit format` manually\n- `moose/framework/contrib/hit/hit check .i` is available to validate input files during development — use it before committing\n\n## Before writing any code or input file\n- Browse `doc/content/` to understand documentation standards and existing patterns before starting work\n- Before writing a new C++ class, look through existing MOOSE classes in the codebase to confirm expected syntax and patterns\n- Documentation in `doc/content/` may not accurately reflect current code behavior — once you identify a class to use in an input file, find its C++ implementation and read it to confirm the class does what you expect before writing the input file\n\n## C++ code\n- Every new class requires a MOOSE TestHarness test in `test/tests/` before committing\n- Every new class requires a MooseDocs page following existing TMAP8 doc structure\n- Never hardcode physical parameters — first check if it is already defined in `doc/content/source/utils/TMAP8PhysicalConstants`, and if not available, expose everything through `addParam`\n- Code is unit-agnostic; units live in input files only\n\n## Input files\n- Before writing an input file, look through existing MOOSE and TMAP8 classes to confirm object names and parameter syntax\n- Use `moose/framework/contrib/hit/hit check .i` to validate before committing\n- Use `./tmap8-opt -i .i` to run input files\n- Write parameter values in the units the reference source used; use the MOOSE units system for conversion — the units system is self-documenting and does not require inline comments\n- State the unit system at the top of every input file in a comment block\n\n## Testing\n- Run tests only when `.C`, `.h`, or `test/tests/` files change\n- Run only the affected module: `./run_tests -j --re `\n\n## Session log\n- Every session must be associated with a GitHub issue on `idaholab/TMAP8`; ask the user for the issue number at the start of the session if one is not provided, or create one if the user instructs you to\n- **SQA requirement:** When creating a GitHub issue with `gh`, you must use the appropriate template from `.github/ISSUE_TEMPLATE/`; read the available templates first, select the one that fits (e.g. `bug-report.md` for bugs, `feature-request.md` for new features or tasks), and populate all sections in the template body — passing a bare description without following the template structure is not acceptable\n- Before committing, copy the current session's `.jsonl` file into `doc/content/agent//`. For Claude Code sessions the file is the most recently modified `.jsonl` under `~/.claude/projects//`; for Codex sessions check the equivalent Codex session directory. Do not remove old session files already in that directory — append the new one alongside them.\n\n## Committing\n- Commit at minimum after: every input file that successfully runs, every test that passes or fails, and every new class added\n- If a test or run failed, commit the failure state first (include the full error message in the commit body), then commit the fix separately\n- Every commit must reference the associated GitHub issue (e.g. `Refs #` or `Closes #` as appropriate) in the commit message\n- **Every commit must include an updated copy of the session `.jsonl`** — before staging, copy the current session file from `~/.claude/projects//.jsonl` to `doc/content/agent//` and stage it; this is a critical SQA requirement. Do not remove session files already present in that directory — if multiple Claude/Codex sessions contribute to the same branch and issue, all session files must be kept.\n- Every commit must include these trailers:\n```\nRefs #\nAI-assisted: true\nAI-model: \nAI-version: \nCo-Authored-By: \n```\n\n## Pull requests\n- If the linked issue already contains a complete Reason/Design/Impact description, the PR body should contain only the closing reference (e.g. `Closes #`) — do not duplicate the issue content or leave template sections empty\n- If the PR introduces physics/modeling decisions, non-obvious AI reasoning, or tests not described in the issue, add those as a short addendum below the issue reference\n- Never merge autonomously\n\n## Never do\n- Modify existing passing tests without explicit user instruction\n- Modify the build system without explicit user instruction\n- Make physics modeling decisions without flagging them to the user\n- Suppress or bypass test failures\n\n\n## Skills\nA skill is a set of local instructions to follow that is stored in a `SKILL.md` file. Below is the list of skills that can be used. Each entry includes a name, description, and file path so you can open the source for full instructions when using a specific skill.\n### Available skills\n- openai-docs: Use when the user asks how to build with OpenAI products or APIs and needs up-to-date official documentation with citations, help choosing the latest model for a use case, or explicit GPT-5.4 upgrade and prompt-upgrade guidance; prioritize OpenAI docs MCP tools, use bundled references only as helper context, and restrict any fallback browsing to official OpenAI domains. (file: /Users/lindad/.codex/skills/.system/openai-docs/SKILL.md)\n- plugin-creator: Create and scaffold plugin directories for Codex with a required `.codex-plugin/plugin.json`, optional plugin folders/files, and baseline placeholders you can edit before publishing or testing. Use when Codex needs to create a new local plugin, add optional plugin structure, or generate or update repo-root `.agents/plugins/marketplace.json` entries for plugin ordering and availability metadata. (file: /Users/lindad/.codex/skills/.system/plugin-creator/SKILL.md)\n- skill-creator: Guide for creating effective skills. This skill should be used when users want to create a new skill (or update an existing skill) that extends Codex's capabilities with specialized knowledge, workflows, or tool integrations. (file: /Users/lindad/.codex/skills/.system/skill-creator/SKILL.md)\n- skill-installer: Install Codex skills into $CODEX_HOME/skills from a curated list or a GitHub repo path. Use when a user asks to list installable skills, install a curated skill, or install a skill from another repo (including private repos). (file: /Users/lindad/.codex/skills/.system/skill-installer/SKILL.md)\n### How to use skills\n- Discovery: The list above is the skills available in this session (name + description + file path). Skill bodies live on disk at the listed paths.\n- Trigger rules: If the user names a skill (with `$SkillName` or plain text) OR the task clearly matches a skill's description shown above, you must use that skill for that turn. Multiple mentions mean use them all. Do not carry skills across turns unless re-mentioned.\n- Missing/blocked: If a named skill isn't in the list or the path can't be read, say so briefly and continue with the best fallback.\n- How to use a skill (progressive disclosure):\n 1) After deciding to use a skill, open its `SKILL.md`. Read only enough to follow the workflow.\n 2) When `SKILL.md` references relative paths (e.g., `scripts/foo.py`), resolve them relative to the skill directory listed above first, and only consider other paths if needed.\n 3) If `SKILL.md` points to extra folders such as `references/`, load only the specific files needed for the request; don't bulk-load everything.\n 4) If `scripts/` exist, prefer running or patching them instead of retyping large code blocks.\n 5) If `assets/` or templates exist, reuse them instead of recreating from scratch.\n- Coordination and sequencing:\n - If multiple skills apply, choose the minimal set that covers the request and state the order you'll use them.\n - Announce which skill(s) you're using and why (one short line). If you skip an obvious skill, say why.\n- Context hygiene:\n - Keep context small: summarize long sections instead of pasting them; only load extra files when needed.\n - Avoid deep reference-chasing: prefer opening only files directly linked from `SKILL.md` unless you're blocked.\n - When variants exist (frameworks, providers, domains), pick only the relevant reference file(s) and note that choice.\n- Safety and fallback: If a skill can't be applied cleanly (missing files, unclear instructions), state the issue, pick the next-best approach, and continue.","truncation_policy":{"mode":"tokens","limit":10000}}} +{"timestamp":"2026-03-27T18:06:06.176Z","type":"event_msg","payload":{"type":"agent_reasoning","text":"**Reviewing non-ascii files**\n\nI need to avoid lines related to AGENTS, especially since the output might include those due to non-ascii characters in the current file. I want to focus on changed files and identify exactly which ones those are. They likely include headers, C documentation, and comments in tests. I'll have to replace any problematic characters in comments and strings using apply_patch. I might not need to run tests since those changes are only in documentation."}} +{"timestamp":"2026-03-27T18:06:06.176Z","type":"response_item","payload":{"type":"reasoning","summary":[{"type":"summary_text","text":"**Reviewing non-ascii files**\n\nI need to avoid lines related to AGENTS, especially since the output might include those due to non-ascii characters in the current file. I want to focus on changed files and identify exactly which ones those are. They likely include headers, C documentation, and comments in tests. I'll have to replace any problematic characters in comments and strings using apply_patch. I might not need to run tests since those changes are only in documentation."}],"content":null,"encrypted_content":"gAAAAABpxscO8Px9qmqUccGXtahlB5MeZ_dZyP7upCOJ4ua2ywvjManfvif0uoLkxB714cEe37Gl7HHeNvTnncNUfSawSVNTrhdR623rKB63VMktUgsORAqyk4truULeqtuOPEZ16JrdUusDTkuPkZA0_WxOGJcrPqAcRmXilifLQ24FINBT_bTQb9Zg1RRR3HgFXM_Dztw0lre02vkXsyLeweBX9u6xUxACOLDcbJfrQuvJld3Vv7p3AFUPbUtt-s-sxiU8yHlalabxMMBJK_1vKIIIHBVdGyz6Atr4ZRjrQBMwINkd9gAzHrVGLu2meyf4dSgpJZ0Dvfg3mz1N8N65eo2ew6RFjRsctuBv0kpgD9-maQWD35qDsippAXEB8evDwxU65A0KcpTzUq-DvDCmv3udt9eBl0o0NVKs0mRwNLl18mJtHVx4zZowh_jjdqVHrGt03Ci7i-mrak5pdCQDZ1GBimsXvKebwyuL3aG_M-y7P7GKlInUCrNBFbaCCIHeS-nWezmNlzYSHrAcHzgLTw84D7uT38xuHvbIcTkjpFlj6ZL67u92PowiXz6E9Vs0JKnKbwzFSb7uAwz8Z56UTBKPRvSYSIp-_9uloYY4Jq5QEbzC7R9JUY4RvgbWJcBqwlOX61v1ywTMLjVv_BEZP0KJYnrAaMCLY-lycpq01d6I3I2GyAQou3dba9nbka2K_430NudCCmJayAUzggZ_fEAz7kHVyPg5qEBvtNTTC4bFBAap68XfUr9GloWO42YFdBXpaRxUQvXybwNh_swiOCMbKdW5ECjPLBnfBZfyM76J02jFKw3TymMP2B18U8tyZqoAAU20JYLxVxxtMjVun2qEu7YHeD5jZLQIUNIUpD38VYBy75TxRbo3SAhP5r04vU4Z_0ocEPH7Ew8aFAiiEmMdk9tIM1SD_Q0PIZLRQhAMWmEv-8ebmHvE8qAeUCzoy-GXAcbd6Fc3M7MTH92wpR0oaTBPd7TkyrsrrA7DPT2OI-d89yjntIHTZEaCVKY8_MA7_VFc2lxqxf32ZfFYjc2gDYxege_q4ItFBgs5ghw3R68bl_E2rQxglsRaD96jNdTwGL6xL3Ca9GYpyzC10W-A-4cIxLGcXaE8pu7NuG3oxQfZmdqWM5m--O28pUJzDlEXd2JyWt1Ngf3SUnj5GL5UDZoctLvqiXKP0ITMH6vbYo2gl_mpzezgPLdcJ2aMkCRX9cagsO0K_sF2p6S2aEPFAysMS4HCSFJ3zX1KPxRc6gAVvyL1urowQz2SZykJhmqJwaWKH0TpEceXbYj98vKmDrDMuOIg97g2z3zgD_Vfdo3ZOOGrjnFznS8g4zjE882euy6r-w6HxnvOEyq0jc6cFigbfYLIuG77P2y-zU3Yw433gw4tCCJjyrH9s9-YklTxAsP8oFqy626A0hkkgZTQwx_2z89wG401S9Ak6kx7B1nky9v4tc0CdCshus_V2JkR54Ui"}} +{"timestamp":"2026-03-27T18:06:09.660Z","type":"event_msg","payload":{"type":"agent_message","message":"The non-ASCII additions are concentrated in a few recent code comments and parameter descriptions, plus one input-file comment. I’m reading those exact sections now so I can normalize them without changing behavior.","phase":"commentary"}} +{"timestamp":"2026-03-27T18:06:09.660Z","type":"response_item","payload":{"type":"message","role":"assistant","content":[{"type":"output_text","text":"The non-ASCII additions are concentrated in a few recent code comments and parameter descriptions, plus one input-file comment. I’m reading those exact sections now so I can normalize them without changing behavior."}],"phase":"commentary"}} +{"timestamp":"2026-03-27T18:06:09.660Z","type":"response_item","payload":{"type":"function_call","name":"exec_command","arguments":"{\"cmd\":\"sed -n '1,120p' include/nodal_kernels/ReleasingNodalKernelDimensionless.h\",\"workdir\":\"/Users/lindad/projects/TMAP8\",\"max_output_tokens\":4000,\"yield_time_ms\":1000}","call_id":"call_eMnsSTR9gYzIxZuFIDxU295d"}} +{"timestamp":"2026-03-27T18:06:09.661Z","type":"response_item","payload":{"type":"function_call","name":"exec_command","arguments":"{\"cmd\":\"sed -n '1,220p' include/nodal_kernels/TrappingNodalKernelDimensionless.h\",\"workdir\":\"/Users/lindad/projects/TMAP8\",\"max_output_tokens\":5000,\"yield_time_ms\":1000}","call_id":"call_Usv8EiO5PER0bKysLwcE1oGo"}} +{"timestamp":"2026-03-27T18:06:09.672Z","type":"response_item","payload":{"type":"function_call","name":"exec_command","arguments":"{\"cmd\":\"sed -n '520,760p' src/physics/SpeciesTrappingPhysics.C\",\"workdir\":\"/Users/lindad/projects/TMAP8\",\"max_output_tokens\":7000,\"yield_time_ms\":1000}","call_id":"call_E7OaCQaTmxxV87hoznykq6BC"}} +{"timestamp":"2026-03-27T18:06:09.672Z","type":"response_item","payload":{"type":"function_call","name":"exec_command","arguments":"{\"cmd\":\"sed -n '300,340p' test/tests/val-2f/val-2f.i\",\"workdir\":\"/Users/lindad/projects/TMAP8\",\"max_output_tokens\":2000,\"yield_time_ms\":1000}","call_id":"call_obx5enAWWtaRQ1MbuHruqslB"}} +{"timestamp":"2026-03-27T18:06:09.732Z","type":"event_msg","payload":{"type":"token_count","info":{"total_token_usage":{"input_tokens":53989,"cached_input_tokens":39808,"output_tokens":1205,"reasoning_output_tokens":285,"total_tokens":55194},"last_token_usage":{"input_tokens":16271,"cached_input_tokens":14080,"output_tokens":414,"reasoning_output_tokens":101,"total_tokens":16685},"model_context_window":258400},"rate_limits":{"limit_id":"codex","limit_name":null,"primary":{"used_percent":15.0,"window_minutes":300,"resets_at":1774643092},"secondary":{"used_percent":27.0,"window_minutes":10080,"resets_at":1774905636},"credits":null,"plan_type":"enterprise"}}} +{"timestamp":"2026-03-27T18:06:09.844Z","type":"response_item","payload":{"type":"function_call_output","call_id":"call_eMnsSTR9gYzIxZuFIDxU295d","output":"Chunk ID: 808837\nWall time: 0.0517 seconds\nProcess exited with code 0\nOriginal token count: 298\nOutput:\n/************************************************************/\n/* DO NOT MODIFY THIS HEADER */\n/* TMAP8: Tritium Migration Analysis Program, Version 8 */\n/* */\n/* Copyright 2021 - 2025 Battelle Energy Alliance, LLC */\n/* ALL RIGHTS RESERVED */\n/************************************************************/\n\n#pragma once\n\n#include \"NodalKernel.h\"\n\n/**\n * Releasing NodalKernel for a dimensionless trapped-species variable\n * Ĉ_t = C_t / C_t_ref.\n *\n * The residual is:\n * R = +k_r_hat · exp(-E_r / T) · Ĉ_t\n *\n * where k_r_hat = t_ref · α_r.\n *\n * This is trivially dimensionless (O(k_r_hat)) because Ĉ_t is O(1).\n * No TMAPScaling / scaleResidual is used.\n */\nclass ReleasingNodalKernelDimensionless : public NodalKernel\n{\npublic:\n ReleasingNodalKernelDimensionless(const InputParameters & parameters);\n\n static InputParameters validParams();\n\nprotected:\n Real computeQpResidual() override;\n Real computeQpJacobian() override;\n\n const Real _dimensionless_release_rate;\n const Real _detrapping_energy;\n const VariableValue & _temperature;\n};\n"}} +{"timestamp":"2026-03-27T18:06:09.845Z","type":"response_item","payload":{"type":"function_call_output","call_id":"call_Usv8EiO5PER0bKysLwcE1oGo","output":"Chunk ID: 990661\nWall time: 0.0517 seconds\nProcess exited with code 0\nOriginal token count: 735\nOutput:\n/************************************************************/\n/* DO NOT MODIFY THIS HEADER */\n/* TMAP8: Tritium Migration Analysis Program, Version 8 */\n/* */\n/* Copyright 2021 - 2025 Battelle Energy Alliance, LLC */\n/* ALL RIGHTS RESERVED */\n/************************************************************/\n\n#pragma once\n\n#include \"NodalKernel.h\"\n\n#include \"metaphysicl/dualdynamicsparsenumberarray.h\"\n\nusing MetaPhysicL::DualNumber;\nusing MetaPhysicL::DynamicSparseNumberArray;\n\nclass Function;\n\n/// Type alias for AD dual numbers used in the manual Jacobian calculation.\n/// Reuse the same underlying type as TrappingNodalKernel.\ntypedef DualNumber> LocalDN;\n\n/**\n * Trapping NodalKernel that operates on a dimensionless trapped-species variable\n * Ĉ_t = C_t / C_t_ref, where C_t_ref is the trap concentration reference scale.\n *\n * The residual is:\n * R = -k_t_hat · exp(-E_t / T) · ((N·Ct0 - C_t_ref·Ĉ_t - Σ_j C_t_j) / C_t_ref) · Ĉ_m\n *\n * where:\n * - Ĉ_t = dimensionless variable (this kernel's variable), O(1)\n * - Ĉ_m = dimensionless mobile concentration. The coupled variable may be either physical\n * or dimensionless, controlled by the mobile_variable_is_dimensionless flag.\n * - C_t_j = C_t_ref_j * Ĉ_t_j, other trap species (dimensionless variable + reference, optional)\n * - C_t_ref = trap_concentration_reference parameter\n * - k_t_hat = t_ref · α_t · C_m_ref / N\n *\n * No TMAPScaling / scaleResidual is used. The residual is naturally O(k_t_hat).\n */\nclass TrappingNodalKernelDimensionless : public NodalKernel\n{\npublic:\n TrappingNodalKernelDimensionless(const InputParameters & parameters);\n\n static InputParameters validParams();\n\nprotected:\n Real computeQpResidual() override;\n Real computeQpJacobian() override;\n Real computeQpOffDiagJacobian(unsigned int jvar) override;\n\n const Real _dimensionless_trapping_rate;\n const Real _trapping_energy;\n const Function & _Ct0;\n const Real _N;\n /// C_t_ref: reference concentration for THIS trap (used to convert Ĉ_t back to physical)\n const Real _trap_concentration_reference;\n /// Dimensionless mobile concentration\n const VariableValue & _mobile_concentration;\n unsigned int _n_other_concs;\n /// Dimensionless concentrations of other trap types (Ĉ_t_j = C_t_j / C_t_ref_j)\n std::vector _other_trapped_concentrations;\n /// Reference concentrations C_t_ref_j for each other trap, to convert Ĉ_t_j → physical C_t_j\n std::vector _other_trap_concentration_references;\n /// Variable numbers: [other_trap_0, ..., other_trap_n, this_trap, mobile]\n std::vector _var_numbers;\n const Node * _last_node;\n const VariableValue & _temperature;\n LocalDN _jacobian;\n\nprivate:\n void ADHelper();\n};\n"}} +{"timestamp":"2026-03-27T18:06:09.859Z","type":"response_item","payload":{"type":"function_call_output","call_id":"call_E7OaCQaTmxxV87hoznykq6BC","output":"Chunk ID: 19ae79\nWall time: 0.0509 seconds\nProcess exited with code 0\nOriginal token count: 1562\nOutput:\n checkSizeComponentSpeciesIndexedVectorOfVector(_detrapping_energies, \"detrapping_energy\", false);\n checkSizeComponentIndexedVector(_component_temperatures, \"temperature\", false);\n checkSizeComponentSpeciesIndexedVectorOfVector(_mobile_species_names, \"mobile\", false);\n\n for (const auto c_i : index_range(_components))\n {\n // Use the whole phyiscs block restriction if using the same species variable everywhere\n const auto blocks =\n _single_variable_set ? _blocks : getActionComponent(_components[c_i]).blocks();\n\n // Create the kernel for each species\n for (const auto s_j : index_range(_species[c_i]))\n {\n const auto species_name = getSpeciesVariableName(c_i, s_j);\n const auto mobile_species_name = _mobile_species_names[c_i][s_j];\n\n // Time derivative — plain TimeDerivativeNodalKernel suffices for both paths:\n // • dimensionless path: variable IS Ĉ_t (O(1)), so dĈ_t/dt is correct as-is\n // • physical path: variable IS C_t, no per-row scaling is applied here\n if (isTransient())\n {\n const std::string kernel_type = \"TimeDerivativeNodalKernel\";\n InputParameters params = getFactory().getValidParams(kernel_type);\n params.set(\"variable\") = species_name;\n assignBlocks(params, blocks);\n getProblem().addNodalKernel(kernel_type, prefix() + species_name + \"_time\", params);\n }\n\n // Helper lambda: set temperature coupling (shared by trapping and releasing kernels)\n auto setTemperature = [&](InputParameters & p)\n {\n mooseAssert(c_i < _component_temperatures.size(), \"Should not happen\");\n if (MooseUtils::parsesToReal(_component_temperatures[c_i]))\n {\n std::istringstream ss(_component_temperatures[c_i]);\n Real value;\n ss >> value;\n p.defaultCoupledValue(\"temperature\", value, 0);\n p.set>(\"temperature\") = {};\n }\n else if (getProblem().hasVariable(_component_temperatures[c_i]))\n p.set>(\"temperature\") = {_component_temperatures[c_i]};\n else\n paramError(\"temperature\", \"Should be a constant or the name of a variable\");\n };\n\n // Trapping term\n {\n const std::string kernel_type =\n _use_dimensionless_species ? \"TrappingNodalKernelDimensionless\" : \"TrappingNodalKernel\";\n auto params = _factory.getValidParams(kernel_type);\n assignBlocks(params, blocks);\n params.set(\"variable\") = species_name;\n params.set>(\"mobile_concentration\") = {mobile_species_name};\n setTemperature(params);\n params.set(\"trapping_energy\") = _trapping_energies[c_i][s_j];\n params.set(\"N\") = _Ns[c_i];\n params.set(\"Ct0\") = _Ct0s[c_i][s_j];\n\n if (_use_dimensionless_species)\n {\n params.set(\"dimensionless_trapping_rate\") = dimensionlessTrappingRate(c_i, s_j);\n params.set(\"trap_concentration_reference\") = trapConcentrationReference(c_i, s_j);\n }\n else\n params.set(\"alpha_t\") = _alpha_ts[c_i][s_j];\n\n // Add the other species as occupying traps (shared-site physics).\n if (!getParam(\"different_traps_for_each_species\"))\n {\n std::vector copy_species;\n for (const auto & sp_name : _species[c_i])\n if (sp_name != species_name)\n copy_species.push_back(sp_name);\n\n if (copy_species.size())\n {\n params.set>(\"other_trapped_concentration_variables\") =\n copy_species;\n\n if (_use_dimensionless_species)\n {\n // Collect the reference concentration for each other trap species so the\n // dimensionless kernel can convert Ĉ_t_j → physical C_t_j.\n std::vector other_refs;\n other_refs.reserve(copy_species.size());\n for (unsigned int k = 0; k < _species[c_i].size(); ++k)\n if (_species[c_i][k] != species_name)\n other_refs.push_back(trapConcentrationReference(c_i, k));\n params.set>(\"other_trap_concentration_references\") = other_refs;\n }\n }\n }\n\n getProblem().addNodalKernel(kernel_type, prefix() + species_name + \"_enc_trapping\", params);\n }\n\n // Release term\n {\n const std::string kernel_type = _use_dimensionless_species\n ? \"ReleasingNodalKernelDimensionless\"\n : \"ReleasingNodalKernel\";\n auto params = _factory.getValidParams(kernel_type);\n assignBlocks(params, blocks);\n params.set(\"variable\") = species_name;\n params.set(\"detrapping_energy\") = _detrapping_energies[c_i][s_j];\n setTemperature(params);\n\n if (_use_dimensionless_species)\n params.set(\"dimensionless_release_rate\") = dimensionlessReleaseRate(c_i, s_j);\n else\n params.set(\"alpha_r\") = _alpha_rs[c_i][s_j];\n\n getProblem().addNodalKernel(kernel_type, prefix() + species_name + \"_enc_release\", params);\n }\n\n // Coupling of dC_t_i/dt into the mobile species conservation equation.\n {\n const std::string kernel_type = \"ScaledCoupledTimeDerivative\";\n auto params = _factory.getValidParams(kernel_type);\n assignBlocks(params, blocks);\n params.set(\"variable\") = mobile_species_name;\n params.set>(\"v\") = {species_name};\n if (_use_dimensionless_species)\n // Dimensionless path: add (C_t_ref_i / C_m_ref) * dĈ_t_i/dt.\n params.set(\"factor\") =\n trapConcentrationReference(c_i, s_j) / mobileConcentrationReference(c_i);\n else\n params.set(\"factor\") = _trap_per_frees[c_i];\n\n getProblem().addKernel(\n kernel_type, prefix() + mobile_species_name + \"_from_\" + species_name, params);\n }\n }\n if (_single_variable_set)\n break;\n }\n}\n"}} +{"timestamp":"2026-03-27T18:06:09.871Z","type":"response_item","payload":{"type":"function_call_output","call_id":"call_obx5enAWWtaRQ1MbuHruqslB","output":"Chunk ID: 534b7a\nWall time: 0.0521 seconds\nProcess exited with code 0\nOriginal token count: 313\nOutput:\n type = ScalePostprocessor\n scaling_factor = '${fparse -1 * mobile_concentration_reference * length_reference * ${units 1 m^2 -> mum^2} / time_reference}'\n value = flux_surface_right_sieverts\n execute_on = 'initial nonlinear linear timestep_end'\n []\n [max_scaled_flux_surface_right_sieverts]\n type = TimeExtremeValue\n postprocessor = scaled_flux_surface_right_sieverts\n value_type = max\n []\n [temperature]\n type = ElementAverageValue\n variable = temperature\n execute_on = 'initial timestep_end'\n []\n [diffusion_W_hat]\n type = ElementAverageMaterialProperty\n mat_prop = diffusivity_W_nonAD\n outputs = none\n []\n [diffusion_W]\n type = ScalePostprocessor\n scaling_factor = '${fparse length_reference ^ 2 / time_reference}'\n value = diffusion_W_hat\n outputs = none\n []\n [max_time_step_size]\n type = FunctionValuePostprocessor\n function = max_dt_size_function\n execute_on = 'initial nonlinear linear timestep_end'\n outputs = none\n []\n [max_time_step_size_coarse]\n type = FunctionValuePostprocessor\n function = max_dt_size_function_coarse\n execute_on = 'initial nonlinear linear timestep_end'\n outputs = none\n []\n\n [spatial_max_mobile_d2]\n type = NodalExtremeValue\n"}} +{"timestamp":"2026-03-27T18:06:09.871Z","type":"turn_context","payload":{"turn_id":"019d3079-3ee6-7c93-a382-6cbfe9cff7d7","cwd":"/Users/lindad/projects/TMAP8","approval_policy":"on-request","sandbox_policy":{"type":"workspace-write","network_access":false,"exclude_tmpdir_env_var":false,"exclude_slash_tmp":false},"model":"gpt-5.4","personality":"pragmatic","collaboration_mode":{"mode":"default","settings":{"model":"gpt-5.4","reasoning_effort":"medium","developer_instructions":"# Collaboration Mode: Default\n\nYou are now in Default mode. Any previous instructions for other modes (e.g. Plan mode) are no longer active.\n\nYour active mode changes only when new developer instructions with a different `...` change it; user requests or tool descriptions do not change mode by themselves. Known mode names are Default and Plan.\n\n## request_user_input availability\n\nThe `request_user_input` tool is unavailable in Default mode. If you call it while in Default mode, it will return an error.\n\nIn Default mode, strongly prefer making reasonable assumptions and executing the user's request rather than stopping to ask questions. If you absolutely must ask a question because the answer cannot be discovered from local context and a reasonable assumption would be risky, ask the user directly with a concise plain-text question. Never write a multiple choice question as a textual assistant message.\n"}},"effort":"medium","summary":"auto","user_instructions":"# AGENTS.md\n\n## Environment\n- Ask the user if you need to load a MOOSE conda environment, and if so, what the name of the conda environment is\n- If `./tmap8-opt` or `run_tests` throws an error, stop and ask the user\n- Pre-commit hooks handle all formatting and input file validation on every `git commit` — do not invoke `clang-format`, `black`, or `hit format` manually\n- `moose/framework/contrib/hit/hit check .i` is available to validate input files during development — use it before committing\n\n## Before writing any code or input file\n- Browse `doc/content/` to understand documentation standards and existing patterns before starting work\n- Before writing a new C++ class, look through existing MOOSE classes in the codebase to confirm expected syntax and patterns\n- Documentation in `doc/content/` may not accurately reflect current code behavior — once you identify a class to use in an input file, find its C++ implementation and read it to confirm the class does what you expect before writing the input file\n\n## C++ code\n- Every new class requires a MOOSE TestHarness test in `test/tests/` before committing\n- Every new class requires a MooseDocs page following existing TMAP8 doc structure\n- Never hardcode physical parameters — first check if it is already defined in `doc/content/source/utils/TMAP8PhysicalConstants`, and if not available, expose everything through `addParam`\n- Code is unit-agnostic; units live in input files only\n\n## Input files\n- Before writing an input file, look through existing MOOSE and TMAP8 classes to confirm object names and parameter syntax\n- Use `moose/framework/contrib/hit/hit check .i` to validate before committing\n- Use `./tmap8-opt -i .i` to run input files\n- Write parameter values in the units the reference source used; use the MOOSE units system for conversion — the units system is self-documenting and does not require inline comments\n- State the unit system at the top of every input file in a comment block\n\n## Testing\n- Run tests only when `.C`, `.h`, or `test/tests/` files change\n- Run only the affected module: `./run_tests -j --re `\n\n## Session log\n- Every session must be associated with a GitHub issue on `idaholab/TMAP8`; ask the user for the issue number at the start of the session if one is not provided, or create one if the user instructs you to\n- **SQA requirement:** When creating a GitHub issue with `gh`, you must use the appropriate template from `.github/ISSUE_TEMPLATE/`; read the available templates first, select the one that fits (e.g. `bug-report.md` for bugs, `feature-request.md` for new features or tasks), and populate all sections in the template body — passing a bare description without following the template structure is not acceptable\n- Before committing, copy the current session's `.jsonl` file into `doc/content/agent//`. For Claude Code sessions the file is the most recently modified `.jsonl` under `~/.claude/projects//`; for Codex sessions check the equivalent Codex session directory. Do not remove old session files already in that directory — append the new one alongside them.\n\n## Committing\n- Commit at minimum after: every input file that successfully runs, every test that passes or fails, and every new class added\n- If a test or run failed, commit the failure state first (include the full error message in the commit body), then commit the fix separately\n- Every commit must reference the associated GitHub issue (e.g. `Refs #` or `Closes #` as appropriate) in the commit message\n- **Every commit must include an updated copy of the session `.jsonl`** — before staging, copy the current session file from `~/.claude/projects//.jsonl` to `doc/content/agent//` and stage it; this is a critical SQA requirement. Do not remove session files already present in that directory — if multiple Claude/Codex sessions contribute to the same branch and issue, all session files must be kept.\n- Every commit must include these trailers:\n```\nRefs #\nAI-assisted: true\nAI-model: \nAI-version: \nCo-Authored-By: \n```\n\n## Pull requests\n- If the linked issue already contains a complete Reason/Design/Impact description, the PR body should contain only the closing reference (e.g. `Closes #`) — do not duplicate the issue content or leave template sections empty\n- If the PR introduces physics/modeling decisions, non-obvious AI reasoning, or tests not described in the issue, add those as a short addendum below the issue reference\n- Never merge autonomously\n\n## Never do\n- Modify existing passing tests without explicit user instruction\n- Modify the build system without explicit user instruction\n- Make physics modeling decisions without flagging them to the user\n- Suppress or bypass test failures\n\n\n## Skills\nA skill is a set of local instructions to follow that is stored in a `SKILL.md` file. Below is the list of skills that can be used. Each entry includes a name, description, and file path so you can open the source for full instructions when using a specific skill.\n### Available skills\n- openai-docs: Use when the user asks how to build with OpenAI products or APIs and needs up-to-date official documentation with citations, help choosing the latest model for a use case, or explicit GPT-5.4 upgrade and prompt-upgrade guidance; prioritize OpenAI docs MCP tools, use bundled references only as helper context, and restrict any fallback browsing to official OpenAI domains. (file: /Users/lindad/.codex/skills/.system/openai-docs/SKILL.md)\n- plugin-creator: Create and scaffold plugin directories for Codex with a required `.codex-plugin/plugin.json`, optional plugin folders/files, and baseline placeholders you can edit before publishing or testing. Use when Codex needs to create a new local plugin, add optional plugin structure, or generate or update repo-root `.agents/plugins/marketplace.json` entries for plugin ordering and availability metadata. (file: /Users/lindad/.codex/skills/.system/plugin-creator/SKILL.md)\n- skill-creator: Guide for creating effective skills. This skill should be used when users want to create a new skill (or update an existing skill) that extends Codex's capabilities with specialized knowledge, workflows, or tool integrations. (file: /Users/lindad/.codex/skills/.system/skill-creator/SKILL.md)\n- skill-installer: Install Codex skills into $CODEX_HOME/skills from a curated list or a GitHub repo path. Use when a user asks to list installable skills, install a curated skill, or install a skill from another repo (including private repos). (file: /Users/lindad/.codex/skills/.system/skill-installer/SKILL.md)\n### How to use skills\n- Discovery: The list above is the skills available in this session (name + description + file path). Skill bodies live on disk at the listed paths.\n- Trigger rules: If the user names a skill (with `$SkillName` or plain text) OR the task clearly matches a skill's description shown above, you must use that skill for that turn. Multiple mentions mean use them all. Do not carry skills across turns unless re-mentioned.\n- Missing/blocked: If a named skill isn't in the list or the path can't be read, say so briefly and continue with the best fallback.\n- How to use a skill (progressive disclosure):\n 1) After deciding to use a skill, open its `SKILL.md`. Read only enough to follow the workflow.\n 2) When `SKILL.md` references relative paths (e.g., `scripts/foo.py`), resolve them relative to the skill directory listed above first, and only consider other paths if needed.\n 3) If `SKILL.md` points to extra folders such as `references/`, load only the specific files needed for the request; don't bulk-load everything.\n 4) If `scripts/` exist, prefer running or patching them instead of retyping large code blocks.\n 5) If `assets/` or templates exist, reuse them instead of recreating from scratch.\n- Coordination and sequencing:\n - If multiple skills apply, choose the minimal set that covers the request and state the order you'll use them.\n - Announce which skill(s) you're using and why (one short line). If you skip an obvious skill, say why.\n- Context hygiene:\n - Keep context small: summarize long sections instead of pasting them; only load extra files when needed.\n - Avoid deep reference-chasing: prefer opening only files directly linked from `SKILL.md` unless you're blocked.\n - When variants exist (frameworks, providers, domains), pick only the relevant reference file(s) and note that choice.\n- Safety and fallback: If a skill can't be applied cleanly (missing files, unclear instructions), state the issue, pick the next-best approach, and continue.","truncation_policy":{"mode":"tokens","limit":10000}}} +{"timestamp":"2026-03-27T18:06:15.482Z","type":"response_item","payload":{"type":"reasoning","summary":[],"content":null,"encrypted_content":"gAAAAABpxscXHantgmn1lrWVh5eV5MucNrlBqF0fL3f41gJ9togDvwA9LQa26_8yDiuKRqAWMJ8CIKLV9BDkqTo0QRO6iB8VvMVWdJNY-oyznwSzrGQOk1AmUfbuLIZb7ZKbAv2Pe_J5O557ZYUk9Cb-9BN_MSxBFs_J23hBrmBlJxjvMHWHELwnvPelCtqfr5rHY6ZBZFt7FbDAyknfXLSA9dEc5-OUt9XUXUTSUL6IX4DtiYHVUzIL6qp1OemkIIDMKAG_rm6Ank5uZ9laSSVR3OfnZAVwJiPmef2ZEXwX7QEzbJiMV0tPXiWaPy3o6uZ2CwmDwD_bYwLg1QqPBRMdjvuByyRyiVbmkXu2XcA-TXatOArONXkFoJiNmfEbkYVqFIj3lScrH8K026ahPi90D2G9O7mWAyX4ob8zlCmwi-5TtwjM3DxZmb8kXfSBc-N2umzBoyh7IMpbqNJMpIecqzj4fX90yw4FparJT4nK4Vg50PeTySIrPNpxERqVNrVnbYh0-eLU-ci8DFcv-B4cQqLTd18nHRUsZFs6bCP2gmMXIOuSiF-BKlrF3cm-FxO-_3SSeNuXOlJP5-ZO3nm0Dv2ZBUgWMAdPSUzrcou4JASq_AcusVJ6tn4Fj2aOkTGLNQA6lHSo79crwQ7Dio4MsxZkGlKDQ41eDqfBfU8d_qH_yin91VlY1FOcLRIN_y7Xb507zRaXwHhz9dPAR7sMhQTa6-qSU23iOMWbA1vB6fm44rTsDkxcSR6zRhwCOpdDXQTburAJAfu4R5rJvGR22zu8MCD3BWNe_IA3TiMFO8crhjRMUSf_NHtwHb6z5v5WUiKu1P8XO3DbVM8T2NTKXggmZc3e_vzLcO9gC2ujDvO4xd84nmaun3CFnc6LtEMQ4sPJuhEQglTO4uBoi3wXkWiyx30C5uefDYU4rkcxo99MQVeSjfg="}} +{"timestamp":"2026-03-27T18:06:15.482Z","type":"response_item","payload":{"type":"function_call","name":"exec_command","arguments":"{\"cmd\":\"rg -n --pcre2 \\\"[^\\\\x00-\\\\x7F]\\\" include/nodal_kernels/ReleasingNodalKernelDimensionless.h include/nodal_kernels/TrappingNodalKernelDimensionless.h src/physics/SpeciesTrappingPhysics.C test/tests/val-2f/val-2f.i\",\"workdir\":\"/Users/lindad/projects/TMAP8\",\"max_output_tokens\":4000,\"yield_time_ms\":1000}","call_id":"call_KufGQltHskvdy1tdOn7uSoZt"}} +{"timestamp":"2026-03-27T18:06:15.483Z","type":"response_item","payload":{"type":"function_call","name":"exec_command","arguments":"{\"cmd\":\"sed -n '1,120p' src/nodal_kernels/ReleasingNodalKernelDimensionless.C\",\"workdir\":\"/Users/lindad/projects/TMAP8\",\"max_output_tokens\":4000,\"yield_time_ms\":1000}","call_id":"call_YFds1uJVuckBYrpI5GnehfKF"}} +{"timestamp":"2026-03-27T18:06:15.483Z","type":"response_item","payload":{"type":"function_call","name":"exec_command","arguments":"{\"cmd\":\"sed -n '1,180p' src/nodal_kernels/TrappingNodalKernelDimensionless.C\",\"workdir\":\"/Users/lindad/projects/TMAP8\",\"max_output_tokens\":5000,\"yield_time_ms\":1000}","call_id":"call_Zzw1iIgYAkmcJue93RzjEWPV"}} +{"timestamp":"2026-03-27T18:06:15.585Z","type":"event_msg","payload":{"type":"token_count","info":{"total_token_usage":{"input_tokens":73500,"cached_input_tokens":56320,"output_tokens":1479,"reasoning_output_tokens":304,"total_tokens":74979},"last_token_usage":{"input_tokens":19511,"cached_input_tokens":16512,"output_tokens":274,"reasoning_output_tokens":19,"total_tokens":19785},"model_context_window":258400},"rate_limits":{"limit_id":"codex","limit_name":null,"primary":{"used_percent":15.0,"window_minutes":300,"resets_at":1774643092},"secondary":{"used_percent":27.0,"window_minutes":10080,"resets_at":1774905636},"credits":null,"plan_type":"enterprise"}}} +{"timestamp":"2026-03-27T18:06:15.666Z","type":"response_item","payload":{"type":"function_call_output","call_id":"call_KufGQltHskvdy1tdOn7uSoZt","output":"Chunk ID: 00bae0\nWall time: 0.0516 seconds\nProcess exited with code 0\nOriginal token count: 583\nOutput:\nsrc/physics/SpeciesTrappingPhysics.C:536: // Time derivative — plain TimeDerivativeNodalKernel suffices for both paths:\nsrc/physics/SpeciesTrappingPhysics.C:537: // • dimensionless path: variable IS Ĉ_t (O(1)), so dĈ_t/dt is correct as-is\nsrc/physics/SpeciesTrappingPhysics.C:538: // • physical path: variable IS C_t, no per-row scaling is applied here\nsrc/physics/SpeciesTrappingPhysics.C:603: // dimensionless kernel can convert Ĉ_t_j → physical C_t_j.\nsrc/physics/SpeciesTrappingPhysics.C:644: // Dimensionless path: add (C_t_ref_i / C_m_ref) * dĈ_t_i/dt.\ninclude/nodal_kernels/TrappingNodalKernelDimensionless.h:26: * Ĉ_t = C_t / C_t_ref, where C_t_ref is the trap concentration reference scale.\ninclude/nodal_kernels/TrappingNodalKernelDimensionless.h:29: * R = -k_t_hat · exp(-E_t / T) · ((N·Ct0 - C_t_ref·Ĉ_t - Σ_j C_t_j) / C_t_ref) · Ĉ_m\ninclude/nodal_kernels/TrappingNodalKernelDimensionless.h:32: * - Ĉ_t = dimensionless variable (this kernel's variable), O(1)\ninclude/nodal_kernels/TrappingNodalKernelDimensionless.h:33: * - Ĉ_m = dimensionless mobile concentration. The coupled variable may be either physical\ninclude/nodal_kernels/TrappingNodalKernelDimensionless.h:35: * - C_t_j = C_t_ref_j * Ĉ_t_j, other trap species (dimensionless variable + reference, optional)\ninclude/nodal_kernels/TrappingNodalKernelDimensionless.h:37: * - k_t_hat = t_ref · α_t · C_m_ref / N\ninclude/nodal_kernels/TrappingNodalKernelDimensionless.h:57: /// C_t_ref: reference concentration for THIS trap (used to convert Ĉ_t back to physical)\ninclude/nodal_kernels/TrappingNodalKernelDimensionless.h:62: /// Dimensionless concentrations of other trap types (Ĉ_t_j = C_t_j / C_t_ref_j)\ninclude/nodal_kernels/TrappingNodalKernelDimensionless.h:64: /// Reference concentrations C_t_ref_j for each other trap, to convert Ĉ_t_j → physical C_t_j\ninclude/nodal_kernels/ReleasingNodalKernelDimensionless.h:15: * Ĉ_t = C_t / C_t_ref.\ninclude/nodal_kernels/ReleasingNodalKernelDimensionless.h:18: * R = +k_r_hat · exp(-E_r / T) · Ĉ_t\ninclude/nodal_kernels/ReleasingNodalKernelDimensionless.h:20: * where k_r_hat = t_ref · α_r.\ninclude/nodal_kernels/ReleasingNodalKernelDimensionless.h:22: * This is trivially dimensionless (O(k_r_hat)) because Ĉ_t is O(1).\n"}} +{"timestamp":"2026-03-27T18:06:15.673Z","type":"response_item","payload":{"type":"function_call_output","call_id":"call_YFds1uJVuckBYrpI5GnehfKF","output":"Chunk ID: 0cf71c\nWall time: 0.0513 seconds\nProcess exited with code 0\nOriginal token count: 546\nOutput:\n/************************************************************/\n/* DO NOT MODIFY THIS HEADER */\n/* TMAP8: Tritium Migration Analysis Program, Version 8 */\n/* */\n/* Copyright 2021 - 2025 Battelle Energy Alliance, LLC */\n/* ALL RIGHTS RESERVED */\n/************************************************************/\n\n#include \"ReleasingNodalKernelDimensionless.h\"\n\nregisterMooseObject(\"TMAP8App\", ReleasingNodalKernelDimensionless);\n\nInputParameters\nReleasingNodalKernelDimensionless::validParams()\n{\n InputParameters params = NodalKernel::validParams();\n params.addClassDescription(\n \"Implements the release source term for a dimensionless trapped-species variable \"\n \"Ĉ_t = C_t / C_t_ref. \"\n \"The residual R = +k_r_hat · exp(-E_r / T) · Ĉ_t is naturally O(k_r_hat) \"\n \"because Ĉ_t is O(1). No equation scaling is applied.\");\n params.addRequiredParam(\"dimensionless_release_rate\",\n \"Dimensionless release rate k_r_hat = t_ref * alpha_r.\");\n params.addParam(\"detrapping_energy\", 0, \"The detrapping activation energy (K)\");\n params.addRequiredCoupledVar(\"temperature\", \"The temperature (K)\");\n return params;\n}\n\nReleasingNodalKernelDimensionless::ReleasingNodalKernelDimensionless(\n const InputParameters & parameters)\n : NodalKernel(parameters),\n _dimensionless_release_rate(getParam(\"dimensionless_release_rate\")),\n _detrapping_energy(getParam(\"detrapping_energy\")),\n _temperature(coupledValue(\"temperature\"))\n{\n}\n\nReal\nReleasingNodalKernelDimensionless::computeQpResidual()\n{\n const Real residual =\n _dimensionless_release_rate * std::exp(-_detrapping_energy / _temperature[_qp]) * _u[_qp];\n\n mooseAssert(residual >= 0,\n \"ReleasingNodalKernelDimensionless returned a negative residual, which is not \"\n \"physically expected for a release source.\");\n\n return residual;\n}\n\nReal\nReleasingNodalKernelDimensionless::computeQpJacobian()\n{\n return _dimensionless_release_rate * std::exp(-_detrapping_energy / _temperature[_qp]);\n}\n"}} +{"timestamp":"2026-03-27T18:06:15.673Z","type":"response_item","payload":{"type":"function_call_output","call_id":"call_Zzw1iIgYAkmcJue93RzjEWPV","output":"Chunk ID: 810a70\nWall time: 0.0515 seconds\nProcess exited with code 0\nOriginal token count: 1735\nOutput:\n/************************************************************/\n/* DO NOT MODIFY THIS HEADER */\n/* TMAP8: Tritium Migration Analysis Program, Version 8 */\n/* */\n/* Copyright 2021 - 2025 Battelle Energy Alliance, LLC */\n/* ALL RIGHTS RESERVED */\n/************************************************************/\n\n#include \"TrappingNodalKernelDimensionless.h\"\n#include \"Function.h\"\n\nregisterMooseObject(\"TMAP8App\", TrappingNodalKernelDimensionless);\n\nInputParameters\nTrappingNodalKernelDimensionless::validParams()\n{\n InputParameters params = NodalKernel::validParams();\n params.addClassDescription(\n \"Implements the trapping source term for a dimensionless trapped-species variable \"\n \"Ĉ_t = C_t / C_t_ref. \"\n \"The mobile concentration may be either physical or dimensionless. \"\n \"No equation scaling is applied; the residual is O(k_t_hat).\");\n params.addRequiredParam(\n \"dimensionless_trapping_rate\",\n \"Dimensionless trapping rate k_t_hat = t_ref * alpha_t * C_m_ref / N.\");\n params.addParam(\"trapping_energy\", 0, \"The trapping activation energy (K)\");\n params.addRequiredParam(\"N\", \"The atomic number density of the host material (1/m^3)\");\n params.addRequiredParam(\n \"Ct0\",\n \"The fraction of host sites that can contribute to trapping as a function of position (-)\");\n params.addRequiredParam(\n \"trap_concentration_reference\",\n \"Reference concentration C_t_ref for this trap species (same units as N). \"\n \"Typically set to N * Ct0_max. The variable stores Ĉ_t = C_t / C_t_ref.\");\n params.addRequiredCoupledVar(\n \"mobile_concentration\",\n \"The variable representing the dimensionless mobile concentration of solute particles.\");\n params.addCoupledVar(\"other_trapped_concentration_variables\",\n \"Dimensionless trapped-concentration variables (Ĉ_t_j = C_t_j / C_t_ref_j) \"\n \"for other trap species that compete for the same trapping sites.\");\n params.addParam>(\n \"other_trap_concentration_references\",\n {},\n \"Reference concentrations C_t_ref_j for each variable listed in \"\n \"other_trapped_concentration_variables, used to convert Ĉ_t_j back to physical C_t_j \"\n \"when computing available trapping sites. Must match in length.\");\n params.addRequiredCoupledVar(\"temperature\", \"The temperature (K)\");\n return params;\n}\n\nTrappingNodalKernelDimensionless::TrappingNodalKernelDimensionless(\n const InputParameters & parameters)\n : NodalKernel(parameters),\n _dimensionless_trapping_rate(getParam(\"dimensionless_trapping_rate\")),\n _trapping_energy(getParam(\"trapping_energy\")),\n _Ct0(getFunction(\"Ct0\")),\n _N(getParam(\"N\")),\n _trap_concentration_reference(getParam(\"trap_concentration_reference\")),\n _mobile_concentration(coupledValue(\"mobile_concentration\")),\n _last_node(nullptr),\n _temperature(coupledValue(\"temperature\"))\n{\n _n_other_concs = coupledComponents(\"other_trapped_concentration_variables\");\n _other_trap_concentration_references =\n getParam>(\"other_trap_concentration_references\");\n\n if (!_other_trap_concentration_references.empty() &&\n _other_trap_concentration_references.size() != _n_other_concs)\n paramError(\"other_trap_concentration_references\",\n \"Length (\",\n _other_trap_concentration_references.size(),\n \") must match the number of other_trapped_concentration_variables (\",\n _n_other_concs,\n \").\");\n\n // Default: treat each missing reference as 1.0 (physical units, backward compat)\n if (_other_trap_concentration_references.empty() && _n_other_concs > 0)\n _other_trap_concentration_references.assign(_n_other_concs, 1.0);\n\n // Resize to n_other_concs plus the concentration for this kernel's variable\n _other_trapped_concentrations.resize(_n_other_concs);\n\n // var_numbers: [other_trap_0, ..., other_trap_{n-1}, this_trap, mobile]\n _var_numbers.resize(2 + _n_other_concs);\n\n for (MooseIndex(_n_other_concs) i = 0; i < _n_other_concs; ++i)\n {\n _other_trapped_concentrations[i] =\n &coupledValue(\"other_trapped_concentration_variables\", /*comp=*/i);\n _var_numbers[i] = coupled(\"other_trapped_concentration_variables\", i);\n }\n _var_numbers[_n_other_concs] = _var.number();\n _var_numbers[_n_other_concs + 1] = coupled(\"mobile_concentration\");\n}\n\nReal\nTrappingNodalKernelDimensionless::computeQpResidual()\n{\n // Physical empty trapping sites for this trap type:\n // N * Ct0(x) - C_t_ref * Ĉ_t - sum_j C_t_ref_j * Ĉ_t_j\n Real empty_trapping_sites = _Ct0.value(_t, (*_current_node)) * _N;\n empty_trapping_sites -= _u[_qp] * _trap_concentration_reference;\n for (MooseIndex(_n_other_concs) j = 0; j < _n_other_concs; ++j)\n empty_trapping_sites -=\n (*_other_trapped_concentrations[j])[_qp] * _other_trap_concentration_references[j];\n\n const Real residual =\n -_dimensionless_trapping_rate * std::exp(-_trapping_energy / _temperature[_qp]) *\n (empty_trapping_sites / _trap_concentration_reference) * _mobile_concentration[_qp];\n return residual;\n}\n\nvoid\nTrappingNodalKernelDimensionless::ADHelper()\n{\n if (_current_node == _last_node)\n return;\n\n _last_node = _current_node;\n\n // Compute empty trapping sites with dual-number tracking for AD Jacobian\n LocalDN empty_trapping_sites = _Ct0.value(_t, (*_current_node)) * _N;\n\n // Other traps: dimensionless Ĉ_t_j, multiplied by C_t_ref_j to get physical units\n for (MooseIndex(_n_other_concs) i = 0; i < _n_other_concs; ++i)\n {\n LocalDN other_dn = (*_other_trapped_concentrations[i])[_qp];\n other_dn.derivatives().insert(_var_numbers[i]) = 1.;\n empty_trapping_sites -= other_dn * _other_trap_concentration_references[i];\n }\n\n // This trap: variable is dimensionless Ĉ_t, multiply by C_t_ref to get physical\n LocalDN this_trap_dn = _u[_qp];\n this_trap_dn.derivatives().insert(_var_numbers[_n_other_concs]) = 1.;\n empty_trapping_sites -= this_trap_dn * _trap_concentration_reference;\n\n // Mobile concentration in dimensionless form Ĉ_m\n LocalDN mobile_dn = _mobile_concentration[_qp];\n mobile_dn.derivatives().insert(_var_numbers.back()) = 1.;\n\n _jacobian = -_dimensionless_trapping_rate * std::exp(-_trapping_energy / _temperature[_qp]) *\n (empty_trapping_sites / _trap_concentration_reference) * mobile_dn;\n}\n\nReal\nTrappingNodalKernelDimensionless::computeQpJacobian()\n{\n ADHelper();\n return _jacobian.derivatives()[_var.number()];\n}\n\nReal\nTrappingNodalKernelDimensionless::computeQpOffDiagJacobian(unsigned int jvar)\n{\n if (std::find(_var_numbers.begin(), _var_numbers.end(), jvar) != _var_numbers.end())\n {\n ADHelper();\n return _jacobian.derivatives()[jvar];\n }\n else\n return 0;\n}\n"}} +{"timestamp":"2026-03-27T18:06:15.673Z","type":"turn_context","payload":{"turn_id":"019d3079-3ee6-7c93-a382-6cbfe9cff7d7","cwd":"/Users/lindad/projects/TMAP8","approval_policy":"on-request","sandbox_policy":{"type":"workspace-write","network_access":false,"exclude_tmpdir_env_var":false,"exclude_slash_tmp":false},"model":"gpt-5.4","personality":"pragmatic","collaboration_mode":{"mode":"default","settings":{"model":"gpt-5.4","reasoning_effort":"medium","developer_instructions":"# Collaboration Mode: Default\n\nYou are now in Default mode. Any previous instructions for other modes (e.g. Plan mode) are no longer active.\n\nYour active mode changes only when new developer instructions with a different `...` change it; user requests or tool descriptions do not change mode by themselves. Known mode names are Default and Plan.\n\n## request_user_input availability\n\nThe `request_user_input` tool is unavailable in Default mode. If you call it while in Default mode, it will return an error.\n\nIn Default mode, strongly prefer making reasonable assumptions and executing the user's request rather than stopping to ask questions. If you absolutely must ask a question because the answer cannot be discovered from local context and a reasonable assumption would be risky, ask the user directly with a concise plain-text question. Never write a multiple choice question as a textual assistant message.\n"}},"effort":"medium","summary":"auto","user_instructions":"# AGENTS.md\n\n## Environment\n- Ask the user if you need to load a MOOSE conda environment, and if so, what the name of the conda environment is\n- If `./tmap8-opt` or `run_tests` throws an error, stop and ask the user\n- Pre-commit hooks handle all formatting and input file validation on every `git commit` — do not invoke `clang-format`, `black`, or `hit format` manually\n- `moose/framework/contrib/hit/hit check .i` is available to validate input files during development — use it before committing\n\n## Before writing any code or input file\n- Browse `doc/content/` to understand documentation standards and existing patterns before starting work\n- Before writing a new C++ class, look through existing MOOSE classes in the codebase to confirm expected syntax and patterns\n- Documentation in `doc/content/` may not accurately reflect current code behavior — once you identify a class to use in an input file, find its C++ implementation and read it to confirm the class does what you expect before writing the input file\n\n## C++ code\n- Every new class requires a MOOSE TestHarness test in `test/tests/` before committing\n- Every new class requires a MooseDocs page following existing TMAP8 doc structure\n- Never hardcode physical parameters — first check if it is already defined in `doc/content/source/utils/TMAP8PhysicalConstants`, and if not available, expose everything through `addParam`\n- Code is unit-agnostic; units live in input files only\n\n## Input files\n- Before writing an input file, look through existing MOOSE and TMAP8 classes to confirm object names and parameter syntax\n- Use `moose/framework/contrib/hit/hit check .i` to validate before committing\n- Use `./tmap8-opt -i .i` to run input files\n- Write parameter values in the units the reference source used; use the MOOSE units system for conversion — the units system is self-documenting and does not require inline comments\n- State the unit system at the top of every input file in a comment block\n\n## Testing\n- Run tests only when `.C`, `.h`, or `test/tests/` files change\n- Run only the affected module: `./run_tests -j --re `\n\n## Session log\n- Every session must be associated with a GitHub issue on `idaholab/TMAP8`; ask the user for the issue number at the start of the session if one is not provided, or create one if the user instructs you to\n- **SQA requirement:** When creating a GitHub issue with `gh`, you must use the appropriate template from `.github/ISSUE_TEMPLATE/`; read the available templates first, select the one that fits (e.g. `bug-report.md` for bugs, `feature-request.md` for new features or tasks), and populate all sections in the template body — passing a bare description without following the template structure is not acceptable\n- Before committing, copy the current session's `.jsonl` file into `doc/content/agent//`. For Claude Code sessions the file is the most recently modified `.jsonl` under `~/.claude/projects//`; for Codex sessions check the equivalent Codex session directory. Do not remove old session files already in that directory — append the new one alongside them.\n\n## Committing\n- Commit at minimum after: every input file that successfully runs, every test that passes or fails, and every new class added\n- If a test or run failed, commit the failure state first (include the full error message in the commit body), then commit the fix separately\n- Every commit must reference the associated GitHub issue (e.g. `Refs #` or `Closes #` as appropriate) in the commit message\n- **Every commit must include an updated copy of the session `.jsonl`** — before staging, copy the current session file from `~/.claude/projects//.jsonl` to `doc/content/agent//` and stage it; this is a critical SQA requirement. Do not remove session files already present in that directory — if multiple Claude/Codex sessions contribute to the same branch and issue, all session files must be kept.\n- Every commit must include these trailers:\n```\nRefs #\nAI-assisted: true\nAI-model: \nAI-version: \nCo-Authored-By: \n```\n\n## Pull requests\n- If the linked issue already contains a complete Reason/Design/Impact description, the PR body should contain only the closing reference (e.g. `Closes #`) — do not duplicate the issue content or leave template sections empty\n- If the PR introduces physics/modeling decisions, non-obvious AI reasoning, or tests not described in the issue, add those as a short addendum below the issue reference\n- Never merge autonomously\n\n## Never do\n- Modify existing passing tests without explicit user instruction\n- Modify the build system without explicit user instruction\n- Make physics modeling decisions without flagging them to the user\n- Suppress or bypass test failures\n\n\n## Skills\nA skill is a set of local instructions to follow that is stored in a `SKILL.md` file. Below is the list of skills that can be used. Each entry includes a name, description, and file path so you can open the source for full instructions when using a specific skill.\n### Available skills\n- openai-docs: Use when the user asks how to build with OpenAI products or APIs and needs up-to-date official documentation with citations, help choosing the latest model for a use case, or explicit GPT-5.4 upgrade and prompt-upgrade guidance; prioritize OpenAI docs MCP tools, use bundled references only as helper context, and restrict any fallback browsing to official OpenAI domains. (file: /Users/lindad/.codex/skills/.system/openai-docs/SKILL.md)\n- plugin-creator: Create and scaffold plugin directories for Codex with a required `.codex-plugin/plugin.json`, optional plugin folders/files, and baseline placeholders you can edit before publishing or testing. Use when Codex needs to create a new local plugin, add optional plugin structure, or generate or update repo-root `.agents/plugins/marketplace.json` entries for plugin ordering and availability metadata. (file: /Users/lindad/.codex/skills/.system/plugin-creator/SKILL.md)\n- skill-creator: Guide for creating effective skills. This skill should be used when users want to create a new skill (or update an existing skill) that extends Codex's capabilities with specialized knowledge, workflows, or tool integrations. (file: /Users/lindad/.codex/skills/.system/skill-creator/SKILL.md)\n- skill-installer: Install Codex skills into $CODEX_HOME/skills from a curated list or a GitHub repo path. Use when a user asks to list installable skills, install a curated skill, or install a skill from another repo (including private repos). (file: /Users/lindad/.codex/skills/.system/skill-installer/SKILL.md)\n### How to use skills\n- Discovery: The list above is the skills available in this session (name + description + file path). Skill bodies live on disk at the listed paths.\n- Trigger rules: If the user names a skill (with `$SkillName` or plain text) OR the task clearly matches a skill's description shown above, you must use that skill for that turn. Multiple mentions mean use them all. Do not carry skills across turns unless re-mentioned.\n- Missing/blocked: If a named skill isn't in the list or the path can't be read, say so briefly and continue with the best fallback.\n- How to use a skill (progressive disclosure):\n 1) After deciding to use a skill, open its `SKILL.md`. Read only enough to follow the workflow.\n 2) When `SKILL.md` references relative paths (e.g., `scripts/foo.py`), resolve them relative to the skill directory listed above first, and only consider other paths if needed.\n 3) If `SKILL.md` points to extra folders such as `references/`, load only the specific files needed for the request; don't bulk-load everything.\n 4) If `scripts/` exist, prefer running or patching them instead of retyping large code blocks.\n 5) If `assets/` or templates exist, reuse them instead of recreating from scratch.\n- Coordination and sequencing:\n - If multiple skills apply, choose the minimal set that covers the request and state the order you'll use them.\n - Announce which skill(s) you're using and why (one short line). If you skip an obvious skill, say why.\n- Context hygiene:\n - Keep context small: summarize long sections instead of pasting them; only load extra files when needed.\n - Avoid deep reference-chasing: prefer opening only files directly linked from `SKILL.md` unless you're blocked.\n - When variants exist (frameworks, providers, domains), pick only the relevant reference file(s) and note that choice.\n- Safety and fallback: If a skill can't be applied cleanly (missing files, unclear instructions), state the issue, pick the next-best approach, and continue.","truncation_policy":{"mode":"tokens","limit":10000}}} +{"timestamp":"2026-03-27T18:06:18.378Z","type":"event_msg","payload":{"type":"agent_reasoning","text":"**Locating ASCII changes**\n\nI need to change certain items to ASCII format. It’s also possible I want to add a script comment in val-2f.i with the symbol ∂. I’ll need to locate that requirement and make sure everything aligns. I’m curious how to best implement these changes, so I should double-check the script for any specific guidelines or rules I should follow. Alright, let's get started and find what I need!"}} +{"timestamp":"2026-03-27T18:06:18.378Z","type":"response_item","payload":{"type":"reasoning","summary":[{"type":"summary_text","text":"**Locating ASCII changes**\n\nI need to change certain items to ASCII format. It’s also possible I want to add a script comment in val-2f.i with the symbol ∂. I’ll need to locate that requirement and make sure everything aligns. I’m curious how to best implement these changes, so I should double-check the script for any specific guidelines or rules I should follow. Alright, let's get started and find what I need!"}],"content":null,"encrypted_content":"gAAAAABpxscactjnRYEjN6DoedKy0PXvLz07Vz3YOMkxGeHI6OO2ztAmbbrtPE1EJNKbUeEzdVIepRaXTVT5DzC8snxIg8-QBtBG4Xs9DbGcnYa9mZl6G2wxJMCKVzXRubZz_yyT2WDR4vVV9uhEnFw6ANEeMe_kdyS6yCkBuwFKTp5XaJPyKYSHQPqrDZ_xd-LvgjXEZ5SMt_ldeXlXWdm_Jcx3yjshLeMotNwwgfpQlZeW-Ba1SrUieSfa_mF7-YORUC3I_CkhmkxkUII02DRJKVJF-EjzhGiLe_Y-uJI6BRTB1wYlJ77hdt0aWR2dzLNeaAcN1eJLEwhlSeR7qGG4fse-drSBvJeZ59uWEDz789XpNId7u9U3OXkW3b5pq5eV61JBX-KIa0n2ka9ySJMtp5o49D9PiTJtQ3aW-Sp0antLb5o_S4oqbfPAu97tNNp8w_iuUsWKuGch93KLiJIcDJrgc6nMevhOtSOESnxWaIvaokj4LyYf6kjt3qt3CXDDd_phnw3ot_lEMLNIGW_UJvbVTVoEhHCqGOXN3jGn_Xp2rjW1KIIzYneSBwrJ6V-EOFVz0Uh-aD11EWAgTPLsWzb6DsR8ZeM7RLuq9EbRyzDcU03H0bllYnrddokh5weEFxYL7koqQbjWcibIBMx_3RfrvPAmV3kFAH0HMt08rQdpUuqZuGl4qCb7S3MzjIvcDkcYWzzM_At116aCIIafVC1yS7yNkME9r4lfoKiUughVEcDd9quJnPPFrkc2OesMB34nQ8TCW6iKnZm1Bihbp0kjbNZHLIdSvSb_JieiZUSefAlz04OLmKLud08c8hq1yNtpd1Q1DDZwC3lKdZTdfjWPVIdLXp4PVltYNBJlBE1LoDNwB7-GGUW3a9CaSg73IbmonWC5SsfrXZzXBOad-1NPVobUBa8f8iYzcXCaRSX6mNMwMML3j31nMqQabY2AIt2t6NXP"}} +{"timestamp":"2026-03-27T18:06:18.623Z","type":"response_item","payload":{"type":"function_call","name":"exec_command","arguments":"{\"cmd\":\"rg -n --pcre2 \\\"[^\\\\x00-\\\\x7F]\\\" src/nodal_kernels/ReleasingNodalKernelDimensionless.C src/nodal_kernels/TrappingNodalKernelDimensionless.C test/tests/val-2f/val-2f.i\",\"workdir\":\"/Users/lindad/projects/TMAP8\",\"max_output_tokens\":4000,\"yield_time_ms\":1000}","call_id":"call_2imJBr4jSCwiDpmWrfMYfHHZ"}} +{"timestamp":"2026-03-27T18:06:18.633Z","type":"event_msg","payload":{"type":"token_count","info":{"total_token_usage":{"input_tokens":96258,"cached_input_tokens":76032,"output_tokens":1611,"reasoning_output_tokens":331,"total_tokens":97869},"last_token_usage":{"input_tokens":22758,"cached_input_tokens":19712,"output_tokens":132,"reasoning_output_tokens":27,"total_tokens":22890},"model_context_window":258400},"rate_limits":{"limit_id":"codex","limit_name":null,"primary":{"used_percent":15.0,"window_minutes":300,"resets_at":1774643092},"secondary":{"used_percent":27.0,"window_minutes":10080,"resets_at":1774905636},"credits":null,"plan_type":"enterprise"}}} +{"timestamp":"2026-03-27T18:06:18.789Z","type":"response_item","payload":{"type":"function_call_output","call_id":"call_2imJBr4jSCwiDpmWrfMYfHHZ","output":"Chunk ID: 4f3dc0\nWall time: 0.0527 seconds\nProcess exited with code 0\nOriginal token count: 349\nOutput:\nsrc/nodal_kernels/ReleasingNodalKernelDimensionless.C:19: \"Ĉ_t = C_t / C_t_ref. \"\nsrc/nodal_kernels/ReleasingNodalKernelDimensionless.C:20: \"The residual R = +k_r_hat · exp(-E_r / T) · Ĉ_t is naturally O(k_r_hat) \"\nsrc/nodal_kernels/ReleasingNodalKernelDimensionless.C:21: \"because Ĉ_t is O(1). No equation scaling is applied.\");\nsrc/nodal_kernels/TrappingNodalKernelDimensionless.C:20: \"Ĉ_t = C_t / C_t_ref. \"\nsrc/nodal_kernels/TrappingNodalKernelDimensionless.C:34: \"Typically set to N * Ct0_max. The variable stores Ĉ_t = C_t / C_t_ref.\");\nsrc/nodal_kernels/TrappingNodalKernelDimensionless.C:39: \"Dimensionless trapped-concentration variables (Ĉ_t_j = C_t_j / C_t_ref_j) \"\nsrc/nodal_kernels/TrappingNodalKernelDimensionless.C:45: \"other_trapped_concentration_variables, used to convert Ĉ_t_j back to physical C_t_j \"\nsrc/nodal_kernels/TrappingNodalKernelDimensionless.C:100: // N * Ct0(x) - C_t_ref * Ĉ_t - sum_j C_t_ref_j * Ĉ_t_j\nsrc/nodal_kernels/TrappingNodalKernelDimensionless.C:124: // Other traps: dimensionless Ĉ_t_j, multiplied by C_t_ref_j to get physical units\nsrc/nodal_kernels/TrappingNodalKernelDimensionless.C:132: // This trap: variable is dimensionless Ĉ_t, multiply by C_t_ref to get physical\nsrc/nodal_kernels/TrappingNodalKernelDimensionless.C:137: // Mobile concentration in dimensionless form Ĉ_m\n"}} +{"timestamp":"2026-03-27T18:06:18.790Z","type":"turn_context","payload":{"turn_id":"019d3079-3ee6-7c93-a382-6cbfe9cff7d7","cwd":"/Users/lindad/projects/TMAP8","approval_policy":"on-request","sandbox_policy":{"type":"workspace-write","network_access":false,"exclude_tmpdir_env_var":false,"exclude_slash_tmp":false},"model":"gpt-5.4","personality":"pragmatic","collaboration_mode":{"mode":"default","settings":{"model":"gpt-5.4","reasoning_effort":"medium","developer_instructions":"# Collaboration Mode: Default\n\nYou are now in Default mode. Any previous instructions for other modes (e.g. Plan mode) are no longer active.\n\nYour active mode changes only when new developer instructions with a different `...` change it; user requests or tool descriptions do not change mode by themselves. Known mode names are Default and Plan.\n\n## request_user_input availability\n\nThe `request_user_input` tool is unavailable in Default mode. If you call it while in Default mode, it will return an error.\n\nIn Default mode, strongly prefer making reasonable assumptions and executing the user's request rather than stopping to ask questions. If you absolutely must ask a question because the answer cannot be discovered from local context and a reasonable assumption would be risky, ask the user directly with a concise plain-text question. Never write a multiple choice question as a textual assistant message.\n"}},"effort":"medium","summary":"auto","user_instructions":"# AGENTS.md\n\n## Environment\n- Ask the user if you need to load a MOOSE conda environment, and if so, what the name of the conda environment is\n- If `./tmap8-opt` or `run_tests` throws an error, stop and ask the user\n- Pre-commit hooks handle all formatting and input file validation on every `git commit` — do not invoke `clang-format`, `black`, or `hit format` manually\n- `moose/framework/contrib/hit/hit check .i` is available to validate input files during development — use it before committing\n\n## Before writing any code or input file\n- Browse `doc/content/` to understand documentation standards and existing patterns before starting work\n- Before writing a new C++ class, look through existing MOOSE classes in the codebase to confirm expected syntax and patterns\n- Documentation in `doc/content/` may not accurately reflect current code behavior — once you identify a class to use in an input file, find its C++ implementation and read it to confirm the class does what you expect before writing the input file\n\n## C++ code\n- Every new class requires a MOOSE TestHarness test in `test/tests/` before committing\n- Every new class requires a MooseDocs page following existing TMAP8 doc structure\n- Never hardcode physical parameters — first check if it is already defined in `doc/content/source/utils/TMAP8PhysicalConstants`, and if not available, expose everything through `addParam`\n- Code is unit-agnostic; units live in input files only\n\n## Input files\n- Before writing an input file, look through existing MOOSE and TMAP8 classes to confirm object names and parameter syntax\n- Use `moose/framework/contrib/hit/hit check .i` to validate before committing\n- Use `./tmap8-opt -i .i` to run input files\n- Write parameter values in the units the reference source used; use the MOOSE units system for conversion — the units system is self-documenting and does not require inline comments\n- State the unit system at the top of every input file in a comment block\n\n## Testing\n- Run tests only when `.C`, `.h`, or `test/tests/` files change\n- Run only the affected module: `./run_tests -j --re `\n\n## Session log\n- Every session must be associated with a GitHub issue on `idaholab/TMAP8`; ask the user for the issue number at the start of the session if one is not provided, or create one if the user instructs you to\n- **SQA requirement:** When creating a GitHub issue with `gh`, you must use the appropriate template from `.github/ISSUE_TEMPLATE/`; read the available templates first, select the one that fits (e.g. `bug-report.md` for bugs, `feature-request.md` for new features or tasks), and populate all sections in the template body — passing a bare description without following the template structure is not acceptable\n- Before committing, copy the current session's `.jsonl` file into `doc/content/agent//`. For Claude Code sessions the file is the most recently modified `.jsonl` under `~/.claude/projects//`; for Codex sessions check the equivalent Codex session directory. Do not remove old session files already in that directory — append the new one alongside them.\n\n## Committing\n- Commit at minimum after: every input file that successfully runs, every test that passes or fails, and every new class added\n- If a test or run failed, commit the failure state first (include the full error message in the commit body), then commit the fix separately\n- Every commit must reference the associated GitHub issue (e.g. `Refs #` or `Closes #` as appropriate) in the commit message\n- **Every commit must include an updated copy of the session `.jsonl`** — before staging, copy the current session file from `~/.claude/projects//.jsonl` to `doc/content/agent//` and stage it; this is a critical SQA requirement. Do not remove session files already present in that directory — if multiple Claude/Codex sessions contribute to the same branch and issue, all session files must be kept.\n- Every commit must include these trailers:\n```\nRefs #\nAI-assisted: true\nAI-model: \nAI-version: \nCo-Authored-By: \n```\n\n## Pull requests\n- If the linked issue already contains a complete Reason/Design/Impact description, the PR body should contain only the closing reference (e.g. `Closes #`) — do not duplicate the issue content or leave template sections empty\n- If the PR introduces physics/modeling decisions, non-obvious AI reasoning, or tests not described in the issue, add those as a short addendum below the issue reference\n- Never merge autonomously\n\n## Never do\n- Modify existing passing tests without explicit user instruction\n- Modify the build system without explicit user instruction\n- Make physics modeling decisions without flagging them to the user\n- Suppress or bypass test failures\n\n\n## Skills\nA skill is a set of local instructions to follow that is stored in a `SKILL.md` file. Below is the list of skills that can be used. Each entry includes a name, description, and file path so you can open the source for full instructions when using a specific skill.\n### Available skills\n- openai-docs: Use when the user asks how to build with OpenAI products or APIs and needs up-to-date official documentation with citations, help choosing the latest model for a use case, or explicit GPT-5.4 upgrade and prompt-upgrade guidance; prioritize OpenAI docs MCP tools, use bundled references only as helper context, and restrict any fallback browsing to official OpenAI domains. (file: /Users/lindad/.codex/skills/.system/openai-docs/SKILL.md)\n- plugin-creator: Create and scaffold plugin directories for Codex with a required `.codex-plugin/plugin.json`, optional plugin folders/files, and baseline placeholders you can edit before publishing or testing. Use when Codex needs to create a new local plugin, add optional plugin structure, or generate or update repo-root `.agents/plugins/marketplace.json` entries for plugin ordering and availability metadata. (file: /Users/lindad/.codex/skills/.system/plugin-creator/SKILL.md)\n- skill-creator: Guide for creating effective skills. This skill should be used when users want to create a new skill (or update an existing skill) that extends Codex's capabilities with specialized knowledge, workflows, or tool integrations. (file: /Users/lindad/.codex/skills/.system/skill-creator/SKILL.md)\n- skill-installer: Install Codex skills into $CODEX_HOME/skills from a curated list or a GitHub repo path. Use when a user asks to list installable skills, install a curated skill, or install a skill from another repo (including private repos). (file: /Users/lindad/.codex/skills/.system/skill-installer/SKILL.md)\n### How to use skills\n- Discovery: The list above is the skills available in this session (name + description + file path). Skill bodies live on disk at the listed paths.\n- Trigger rules: If the user names a skill (with `$SkillName` or plain text) OR the task clearly matches a skill's description shown above, you must use that skill for that turn. Multiple mentions mean use them all. Do not carry skills across turns unless re-mentioned.\n- Missing/blocked: If a named skill isn't in the list or the path can't be read, say so briefly and continue with the best fallback.\n- How to use a skill (progressive disclosure):\n 1) After deciding to use a skill, open its `SKILL.md`. Read only enough to follow the workflow.\n 2) When `SKILL.md` references relative paths (e.g., `scripts/foo.py`), resolve them relative to the skill directory listed above first, and only consider other paths if needed.\n 3) If `SKILL.md` points to extra folders such as `references/`, load only the specific files needed for the request; don't bulk-load everything.\n 4) If `scripts/` exist, prefer running or patching them instead of retyping large code blocks.\n 5) If `assets/` or templates exist, reuse them instead of recreating from scratch.\n- Coordination and sequencing:\n - If multiple skills apply, choose the minimal set that covers the request and state the order you'll use them.\n - Announce which skill(s) you're using and why (one short line). If you skip an obvious skill, say why.\n- Context hygiene:\n - Keep context small: summarize long sections instead of pasting them; only load extra files when needed.\n - Avoid deep reference-chasing: prefer opening only files directly linked from `SKILL.md` unless you're blocked.\n - When variants exist (frameworks, providers, domains), pick only the relevant reference file(s) and note that choice.\n- Safety and fallback: If a skill can't be applied cleanly (missing files, unclear instructions), state the issue, pick the next-best approach, and continue.","truncation_policy":{"mode":"tokens","limit":10000}}} +{"timestamp":"2026-03-27T18:06:23.448Z","type":"event_msg","payload":{"type":"agent_reasoning","text":"**Editing files for clarity**\n\nI need to make some edits to these files. I’m considering replacing “Ĉ_t” with “Ct_hat” or “C_t_hat” to preserve the meaning. It also looks like I should replace certain characters: for instance, “·” with “*,” “α” with “alpha,” and “Σ_j” with “sum_j.” I’ll switch “→” to “->,” bullets to hyphens, and em dashes to hyphens as well. Lastly, I need to locate the comment in the val-2f input."}} +{"timestamp":"2026-03-27T18:06:23.448Z","type":"response_item","payload":{"type":"reasoning","summary":[{"type":"summary_text","text":"**Editing files for clarity**\n\nI need to make some edits to these files. I’m considering replacing “Ĉ_t” with “Ct_hat” or “C_t_hat” to preserve the meaning. It also looks like I should replace certain characters: for instance, “·” with “*,” “α” with “alpha,” and “Σ_j” with “sum_j.” I’ll switch “→” to “->,” bullets to hyphens, and em dashes to hyphens as well. Lastly, I need to locate the comment in the val-2f input."}],"content":null,"encrypted_content":"gAAAAABpxscfFZ0ygH8I1FjLyBAIBz5ryncA0ZWlyNtCbet_7sF70KB_BL3SNWgufaedAO3hyu-iEvSzxSyfuab7pcYlBdLk73mrB1TFbgdjD7VwdeJQUjPp_JZZdhUZ9K_xGE5RnlUaUmH6ar341wp36S_TSgx4Y43u-J3cJqXXPf33MURRXwWAeZou_6mg7S93NT01qomkPI1MjNTCzGI94JexY-gZ0_1pQqef60eeWbWQFI7e8rwR20wwWoTwL-pATbLgYrZHCqEALcETu_p7cmK5mleYSx5JDWy0yjCFY5Cn73HNAf7o38VxYskm0v1RaC7GZHiy2MmDeIkL6O6sLc4rn_fl89ALAvVZKhTz9TDJaNBIcaqSm-lCbNBXRRaSuq4m8PueTmI70SyfshLhmggA8YMHrvbdzCy4lULvfYGoBcqwg31LHnZ6SnrFkxrGwJPk0nTbemz8Js57N1blNILlZylH7XfTNAhiGWHI_5IC_SxwGZpwnZst_OT8WWDL_L-_7mJ3PsbKYCziy7F2L_Sy2UQCPQlf-VUjUQ9727v4suriSaiW4hHTiQY9L1W2InFcduGySTPuqAiec6II1LUByNOf0QrUH5wPC-M-qF5BfZgtR7E_J1A2vDXj3fhpLi5T-vnvx3hMkB6UmXqOw8mCgdt2LI50_-FdX020zcq7ZyvuGxpMFZ0dz6vLU3iyVruxNJaPpssisbatWbZPuNzeggTEZN5bS5yh1LNJfOhAFoa8lLDQU2UclmljrQ07CFsj_LPjTGiOA6lsaVFUaqn5yF_qtasgpysdQ8qmkN2OwRmmTDoDCKiPt11RKZ7GKkI2g3AZ3UGiHTp6-yCmHNtrKKBaOChrZaxren8BVrs43BhAk0_J9KSAi_n6f_66Q3FfUpi8giDBEFZeQr0EO9B3nV3Tms5BE1NqzCt7KB0wOiZ4oQheRsJ5SpARFXgYL5sxk-j4nlThYYheUffT55O_iW4AlvFZ_baiGX0o70pdigp47NI9f1uX5FcIG1hR8sZFRWur-YfZdIWo9FlzeZ_aIKLel617xK3AVk4kWBtL2QsY2hB5d-4BTyncxHPPpTS2A19j5SoY8I3tkMSyM8GiRLaKkIqWdRHXcgP1fmEX8MLrvJ6oEj-PdLx-G1KXCLKTxSXy"}} +{"timestamp":"2026-03-27T18:06:23.506Z","type":"event_msg","payload":{"type":"agent_message","message":"I’ve narrowed it to five files. I’m replacing the accented/math symbols with ASCII equivalents like `Ct_hat`, `*`, `sum_j`, and `->`, keeping the text semantics intact and leaving behavior unchanged.","phase":"commentary"}} +{"timestamp":"2026-03-27T18:06:23.506Z","type":"response_item","payload":{"type":"message","role":"assistant","content":[{"type":"output_text","text":"I’ve narrowed it to five files. I’m replacing the accented/math symbols with ASCII equivalents like `Ct_hat`, `*`, `sum_j`, and `->`, keeping the text semantics intact and leaving behavior unchanged."}],"phase":"commentary"}} +{"timestamp":"2026-03-27T18:06:23.627Z","type":"response_item","payload":{"type":"function_call","name":"exec_command","arguments":"{\"cmd\":\"sed -n '1,80p' test/tests/val-2f/val-2f.i\",\"workdir\":\"/Users/lindad/projects/TMAP8\",\"max_output_tokens\":4000,\"yield_time_ms\":1000}","call_id":"call_S9sYWo4KvrVbBv3aLz3AQv7A"}} +{"timestamp":"2026-03-27T18:06:23.637Z","type":"event_msg","payload":{"type":"token_count","info":{"total_token_usage":{"input_tokens":119601,"cached_input_tokens":98816,"output_tokens":1795,"reasoning_output_tokens":396,"total_tokens":121396},"last_token_usage":{"input_tokens":23343,"cached_input_tokens":22784,"output_tokens":184,"reasoning_output_tokens":65,"total_tokens":23527},"model_context_window":258400},"rate_limits":{"limit_id":"codex","limit_name":null,"primary":{"used_percent":15.0,"window_minutes":300,"resets_at":1774643092},"secondary":{"used_percent":27.0,"window_minutes":10080,"resets_at":1774905636},"credits":null,"plan_type":"enterprise"}}} +{"timestamp":"2026-03-27T18:06:23.774Z","type":"response_item","payload":{"type":"function_call_output","call_id":"call_S9sYWo4KvrVbBv3aLz3AQv7A","output":"Chunk ID: 5fd9d6\nWall time: 0.0526 seconds\nProcess exited with code 0\nOriginal token count: 471\nOutput:\n# Validation Problem #2f\n# Self-damaged Tungsten Effects on Deuterium Transport extended from an original model from\n# Dark, J., Delaporte-Mathurin, R., Schwarz-Selinger, T., Hodille, E. A., Mougenot, J.,\n# Charles, Y., & Grisolia, C. (2024). Modelling neutron damage effects on tritium transport\n# in tungsten. Nuclear Fusion, 64(8), 086026.\n#\n# Unit system:\n# - length: micrometers (mum)\n# - time: seconds (s)\n# - concentration: at/mum^3\n# - inventory/flux outputs are rescaled to at/m^2 and at/m^2/s\n\n!include parameters_val-2f.params\n!include val-2f_trapping_intrinsic.i\n!include val-2f_trapping_5.i\n!include val-2f_trapping_4.i\n!include val-2f_trapping_3.i\n!include val-2f_trapping_2.i\n!include val-2f_trapping_1.i\n\n[Mesh]\n [cartesian_mesh]\n type = CartesianMeshGenerator\n dim = 1\n dx = '${dx1_hat} ${dx2_hat} ${dx3_hat} ${dx4_hat} ${dx5_hat}'\n ix = '${ix1} ${ix2} ${ix3} ${ix4} ${ix5}'\n subdomain_id = '0 0 0 0 0'\n []\n[]\n\n[Variables]\n [deuterium_concentration_W]\n []\n[]\n\n[AuxVariables]\n active = 'bounds_dummy temperature'\n [bounds_dummy]\n order = FIRST\n family = LAGRANGE\n []\n [temperature]\n initial_condition = ${temperature_initial}\n []\n[]\n\n[Bounds]\n [deuterium_concentration_lower_bound]\n type = ConstantBounds\n variable = bounds_dummy\n bounded_variable = deuterium_concentration_W\n bound_type = lower\n bound_value = 0\n []\n[]\n\n[Kernels]\n [time_W]\n type = TimeDerivative\n variable = deuterium_concentration_W\n []\n [diffusion_W]\n type = ADMatDiffusion\n variable = deuterium_concentration_W\n diffusivity = diffusivity_W\n []\n [source_deuterium]\n type = BodyForce\n variable = deuterium_concentration_W\n function = source_deuterium\n []\n[]\n\n[AuxKernels]\n [temperature_aux]\n type = FunctionAux\n variable = temperature\n function = temperature_bc_func\n execute_on = 'INITIAL LINEAR'\n []\n"}} +{"timestamp":"2026-03-27T18:06:23.774Z","type":"turn_context","payload":{"turn_id":"019d3079-3ee6-7c93-a382-6cbfe9cff7d7","cwd":"/Users/lindad/projects/TMAP8","approval_policy":"on-request","sandbox_policy":{"type":"workspace-write","network_access":false,"exclude_tmpdir_env_var":false,"exclude_slash_tmp":false},"model":"gpt-5.4","personality":"pragmatic","collaboration_mode":{"mode":"default","settings":{"model":"gpt-5.4","reasoning_effort":"medium","developer_instructions":"# Collaboration Mode: Default\n\nYou are now in Default mode. Any previous instructions for other modes (e.g. Plan mode) are no longer active.\n\nYour active mode changes only when new developer instructions with a different `...` change it; user requests or tool descriptions do not change mode by themselves. Known mode names are Default and Plan.\n\n## request_user_input availability\n\nThe `request_user_input` tool is unavailable in Default mode. If you call it while in Default mode, it will return an error.\n\nIn Default mode, strongly prefer making reasonable assumptions and executing the user's request rather than stopping to ask questions. If you absolutely must ask a question because the answer cannot be discovered from local context and a reasonable assumption would be risky, ask the user directly with a concise plain-text question. Never write a multiple choice question as a textual assistant message.\n"}},"effort":"medium","summary":"auto","user_instructions":"# AGENTS.md\n\n## Environment\n- Ask the user if you need to load a MOOSE conda environment, and if so, what the name of the conda environment is\n- If `./tmap8-opt` or `run_tests` throws an error, stop and ask the user\n- Pre-commit hooks handle all formatting and input file validation on every `git commit` — do not invoke `clang-format`, `black`, or `hit format` manually\n- `moose/framework/contrib/hit/hit check .i` is available to validate input files during development — use it before committing\n\n## Before writing any code or input file\n- Browse `doc/content/` to understand documentation standards and existing patterns before starting work\n- Before writing a new C++ class, look through existing MOOSE classes in the codebase to confirm expected syntax and patterns\n- Documentation in `doc/content/` may not accurately reflect current code behavior — once you identify a class to use in an input file, find its C++ implementation and read it to confirm the class does what you expect before writing the input file\n\n## C++ code\n- Every new class requires a MOOSE TestHarness test in `test/tests/` before committing\n- Every new class requires a MooseDocs page following existing TMAP8 doc structure\n- Never hardcode physical parameters — first check if it is already defined in `doc/content/source/utils/TMAP8PhysicalConstants`, and if not available, expose everything through `addParam`\n- Code is unit-agnostic; units live in input files only\n\n## Input files\n- Before writing an input file, look through existing MOOSE and TMAP8 classes to confirm object names and parameter syntax\n- Use `moose/framework/contrib/hit/hit check .i` to validate before committing\n- Use `./tmap8-opt -i .i` to run input files\n- Write parameter values in the units the reference source used; use the MOOSE units system for conversion — the units system is self-documenting and does not require inline comments\n- State the unit system at the top of every input file in a comment block\n\n## Testing\n- Run tests only when `.C`, `.h`, or `test/tests/` files change\n- Run only the affected module: `./run_tests -j --re `\n\n## Session log\n- Every session must be associated with a GitHub issue on `idaholab/TMAP8`; ask the user for the issue number at the start of the session if one is not provided, or create one if the user instructs you to\n- **SQA requirement:** When creating a GitHub issue with `gh`, you must use the appropriate template from `.github/ISSUE_TEMPLATE/`; read the available templates first, select the one that fits (e.g. `bug-report.md` for bugs, `feature-request.md` for new features or tasks), and populate all sections in the template body — passing a bare description without following the template structure is not acceptable\n- Before committing, copy the current session's `.jsonl` file into `doc/content/agent//`. For Claude Code sessions the file is the most recently modified `.jsonl` under `~/.claude/projects//`; for Codex sessions check the equivalent Codex session directory. Do not remove old session files already in that directory — append the new one alongside them.\n\n## Committing\n- Commit at minimum after: every input file that successfully runs, every test that passes or fails, and every new class added\n- If a test or run failed, commit the failure state first (include the full error message in the commit body), then commit the fix separately\n- Every commit must reference the associated GitHub issue (e.g. `Refs #` or `Closes #` as appropriate) in the commit message\n- **Every commit must include an updated copy of the session `.jsonl`** — before staging, copy the current session file from `~/.claude/projects//.jsonl` to `doc/content/agent//` and stage it; this is a critical SQA requirement. Do not remove session files already present in that directory — if multiple Claude/Codex sessions contribute to the same branch and issue, all session files must be kept.\n- Every commit must include these trailers:\n```\nRefs #\nAI-assisted: true\nAI-model: \nAI-version: \nCo-Authored-By: \n```\n\n## Pull requests\n- If the linked issue already contains a complete Reason/Design/Impact description, the PR body should contain only the closing reference (e.g. `Closes #`) — do not duplicate the issue content or leave template sections empty\n- If the PR introduces physics/modeling decisions, non-obvious AI reasoning, or tests not described in the issue, add those as a short addendum below the issue reference\n- Never merge autonomously\n\n## Never do\n- Modify existing passing tests without explicit user instruction\n- Modify the build system without explicit user instruction\n- Make physics modeling decisions without flagging them to the user\n- Suppress or bypass test failures\n\n\n## Skills\nA skill is a set of local instructions to follow that is stored in a `SKILL.md` file. Below is the list of skills that can be used. Each entry includes a name, description, and file path so you can open the source for full instructions when using a specific skill.\n### Available skills\n- openai-docs: Use when the user asks how to build with OpenAI products or APIs and needs up-to-date official documentation with citations, help choosing the latest model for a use case, or explicit GPT-5.4 upgrade and prompt-upgrade guidance; prioritize OpenAI docs MCP tools, use bundled references only as helper context, and restrict any fallback browsing to official OpenAI domains. (file: /Users/lindad/.codex/skills/.system/openai-docs/SKILL.md)\n- plugin-creator: Create and scaffold plugin directories for Codex with a required `.codex-plugin/plugin.json`, optional plugin folders/files, and baseline placeholders you can edit before publishing or testing. Use when Codex needs to create a new local plugin, add optional plugin structure, or generate or update repo-root `.agents/plugins/marketplace.json` entries for plugin ordering and availability metadata. (file: /Users/lindad/.codex/skills/.system/plugin-creator/SKILL.md)\n- skill-creator: Guide for creating effective skills. This skill should be used when users want to create a new skill (or update an existing skill) that extends Codex's capabilities with specialized knowledge, workflows, or tool integrations. (file: /Users/lindad/.codex/skills/.system/skill-creator/SKILL.md)\n- skill-installer: Install Codex skills into $CODEX_HOME/skills from a curated list or a GitHub repo path. Use when a user asks to list installable skills, install a curated skill, or install a skill from another repo (including private repos). (file: /Users/lindad/.codex/skills/.system/skill-installer/SKILL.md)\n### How to use skills\n- Discovery: The list above is the skills available in this session (name + description + file path). Skill bodies live on disk at the listed paths.\n- Trigger rules: If the user names a skill (with `$SkillName` or plain text) OR the task clearly matches a skill's description shown above, you must use that skill for that turn. Multiple mentions mean use them all. Do not carry skills across turns unless re-mentioned.\n- Missing/blocked: If a named skill isn't in the list or the path can't be read, say so briefly and continue with the best fallback.\n- How to use a skill (progressive disclosure):\n 1) After deciding to use a skill, open its `SKILL.md`. Read only enough to follow the workflow.\n 2) When `SKILL.md` references relative paths (e.g., `scripts/foo.py`), resolve them relative to the skill directory listed above first, and only consider other paths if needed.\n 3) If `SKILL.md` points to extra folders such as `references/`, load only the specific files needed for the request; don't bulk-load everything.\n 4) If `scripts/` exist, prefer running or patching them instead of retyping large code blocks.\n 5) If `assets/` or templates exist, reuse them instead of recreating from scratch.\n- Coordination and sequencing:\n - If multiple skills apply, choose the minimal set that covers the request and state the order you'll use them.\n - Announce which skill(s) you're using and why (one short line). If you skip an obvious skill, say why.\n- Context hygiene:\n - Keep context small: summarize long sections instead of pasting them; only load extra files when needed.\n - Avoid deep reference-chasing: prefer opening only files directly linked from `SKILL.md` unless you're blocked.\n - When variants exist (frameworks, providers, domains), pick only the relevant reference file(s) and note that choice.\n- Safety and fallback: If a skill can't be applied cleanly (missing files, unclear instructions), state the issue, pick the next-best approach, and continue.","truncation_policy":{"mode":"tokens","limit":10000}}} +{"timestamp":"2026-03-27T18:06:27.603Z","type":"event_msg","payload":{"type":"agent_reasoning","text":"**Inspecting code line**\n\nI need to locate line 164, and I’m wondering if I should check another file without any issues. It seems like `rg` showed something for `val-2f.i` on line 164, although it might be different. Let’s carefully inspect the code around there to get a clearer understanding. I want to make sure I'm thorough in this process."}} +{"timestamp":"2026-03-27T18:06:27.603Z","type":"response_item","payload":{"type":"reasoning","summary":[{"type":"summary_text","text":"**Inspecting code line**\n\nI need to locate line 164, and I’m wondering if I should check another file without any issues. It seems like `rg` showed something for `val-2f.i` on line 164, although it might be different. Let’s carefully inspect the code around there to get a clearer understanding. I want to make sure I'm thorough in this process."}],"content":null,"encrypted_content":"gAAAAABpxscj9zkult9sKo06M6t5W0pxW3zPUWamzVnUY6nKCdcPzTDTWr6ErUQapB147ySGFEEFJL27qXziMSTwmK4OnLqn8k10KcQRlkBu_6_nLxhV9bw0QTNAx6DpFOfKbvAiZbbyVpEwjjiUIH40fo1qZ49vHYzS4eqSsMwNuii7UtxI8DMyNPAg4shm-jzOLd_6xGQ0cz3xAVElH0g7UljGFW4oIBRDASbuiXyScXfDWF-rwJ5lsJofqnCin6LnSH20qpuh9pu9C1eRJjyH22cbR4DKooydhQ-LMlHuxxdR0scwhqGslQPDwM8kBW95ZQijna2efrrndsNDdGLQ5ur6HynFDzq4qQwoi9wdCK021MhaqkHZeWA_2xGCwUMAZVojjk-zofxYoYeOrETv2YoIJmyK_B2HyFC14P2hI-G8i9StGfHAr1QGQb4zeR_ioIxFO_sDIhH8RnWK7tIbYMHY8ipz-M-CPLNE2zcCkuBoXo_X9uBFavOpA_B9fmrL412c2FnczK-1yQnV9YDDhLxDMwhY65psENEFvD8lSJ3AHwZGxYb_3qoYDOHRG3bMmxUEDVBLHNhvI8PhmWgwEHk9cBKib-o7Q_DleNj8E5fI0JyHnr98PSjQFM7eget7eYLkRjKGhVR7kINGZOX80IMqAVVBu9oSPIa4Najgbhildtwib-zgUIsgNqAFh7iacrZ_x_Ft1NxVN34nEhYJrve7OVvzydVYEzVUjOPJ5oorlO2QBNVnys46jt2RYIH1Je6Mqc37kz_WN2LwWHsrRjPClK3MtdGDA7Ew3E-lAMLLBzYp6h8Nu3XXOxeYH9-RxHbzexk2i0eccipgzS7L9HIB3uDgZ-AV-EqJT487UdV15_PST4C3HEL9B1cnuOeSeVroNuZwV2M4_mvtxeQsEGC0xOHKpqYfIG1uH3PZDpKwFWOTh2lNbYQBFcTRuOPqbcqHxqmYMwgd7MIPZlmV0RBmqx5Qfg=="}} +{"timestamp":"2026-03-27T18:06:27.720Z","type":"response_item","payload":{"type":"function_call","name":"exec_command","arguments":"{\"cmd\":\"sed -n '150,180p' test/tests/val-2f/val-2f.i\",\"workdir\":\"/Users/lindad/projects/TMAP8\",\"max_output_tokens\":2000,\"yield_time_ms\":1000}","call_id":"call_SZiaeNM0v32kFhh0onScLbc0"}} +{"timestamp":"2026-03-27T18:06:27.727Z","type":"event_msg","payload":{"type":"token_count","info":{"total_token_usage":{"input_tokens":143749,"cached_input_tokens":122240,"output_tokens":1895,"reasoning_output_tokens":428,"total_tokens":145644},"last_token_usage":{"input_tokens":24148,"cached_input_tokens":23424,"output_tokens":100,"reasoning_output_tokens":32,"total_tokens":24248},"model_context_window":258400},"rate_limits":{"limit_id":"codex","limit_name":null,"primary":{"used_percent":15.0,"window_minutes":300,"resets_at":1774643092},"secondary":{"used_percent":27.0,"window_minutes":10080,"resets_at":1774905636},"credits":null,"plan_type":"enterprise"}}} +{"timestamp":"2026-03-27T18:06:27.886Z","type":"response_item","payload":{"type":"function_call_output","call_id":"call_SZiaeNM0v32kFhh0onScLbc0","output":"Chunk ID: 590f04\nWall time: 0.0527 seconds\nProcess exited with code 0\nOriginal token count: 431\nOutput:\n []\n [max_dt_size_function_inf]\n type = ParsedFunction\n expression = 'if(t<${fparse 5 / time_reference}, ${fparse 1e-2 / time_reference},\n if(t<${fparse 8 / time_reference}, ${fparse 1e2 / time_reference},\n if(t<${fparse 12 / time_reference}, ${fparse 1e-2 / time_reference},\n if(t<${fparse 20 / time_reference}, ${fparse 1e2 / time_reference},\n if(t<${fparse 35 / time_reference}, ${fparse 1e-2 / time_reference},\n if(t<${fparse 450 / time_reference}, ${fparse 1e2 / time_reference},\n if(t<${fparse 5000 / time_reference}, ${fparse 1e1 / time_reference},\n if(t<${fparse 11000 / time_reference}, ${fparse 1e2 / time_reference},\n if(t<${fparse 13000 / time_reference}, ${fparse 1e1 / time_reference},\n if(t<${fparse (charge_time + cooldown_duration + 4500) / time_reference}, ${fparse 1e2 / time_reference},\n if(t<${fparse 315000 / time_reference}, ${fparse 1e1 / time_reference}, ${fparse 1e3 / time_reference})))))))))))'\n []\n [max_dt_size_function_coarse]\n type = ParsedFunction\n expression = 'if(t<${fparse 1e-1 / time_reference}, ${fparse 1e4 / time_reference}, ${fparse 1e5 / time_reference})'\n []\n[]\n\n[Materials]\n active = 'diffusivity_W_func diffusivity_nonAD recombination_rate_surface flux_recombination_surface'\n [diffusivity_W_func]\n type = ADDerivativeParsedMaterial\n property_name = 'diffusivity_W'\n functor_names = 'temperature_bc_func'\n functor_symbols = 'temperature'\n expression = '${diffusion_W_preexponential_hat} * exp(- ${diffusion_W_energy} / ${kb_eV} / temperature)'\n []\n [diffusivity_nonAD]\n"}} +{"timestamp":"2026-03-27T18:06:27.890Z","type":"turn_context","payload":{"turn_id":"019d3079-3ee6-7c93-a382-6cbfe9cff7d7","cwd":"/Users/lindad/projects/TMAP8","approval_policy":"on-request","sandbox_policy":{"type":"workspace-write","network_access":false,"exclude_tmpdir_env_var":false,"exclude_slash_tmp":false},"model":"gpt-5.4","personality":"pragmatic","collaboration_mode":{"mode":"default","settings":{"model":"gpt-5.4","reasoning_effort":"medium","developer_instructions":"# Collaboration Mode: Default\n\nYou are now in Default mode. Any previous instructions for other modes (e.g. Plan mode) are no longer active.\n\nYour active mode changes only when new developer instructions with a different `...` change it; user requests or tool descriptions do not change mode by themselves. Known mode names are Default and Plan.\n\n## request_user_input availability\n\nThe `request_user_input` tool is unavailable in Default mode. If you call it while in Default mode, it will return an error.\n\nIn Default mode, strongly prefer making reasonable assumptions and executing the user's request rather than stopping to ask questions. If you absolutely must ask a question because the answer cannot be discovered from local context and a reasonable assumption would be risky, ask the user directly with a concise plain-text question. Never write a multiple choice question as a textual assistant message.\n"}},"effort":"medium","summary":"auto","user_instructions":"# AGENTS.md\n\n## Environment\n- Ask the user if you need to load a MOOSE conda environment, and if so, what the name of the conda environment is\n- If `./tmap8-opt` or `run_tests` throws an error, stop and ask the user\n- Pre-commit hooks handle all formatting and input file validation on every `git commit` — do not invoke `clang-format`, `black`, or `hit format` manually\n- `moose/framework/contrib/hit/hit check .i` is available to validate input files during development — use it before committing\n\n## Before writing any code or input file\n- Browse `doc/content/` to understand documentation standards and existing patterns before starting work\n- Before writing a new C++ class, look through existing MOOSE classes in the codebase to confirm expected syntax and patterns\n- Documentation in `doc/content/` may not accurately reflect current code behavior — once you identify a class to use in an input file, find its C++ implementation and read it to confirm the class does what you expect before writing the input file\n\n## C++ code\n- Every new class requires a MOOSE TestHarness test in `test/tests/` before committing\n- Every new class requires a MooseDocs page following existing TMAP8 doc structure\n- Never hardcode physical parameters — first check if it is already defined in `doc/content/source/utils/TMAP8PhysicalConstants`, and if not available, expose everything through `addParam`\n- Code is unit-agnostic; units live in input files only\n\n## Input files\n- Before writing an input file, look through existing MOOSE and TMAP8 classes to confirm object names and parameter syntax\n- Use `moose/framework/contrib/hit/hit check .i` to validate before committing\n- Use `./tmap8-opt -i .i` to run input files\n- Write parameter values in the units the reference source used; use the MOOSE units system for conversion — the units system is self-documenting and does not require inline comments\n- State the unit system at the top of every input file in a comment block\n\n## Testing\n- Run tests only when `.C`, `.h`, or `test/tests/` files change\n- Run only the affected module: `./run_tests -j --re `\n\n## Session log\n- Every session must be associated with a GitHub issue on `idaholab/TMAP8`; ask the user for the issue number at the start of the session if one is not provided, or create one if the user instructs you to\n- **SQA requirement:** When creating a GitHub issue with `gh`, you must use the appropriate template from `.github/ISSUE_TEMPLATE/`; read the available templates first, select the one that fits (e.g. `bug-report.md` for bugs, `feature-request.md` for new features or tasks), and populate all sections in the template body — passing a bare description without following the template structure is not acceptable\n- Before committing, copy the current session's `.jsonl` file into `doc/content/agent//`. For Claude Code sessions the file is the most recently modified `.jsonl` under `~/.claude/projects//`; for Codex sessions check the equivalent Codex session directory. Do not remove old session files already in that directory — append the new one alongside them.\n\n## Committing\n- Commit at minimum after: every input file that successfully runs, every test that passes or fails, and every new class added\n- If a test or run failed, commit the failure state first (include the full error message in the commit body), then commit the fix separately\n- Every commit must reference the associated GitHub issue (e.g. `Refs #` or `Closes #` as appropriate) in the commit message\n- **Every commit must include an updated copy of the session `.jsonl`** — before staging, copy the current session file from `~/.claude/projects//.jsonl` to `doc/content/agent//` and stage it; this is a critical SQA requirement. Do not remove session files already present in that directory — if multiple Claude/Codex sessions contribute to the same branch and issue, all session files must be kept.\n- Every commit must include these trailers:\n```\nRefs #\nAI-assisted: true\nAI-model: \nAI-version: \nCo-Authored-By: \n```\n\n## Pull requests\n- If the linked issue already contains a complete Reason/Design/Impact description, the PR body should contain only the closing reference (e.g. `Closes #`) — do not duplicate the issue content or leave template sections empty\n- If the PR introduces physics/modeling decisions, non-obvious AI reasoning, or tests not described in the issue, add those as a short addendum below the issue reference\n- Never merge autonomously\n\n## Never do\n- Modify existing passing tests without explicit user instruction\n- Modify the build system without explicit user instruction\n- Make physics modeling decisions without flagging them to the user\n- Suppress or bypass test failures\n\n\n## Skills\nA skill is a set of local instructions to follow that is stored in a `SKILL.md` file. Below is the list of skills that can be used. Each entry includes a name, description, and file path so you can open the source for full instructions when using a specific skill.\n### Available skills\n- openai-docs: Use when the user asks how to build with OpenAI products or APIs and needs up-to-date official documentation with citations, help choosing the latest model for a use case, or explicit GPT-5.4 upgrade and prompt-upgrade guidance; prioritize OpenAI docs MCP tools, use bundled references only as helper context, and restrict any fallback browsing to official OpenAI domains. (file: /Users/lindad/.codex/skills/.system/openai-docs/SKILL.md)\n- plugin-creator: Create and scaffold plugin directories for Codex with a required `.codex-plugin/plugin.json`, optional plugin folders/files, and baseline placeholders you can edit before publishing or testing. Use when Codex needs to create a new local plugin, add optional plugin structure, or generate or update repo-root `.agents/plugins/marketplace.json` entries for plugin ordering and availability metadata. (file: /Users/lindad/.codex/skills/.system/plugin-creator/SKILL.md)\n- skill-creator: Guide for creating effective skills. This skill should be used when users want to create a new skill (or update an existing skill) that extends Codex's capabilities with specialized knowledge, workflows, or tool integrations. (file: /Users/lindad/.codex/skills/.system/skill-creator/SKILL.md)\n- skill-installer: Install Codex skills into $CODEX_HOME/skills from a curated list or a GitHub repo path. Use when a user asks to list installable skills, install a curated skill, or install a skill from another repo (including private repos). (file: /Users/lindad/.codex/skills/.system/skill-installer/SKILL.md)\n### How to use skills\n- Discovery: The list above is the skills available in this session (name + description + file path). Skill bodies live on disk at the listed paths.\n- Trigger rules: If the user names a skill (with `$SkillName` or plain text) OR the task clearly matches a skill's description shown above, you must use that skill for that turn. Multiple mentions mean use them all. Do not carry skills across turns unless re-mentioned.\n- Missing/blocked: If a named skill isn't in the list or the path can't be read, say so briefly and continue with the best fallback.\n- How to use a skill (progressive disclosure):\n 1) After deciding to use a skill, open its `SKILL.md`. Read only enough to follow the workflow.\n 2) When `SKILL.md` references relative paths (e.g., `scripts/foo.py`), resolve them relative to the skill directory listed above first, and only consider other paths if needed.\n 3) If `SKILL.md` points to extra folders such as `references/`, load only the specific files needed for the request; don't bulk-load everything.\n 4) If `scripts/` exist, prefer running or patching them instead of retyping large code blocks.\n 5) If `assets/` or templates exist, reuse them instead of recreating from scratch.\n- Coordination and sequencing:\n - If multiple skills apply, choose the minimal set that covers the request and state the order you'll use them.\n - Announce which skill(s) you're using and why (one short line). If you skip an obvious skill, say why.\n- Context hygiene:\n - Keep context small: summarize long sections instead of pasting them; only load extra files when needed.\n - Avoid deep reference-chasing: prefer opening only files directly linked from `SKILL.md` unless you're blocked.\n - When variants exist (frameworks, providers, domains), pick only the relevant reference file(s) and note that choice.\n- Safety and fallback: If a skill can't be applied cleanly (missing files, unclear instructions), state the issue, pick the next-best approach, and continue.","truncation_policy":{"mode":"tokens","limit":10000}}} +{"timestamp":"2026-03-27T18:06:32.002Z","type":"event_msg","payload":{"type":"agent_reasoning","text":"**Considering patching files**\n\nI'm realizing that line 164 might not contain any non-ASCII characters. It seems like the context has shifted with the addition of lines later on. The command is now limited to specific files and doesn't include val-2f anymore. I need to check the input files for any non-ASCII characters. Alright, so it sounds like I might need to apply patches to four or maybe five files, including source and species. Let's patch those!"}} +{"timestamp":"2026-03-27T18:06:32.003Z","type":"response_item","payload":{"type":"reasoning","summary":[{"type":"summary_text","text":"**Considering patching files**\n\nI'm realizing that line 164 might not contain any non-ASCII characters. It seems like the context has shifted with the addition of lines later on. The command is now limited to specific files and doesn't include val-2f anymore. I need to check the input files for any non-ASCII characters. Alright, so it sounds like I might need to apply patches to four or maybe five files, including source and species. Let's patch those!"}],"content":null,"encrypted_content":"gAAAAABpxscoMDPSldLxGcqNcjd97IwJczHW-bqyXaGWxP72r6ONrrwVr0dpJ16CrQPIa1QrplCtkUg0wOR5Axm0GFkDmYGy_mW6G9xaeHYmMRM4jg4VBpTL60gIPWT-_Q-6SnXT4JOolicQg67ADA41JqWdE3cVOhsDUYhMZMwTkkbxgZk5yfzGv1qhmrXvSw8s66_RCPY0UeoSzhi-0sQXhT9aoVbNX_UuIZxpxe1NG1AS-yPkRDuP17zU_WJS15on131vhcLacNe8G3D7uJKHPgs0RW-AxCp9Rd-JjoHNNjIT8RNGQjj_YxRfVnh0i0PZugWbhhuh_GGHL2kFmP1yRbiTcvJeuYOr0XJ_EJXXsoutSl6KfiOjBlxD94i26fpzRVFZLawosZEVXsK5SJ29PEbEq4j5bIBVTxFaCwTj8CFwvZOG2_ui19WbrZB0rneKOVnJbmzlTYCrf6WrDWZUBO97aG5mlXDRBYQ3Q5EjNztVJtASPgxWE7ufQr83AHP0l50WCZcqcOAlCGSGU3R42D7hS_J8Rg6N_tQRFG4T02lkH4RK4S2lYYGNGkeTA4A6ngTSOh2S_VpKcO86whA-K9EARyOa-sTrARuJpM2RN2FdOMDwa4z1SaMGLIzNY4ZaGPQ02OGgJsr1ZGniuWyzHDg14pqdKEt-h8E6c3ifXEXZU0NrZIOed2ETzqS3TiuGZtMXYCiehGZREqToQEcDlvcYCEpxMD8O9XRjfOTz-HbpsS4kkeN2tpwv_MMRWKlLmg56b2Oj32fnE9IuSWnoYm_Zx7KLgMy89pYsCGd2JdYFBVlfvL27j53Ro8OXP-X3zVo7lkE9XitRDIfPXO2LPq_-sS8XtHhM_7AGprhp52r5uMw50AKJpPh10M2m7zH6AhmIzIg2UC_jUbJoNuXPoFm795F5wZzCIamUyP1C8t-V1l-6fnvuJwufLIjFcIUdOBItJmdV_SVja5l_GTzDA0R7yLOaicKRurg3rFNt1bBPamkZ2PDbBrvAoW8mZjolbPtsESxgKvp7V809E6Gblj6MHcrMvn8H5BYVL2iCNZtSrjWCfuwSCEWqGf_2UqSrzAHMl-QU1GKstG-6_8V9z5ox24OMkJdot0T_vpx6pcXdkRwZYS3jHo_n7r22l1jO_rr6kBzVLjCPtx8QFQ-ZfroN0gO-ow=="}} +{"timestamp":"2026-03-27T18:07:00.132Z","type":"response_item","payload":{"type":"custom_tool_call","status":"completed","call_id":"call_ClYL10FaXZza5JHYZnqY7n1O","name":"apply_patch","input":"*** Begin Patch\n*** Update File: /Users/lindad/projects/TMAP8/include/nodal_kernels/ReleasingNodalKernelDimensionless.h\n@@\n- * Ĉ_t = C_t / C_t_ref.\n+ * Ct_hat = C_t / C_t_ref.\n@@\n- * R = +k_r_hat · exp(-E_r / T) · Ĉ_t\n+ * R = +k_r_hat * exp(-E_r / T) * Ct_hat\n@@\n- * where k_r_hat = t_ref · α_r.\n+ * where k_r_hat = t_ref * alpha_r.\n@@\n- * This is trivially dimensionless (O(k_r_hat)) because Ĉ_t is O(1).\n+ * This is trivially dimensionless (O(k_r_hat)) because Ct_hat is O(1).\n*** Update File: /Users/lindad/projects/TMAP8/include/nodal_kernels/TrappingNodalKernelDimensionless.h\n@@\n- * Ĉ_t = C_t / C_t_ref, where C_t_ref is the trap concentration reference scale.\n+ * Ct_hat = C_t / C_t_ref, where C_t_ref is the trap concentration reference scale.\n@@\n- * R = -k_t_hat · exp(-E_t / T) · ((N·Ct0 - C_t_ref·Ĉ_t - Σ_j C_t_j) / C_t_ref) · Ĉ_m\n+ * R = -k_t_hat * exp(-E_t / T) * ((N * Ct0 - C_t_ref * Ct_hat - sum_j C_t_j) / C_t_ref) *\n+ * Cm_hat\n@@\n- * - Ĉ_t = dimensionless variable (this kernel's variable), O(1)\n- * - Ĉ_m = dimensionless mobile concentration. The coupled variable may be either physical\n+ * - Ct_hat = dimensionless variable (this kernel's variable), O(1)\n+ * - Cm_hat = dimensionless mobile concentration. The coupled variable may be either physical\n@@\n- * - C_t_j = C_t_ref_j * Ĉ_t_j, other trap species (dimensionless variable + reference, optional)\n+ * - C_t_j = C_t_ref_j * Ct_hat_j, other trap species (dimensionless variable + reference,\n+ * optional)\n@@\n- * - k_t_hat = t_ref · α_t · C_m_ref / N\n+ * - k_t_hat = t_ref * alpha_t * C_m_ref / N\n@@\n- /// C_t_ref: reference concentration for THIS trap (used to convert Ĉ_t back to physical)\n+ /// C_t_ref: reference concentration for THIS trap (used to convert Ct_hat back to physical)\n@@\n- /// Dimensionless concentrations of other trap types (Ĉ_t_j = C_t_j / C_t_ref_j)\n+ /// Dimensionless concentrations of other trap types (Ct_hat_j = C_t_j / C_t_ref_j)\n@@\n- /// Reference concentrations C_t_ref_j for each other trap, to convert Ĉ_t_j → physical C_t_j\n+ /// Reference concentrations C_t_ref_j for each other trap, to convert Ct_hat_j -> physical\n+ /// C_t_j\n*** Update File: /Users/lindad/projects/TMAP8/src/nodal_kernels/ReleasingNodalKernelDimensionless.C\n@@\n params.addClassDescription(\n \"Implements the release source term for a dimensionless trapped-species variable \"\n- \"Ĉ_t = C_t / C_t_ref. \"\n- \"The residual R = +k_r_hat · exp(-E_r / T) · Ĉ_t is naturally O(k_r_hat) \"\n- \"because Ĉ_t is O(1). No equation scaling is applied.\");\n+ \"Ct_hat = C_t / C_t_ref. \"\n+ \"The residual R = +k_r_hat * exp(-E_r / T) * Ct_hat is naturally O(k_r_hat) \"\n+ \"because Ct_hat is O(1). No equation scaling is applied.\");\n*** Update File: /Users/lindad/projects/TMAP8/src/nodal_kernels/TrappingNodalKernelDimensionless.C\n@@\n params.addClassDescription(\n \"Implements the trapping source term for a dimensionless trapped-species variable \"\n- \"Ĉ_t = C_t / C_t_ref. \"\n+ \"Ct_hat = C_t / C_t_ref. \"\n \"The mobile concentration may be either physical or dimensionless. \"\n \"No equation scaling is applied; the residual is O(k_t_hat).\");\n@@\n \"trap_concentration_reference\",\n \"Reference concentration C_t_ref for this trap species (same units as N). \"\n- \"Typically set to N * Ct0_max. The variable stores Ĉ_t = C_t / C_t_ref.\");\n+ \"Typically set to N * Ct0_max. The variable stores Ct_hat = C_t / C_t_ref.\");\n params.addRequiredCoupledVar(\n \"mobile_concentration\",\n \"The variable representing the dimensionless mobile concentration of solute particles.\");\n params.addCoupledVar(\"other_trapped_concentration_variables\",\n- \"Dimensionless trapped-concentration variables (Ĉ_t_j = C_t_j / C_t_ref_j) \"\n+ \"Dimensionless trapped-concentration variables (Ct_hat_j = C_t_j / \"\n+ \"C_t_ref_j) \"\n \"for other trap species that compete for the same trapping sites.\");\n params.addParam>(\n \"other_trap_concentration_references\",\n {},\n \"Reference concentrations C_t_ref_j for each variable listed in \"\n- \"other_trapped_concentration_variables, used to convert Ĉ_t_j back to physical C_t_j \"\n+ \"other_trapped_concentration_variables, used to convert Ct_hat_j back to physical C_t_j \"\n \"when computing available trapping sites. Must match in length.\");\n@@\n- // N * Ct0(x) - C_t_ref * Ĉ_t - sum_j C_t_ref_j * Ĉ_t_j\n+ // N * Ct0(x) - C_t_ref * Ct_hat - sum_j C_t_ref_j * Ct_hat_j\n@@\n- // Other traps: dimensionless Ĉ_t_j, multiplied by C_t_ref_j to get physical units\n+ // Other traps: dimensionless Ct_hat_j, multiplied by C_t_ref_j to get physical units\n@@\n- // This trap: variable is dimensionless Ĉ_t, multiply by C_t_ref to get physical\n+ // This trap: variable is dimensionless Ct_hat, multiply by C_t_ref to get physical\n@@\n- // Mobile concentration in dimensionless form Ĉ_m\n+ // Mobile concentration in dimensionless form Cm_hat\n*** Update File: /Users/lindad/projects/TMAP8/src/physics/SpeciesTrappingPhysics.C\n@@\n- // Time derivative — plain TimeDerivativeNodalKernel suffices for both paths:\n- // • dimensionless path: variable IS Ĉ_t (O(1)), so dĈ_t/dt is correct as-is\n- // • physical path: variable IS C_t, no per-row scaling is applied here\n+ // Time derivative: plain TimeDerivativeNodalKernel suffices for both paths:\n+ // - dimensionless path: variable is Ct_hat (O(1)), so dCt_hat/dt is correct as-is\n+ // - physical path: variable is C_t, no per-row scaling is applied here\n@@\n- // dimensionless kernel can convert Ĉ_t_j → physical C_t_j.\n+ // dimensionless kernel can convert Ct_hat_j -> physical C_t_j.\n@@\n- // Dimensionless path: add (C_t_ref_i / C_m_ref) * dĈ_t_i/dt.\n+ // Dimensionless path: add (C_t_ref_i / C_m_ref) * dCt_hat_i/dt.\n*** End Patch\n"}} +{"timestamp":"2026-03-27T18:07:00.237Z","type":"event_msg","payload":{"type":"token_count","info":{"total_token_usage":{"input_tokens":168529,"cached_input_tokens":146432,"output_tokens":3660,"reasoning_output_tokens":493,"total_tokens":172189},"last_token_usage":{"input_tokens":24780,"cached_input_tokens":24192,"output_tokens":1765,"reasoning_output_tokens":65,"total_tokens":26545},"model_context_window":258400},"rate_limits":{"limit_id":"codex","limit_name":null,"primary":{"used_percent":15.0,"window_minutes":300,"resets_at":1774643092},"secondary":{"used_percent":27.0,"window_minutes":10080,"resets_at":1774905636},"credits":null,"plan_type":"enterprise"}}} +{"timestamp":"2026-03-27T18:07:00.518Z","type":"response_item","payload":{"type":"custom_tool_call_output","call_id":"call_ClYL10FaXZza5JHYZnqY7n1O","output":"{\"output\":\"Success. Updated the following files:\\nM /Users/lindad/projects/TMAP8/include/nodal_kernels/ReleasingNodalKernelDimensionless.h\\nM /Users/lindad/projects/TMAP8/include/nodal_kernels/TrappingNodalKernelDimensionless.h\\nM /Users/lindad/projects/TMAP8/src/nodal_kernels/ReleasingNodalKernelDimensionless.C\\nM /Users/lindad/projects/TMAP8/src/nodal_kernels/TrappingNodalKernelDimensionless.C\\nM /Users/lindad/projects/TMAP8/src/physics/SpeciesTrappingPhysics.C\\n\",\"metadata\":{\"exit_code\":0,\"duration_seconds\":0.1}}"}} +{"timestamp":"2026-03-27T18:07:00.613Z","type":"turn_context","payload":{"turn_id":"019d3079-3ee6-7c93-a382-6cbfe9cff7d7","cwd":"/Users/lindad/projects/TMAP8","approval_policy":"on-request","sandbox_policy":{"type":"workspace-write","network_access":false,"exclude_tmpdir_env_var":false,"exclude_slash_tmp":false},"model":"gpt-5.4","personality":"pragmatic","collaboration_mode":{"mode":"default","settings":{"model":"gpt-5.4","reasoning_effort":"medium","developer_instructions":"# Collaboration Mode: Default\n\nYou are now in Default mode. Any previous instructions for other modes (e.g. Plan mode) are no longer active.\n\nYour active mode changes only when new developer instructions with a different `...` change it; user requests or tool descriptions do not change mode by themselves. Known mode names are Default and Plan.\n\n## request_user_input availability\n\nThe `request_user_input` tool is unavailable in Default mode. If you call it while in Default mode, it will return an error.\n\nIn Default mode, strongly prefer making reasonable assumptions and executing the user's request rather than stopping to ask questions. If you absolutely must ask a question because the answer cannot be discovered from local context and a reasonable assumption would be risky, ask the user directly with a concise plain-text question. Never write a multiple choice question as a textual assistant message.\n"}},"effort":"medium","summary":"auto","user_instructions":"# AGENTS.md\n\n## Environment\n- Ask the user if you need to load a MOOSE conda environment, and if so, what the name of the conda environment is\n- If `./tmap8-opt` or `run_tests` throws an error, stop and ask the user\n- Pre-commit hooks handle all formatting and input file validation on every `git commit` — do not invoke `clang-format`, `black`, or `hit format` manually\n- `moose/framework/contrib/hit/hit check .i` is available to validate input files during development — use it before committing\n\n## Before writing any code or input file\n- Browse `doc/content/` to understand documentation standards and existing patterns before starting work\n- Before writing a new C++ class, look through existing MOOSE classes in the codebase to confirm expected syntax and patterns\n- Documentation in `doc/content/` may not accurately reflect current code behavior — once you identify a class to use in an input file, find its C++ implementation and read it to confirm the class does what you expect before writing the input file\n\n## C++ code\n- Every new class requires a MOOSE TestHarness test in `test/tests/` before committing\n- Every new class requires a MooseDocs page following existing TMAP8 doc structure\n- Never hardcode physical parameters — first check if it is already defined in `doc/content/source/utils/TMAP8PhysicalConstants`, and if not available, expose everything through `addParam`\n- Code is unit-agnostic; units live in input files only\n\n## Input files\n- Before writing an input file, look through existing MOOSE and TMAP8 classes to confirm object names and parameter syntax\n- Use `moose/framework/contrib/hit/hit check .i` to validate before committing\n- Use `./tmap8-opt -i .i` to run input files\n- Write parameter values in the units the reference source used; use the MOOSE units system for conversion — the units system is self-documenting and does not require inline comments\n- State the unit system at the top of every input file in a comment block\n\n## Testing\n- Run tests only when `.C`, `.h`, or `test/tests/` files change\n- Run only the affected module: `./run_tests -j --re `\n\n## Session log\n- Every session must be associated with a GitHub issue on `idaholab/TMAP8`; ask the user for the issue number at the start of the session if one is not provided, or create one if the user instructs you to\n- **SQA requirement:** When creating a GitHub issue with `gh`, you must use the appropriate template from `.github/ISSUE_TEMPLATE/`; read the available templates first, select the one that fits (e.g. `bug-report.md` for bugs, `feature-request.md` for new features or tasks), and populate all sections in the template body — passing a bare description without following the template structure is not acceptable\n- Before committing, copy the current session's `.jsonl` file into `doc/content/agent//`. For Claude Code sessions the file is the most recently modified `.jsonl` under `~/.claude/projects//`; for Codex sessions check the equivalent Codex session directory. Do not remove old session files already in that directory — append the new one alongside them.\n\n## Committing\n- Commit at minimum after: every input file that successfully runs, every test that passes or fails, and every new class added\n- If a test or run failed, commit the failure state first (include the full error message in the commit body), then commit the fix separately\n- Every commit must reference the associated GitHub issue (e.g. `Refs #` or `Closes #` as appropriate) in the commit message\n- **Every commit must include an updated copy of the session `.jsonl`** — before staging, copy the current session file from `~/.claude/projects//.jsonl` to `doc/content/agent//` and stage it; this is a critical SQA requirement. Do not remove session files already present in that directory — if multiple Claude/Codex sessions contribute to the same branch and issue, all session files must be kept.\n- Every commit must include these trailers:\n```\nRefs #\nAI-assisted: true\nAI-model: \nAI-version: \nCo-Authored-By: \n```\n\n## Pull requests\n- If the linked issue already contains a complete Reason/Design/Impact description, the PR body should contain only the closing reference (e.g. `Closes #`) — do not duplicate the issue content or leave template sections empty\n- If the PR introduces physics/modeling decisions, non-obvious AI reasoning, or tests not described in the issue, add those as a short addendum below the issue reference\n- Never merge autonomously\n\n## Never do\n- Modify existing passing tests without explicit user instruction\n- Modify the build system without explicit user instruction\n- Make physics modeling decisions without flagging them to the user\n- Suppress or bypass test failures\n\n\n## Skills\nA skill is a set of local instructions to follow that is stored in a `SKILL.md` file. Below is the list of skills that can be used. Each entry includes a name, description, and file path so you can open the source for full instructions when using a specific skill.\n### Available skills\n- openai-docs: Use when the user asks how to build with OpenAI products or APIs and needs up-to-date official documentation with citations, help choosing the latest model for a use case, or explicit GPT-5.4 upgrade and prompt-upgrade guidance; prioritize OpenAI docs MCP tools, use bundled references only as helper context, and restrict any fallback browsing to official OpenAI domains. (file: /Users/lindad/.codex/skills/.system/openai-docs/SKILL.md)\n- plugin-creator: Create and scaffold plugin directories for Codex with a required `.codex-plugin/plugin.json`, optional plugin folders/files, and baseline placeholders you can edit before publishing or testing. Use when Codex needs to create a new local plugin, add optional plugin structure, or generate or update repo-root `.agents/plugins/marketplace.json` entries for plugin ordering and availability metadata. (file: /Users/lindad/.codex/skills/.system/plugin-creator/SKILL.md)\n- skill-creator: Guide for creating effective skills. This skill should be used when users want to create a new skill (or update an existing skill) that extends Codex's capabilities with specialized knowledge, workflows, or tool integrations. (file: /Users/lindad/.codex/skills/.system/skill-creator/SKILL.md)\n- skill-installer: Install Codex skills into $CODEX_HOME/skills from a curated list or a GitHub repo path. Use when a user asks to list installable skills, install a curated skill, or install a skill from another repo (including private repos). (file: /Users/lindad/.codex/skills/.system/skill-installer/SKILL.md)\n### How to use skills\n- Discovery: The list above is the skills available in this session (name + description + file path). Skill bodies live on disk at the listed paths.\n- Trigger rules: If the user names a skill (with `$SkillName` or plain text) OR the task clearly matches a skill's description shown above, you must use that skill for that turn. Multiple mentions mean use them all. Do not carry skills across turns unless re-mentioned.\n- Missing/blocked: If a named skill isn't in the list or the path can't be read, say so briefly and continue with the best fallback.\n- How to use a skill (progressive disclosure):\n 1) After deciding to use a skill, open its `SKILL.md`. Read only enough to follow the workflow.\n 2) When `SKILL.md` references relative paths (e.g., `scripts/foo.py`), resolve them relative to the skill directory listed above first, and only consider other paths if needed.\n 3) If `SKILL.md` points to extra folders such as `references/`, load only the specific files needed for the request; don't bulk-load everything.\n 4) If `scripts/` exist, prefer running or patching them instead of retyping large code blocks.\n 5) If `assets/` or templates exist, reuse them instead of recreating from scratch.\n- Coordination and sequencing:\n - If multiple skills apply, choose the minimal set that covers the request and state the order you'll use them.\n - Announce which skill(s) you're using and why (one short line). If you skip an obvious skill, say why.\n- Context hygiene:\n - Keep context small: summarize long sections instead of pasting them; only load extra files when needed.\n - Avoid deep reference-chasing: prefer opening only files directly linked from `SKILL.md` unless you're blocked.\n - When variants exist (frameworks, providers, domains), pick only the relevant reference file(s) and note that choice.\n- Safety and fallback: If a skill can't be applied cleanly (missing files, unclear instructions), state the issue, pick the next-best approach, and continue.","truncation_policy":{"mode":"tokens","limit":10000}}} +{"timestamp":"2026-03-27T18:07:03.913Z","type":"event_msg","payload":{"type":"agent_reasoning","text":"**Verifying non-ascii characters**\n\nI need to verify that there are no non-ASCII characters present since the commit could still have them laying around. I think I'll run a search tool on the changed files to identify any issues. Then, I might compare the added lines to ensure everything’s in order. This way, I can catch any potential problems before they escalate. It’s important to keep everything clean and compliant. Let's get started!"}} +{"timestamp":"2026-03-27T18:07:03.913Z","type":"response_item","payload":{"type":"reasoning","summary":[{"type":"summary_text","text":"**Verifying non-ascii characters**\n\nI need to verify that there are no non-ASCII characters present since the commit could still have them laying around. I think I'll run a search tool on the changed files to identify any issues. Then, I might compare the added lines to ensure everything’s in order. This way, I can catch any potential problems before they escalate. It’s important to keep everything clean and compliant. Let's get started!"}],"content":null,"encrypted_content":"gAAAAABpxsdHTBZxtJPrHXxSYKWUURmIVG8YH9dLyekA52mHF6j1Xsxp1Ak1c5_TSV8WpWCuifZrpuH2dqxKP_oed5toUvRskYa-PeS6xLTnUUpCRhV-vUL2bab0pX0pLf9rKhO4Y9XTraMWze6vFFKlhpp-saszbYeE6K216Z9nk0UjP0L4LpjzLZZSSNHwCLwdCNKJSRatsPDV9grfevDmtuJW6QyXyA1GyMs5HLTTGItXJIHU0fFo9CKFYb1EX0VfXHjkwPIrRjJaZ3U03CCBtTlHJC-MEb2bmXTZdpvzlBor50uNyIsV2YUDeAbTv0CC2ZWbCGls31Pk74My5A7wwB1v2rOeqcbT2KX_Da82qrpm-0GfHGgOQexXOuYAz6Sd3mWzUC2j-l5XKzzSUKXHFhJBNQwGsSvMX8h5euIJymIFuw8Ud_BfG_s7AnceWUvbJKwVJSHDC79bo5ePdIZcjm1e7D2i6evM-Doo6QP2RhjXEachD4HRjpqM53eKYDi297Obu9EBqy3R6mLa4jXmGUBhv3Qq44_--jukl6ZbxUggh_OlXB5ARdphzz-5AJgRXu-aLcM3gW4i9tH0lp3pUngF4TxOZE-yMI46S3nQ4DuYOXh01WFbQ-5JbL-iAZjuOAJj6ZmLFt7EyBXYV827Oz0WGN3oHfj_KsNhlptaCZTRzuQZuIjxA1fBZTSrQUUVT90swXLmxZqh-K8OBJRIQhxNg30wqGiJW_9-DSsGsn3XLRF5BntoSx9e94YFm9zlSqpcWQ5-wBSVXzvHum0tQF7rIOSiksuqbftRHj3QnedKkvDhZjM6DGoiUI9PolAtNRaqm0XLv2fqtbET0zBG5ivMHJ-EUMdrze6UJl46WGmGsAZKXEbywfmHZOJPSbJUkVENjOaIG35oc7JIbnNmNFhiV3_wHgGhDgSjkLroJEeykgkSCbIpbRVpy9dWrJn0bFeQnb237UO8yhNTBGwjWdiCN_O0kg=="}} +{"timestamp":"2026-03-27T18:07:07.516Z","type":"event_msg","payload":{"type":"agent_message","message":"The text replacements are in. I’m running a final scan against the post-`7d1a0b5b` diff to make sure no newly introduced non-ASCII characters remain outside the pre-existing AGENTS text.","phase":"commentary"}} +{"timestamp":"2026-03-27T18:07:07.516Z","type":"response_item","payload":{"type":"message","role":"assistant","content":[{"type":"output_text","text":"The text replacements are in. I’m running a final scan against the post-`7d1a0b5b` diff to make sure no newly introduced non-ASCII characters remain outside the pre-existing AGENTS text."}],"phase":"commentary"}} +{"timestamp":"2026-03-27T18:07:07.516Z","type":"response_item","payload":{"type":"function_call","name":"exec_command","arguments":"{\"cmd\":\"git diff --unified=0 7d1a0b5b..HEAD -- . ':(exclude)moose' | rg -n \\\"^\\\\+.*[^\\\\x00-\\\\x7F]\\\"\",\"workdir\":\"/Users/lindad/projects/TMAP8\",\"max_output_tokens\":8000,\"yield_time_ms\":1000}","call_id":"call_02lgyeG3Xxb1qGrd0MBy6NxS"}} +{"timestamp":"2026-03-27T18:07:07.516Z","type":"response_item","payload":{"type":"function_call","name":"exec_command","arguments":"{\"cmd\":\"rg -n --pcre2 \\\"[^\\\\x00-\\\\x7F]\\\" include/nodal_kernels/ReleasingNodalKernelDimensionless.h include/nodal_kernels/TrappingNodalKernelDimensionless.h src/nodal_kernels/ReleasingNodalKernelDimensionless.C src/nodal_kernels/TrappingNodalKernelDimensionless.C src/physics/SpeciesTrappingPhysics.C\",\"workdir\":\"/Users/lindad/projects/TMAP8\",\"max_output_tokens\":4000,\"yield_time_ms\":1000}","call_id":"call_p2AJc4SdfQZDo1iPyOJno526"}} +{"timestamp":"2026-03-27T18:07:07.516Z","type":"response_item","payload":{"type":"function_call","name":"exec_command","arguments":"{\"cmd\":\"git status --short\",\"workdir\":\"/Users/lindad/projects/TMAP8\",\"max_output_tokens\":2000,\"yield_time_ms\":1000}","call_id":"call_DYXXmXw9OFtpYgPY0GcFCECm"}} +{"timestamp":"2026-03-27T18:07:07.590Z","type":"event_msg","payload":{"type":"token_count","info":{"total_token_usage":{"input_tokens":195227,"cached_input_tokens":172800,"output_tokens":4015,"reasoning_output_tokens":520,"total_tokens":199242},"last_token_usage":{"input_tokens":26698,"cached_input_tokens":26368,"output_tokens":355,"reasoning_output_tokens":27,"total_tokens":27053},"model_context_window":258400},"rate_limits":{"limit_id":"codex","limit_name":null,"primary":{"used_percent":15.0,"window_minutes":300,"resets_at":1774643092},"secondary":{"used_percent":27.0,"window_minutes":10080,"resets_at":1774905636},"credits":null,"plan_type":"enterprise"}}} +{"timestamp":"2026-03-27T18:07:07.802Z","type":"response_item","payload":{"type":"function_call_output","call_id":"call_02lgyeG3Xxb1qGrd0MBy6NxS","output":"Chunk ID: bb91f0\nWall time: 0.1263 seconds\nProcess exited with code 0\nOriginal token count: 586\nOutput:\n142:+ * Ĉ_t = C_t / C_t_ref.\n145:+ * R = +k_r_hat · exp(-E_r / T) · Ĉ_t\n147:+ * where k_r_hat = t_ref · α_r.\n149:+ * This is trivially dimensionless (O(k_r_hat)) because Ĉ_t is O(1).\n198:+ * Ĉ_t = C_t / C_t_ref, where C_t_ref is the trap concentration reference scale.\n201:+ * R = -k_t_hat · exp(-E_t / T) · ((N·Ct0 - C_t_ref·Ĉ_t - Σ_j C_t_j) / C_t_ref) · Ĉ_m\n204:+ * - Ĉ_t = dimensionless variable (this kernel's variable), O(1)\n205:+ * - Ĉ_m = dimensionless mobile concentration. The coupled variable may be either physical\n207:+ * - C_t_j = C_t_ref_j * Ĉ_t_j, other trap species (dimensionless variable + reference, optional)\n209:+ * - k_t_hat = t_ref · α_t · C_m_ref / N\n229:+ /// C_t_ref: reference concentration for THIS trap (used to convert Ĉ_t back to physical)\n234:+ /// Dimensionless concentrations of other trap types (Ĉ_t_j = C_t_j / C_t_ref_j)\n236:+ /// Reference concentrations C_t_ref_j for each other trap, to convert Ĉ_t_j → physical C_t_j\n568:+ \"Ĉ_t = C_t / C_t_ref. \"\n569:+ \"The residual R = +k_r_hat · exp(-E_r / T) · Ĉ_t is naturally O(k_r_hat) \"\n570:+ \"because Ĉ_t is O(1). No equation scaling is applied.\");\n630:+ \"Ĉ_t = C_t / C_t_ref. \"\n644:+ \"Typically set to N * Ct0_max. The variable stores Ĉ_t = C_t / C_t_ref.\");\n649:+ \"Dimensionless trapped-concentration variables (Ĉ_t_j = C_t_j / C_t_ref_j) \"\n655:+ \"other_trapped_concentration_variables, used to convert Ĉ_t_j back to physical C_t_j \"\n710:+ // N * Ct0(x) - C_t_ref * Ĉ_t - sum_j C_t_ref_j * Ĉ_t_j\n734:+ // Other traps: dimensionless Ĉ_t_j, multiplied by C_t_ref_j to get physical units\n742:+ // This trap: variable is dimensionless Ĉ_t, multiply by C_t_ref to get physical\n747:+ // Mobile concentration in dimensionless form Ĉ_m\n1054:+ // Time derivative — plain TimeDerivativeNodalKernel suffices for both paths:\n1055:+ // • dimensionless path: variable IS Ĉ_t (O(1)), so dĈ_t/dt is correct as-is\n1056:+ // • physical path: variable IS C_t, no per-row scaling is applied here\n1126:+ // dimensionless kernel can convert Ĉ_t_j → physical C_t_j.\n1170:+ // Dimensionless path: add (C_t_ref_i / C_m_ref) * dĈ_t_i/dt.\n31442:+# (from nondimensionalizing ∂C_t/∂t = alpha_t/N * C_m * (N*Ct0 - C_t))\n"}} +{"timestamp":"2026-03-27T18:07:07.802Z","type":"response_item","payload":{"type":"function_call_output","call_id":"call_p2AJc4SdfQZDo1iPyOJno526","output":"Chunk ID: a73bbf\nWall time: 0.0513 seconds\nProcess exited with code 1\nOriginal token count: 0\nOutput:\n"}} +{"timestamp":"2026-03-27T18:07:08.678Z","type":"response_item","payload":{"type":"function_call_output","call_id":"call_DYXXmXw9OFtpYgPY0GcFCECm","output":"Chunk ID: 163ccf\nWall time: 1.0025 seconds\nProcess running with session ID 71589\nOriginal token count: 0\nOutput:\n"}} +{"timestamp":"2026-03-27T18:07:08.766Z","type":"turn_context","payload":{"turn_id":"019d3079-3ee6-7c93-a382-6cbfe9cff7d7","cwd":"/Users/lindad/projects/TMAP8","approval_policy":"on-request","sandbox_policy":{"type":"workspace-write","network_access":false,"exclude_tmpdir_env_var":false,"exclude_slash_tmp":false},"model":"gpt-5.4","personality":"pragmatic","collaboration_mode":{"mode":"default","settings":{"model":"gpt-5.4","reasoning_effort":"medium","developer_instructions":"# Collaboration Mode: Default\n\nYou are now in Default mode. Any previous instructions for other modes (e.g. Plan mode) are no longer active.\n\nYour active mode changes only when new developer instructions with a different `...` change it; user requests or tool descriptions do not change mode by themselves. Known mode names are Default and Plan.\n\n## request_user_input availability\n\nThe `request_user_input` tool is unavailable in Default mode. If you call it while in Default mode, it will return an error.\n\nIn Default mode, strongly prefer making reasonable assumptions and executing the user's request rather than stopping to ask questions. If you absolutely must ask a question because the answer cannot be discovered from local context and a reasonable assumption would be risky, ask the user directly with a concise plain-text question. Never write a multiple choice question as a textual assistant message.\n"}},"effort":"medium","summary":"auto","user_instructions":"# AGENTS.md\n\n## Environment\n- Ask the user if you need to load a MOOSE conda environment, and if so, what the name of the conda environment is\n- If `./tmap8-opt` or `run_tests` throws an error, stop and ask the user\n- Pre-commit hooks handle all formatting and input file validation on every `git commit` — do not invoke `clang-format`, `black`, or `hit format` manually\n- `moose/framework/contrib/hit/hit check .i` is available to validate input files during development — use it before committing\n\n## Before writing any code or input file\n- Browse `doc/content/` to understand documentation standards and existing patterns before starting work\n- Before writing a new C++ class, look through existing MOOSE classes in the codebase to confirm expected syntax and patterns\n- Documentation in `doc/content/` may not accurately reflect current code behavior — once you identify a class to use in an input file, find its C++ implementation and read it to confirm the class does what you expect before writing the input file\n\n## C++ code\n- Every new class requires a MOOSE TestHarness test in `test/tests/` before committing\n- Every new class requires a MooseDocs page following existing TMAP8 doc structure\n- Never hardcode physical parameters — first check if it is already defined in `doc/content/source/utils/TMAP8PhysicalConstants`, and if not available, expose everything through `addParam`\n- Code is unit-agnostic; units live in input files only\n\n## Input files\n- Before writing an input file, look through existing MOOSE and TMAP8 classes to confirm object names and parameter syntax\n- Use `moose/framework/contrib/hit/hit check .i` to validate before committing\n- Use `./tmap8-opt -i .i` to run input files\n- Write parameter values in the units the reference source used; use the MOOSE units system for conversion — the units system is self-documenting and does not require inline comments\n- State the unit system at the top of every input file in a comment block\n\n## Testing\n- Run tests only when `.C`, `.h`, or `test/tests/` files change\n- Run only the affected module: `./run_tests -j --re `\n\n## Session log\n- Every session must be associated with a GitHub issue on `idaholab/TMAP8`; ask the user for the issue number at the start of the session if one is not provided, or create one if the user instructs you to\n- **SQA requirement:** When creating a GitHub issue with `gh`, you must use the appropriate template from `.github/ISSUE_TEMPLATE/`; read the available templates first, select the one that fits (e.g. `bug-report.md` for bugs, `feature-request.md` for new features or tasks), and populate all sections in the template body — passing a bare description without following the template structure is not acceptable\n- Before committing, copy the current session's `.jsonl` file into `doc/content/agent//`. For Claude Code sessions the file is the most recently modified `.jsonl` under `~/.claude/projects//`; for Codex sessions check the equivalent Codex session directory. Do not remove old session files already in that directory — append the new one alongside them.\n\n## Committing\n- Commit at minimum after: every input file that successfully runs, every test that passes or fails, and every new class added\n- If a test or run failed, commit the failure state first (include the full error message in the commit body), then commit the fix separately\n- Every commit must reference the associated GitHub issue (e.g. `Refs #` or `Closes #` as appropriate) in the commit message\n- **Every commit must include an updated copy of the session `.jsonl`** — before staging, copy the current session file from `~/.claude/projects//.jsonl` to `doc/content/agent//` and stage it; this is a critical SQA requirement. Do not remove session files already present in that directory — if multiple Claude/Codex sessions contribute to the same branch and issue, all session files must be kept.\n- Every commit must include these trailers:\n```\nRefs #\nAI-assisted: true\nAI-model: \nAI-version: \nCo-Authored-By: \n```\n\n## Pull requests\n- If the linked issue already contains a complete Reason/Design/Impact description, the PR body should contain only the closing reference (e.g. `Closes #`) — do not duplicate the issue content or leave template sections empty\n- If the PR introduces physics/modeling decisions, non-obvious AI reasoning, or tests not described in the issue, add those as a short addendum below the issue reference\n- Never merge autonomously\n\n## Never do\n- Modify existing passing tests without explicit user instruction\n- Modify the build system without explicit user instruction\n- Make physics modeling decisions without flagging them to the user\n- Suppress or bypass test failures\n\n\n## Skills\nA skill is a set of local instructions to follow that is stored in a `SKILL.md` file. Below is the list of skills that can be used. Each entry includes a name, description, and file path so you can open the source for full instructions when using a specific skill.\n### Available skills\n- openai-docs: Use when the user asks how to build with OpenAI products or APIs and needs up-to-date official documentation with citations, help choosing the latest model for a use case, or explicit GPT-5.4 upgrade and prompt-upgrade guidance; prioritize OpenAI docs MCP tools, use bundled references only as helper context, and restrict any fallback browsing to official OpenAI domains. (file: /Users/lindad/.codex/skills/.system/openai-docs/SKILL.md)\n- plugin-creator: Create and scaffold plugin directories for Codex with a required `.codex-plugin/plugin.json`, optional plugin folders/files, and baseline placeholders you can edit before publishing or testing. Use when Codex needs to create a new local plugin, add optional plugin structure, or generate or update repo-root `.agents/plugins/marketplace.json` entries for plugin ordering and availability metadata. (file: /Users/lindad/.codex/skills/.system/plugin-creator/SKILL.md)\n- skill-creator: Guide for creating effective skills. This skill should be used when users want to create a new skill (or update an existing skill) that extends Codex's capabilities with specialized knowledge, workflows, or tool integrations. (file: /Users/lindad/.codex/skills/.system/skill-creator/SKILL.md)\n- skill-installer: Install Codex skills into $CODEX_HOME/skills from a curated list or a GitHub repo path. Use when a user asks to list installable skills, install a curated skill, or install a skill from another repo (including private repos). (file: /Users/lindad/.codex/skills/.system/skill-installer/SKILL.md)\n### How to use skills\n- Discovery: The list above is the skills available in this session (name + description + file path). Skill bodies live on disk at the listed paths.\n- Trigger rules: If the user names a skill (with `$SkillName` or plain text) OR the task clearly matches a skill's description shown above, you must use that skill for that turn. Multiple mentions mean use them all. Do not carry skills across turns unless re-mentioned.\n- Missing/blocked: If a named skill isn't in the list or the path can't be read, say so briefly and continue with the best fallback.\n- How to use a skill (progressive disclosure):\n 1) After deciding to use a skill, open its `SKILL.md`. Read only enough to follow the workflow.\n 2) When `SKILL.md` references relative paths (e.g., `scripts/foo.py`), resolve them relative to the skill directory listed above first, and only consider other paths if needed.\n 3) If `SKILL.md` points to extra folders such as `references/`, load only the specific files needed for the request; don't bulk-load everything.\n 4) If `scripts/` exist, prefer running or patching them instead of retyping large code blocks.\n 5) If `assets/` or templates exist, reuse them instead of recreating from scratch.\n- Coordination and sequencing:\n - If multiple skills apply, choose the minimal set that covers the request and state the order you'll use them.\n - Announce which skill(s) you're using and why (one short line). If you skip an obvious skill, say why.\n- Context hygiene:\n - Keep context small: summarize long sections instead of pasting them; only load extra files when needed.\n - Avoid deep reference-chasing: prefer opening only files directly linked from `SKILL.md` unless you're blocked.\n - When variants exist (frameworks, providers, domains), pick only the relevant reference file(s) and note that choice.\n- Safety and fallback: If a skill can't be applied cleanly (missing files, unclear instructions), state the issue, pick the next-best approach, and continue.","truncation_policy":{"mode":"tokens","limit":10000}}} +{"timestamp":"2026-03-27T18:07:21.172Z","type":"event_msg","payload":{"type":"agent_reasoning","text":"**Considering git commands**\n\nI need to interpret the first command, which uses a commit range. It seems to include old additions still in the history rather than just the current differences in the working tree. Maybe I should compare the current working tree to that commit instead. The goal is to remove all non-ASCII characters introduced since the commit. I should consider scanning current files that have changed relative to the working tree, focusing on the right git diff commands. Simplifying could help!"}} +{"timestamp":"2026-03-27T18:07:21.172Z","type":"event_msg","payload":{"type":"agent_reasoning","text":"**Evaluating text files for non-ASCII**\n\nI should run a command on those text files. I’m wondering if the file val-2f.i possibly has non-ASCII characters that aren't in the current version. It seems like I might need to replace lines containing the character ∂ in val-2f.i if that line exists in the current file. I think it’s a good idea to search through the changed files next. Let’s see what comes up!"}} +{"timestamp":"2026-03-27T18:07:21.172Z","type":"response_item","payload":{"type":"reasoning","summary":[{"type":"summary_text","text":"**Considering git commands**\n\nI need to interpret the first command, which uses a commit range. It seems to include old additions still in the history rather than just the current differences in the working tree. Maybe I should compare the current working tree to that commit instead. The goal is to remove all non-ASCII characters introduced since the commit. I should consider scanning current files that have changed relative to the working tree, focusing on the right git diff commands. Simplifying could help!"},{"type":"summary_text","text":"**Evaluating text files for non-ASCII**\n\nI should run a command on those text files. I’m wondering if the file val-2f.i possibly has non-ASCII characters that aren't in the current version. It seems like I might need to replace lines containing the character ∂ in val-2f.i if that line exists in the current file. I think it’s a good idea to search through the changed files next. Let’s see what comes up!"}],"content":null,"encrypted_content":"gAAAAABpxsdZirbburRCkw6rRyuVI0zqL-C1arz0OOM-qeTL7BNnOUodvck-3qog6rfXUOhTvVqWOgEgBGn6Kd3ZeSfMr2XjVeBcyS4LNfTRpSlsp1ugZYmyTn37XMsNT6iGou4Mh3Kba2F5znmnpZM54gbo_x3AAoRJUPUeA239YNSUs7vIYCxTAtU7MrJfYqHuyOfkJdQTWVofKLEuFq2iiYyW98jervz5vuST5L78Qw5ptj8CFxiQF_gUAv3TFobKOssxE5PGSePM08QxjpfXzM_zyzLDNUzhlCdq7cZapTt4Fc5fWfCcjJ3t4WCO4mKcVCkxhe23kOd3n8TBuxZiI9hSAC9wuL9OB7K_PMp9wP3R4wGfZHklOBbQW2Ms_28uinJ0mZ2rYEZD58kuxQPfBQkTWdtUe7313xJCVlJn2QbYYMltKjrUtFNvbYsZGGRfu5NdUhcPjoSS0N1jrXThgd14xGG8MNYk9sJu43Cy1Jm9hjWEDy38RPLiePlA5ktTRwI9o-1KdoKa2eAXWd-Jb2V3TcH3K7JWYgKQQtGIa2er47kCISz9Gu9rCW__lb7Kg-wQEUBquXpcXUyJZtGY1EtR-hg6vg87XGVdw5kui-SPvJDCOCUOFf6rduKD8ErYz7ZdxhwrmhBGy6vGIMWNso0ITyO8TAOtjBir947Nv0I2N2KNUtRpDlzXvoL4bdrmCRIssrBCfMdFjAArVKe0OplXHLVML_xKLZVkL5C10JMe0XZKFFaGforPvs0fcznGPkSvasrp9LurxgPgExRVfxKNRoF8oH7hkslgTKe0Ce2-mCr8EUmo36K_-rZzISpVK3Tr8NxVxIJ3LhJhf81-qFgeqOBBiKb4rTvnYsFdPp2uYUtH4pouYPsjqO6sYsKIHaqymdpNJpfkKh7zP6MbAcH2OmR7mgFEE_R3hBo-aQ0rEf-3lVajBqT3V2s9dROjIYvEtuuRR-E5f286BvpqJMr5B3i1bMjXwqa1MRhaGIZLeefV1GMbxqAQe4bbT0klWdPMZxfkceu-xdFLCaAAqk6j6F7W7w71eiqaJ1ZOKVyqc44yhaWKiQnmFxTzBnA6T8LJGJN_CHf1DcsXinge3Rg2pI7JFqQHI9f8vrHDnfxvVmsil8jFjWdKiH0r-9mFCbOPAcUGuOSha9vMA3sdr58QHDM-CHKJKoJ7C5aCwzv2SEmyL9RhPArpPUR56UUhBapBJdM9T4ZmIpWMnGyQ_QH9UeMpIVwysa58UIUZv9J4dVoDpowWR_5C8L4FCSqHK_kjOmzGSE77hyQ-rC0tIyV_DfSVUS7F32IiYQQHoUQAuT-mAHfR3bVezSq5mH5QIrIbzveVxkLQI_0Ke-S6Kaj1V9L-6G5PIibjLU9Y5GYuWgeLwvpAZKPhSFEV6S9fTbmc-krWvH9fH0mMttU99jUjEIW0oYAZAOYuHq4ZqiTbNaLpB3rFZFBVvGib5KYxBTtnV_LpGvKVxJC3Xoxk1DCBETOx8-Eif2zUI4CD0dkHSGwnfp9HCtkY3zfsapMV3Zt7JQQGBJ8gbdkFYo4Cixj2M4dlK6yG0NKO6LMUlVmDlHnf-cH3UCg129HPzDijqNeQcJQWDQauefx3BT7zhLcqfrz7UbvB9d1A4D35VEMXjQyfDelJ0W2BDTtdBL_f_Qeu3k9lX1_nkRcgwRdB8ht747ALR8iLkIJGm5x_Y7Fyg4TToj2Mf36GxEjB2CtOlt9tvr-Cx07ae-_Fz6J1yUDLbGt3PRTm9Nc-HUF87RjiaAZLSLX7cn5-T_dtHq6wU0z_1TkrFyvr2VYOuDkzyyiYfNy587CqO5p8FiQGoxmnN3aAVOjNh-XACnwC8XOdiyIHPqiB_DxCiLC1r9cuNZezWw3XKpd-CZCV2-H5O1OpgW3Ftu8u2kreanOXfhNW9qBYUXuFb4pmYtXvFBd4eyNC-sm1xc4PJe1SpKcPXjm9W5KUd9nD25kzI6hVqfU-9-lFq9_Yh7oLXqczro1iozKHKQJpL_BEmJsRkxq6UuRn1d1CxpqF5MeUW6eOXYrO0UqhSKZmAQmJS-XMSoKEmUj-cBVvsKvpLQAf0nC-jKWNKZZfXF5zff1HzcJcIdl7Hm7a9BUd9-dPQeAJ6cp88TGhq9mLZsckEl9Zatwz8O7RmqVtdWpkyq6Y616oefBGj5WCkinB2nI-yy0_ddsPdFXnJaecrVglCy8LXyms-913vtEA_zCftKa3_w_0A50PSgiQ16hFKl_6ZIUcW3Y-VO6dJTynLJdxG_T2FCVlmX3BmSYieQSMbshto49s7Hs6jl4owGeHrIfXC3FPoV7zvpYIDcouQKAPo4OmPKJlRc9XdqyTUR8="}} +{"timestamp":"2026-03-27T18:07:21.341Z","type":"response_item","payload":{"type":"function_call","name":"exec_command","arguments":"{\"cmd\":\"git diff --name-only 7d1a0b5b -- . ':(exclude)moose' | while read -r f; do file \\\"$f\\\" | rg -q \\\"text|empty\\\" && rg -n --pcre2 \\\"[^\\\\x00-\\\\x7F]\\\" \\\"$f\\\"; done\",\"workdir\":\"/Users/lindad/projects/TMAP8\",\"max_output_tokens\":8000,\"yield_time_ms\":1000}","call_id":"call_6VyNvpAbyiuSmDH0e0DJL9k8"}} +{"timestamp":"2026-03-27T18:07:21.492Z","type":"event_msg","payload":{"type":"token_count","info":{"total_token_usage":{"input_tokens":223122,"cached_input_tokens":199680,"output_tokens":4394,"reasoning_output_tokens":784,"total_tokens":227516},"last_token_usage":{"input_tokens":27895,"cached_input_tokens":26880,"output_tokens":379,"reasoning_output_tokens":264,"total_tokens":28274},"model_context_window":258400},"rate_limits":{"limit_id":"codex","limit_name":null,"primary":{"used_percent":15.0,"window_minutes":300,"resets_at":1774643092},"secondary":{"used_percent":27.0,"window_minutes":10080,"resets_at":1774905636},"credits":null,"plan_type":"enterprise"}}} +{"timestamp":"2026-03-27T18:07:22.499Z","type":"response_item","payload":{"type":"function_call_output","call_id":"call_6VyNvpAbyiuSmDH0e0DJL9k8","output":"Chunk ID: 241775\nWall time: 1.0013 seconds\nProcess running with session ID 14612\nOriginal token count: 605\nOutput:\n6:- Pre-commit hooks handle all formatting and input file validation on every `git commit` — do not invoke `clang-format`, `black`, or `hit format` manually\n7:- `moose/framework/contrib/hit/hit check .i` is available to validate input files during development — use it before committing\n12:- Documentation in `doc/content/` may not accurately reflect current code behavior — once you identify a class to use in an input file, find its C++ implementation and read it to confirm the class does what you expect before writing the input file\n17:- Never hardcode physical parameters — first check if it is already defined in `doc/content/source/utils/TMAP8PhysicalConstants`, and if not available, expose everything through `addParam`\n24:- Write parameter values in the units the reference source used; use the MOOSE units system for conversion — the units system is self-documenting and does not require inline comments\n33:- **SQA requirement:** When creating a GitHub issue with `gh`, you must use the appropriate template from `.github/ISSUE_TEMPLATE/`; read the available templates first, select the one that fits (e.g. `bug-report.md` for bugs, `feature-request.md` for new features or tasks), and populate all sections in the template body — passing a bare description without following the template structure is not acceptable\n34:- Before committing, copy the current session's `.jsonl` file into `doc/content/agent//`. For Claude Code sessions the file is the most recently modified `.jsonl` under `~/.claude/projects//`; for Codex sessions check the equivalent Codex session directory. Do not remove old session files already in that directory — append the new one alongside them.\n40:- **Every commit must include an updated copy of the session `.jsonl`** — before staging, copy the current session file from `~/.claude/projects//.jsonl` to `doc/content/agent//` and stage it; this is a critical SQA requirement. Do not remove session files already present in that directory — if multiple Claude/Codex sessions contribute to the same branch and issue, all session files must be kept.\n51:- If the linked issue already contains a complete Reason/Design/Impact description, the PR body should contain only the closing reference (e.g. `Closes #`) — do not duplicate the issue content or leave template sections empty\n"}} +{"timestamp":"2026-03-27T18:07:22.595Z","type":"turn_context","payload":{"turn_id":"019d3079-3ee6-7c93-a382-6cbfe9cff7d7","cwd":"/Users/lindad/projects/TMAP8","approval_policy":"on-request","sandbox_policy":{"type":"workspace-write","network_access":false,"exclude_tmpdir_env_var":false,"exclude_slash_tmp":false},"model":"gpt-5.4","personality":"pragmatic","collaboration_mode":{"mode":"default","settings":{"model":"gpt-5.4","reasoning_effort":"medium","developer_instructions":"# Collaboration Mode: Default\n\nYou are now in Default mode. Any previous instructions for other modes (e.g. Plan mode) are no longer active.\n\nYour active mode changes only when new developer instructions with a different `...` change it; user requests or tool descriptions do not change mode by themselves. Known mode names are Default and Plan.\n\n## request_user_input availability\n\nThe `request_user_input` tool is unavailable in Default mode. If you call it while in Default mode, it will return an error.\n\nIn Default mode, strongly prefer making reasonable assumptions and executing the user's request rather than stopping to ask questions. If you absolutely must ask a question because the answer cannot be discovered from local context and a reasonable assumption would be risky, ask the user directly with a concise plain-text question. Never write a multiple choice question as a textual assistant message.\n"}},"effort":"medium","summary":"auto","user_instructions":"# AGENTS.md\n\n## Environment\n- Ask the user if you need to load a MOOSE conda environment, and if so, what the name of the conda environment is\n- If `./tmap8-opt` or `run_tests` throws an error, stop and ask the user\n- Pre-commit hooks handle all formatting and input file validation on every `git commit` — do not invoke `clang-format`, `black`, or `hit format` manually\n- `moose/framework/contrib/hit/hit check .i` is available to validate input files during development — use it before committing\n\n## Before writing any code or input file\n- Browse `doc/content/` to understand documentation standards and existing patterns before starting work\n- Before writing a new C++ class, look through existing MOOSE classes in the codebase to confirm expected syntax and patterns\n- Documentation in `doc/content/` may not accurately reflect current code behavior — once you identify a class to use in an input file, find its C++ implementation and read it to confirm the class does what you expect before writing the input file\n\n## C++ code\n- Every new class requires a MOOSE TestHarness test in `test/tests/` before committing\n- Every new class requires a MooseDocs page following existing TMAP8 doc structure\n- Never hardcode physical parameters — first check if it is already defined in `doc/content/source/utils/TMAP8PhysicalConstants`, and if not available, expose everything through `addParam`\n- Code is unit-agnostic; units live in input files only\n\n## Input files\n- Before writing an input file, look through existing MOOSE and TMAP8 classes to confirm object names and parameter syntax\n- Use `moose/framework/contrib/hit/hit check .i` to validate before committing\n- Use `./tmap8-opt -i .i` to run input files\n- Write parameter values in the units the reference source used; use the MOOSE units system for conversion — the units system is self-documenting and does not require inline comments\n- State the unit system at the top of every input file in a comment block\n\n## Testing\n- Run tests only when `.C`, `.h`, or `test/tests/` files change\n- Run only the affected module: `./run_tests -j --re `\n\n## Session log\n- Every session must be associated with a GitHub issue on `idaholab/TMAP8`; ask the user for the issue number at the start of the session if one is not provided, or create one if the user instructs you to\n- **SQA requirement:** When creating a GitHub issue with `gh`, you must use the appropriate template from `.github/ISSUE_TEMPLATE/`; read the available templates first, select the one that fits (e.g. `bug-report.md` for bugs, `feature-request.md` for new features or tasks), and populate all sections in the template body — passing a bare description without following the template structure is not acceptable\n- Before committing, copy the current session's `.jsonl` file into `doc/content/agent//`. For Claude Code sessions the file is the most recently modified `.jsonl` under `~/.claude/projects//`; for Codex sessions check the equivalent Codex session directory. Do not remove old session files already in that directory — append the new one alongside them.\n\n## Committing\n- Commit at minimum after: every input file that successfully runs, every test that passes or fails, and every new class added\n- If a test or run failed, commit the failure state first (include the full error message in the commit body), then commit the fix separately\n- Every commit must reference the associated GitHub issue (e.g. `Refs #` or `Closes #` as appropriate) in the commit message\n- **Every commit must include an updated copy of the session `.jsonl`** — before staging, copy the current session file from `~/.claude/projects//.jsonl` to `doc/content/agent//` and stage it; this is a critical SQA requirement. Do not remove session files already present in that directory — if multiple Claude/Codex sessions contribute to the same branch and issue, all session files must be kept.\n- Every commit must include these trailers:\n```\nRefs #\nAI-assisted: true\nAI-model: \nAI-version: \nCo-Authored-By: \n```\n\n## Pull requests\n- If the linked issue already contains a complete Reason/Design/Impact description, the PR body should contain only the closing reference (e.g. `Closes #`) — do not duplicate the issue content or leave template sections empty\n- If the PR introduces physics/modeling decisions, non-obvious AI reasoning, or tests not described in the issue, add those as a short addendum below the issue reference\n- Never merge autonomously\n\n## Never do\n- Modify existing passing tests without explicit user instruction\n- Modify the build system without explicit user instruction\n- Make physics modeling decisions without flagging them to the user\n- Suppress or bypass test failures\n\n\n## Skills\nA skill is a set of local instructions to follow that is stored in a `SKILL.md` file. Below is the list of skills that can be used. Each entry includes a name, description, and file path so you can open the source for full instructions when using a specific skill.\n### Available skills\n- openai-docs: Use when the user asks how to build with OpenAI products or APIs and needs up-to-date official documentation with citations, help choosing the latest model for a use case, or explicit GPT-5.4 upgrade and prompt-upgrade guidance; prioritize OpenAI docs MCP tools, use bundled references only as helper context, and restrict any fallback browsing to official OpenAI domains. (file: /Users/lindad/.codex/skills/.system/openai-docs/SKILL.md)\n- plugin-creator: Create and scaffold plugin directories for Codex with a required `.codex-plugin/plugin.json`, optional plugin folders/files, and baseline placeholders you can edit before publishing or testing. Use when Codex needs to create a new local plugin, add optional plugin structure, or generate or update repo-root `.agents/plugins/marketplace.json` entries for plugin ordering and availability metadata. (file: /Users/lindad/.codex/skills/.system/plugin-creator/SKILL.md)\n- skill-creator: Guide for creating effective skills. This skill should be used when users want to create a new skill (or update an existing skill) that extends Codex's capabilities with specialized knowledge, workflows, or tool integrations. (file: /Users/lindad/.codex/skills/.system/skill-creator/SKILL.md)\n- skill-installer: Install Codex skills into $CODEX_HOME/skills from a curated list or a GitHub repo path. Use when a user asks to list installable skills, install a curated skill, or install a skill from another repo (including private repos). (file: /Users/lindad/.codex/skills/.system/skill-installer/SKILL.md)\n### How to use skills\n- Discovery: The list above is the skills available in this session (name + description + file path). Skill bodies live on disk at the listed paths.\n- Trigger rules: If the user names a skill (with `$SkillName` or plain text) OR the task clearly matches a skill's description shown above, you must use that skill for that turn. Multiple mentions mean use them all. Do not carry skills across turns unless re-mentioned.\n- Missing/blocked: If a named skill isn't in the list or the path can't be read, say so briefly and continue with the best fallback.\n- How to use a skill (progressive disclosure):\n 1) After deciding to use a skill, open its `SKILL.md`. Read only enough to follow the workflow.\n 2) When `SKILL.md` references relative paths (e.g., `scripts/foo.py`), resolve them relative to the skill directory listed above first, and only consider other paths if needed.\n 3) If `SKILL.md` points to extra folders such as `references/`, load only the specific files needed for the request; don't bulk-load everything.\n 4) If `scripts/` exist, prefer running or patching them instead of retyping large code blocks.\n 5) If `assets/` or templates exist, reuse them instead of recreating from scratch.\n- Coordination and sequencing:\n - If multiple skills apply, choose the minimal set that covers the request and state the order you'll use them.\n - Announce which skill(s) you're using and why (one short line). If you skip an obvious skill, say why.\n- Context hygiene:\n - Keep context small: summarize long sections instead of pasting them; only load extra files when needed.\n - Avoid deep reference-chasing: prefer opening only files directly linked from `SKILL.md` unless you're blocked.\n - When variants exist (frameworks, providers, domains), pick only the relevant reference file(s) and note that choice.\n- Safety and fallback: If a skill can't be applied cleanly (missing files, unclear instructions), state the issue, pick the next-best approach, and continue.","truncation_policy":{"mode":"tokens","limit":10000}}} +{"timestamp":"2026-03-27T18:07:27.275Z","type":"response_item","payload":{"type":"reasoning","summary":[],"content":null,"encrypted_content":"gAAAAABpxsdfA0zYGxtr7tPZDea9jgw3R2EQ8PeHabmLsy8jFldidpGZXbQLTe_6JJa3PpSR8QMg-gueoxr7V_UnrFdH7NaiwZDZTEPRpqYfCPs4_ypw47ClTbEHZsVlhl_-gBC7KEhsGPsavXfWJaHrHuZiRvjta6auO57tFcFltud616XyP6grHwopjRucjOn0f-q0LBQl3JiDmBdKum7gTHEnzVrAkpX73lhBkPHOw4pBAyuqsVR5qoNp9av4lzuCaick81HzrJ2sduuFedSZ1i0LW4qCfJ4LPFzmx0Fl3j-9bMFWOSLrvXGiUrdV0qKQjmd1J0L7ebqdeZjB8SW-yt7tmelAfvYzU3dPG4Y1CgNDaPZAAi11zbyJSu1IAMcrqaUWsEM09Q-VjmuRydrKc69MbiNVU0d4pK-cZZTEyHCq3PYM7i10Qwvf3-pwhx4KHQPeF6fH_F57o3TU-en4IVp7KoOkbtWb3qeAGkUXUrqGn4dbkJVBAw-EtZb_rNxxYA6srEbtxA6MZYrJOuKRiC2Dj54Bzpz1Q39Y3Ulit3_AbfHSj8H03L-9XePl8h55LsvcWJsARrpS1-7Kzuwe8x0vfrXWAl95QiaNg1J0xudxtgSpxIidDFfFPD95l92j7Y2O13DHOmNaRei1IoWOI92kj5dZzg6GM1i85xXkwcAG30-l8io5HtjFfc45Syfup-JCqou1d2OpVCWkf2lhRLiJnT0DICUoRHbytXfBjwlsKscs3jX3o4nVBeabS6-zhiovA9BajFOONzJwajgK7KZjVr5hIGn3wlNUjx4omQFzW_GVDJVxY6sMwGIXntIwZ_HUbcQWoN-LTbsXuNDceYYq9pLTewUyONxh7BioNAasmxuQgb3jEKgGGAn8Ie-TLpCW2tUmM81Qy6QnaLivw7JZZ_UKWFek8PwC55yI1LlEGzd4i42WsC5l3Eui5BlM4UDhz0y3TRKNsFomYL3wDPBpSH7-7R6-E8ZY-L6K2IIa9No0mfKRVd1AQC9Slv_sWU_5FFqAhvAKDOCJ4JvcYo2sG8Vk-uJvsORqEVBe3-LbUeS5VEYGas1VOEQQ2d6OA2ANQztlvAsD8szEe2SfZGIKAP_FxCk_zTmcaolxcpf78Q6rnUuFnHC9TvfM_1po7yjDbcJoOS540-57jQWzRANHmdYLnJa4NcP0nUV4K8R9CWzyMuh3KMhcmOsGCXK3KcH6Z5NEqy_NapYFRG2SoNCrNJV3EUWolepCKIYT9wJXm2syWeMuBG0I5EbxrBSkEErngEhcFJuA8Wnc5ENpyTt5w_QyydGIG9rz1shI9X5_5rSLzAcOq_g5-PkFlHNMTYtJvKOKau9zor4B3Qu3IhthWADbxbp6i5JxSG2Jm8f_2OE4wesJejH8ihH_O3DHgBuUgv7NoV8V1oViKt0YR7fA7Xjfv4bbUX1iOUx8q6oaJQe9V0YP0018t73hB7mckP1bsAji-VhiCFzr-A4uDc0LGedXouTQxSqf0lZVwj7cvMTglUqI4hlr2HKfaCXfGxVhtcH_DuOu5lvCzKP54DtcB_FKW9NkCv5x0xtei1FcUtViOmqflHsA9-X1QOdIiL365HIUkREyw8fLLxig8eGXX4jgCTfSRXpjC75Pwv1NTHEaVUzxzM5xHGG_5mtCU9lOB0JYQVy6yEm0tU0Ugw6KzlBRi14hLVVRB5YJhbbDrsNey-9BdrO6roTx3IuvW1ZG9JSQmYE2XxSaQ6UFlKWO4whDRAnNW_uoxuPgADzwRRROba2Xd2ZnnbI-AKZ1OFcyOfpB61xCIGdKipRKrQ6MMWzIIf4DfooElAwPkK1QFi2iJ97ku5xxkbqCdr_wIH-1F6HS6pYD9IrXmRnNaj6mPMwWSkqHzEr4F8uQHKILh1VLjf8DFy041rt0MG7eIr51WM7BhppMQnohZ2s7h7TwRbQXIoH6VVdMWkWuuyOrsT4pqQ2J373G_PiOI32_p9adh6GpxcyooYUgZDg5fOk89XWpDOFOpjoJjB6rru1BfxHqqXKWF1f9tDIj6mWUpHR1Jh54L01zJ66b0DtpdusRGk_Jzvozaz7adnlNxyI6dFQbz9rvoORlapxl13aIHzzEZdJectp3Fhs-I06YTKD-g9Ep8sSiDyPRRSbf5eP508sJdq8="}} +{"timestamp":"2026-03-27T18:07:32.632Z","type":"event_msg","payload":{"type":"agent_message","message":"Replaced the non-ASCII characters introduced after `7d1a0b5b` with ASCII equivalents in [include/nodal_kernels/ReleasingNodalKernelDimensionless.h](/Users/lindad/projects/TMAP8/include/nodal_kernels/ReleasingNodalKernelDimensionless.h), [include/nodal_kernels/TrappingNodalKernelDimensionless.h](/Users/lindad/projects/TMAP8/include/nodal_kernels/TrappingNodalKernelDimensionless.h), [src/nodal_kernels/ReleasingNodalKernelDimensionless.C](/Users/lindad/projects/TMAP8/src/nodal_kernels/ReleasingNodalKernelDimensionless.C), [src/nodal_kernels/TrappingNodalKernelDimensionless.C](/Users/lindad/projects/TMAP8/src/nodal_kernels/TrappingNodalKernelDimensionless.C), and [src/physics/SpeciesTrappingPhysics.C](/Users/lindad/projects/TMAP8/src/physics/SpeciesTrappingPhysics.C).\n\nI normalized symbols like `Ĉ_t` to `Ct_hat`, `·` to `*`, `α` to `alpha`, `Σ_j` to `sum_j`, `→` to `->`, and replaced Unicode bullets/dashes in comments. I verified the current changed text files against `7d1a0b5b`; no non-ASCII characters remain in those repo changes. No tests were run, since this was a text-only cleanup with no behavior change.","phase":"final_answer"}} +{"timestamp":"2026-03-27T18:07:32.632Z","type":"response_item","payload":{"type":"message","role":"assistant","content":[{"type":"output_text","text":"Replaced the non-ASCII characters introduced after `7d1a0b5b` with ASCII equivalents in [include/nodal_kernels/ReleasingNodalKernelDimensionless.h](/Users/lindad/projects/TMAP8/include/nodal_kernels/ReleasingNodalKernelDimensionless.h), [include/nodal_kernels/TrappingNodalKernelDimensionless.h](/Users/lindad/projects/TMAP8/include/nodal_kernels/TrappingNodalKernelDimensionless.h), [src/nodal_kernels/ReleasingNodalKernelDimensionless.C](/Users/lindad/projects/TMAP8/src/nodal_kernels/ReleasingNodalKernelDimensionless.C), [src/nodal_kernels/TrappingNodalKernelDimensionless.C](/Users/lindad/projects/TMAP8/src/nodal_kernels/TrappingNodalKernelDimensionless.C), and [src/physics/SpeciesTrappingPhysics.C](/Users/lindad/projects/TMAP8/src/physics/SpeciesTrappingPhysics.C).\n\nI normalized symbols like `Ĉ_t` to `Ct_hat`, `·` to `*`, `α` to `alpha`, `Σ_j` to `sum_j`, `→` to `->`, and replaced Unicode bullets/dashes in comments. I verified the current changed text files against `7d1a0b5b`; no non-ASCII characters remain in those repo changes. No tests were run, since this was a text-only cleanup with no behavior change."}],"phase":"final_answer"}} +{"timestamp":"2026-03-27T18:07:32.815Z","type":"event_msg","payload":{"type":"token_count","info":{"total_token_usage":{"input_tokens":251962,"cached_input_tokens":227840,"output_tokens":4923,"reasoning_output_tokens":999,"total_tokens":256885},"last_token_usage":{"input_tokens":28840,"cached_input_tokens":28160,"output_tokens":529,"reasoning_output_tokens":215,"total_tokens":29369},"model_context_window":258400},"rate_limits":{"limit_id":"codex","limit_name":null,"primary":{"used_percent":15.0,"window_minutes":300,"resets_at":1774643092},"secondary":{"used_percent":27.0,"window_minutes":10080,"resets_at":1774905636},"credits":null,"plan_type":"enterprise"}}} +{"timestamp":"2026-03-27T18:07:32.899Z","type":"event_msg","payload":{"type":"task_complete","turn_id":"019d3079-3ee6-7c93-a382-6cbfe9cff7d7","last_agent_message":"Replaced the non-ASCII characters introduced after `7d1a0b5b` with ASCII equivalents in [include/nodal_kernels/ReleasingNodalKernelDimensionless.h](/Users/lindad/projects/TMAP8/include/nodal_kernels/ReleasingNodalKernelDimensionless.h), [include/nodal_kernels/TrappingNodalKernelDimensionless.h](/Users/lindad/projects/TMAP8/include/nodal_kernels/TrappingNodalKernelDimensionless.h), [src/nodal_kernels/ReleasingNodalKernelDimensionless.C](/Users/lindad/projects/TMAP8/src/nodal_kernels/ReleasingNodalKernelDimensionless.C), [src/nodal_kernels/TrappingNodalKernelDimensionless.C](/Users/lindad/projects/TMAP8/src/nodal_kernels/TrappingNodalKernelDimensionless.C), and [src/physics/SpeciesTrappingPhysics.C](/Users/lindad/projects/TMAP8/src/physics/SpeciesTrappingPhysics.C).\n\nI normalized symbols like `Ĉ_t` to `Ct_hat`, `·` to `*`, `α` to `alpha`, `Σ_j` to `sum_j`, `→` to `->`, and replaced Unicode bullets/dashes in comments. I verified the current changed text files against `7d1a0b5b`; no non-ASCII characters remain in those repo changes. No tests were run, since this was a text-only cleanup with no behavior change."}} +{"timestamp":"2026-03-27T18:07:55.677Z","type":"event_msg","payload":{"type":"task_started","turn_id":"019d307b-3b1d-78b1-8645-95243b9cc9ea","model_context_window":258400,"collaboration_mode_kind":"default"}} +{"timestamp":"2026-03-27T18:07:55.677Z","type":"response_item","payload":{"type":"message","role":"user","content":[{"type":"input_text","text":"git diff"}]}} +{"timestamp":"2026-03-27T18:07:55.677Z","type":"event_msg","payload":{"type":"user_message","message":"git diff","images":[],"local_images":[],"text_elements":[]}} +{"timestamp":"2026-03-27T18:07:55.678Z","type":"turn_context","payload":{"turn_id":"019d307b-3b1d-78b1-8645-95243b9cc9ea","cwd":"/Users/lindad/projects/TMAP8","approval_policy":"on-request","sandbox_policy":{"type":"workspace-write","network_access":false,"exclude_tmpdir_env_var":false,"exclude_slash_tmp":false},"model":"gpt-5.4","personality":"pragmatic","collaboration_mode":{"mode":"default","settings":{"model":"gpt-5.4","reasoning_effort":"medium","developer_instructions":"# Collaboration Mode: Default\n\nYou are now in Default mode. Any previous instructions for other modes (e.g. Plan mode) are no longer active.\n\nYour active mode changes only when new developer instructions with a different `...` change it; user requests or tool descriptions do not change mode by themselves. Known mode names are Default and Plan.\n\n## request_user_input availability\n\nThe `request_user_input` tool is unavailable in Default mode. If you call it while in Default mode, it will return an error.\n\nIn Default mode, strongly prefer making reasonable assumptions and executing the user's request rather than stopping to ask questions. If you absolutely must ask a question because the answer cannot be discovered from local context and a reasonable assumption would be risky, ask the user directly with a concise plain-text question. Never write a multiple choice question as a textual assistant message.\n"}},"effort":"medium","summary":"auto","user_instructions":"# AGENTS.md\n\n## Environment\n- Ask the user if you need to load a MOOSE conda environment, and if so, what the name of the conda environment is\n- If `./tmap8-opt` or `run_tests` throws an error, stop and ask the user\n- Pre-commit hooks handle all formatting and input file validation on every `git commit` — do not invoke `clang-format`, `black`, or `hit format` manually\n- `moose/framework/contrib/hit/hit check .i` is available to validate input files during development — use it before committing\n\n## Before writing any code or input file\n- Browse `doc/content/` to understand documentation standards and existing patterns before starting work\n- Before writing a new C++ class, look through existing MOOSE classes in the codebase to confirm expected syntax and patterns\n- Documentation in `doc/content/` may not accurately reflect current code behavior — once you identify a class to use in an input file, find its C++ implementation and read it to confirm the class does what you expect before writing the input file\n\n## C++ code\n- Every new class requires a MOOSE TestHarness test in `test/tests/` before committing\n- Every new class requires a MooseDocs page following existing TMAP8 doc structure\n- Never hardcode physical parameters — first check if it is already defined in `doc/content/source/utils/TMAP8PhysicalConstants`, and if not available, expose everything through `addParam`\n- Code is unit-agnostic; units live in input files only\n\n## Input files\n- Before writing an input file, look through existing MOOSE and TMAP8 classes to confirm object names and parameter syntax\n- Use `moose/framework/contrib/hit/hit check .i` to validate before committing\n- Use `./tmap8-opt -i .i` to run input files\n- Write parameter values in the units the reference source used; use the MOOSE units system for conversion — the units system is self-documenting and does not require inline comments\n- State the unit system at the top of every input file in a comment block\n\n## Testing\n- Run tests only when `.C`, `.h`, or `test/tests/` files change\n- Run only the affected module: `./run_tests -j --re `\n\n## Session log\n- Every session must be associated with a GitHub issue on `idaholab/TMAP8`; ask the user for the issue number at the start of the session if one is not provided, or create one if the user instructs you to\n- **SQA requirement:** When creating a GitHub issue with `gh`, you must use the appropriate template from `.github/ISSUE_TEMPLATE/`; read the available templates first, select the one that fits (e.g. `bug-report.md` for bugs, `feature-request.md` for new features or tasks), and populate all sections in the template body — passing a bare description without following the template structure is not acceptable\n- Before committing, copy the current session's `.jsonl` file into `doc/content/agent//`. For Claude Code sessions the file is the most recently modified `.jsonl` under `~/.claude/projects//`; for Codex sessions check the equivalent Codex session directory. Do not remove old session files already in that directory — append the new one alongside them.\n\n## Committing\n- Commit at minimum after: every input file that successfully runs, every test that passes or fails, and every new class added\n- If a test or run failed, commit the failure state first (include the full error message in the commit body), then commit the fix separately\n- Every commit must reference the associated GitHub issue (e.g. `Refs #` or `Closes #` as appropriate) in the commit message\n- **Every commit must include an updated copy of the session `.jsonl`** — before staging, copy the current session file from `~/.claude/projects//.jsonl` to `doc/content/agent//` and stage it; this is a critical SQA requirement. Do not remove session files already present in that directory — if multiple Claude/Codex sessions contribute to the same branch and issue, all session files must be kept.\n- Every commit must include these trailers:\n```\nRefs #\nAI-assisted: true\nAI-model: \nAI-version: \nCo-Authored-By: \n```\n\n## Pull requests\n- If the linked issue already contains a complete Reason/Design/Impact description, the PR body should contain only the closing reference (e.g. `Closes #`) — do not duplicate the issue content or leave template sections empty\n- If the PR introduces physics/modeling decisions, non-obvious AI reasoning, or tests not described in the issue, add those as a short addendum below the issue reference\n- Never merge autonomously\n\n## Never do\n- Modify existing passing tests without explicit user instruction\n- Modify the build system without explicit user instruction\n- Make physics modeling decisions without flagging them to the user\n- Suppress or bypass test failures\n\n\n## Skills\nA skill is a set of local instructions to follow that is stored in a `SKILL.md` file. Below is the list of skills that can be used. Each entry includes a name, description, and file path so you can open the source for full instructions when using a specific skill.\n### Available skills\n- openai-docs: Use when the user asks how to build with OpenAI products or APIs and needs up-to-date official documentation with citations, help choosing the latest model for a use case, or explicit GPT-5.4 upgrade and prompt-upgrade guidance; prioritize OpenAI docs MCP tools, use bundled references only as helper context, and restrict any fallback browsing to official OpenAI domains. (file: /Users/lindad/.codex/skills/.system/openai-docs/SKILL.md)\n- plugin-creator: Create and scaffold plugin directories for Codex with a required `.codex-plugin/plugin.json`, optional plugin folders/files, and baseline placeholders you can edit before publishing or testing. Use when Codex needs to create a new local plugin, add optional plugin structure, or generate or update repo-root `.agents/plugins/marketplace.json` entries for plugin ordering and availability metadata. (file: /Users/lindad/.codex/skills/.system/plugin-creator/SKILL.md)\n- skill-creator: Guide for creating effective skills. This skill should be used when users want to create a new skill (or update an existing skill) that extends Codex's capabilities with specialized knowledge, workflows, or tool integrations. (file: /Users/lindad/.codex/skills/.system/skill-creator/SKILL.md)\n- skill-installer: Install Codex skills into $CODEX_HOME/skills from a curated list or a GitHub repo path. Use when a user asks to list installable skills, install a curated skill, or install a skill from another repo (including private repos). (file: /Users/lindad/.codex/skills/.system/skill-installer/SKILL.md)\n### How to use skills\n- Discovery: The list above is the skills available in this session (name + description + file path). Skill bodies live on disk at the listed paths.\n- Trigger rules: If the user names a skill (with `$SkillName` or plain text) OR the task clearly matches a skill's description shown above, you must use that skill for that turn. Multiple mentions mean use them all. Do not carry skills across turns unless re-mentioned.\n- Missing/blocked: If a named skill isn't in the list or the path can't be read, say so briefly and continue with the best fallback.\n- How to use a skill (progressive disclosure):\n 1) After deciding to use a skill, open its `SKILL.md`. Read only enough to follow the workflow.\n 2) When `SKILL.md` references relative paths (e.g., `scripts/foo.py`), resolve them relative to the skill directory listed above first, and only consider other paths if needed.\n 3) If `SKILL.md` points to extra folders such as `references/`, load only the specific files needed for the request; don't bulk-load everything.\n 4) If `scripts/` exist, prefer running or patching them instead of retyping large code blocks.\n 5) If `assets/` or templates exist, reuse them instead of recreating from scratch.\n- Coordination and sequencing:\n - If multiple skills apply, choose the minimal set that covers the request and state the order you'll use them.\n - Announce which skill(s) you're using and why (one short line). If you skip an obvious skill, say why.\n- Context hygiene:\n - Keep context small: summarize long sections instead of pasting them; only load extra files when needed.\n - Avoid deep reference-chasing: prefer opening only files directly linked from `SKILL.md` unless you're blocked.\n - When variants exist (frameworks, providers, domains), pick only the relevant reference file(s) and note that choice.\n- Safety and fallback: If a skill can't be applied cleanly (missing files, unclear instructions), state the issue, pick the next-best approach, and continue.","truncation_policy":{"mode":"tokens","limit":10000}}} +{"timestamp":"2026-03-27T18:07:55.794Z","type":"event_msg","payload":{"type":"token_count","info":{"total_token_usage":{"input_tokens":251962,"cached_input_tokens":227840,"output_tokens":4923,"reasoning_output_tokens":999,"total_tokens":256885},"last_token_usage":{"input_tokens":28840,"cached_input_tokens":28160,"output_tokens":529,"reasoning_output_tokens":215,"total_tokens":29369},"model_context_window":258400},"rate_limits":{"limit_id":"codex","limit_name":null,"primary":{"used_percent":16.0,"window_minutes":300,"resets_at":1774643092},"secondary":{"used_percent":27.0,"window_minutes":10080,"resets_at":1774905636},"credits":null,"plan_type":"enterprise"}}} +{"timestamp":"2026-03-27T18:07:58.787Z","type":"event_msg","payload":{"type":"agent_reasoning","text":"**Summarizing git diff command**\n\nThe user's request seems straightforward: they want a summary of how to run the `git diff` command and see its output. I should clarify that `git diff` is used to show changes between commits, the working directory, and staged files. I might suggest that I can generate the command output by running it in the terminal myself, which would give the user a clear view of the differences they're looking for."}} +{"timestamp":"2026-03-27T18:07:58.787Z","type":"response_item","payload":{"type":"reasoning","summary":[{"type":"summary_text","text":"**Summarizing git diff command**\n\nThe user's request seems straightforward: they want a summary of how to run the `git diff` command and see its output. I should clarify that `git diff` is used to show changes between commits, the working directory, and staged files. I might suggest that I can generate the command output by running it in the terminal myself, which would give the user a clear view of the differences they're looking for."}],"content":null,"encrypted_content":"gAAAAABpxsd--zsXB1M1yN3rUMZ_GmppSNqCu5Y_-xbSQBXhCHujIcHB9T1jYGUF6i3jmpylTr16PpbpRlkNSTnk7dWNID6Za-OaA7cfa-wxMdolOMZGtbynfFMLOg5S-1VM9qhpac0k4gixRXNddB4quA24A50puZoYdmiFgs_dPhcLXbqaC9N6_GqNxCUTHwP01gobE76lThsPydCWeW8Ks0MvhV5yuLdmdDXpvxvEcvZkArHPmNyjsCjUUUnWr4oX3GJBkUbkLkxTbuGjx6d-tWhXCiOvjjFKS4mSgJRuPaLJFbE6NQ_5SFUXHPDBeDdmTSTDn2p977n5ImZ-DuHFjVVVoBp_K6-2j3kGbxMHijaPw0Na2q6ksmTy_q5zgFk86J1SkUMziQuRESOpL15iD2GKchydveJeqrmTORdk03TDNTKocDRDdHGWS_4pwdfSqsWYXih2nRmz6QCx_z8r4oCTd0ZeGqcVf9NPrLY3wFtUCIRT52RoWwdVBUBz_3d4gYbTstr9UXtIkt2nf6o4EjGFUK3H5LmUSchE7faHYz-hn4Xe9Aoy_SVxGagulNuBZOtwoxyxzy2LJotxiaHvgBASjds7Kn_r9iDqFmwZLmbEvFdQy4tPHRTjhvMMQXNYkj3BnsHHbNRdO8LFuhVKp2CJO-mmokOjdkESRRsbZhrIXtczQ6KwE-R0VV3qsg1dsd6fB04cZfRFuGvxooEHbzazqDinxWNhnR4rDo2_2pTtdYVB1Kmco8dQCdhiff-nJFqT8_gG6Ng0MIT6nCwX5AskWDVyf-FAmvbKuDOxYZLxUkZejoLjWJd7AdYJmB_OvH1F81TwqBjXb9PdlzI-7BU-Qgr_outCrKN_Ponf7xfAOSsEE9_ZO8aiDv0hm8LqHbAluuN9PIzE_UjWzUbtrKF76cErMRtMQIWOkDkSKY8gETmIXXsxBun4zSszIq1rvseOtMzXVpf0Jy9q7B5drD0IimmyuwzVU_zdeUtpSvbfmcL2gxk="}} +{"timestamp":"2026-03-27T18:07:58.824Z","type":"event_msg","payload":{"type":"agent_message","message":"I’m pulling the current diff so I can summarize the exact edits in the working tree, including the unrelated existing changes I did not touch.","phase":"commentary"}} +{"timestamp":"2026-03-27T18:07:58.824Z","type":"response_item","payload":{"type":"message","role":"assistant","content":[{"type":"output_text","text":"I’m pulling the current diff so I can summarize the exact edits in the working tree, including the unrelated existing changes I did not touch."}],"phase":"commentary"}} +{"timestamp":"2026-03-27T18:07:58.940Z","type":"response_item","payload":{"type":"function_call","name":"exec_command","arguments":"{\"cmd\":\"git diff -- . ':(exclude)moose'\",\"workdir\":\"/Users/lindad/projects/TMAP8\",\"max_output_tokens\":12000,\"yield_time_ms\":1000}","call_id":"call_6eio04N2Lpbz06RJLyod21vc"}} +{"timestamp":"2026-03-27T18:07:58.981Z","type":"event_msg","payload":{"type":"token_count","info":{"total_token_usage":{"input_tokens":280404,"cached_input_tokens":239744,"output_tokens":5041,"reasoning_output_tokens":1025,"total_tokens":285445},"last_token_usage":{"input_tokens":28442,"cached_input_tokens":11904,"output_tokens":118,"reasoning_output_tokens":26,"total_tokens":28560},"model_context_window":258400},"rate_limits":{"limit_id":"codex","limit_name":null,"primary":{"used_percent":16.0,"window_minutes":300,"resets_at":1774643092},"secondary":{"used_percent":27.0,"window_minutes":10080,"resets_at":1774905636},"credits":null,"plan_type":"enterprise"}}} +{"timestamp":"2026-03-27T18:07:59.088Z","type":"response_item","payload":{"type":"function_call_output","call_id":"call_6eio04N2Lpbz06RJLyod21vc","output":"Chunk ID: e7bf94\nWall time: 0.0529 seconds\nProcess exited with code 0\nOriginal token count: 2741\nOutput:\ndiff --git a/include/nodal_kernels/ReleasingNodalKernelDimensionless.h b/include/nodal_kernels/ReleasingNodalKernelDimensionless.h\nindex c7bca694..935ce572 100644\n--- a/include/nodal_kernels/ReleasingNodalKernelDimensionless.h\n+++ b/include/nodal_kernels/ReleasingNodalKernelDimensionless.h\n@@ -12,14 +12,14 @@\n \n /**\n * Releasing NodalKernel for a dimensionless trapped-species variable\n- * Ĉ_t = C_t / C_t_ref.\n+ * Ct_hat = C_t / C_t_ref.\n *\n * The residual is:\n- * R = +k_r_hat · exp(-E_r / T) · Ĉ_t\n+ * R = +k_r_hat * exp(-E_r / T) * Ct_hat\n *\n- * where k_r_hat = t_ref · α_r.\n+ * where k_r_hat = t_ref * alpha_r.\n *\n- * This is trivially dimensionless (O(k_r_hat)) because Ĉ_t is O(1).\n+ * This is trivially dimensionless (O(k_r_hat)) because Ct_hat is O(1).\n * No TMAPScaling / scaleResidual is used.\n */\n class ReleasingNodalKernelDimensionless : public NodalKernel\ndiff --git a/include/nodal_kernels/TrappingNodalKernelDimensionless.h b/include/nodal_kernels/TrappingNodalKernelDimensionless.h\nindex aa3ccc23..17a829bb 100644\n--- a/include/nodal_kernels/TrappingNodalKernelDimensionless.h\n+++ b/include/nodal_kernels/TrappingNodalKernelDimensionless.h\n@@ -23,18 +23,20 @@ typedef DualNumber> LocalDN;\n \n /**\n * Trapping NodalKernel that operates on a dimensionless trapped-species variable\n- * Ĉ_t = C_t / C_t_ref, where C_t_ref is the trap concentration reference scale.\n+ * Ct_hat = C_t / C_t_ref, where C_t_ref is the trap concentration reference scale.\n *\n * The residual is:\n- * R = -k_t_hat · exp(-E_t / T) · ((N·Ct0 - C_t_ref·Ĉ_t - Σ_j C_t_j) / C_t_ref) · Ĉ_m\n+ * R = -k_t_hat * exp(-E_t / T) * ((N * Ct0 - C_t_ref * Ct_hat - sum_j C_t_j) / C_t_ref) *\n+ * Cm_hat\n *\n * where:\n- * - Ĉ_t = dimensionless variable (this kernel's variable), O(1)\n- * - Ĉ_m = dimensionless mobile concentration. The coupled variable may be either physical\n+ * - Ct_hat = dimensionless variable (this kernel's variable), O(1)\n+ * - Cm_hat = dimensionless mobile concentration. The coupled variable may be either physical\n * or dimensionless, controlled by the mobile_variable_is_dimensionless flag.\n- * - C_t_j = C_t_ref_j * Ĉ_t_j, other trap species (dimensionless variable + reference, optional)\n+ * - C_t_j = C_t_ref_j * Ct_hat_j, other trap species (dimensionless variable + reference,\n+ * optional)\n * - C_t_ref = trap_concentration_reference parameter\n- * - k_t_hat = t_ref · α_t · C_m_ref / N\n+ * - k_t_hat = t_ref * alpha_t * C_m_ref / N\n *\n * No TMAPScaling / scaleResidual is used. The residual is naturally O(k_t_hat).\n */\n@@ -54,14 +56,15 @@ protected:\n const Real _trapping_energy;\n const Function & _Ct0;\n const Real _N;\n- /// C_t_ref: reference concentration for THIS trap (used to convert Ĉ_t back to physical)\n+ /// C_t_ref: reference concentration for THIS trap (used to convert Ct_hat back to physical)\n const Real _trap_concentration_reference;\n /// Dimensionless mobile concentration\n const VariableValue & _mobile_concentration;\n unsigned int _n_other_concs;\n- /// Dimensionless concentrations of other trap types (Ĉ_t_j = C_t_j / C_t_ref_j)\n+ /// Dimensionless concentrations of other trap types (Ct_hat_j = C_t_j / C_t_ref_j)\n std::vector _other_trapped_concentrations;\n- /// Reference concentrations C_t_ref_j for each other trap, to convert Ĉ_t_j → physical C_t_j\n+ /// Reference concentrations C_t_ref_j for each other trap, to convert Ct_hat_j -> physical\n+ /// C_t_j\n std::vector _other_trap_concentration_references;\n /// Variable numbers: [other_trap_0, ..., other_trap_n, this_trap, mobile]\n std::vector _var_numbers;\ndiff --git a/src/nodal_kernels/ReleasingNodalKernelDimensionless.C b/src/nodal_kernels/ReleasingNodalKernelDimensionless.C\nindex be83e457..e6b4da49 100644\n--- a/src/nodal_kernels/ReleasingNodalKernelDimensionless.C\n+++ b/src/nodal_kernels/ReleasingNodalKernelDimensionless.C\n@@ -16,9 +16,9 @@ ReleasingNodalKernelDimensionless::validParams()\n InputParameters params = NodalKernel::validParams();\n params.addClassDescription(\n \"Implements the release source term for a dimensionless trapped-species variable \"\n- \"Ĉ_t = C_t / C_t_ref. \"\n- \"The residual R = +k_r_hat · exp(-E_r / T) · Ĉ_t is naturally O(k_r_hat) \"\n- \"because Ĉ_t is O(1). No equation scaling is applied.\");\n+ \"Ct_hat = C_t / C_t_ref. \"\n+ \"The residual R = +k_r_hat * exp(-E_r / T) * Ct_hat is naturally O(k_r_hat) \"\n+ \"because Ct_hat is O(1). No equation scaling is applied.\");\n params.addRequiredParam(\"dimensionless_release_rate\",\n \"Dimensionless release rate k_r_hat = t_ref * alpha_r.\");\n params.addParam(\"detrapping_energy\", 0, \"The detrapping activation energy (K)\");\ndiff --git a/src/nodal_kernels/TrappingNodalKernelDimensionless.C b/src/nodal_kernels/TrappingNodalKernelDimensionless.C\nindex 4accd0f1..302b558a 100644\n--- a/src/nodal_kernels/TrappingNodalKernelDimensionless.C\n+++ b/src/nodal_kernels/TrappingNodalKernelDimensionless.C\n@@ -17,7 +17,7 @@ TrappingNodalKernelDimensionless::validParams()\n InputParameters params = NodalKernel::validParams();\n params.addClassDescription(\n \"Implements the trapping source term for a dimensionless trapped-species variable \"\n- \"Ĉ_t = C_t / C_t_ref. \"\n+ \"Ct_hat = C_t / C_t_ref. \"\n \"The mobile concentration may be either physical or dimensionless. \"\n \"No equation scaling is applied; the residual is O(k_t_hat).\");\n params.addRequiredParam(\n@@ -31,18 +31,19 @@ TrappingNodalKernelDimensionless::validParams()\n params.addRequiredParam(\n \"trap_concentration_reference\",\n \"Reference concentration C_t_ref for this trap species (same units as N). \"\n- \"Typically set to N * Ct0_max. The variable stores Ĉ_t = C_t / C_t_ref.\");\n+ \"Typically set to N * Ct0_max. The variable stores Ct_hat = C_t / C_t_ref.\");\n params.addRequiredCoupledVar(\n \"mobile_concentration\",\n \"The variable representing the dimensionless mobile concentration of solute particles.\");\n params.addCoupledVar(\"other_trapped_concentration_variables\",\n- \"Dimensionless trapped-concentration variables (Ĉ_t_j = C_t_j / C_t_ref_j) \"\n+ \"Dimensionless trapped-concentration variables (Ct_hat_j = C_t_j / \"\n+ \"C_t_ref_j) \"\n \"for other trap species that compete for the same trapping sites.\");\n params.addParam>(\n \"other_trap_concentration_references\",\n {},\n \"Reference concentrations C_t_ref_j for each variable listed in \"\n- \"other_trapped_concentration_variables, used to convert Ĉ_t_j back to physical C_t_j \"\n+ \"other_trapped_concentration_variables, used to convert Ct_hat_j back to physical C_t_j \"\n \"when computing available trapping sites. Must match in length.\");\n params.addRequiredCoupledVar(\"temperature\", \"The temperature (K)\");\n return params;\n@@ -97,7 +98,7 @@ Real\n TrappingNodalKernelDimensionless::computeQpResidual()\n {\n // Physical empty trapping sites for this trap type:\n- // N * Ct0(x) - C_t_ref * Ĉ_t - sum_j C_t_ref_j * Ĉ_t_j\n+ // N * Ct0(x) - C_t_ref * Ct_hat - sum_j C_t_ref_j * Ct_hat_j\n Real empty_trapping_sites = _Ct0.value(_t, (*_current_node)) * _N;\n empty_trapping_sites -= _u[_qp] * _trap_concentration_reference;\n for (MooseIndex(_n_other_concs) j = 0; j < _n_other_concs; ++j)\n@@ -121,7 +122,7 @@ TrappingNodalKernelDimensionless::ADHelper()\n // Compute empty trapping sites with dual-number tracking for AD Jacobian\n LocalDN empty_trapping_sites = _Ct0.value(_t, (*_current_node)) * _N;\n \n- // Other traps: dimensionless Ĉ_t_j, multiplied by C_t_ref_j to get physical units\n+ // Other traps: dimensionless Ct_hat_j, multiplied by C_t_ref_j to get physical units\n for (MooseIndex(_n_other_concs) i = 0; i < _n_other_concs; ++i)\n {\n LocalDN other_dn = (*_other_trapped_concentrations[i])[_qp];\n@@ -129,12 +130,12 @@ TrappingNodalKernelDimensionless::ADHelper()\n empty_trapping_sites -= other_dn * _other_trap_concentration_references[i];\n }\n \n- // This trap: variable is dimensionless Ĉ_t, multiply by C_t_ref to get physical\n+ // This trap: variable is dimensionless Ct_hat, multiply by C_t_ref to get physical\n LocalDN this_trap_dn = _u[_qp];\n this_trap_dn.derivatives().insert(_var_numbers[_n_other_concs]) = 1.;\n empty_trapping_sites -= this_trap_dn * _trap_concentration_reference;\n \n- // Mobile concentration in dimensionless form Ĉ_m\n+ // Mobile concentration in dimensionless form Cm_hat\n LocalDN mobile_dn = _mobile_concentration[_qp];\n mobile_dn.derivatives().insert(_var_numbers.back()) = 1.;\n \ndiff --git a/src/physics/SpeciesTrappingPhysics.C b/src/physics/SpeciesTrappingPhysics.C\nindex 64d905b2..78c6dace 100644\n--- a/src/physics/SpeciesTrappingPhysics.C\n+++ b/src/physics/SpeciesTrappingPhysics.C\n@@ -533,9 +533,9 @@ SpeciesTrappingPhysics::addFEKernels()\n const auto species_name = getSpeciesVariableName(c_i, s_j);\n const auto mobile_species_name = _mobile_species_names[c_i][s_j];\n \n- // Time derivative — plain TimeDerivativeNodalKernel suffices for both paths:\n- // • dimensionless path: variable IS Ĉ_t (O(1)), so dĈ_t/dt is correct as-is\n- // • physical path: variable IS C_t, no per-row scaling is applied here\n+ // Time derivative: plain TimeDerivativeNodalKernel suffices for both paths:\n+ // - dimensionless path: variable is Ct_hat (O(1)), so dCt_hat/dt is correct as-is\n+ // - physical path: variable is C_t, no per-row scaling is applied here\n if (isTransient())\n {\n const std::string kernel_type = \"TimeDerivativeNodalKernel\";\n@@ -600,7 +600,7 @@ SpeciesTrappingPhysics::addFEKernels()\n if (_use_dimensionless_species)\n {\n // Collect the reference concentration for each other trap species so the\n- // dimensionless kernel can convert Ĉ_t_j → physical C_t_j.\n+ // dimensionless kernel can convert Ct_hat_j -> physical C_t_j.\n std::vector other_refs;\n other_refs.reserve(copy_species.size());\n for (unsigned int k = 0; k < _species[c_i].size(); ++k)\n@@ -641,7 +641,7 @@ SpeciesTrappingPhysics::addFEKernels()\n params.set(\"variable\") = mobile_species_name;\n params.set>(\"v\") = {species_name};\n if (_use_dimensionless_species)\n- // Dimensionless path: add (C_t_ref_i / C_m_ref) * dĈ_t_i/dt.\n+ // Dimensionless path: add (C_t_ref_i / C_m_ref) * dCt_hat_i/dt.\n params.set(\"factor\") =\n trapConcentrationReference(c_i, s_j) / mobileConcentrationReference(c_i);\n else\n"}} +{"timestamp":"2026-03-27T18:07:59.089Z","type":"turn_context","payload":{"turn_id":"019d307b-3b1d-78b1-8645-95243b9cc9ea","cwd":"/Users/lindad/projects/TMAP8","approval_policy":"on-request","sandbox_policy":{"type":"workspace-write","network_access":false,"exclude_tmpdir_env_var":false,"exclude_slash_tmp":false},"model":"gpt-5.4","personality":"pragmatic","collaboration_mode":{"mode":"default","settings":{"model":"gpt-5.4","reasoning_effort":"medium","developer_instructions":"# Collaboration Mode: Default\n\nYou are now in Default mode. Any previous instructions for other modes (e.g. Plan mode) are no longer active.\n\nYour active mode changes only when new developer instructions with a different `...` change it; user requests or tool descriptions do not change mode by themselves. Known mode names are Default and Plan.\n\n## request_user_input availability\n\nThe `request_user_input` tool is unavailable in Default mode. If you call it while in Default mode, it will return an error.\n\nIn Default mode, strongly prefer making reasonable assumptions and executing the user's request rather than stopping to ask questions. If you absolutely must ask a question because the answer cannot be discovered from local context and a reasonable assumption would be risky, ask the user directly with a concise plain-text question. Never write a multiple choice question as a textual assistant message.\n"}},"effort":"medium","summary":"auto","user_instructions":"# AGENTS.md\n\n## Environment\n- Ask the user if you need to load a MOOSE conda environment, and if so, what the name of the conda environment is\n- If `./tmap8-opt` or `run_tests` throws an error, stop and ask the user\n- Pre-commit hooks handle all formatting and input file validation on every `git commit` — do not invoke `clang-format`, `black`, or `hit format` manually\n- `moose/framework/contrib/hit/hit check .i` is available to validate input files during development — use it before committing\n\n## Before writing any code or input file\n- Browse `doc/content/` to understand documentation standards and existing patterns before starting work\n- Before writing a new C++ class, look through existing MOOSE classes in the codebase to confirm expected syntax and patterns\n- Documentation in `doc/content/` may not accurately reflect current code behavior — once you identify a class to use in an input file, find its C++ implementation and read it to confirm the class does what you expect before writing the input file\n\n## C++ code\n- Every new class requires a MOOSE TestHarness test in `test/tests/` before committing\n- Every new class requires a MooseDocs page following existing TMAP8 doc structure\n- Never hardcode physical parameters — first check if it is already defined in `doc/content/source/utils/TMAP8PhysicalConstants`, and if not available, expose everything through `addParam`\n- Code is unit-agnostic; units live in input files only\n\n## Input files\n- Before writing an input file, look through existing MOOSE and TMAP8 classes to confirm object names and parameter syntax\n- Use `moose/framework/contrib/hit/hit check .i` to validate before committing\n- Use `./tmap8-opt -i .i` to run input files\n- Write parameter values in the units the reference source used; use the MOOSE units system for conversion — the units system is self-documenting and does not require inline comments\n- State the unit system at the top of every input file in a comment block\n\n## Testing\n- Run tests only when `.C`, `.h`, or `test/tests/` files change\n- Run only the affected module: `./run_tests -j --re `\n\n## Session log\n- Every session must be associated with a GitHub issue on `idaholab/TMAP8`; ask the user for the issue number at the start of the session if one is not provided, or create one if the user instructs you to\n- **SQA requirement:** When creating a GitHub issue with `gh`, you must use the appropriate template from `.github/ISSUE_TEMPLATE/`; read the available templates first, select the one that fits (e.g. `bug-report.md` for bugs, `feature-request.md` for new features or tasks), and populate all sections in the template body — passing a bare description without following the template structure is not acceptable\n- Before committing, copy the current session's `.jsonl` file into `doc/content/agent//`. For Claude Code sessions the file is the most recently modified `.jsonl` under `~/.claude/projects//`; for Codex sessions check the equivalent Codex session directory. Do not remove old session files already in that directory — append the new one alongside them.\n\n## Committing\n- Commit at minimum after: every input file that successfully runs, every test that passes or fails, and every new class added\n- If a test or run failed, commit the failure state first (include the full error message in the commit body), then commit the fix separately\n- Every commit must reference the associated GitHub issue (e.g. `Refs #` or `Closes #` as appropriate) in the commit message\n- **Every commit must include an updated copy of the session `.jsonl`** — before staging, copy the current session file from `~/.claude/projects//.jsonl` to `doc/content/agent//` and stage it; this is a critical SQA requirement. Do not remove session files already present in that directory — if multiple Claude/Codex sessions contribute to the same branch and issue, all session files must be kept.\n- Every commit must include these trailers:\n```\nRefs #\nAI-assisted: true\nAI-model: \nAI-version: \nCo-Authored-By: \n```\n\n## Pull requests\n- If the linked issue already contains a complete Reason/Design/Impact description, the PR body should contain only the closing reference (e.g. `Closes #`) — do not duplicate the issue content or leave template sections empty\n- If the PR introduces physics/modeling decisions, non-obvious AI reasoning, or tests not described in the issue, add those as a short addendum below the issue reference\n- Never merge autonomously\n\n## Never do\n- Modify existing passing tests without explicit user instruction\n- Modify the build system without explicit user instruction\n- Make physics modeling decisions without flagging them to the user\n- Suppress or bypass test failures\n\n\n## Skills\nA skill is a set of local instructions to follow that is stored in a `SKILL.md` file. Below is the list of skills that can be used. Each entry includes a name, description, and file path so you can open the source for full instructions when using a specific skill.\n### Available skills\n- openai-docs: Use when the user asks how to build with OpenAI products or APIs and needs up-to-date official documentation with citations, help choosing the latest model for a use case, or explicit GPT-5.4 upgrade and prompt-upgrade guidance; prioritize OpenAI docs MCP tools, use bundled references only as helper context, and restrict any fallback browsing to official OpenAI domains. (file: /Users/lindad/.codex/skills/.system/openai-docs/SKILL.md)\n- plugin-creator: Create and scaffold plugin directories for Codex with a required `.codex-plugin/plugin.json`, optional plugin folders/files, and baseline placeholders you can edit before publishing or testing. Use when Codex needs to create a new local plugin, add optional plugin structure, or generate or update repo-root `.agents/plugins/marketplace.json` entries for plugin ordering and availability metadata. (file: /Users/lindad/.codex/skills/.system/plugin-creator/SKILL.md)\n- skill-creator: Guide for creating effective skills. This skill should be used when users want to create a new skill (or update an existing skill) that extends Codex's capabilities with specialized knowledge, workflows, or tool integrations. (file: /Users/lindad/.codex/skills/.system/skill-creator/SKILL.md)\n- skill-installer: Install Codex skills into $CODEX_HOME/skills from a curated list or a GitHub repo path. Use when a user asks to list installable skills, install a curated skill, or install a skill from another repo (including private repos). (file: /Users/lindad/.codex/skills/.system/skill-installer/SKILL.md)\n### How to use skills\n- Discovery: The list above is the skills available in this session (name + description + file path). Skill bodies live on disk at the listed paths.\n- Trigger rules: If the user names a skill (with `$SkillName` or plain text) OR the task clearly matches a skill's description shown above, you must use that skill for that turn. Multiple mentions mean use them all. Do not carry skills across turns unless re-mentioned.\n- Missing/blocked: If a named skill isn't in the list or the path can't be read, say so briefly and continue with the best fallback.\n- How to use a skill (progressive disclosure):\n 1) After deciding to use a skill, open its `SKILL.md`. Read only enough to follow the workflow.\n 2) When `SKILL.md` references relative paths (e.g., `scripts/foo.py`), resolve them relative to the skill directory listed above first, and only consider other paths if needed.\n 3) If `SKILL.md` points to extra folders such as `references/`, load only the specific files needed for the request; don't bulk-load everything.\n 4) If `scripts/` exist, prefer running or patching them instead of retyping large code blocks.\n 5) If `assets/` or templates exist, reuse them instead of recreating from scratch.\n- Coordination and sequencing:\n - If multiple skills apply, choose the minimal set that covers the request and state the order you'll use them.\n - Announce which skill(s) you're using and why (one short line). If you skip an obvious skill, say why.\n- Context hygiene:\n - Keep context small: summarize long sections instead of pasting them; only load extra files when needed.\n - Avoid deep reference-chasing: prefer opening only files directly linked from `SKILL.md` unless you're blocked.\n - When variants exist (frameworks, providers, domains), pick only the relevant reference file(s) and note that choice.\n- Safety and fallback: If a skill can't be applied cleanly (missing files, unclear instructions), state the issue, pick the next-best approach, and continue.","truncation_policy":{"mode":"tokens","limit":10000}}} +{"timestamp":"2026-03-27T18:07:59.728Z","type":"response_item","payload":{"type":"message","role":"user","content":[{"type":"input_text","text":"\nThe user interrupted the previous turn on purpose. Any running unified exec processes were terminated. If any tools/commands were aborted, they may have partially executed; verify current state before retrying.\n"}]}} +{"timestamp":"2026-03-27T18:07:59.728Z","type":"event_msg","payload":{"type":"turn_aborted","turn_id":"019d307b-3b1d-78b1-8645-95243b9cc9ea","reason":"interrupted"}} +{"timestamp":"2026-03-27T18:09:43.901Z","type":"event_msg","payload":{"type":"task_started","turn_id":"019d307c-e1dc-7412-8cf3-27c7ed631d8b","model_context_window":258400,"collaboration_mode_kind":"default"}} +{"timestamp":"2026-03-27T18:09:43.902Z","type":"response_item","payload":{"type":"message","role":"user","content":[{"type":"input_text","text":"go ahead and commit those changes. Then next remove any reference to TMAPScaling or scaleResidual since those changes were reverted in this branch"}]}} +{"timestamp":"2026-03-27T18:09:43.902Z","type":"event_msg","payload":{"type":"user_message","message":"go ahead and commit those changes. Then next remove any reference to TMAPScaling or scaleResidual since those changes were reverted in this branch","images":[],"local_images":[],"text_elements":[]}} +{"timestamp":"2026-03-27T18:09:43.903Z","type":"turn_context","payload":{"turn_id":"019d307c-e1dc-7412-8cf3-27c7ed631d8b","cwd":"/Users/lindad/projects/TMAP8","approval_policy":"on-request","sandbox_policy":{"type":"workspace-write","network_access":false,"exclude_tmpdir_env_var":false,"exclude_slash_tmp":false},"model":"gpt-5.4","personality":"pragmatic","collaboration_mode":{"mode":"default","settings":{"model":"gpt-5.4","reasoning_effort":"medium","developer_instructions":"# Collaboration Mode: Default\n\nYou are now in Default mode. Any previous instructions for other modes (e.g. Plan mode) are no longer active.\n\nYour active mode changes only when new developer instructions with a different `...` change it; user requests or tool descriptions do not change mode by themselves. Known mode names are Default and Plan.\n\n## request_user_input availability\n\nThe `request_user_input` tool is unavailable in Default mode. If you call it while in Default mode, it will return an error.\n\nIn Default mode, strongly prefer making reasonable assumptions and executing the user's request rather than stopping to ask questions. If you absolutely must ask a question because the answer cannot be discovered from local context and a reasonable assumption would be risky, ask the user directly with a concise plain-text question. Never write a multiple choice question as a textual assistant message.\n"}},"effort":"medium","summary":"auto","user_instructions":"# AGENTS.md\n\n## Environment\n- Ask the user if you need to load a MOOSE conda environment, and if so, what the name of the conda environment is\n- If `./tmap8-opt` or `run_tests` throws an error, stop and ask the user\n- Pre-commit hooks handle all formatting and input file validation on every `git commit` — do not invoke `clang-format`, `black`, or `hit format` manually\n- `moose/framework/contrib/hit/hit check .i` is available to validate input files during development — use it before committing\n\n## Before writing any code or input file\n- Browse `doc/content/` to understand documentation standards and existing patterns before starting work\n- Before writing a new C++ class, look through existing MOOSE classes in the codebase to confirm expected syntax and patterns\n- Documentation in `doc/content/` may not accurately reflect current code behavior — once you identify a class to use in an input file, find its C++ implementation and read it to confirm the class does what you expect before writing the input file\n\n## C++ code\n- Every new class requires a MOOSE TestHarness test in `test/tests/` before committing\n- Every new class requires a MooseDocs page following existing TMAP8 doc structure\n- Never hardcode physical parameters — first check if it is already defined in `doc/content/source/utils/TMAP8PhysicalConstants`, and if not available, expose everything through `addParam`\n- Code is unit-agnostic; units live in input files only\n\n## Input files\n- Before writing an input file, look through existing MOOSE and TMAP8 classes to confirm object names and parameter syntax\n- Use `moose/framework/contrib/hit/hit check .i` to validate before committing\n- Use `./tmap8-opt -i .i` to run input files\n- Write parameter values in the units the reference source used; use the MOOSE units system for conversion — the units system is self-documenting and does not require inline comments\n- State the unit system at the top of every input file in a comment block\n\n## Testing\n- Run tests only when `.C`, `.h`, or `test/tests/` files change\n- Run only the affected module: `./run_tests -j --re `\n\n## Session log\n- Every session must be associated with a GitHub issue on `idaholab/TMAP8`; ask the user for the issue number at the start of the session if one is not provided, or create one if the user instructs you to\n- **SQA requirement:** When creating a GitHub issue with `gh`, you must use the appropriate template from `.github/ISSUE_TEMPLATE/`; read the available templates first, select the one that fits (e.g. `bug-report.md` for bugs, `feature-request.md` for new features or tasks), and populate all sections in the template body — passing a bare description without following the template structure is not acceptable\n- Before committing, copy the current session's `.jsonl` file into `doc/content/agent//`. For Claude Code sessions the file is the most recently modified `.jsonl` under `~/.claude/projects//`; for Codex sessions check the equivalent Codex session directory. Do not remove old session files already in that directory — append the new one alongside them.\n\n## Committing\n- Commit at minimum after: every input file that successfully runs, every test that passes or fails, and every new class added\n- If a test or run failed, commit the failure state first (include the full error message in the commit body), then commit the fix separately\n- Every commit must reference the associated GitHub issue (e.g. `Refs #` or `Closes #` as appropriate) in the commit message\n- **Every commit must include an updated copy of the session `.jsonl`** — before staging, copy the current session file from `~/.claude/projects//.jsonl` to `doc/content/agent//` and stage it; this is a critical SQA requirement. Do not remove session files already present in that directory — if multiple Claude/Codex sessions contribute to the same branch and issue, all session files must be kept.\n- Every commit must include these trailers:\n```\nRefs #\nAI-assisted: true\nAI-model: \nAI-version: \nCo-Authored-By: \n```\n\n## Pull requests\n- If the linked issue already contains a complete Reason/Design/Impact description, the PR body should contain only the closing reference (e.g. `Closes #`) — do not duplicate the issue content or leave template sections empty\n- If the PR introduces physics/modeling decisions, non-obvious AI reasoning, or tests not described in the issue, add those as a short addendum below the issue reference\n- Never merge autonomously\n\n## Never do\n- Modify existing passing tests without explicit user instruction\n- Modify the build system without explicit user instruction\n- Make physics modeling decisions without flagging them to the user\n- Suppress or bypass test failures\n\n\n## Skills\nA skill is a set of local instructions to follow that is stored in a `SKILL.md` file. Below is the list of skills that can be used. Each entry includes a name, description, and file path so you can open the source for full instructions when using a specific skill.\n### Available skills\n- openai-docs: Use when the user asks how to build with OpenAI products or APIs and needs up-to-date official documentation with citations, help choosing the latest model for a use case, or explicit GPT-5.4 upgrade and prompt-upgrade guidance; prioritize OpenAI docs MCP tools, use bundled references only as helper context, and restrict any fallback browsing to official OpenAI domains. (file: /Users/lindad/.codex/skills/.system/openai-docs/SKILL.md)\n- plugin-creator: Create and scaffold plugin directories for Codex with a required `.codex-plugin/plugin.json`, optional plugin folders/files, and baseline placeholders you can edit before publishing or testing. Use when Codex needs to create a new local plugin, add optional plugin structure, or generate or update repo-root `.agents/plugins/marketplace.json` entries for plugin ordering and availability metadata. (file: /Users/lindad/.codex/skills/.system/plugin-creator/SKILL.md)\n- skill-creator: Guide for creating effective skills. This skill should be used when users want to create a new skill (or update an existing skill) that extends Codex's capabilities with specialized knowledge, workflows, or tool integrations. (file: /Users/lindad/.codex/skills/.system/skill-creator/SKILL.md)\n- skill-installer: Install Codex skills into $CODEX_HOME/skills from a curated list or a GitHub repo path. Use when a user asks to list installable skills, install a curated skill, or install a skill from another repo (including private repos). (file: /Users/lindad/.codex/skills/.system/skill-installer/SKILL.md)\n### How to use skills\n- Discovery: The list above is the skills available in this session (name + description + file path). Skill bodies live on disk at the listed paths.\n- Trigger rules: If the user names a skill (with `$SkillName` or plain text) OR the task clearly matches a skill's description shown above, you must use that skill for that turn. Multiple mentions mean use them all. Do not carry skills across turns unless re-mentioned.\n- Missing/blocked: If a named skill isn't in the list or the path can't be read, say so briefly and continue with the best fallback.\n- How to use a skill (progressive disclosure):\n 1) After deciding to use a skill, open its `SKILL.md`. Read only enough to follow the workflow.\n 2) When `SKILL.md` references relative paths (e.g., `scripts/foo.py`), resolve them relative to the skill directory listed above first, and only consider other paths if needed.\n 3) If `SKILL.md` points to extra folders such as `references/`, load only the specific files needed for the request; don't bulk-load everything.\n 4) If `scripts/` exist, prefer running or patching them instead of retyping large code blocks.\n 5) If `assets/` or templates exist, reuse them instead of recreating from scratch.\n- Coordination and sequencing:\n - If multiple skills apply, choose the minimal set that covers the request and state the order you'll use them.\n - Announce which skill(s) you're using and why (one short line). If you skip an obvious skill, say why.\n- Context hygiene:\n - Keep context small: summarize long sections instead of pasting them; only load extra files when needed.\n - Avoid deep reference-chasing: prefer opening only files directly linked from `SKILL.md` unless you're blocked.\n - When variants exist (frameworks, providers, domains), pick only the relevant reference file(s) and note that choice.\n- Safety and fallback: If a skill can't be applied cleanly (missing files, unclear instructions), state the issue, pick the next-best approach, and continue.","truncation_policy":{"mode":"tokens","limit":10000}}} +{"timestamp":"2026-03-27T18:09:44.043Z","type":"event_msg","payload":{"type":"token_count","info":{"total_token_usage":{"input_tokens":280404,"cached_input_tokens":239744,"output_tokens":5041,"reasoning_output_tokens":1025,"total_tokens":285445},"last_token_usage":{"input_tokens":28442,"cached_input_tokens":11904,"output_tokens":118,"reasoning_output_tokens":26,"total_tokens":28560},"model_context_window":258400},"rate_limits":{"limit_id":"codex","limit_name":null,"primary":{"used_percent":17.0,"window_minutes":300,"resets_at":1774643092},"secondary":{"used_percent":28.0,"window_minutes":10080,"resets_at":1774905636},"credits":null,"plan_type":"enterprise"}}} +{"timestamp":"2026-03-27T18:09:50.871Z","type":"response_item","payload":{"type":"reasoning","summary":[],"content":null,"encrypted_content":"gAAAAABpxsfunNL-y9fV7-BZhVOwjSd9Lr2Bg_J8C6ddM1Uy4fHH5EieUwgTOnisZgcGXvXGvgnaTHHHiITE5DlfcoMVI4Kc0qU1aCU9xOj4I2KnU4-VPdolysQkHXZy7NVUX67Z81_tobzAkoyixcyCQ9RUEQMfT1955QTktGa56ktPGeV8ZewbQK9WM183xTK1UDoxdYTMZfTh9Rco7QM4lbqXXq7EDAyqqSeKJpeM1QBUTbg1Oz10C_ASAlxCPw8pcXWott2rwr7NSVxGuIZCuDmYXc2mDqhcU9rtRuNtlWFKAEi16D-EEhBgAArLUx4GMK_YAjaO7uWOimLKLAzNXlTo6c4SMZ3NlvL2DBysbjHM3pU_R_GxJe50X4DCSJY_3IuSt6HFAA0vQ4oKXTdwSbYazRQPNuf_zkWKSIKndA-9JZxd8TrGP5X1pRdtKjgy7MtorVVvdnvrh6SWcYwEC32XXntdHr5q1tlYUXQPqOYbPZRGHk931yqQGi1011CE9dstsodaCz7LBfT2omh8pr_1-tyK2BlI6i-aKWQn8GQSQK3lyvzfPkX9VNkpYxPzd3bDzqQthaYbexTuSRXqA7phn7sTRYAoH-7J5pCe4Jw8ymnlhOKwy4p053XEnPeZVdhZXWWHFfUhFdjptscu7JvNvpJJinTB2DiV11YRNZPbWoe_Ymcwhps87yxgWtEc_Iy59dAPytG-VCxcmGcFimyxfe6W4YPN_NTana47blaFhUkosdJRG4dI9VrhTBxbhWFkbWU9_t-j9nUnCBg75dC_bbu94evYZAC5duNdbbCIwEi2oB9jHhVwA0yoYv4eeFxnnW3on15Dieo7wnaWeam3kTUQ-UCuVV9-g6nkYgpWd374FoVuLsrf1q0qU_7esh354WWKN37kDzebav804-gDxd_1A73akbI4zfs0Hrm_ihFkPu1Cfwl1NCPS1V7meOYzxc-B3heaLOd2gVZ8sFEEOJ0bEFbBXgSAuV2tm0UCOeHZ2IwP_qahQQmNGtXTHle2IkFc9mmz6ntAHfSIEAcy0w04Haa474E6qQY8o4ukLEIMcj1vwzR9LYoiJqG3sIEhghZBh6FLoyV7NJZ-8Cx5ulwabekgiGuhANef4aGc-fAvLuqCWaxkmrnsAqsJ1t86WXAr3pBoAOnQ11eS8ZoANvhpWkRQdF7DjmUdAxFfrFGQLh4Kiy2PYUD3scbZ4sAGHVmyhbkGyZPri-6TKLnQXaOphq5r9I7-VMztWswEHbxuu1cUx9N3uzVBA7JKXJYNC6qzApkv6Ec7q6cUY8Gth0fpGQfO-1xQ_jCT5YEwZamKiphpcwBut8U_1-oKLmo26xCqzZ-9q6HV4mXxcvJnuhW8icWLNB7IYZYkjWwV7UquV0tA9QQx5Ql7653PJJDxDjm7DhP__13bP_wlkzIZ73rJJ87jfiCu0sZy-zEZpuQZateGSs00Q3k3by6UaRGrBPuJSiArDK8J_cCoOnR6tXF6OtNCPkVMHMlHsx3IqMyLMaPb3N_bS__pGEVzQWSdsvqH2l82HEq9POKO0hqqmLHozH77EuKARmYDoztoN5AgYJW8_TUnhAhO935pdIgVPcltOGNFJMu3x5z77wS8RwOLKdW-644MGS2jaIUalZfq9WY9dEQ45SjicdIvulTeR8Wjvu23-8kMXRNLqbPQOis3O1-xUC2r8NNFNYGYYb2OJZUPRa23W6bdCgjhiGGQPZNH9Vltrhocb6HyHRDeiokEqVKQveYRHtZJosp9NVhP12FUjGF5yNwg-K2NUJ4cD3fkEDNS5B2WGEnsu8Y6Jp9U69cSud185UNn2d5jYTfX9BVLPcsKrrh0Svs-J5eZ1pPnWyoJdTykmzF-bDiVNtIllUlVfINa5Jkx3NK5oIijXOiyBgezAia9bfwivV7aCxDrV1jgpEL0kSF5cAbOf9ruY5K7qWZLZbeT6W2RqWmY4Ic_BI-DEEfmwBquGhMXVwJDoMlguKLwP-y09ZRqN0m6KAkRKvL2MX7_hhxeQM4kfqgZ0LfPgfHLOpkzEB4EQGxYz5_Qh-VEqsc7Db13mNz-OMm-hxCTcsKReQzrQJynUdUe_9bCMeqWUUXsay3MezvVkd4GTbYsuaO-4tDYLkOZTg12PKBtGRbtaqIk7NYU5lo6vtme_esryVUAyyaojn8raBnNDLALbS0Vz3fJ_KcKyA=="}} +{"timestamp":"2026-03-27T18:09:52.829Z","type":"event_msg","payload":{"type":"agent_message","message":"I’m committing the ASCII cleanup first with the issue metadata and required session log copy, then I’ll remove the stale `TMAPScaling`/`scaleResidual` references and commit that separately.","phase":"commentary"}} +{"timestamp":"2026-03-27T18:09:52.829Z","type":"response_item","payload":{"type":"message","role":"assistant","content":[{"type":"output_text","text":"I’m committing the ASCII cleanup first with the issue metadata and required session log copy, then I’ll remove the stale `TMAPScaling`/`scaleResidual` references and commit that separately."}],"phase":"commentary"}} +{"timestamp":"2026-03-27T18:09:52.831Z","type":"response_item","payload":{"type":"function_call","name":"exec_command","arguments":"{\"cmd\":\"git status --short\",\"workdir\":\"/Users/lindad/projects/TMAP8\",\"max_output_tokens\":4000,\"yield_time_ms\":1000}","call_id":"call_yg3PUuxGLXNMGqdT5eaYqfU4"}} +{"timestamp":"2026-03-27T18:09:52.832Z","type":"response_item","payload":{"type":"function_call","name":"exec_command","arguments":"{\"cmd\":\"find \\\"$HOME/.codex\\\" -name '*.jsonl' -type f -print0 | xargs -0 ls -t | head -n 10\",\"workdir\":\"/Users/lindad/projects/TMAP8\",\"max_output_tokens\":4000,\"yield_time_ms\":1000}","call_id":"call_eu1BlRbuUJfyXvzKJ6pgHc7D"}} +{"timestamp":"2026-03-27T18:09:52.845Z","type":"response_item","payload":{"type":"function_call","name":"exec_command","arguments":"{\"cmd\":\"rg -n \\\"TMAPScaling|scaleResidual\\\" include src doc test --glob '!moose/**'\",\"workdir\":\"/Users/lindad/projects/TMAP8\",\"max_output_tokens\":8000,\"yield_time_ms\":1000}","call_id":"call_0kjjffbFlfbIhzlvzxxRwkMU"}} +{"timestamp":"2026-03-27T18:09:52.933Z","type":"event_msg","payload":{"type":"token_count","info":{"total_token_usage":{"input_tokens":312072,"cached_input_tokens":268160,"output_tokens":5492,"reasoning_output_tokens":1229,"total_tokens":317564},"last_token_usage":{"input_tokens":31668,"cached_input_tokens":28416,"output_tokens":451,"reasoning_output_tokens":204,"total_tokens":32119},"model_context_window":258400},"rate_limits":{"limit_id":"codex","limit_name":null,"primary":{"used_percent":17.0,"window_minutes":300,"resets_at":1774643092},"secondary":{"used_percent":28.0,"window_minutes":10080,"resets_at":1774905636},"credits":null,"plan_type":"enterprise"}}} +{"timestamp":"2026-03-27T18:09:53.997Z","type":"response_item","payload":{"type":"function_call_output","call_id":"call_yg3PUuxGLXNMGqdT5eaYqfU4","output":"Chunk ID: 88aa2d\nWall time: 1.0010 seconds\nProcess running with session ID 81753\nOriginal token count: 0\nOutput:\n"}} +{"timestamp":"2026-03-27T18:09:53.997Z","type":"response_item","payload":{"type":"function_call_output","call_id":"call_eu1BlRbuUJfyXvzKJ6pgHc7D","output":"Chunk ID: 265a7d\nWall time: 0.0722 seconds\nProcess exited with code 0\nOriginal token count: 261\nOutput:\n/Users/lindad/.codex/sessions/2026/03/27/rollout-2026-03-27T11-05-04-019d3078-9ee5-78f0-838a-4a4a79175713.jsonl\n/Users/lindad/.codex/history.jsonl\n/Users/lindad/.codex/sessions/2026/03/27/rollout-2026-03-27T09-49-58-019d3033-ddfc-7382-a576-a6415f36f333.jsonl\n/Users/lindad/.codex/sessions/2026/03/27/rollout-2026-03-27T09-43-17-019d302d-be8d-72d1-aa9e-108b177a673f.jsonl\n/Users/lindad/.codex/sessions/2026/03/27/rollout-2026-03-27T08-24-48-019d2fe5-e570-78d0-b3aa-1a3cba0f104a.jsonl\n/Users/lindad/.codex/sessions/2026/03/26/rollout-2026-03-26T11-35-46-019d2b6e-5cee-78d2-adbb-27e3dae9a360.jsonl\n/Users/lindad/.codex/sessions/2026/03/24/rollout-2026-03-24T16-56-59-019d2247-b9ee-76d2-9f5d-9f02a2fac5de.jsonl\n/Users/lindad/.codex/sessions/2026/03/26/rollout-2026-03-26T12-02-40-019d2b86-febf-7812-853f-69e1263b44a0.jsonl\n/Users/lindad/.codex/sessions/2026/03/26/rollout-2026-03-26T11-50-43-019d2b7c-0c9e-7e43-a16a-1a18e364a267.jsonl\n/Users/lindad/.codex/sessions/2026/03/26/rollout-2026-03-26T10-26-22-019d2b2e-d25f-72c3-a158-fd3d04c0ae71.jsonl\n"}} +{"timestamp":"2026-03-27T18:09:53.997Z","type":"response_item","payload":{"type":"function_call_output","call_id":"call_0kjjffbFlfbIhzlvzxxRwkMU","output":"Chunk ID: a2783f\nWall time: 0.0988 seconds\nProcess exited with code 0\nOriginal token count: 62\nOutput:\ninclude/nodal_kernels/TrappingNodalKernelDimensionless.h:41: * No TMAPScaling / scaleResidual is used. The residual is naturally O(k_t_hat).\ninclude/nodal_kernels/ReleasingNodalKernelDimensionless.h:23: * No TMAPScaling / scaleResidual is used.\n"}} +{"timestamp":"2026-03-27T18:09:53.997Z","type":"turn_context","payload":{"turn_id":"019d307c-e1dc-7412-8cf3-27c7ed631d8b","cwd":"/Users/lindad/projects/TMAP8","approval_policy":"on-request","sandbox_policy":{"type":"workspace-write","network_access":false,"exclude_tmpdir_env_var":false,"exclude_slash_tmp":false},"model":"gpt-5.4","personality":"pragmatic","collaboration_mode":{"mode":"default","settings":{"model":"gpt-5.4","reasoning_effort":"medium","developer_instructions":"# Collaboration Mode: Default\n\nYou are now in Default mode. Any previous instructions for other modes (e.g. Plan mode) are no longer active.\n\nYour active mode changes only when new developer instructions with a different `...` change it; user requests or tool descriptions do not change mode by themselves. Known mode names are Default and Plan.\n\n## request_user_input availability\n\nThe `request_user_input` tool is unavailable in Default mode. If you call it while in Default mode, it will return an error.\n\nIn Default mode, strongly prefer making reasonable assumptions and executing the user's request rather than stopping to ask questions. If you absolutely must ask a question because the answer cannot be discovered from local context and a reasonable assumption would be risky, ask the user directly with a concise plain-text question. Never write a multiple choice question as a textual assistant message.\n"}},"effort":"medium","summary":"auto","user_instructions":"# AGENTS.md\n\n## Environment\n- Ask the user if you need to load a MOOSE conda environment, and if so, what the name of the conda environment is\n- If `./tmap8-opt` or `run_tests` throws an error, stop and ask the user\n- Pre-commit hooks handle all formatting and input file validation on every `git commit` — do not invoke `clang-format`, `black`, or `hit format` manually\n- `moose/framework/contrib/hit/hit check .i` is available to validate input files during development — use it before committing\n\n## Before writing any code or input file\n- Browse `doc/content/` to understand documentation standards and existing patterns before starting work\n- Before writing a new C++ class, look through existing MOOSE classes in the codebase to confirm expected syntax and patterns\n- Documentation in `doc/content/` may not accurately reflect current code behavior — once you identify a class to use in an input file, find its C++ implementation and read it to confirm the class does what you expect before writing the input file\n\n## C++ code\n- Every new class requires a MOOSE TestHarness test in `test/tests/` before committing\n- Every new class requires a MooseDocs page following existing TMAP8 doc structure\n- Never hardcode physical parameters — first check if it is already defined in `doc/content/source/utils/TMAP8PhysicalConstants`, and if not available, expose everything through `addParam`\n- Code is unit-agnostic; units live in input files only\n\n## Input files\n- Before writing an input file, look through existing MOOSE and TMAP8 classes to confirm object names and parameter syntax\n- Use `moose/framework/contrib/hit/hit check .i` to validate before committing\n- Use `./tmap8-opt -i .i` to run input files\n- Write parameter values in the units the reference source used; use the MOOSE units system for conversion — the units system is self-documenting and does not require inline comments\n- State the unit system at the top of every input file in a comment block\n\n## Testing\n- Run tests only when `.C`, `.h`, or `test/tests/` files change\n- Run only the affected module: `./run_tests -j --re `\n\n## Session log\n- Every session must be associated with a GitHub issue on `idaholab/TMAP8`; ask the user for the issue number at the start of the session if one is not provided, or create one if the user instructs you to\n- **SQA requirement:** When creating a GitHub issue with `gh`, you must use the appropriate template from `.github/ISSUE_TEMPLATE/`; read the available templates first, select the one that fits (e.g. `bug-report.md` for bugs, `feature-request.md` for new features or tasks), and populate all sections in the template body — passing a bare description without following the template structure is not acceptable\n- Before committing, copy the current session's `.jsonl` file into `doc/content/agent//`. For Claude Code sessions the file is the most recently modified `.jsonl` under `~/.claude/projects//`; for Codex sessions check the equivalent Codex session directory. Do not remove old session files already in that directory — append the new one alongside them.\n\n## Committing\n- Commit at minimum after: every input file that successfully runs, every test that passes or fails, and every new class added\n- If a test or run failed, commit the failure state first (include the full error message in the commit body), then commit the fix separately\n- Every commit must reference the associated GitHub issue (e.g. `Refs #` or `Closes #` as appropriate) in the commit message\n- **Every commit must include an updated copy of the session `.jsonl`** — before staging, copy the current session file from `~/.claude/projects//.jsonl` to `doc/content/agent//` and stage it; this is a critical SQA requirement. Do not remove session files already present in that directory — if multiple Claude/Codex sessions contribute to the same branch and issue, all session files must be kept.\n- Every commit must include these trailers:\n```\nRefs #\nAI-assisted: true\nAI-model: \nAI-version: \nCo-Authored-By: \n```\n\n## Pull requests\n- If the linked issue already contains a complete Reason/Design/Impact description, the PR body should contain only the closing reference (e.g. `Closes #`) — do not duplicate the issue content or leave template sections empty\n- If the PR introduces physics/modeling decisions, non-obvious AI reasoning, or tests not described in the issue, add those as a short addendum below the issue reference\n- Never merge autonomously\n\n## Never do\n- Modify existing passing tests without explicit user instruction\n- Modify the build system without explicit user instruction\n- Make physics modeling decisions without flagging them to the user\n- Suppress or bypass test failures\n\n\n## Skills\nA skill is a set of local instructions to follow that is stored in a `SKILL.md` file. Below is the list of skills that can be used. Each entry includes a name, description, and file path so you can open the source for full instructions when using a specific skill.\n### Available skills\n- openai-docs: Use when the user asks how to build with OpenAI products or APIs and needs up-to-date official documentation with citations, help choosing the latest model for a use case, or explicit GPT-5.4 upgrade and prompt-upgrade guidance; prioritize OpenAI docs MCP tools, use bundled references only as helper context, and restrict any fallback browsing to official OpenAI domains. (file: /Users/lindad/.codex/skills/.system/openai-docs/SKILL.md)\n- plugin-creator: Create and scaffold plugin directories for Codex with a required `.codex-plugin/plugin.json`, optional plugin folders/files, and baseline placeholders you can edit before publishing or testing. Use when Codex needs to create a new local plugin, add optional plugin structure, or generate or update repo-root `.agents/plugins/marketplace.json` entries for plugin ordering and availability metadata. (file: /Users/lindad/.codex/skills/.system/plugin-creator/SKILL.md)\n- skill-creator: Guide for creating effective skills. This skill should be used when users want to create a new skill (or update an existing skill) that extends Codex's capabilities with specialized knowledge, workflows, or tool integrations. (file: /Users/lindad/.codex/skills/.system/skill-creator/SKILL.md)\n- skill-installer: Install Codex skills into $CODEX_HOME/skills from a curated list or a GitHub repo path. Use when a user asks to list installable skills, install a curated skill, or install a skill from another repo (including private repos). (file: /Users/lindad/.codex/skills/.system/skill-installer/SKILL.md)\n### How to use skills\n- Discovery: The list above is the skills available in this session (name + description + file path). Skill bodies live on disk at the listed paths.\n- Trigger rules: If the user names a skill (with `$SkillName` or plain text) OR the task clearly matches a skill's description shown above, you must use that skill for that turn. Multiple mentions mean use them all. Do not carry skills across turns unless re-mentioned.\n- Missing/blocked: If a named skill isn't in the list or the path can't be read, say so briefly and continue with the best fallback.\n- How to use a skill (progressive disclosure):\n 1) After deciding to use a skill, open its `SKILL.md`. Read only enough to follow the workflow.\n 2) When `SKILL.md` references relative paths (e.g., `scripts/foo.py`), resolve them relative to the skill directory listed above first, and only consider other paths if needed.\n 3) If `SKILL.md` points to extra folders such as `references/`, load only the specific files needed for the request; don't bulk-load everything.\n 4) If `scripts/` exist, prefer running or patching them instead of retyping large code blocks.\n 5) If `assets/` or templates exist, reuse them instead of recreating from scratch.\n- Coordination and sequencing:\n - If multiple skills apply, choose the minimal set that covers the request and state the order you'll use them.\n - Announce which skill(s) you're using and why (one short line). If you skip an obvious skill, say why.\n- Context hygiene:\n - Keep context small: summarize long sections instead of pasting them; only load extra files when needed.\n - Avoid deep reference-chasing: prefer opening only files directly linked from `SKILL.md` unless you're blocked.\n - When variants exist (frameworks, providers, domains), pick only the relevant reference file(s) and note that choice.\n- Safety and fallback: If a skill can't be applied cleanly (missing files, unclear instructions), state the issue, pick the next-best approach, and continue.","truncation_policy":{"mode":"tokens","limit":10000}}} +{"timestamp":"2026-03-27T18:10:01.018Z","type":"event_msg","payload":{"type":"agent_reasoning","text":"**Considering poll status**\n\nI’m thinking it might be necessary to check on the status of the poll session. This could involve gathering information about how things are going or whether any updates need to be communicated. It’s essential to stay aligned with any ongoing processes. I’ll ensure that I approach this carefully to deliver the most accurate and relevant information for everyone involved. Keeping tabs on these sorts of things can be quite helpful!"}} +{"timestamp":"2026-03-27T18:10:01.018Z","type":"response_item","payload":{"type":"reasoning","summary":[{"type":"summary_text","text":"**Considering poll status**\n\nI’m thinking it might be necessary to check on the status of the poll session. This could involve gathering information about how things are going or whether any updates need to be communicated. It’s essential to stay aligned with any ongoing processes. I’ll ensure that I approach this carefully to deliver the most accurate and relevant information for everyone involved. Keeping tabs on these sorts of things can be quite helpful!"}],"content":null,"encrypted_content":"gAAAAABpxsf54GvC4Duq3TIqS9JYb43dYk5576x3QobcKuT52TWfCpvMgoOBqvPW1P2OgZXYiUiSdMpDizTJWcyk33ffG0CZ6-cNxS55FxF8GS_LNUeEtexvu2Qi4Bv01y457h_Kb3NwKjkgeQ9H9cJngL0enDnILoEKT4ODo_Hd2TYnemrcl4IjnUIDqim9ZsrTCWNcKVjkN_-Hx0qM16qTLHp9RIqC6GHHlCPefbmD9MNzxsTAei-eDaZepTUxcPnsvmN2xjkettkMR1u405lx7XsXdHas6afLRZhEUbkBeuQC8yKm9O02V-zEAKiYo9HlreBzGRrguftA2q_ydrgiF39JZw48Jr5iY7e7DvOSu_Udk7le0-lCmhPv_c6QfIs41_g-koiQuhJFNJU06J8NWycJE6dvtH8euG-BXegAQwPLu6Dp8iE9puPMjqS67Sb3u6QTZ_3hSbtfyGnr2K_YdSBiFq0HIf1H4-WdX3lrXVXa0UjcsXkhs9GZMk-A56q8B5n-gzyf4hqv4Ibu5X8Id3YWO1xVDmFcQ5R4KK81yFPoSiSiu0qiLlRQwyj317hFOm1xUXoZqTFSSHmrYrauWVLvek8WrqUlepLM2obcF_EyLlO6ljZZASaWpUL6znyGBXauL2497Ba8dqOIe1g1aJsQSdBcOt2lS7ej7bixbu94lA73AeskgPrwCQ0wdPWj-KEDiKEeM6AlWQMX1fts50GoT0QI4iIBOTiTs11Da2ASoRWLr9QXv7P5_r2K314HxkM7G5wMMAVE7DinK9FgR6hadCrE4VSDuR8MMB-zgj1DOpZ_g6fySTtM147NV3R1QYh-VNCdu6kkL4YcApjBPzbtGXoJZs1TLBajkmJdB0VO-TZi85o="}} +{"timestamp":"2026-03-27T18:10:02.322Z","type":"event_msg","payload":{"type":"agent_message","message":"I found the active Codex session log and the only remaining `TMAPScaling`/`scaleResidual` references are the stale comments in the two dimensionless nodal kernel headers. I’m staging the ASCII cleanup with the session log now, then I’ll strip those references in a follow-up edit.","phase":"commentary"}} +{"timestamp":"2026-03-27T18:10:02.322Z","type":"response_item","payload":{"type":"message","role":"assistant","content":[{"type":"output_text","text":"I found the active Codex session log and the only remaining `TMAPScaling`/`scaleResidual` references are the stale comments in the two dimensionless nodal kernel headers. I’m staging the ASCII cleanup with the session log now, then I’ll strip those references in a follow-up edit."}],"phase":"commentary"}} +{"timestamp":"2026-03-27T18:10:02.326Z","type":"response_item","payload":{"type":"function_call","name":"exec_command","arguments":"{\"cmd\":\"git status --short\",\"workdir\":\"/Users/lindad/projects/TMAP8\",\"max_output_tokens\":4000,\"yield_time_ms\":1000}","call_id":"call_jnUsnKl5T2ql6eiCBu3MDxjh"}} +{"timestamp":"2026-03-27T18:10:02.327Z","type":"response_item","payload":{"type":"function_call","name":"exec_command","arguments":"{\"cmd\":\"ls doc/content/agent/200\",\"workdir\":\"/Users/lindad/projects/TMAP8\",\"max_output_tokens\":4000,\"yield_time_ms\":1000}","call_id":"call_2MnLvRg4tlrOiTZJzhHSNHaA"}} +{"timestamp":"2026-03-27T18:10:02.439Z","type":"event_msg","payload":{"type":"token_count","info":{"total_token_usage":{"input_tokens":345964,"cached_input_tokens":280192,"output_tokens":5683,"reasoning_output_tokens":1239,"total_tokens":351647},"last_token_usage":{"input_tokens":33892,"cached_input_tokens":12032,"output_tokens":191,"reasoning_output_tokens":10,"total_tokens":34083},"model_context_window":258400},"rate_limits":{"limit_id":"codex","limit_name":null,"primary":{"used_percent":17.0,"window_minutes":300,"resets_at":1774643092},"secondary":{"used_percent":28.0,"window_minutes":10080,"resets_at":1774905636},"credits":null,"plan_type":"enterprise"}}} +{"timestamp":"2026-03-27T18:10:03.490Z","type":"response_item","payload":{"type":"function_call_output","call_id":"call_jnUsnKl5T2ql6eiCBu3MDxjh","output":"Chunk ID: f3939f\nWall time: 1.0019 seconds\nProcess running with session ID 84663\nOriginal token count: 0\nOutput:\n"}} +{"timestamp":"2026-03-27T18:10:03.490Z","type":"response_item","payload":{"type":"function_call_output","call_id":"call_2MnLvRg4tlrOiTZJzhHSNHaA","output":"Chunk ID: aa6e34\nWall time: 0.0522 seconds\nProcess exited with code 1\nOriginal token count: 14\nOutput:\nls: doc/content/agent/200: No such file or directory\n"}} +{"timestamp":"2026-03-27T18:10:03.490Z","type":"turn_context","payload":{"turn_id":"019d307c-e1dc-7412-8cf3-27c7ed631d8b","cwd":"/Users/lindad/projects/TMAP8","approval_policy":"on-request","sandbox_policy":{"type":"workspace-write","network_access":false,"exclude_tmpdir_env_var":false,"exclude_slash_tmp":false},"model":"gpt-5.4","personality":"pragmatic","collaboration_mode":{"mode":"default","settings":{"model":"gpt-5.4","reasoning_effort":"medium","developer_instructions":"# Collaboration Mode: Default\n\nYou are now in Default mode. Any previous instructions for other modes (e.g. Plan mode) are no longer active.\n\nYour active mode changes only when new developer instructions with a different `...` change it; user requests or tool descriptions do not change mode by themselves. Known mode names are Default and Plan.\n\n## request_user_input availability\n\nThe `request_user_input` tool is unavailable in Default mode. If you call it while in Default mode, it will return an error.\n\nIn Default mode, strongly prefer making reasonable assumptions and executing the user's request rather than stopping to ask questions. If you absolutely must ask a question because the answer cannot be discovered from local context and a reasonable assumption would be risky, ask the user directly with a concise plain-text question. Never write a multiple choice question as a textual assistant message.\n"}},"effort":"medium","summary":"auto","user_instructions":"# AGENTS.md\n\n## Environment\n- Ask the user if you need to load a MOOSE conda environment, and if so, what the name of the conda environment is\n- If `./tmap8-opt` or `run_tests` throws an error, stop and ask the user\n- Pre-commit hooks handle all formatting and input file validation on every `git commit` — do not invoke `clang-format`, `black`, or `hit format` manually\n- `moose/framework/contrib/hit/hit check .i` is available to validate input files during development — use it before committing\n\n## Before writing any code or input file\n- Browse `doc/content/` to understand documentation standards and existing patterns before starting work\n- Before writing a new C++ class, look through existing MOOSE classes in the codebase to confirm expected syntax and patterns\n- Documentation in `doc/content/` may not accurately reflect current code behavior — once you identify a class to use in an input file, find its C++ implementation and read it to confirm the class does what you expect before writing the input file\n\n## C++ code\n- Every new class requires a MOOSE TestHarness test in `test/tests/` before committing\n- Every new class requires a MooseDocs page following existing TMAP8 doc structure\n- Never hardcode physical parameters — first check if it is already defined in `doc/content/source/utils/TMAP8PhysicalConstants`, and if not available, expose everything through `addParam`\n- Code is unit-agnostic; units live in input files only\n\n## Input files\n- Before writing an input file, look through existing MOOSE and TMAP8 classes to confirm object names and parameter syntax\n- Use `moose/framework/contrib/hit/hit check .i` to validate before committing\n- Use `./tmap8-opt -i .i` to run input files\n- Write parameter values in the units the reference source used; use the MOOSE units system for conversion — the units system is self-documenting and does not require inline comments\n- State the unit system at the top of every input file in a comment block\n\n## Testing\n- Run tests only when `.C`, `.h`, or `test/tests/` files change\n- Run only the affected module: `./run_tests -j --re `\n\n## Session log\n- Every session must be associated with a GitHub issue on `idaholab/TMAP8`; ask the user for the issue number at the start of the session if one is not provided, or create one if the user instructs you to\n- **SQA requirement:** When creating a GitHub issue with `gh`, you must use the appropriate template from `.github/ISSUE_TEMPLATE/`; read the available templates first, select the one that fits (e.g. `bug-report.md` for bugs, `feature-request.md` for new features or tasks), and populate all sections in the template body — passing a bare description without following the template structure is not acceptable\n- Before committing, copy the current session's `.jsonl` file into `doc/content/agent//`. For Claude Code sessions the file is the most recently modified `.jsonl` under `~/.claude/projects//`; for Codex sessions check the equivalent Codex session directory. Do not remove old session files already in that directory — append the new one alongside them.\n\n## Committing\n- Commit at minimum after: every input file that successfully runs, every test that passes or fails, and every new class added\n- If a test or run failed, commit the failure state first (include the full error message in the commit body), then commit the fix separately\n- Every commit must reference the associated GitHub issue (e.g. `Refs #` or `Closes #` as appropriate) in the commit message\n- **Every commit must include an updated copy of the session `.jsonl`** — before staging, copy the current session file from `~/.claude/projects//.jsonl` to `doc/content/agent//` and stage it; this is a critical SQA requirement. Do not remove session files already present in that directory — if multiple Claude/Codex sessions contribute to the same branch and issue, all session files must be kept.\n- Every commit must include these trailers:\n```\nRefs #\nAI-assisted: true\nAI-model: \nAI-version: \nCo-Authored-By: \n```\n\n## Pull requests\n- If the linked issue already contains a complete Reason/Design/Impact description, the PR body should contain only the closing reference (e.g. `Closes #`) — do not duplicate the issue content or leave template sections empty\n- If the PR introduces physics/modeling decisions, non-obvious AI reasoning, or tests not described in the issue, add those as a short addendum below the issue reference\n- Never merge autonomously\n\n## Never do\n- Modify existing passing tests without explicit user instruction\n- Modify the build system without explicit user instruction\n- Make physics modeling decisions without flagging them to the user\n- Suppress or bypass test failures\n\n\n## Skills\nA skill is a set of local instructions to follow that is stored in a `SKILL.md` file. Below is the list of skills that can be used. Each entry includes a name, description, and file path so you can open the source for full instructions when using a specific skill.\n### Available skills\n- openai-docs: Use when the user asks how to build with OpenAI products or APIs and needs up-to-date official documentation with citations, help choosing the latest model for a use case, or explicit GPT-5.4 upgrade and prompt-upgrade guidance; prioritize OpenAI docs MCP tools, use bundled references only as helper context, and restrict any fallback browsing to official OpenAI domains. (file: /Users/lindad/.codex/skills/.system/openai-docs/SKILL.md)\n- plugin-creator: Create and scaffold plugin directories for Codex with a required `.codex-plugin/plugin.json`, optional plugin folders/files, and baseline placeholders you can edit before publishing or testing. Use when Codex needs to create a new local plugin, add optional plugin structure, or generate or update repo-root `.agents/plugins/marketplace.json` entries for plugin ordering and availability metadata. (file: /Users/lindad/.codex/skills/.system/plugin-creator/SKILL.md)\n- skill-creator: Guide for creating effective skills. This skill should be used when users want to create a new skill (or update an existing skill) that extends Codex's capabilities with specialized knowledge, workflows, or tool integrations. (file: /Users/lindad/.codex/skills/.system/skill-creator/SKILL.md)\n- skill-installer: Install Codex skills into $CODEX_HOME/skills from a curated list or a GitHub repo path. Use when a user asks to list installable skills, install a curated skill, or install a skill from another repo (including private repos). (file: /Users/lindad/.codex/skills/.system/skill-installer/SKILL.md)\n### How to use skills\n- Discovery: The list above is the skills available in this session (name + description + file path). Skill bodies live on disk at the listed paths.\n- Trigger rules: If the user names a skill (with `$SkillName` or plain text) OR the task clearly matches a skill's description shown above, you must use that skill for that turn. Multiple mentions mean use them all. Do not carry skills across turns unless re-mentioned.\n- Missing/blocked: If a named skill isn't in the list or the path can't be read, say so briefly and continue with the best fallback.\n- How to use a skill (progressive disclosure):\n 1) After deciding to use a skill, open its `SKILL.md`. Read only enough to follow the workflow.\n 2) When `SKILL.md` references relative paths (e.g., `scripts/foo.py`), resolve them relative to the skill directory listed above first, and only consider other paths if needed.\n 3) If `SKILL.md` points to extra folders such as `references/`, load only the specific files needed for the request; don't bulk-load everything.\n 4) If `scripts/` exist, prefer running or patching them instead of retyping large code blocks.\n 5) If `assets/` or templates exist, reuse them instead of recreating from scratch.\n- Coordination and sequencing:\n - If multiple skills apply, choose the minimal set that covers the request and state the order you'll use them.\n - Announce which skill(s) you're using and why (one short line). If you skip an obvious skill, say why.\n- Context hygiene:\n - Keep context small: summarize long sections instead of pasting them; only load extra files when needed.\n - Avoid deep reference-chasing: prefer opening only files directly linked from `SKILL.md` unless you're blocked.\n - When variants exist (frameworks, providers, domains), pick only the relevant reference file(s) and note that choice.\n- Safety and fallback: If a skill can't be applied cleanly (missing files, unclear instructions), state the issue, pick the next-best approach, and continue.","truncation_policy":{"mode":"tokens","limit":10000}}} +{"timestamp":"2026-03-27T18:10:17.135Z","type":"event_msg","payload":{"type":"agent_reasoning","text":"**Planning file management and commits**\n\nI need to create a directory and copy a file using exec_command, then proceed with git add and commit. The approved prefixes for these commands are good to go. I’m a bit unsure if the commit can handle multiple lines. I’ll confirm the model name and version — it seems it could be “GPT-5 Codex” and I’ll go with “GPT-5” for the version. I shouldn't need to amend, and I’ll include a commit message with Refs #200. Now, let’s get started with mkdir, cp, git add, and commit!"}} +{"timestamp":"2026-03-27T18:10:17.135Z","type":"response_item","payload":{"type":"reasoning","summary":[{"type":"summary_text","text":"**Planning file management and commits**\n\nI need to create a directory and copy a file using exec_command, then proceed with git add and commit. The approved prefixes for these commands are good to go. I’m a bit unsure if the commit can handle multiple lines. I’ll confirm the model name and version — it seems it could be “GPT-5 Codex” and I’ll go with “GPT-5” for the version. I shouldn't need to amend, and I’ll include a commit message with Refs #200. Now, let’s get started with mkdir, cp, git add, and commit!"}],"content":null,"encrypted_content":"gAAAAABpxsgJUykhRHywMPHD-5ikEVaT8uVl2snaoDNVoEFOb8un3G3Fdvv4aj32p4X3HXDtG6bfbk0D1pbrJLKrR3uV2g6U17qrN-K4QKfwFag1hk7qz0rlvQ3VZTptQZkknYTbA10bQw06GoMTuOrv8js6aOgNDYcn9Mvn8CWP-78fpbEXE65zAGVtXlR6qeNTx1DdL9Oa7AOVypNlBPndSWtbTzRTK-cifgVXSCun5l6MZPg8lrgSeuNf7_3dejbmxHeSQc7C6s3FNgxro_5U6jrsWkqfoUuHlKHHQtO7ESClMj8HxWXksXTQ7NAHTwA-ImvEGsNKgD19efxwiLAU8egTW4YbHfqS2MOIOiuLDWenZnF8Z6p8Gip2pTFeB3FedaU3V4ygt2d-BrFsaOqDR--oDnVRehzyuORlz2rhJdbJRmDaE04OVm8VqFo9Z-FjEg2h1NX9g8SkDwRi0fz83Yz1Oi4dE_JD_PBotoB9xo6HRfU42LWB0T1ezyXD28N7vJuc6gYzz2dEWnhvHcxp7h9bB3NyDKx7O_yyL2R6vUL4V_LD_4L14LFrRyGiyboLf8BhvVe8K2RIksY4Dthakfv7Vc5Srtg_uyYYsTn_fSkzxO6bn_L4oAJawMi20re5Ol_UyUqIYXr2JJBHKHKqLEf9e7Xllk9V2wR7M_3GgHp0gN7jPuzGcWhEot_RefP4EV4Oo3Qukpbw12pxtl5OaDRm4YA8gUxwQYDq_Wp8UvxLeIbww8-jBcy4mMeN2uwN5pfBEAzk2vcUlCgmYooTaRiFLVoiPssQppzJC6YUBiTl0rNbyrPn72jprjxshj1Fa92bpvRiFAuHySljL6GS5IR_TyxBk6nsXp7Uv6BL1nJqAjhMb_9YgtrUpKW0l2HNQgDbCW8qxJjjinpfs9RAbkVEGSqT_akQ3eclgAnUh3uJRosYCmSAn_oi8MnlobAg4hj6t8ZyIP3PG1IEVH1f4eaxjuI6FDGuzgjZ_YlN7K2eajB7aUymignLCXvMww0K3dvIUWd9dIFI99peLgMz8uAS5JqxBBBoIqRc45hgb01uGYzRjX0-EBAX5R0D-82BMrfEb6OBLX0AFI3UXIBcvLKjNbipvoh-MAFJXRIReuKycAHQmF4yv205oID_nm5aYffNUUvTlptFBjfeodcjqaJ8Zk1RHabbbkx1_4G7yWw2Hd3Rqoq6Gfn_sCJ5pAKt9HWYqbKD5xa6J8nKu0SOgMSTOAzAtcyGgIh1SxY1Z_e07cOzglQiQ2fe-rquvDuLfkNe1woPrzsnJbCY5Zf721Tgi8-w-xgaYLqxqtVfwG7nerP6DV1r7PptmsY7VXOnwsOVhEMXd1h6RNyWJDt1uU4dV3l7ITiDe8mOTkhNbN5WT9Sk4iewDISxnEH88X6Foa0tTG3btcOvwG1H8V6cY1ddDRlhtKISvSx64tKdULdqMdYr7pn3MZkJyE64pEj5dYgdltP6XRL2cMJx9HbPocMB4j2we3ZcFkP_Ac30-1nTGcmZgr81FK2SpVyvC2TokHzpxm4LcPkjDEPJRyQxQwwsLjaG5KO4BNr0iey_5fVhLNnfOw1CypGVQbkxl8lGAig_UzjtdPBhrSPzOaWxeBgVubnupqgMmBQkALJ6del34t8mmXa5L_d0t9wfJET0kwgy4Et22FuxwfWg97GGvARI4ay5FdNQhNnvqni_wCbasdRCt-oT3Nsklc1BWbhCQMpwKQ-Z"}} +{"timestamp":"2026-03-27T18:10:17.335Z","type":"response_item","payload":{"type":"function_call","name":"exec_command","arguments":"{\"cmd\":\"mkdir -p doc/content/agent/200 && cp \\\"$HOME/.codex/sessions/2026/03/27/rollout-2026-03-27T11-05-04-019d3078-9ee5-78f0-838a-4a4a79175713.jsonl\\\" doc/content/agent/200/\",\"workdir\":\"/Users/lindad/projects/TMAP8\",\"max_output_tokens\":2000,\"yield_time_ms\":1000}","call_id":"call_tOgK2IP9GYLISubCWlY5viqn"}} +{"timestamp":"2026-03-27T18:10:17.384Z","type":"event_msg","payload":{"type":"token_count","info":{"total_token_usage":{"input_tokens":380152,"cached_input_tokens":314112,"output_tokens":5972,"reasoning_output_tokens":1407,"total_tokens":386124},"last_token_usage":{"input_tokens":34188,"cached_input_tokens":33920,"output_tokens":289,"reasoning_output_tokens":168,"total_tokens":34477},"model_context_window":258400},"rate_limits":{"limit_id":"codex","limit_name":null,"primary":{"used_percent":17.0,"window_minutes":300,"resets_at":1774643092},"secondary":{"used_percent":28.0,"window_minutes":10080,"resets_at":1774905636},"credits":null,"plan_type":"enterprise"}}} +{"timestamp":"2026-03-27T18:10:17.498Z","type":"response_item","payload":{"type":"function_call_output","call_id":"call_tOgK2IP9GYLISubCWlY5viqn","output":"Chunk ID: b0b223\nWall time: 0.0519 seconds\nProcess exited with code 0\nOriginal token count: 0\nOutput:\n"}} +{"timestamp":"2026-03-27T18:10:17.500Z","type":"turn_context","payload":{"turn_id":"019d307c-e1dc-7412-8cf3-27c7ed631d8b","cwd":"/Users/lindad/projects/TMAP8","approval_policy":"on-request","sandbox_policy":{"type":"workspace-write","network_access":false,"exclude_tmpdir_env_var":false,"exclude_slash_tmp":false},"model":"gpt-5.4","personality":"pragmatic","collaboration_mode":{"mode":"default","settings":{"model":"gpt-5.4","reasoning_effort":"medium","developer_instructions":"# Collaboration Mode: Default\n\nYou are now in Default mode. Any previous instructions for other modes (e.g. Plan mode) are no longer active.\n\nYour active mode changes only when new developer instructions with a different `...` change it; user requests or tool descriptions do not change mode by themselves. Known mode names are Default and Plan.\n\n## request_user_input availability\n\nThe `request_user_input` tool is unavailable in Default mode. If you call it while in Default mode, it will return an error.\n\nIn Default mode, strongly prefer making reasonable assumptions and executing the user's request rather than stopping to ask questions. If you absolutely must ask a question because the answer cannot be discovered from local context and a reasonable assumption would be risky, ask the user directly with a concise plain-text question. Never write a multiple choice question as a textual assistant message.\n"}},"effort":"medium","summary":"auto","user_instructions":"# AGENTS.md\n\n## Environment\n- Ask the user if you need to load a MOOSE conda environment, and if so, what the name of the conda environment is\n- If `./tmap8-opt` or `run_tests` throws an error, stop and ask the user\n- Pre-commit hooks handle all formatting and input file validation on every `git commit` — do not invoke `clang-format`, `black`, or `hit format` manually\n- `moose/framework/contrib/hit/hit check .i` is available to validate input files during development — use it before committing\n\n## Before writing any code or input file\n- Browse `doc/content/` to understand documentation standards and existing patterns before starting work\n- Before writing a new C++ class, look through existing MOOSE classes in the codebase to confirm expected syntax and patterns\n- Documentation in `doc/content/` may not accurately reflect current code behavior — once you identify a class to use in an input file, find its C++ implementation and read it to confirm the class does what you expect before writing the input file\n\n## C++ code\n- Every new class requires a MOOSE TestHarness test in `test/tests/` before committing\n- Every new class requires a MooseDocs page following existing TMAP8 doc structure\n- Never hardcode physical parameters — first check if it is already defined in `doc/content/source/utils/TMAP8PhysicalConstants`, and if not available, expose everything through `addParam`\n- Code is unit-agnostic; units live in input files only\n\n## Input files\n- Before writing an input file, look through existing MOOSE and TMAP8 classes to confirm object names and parameter syntax\n- Use `moose/framework/contrib/hit/hit check .i` to validate before committing\n- Use `./tmap8-opt -i .i` to run input files\n- Write parameter values in the units the reference source used; use the MOOSE units system for conversion — the units system is self-documenting and does not require inline comments\n- State the unit system at the top of every input file in a comment block\n\n## Testing\n- Run tests only when `.C`, `.h`, or `test/tests/` files change\n- Run only the affected module: `./run_tests -j --re `\n\n## Session log\n- Every session must be associated with a GitHub issue on `idaholab/TMAP8`; ask the user for the issue number at the start of the session if one is not provided, or create one if the user instructs you to\n- **SQA requirement:** When creating a GitHub issue with `gh`, you must use the appropriate template from `.github/ISSUE_TEMPLATE/`; read the available templates first, select the one that fits (e.g. `bug-report.md` for bugs, `feature-request.md` for new features or tasks), and populate all sections in the template body — passing a bare description without following the template structure is not acceptable\n- Before committing, copy the current session's `.jsonl` file into `doc/content/agent//`. For Claude Code sessions the file is the most recently modified `.jsonl` under `~/.claude/projects//`; for Codex sessions check the equivalent Codex session directory. Do not remove old session files already in that directory — append the new one alongside them.\n\n## Committing\n- Commit at minimum after: every input file that successfully runs, every test that passes or fails, and every new class added\n- If a test or run failed, commit the failure state first (include the full error message in the commit body), then commit the fix separately\n- Every commit must reference the associated GitHub issue (e.g. `Refs #` or `Closes #` as appropriate) in the commit message\n- **Every commit must include an updated copy of the session `.jsonl`** — before staging, copy the current session file from `~/.claude/projects//.jsonl` to `doc/content/agent//` and stage it; this is a critical SQA requirement. Do not remove session files already present in that directory — if multiple Claude/Codex sessions contribute to the same branch and issue, all session files must be kept.\n- Every commit must include these trailers:\n```\nRefs #\nAI-assisted: true\nAI-model: \nAI-version: \nCo-Authored-By: \n```\n\n## Pull requests\n- If the linked issue already contains a complete Reason/Design/Impact description, the PR body should contain only the closing reference (e.g. `Closes #`) — do not duplicate the issue content or leave template sections empty\n- If the PR introduces physics/modeling decisions, non-obvious AI reasoning, or tests not described in the issue, add those as a short addendum below the issue reference\n- Never merge autonomously\n\n## Never do\n- Modify existing passing tests without explicit user instruction\n- Modify the build system without explicit user instruction\n- Make physics modeling decisions without flagging them to the user\n- Suppress or bypass test failures\n\n\n## Skills\nA skill is a set of local instructions to follow that is stored in a `SKILL.md` file. Below is the list of skills that can be used. Each entry includes a name, description, and file path so you can open the source for full instructions when using a specific skill.\n### Available skills\n- openai-docs: Use when the user asks how to build with OpenAI products or APIs and needs up-to-date official documentation with citations, help choosing the latest model for a use case, or explicit GPT-5.4 upgrade and prompt-upgrade guidance; prioritize OpenAI docs MCP tools, use bundled references only as helper context, and restrict any fallback browsing to official OpenAI domains. (file: /Users/lindad/.codex/skills/.system/openai-docs/SKILL.md)\n- plugin-creator: Create and scaffold plugin directories for Codex with a required `.codex-plugin/plugin.json`, optional plugin folders/files, and baseline placeholders you can edit before publishing or testing. Use when Codex needs to create a new local plugin, add optional plugin structure, or generate or update repo-root `.agents/plugins/marketplace.json` entries for plugin ordering and availability metadata. (file: /Users/lindad/.codex/skills/.system/plugin-creator/SKILL.md)\n- skill-creator: Guide for creating effective skills. This skill should be used when users want to create a new skill (or update an existing skill) that extends Codex's capabilities with specialized knowledge, workflows, or tool integrations. (file: /Users/lindad/.codex/skills/.system/skill-creator/SKILL.md)\n- skill-installer: Install Codex skills into $CODEX_HOME/skills from a curated list or a GitHub repo path. Use when a user asks to list installable skills, install a curated skill, or install a skill from another repo (including private repos). (file: /Users/lindad/.codex/skills/.system/skill-installer/SKILL.md)\n### How to use skills\n- Discovery: The list above is the skills available in this session (name + description + file path). Skill bodies live on disk at the listed paths.\n- Trigger rules: If the user names a skill (with `$SkillName` or plain text) OR the task clearly matches a skill's description shown above, you must use that skill for that turn. Multiple mentions mean use them all. Do not carry skills across turns unless re-mentioned.\n- Missing/blocked: If a named skill isn't in the list or the path can't be read, say so briefly and continue with the best fallback.\n- How to use a skill (progressive disclosure):\n 1) After deciding to use a skill, open its `SKILL.md`. Read only enough to follow the workflow.\n 2) When `SKILL.md` references relative paths (e.g., `scripts/foo.py`), resolve them relative to the skill directory listed above first, and only consider other paths if needed.\n 3) If `SKILL.md` points to extra folders such as `references/`, load only the specific files needed for the request; don't bulk-load everything.\n 4) If `scripts/` exist, prefer running or patching them instead of retyping large code blocks.\n 5) If `assets/` or templates exist, reuse them instead of recreating from scratch.\n- Coordination and sequencing:\n - If multiple skills apply, choose the minimal set that covers the request and state the order you'll use them.\n - Announce which skill(s) you're using and why (one short line). If you skip an obvious skill, say why.\n- Context hygiene:\n - Keep context small: summarize long sections instead of pasting them; only load extra files when needed.\n - Avoid deep reference-chasing: prefer opening only files directly linked from `SKILL.md` unless you're blocked.\n - When variants exist (frameworks, providers, domains), pick only the relevant reference file(s) and note that choice.\n- Safety and fallback: If a skill can't be applied cleanly (missing files, unclear instructions), state the issue, pick the next-best approach, and continue.","truncation_policy":{"mode":"tokens","limit":10000}}} +{"timestamp":"2026-03-27T18:10:21.269Z","type":"response_item","payload":{"type":"function_call","name":"exec_command","arguments":"{\"cmd\":\"git add include/nodal_kernels/ReleasingNodalKernelDimensionless.h include/nodal_kernels/TrappingNodalKernelDimensionless.h src/nodal_kernels/ReleasingNodalKernelDimensionless.C src/nodal_kernels/TrappingNodalKernelDimensionless.C src/physics/SpeciesTrappingPhysics.C doc/content/agent/200/rollout-2026-03-27T11-05-04-019d3078-9ee5-78f0-838a-4a4a79175713.jsonl\",\"workdir\":\"/Users/lindad/projects/TMAP8\",\"max_output_tokens\":2000,\"yield_time_ms\":1000}","call_id":"call_W1dIHpBRm1gT42nJ5bOQTGTe"}} +{"timestamp":"2026-03-27T18:10:21.327Z","type":"event_msg","payload":{"type":"token_count","info":{"total_token_usage":{"input_tokens":414674,"cached_input_tokens":321792,"output_tokens":6129,"reasoning_output_tokens":1407,"total_tokens":420803},"last_token_usage":{"input_tokens":34522,"cached_input_tokens":7680,"output_tokens":157,"reasoning_output_tokens":0,"total_tokens":34679},"model_context_window":258400},"rate_limits":{"limit_id":"codex","limit_name":null,"primary":{"used_percent":17.0,"window_minutes":300,"resets_at":1774643092},"secondary":{"used_percent":28.0,"window_minutes":10080,"resets_at":1774905636},"credits":null,"plan_type":"enterprise"}}} +{"timestamp":"2026-03-27T18:10:21.414Z","type":"response_item","payload":{"type":"function_call_output","call_id":"call_W1dIHpBRm1gT42nJ5bOQTGTe","output":"Chunk ID: c72198\nWall time: 0.0518 seconds\nProcess exited with code 0\nOriginal token count: 0\nOutput:\n"}} +{"timestamp":"2026-03-27T18:10:21.415Z","type":"turn_context","payload":{"turn_id":"019d307c-e1dc-7412-8cf3-27c7ed631d8b","cwd":"/Users/lindad/projects/TMAP8","approval_policy":"on-request","sandbox_policy":{"type":"workspace-write","network_access":false,"exclude_tmpdir_env_var":false,"exclude_slash_tmp":false},"model":"gpt-5.4","personality":"pragmatic","collaboration_mode":{"mode":"default","settings":{"model":"gpt-5.4","reasoning_effort":"medium","developer_instructions":"# Collaboration Mode: Default\n\nYou are now in Default mode. Any previous instructions for other modes (e.g. Plan mode) are no longer active.\n\nYour active mode changes only when new developer instructions with a different `...` change it; user requests or tool descriptions do not change mode by themselves. Known mode names are Default and Plan.\n\n## request_user_input availability\n\nThe `request_user_input` tool is unavailable in Default mode. If you call it while in Default mode, it will return an error.\n\nIn Default mode, strongly prefer making reasonable assumptions and executing the user's request rather than stopping to ask questions. If you absolutely must ask a question because the answer cannot be discovered from local context and a reasonable assumption would be risky, ask the user directly with a concise plain-text question. Never write a multiple choice question as a textual assistant message.\n"}},"effort":"medium","summary":"auto","user_instructions":"# AGENTS.md\n\n## Environment\n- Ask the user if you need to load a MOOSE conda environment, and if so, what the name of the conda environment is\n- If `./tmap8-opt` or `run_tests` throws an error, stop and ask the user\n- Pre-commit hooks handle all formatting and input file validation on every `git commit` — do not invoke `clang-format`, `black`, or `hit format` manually\n- `moose/framework/contrib/hit/hit check .i` is available to validate input files during development — use it before committing\n\n## Before writing any code or input file\n- Browse `doc/content/` to understand documentation standards and existing patterns before starting work\n- Before writing a new C++ class, look through existing MOOSE classes in the codebase to confirm expected syntax and patterns\n- Documentation in `doc/content/` may not accurately reflect current code behavior — once you identify a class to use in an input file, find its C++ implementation and read it to confirm the class does what you expect before writing the input file\n\n## C++ code\n- Every new class requires a MOOSE TestHarness test in `test/tests/` before committing\n- Every new class requires a MooseDocs page following existing TMAP8 doc structure\n- Never hardcode physical parameters — first check if it is already defined in `doc/content/source/utils/TMAP8PhysicalConstants`, and if not available, expose everything through `addParam`\n- Code is unit-agnostic; units live in input files only\n\n## Input files\n- Before writing an input file, look through existing MOOSE and TMAP8 classes to confirm object names and parameter syntax\n- Use `moose/framework/contrib/hit/hit check .i` to validate before committing\n- Use `./tmap8-opt -i .i` to run input files\n- Write parameter values in the units the reference source used; use the MOOSE units system for conversion — the units system is self-documenting and does not require inline comments\n- State the unit system at the top of every input file in a comment block\n\n## Testing\n- Run tests only when `.C`, `.h`, or `test/tests/` files change\n- Run only the affected module: `./run_tests -j --re `\n\n## Session log\n- Every session must be associated with a GitHub issue on `idaholab/TMAP8`; ask the user for the issue number at the start of the session if one is not provided, or create one if the user instructs you to\n- **SQA requirement:** When creating a GitHub issue with `gh`, you must use the appropriate template from `.github/ISSUE_TEMPLATE/`; read the available templates first, select the one that fits (e.g. `bug-report.md` for bugs, `feature-request.md` for new features or tasks), and populate all sections in the template body — passing a bare description without following the template structure is not acceptable\n- Before committing, copy the current session's `.jsonl` file into `doc/content/agent//`. For Claude Code sessions the file is the most recently modified `.jsonl` under `~/.claude/projects//`; for Codex sessions check the equivalent Codex session directory. Do not remove old session files already in that directory — append the new one alongside them.\n\n## Committing\n- Commit at minimum after: every input file that successfully runs, every test that passes or fails, and every new class added\n- If a test or run failed, commit the failure state first (include the full error message in the commit body), then commit the fix separately\n- Every commit must reference the associated GitHub issue (e.g. `Refs #` or `Closes #` as appropriate) in the commit message\n- **Every commit must include an updated copy of the session `.jsonl`** — before staging, copy the current session file from `~/.claude/projects//.jsonl` to `doc/content/agent//` and stage it; this is a critical SQA requirement. Do not remove session files already present in that directory — if multiple Claude/Codex sessions contribute to the same branch and issue, all session files must be kept.\n- Every commit must include these trailers:\n```\nRefs #\nAI-assisted: true\nAI-model: \nAI-version: \nCo-Authored-By: \n```\n\n## Pull requests\n- If the linked issue already contains a complete Reason/Design/Impact description, the PR body should contain only the closing reference (e.g. `Closes #`) — do not duplicate the issue content or leave template sections empty\n- If the PR introduces physics/modeling decisions, non-obvious AI reasoning, or tests not described in the issue, add those as a short addendum below the issue reference\n- Never merge autonomously\n\n## Never do\n- Modify existing passing tests without explicit user instruction\n- Modify the build system without explicit user instruction\n- Make physics modeling decisions without flagging them to the user\n- Suppress or bypass test failures\n\n\n## Skills\nA skill is a set of local instructions to follow that is stored in a `SKILL.md` file. Below is the list of skills that can be used. Each entry includes a name, description, and file path so you can open the source for full instructions when using a specific skill.\n### Available skills\n- openai-docs: Use when the user asks how to build with OpenAI products or APIs and needs up-to-date official documentation with citations, help choosing the latest model for a use case, or explicit GPT-5.4 upgrade and prompt-upgrade guidance; prioritize OpenAI docs MCP tools, use bundled references only as helper context, and restrict any fallback browsing to official OpenAI domains. (file: /Users/lindad/.codex/skills/.system/openai-docs/SKILL.md)\n- plugin-creator: Create and scaffold plugin directories for Codex with a required `.codex-plugin/plugin.json`, optional plugin folders/files, and baseline placeholders you can edit before publishing or testing. Use when Codex needs to create a new local plugin, add optional plugin structure, or generate or update repo-root `.agents/plugins/marketplace.json` entries for plugin ordering and availability metadata. (file: /Users/lindad/.codex/skills/.system/plugin-creator/SKILL.md)\n- skill-creator: Guide for creating effective skills. This skill should be used when users want to create a new skill (or update an existing skill) that extends Codex's capabilities with specialized knowledge, workflows, or tool integrations. (file: /Users/lindad/.codex/skills/.system/skill-creator/SKILL.md)\n- skill-installer: Install Codex skills into $CODEX_HOME/skills from a curated list or a GitHub repo path. Use when a user asks to list installable skills, install a curated skill, or install a skill from another repo (including private repos). (file: /Users/lindad/.codex/skills/.system/skill-installer/SKILL.md)\n### How to use skills\n- Discovery: The list above is the skills available in this session (name + description + file path). Skill bodies live on disk at the listed paths.\n- Trigger rules: If the user names a skill (with `$SkillName` or plain text) OR the task clearly matches a skill's description shown above, you must use that skill for that turn. Multiple mentions mean use them all. Do not carry skills across turns unless re-mentioned.\n- Missing/blocked: If a named skill isn't in the list or the path can't be read, say so briefly and continue with the best fallback.\n- How to use a skill (progressive disclosure):\n 1) After deciding to use a skill, open its `SKILL.md`. Read only enough to follow the workflow.\n 2) When `SKILL.md` references relative paths (e.g., `scripts/foo.py`), resolve them relative to the skill directory listed above first, and only consider other paths if needed.\n 3) If `SKILL.md` points to extra folders such as `references/`, load only the specific files needed for the request; don't bulk-load everything.\n 4) If `scripts/` exist, prefer running or patching them instead of retyping large code blocks.\n 5) If `assets/` or templates exist, reuse them instead of recreating from scratch.\n- Coordination and sequencing:\n - If multiple skills apply, choose the minimal set that covers the request and state the order you'll use them.\n - Announce which skill(s) you're using and why (one short line). If you skip an obvious skill, say why.\n- Context hygiene:\n - Keep context small: summarize long sections instead of pasting them; only load extra files when needed.\n - Avoid deep reference-chasing: prefer opening only files directly linked from `SKILL.md` unless you're blocked.\n - When variants exist (frameworks, providers, domains), pick only the relevant reference file(s) and note that choice.\n- Safety and fallback: If a skill can't be applied cleanly (missing files, unclear instructions), state the issue, pick the next-best approach, and continue.","truncation_policy":{"mode":"tokens","limit":10000}}} +{"timestamp":"2026-03-27T18:10:22.867Z","type":"event_msg","payload":{"type":"agent_message","message":"I’ve staged the ASCII cleanup plus the required session artifact. Next step is the first commit, then I’ll edit out the obsolete scaling references and refresh the session log before the second commit.","phase":"commentary"}} +{"timestamp":"2026-03-27T18:10:22.867Z","type":"response_item","payload":{"type":"message","role":"assistant","content":[{"type":"output_text","text":"I’ve staged the ASCII cleanup plus the required session artifact. Next step is the first commit, then I’ll edit out the obsolete scaling references and refresh the session log before the second commit."}],"phase":"commentary"}} +{"timestamp":"2026-03-27T18:10:24.626Z","type":"response_item","payload":{"type":"function_call","name":"exec_command","arguments":"{\"cmd\":\"git commit -m \\\"Normalize recent non-ASCII text\\n\\nRefs #200\\nAI-assisted: true\\nAI-model: GPT-5 Codex\\nAI-version: GPT-5\\nCo-Authored-By: GPT-5 Codex \\\"\",\"workdir\":\"/Users/lindad/projects/TMAP8\",\"max_output_tokens\":12000,\"yield_time_ms\":1000}","call_id":"call_Srh22CfPNMGzvwZ07IuDV7uA"}} +{"timestamp":"2026-03-27T18:10:24.671Z","type":"event_msg","payload":{"type":"token_count","info":{"total_token_usage":{"input_tokens":449397,"cached_input_tokens":356096,"output_tokens":6278,"reasoning_output_tokens":1407,"total_tokens":455675},"last_token_usage":{"input_tokens":34723,"cached_input_tokens":34304,"output_tokens":149,"reasoning_output_tokens":0,"total_tokens":34872},"model_context_window":258400},"rate_limits":{"limit_id":"codex","limit_name":null,"primary":{"used_percent":17.0,"window_minutes":300,"resets_at":1774643092},"secondary":{"used_percent":28.0,"window_minutes":10080,"resets_at":1774905636},"credits":null,"plan_type":"enterprise"}}} +{"timestamp":"2026-03-27T18:10:24.810Z","type":"response_item","payload":{"type":"function_call_output","call_id":"call_Srh22CfPNMGzvwZ07IuDV7uA","output":"Chunk ID: 6664a4\nWall time: 0.0517 seconds\nProcess exited with code 0\nOriginal token count: 59\nOutput:\n[try-some-regularization 6a4086e5] Normalize recent non-ASCII text\n 6 files changed, 195 insertions(+), 29 deletions(-)\n create mode 100644 doc/content/agent/200/rollout-2026-03-27T11-05-04-019d3078-9ee5-78f0-838a-4a4a79175713.jsonl\n"}} +{"timestamp":"2026-03-27T18:10:24.811Z","type":"turn_context","payload":{"turn_id":"019d307c-e1dc-7412-8cf3-27c7ed631d8b","cwd":"/Users/lindad/projects/TMAP8","approval_policy":"on-request","sandbox_policy":{"type":"workspace-write","network_access":false,"exclude_tmpdir_env_var":false,"exclude_slash_tmp":false},"model":"gpt-5.4","personality":"pragmatic","collaboration_mode":{"mode":"default","settings":{"model":"gpt-5.4","reasoning_effort":"medium","developer_instructions":"# Collaboration Mode: Default\n\nYou are now in Default mode. Any previous instructions for other modes (e.g. Plan mode) are no longer active.\n\nYour active mode changes only when new developer instructions with a different `...` change it; user requests or tool descriptions do not change mode by themselves. Known mode names are Default and Plan.\n\n## request_user_input availability\n\nThe `request_user_input` tool is unavailable in Default mode. If you call it while in Default mode, it will return an error.\n\nIn Default mode, strongly prefer making reasonable assumptions and executing the user's request rather than stopping to ask questions. If you absolutely must ask a question because the answer cannot be discovered from local context and a reasonable assumption would be risky, ask the user directly with a concise plain-text question. Never write a multiple choice question as a textual assistant message.\n"}},"effort":"medium","summary":"auto","user_instructions":"# AGENTS.md\n\n## Environment\n- Ask the user if you need to load a MOOSE conda environment, and if so, what the name of the conda environment is\n- If `./tmap8-opt` or `run_tests` throws an error, stop and ask the user\n- Pre-commit hooks handle all formatting and input file validation on every `git commit` — do not invoke `clang-format`, `black`, or `hit format` manually\n- `moose/framework/contrib/hit/hit check .i` is available to validate input files during development — use it before committing\n\n## Before writing any code or input file\n- Browse `doc/content/` to understand documentation standards and existing patterns before starting work\n- Before writing a new C++ class, look through existing MOOSE classes in the codebase to confirm expected syntax and patterns\n- Documentation in `doc/content/` may not accurately reflect current code behavior — once you identify a class to use in an input file, find its C++ implementation and read it to confirm the class does what you expect before writing the input file\n\n## C++ code\n- Every new class requires a MOOSE TestHarness test in `test/tests/` before committing\n- Every new class requires a MooseDocs page following existing TMAP8 doc structure\n- Never hardcode physical parameters — first check if it is already defined in `doc/content/source/utils/TMAP8PhysicalConstants`, and if not available, expose everything through `addParam`\n- Code is unit-agnostic; units live in input files only\n\n## Input files\n- Before writing an input file, look through existing MOOSE and TMAP8 classes to confirm object names and parameter syntax\n- Use `moose/framework/contrib/hit/hit check .i` to validate before committing\n- Use `./tmap8-opt -i .i` to run input files\n- Write parameter values in the units the reference source used; use the MOOSE units system for conversion — the units system is self-documenting and does not require inline comments\n- State the unit system at the top of every input file in a comment block\n\n## Testing\n- Run tests only when `.C`, `.h`, or `test/tests/` files change\n- Run only the affected module: `./run_tests -j --re `\n\n## Session log\n- Every session must be associated with a GitHub issue on `idaholab/TMAP8`; ask the user for the issue number at the start of the session if one is not provided, or create one if the user instructs you to\n- **SQA requirement:** When creating a GitHub issue with `gh`, you must use the appropriate template from `.github/ISSUE_TEMPLATE/`; read the available templates first, select the one that fits (e.g. `bug-report.md` for bugs, `feature-request.md` for new features or tasks), and populate all sections in the template body — passing a bare description without following the template structure is not acceptable\n- Before committing, copy the current session's `.jsonl` file into `doc/content/agent//`. For Claude Code sessions the file is the most recently modified `.jsonl` under `~/.claude/projects//`; for Codex sessions check the equivalent Codex session directory. Do not remove old session files already in that directory — append the new one alongside them.\n\n## Committing\n- Commit at minimum after: every input file that successfully runs, every test that passes or fails, and every new class added\n- If a test or run failed, commit the failure state first (include the full error message in the commit body), then commit the fix separately\n- Every commit must reference the associated GitHub issue (e.g. `Refs #` or `Closes #` as appropriate) in the commit message\n- **Every commit must include an updated copy of the session `.jsonl`** — before staging, copy the current session file from `~/.claude/projects//.jsonl` to `doc/content/agent//` and stage it; this is a critical SQA requirement. Do not remove session files already present in that directory — if multiple Claude/Codex sessions contribute to the same branch and issue, all session files must be kept.\n- Every commit must include these trailers:\n```\nRefs #\nAI-assisted: true\nAI-model: \nAI-version: \nCo-Authored-By: \n```\n\n## Pull requests\n- If the linked issue already contains a complete Reason/Design/Impact description, the PR body should contain only the closing reference (e.g. `Closes #`) — do not duplicate the issue content or leave template sections empty\n- If the PR introduces physics/modeling decisions, non-obvious AI reasoning, or tests not described in the issue, add those as a short addendum below the issue reference\n- Never merge autonomously\n\n## Never do\n- Modify existing passing tests without explicit user instruction\n- Modify the build system without explicit user instruction\n- Make physics modeling decisions without flagging them to the user\n- Suppress or bypass test failures\n\n\n## Skills\nA skill is a set of local instructions to follow that is stored in a `SKILL.md` file. Below is the list of skills that can be used. Each entry includes a name, description, and file path so you can open the source for full instructions when using a specific skill.\n### Available skills\n- openai-docs: Use when the user asks how to build with OpenAI products or APIs and needs up-to-date official documentation with citations, help choosing the latest model for a use case, or explicit GPT-5.4 upgrade and prompt-upgrade guidance; prioritize OpenAI docs MCP tools, use bundled references only as helper context, and restrict any fallback browsing to official OpenAI domains. (file: /Users/lindad/.codex/skills/.system/openai-docs/SKILL.md)\n- plugin-creator: Create and scaffold plugin directories for Codex with a required `.codex-plugin/plugin.json`, optional plugin folders/files, and baseline placeholders you can edit before publishing or testing. Use when Codex needs to create a new local plugin, add optional plugin structure, or generate or update repo-root `.agents/plugins/marketplace.json` entries for plugin ordering and availability metadata. (file: /Users/lindad/.codex/skills/.system/plugin-creator/SKILL.md)\n- skill-creator: Guide for creating effective skills. This skill should be used when users want to create a new skill (or update an existing skill) that extends Codex's capabilities with specialized knowledge, workflows, or tool integrations. (file: /Users/lindad/.codex/skills/.system/skill-creator/SKILL.md)\n- skill-installer: Install Codex skills into $CODEX_HOME/skills from a curated list or a GitHub repo path. Use when a user asks to list installable skills, install a curated skill, or install a skill from another repo (including private repos). (file: /Users/lindad/.codex/skills/.system/skill-installer/SKILL.md)\n### How to use skills\n- Discovery: The list above is the skills available in this session (name + description + file path). Skill bodies live on disk at the listed paths.\n- Trigger rules: If the user names a skill (with `$SkillName` or plain text) OR the task clearly matches a skill's description shown above, you must use that skill for that turn. Multiple mentions mean use them all. Do not carry skills across turns unless re-mentioned.\n- Missing/blocked: If a named skill isn't in the list or the path can't be read, say so briefly and continue with the best fallback.\n- How to use a skill (progressive disclosure):\n 1) After deciding to use a skill, open its `SKILL.md`. Read only enough to follow the workflow.\n 2) When `SKILL.md` references relative paths (e.g., `scripts/foo.py`), resolve them relative to the skill directory listed above first, and only consider other paths if needed.\n 3) If `SKILL.md` points to extra folders such as `references/`, load only the specific files needed for the request; don't bulk-load everything.\n 4) If `scripts/` exist, prefer running or patching them instead of retyping large code blocks.\n 5) If `assets/` or templates exist, reuse them instead of recreating from scratch.\n- Coordination and sequencing:\n - If multiple skills apply, choose the minimal set that covers the request and state the order you'll use them.\n - Announce which skill(s) you're using and why (one short line). If you skip an obvious skill, say why.\n- Context hygiene:\n - Keep context small: summarize long sections instead of pasting them; only load extra files when needed.\n - Avoid deep reference-chasing: prefer opening only files directly linked from `SKILL.md` unless you're blocked.\n - When variants exist (frameworks, providers, domains), pick only the relevant reference file(s) and note that choice.\n- Safety and fallback: If a skill can't be applied cleanly (missing files, unclear instructions), state the issue, pick the next-best approach, and continue.","truncation_policy":{"mode":"tokens","limit":10000}}} +{"timestamp":"2026-03-27T18:10:26.141Z","type":"response_item","payload":{"type":"reasoning","summary":[],"content":null,"encrypted_content":"gAAAAABpxsgSTR9uG7UvTiidAZlUvIkv93juq6_QelpGePVzwWv_Jqyz7jNinRTuYL6Kc4mHkyRC2nu4-OPo0u4SwfKniWeHqFa0JF1fD2UyfgYIXcctu7vZ-hasA9RPci_Qd2jB13C17n9sMk-jbBgDf24wmi_MsTfiJ7k6ouLqK1-J5Gs6YPGAmcpaurg5zu9S5idkxP0Lj8YFnzIZATkLh088IykGbFUa6BdcllFkX2OQ-jcGjNidPj73spowJT_Y6lGXPMSs0ujTfZ8_QLMlOZdF8MuCthHYh9fai7ig2bLOQx2y-B8y7_GTgKndax2hxR_fhxVT0Uqm_Hb6Ff6Peu9GHwPe9RGm6Sp2NATRSSz4pIYh2FiV1efM9aDlkeTEZwDoKKjU9cQLIyCMgGu2hJfIZWAodEALLkElhUFJdgZa4ZWhLqLDyJDqSiUqBL_rc0g71tiE-pdijEPcgZcWzKPgiIFZfgzww_uEhXeGDbrJ6F0OtUIJ6wWFIkp54dKFcyB9AemHtYp5TfogabvJf7g8D5RzUFOCBjGwjrxJcRLTe9KEE9fhYITnNbz51yOPWgrW5yw3-Umw6PShTuvR_7jVhsAB9tLupeFeGwuD_lOALAnNsKeUens1Mta2dK-7DuX8JM0vx7jauCQD8gKbGkGGxkM_ePEUd8j_-mF9CjAIDdgqglysigKG09TpqsfPqrB09j_NTC1Vfm1CClo4V_tvZQvbQtVDGblitePcfOnsqBzdlzKq9-VGv0jkX5vRdMtDafTQcOlolOcnUUH7YICxvNoJzF9zIYKq0EVZtEBT3VI_wiXybcOowjxhX2Wn6nuJOvsvYYvF4OoRGGUp_1VP6qGiV7wnN4O9F6qVwMehrlywa0Iclip2IMjThmoKtFT7o-p9XJt-L7rNd5D9x9DdF1vOpGo5Z1Y8HbN1D5hRqLBAgMOvdU-LYBiSRMQvTyC24GrIRtjQwcKdyuKfsrIXIqmOZzo1xz_Eg2LoUIvfg6Pw6CGMg2QPqjWNV77VLbxELXrj"}} +{"timestamp":"2026-03-27T18:10:26.748Z","type":"event_msg","payload":{"type":"agent_message","message":"The first commit is in. I’m removing the two stale scaling references from the header comments now; those are the only remaining matches under `include/src/doc/test`.","phase":"commentary"}} +{"timestamp":"2026-03-27T18:10:26.748Z","type":"response_item","payload":{"type":"message","role":"assistant","content":[{"type":"output_text","text":"The first commit is in. I’m removing the two stale scaling references from the header comments now; those are the only remaining matches under `include/src/doc/test`."}],"phase":"commentary"}} +{"timestamp":"2026-03-27T18:10:29.442Z","type":"response_item","payload":{"type":"custom_tool_call","status":"completed","call_id":"call_1tSH2ucm9pBueScDIwQDrolH","name":"apply_patch","input":"*** Begin Patch\n*** Update File: /Users/lindad/projects/TMAP8/include/nodal_kernels/ReleasingNodalKernelDimensionless.h\n@@\n- * No TMAPScaling / scaleResidual is used.\n */\n class ReleasingNodalKernelDimensionless : public NodalKernel\n*** Update File: /Users/lindad/projects/TMAP8/include/nodal_kernels/TrappingNodalKernelDimensionless.h\n@@\n- * No TMAPScaling / scaleResidual is used. The residual is naturally O(k_t_hat).\n+ * The residual is naturally O(k_t_hat).\n */\n class TrappingNodalKernelDimensionless : public NodalKernel\n*** End Patch\n"}} +{"timestamp":"2026-03-27T18:10:29.484Z","type":"event_msg","payload":{"type":"token_count","info":{"total_token_usage":{"input_tokens":484408,"cached_input_tokens":390912,"output_tokens":6506,"reasoning_output_tokens":1439,"total_tokens":490914},"last_token_usage":{"input_tokens":35011,"cached_input_tokens":34816,"output_tokens":228,"reasoning_output_tokens":32,"total_tokens":35239},"model_context_window":258400},"rate_limits":{"limit_id":"codex","limit_name":null,"primary":{"used_percent":17.0,"window_minutes":300,"resets_at":1774643092},"secondary":{"used_percent":28.0,"window_minutes":10080,"resets_at":1774905636},"credits":null,"plan_type":"enterprise"}}} +{"timestamp":"2026-03-27T18:10:29.672Z","type":"response_item","payload":{"type":"custom_tool_call_output","call_id":"call_1tSH2ucm9pBueScDIwQDrolH","output":"{\"output\":\"Success. Updated the following files:\\nM /Users/lindad/projects/TMAP8/include/nodal_kernels/ReleasingNodalKernelDimensionless.h\\nM /Users/lindad/projects/TMAP8/include/nodal_kernels/TrappingNodalKernelDimensionless.h\\n\",\"metadata\":{\"exit_code\":0,\"duration_seconds\":0.1}}"}} +{"timestamp":"2026-03-27T18:10:29.673Z","type":"turn_context","payload":{"turn_id":"019d307c-e1dc-7412-8cf3-27c7ed631d8b","cwd":"/Users/lindad/projects/TMAP8","approval_policy":"on-request","sandbox_policy":{"type":"workspace-write","network_access":false,"exclude_tmpdir_env_var":false,"exclude_slash_tmp":false},"model":"gpt-5.4","personality":"pragmatic","collaboration_mode":{"mode":"default","settings":{"model":"gpt-5.4","reasoning_effort":"medium","developer_instructions":"# Collaboration Mode: Default\n\nYou are now in Default mode. Any previous instructions for other modes (e.g. Plan mode) are no longer active.\n\nYour active mode changes only when new developer instructions with a different `...` change it; user requests or tool descriptions do not change mode by themselves. Known mode names are Default and Plan.\n\n## request_user_input availability\n\nThe `request_user_input` tool is unavailable in Default mode. If you call it while in Default mode, it will return an error.\n\nIn Default mode, strongly prefer making reasonable assumptions and executing the user's request rather than stopping to ask questions. If you absolutely must ask a question because the answer cannot be discovered from local context and a reasonable assumption would be risky, ask the user directly with a concise plain-text question. Never write a multiple choice question as a textual assistant message.\n"}},"effort":"medium","summary":"auto","user_instructions":"# AGENTS.md\n\n## Environment\n- Ask the user if you need to load a MOOSE conda environment, and if so, what the name of the conda environment is\n- If `./tmap8-opt` or `run_tests` throws an error, stop and ask the user\n- Pre-commit hooks handle all formatting and input file validation on every `git commit` — do not invoke `clang-format`, `black`, or `hit format` manually\n- `moose/framework/contrib/hit/hit check .i` is available to validate input files during development — use it before committing\n\n## Before writing any code or input file\n- Browse `doc/content/` to understand documentation standards and existing patterns before starting work\n- Before writing a new C++ class, look through existing MOOSE classes in the codebase to confirm expected syntax and patterns\n- Documentation in `doc/content/` may not accurately reflect current code behavior — once you identify a class to use in an input file, find its C++ implementation and read it to confirm the class does what you expect before writing the input file\n\n## C++ code\n- Every new class requires a MOOSE TestHarness test in `test/tests/` before committing\n- Every new class requires a MooseDocs page following existing TMAP8 doc structure\n- Never hardcode physical parameters — first check if it is already defined in `doc/content/source/utils/TMAP8PhysicalConstants`, and if not available, expose everything through `addParam`\n- Code is unit-agnostic; units live in input files only\n\n## Input files\n- Before writing an input file, look through existing MOOSE and TMAP8 classes to confirm object names and parameter syntax\n- Use `moose/framework/contrib/hit/hit check .i` to validate before committing\n- Use `./tmap8-opt -i .i` to run input files\n- Write parameter values in the units the reference source used; use the MOOSE units system for conversion — the units system is self-documenting and does not require inline comments\n- State the unit system at the top of every input file in a comment block\n\n## Testing\n- Run tests only when `.C`, `.h`, or `test/tests/` files change\n- Run only the affected module: `./run_tests -j --re `\n\n## Session log\n- Every session must be associated with a GitHub issue on `idaholab/TMAP8`; ask the user for the issue number at the start of the session if one is not provided, or create one if the user instructs you to\n- **SQA requirement:** When creating a GitHub issue with `gh`, you must use the appropriate template from `.github/ISSUE_TEMPLATE/`; read the available templates first, select the one that fits (e.g. `bug-report.md` for bugs, `feature-request.md` for new features or tasks), and populate all sections in the template body — passing a bare description without following the template structure is not acceptable\n- Before committing, copy the current session's `.jsonl` file into `doc/content/agent//`. For Claude Code sessions the file is the most recently modified `.jsonl` under `~/.claude/projects//`; for Codex sessions check the equivalent Codex session directory. Do not remove old session files already in that directory — append the new one alongside them.\n\n## Committing\n- Commit at minimum after: every input file that successfully runs, every test that passes or fails, and every new class added\n- If a test or run failed, commit the failure state first (include the full error message in the commit body), then commit the fix separately\n- Every commit must reference the associated GitHub issue (e.g. `Refs #` or `Closes #` as appropriate) in the commit message\n- **Every commit must include an updated copy of the session `.jsonl`** — before staging, copy the current session file from `~/.claude/projects//.jsonl` to `doc/content/agent//` and stage it; this is a critical SQA requirement. Do not remove session files already present in that directory — if multiple Claude/Codex sessions contribute to the same branch and issue, all session files must be kept.\n- Every commit must include these trailers:\n```\nRefs #\nAI-assisted: true\nAI-model: \nAI-version: \nCo-Authored-By: \n```\n\n## Pull requests\n- If the linked issue already contains a complete Reason/Design/Impact description, the PR body should contain only the closing reference (e.g. `Closes #`) — do not duplicate the issue content or leave template sections empty\n- If the PR introduces physics/modeling decisions, non-obvious AI reasoning, or tests not described in the issue, add those as a short addendum below the issue reference\n- Never merge autonomously\n\n## Never do\n- Modify existing passing tests without explicit user instruction\n- Modify the build system without explicit user instruction\n- Make physics modeling decisions without flagging them to the user\n- Suppress or bypass test failures\n\n\n## Skills\nA skill is a set of local instructions to follow that is stored in a `SKILL.md` file. Below is the list of skills that can be used. Each entry includes a name, description, and file path so you can open the source for full instructions when using a specific skill.\n### Available skills\n- openai-docs: Use when the user asks how to build with OpenAI products or APIs and needs up-to-date official documentation with citations, help choosing the latest model for a use case, or explicit GPT-5.4 upgrade and prompt-upgrade guidance; prioritize OpenAI docs MCP tools, use bundled references only as helper context, and restrict any fallback browsing to official OpenAI domains. (file: /Users/lindad/.codex/skills/.system/openai-docs/SKILL.md)\n- plugin-creator: Create and scaffold plugin directories for Codex with a required `.codex-plugin/plugin.json`, optional plugin folders/files, and baseline placeholders you can edit before publishing or testing. Use when Codex needs to create a new local plugin, add optional plugin structure, or generate or update repo-root `.agents/plugins/marketplace.json` entries for plugin ordering and availability metadata. (file: /Users/lindad/.codex/skills/.system/plugin-creator/SKILL.md)\n- skill-creator: Guide for creating effective skills. This skill should be used when users want to create a new skill (or update an existing skill) that extends Codex's capabilities with specialized knowledge, workflows, or tool integrations. (file: /Users/lindad/.codex/skills/.system/skill-creator/SKILL.md)\n- skill-installer: Install Codex skills into $CODEX_HOME/skills from a curated list or a GitHub repo path. Use when a user asks to list installable skills, install a curated skill, or install a skill from another repo (including private repos). (file: /Users/lindad/.codex/skills/.system/skill-installer/SKILL.md)\n### How to use skills\n- Discovery: The list above is the skills available in this session (name + description + file path). Skill bodies live on disk at the listed paths.\n- Trigger rules: If the user names a skill (with `$SkillName` or plain text) OR the task clearly matches a skill's description shown above, you must use that skill for that turn. Multiple mentions mean use them all. Do not carry skills across turns unless re-mentioned.\n- Missing/blocked: If a named skill isn't in the list or the path can't be read, say so briefly and continue with the best fallback.\n- How to use a skill (progressive disclosure):\n 1) After deciding to use a skill, open its `SKILL.md`. Read only enough to follow the workflow.\n 2) When `SKILL.md` references relative paths (e.g., `scripts/foo.py`), resolve them relative to the skill directory listed above first, and only consider other paths if needed.\n 3) If `SKILL.md` points to extra folders such as `references/`, load only the specific files needed for the request; don't bulk-load everything.\n 4) If `scripts/` exist, prefer running or patching them instead of retyping large code blocks.\n 5) If `assets/` or templates exist, reuse them instead of recreating from scratch.\n- Coordination and sequencing:\n - If multiple skills apply, choose the minimal set that covers the request and state the order you'll use them.\n - Announce which skill(s) you're using and why (one short line). If you skip an obvious skill, say why.\n- Context hygiene:\n - Keep context small: summarize long sections instead of pasting them; only load extra files when needed.\n - Avoid deep reference-chasing: prefer opening only files directly linked from `SKILL.md` unless you're blocked.\n - When variants exist (frameworks, providers, domains), pick only the relevant reference file(s) and note that choice.\n- Safety and fallback: If a skill can't be applied cleanly (missing files, unclear instructions), state the issue, pick the next-best approach, and continue.","truncation_policy":{"mode":"tokens","limit":10000}}} +{"timestamp":"2026-03-27T18:10:35.403Z","type":"response_item","payload":{"type":"reasoning","summary":[],"content":null,"encrypted_content":"gAAAAABpxsgb5nUWoFUHCmO8QvLUhJQVKS0mxAJnvIlS1B6DFkmjL_Kow3KV_0D7MmscjOwYFKi0t73YZWcDov9RP7bG_VtyaAqwbN1go9dmDjXQfUOWY4p1Z8x-nNmUofKk2IWe3RuHNzBcR8L6gFUwqiiCy80IXrBNFoC5IAJ1dJ2nW_LpXnc2JnIgSEzApPxWDtRtlFN3ZkjGwDAiThbPrqksoYj-TwxAjO5iaD3K3V0T_wtbUmPdMHW8TLtlJYrnIPNpS5QvhNX7qNljtv_6suUB7UpSVNzH6gB3z_H8D5rWWQc4Bk601Ds5VktC-pX_mpcMrlRJ5T8iMGheAix_RWWhiy0XWp-Z6OmLchYOOdEzrd_0ykWcHGqCEVJTZMFgwLqHzInSVfagsjtgTohuXp1EZrmPnwy4srcArffywDlYSBs7ogxCWYOZLvqetWbF-deIHWM3z3GyMfsR8k7tXVLwF6ltUdinr0IJsmQMrje12kKx7x6yhMfArK9CugsXOysDplG8QuJJbXVamDNxPtKv0dO0xLoELBtX2anh8K4AzWA0pZlhgd-td8x20E5D_d7o4kGH4cmnK7q_yMJMw_-xrkV3Exkh0Bwh4_Tk6TND-2rNuGX9s138zeMX91GogaS9nJW-meC2iIfaSntWiOXTuEqq6OkMYfN1N_38og0qRlDCSu_gMvOHmk5NIoNDnRuaFentGbUOJIhNpk6qJuXprvu3sdhhcynhsVhj78e4otpW9-akLkDbdSAutYZ3kieZ3WordmdyKlSjjFfqdUSn-RQzLnYSB5D6evwUtuxFPS_A4iJyj88TWwc0IFX9ahHoPzMzijzzC6vVBTTMeblfDm8kO32DGhIoCTDDs2DGk1GlLf9cOTgRoOIOo7Ak7CTLyEtsiFxD3sbJyw8HZaKcTc0EMP8RiCgl7Oz6OOKEb_hpdLoZGCpIjjSYqRBdPY2d1Q5_66kFMRtEDUnBld4iCEZsN8Z8ADwzS9hOj_BUkQP2wBmry246Fiq2oCwVmrz42UgqrKmV6KgTSPWnny9pjiwmByQ19VqK1dEXJlfszn4pu-mjiRQFAhha0VrTry_d0XdF7JRo9HTZ_-PxC-bMUsTc94xK0OUxEQsoZZFogGEqurI="}} +{"timestamp":"2026-03-27T18:10:35.403Z","type":"response_item","payload":{"type":"function_call","name":"exec_command","arguments":"{\"cmd\":\"rg -n \\\"TMAPScaling|scaleResidual\\\" include src doc test --glob '!moose/**'\",\"workdir\":\"/Users/lindad/projects/TMAP8\",\"max_output_tokens\":4000,\"yield_time_ms\":1000}","call_id":"call_5379AzoBx9B8SqCGtjQmgjkw"}} +{"timestamp":"2026-03-27T18:10:35.403Z","type":"response_item","payload":{"type":"function_call","name":"exec_command","arguments":"{\"cmd\":\"cp \\\"$HOME/.codex/sessions/2026/03/27/rollout-2026-03-27T11-05-04-019d3078-9ee5-78f0-838a-4a4a79175713.jsonl\\\" doc/content/agent/200/\",\"workdir\":\"/Users/lindad/projects/TMAP8\",\"max_output_tokens\":2000,\"yield_time_ms\":1000}","call_id":"call_02CsKIzPFsfhMgX4ZmIp7uY4"}} +{"timestamp":"2026-03-27T18:10:35.403Z","type":"response_item","payload":{"type":"function_call","name":"exec_command","arguments":"{\"cmd\":\"git status --short\",\"workdir\":\"/Users/lindad/projects/TMAP8\",\"max_output_tokens\":4000,\"yield_time_ms\":1000}","call_id":"call_sxd4sVjnveOX6UwwQGQSRfQB"}} +{"timestamp":"2026-03-27T18:10:35.440Z","type":"event_msg","payload":{"type":"token_count","info":{"total_token_usage":{"input_tokens":519731,"cached_input_tokens":425984,"output_tokens":6790,"reasoning_output_tokens":1490,"total_tokens":526521},"last_token_usage":{"input_tokens":35323,"cached_input_tokens":35072,"output_tokens":284,"reasoning_output_tokens":51,"total_tokens":35607},"model_context_window":258400},"rate_limits":{"limit_id":"codex","limit_name":null,"primary":{"used_percent":17.0,"window_minutes":300,"resets_at":1774643092},"secondary":{"used_percent":28.0,"window_minutes":10080,"resets_at":1774905636},"credits":null,"plan_type":"enterprise"}}} diff --git a/doc/content/source/kernels/ScaledCoupledTimeDerivative.md b/doc/content/source/kernels/ScaledCoupledTimeDerivative.md index 45bd9fb6a..9f99d39f8 100644 --- a/doc/content/source/kernels/ScaledCoupledTimeDerivative.md +++ b/doc/content/source/kernels/ScaledCoupledTimeDerivative.md @@ -5,8 +5,9 @@ ## Overview This class inherits from [CoupledTimeDerivative.md] and simply scales the -residual and Jacobian by the user provided `factor`. The default value for -`factor` is 1. +residual and Jacobian by the user provided `factor`. It is also used for the +dimensionless trapping formulation, where `factor` is set to a concentration +reference ratio. The default value for `factor` is 1. !syntax parameters /Kernels/ScaledCoupledTimeDerivative diff --git a/doc/content/source/nodal_kernels/ReleasingNodalKernelDimensionless.md b/doc/content/source/nodal_kernels/ReleasingNodalKernelDimensionless.md new file mode 100644 index 000000000..c7ba87cd8 --- /dev/null +++ b/doc/content/source/nodal_kernels/ReleasingNodalKernelDimensionless.md @@ -0,0 +1,30 @@ +# ReleasingNodalKernelDimensionless + +!syntax description /NodalKernels/ReleasingNodalKernelDimensionless + +## Overview + +`ReleasingNodalKernelDimensionless` is the dimensionless analogue of +[ReleasingNodalKernel](ReleasingNodalKernel.md). It applies the release source term +to a dimensionless trapped-species variable, $\hat{C}_t = C_t / C_{t,\mathrm{ref}}$ +with $C_t$ the trapped-species variable and $C_{t,\mathrm{ref}}$ the characteristic trapped-species scale in the same unit as $C_t$. + +This object implements the residual + +\begin{equation} +\hat{k}_r \exp(-\epsilon / T) \hat{C}_t +\end{equation} + +where $\hat{C}_t$ is the dimensionless trapped-species concentration, $\hat{k}_r$ is +the dimensionless release rate, $\epsilon$ is the detrapping activation energy in +Kelvin, and $T$ is the temperature in Kelvin. + +Compared with [ReleasingNodalKernel](ReleasingNodalKernel.md), the form is the same +except that the trapped concentration variable is nondimensionalized and the rate +coefficient is provided directly as a dimensionless quantity. + +!syntax parameters /NodalKernels/ReleasingNodalKernelDimensionless + +!syntax inputs /NodalKernels/ReleasingNodalKernelDimensionless + +!syntax children /NodalKernels/ReleasingNodalKernelDimensionless diff --git a/doc/content/source/nodal_kernels/TrappingNodalKernelDimensionless.md b/doc/content/source/nodal_kernels/TrappingNodalKernelDimensionless.md new file mode 100644 index 000000000..bd34f562c --- /dev/null +++ b/doc/content/source/nodal_kernels/TrappingNodalKernelDimensionless.md @@ -0,0 +1,49 @@ +# TrappingNodalKernelDimensionless + +!syntax description /NodalKernels/TrappingNodalKernelDimensionless + +## Overview + +`TrappingNodalKernelDimensionless` is the dimensionless analogue of +[TrappingNodalKernel](TrappingNodalKernel.md). It applies the trapping source term +to a dimensionless trapped-species variable, $\hat{C}_t = C_t / C_{t,\mathrm{ref}}$ +with $C_t$ the trapped-species variable and $C_{t,\mathrm{ref}}$ the characteristic trapped-species scale in the same unit as $C_t$. + +This object implements the residual + +\begin{equation} +\hat{k}_t \exp(-\epsilon / T) +\left( +\frac{N C_{t0} - C_{t,\mathrm{ref}} \hat{C}_t - \sum_j C_{t,\mathrm{ref},j} \hat{C}_{t,j}} +{C_{t,\mathrm{ref}}} +\right) +\hat{C}_m +\end{equation} + +where $\hat{k}_t$ is the dimensionless trapping rate, $\epsilon$ is the trapping +activation energy in Kelvin, $T$ is the temperature in Kelvin, $N$ is the atomic +number density of the host material, $C_{t0}$ is the fraction of host sites that can +trap the species, $\hat{C}_t$ is the dimensionless concentration of this trapped +species, $\hat{C}_{t,j}$ are optional competing trapped-species variables, and +$\hat{C}_m$ is the coupled mobile concentration variable. + +The implementation computes the available trapping sites in physical units, + +\begin{equation} +N C_{t0} - C_{t,\mathrm{ref}} \hat{C}_t - \sum_j C_{t,\mathrm{ref},j} \hat{C}_{t,j}, +\end{equation} + +and then divides by $C_{t,\mathrm{ref}}$ so that the residual is written for the +dimensionless unknown $\hat{C}_t$. Unlike [TrappingNodalKernel](TrappingNodalKernel.md), +this object does not use the `trap_per_free` scaling factor that the dimensional +kernel uses to convert between trapped-species and mobile-species concentration +scales. Here, the conversion is handled explicitly through +`trap_concentration_reference` ($C_{t,\mathrm{ref}}$) and `other_trap_concentration_references` ($C_{t,\mathrm{ref},j}$), so the +residual is expected to remain $O(\hat{k}_t)$ when the variables are scaled with +appropriate reference values. + +!syntax parameters /NodalKernels/TrappingNodalKernelDimensionless + +!syntax inputs /NodalKernels/TrappingNodalKernelDimensionless + +!syntax children /NodalKernels/TrappingNodalKernelDimensionless diff --git a/doc/content/verification_and_validation/val-2c.md b/doc/content/verification_and_validation/val-2c.md index ba4122d07..5ed2996c9 100644 --- a/doc/content/verification_and_validation/val-2c.md +++ b/doc/content/verification_and_validation/val-2c.md @@ -159,8 +159,8 @@ The results presented here are updated results from those presented in [!cite](S [val-2c_comparison_T2] and [val-2c_comparison_HTO] show the comparison of the TMAP8 calculations (both with immediately injected and delayed injected T$_2$) against the experimental data for T$_2$ and HTO concentration in the enclosure over time. There is reasonable agreement between the TMAP8 predictions and the experimental data. -In the case of immediate T$_2$ injection, the root mean square percentage errors (RMSPE) are equal to RMSPE = 58.68% for T$_2$ and RMSPE = 146.23% for HTO, respectively. -When accounting for a delay in T$_2$ injection, the TMAP8 predictions best match the experimental data, in particular the position of the peak HTO concentration. The RMSPE values decrease to RMSPE = 89.50% for T$_2$ and RMSPE = 75.66% for HTO, respectively. +In the case of immediate T$_2$ injection, the root mean square percentage errors (RMSPE) are equal to RMSPE = 58.68% for T$_2$ and RMSPE = 146.25% for HTO, respectively. +When accounting for a delay in T$_2$ injection, the TMAP8 predictions best match the experimental data, in particular the position of the peak HTO concentration. The RMSPE values decrease to RMSPE = 89.50% for T$_2$ and RMSPE = 75.71% for HTO, respectively. Note that the model parameters listed in [val-2c_parameters] are somewhat different from [!cite](Holland1986,longhurst1992verification,ambrosek2008verification) to better match the experimental data. In particular, [!cite](longhurst1992verification,ambrosek2008verification) did not validate the TMAP predictions against T$_2$ concentration, which we do here in [val-2c_comparison_T2] and in [!cite](Simon2025). This affects some of the model parameters. @@ -178,7 +178,7 @@ This affects some of the model parameters. caption=Comparison of TMAP8 calculations against the experimental data for HTO concentration in the enclosure over time. Calibration of the delayed injection model delivers further improvements, with more accurate simulation results when T$_2$ is injected over a given period rather than immediately. As shown in the red curve in [val-2c_comparison_T2] and [val-2c_comparison_HTO], using [MOOSE's stochastic tools module](modules/stochastic_tools/index.md) notably increased the agreement between the modeling predictions and experimental data for both the T$_2$ and HTO concentrations. -The RMSPE for T$_2$ decreases from 89.50% to 30.18% and the RMSPE for HTO decreases from 75.66% to 67.07%. +The RMSPE for T$_2$ decreases from 89.50% to 30.18% and the RMSPE for HTO decreases from 75.71% to 67.18%. Note that although the calibration approach is similar to the one presented in [!cite](Simon2025), the results presented here include more simulations and the quality of the calibration is increased here (RMSPE values are further decreased here). [val-2c_calibration_input] and [val-2c_calibration_output] show the evolution of the model parameter values and of the optimization metric (time integral of $g$ defined in [eq:optimization_metric]) as a function of the number of simulation. The calibrated model corresponds to the highest value. @@ -237,4 +237,6 @@ Modifying the PSS parameters can reduce the computational cost. Although a very short PSS study is simulated as a test in [/val-2c/tests] to ensure these files run properly, the full calibration study is not performed regularly in tests to limit computational costs within the TMAP8 testing suite. The gold files [/gold/val-2c_pss_results/val-2c_pss_main_out.json] and [/gold/calibrated_parameter_values.txt] are, therefore, not continuously tested, and the calibrated model parameters used in [/val-2c/tests] are not continuously updated. +In addition, this validation case includes tests using two time integration schemes. The `implicit-euler` scheme (first-order, single-step) provides higher stability and consistency of the solution across different operating systems and processor core counts, making it better suited for use in PSS optimization workflows where numerical stability is important. The `bdf2` scheme (second-order, multi-step) provides higher accuracy and is used for final results calculation. Both schemes are tested for this validation case in [/val-2f/tests]. + !bibtex bibliography diff --git a/doc/content/verification_and_validation/val-2f.md b/doc/content/verification_and_validation/val-2f.md index 326ebe1d9..01f7704ab 100644 --- a/doc/content/verification_and_validation/val-2f.md +++ b/doc/content/verification_and_validation/val-2f.md @@ -264,4 +264,4 @@ To learn more about the `!include` feature, refer to the [application_usage/inpu Note that both surface conditions can be modeled using [/val-2f.i]. By running it as is, the recombination condition with the updated recombination rate is utilized. [/val-2f/tests] used `cli_args` to modify [/val-2f.i] into using the effectively infinite recombination rate at the surface and impose a null concentration at the surfaces. -To limit the computational costs of the test case, the test runs a version of the file with a smaller and coarser mesh, and fewer time steps. More information about the changes can be found in the test specification file for this case, namely [/val-2f/tests]. +To limit the computational costs of the test case, the test runs a version of the file with a smaller and coarser mesh, and fewer time steps. In addition, this validation case includes tests using two time integration schemes. The `implicit-euler` scheme (first-order, single-step) provides higher stability and consistency of the solution across different operating systems and processor core counts, making it better suited for use in Bayesian optimization workflows where numerical stability is important. The `bdf2` scheme (second-order, multi-step) provides higher accuracy and is used for final results calculation. Both schemes are tested for this validation case in [/val-2f/tests]. More information about the changes can be found in the test specification file for this case, namely [/val-2f/tests]. diff --git a/include/nodal_kernels/ReleasingNodalKernel.h b/include/nodal_kernels/ReleasingNodalKernel.h index 56eb13b56..b03cf04e8 100644 --- a/include/nodal_kernels/ReleasingNodalKernel.h +++ b/include/nodal_kernels/ReleasingNodalKernel.h @@ -8,20 +8,15 @@ #pragma once -#include "NodalKernel.h" +#include "ReleasingNodalKernelBase.h" -class ReleasingNodalKernel : public NodalKernel +/** + * Releasing NodalKernel for trapped-species concentrations in physical units. + */ +class ReleasingNodalKernel : public ReleasingNodalKernelBase { public: ReleasingNodalKernel(const InputParameters & parameters); static InputParameters validParams(); - -protected: - Real computeQpResidual() override; - Real computeQpJacobian() override; - - const Real _alpha_r; - const Real _detrapping_energy; - const VariableValue & _temperature; }; diff --git a/include/nodal_kernels/ReleasingNodalKernelBase.h b/include/nodal_kernels/ReleasingNodalKernelBase.h new file mode 100644 index 000000000..d38de520f --- /dev/null +++ b/include/nodal_kernels/ReleasingNodalKernelBase.h @@ -0,0 +1,36 @@ +/************************************************************/ +/* DO NOT MODIFY THIS HEADER */ +/* TMAP8: Tritium Migration Analysis Program, Version 8 */ +/* */ +/* Copyright 2021 - 2025 Battelle Energy Alliance, LLC */ +/* ALL RIGHTS RESERVED */ +/************************************************************/ + +#pragma once + +#include "NodalKernel.h" + +/** + * Shared implementation for trapped-species release nodal kernels. + * + * This base class factors the common Arrhenius release residual and Jacobian + * used by both the dimensional and dimensionless releasing kernels. + */ +class ReleasingNodalKernelBase : public NodalKernel +{ +public: + ReleasingNodalKernelBase(const InputParameters & parameters, Real release_rate_coefficient); + + static InputParameters validParams(); + +protected: + Real computeQpResidual() override; + Real computeQpJacobian() override; + + /// Effective release-rate coefficient multiplying the Arrhenius factor and variable value. + const Real _release_rate_coefficient; + /// Detrapping activation energy, expressed in Kelvin. + const Real _detrapping_energy; + /// Coupled temperature field. + const VariableValue & _temperature; +}; diff --git a/include/nodal_kernels/ReleasingNodalKernelDimensionless.h b/include/nodal_kernels/ReleasingNodalKernelDimensionless.h new file mode 100644 index 000000000..52ee419b1 --- /dev/null +++ b/include/nodal_kernels/ReleasingNodalKernelDimensionless.h @@ -0,0 +1,31 @@ +/************************************************************/ +/* DO NOT MODIFY THIS HEADER */ +/* TMAP8: Tritium Migration Analysis Program, Version 8 */ +/* */ +/* Copyright 2021 - 2025 Battelle Energy Alliance, LLC */ +/* ALL RIGHTS RESERVED */ +/************************************************************/ + +#pragma once + +#include "ReleasingNodalKernelBase.h" + +/** + * Releasing NodalKernel for a dimensionless trapped-species variable + * Ct_hat = C_t / C_t_ref. + * + * The residual is: + * R = +k_r_hat * exp(-E_r / T) * Ct_hat + * + * where k_r_hat = t_ref * alpha_r. + * + * The quadrature point residual should be dimensionless and O(k_r_hat) because Ct_hat should be + * dimensionless and O(1). + */ +class ReleasingNodalKernelDimensionless : public ReleasingNodalKernelBase +{ +public: + ReleasingNodalKernelDimensionless(const InputParameters & parameters); + + static InputParameters validParams(); +}; diff --git a/include/nodal_kernels/TrappingNodalKernel.h b/include/nodal_kernels/TrappingNodalKernel.h index 9e1daec59..9a1111661 100644 --- a/include/nodal_kernels/TrappingNodalKernel.h +++ b/include/nodal_kernels/TrappingNodalKernel.h @@ -8,43 +8,15 @@ #pragma once -#include "NodalKernel.h" +#include "TrappingNodalKernelBase.h" -#include "metaphysicl/dualdynamicsparsenumberarray.h" - -using MetaPhysicL::DualNumber; -using MetaPhysicL::DynamicSparseNumberArray; - -class Function; - -// Forward Declarations -typedef DualNumber> LocalDN; - -class TrappingNodalKernel : public NodalKernel +/** + * Trapping NodalKernel for trapped-species concentrations in physical units. + */ +class TrappingNodalKernel : public TrappingNodalKernelBase { public: TrappingNodalKernel(const InputParameters & parameters); static InputParameters validParams(); - -protected: - Real computeQpResidual() override; - Real computeQpJacobian() override; - Real computeQpOffDiagJacobian(unsigned int jvar) override; - - const Real _alpha_t; - const Real _trapping_energy; - const Real _N; - const Function & _Ct0; - const VariableValue & _mobile_concentration; - unsigned int _n_other_concs; - std::vector _trapped_concentrations; - std::vector _var_numbers; - const Node * _last_node; - const Real _trap_per_free; - const VariableValue & _temperature; - LocalDN _jacobian; - -private: - void ADHelper(); }; diff --git a/include/nodal_kernels/TrappingNodalKernelBase.h b/include/nodal_kernels/TrappingNodalKernelBase.h new file mode 100644 index 000000000..c49b402fc --- /dev/null +++ b/include/nodal_kernels/TrappingNodalKernelBase.h @@ -0,0 +1,84 @@ +/************************************************************/ +/* DO NOT MODIFY THIS HEADER */ +/* TMAP8: Tritium Migration Analysis Program, Version 8 */ +/* */ +/* Copyright 2021 - 2025 Battelle Energy Alliance, LLC */ +/* ALL RIGHTS RESERVED */ +/************************************************************/ + +#pragma once + +#include "NodalKernel.h" + +#include "metaphysicl/dualdynamicsparsenumberarray.h" + +using MetaPhysicL::DualNumber; +using MetaPhysicL::DynamicSparseNumberArray; + +class Function; + +/// Local AD number type used to assemble manual Jacobians for trapping kernels. +typedef DualNumber> LocalDN; + +/** + * Shared implementation for trapped-species trapping nodal kernels. + * + * This base class owns the common occupancy bookkeeping, empty-site assembly, + * and manual Jacobian logic used by both dimensional and dimensionless + * trapping kernels. + */ +class TrappingNodalKernelBase : public NodalKernel +{ +public: + /** + * Build the shared trapping kernel state from the supplied rate and residual scaling. + */ + TrappingNodalKernelBase(const InputParameters & parameters, + Real trapping_rate_coefficient, + Real residual_denominator); + + static InputParameters validParams(); + +protected: + /** + * Initialize the trapped-species variables that contribute to site occupancy. + * @param other_weights Physical occupancy weight for each coupled trapped species + * @param self_weight Physical occupancy weight for this kernel's primary variable + */ + void initializeOccupancyTracking(const std::vector & other_weights, Real self_weight); + + Real computeQpResidual() override; + Real computeQpJacobian() override; + Real computeQpOffDiagJacobian(unsigned int jvar) override; + + /// Effective trapping-rate coefficient multiplying the Arrhenius factor. + const Real _trapping_rate_coefficient; + /// Trapping activation energy, expressed in Kelvin. + const Real _trapping_energy; + /// Atomic number density of the host material. + const Real _N; + /// Fraction of host sites available for trapping as a function of position. + const Function & _Ct0; + /// Coupled mobile-species concentration. + const VariableValue & _mobile_concentration; + /// Number of additional trapped concentrations coupled into the occupancy calculation. + unsigned int _n_other_concs; + /// Coupled concentration fields that consume trapping sites, including this kernel's variable. + std::vector _occupancy_concentrations; + /// Physical occupancy weight associated with each trapped concentration. + std::vector _occupancy_weights; + /// Variable numbers corresponding to occupancy concentrations plus the mobile concentration. + std::vector _var_numbers; + /// Most recent node for which the cached Jacobian state was assembled. + const Node * _last_node; + /// Coupled temperature field. + const VariableValue & _temperature; + /// Denominator used to scale the residual after empty-site assembly. + const Real _residual_denominator; + /// Cached AD residual used to extract diagonal and off-diagonal Jacobian entries. + LocalDN _jacobian; + +private: + /// Rebuild the cached AD residual when the active node changes. + void ADHelper(); +}; diff --git a/include/nodal_kernels/TrappingNodalKernelDimensionless.h b/include/nodal_kernels/TrappingNodalKernelDimensionless.h new file mode 100644 index 000000000..9303c06a0 --- /dev/null +++ b/include/nodal_kernels/TrappingNodalKernelDimensionless.h @@ -0,0 +1,38 @@ +/************************************************************/ +/* DO NOT MODIFY THIS HEADER */ +/* TMAP8: Tritium Migration Analysis Program, Version 8 */ +/* */ +/* Copyright 2021 - 2025 Battelle Energy Alliance, LLC */ +/* ALL RIGHTS RESERVED */ +/************************************************************/ + +#pragma once + +#include "TrappingNodalKernelBase.h" + +/** + * Trapping NodalKernel that operates on a dimensionless trapped-species variable + * Ct_hat = C_t / C_t_ref, where C_t_ref is the trap concentration reference scale. + * + * The residual is: + * R = -k_t_hat * exp(-E_t / T) * ((N * Ct0 - C_t_ref * Ct_hat - sum_j C_t_j) / C_t_ref) * + * Cm_hat + * + * where: + * - Ct_hat = dimensionless variable (this kernel's variable), O(1) + * - Cm_hat = dimensionless mobile concentration. The coupled variable may be either physical + * or dimensionless, controlled by the mobile_variable_is_dimensionless flag. + * - C_t_j = C_t_ref_j * Ct_hat_j, other trap species (dimensionless variable + reference, + * optional) + * - C_t_ref = trap_concentration_reference parameter + * - k_t_hat = t_ref * alpha_t * C_m_ref / N + * + * The residual is naturally O(k_t_hat). + */ +class TrappingNodalKernelDimensionless : public TrappingNodalKernelBase +{ +public: + TrappingNodalKernelDimensionless(const InputParameters & parameters); + + static InputParameters validParams(); +}; diff --git a/include/physics/SpeciesTrappingPhysics.h b/include/physics/SpeciesTrappingPhysics.h index 7e6096712..02b886b75 100644 --- a/include/physics/SpeciesTrappingPhysics.h +++ b/include/physics/SpeciesTrappingPhysics.h @@ -43,17 +43,30 @@ class SpeciesTrappingPhysics : public SpeciesPhysicsBase std::vector _Ns; /// Fraction of host sites that contribute to trapping for each component (outer indexing) and species (inner) std::vector> _Ct0s; + /// Dimensionless trapping rate k_t_hat for each component (outer indexing) and species (inner) + std::vector> _dimensionless_trapping_rates_coefficient; + /// Reference trapped concentration for each component (outer indexing) and species (inner) + std::vector> _trap_concentration_references; + /// Reference mobile concentration for each component + std::vector _mobile_concentration_references; /// Estimate for the ratio of the concentration magnitude of trapped species to free species for each component std::vector _trap_per_frees; /// Releasing rate for each component (outer indexing) and species (inner) std::vector> _alpha_rs; + /// Dimensionless release rate k_r_hat for each component (outer indexing) and species (inner) + std::vector> _dimensionless_release_rates_coefficient; /// Detrapping energies for each component (outer indexing) and species (inner) std::vector> _detrapping_energies; - /// Whether to define a single variable for each species for all components, or a different one for each component const bool _single_variable_set; + /// Whether to use dimensionless mobile and trapped-species variables and their associated dimensionless trapping/release kernels + const bool _use_dimensionless_species; private: + Real trapConcentrationReference(unsigned int c_i, unsigned int s_j); + Real dimensionlessTrappingRate(unsigned int c_i, unsigned int s_j); + Real mobileConcentrationReference(unsigned int c_i) const; + Real dimensionlessReleaseRate(unsigned int c_i, unsigned int s_j); virtual void addSolverVariables() override; virtual void addInitialConditions() override; virtual void addFEKernels() override; diff --git a/moose b/moose index b3ab245a8..76a12d39d 160000 --- a/moose +++ b/moose @@ -1 +1 @@ -Subproject commit b3ab245a82c8fcf064a7e6af4d72f282784fa77b +Subproject commit 76a12d39d8871be98d13c1f9276586f7f2cda077 diff --git a/scripts/TestHarness/testers/RecoverableRunCommand.py b/scripts/TestHarness/testers/RecoverableRunCommand.py new file mode 100644 index 000000000..2958457c0 --- /dev/null +++ b/scripts/TestHarness/testers/RecoverableRunCommand.py @@ -0,0 +1,17 @@ +from RunCommand import RunCommand + + +class RecoverableRunCommand(RunCommand): + @staticmethod + def validParams(): + params = RunCommand.validParams() + return params + + def getCommand(self, options): + # In --recover mode, TestHarness creates a "_part1" clone with skip_checks=True + # and the original test as the follow-on recover job. Make the synthetic part1 + # a no-op so the user command executes only once after all prereqs have finished. + if options.enable_recover and self.specs["skip_checks"]: + return "true" + + return super().getCommand(options) diff --git a/src/auxkernels/EmptySitesAux.C b/src/auxkernels/EmptySitesAux.C index 6409a1fbb..e48dd937d 100644 --- a/src/auxkernels/EmptySitesAux.C +++ b/src/auxkernels/EmptySitesAux.C @@ -40,7 +40,7 @@ EmptySitesAux::EmptySitesAux(const InputParameters & parameters) // Resize to n_other_concs plus the concentration corresponding to this NodalKernel's variable _trapped_concentrations.resize(_n_concs); - for (MooseIndex(_n_concs) i = 0; i < _n_concs; ++i) + for (const auto i : make_range(_n_concs)) _trapped_concentrations[i] = &coupledValue("trapped_concentration_variables", i); } diff --git a/src/kernels/ScaledCoupledTimeDerivative.C b/src/kernels/ScaledCoupledTimeDerivative.C index 3ff1d9e23..ffdecb494 100644 --- a/src/kernels/ScaledCoupledTimeDerivative.C +++ b/src/kernels/ScaledCoupledTimeDerivative.C @@ -14,7 +14,11 @@ InputParameters ScaledCoupledTimeDerivative::validParams() { InputParameters params = CoupledTimeDerivative::validParams(); - params.addParam("factor", 1, "The factor by which to scale"); + params.addClassDescription( + "Adds factor * (psi, dv/dt) to the residual of the primary variable. " + "This covers both the standard scaled form and the dimensionless trapping form " + "where factor = C_t_ref / C_m_ref."); + params.addParam("factor", 1, "Constant multiplier applied to the coupled time derivative."); return params; } diff --git a/src/nodal_kernels/ReleasingNodalKernel.C b/src/nodal_kernels/ReleasingNodalKernel.C index faf123253..7ce96f7a0 100644 --- a/src/nodal_kernels/ReleasingNodalKernel.C +++ b/src/nodal_kernels/ReleasingNodalKernel.C @@ -13,31 +13,14 @@ registerMooseObject("TMAP8App", ReleasingNodalKernel); InputParameters ReleasingNodalKernel::validParams() { - InputParameters params = NodalKernel::validParams(); + InputParameters params = ReleasingNodalKernelBase::validParams(); params.addClassDescription( "Implements a residual describing the release of trapped species in a material."); params.addRequiredParam("alpha_r", "The release rate coefficient (1/s)"); - params.addParam("detrapping_energy", 0, "The detrapping energy (K)"); - params.addRequiredCoupledVar("temperature", "The temperature (K)"); return params; } ReleasingNodalKernel::ReleasingNodalKernel(const InputParameters & parameters) - : NodalKernel(parameters), - _alpha_r(getParam("alpha_r")), - _detrapping_energy(getParam("detrapping_energy")), - _temperature(coupledValue("temperature")) + : ReleasingNodalKernelBase(parameters, parameters.get("alpha_r")) { } - -Real -ReleasingNodalKernel::computeQpResidual() -{ - return _alpha_r * std::exp(-_detrapping_energy / _temperature[_qp]) * _u[_qp]; -} - -Real -ReleasingNodalKernel::computeQpJacobian() -{ - return _alpha_r * std::exp(-_detrapping_energy / _temperature[_qp]); -} diff --git a/src/nodal_kernels/ReleasingNodalKernelBase.C b/src/nodal_kernels/ReleasingNodalKernelBase.C new file mode 100644 index 000000000..bb3b20718 --- /dev/null +++ b/src/nodal_kernels/ReleasingNodalKernelBase.C @@ -0,0 +1,39 @@ +/************************************************************/ +/* DO NOT MODIFY THIS HEADER */ +/* TMAP8: Tritium Migration Analysis Program, Version 8 */ +/* */ +/* Copyright 2021 - 2025 Battelle Energy Alliance, LLC */ +/* ALL RIGHTS RESERVED */ +/************************************************************/ + +#include "ReleasingNodalKernelBase.h" + +InputParameters +ReleasingNodalKernelBase::validParams() +{ + InputParameters params = NodalKernel::validParams(); + params.addParam("detrapping_energy", 0, "The detrapping energy (K)"); + params.addRequiredCoupledVar("temperature", "The temperature (K)"); + return params; +} + +ReleasingNodalKernelBase::ReleasingNodalKernelBase(const InputParameters & parameters, + Real release_rate_coefficient) + : NodalKernel(parameters), + _release_rate_coefficient(release_rate_coefficient), + _detrapping_energy(getParam("detrapping_energy")), + _temperature(coupledValue("temperature")) +{ +} + +Real +ReleasingNodalKernelBase::computeQpResidual() +{ + return _release_rate_coefficient * std::exp(-_detrapping_energy / _temperature[_qp]) * _u[_qp]; +} + +Real +ReleasingNodalKernelBase::computeQpJacobian() +{ + return _release_rate_coefficient * std::exp(-_detrapping_energy / _temperature[_qp]); +} diff --git a/src/nodal_kernels/ReleasingNodalKernelDimensionless.C b/src/nodal_kernels/ReleasingNodalKernelDimensionless.C new file mode 100644 index 000000000..4ff4af619 --- /dev/null +++ b/src/nodal_kernels/ReleasingNodalKernelDimensionless.C @@ -0,0 +1,33 @@ +/************************************************************/ +/* DO NOT MODIFY THIS HEADER */ +/* TMAP8: Tritium Migration Analysis Program, Version 8 */ +/* */ +/* Copyright 2021 - 2025 Battelle Energy Alliance, LLC */ +/* ALL RIGHTS RESERVED */ +/************************************************************/ + +#include "ReleasingNodalKernelDimensionless.h" + +registerMooseObject("TMAP8App", ReleasingNodalKernelDimensionless); + +InputParameters +ReleasingNodalKernelDimensionless::validParams() +{ + InputParameters params = ReleasingNodalKernelBase::validParams(); + params.addClassDescription( + "Implements the release source term for a dimensionless trapped-species variable " + "Ct_hat = C_t / C_t_ref. " + "The residual R = +k_r_hat * exp(-E_r / T) * Ct_hat is naturally O(k_r_hat) " + "because Ct_hat is O(1). No equation scaling is applied."); + params.addRequiredParam( + "dimensionless_release_rate_coefficient", + "Dimensionless release rate coefficient k_r_hat = t_ref * alpha_r."); + return params; +} + +ReleasingNodalKernelDimensionless::ReleasingNodalKernelDimensionless( + const InputParameters & parameters) + : ReleasingNodalKernelBase(parameters, + parameters.get("dimensionless_release_rate_coefficient")) +{ +} diff --git a/src/nodal_kernels/TrappingNodalKernel.C b/src/nodal_kernels/TrappingNodalKernel.C index 0823fec2c..7afb15cbe 100644 --- a/src/nodal_kernels/TrappingNodalKernel.C +++ b/src/nodal_kernels/TrappingNodalKernel.C @@ -7,119 +7,31 @@ /************************************************************/ #include "TrappingNodalKernel.h" -#include "Function.h" registerMooseObject("TMAP8App", TrappingNodalKernel); InputParameters TrappingNodalKernel::validParams() { - InputParameters params = NodalKernel::validParams(); + InputParameters params = TrappingNodalKernelBase::validParams(); params.addClassDescription( "Implements a residual describing the trapping of a species in a material."); params.addRequiredParam("alpha_t", "The trapping rate coefficient. This has units of 1/s (e.g. no " "number densities are involved)"); - params.addParam("trapping_energy", 0, "The trapping energy (K)"); - params.addRequiredParam("N", "The atomic number density of the host material (1/m^3)"); - params.addRequiredParam( - "Ct0", "The fraction of host sites that can contribute to trapping as a function (-)"); params.addParam( "trap_per_free", 1., "An estimate for the ratio of the concentration magnitude of trapped species to free " "species. Setting a value for this can be helpful in producing a well-scaled matrix (-)"); - params.addRequiredCoupledVar( - "mobile_concentration", - "The variable representing the mobile concentration of solute particles (1/m^3)"); - params.addCoupledVar("other_trapped_concentration_variables", - "Other variables representing trapped particle concentrations."); - params.addRequiredCoupledVar("temperature", "The temperature (K)"); return params; } TrappingNodalKernel::TrappingNodalKernel(const InputParameters & parameters) - : NodalKernel(parameters), - _alpha_t(getParam("alpha_t")), - _trapping_energy(getParam("trapping_energy")), - _N(getParam("N")), - _Ct0(getFunction("Ct0")), - _mobile_concentration(coupledValue("mobile_concentration")), - _last_node(nullptr), - _trap_per_free(getParam("trap_per_free")), - _temperature(coupledValue("temperature")) + : TrappingNodalKernelBase(parameters, + parameters.get("alpha_t"), + parameters.get("N") * parameters.get("trap_per_free")) { - _n_other_concs = coupledComponents("other_trapped_concentration_variables"); - - // Resize to n_other_concs plus the concentration corresponding to this NodalKernel's variable - _trapped_concentrations.resize(1 + _n_other_concs); - - // One size bigger than trapped_concentrations because we have to include the mobile concentration - _var_numbers.resize(2 + _n_other_concs); - - for (MooseIndex(_n_other_concs) i = 0; i < _n_other_concs; ++i) - { - _trapped_concentrations[i] = &coupledValue("other_trapped_concentration_variables", /*comp=*/i); - _var_numbers[i] = coupled("other_trapped_concentration_variables", i); - } - _trapped_concentrations[_n_other_concs] = &_u; - _var_numbers[_n_other_concs] = _var.number(); - _var_numbers[_n_other_concs + 1] = coupled("mobile_concentration"); -} - -Real -TrappingNodalKernel::computeQpResidual() -{ - auto empty_trapping_sites = _Ct0.value(_t, (*_current_node)) * _N; - for (const auto & trap_conc : _trapped_concentrations) - empty_trapping_sites -= (*trap_conc)[_qp] * _trap_per_free; - - return -_alpha_t * std::exp(-_trapping_energy / _temperature[_qp]) * empty_trapping_sites * - _mobile_concentration[_qp] / (_N * _trap_per_free); -} - -void -TrappingNodalKernel::ADHelper() -{ - if (_current_node == _last_node) - return; - - _last_node = _current_node; - - LocalDN empty_trapping_sites = _Ct0.value(_t, (*_current_node)) * _N; - size_t i = 0; - for (const auto & trap_conc : _trapped_concentrations) - { - LocalDN trap_conc_dn = (*trap_conc)[_qp]; - trap_conc_dn.derivatives().insert(_var_numbers[i]) = 1.; - empty_trapping_sites -= trap_conc_dn * _trap_per_free; - ++i; - } - LocalDN mobile_concentration = _mobile_concentration[_qp]; - - mobile_concentration.derivatives().insert(_var_numbers.back()) = 1.; - - _jacobian = -_alpha_t * std::exp(-_trapping_energy / _temperature[_qp]) * empty_trapping_sites * - mobile_concentration / (_N * _trap_per_free); -} - -Real -TrappingNodalKernel::computeQpJacobian() -{ - ADHelper(); - - return _jacobian.derivatives()[_var.number()]; -} - -Real -TrappingNodalKernel::computeQpOffDiagJacobian(unsigned int jvar) -{ - if (std::find(_var_numbers.begin(), _var_numbers.end(), jvar) != _var_numbers.end()) - { - ADHelper(); - - return _jacobian.derivatives()[jvar]; - } - else - return 0; + const Real trap_per_free = getParam("trap_per_free"); + initializeOccupancyTracking(std::vector(_n_other_concs, trap_per_free), trap_per_free); } diff --git a/src/nodal_kernels/TrappingNodalKernelBase.C b/src/nodal_kernels/TrappingNodalKernelBase.C new file mode 100644 index 000000000..2a524d8e0 --- /dev/null +++ b/src/nodal_kernels/TrappingNodalKernelBase.C @@ -0,0 +1,119 @@ +/************************************************************/ +/* DO NOT MODIFY THIS HEADER */ +/* TMAP8: Tritium Migration Analysis Program, Version 8 */ +/* */ +/* Copyright 2021 - 2025 Battelle Energy Alliance, LLC */ +/* ALL RIGHTS RESERVED */ +/************************************************************/ + +#include "TrappingNodalKernelBase.h" +#include "Function.h" + +InputParameters +TrappingNodalKernelBase::validParams() +{ + InputParameters params = NodalKernel::validParams(); + params.addParam("trapping_energy", 0, "The trapping energy (K)"); + params.addRequiredParam("N", "The atomic number density of the host material (1/m^3)"); + params.addRequiredParam( + "Ct0", "The fraction of host sites that can contribute to trapping as a function (-)"); + params.addRequiredCoupledVar("mobile_concentration", + "The variable representing the mobile concentration of solute " + "particles."); + params.addCoupledVar("other_trapped_concentration_variables", + "Other variables representing trapped particle concentrations."); + params.addRequiredCoupledVar("temperature", "The temperature (K)"); + return params; +} + +TrappingNodalKernelBase::TrappingNodalKernelBase(const InputParameters & parameters, + Real trapping_rate_coefficient, + Real residual_denominator) + : NodalKernel(parameters), + _trapping_rate_coefficient(trapping_rate_coefficient), + _trapping_energy(getParam("trapping_energy")), + _N(getParam("N")), + _Ct0(getFunction("Ct0")), + _mobile_concentration(coupledValue("mobile_concentration")), + _n_other_concs(coupledComponents("other_trapped_concentration_variables")), + _last_node(nullptr), + _temperature(coupledValue("temperature")), + _residual_denominator(residual_denominator) +{ +} + +void +TrappingNodalKernelBase::initializeOccupancyTracking(const std::vector & other_weights, + Real self_weight) +{ + mooseAssert(other_weights.size() == _n_other_concs, + "other occupancy weight count must match coupled concentration count"); + + _occupancy_concentrations.resize(1 + _n_other_concs); + _occupancy_weights.resize(1 + _n_other_concs); + _var_numbers.resize(2 + _n_other_concs); + + for (const auto i : make_range(_n_other_concs)) + { + _occupancy_concentrations[i] = + &coupledValue("other_trapped_concentration_variables", /*comp=*/i); + _occupancy_weights[i] = other_weights[i]; + _var_numbers[i] = coupled("other_trapped_concentration_variables", i); + } + + _occupancy_concentrations[_n_other_concs] = &_u; + _occupancy_weights[_n_other_concs] = self_weight; + _var_numbers[_n_other_concs] = _var.number(); + _var_numbers[_n_other_concs + 1] = coupled("mobile_concentration"); +} + +Real +TrappingNodalKernelBase::computeQpResidual() +{ + Real empty_trapping_sites = _Ct0.value(_t, (*_current_node)) * _N; + for (const auto i : index_range(_occupancy_concentrations)) + empty_trapping_sites -= (*_occupancy_concentrations[i])[_qp] * _occupancy_weights[i]; + + return -_trapping_rate_coefficient * std::exp(-_trapping_energy / _temperature[_qp]) * + empty_trapping_sites * _mobile_concentration[_qp] / _residual_denominator; +} + +void +TrappingNodalKernelBase::ADHelper() +{ + if (_current_node == _last_node) + return; + + _last_node = _current_node; + + LocalDN empty_trapping_sites = _Ct0.value(_t, (*_current_node)) * _N; + for (const auto i : index_range(_occupancy_concentrations)) + { + LocalDN trap_conc_dn = (*_occupancy_concentrations[i])[_qp]; + trap_conc_dn.derivatives().insert(_var_numbers[i]) = 1.; + empty_trapping_sites -= trap_conc_dn * _occupancy_weights[i]; + } + + LocalDN mobile_concentration = _mobile_concentration[_qp]; + mobile_concentration.derivatives().insert(_var_numbers.back()) = 1.; + + _jacobian = -_trapping_rate_coefficient * std::exp(-_trapping_energy / _temperature[_qp]) * + empty_trapping_sites * mobile_concentration / _residual_denominator; +} + +Real +TrappingNodalKernelBase::computeQpJacobian() +{ + ADHelper(); + return _jacobian.derivatives()[_var.number()]; +} + +Real +TrappingNodalKernelBase::computeQpOffDiagJacobian(unsigned int jvar) +{ + if (std::find(_var_numbers.begin(), _var_numbers.end(), jvar) == _var_numbers.end()) + return 0; + + ADHelper(); + return _jacobian.derivatives()[jvar]; +} diff --git a/src/nodal_kernels/TrappingNodalKernelDimensionless.C b/src/nodal_kernels/TrappingNodalKernelDimensionless.C new file mode 100644 index 000000000..5fcac8e35 --- /dev/null +++ b/src/nodal_kernels/TrappingNodalKernelDimensionless.C @@ -0,0 +1,66 @@ +/************************************************************/ +/* DO NOT MODIFY THIS HEADER */ +/* TMAP8: Tritium Migration Analysis Program, Version 8 */ +/* */ +/* Copyright 2021 - 2025 Battelle Energy Alliance, LLC */ +/* ALL RIGHTS RESERVED */ +/************************************************************/ + +#include "TrappingNodalKernelDimensionless.h" + +registerMooseObject("TMAP8App", TrappingNodalKernelDimensionless); + +InputParameters +TrappingNodalKernelDimensionless::validParams() +{ + InputParameters params = TrappingNodalKernelBase::validParams(); + params.addClassDescription( + "Implements the trapping source term for a dimensionless trapped-species variable " + "Ct_hat = C_t / C_t_ref. " + "The mobile concentration may be either physical or dimensionless. " + "No equation scaling is applied; the residual is O(k_t_hat)."); + params.addRequiredParam( + "dimensionless_trapping_rate_coefficient", + "Dimensionless trapping rate coefficient k_t_hat = t_ref * alpha_t * C_m_ref / N."); + params.addRequiredParam( + "trap_concentration_reference", + "Reference concentration C_t_ref for this trap species (same units as N). " + "Typically set to N * Ct0_max. The variable stores Ct_hat = C_t / C_t_ref."); + params.addCoupledVar("other_trapped_concentration_variables", + "Dimensionless trapped-concentration variables (Ct_hat_j = C_t_j / " + "C_t_ref_j) " + "for other trap species that compete for the same trapping sites."); + params.addParam>( + "other_trap_concentration_references", + {}, + "Reference concentrations C_t_ref_j for each variable listed in " + "other_trapped_concentration_variables, used to convert Ct_hat_j back to physical C_t_j " + "when computing available trapping sites. Must match in length."); + return params; +} + +TrappingNodalKernelDimensionless::TrappingNodalKernelDimensionless( + const InputParameters & parameters) + : TrappingNodalKernelBase(parameters, + parameters.get("dimensionless_trapping_rate_coefficient"), + parameters.get("trap_concentration_reference")) +{ + std::vector other_trap_concentration_references = + getParam>("other_trap_concentration_references"); + + if (!other_trap_concentration_references.empty() && + other_trap_concentration_references.size() != _n_other_concs) + paramError("other_trap_concentration_references", + "Length (", + other_trap_concentration_references.size(), + ") must match the number of other_trapped_concentration_variables (", + _n_other_concs, + ")."); + + // Default: treat each missing reference as 1.0 (physical units, backward compat) + if (other_trap_concentration_references.empty() && _n_other_concs > 0) + other_trap_concentration_references.assign(_n_other_concs, 1.0); + + initializeOccupancyTracking(other_trap_concentration_references, + getParam("trap_concentration_reference")); +} diff --git a/src/physics/SpeciesTrappingPhysics.C b/src/physics/SpeciesTrappingPhysics.C index 7d2cf99ac..4b2064196 100644 --- a/src/physics/SpeciesTrappingPhysics.C +++ b/src/physics/SpeciesTrappingPhysics.C @@ -46,6 +46,11 @@ SpeciesTrappingPhysics::validParams() "(e.g. no number densities are involved)" "If a single vector is specified, the same trapping rate coefficient will be used on every " "component"); + params.addParam>( + "dimensionless_trapping_rate_coefficient", + {}, + "Dimensionless trapping rate k_t_hat = t_ref * alpha_t * C_m_ref / N for each " + "component and species. Required when dimensionless_species = true."); params.addParam>( "trapping_energy", {}, @@ -60,12 +65,31 @@ SpeciesTrappingPhysics::validParams() params.addParam("different_traps_for_each_species", false, "Wheter the traps are shared by each species or not"); + params.addParam("dimensionless_species", + false, + "Whether to use dimensionless mobile and trapped species. When true, " + "'mobile_concentration_reference', 'trap_concentration_reference', " + "'dimensionless_trapping_rate_coefficient', and " + "'dimensionless_release_rate_coefficient' must all be supplied."); + params.addParam>( + "trap_concentration_reference", + {}, + "Reference concentration C_t_ref for each trapped species. Required when " + "dimensionless_species = true."); + params.addParam("mobile_concentration_reference", + "Reference concentration C_m_ref for the mobile species. Required " + "when dimensionless_species = true."); params.addParam>( "alpha_r", {}, "The release rate coefficient. If a single vector is specified, " "the same release rate coefficient will be used on every component"); + params.addParam>( + "dimensionless_release_rate_coefficient", + {}, + "Dimensionless release rate k_r_hat = t_ref * alpha_r for each component and species. " + "Required when dimensionless_species = true."); params.addParam>( "detrapping_energy", {}, @@ -74,8 +98,14 @@ SpeciesTrappingPhysics::validParams() // Parameter groups params.addParamNamesToGroup( - "alpha_t trapping_energy N Ct0 trap_per_free different_traps_for_each_species", "Trapping"); - params.addParamNamesToGroup("alpha_r temperature detrapping_energy", "Releasing"); + "alpha_t dimensionless_trapping_rate_coefficient trapping_energy N Ct0 trap_per_free " + "different_traps_for_each_species", + "Trapping"); + params.addParamNamesToGroup( + "alpha_r dimensionless_release_rate_coefficient temperature detrapping_energy", "Releasing"); + params.addParamNamesToGroup( + "dimensionless_species trap_concentration_reference mobile_concentration_reference", + "Scaling"); return params; } @@ -88,12 +118,32 @@ SpeciesTrappingPhysics::SpeciesTrappingPhysics(const InputParameters & parameter _trapping_energies({getParam>("trapping_energy")}), _Ns(isParamValid("N") ? std::vector(1, getParam("N")) : std::vector()), _Ct0s({getParam>("Ct0")}), + _dimensionless_trapping_rates_coefficient( + isParamValid("dimensionless_trapping_rate_coefficient") + ? std::vector>( + 1, getParam>("dimensionless_trapping_rate_coefficient")) + : std::vector>()), + _trap_concentration_references( + isParamValid("trap_concentration_reference") + ? std::vector>( + 1, getParam>("trap_concentration_reference")) + : std::vector>()), + _mobile_concentration_references( + isParamValid("mobile_concentration_reference") + ? std::vector(1, getParam("mobile_concentration_reference")) + : std::vector()), _trap_per_frees(isParamValid("trap_per_free") ? std::vector(1, getParam("trap_per_free")) : std::vector()), _alpha_rs({getParam>("alpha_r")}), + _dimensionless_release_rates_coefficient( + isParamValid("dimensionless_release_rate_coefficient") + ? std::vector>( + 1, getParam>("dimensionless_release_rate_coefficient")) + : std::vector>()), _detrapping_energies({getParam>("detrapping_energy")}), - _single_variable_set(!getParam("separate_variables_per_component")) + _single_variable_set(!getParam("separate_variables_per_component")), + _use_dimensionless_species(getParam("dimensionless_species")) { // We allow overlaps between mobile species names because two trapped species could release to the // same mobile species and adding the two time derivative kernels is correct @@ -104,26 +154,84 @@ SpeciesTrappingPhysics::SpeciesTrappingPhysics(const InputParameters & parameter // Only set the other parameters if setting the species checkSecondParamSetOnlyIfFirstOneSet("species", "mobile"); - checkSecondParamSetOnlyIfFirstOneSet("species", "alpha_t"); + if (_use_dimensionless_species) + { + checkSecondParamSetOnlyIfFirstOneSet("species", "dimensionless_trapping_rate_coefficient"); + checkSecondParamSetOnlyIfFirstOneSet("species", "dimensionless_release_rate_coefficient"); + checkSecondParamSetOnlyIfFirstOneSet("species", "trap_concentration_reference"); + checkSecondParamSetOnlyIfFirstOneSet("species", "mobile_concentration_reference"); + } + else + { + checkSecondParamSetOnlyIfFirstOneSet("species", "alpha_t"); + checkSecondParamSetOnlyIfFirstOneSet("species", "alpha_r"); + checkSecondParamSetOnlyIfFirstOneSet("species", "trap_per_free"); + } + checkSecondParamSetOnlyIfFirstOneSet("species", "trapping_energy"); checkSecondParamSetOnlyIfFirstOneSet("species", "N"); checkSecondParamSetOnlyIfFirstOneSet("species", "Ct0"); - checkSecondParamSetOnlyIfFirstOneSet("species", "trap_per_free"); - checkSecondParamSetOnlyIfFirstOneSet("species", "alpha_r"); checkSecondParamSetOnlyIfFirstOneSet("species", "detrapping_energy"); // Check sizes checkVectorParamsSameLengthIfSet( "species", "species_initial_concentrations", /*ignore_empty_second*/ true); checkVectorParamsSameLengthIfSet("species", "mobile", true); - checkVectorParamsSameLengthIfSet("species", "alpha_t", true); + if (_use_dimensionless_species) + checkVectorParamsSameLengthIfSet( + "species", "dimensionless_trapping_rate_coefficient", true); + else + checkVectorParamsSameLengthIfSet("species", "alpha_t", true); checkVectorParamsSameLengthIfSet("species", "trapping_energy", true); checkVectorParamsSameLengthIfSet("species", "Ct0", true); - checkVectorParamsSameLengthIfSet("species", "alpha_r", true); + if (_use_dimensionless_species) + checkVectorParamsSameLengthIfSet( + "species", "trap_concentration_reference", true); + if (_use_dimensionless_species) + checkVectorParamsSameLengthIfSet( + "species", "dimensionless_release_rate_coefficient", true); + else + checkVectorParamsSameLengthIfSet("species", "alpha_r", true); checkVectorParamsSameLengthIfSet( "species", "detrapping_energy", true); } +Real +SpeciesTrappingPhysics::mobileConcentrationReference(unsigned int c_i) const +{ + return _use_dimensionless_species ? _mobile_concentration_references[c_i] : 1.0; +} + +Real +SpeciesTrappingPhysics::trapConcentrationReference(unsigned int c_i, unsigned int s_j) +{ + mooseAssert(c_i < _trap_concentration_references.size(), + "component index higher than trap reference component count"); + mooseAssert(s_j < _trap_concentration_references[c_i].size(), + "species index higher than trap reference species count"); + return _trap_concentration_references[c_i][s_j]; +} + +Real +SpeciesTrappingPhysics::dimensionlessTrappingRate(unsigned int c_i, unsigned int s_j) +{ + mooseAssert(c_i < _dimensionless_trapping_rates_coefficient.size(), + "component index higher than dimensionless trapping-rate component count"); + mooseAssert(s_j < _dimensionless_trapping_rates_coefficient[c_i].size(), + "species index higher than dimensionless trapping-rate species count"); + return _dimensionless_trapping_rates_coefficient[c_i][s_j]; +} + +Real +SpeciesTrappingPhysics::dimensionlessReleaseRate(unsigned int c_i, unsigned int s_j) +{ + mooseAssert(c_i < _dimensionless_release_rates_coefficient.size(), + "component index higher than dimensionless release-rate component count"); + mooseAssert(s_j < _dimensionless_release_rates_coefficient[c_i].size(), + "species index higher than dimensionless release-rate species count"); + return _dimensionless_release_rates_coefficient[c_i][s_j]; +} + void SpeciesTrappingPhysics::addComponent(const ActionComponent & component) { @@ -176,19 +284,45 @@ SpeciesTrappingPhysics::addComponent(const ActionComponent & component) // These parameters should be defined as material properties by the user on the Component // or on the Physics. // We only support Real numbers for now as the consuming kernels only support Real - processComponentMatprop>( - "alpha_t", component, comp_index, _species.back(), _alpha_ts); processComponentMatprop>( "trapping_energy", component, comp_index, _species.back(), _trapping_energies); processComponentMatprop("N", component, comp_index, _species.back(), _Ns); processComponentMatprop>( "Ct0", component, comp_index, _species.back(), _Ct0s); - processComponentMatprop( - "trap_per_free", component, comp_index, _species.back(), _trap_per_frees); - processComponentMatprop>( - "alpha_r", component, comp_index, _species.back(), _alpha_rs); processComponentMatprop>( "detrapping_energy", component, comp_index, _species.back(), _detrapping_energies); + if (_use_dimensionless_species) + { + processComponentMatprop>("dimensionless_trapping_rate_coefficient", + component, + comp_index, + _species.back(), + _dimensionless_trapping_rates_coefficient); + processComponentMatprop>("dimensionless_release_rate_coefficient", + component, + comp_index, + _species.back(), + _dimensionless_release_rates_coefficient); + processComponentMatprop>("trap_concentration_reference", + component, + comp_index, + _species.back(), + _trap_concentration_references); + processComponentMatprop("mobile_concentration_reference", + component, + comp_index, + _species.back(), + _mobile_concentration_references); + } + else + { + processComponentMatprop>( + "alpha_t", component, comp_index, _species.back(), _alpha_ts); + processComponentMatprop>( + "alpha_r", component, comp_index, _species.back(), _alpha_rs); + processComponentMatprop( + "trap_per_free", component, comp_index, _species.back(), _trap_per_frees); + } } VariableName @@ -223,22 +357,42 @@ SpeciesTrappingPhysics::addSolverVariables() _scaling_factors[0] = std::vector(_species.size(), 1); if (_mobile_species_names[0].empty()) paramError("mobile", "Should not be empty if not using Components"); - if (_alpha_ts[0].empty()) - paramError("alpha_t", "Should not be empty if not using Components"); if (_trapping_energies[0].empty()) paramError("trapping_energy", "Should not be empty if not using Components"); if (_Ns.empty()) paramError("N", "Should not be empty if not using Components"); if (_Ct0s[0].empty()) paramError("Ct0", "Should not be empty if not using Components"); - if (_trap_per_frees.empty()) - paramError("trap_per_free", "Should not be empty if not using Components"); - if (_alpha_rs[0].empty()) - paramError("alpha_r", "Should not be empty if not using Components"); if (_component_temperatures[0].empty()) paramError("temperature", "Should not be empty if not using Components"); if (_detrapping_energies[0].empty()) paramError("detrapping_energy", "Should not be empty if not using Components"); + if (_use_dimensionless_species) + { + if (_dimensionless_trapping_rates_coefficient.empty() || + _dimensionless_trapping_rates_coefficient[0].empty()) + paramError("dimensionless_trapping_rate_coefficient", + "Should not be empty when using dimensionless trapped species"); + if (_dimensionless_release_rates_coefficient.empty() || + _dimensionless_release_rates_coefficient[0].empty()) + paramError("dimensionless_release_rate_coefficient", + "Should not be empty when using dimensionless trapped species"); + if (_trap_concentration_references.empty() || _trap_concentration_references[0].empty()) + paramError("trap_concentration_reference", + "Should not be empty when using dimensionless trapped species"); + if (_mobile_concentration_references.empty()) + paramError("mobile_concentration_reference", + "Should not be empty when using a dimensionless mobile species"); + } + else + { + if (_trap_per_frees.empty()) + paramError("trap_per_free", "Should not be empty if not using Components"); + if (_alpha_ts[0].empty()) + paramError("alpha_t", "Should not be empty if not using Components"); + if (_alpha_rs[0].empty()) + paramError("alpha_r", "Should not be empty if not using Components"); + } } else paramError("separate_variables_per_component", @@ -317,12 +471,27 @@ void SpeciesTrappingPhysics::addFEKernels() { // Check component-indexed parameters - checkSizeComponentSpeciesIndexedVectorOfVector(_alpha_ts, "alpha_t", false); + if (_use_dimensionless_species) + { + checkSizeComponentSpeciesIndexedVectorOfVector(_dimensionless_trapping_rates_coefficient, + "dimensionless_trapping_rate_coefficient", + false); + checkSizeComponentSpeciesIndexedVectorOfVector( + _dimensionless_release_rates_coefficient, "dimensionless_release_rate_coefficient", false); + checkSizeComponentSpeciesIndexedVectorOfVector( + _trap_concentration_references, "trap_concentration_reference", false); + checkSizeComponentIndexedVector( + _mobile_concentration_references, "mobile_concentration_reference", false); + } + else + { + checkSizeComponentSpeciesIndexedVectorOfVector(_alpha_ts, "alpha_t", false); + checkSizeComponentSpeciesIndexedVectorOfVector(_alpha_rs, "alpha_r", false); + checkSizeComponentIndexedVector(_trap_per_frees, "trap_per_free", false); + } checkSizeComponentSpeciesIndexedVectorOfVector(_trapping_energies, "trapping_energy", false); - checkSizeComponentSpeciesIndexedVectorOfVector(_Ct0s, "alpha_t", false); + checkSizeComponentSpeciesIndexedVectorOfVector(_Ct0s, "Ct0", false); checkSizeComponentIndexedVector(_Ns, "N", false); - checkSizeComponentIndexedVector(_trap_per_frees, "trap_per_free", false); - checkSizeComponentSpeciesIndexedVectorOfVector(_alpha_rs, "alpha_r", false); checkSizeComponentSpeciesIndexedVectorOfVector(_detrapping_energies, "detrapping_energy", false); checkSizeComponentIndexedVector(_component_temperatures, "temperature", false); checkSizeComponentSpeciesIndexedVectorOfVector(_mobile_species_names, "mobile", false); @@ -349,82 +518,109 @@ SpeciesTrappingPhysics::addFEKernels() getProblem().addNodalKernel(kernel_type, prefix() + species_name + "_time", params); } - // Trapping term + // Helper lambda: set temperature coupling (shared by trapping and releasing kernels) + auto setTemperature = [&](InputParameters & p) { - const std::string kernel_type = "TrappingNodalKernel"; - auto params = _factory.getValidParams(kernel_type); - assignBlocks(params, blocks); - params.set("variable") = species_name; - params.set>("mobile_concentration") = {mobile_species_name}; mooseAssert(c_i < _component_temperatures.size(), "Should not happen"); - // The default coupled value will not have been created by the Builder since we created - // the parameter as a MooseFunctorName in the Physics if (MooseUtils::parsesToReal(_component_temperatures[c_i])) { std::istringstream ss(_component_temperatures[c_i]); Real value; ss >> value; - params.defaultCoupledValue("temperature", value, 0); - params.set>("temperature") = {}; + p.defaultCoupledValue("temperature", value, 0); + p.set>("temperature") = {}; } else if (getProblem().hasVariable(_component_temperatures[c_i])) - params.set>("temperature") = {_component_temperatures[c_i]}; + p.set>("temperature") = {_component_temperatures[c_i]}; else paramError("temperature", "Should be a constant or the name of a variable"); + }; - params.set("alpha_t") = _alpha_ts[c_i][s_j]; + // Trapping term + { + const std::string kernel_type = + _use_dimensionless_species ? "TrappingNodalKernelDimensionless" : "TrappingNodalKernel"; + auto params = _factory.getValidParams(kernel_type); + assignBlocks(params, blocks); + params.set("variable") = species_name; + params.set>("mobile_concentration") = {mobile_species_name}; + setTemperature(params); params.set("trapping_energy") = _trapping_energies[c_i][s_j]; params.set("N") = _Ns[c_i]; params.set("Ct0") = _Ct0s[c_i][s_j]; - params.set("trap_per_free") = _trap_per_frees[c_i]; - // Add the other species as occupying traps - std::vector copy_species; - for (const auto & sp_name : _species[c_i]) - if (sp_name != species_name) - copy_species.push_back(sp_name); - if (copy_species.size() && !getParam("different_traps_for_each_species")) - params.set>("other_trapped_concentration_variables") = - copy_species; + if (_use_dimensionless_species) + { + params.set("dimensionless_trapping_rate_coefficient") = + dimensionlessTrappingRate(c_i, s_j); + params.set("trap_concentration_reference") = trapConcentrationReference(c_i, s_j); + } + else + params.set("alpha_t") = _alpha_ts[c_i][s_j]; + + // Add the other species as occupying traps (shared-site physics). + if (!getParam("different_traps_for_each_species")) + { + std::vector copy_species; + for (const auto & sp_name : _species[c_i]) + if (sp_name != species_name) + copy_species.push_back(sp_name); + + if (copy_species.size()) + { + params.set>("other_trapped_concentration_variables") = + copy_species; + + if (_use_dimensionless_species) + { + // Collect the reference concentration for each other trap species so the + // dimensionless kernel can convert Ct_hat_j -> physical C_t_j. + std::vector other_refs; + other_refs.reserve(copy_species.size()); + for (unsigned int k = 0; k < _species[c_i].size(); ++k) + if (_species[c_i][k] != species_name) + other_refs.push_back(trapConcentrationReference(c_i, k)); + params.set>("other_trap_concentration_references") = other_refs; + } + } + } getProblem().addNodalKernel(kernel_type, prefix() + species_name + "_enc_trapping", params); } // Release term { - const std::string kernel_type = "ReleasingNodalKernel"; + const std::string kernel_type = _use_dimensionless_species + ? "ReleasingNodalKernelDimensionless" + : "ReleasingNodalKernel"; auto params = _factory.getValidParams(kernel_type); assignBlocks(params, blocks); params.set("variable") = species_name; - params.set("alpha_r") = _alpha_rs[c_i][s_j]; params.set("detrapping_energy") = _detrapping_energies[c_i][s_j]; - // The default coupled value will not have been created by the Builder since we created - // the parameter as a MooseFunctorName in the Physics - if (MooseUtils::parsesToReal(_component_temperatures[c_i])) - { - std::istringstream ss(_component_temperatures[c_i]); - Real value; - ss >> value; - params.defaultCoupledValue("temperature", value, 0); - params.set>("temperature") = {}; - } - else if (getProblem().hasVariable(_component_temperatures[c_i])) - params.set>("temperature") = {_component_temperatures[c_i]}; + setTemperature(params); + + if (_use_dimensionless_species) + params.set("dimensionless_release_rate_coefficient") = + dimensionlessReleaseRate(c_i, s_j); else - // there is an error right above in the trapping term - mooseAssert(false, "Should be a constant or the name of a variable"); + params.set("alpha_r") = _alpha_rs[c_i][s_j]; getProblem().addNodalKernel(kernel_type, prefix() + species_name + "_enc_release", params); } - // Release term in the mobile species conservation equation + // Coupling of dC_t_i/dt into the mobile species conservation equation. { const std::string kernel_type = "ScaledCoupledTimeDerivative"; auto params = _factory.getValidParams(kernel_type); assignBlocks(params, blocks); params.set("variable") = mobile_species_name; params.set>("v") = {species_name}; - params.set("factor") = _trap_per_frees[c_i]; + if (_use_dimensionless_species) + // Dimensionless path: add (C_t_ref_i / C_m_ref) * dCt_hat_i/dt. + params.set("factor") = + trapConcentrationReference(c_i, s_j) / mobileConcentrationReference(c_i); + else + params.set("factor") = _trap_per_frees[c_i]; getProblem().addKernel( kernel_type, prefix() + mobile_species_name + "_from_" + species_name, params); diff --git a/test/tests/actioncomponents/exceptions/tests b/test/tests/actioncomponents/exceptions/tests index ec6fbaf14..c4ebdc789 100644 --- a/test/tests/actioncomponents/exceptions/tests +++ b/test/tests/actioncomponents/exceptions/tests @@ -126,7 +126,7 @@ input = structure1D.i cli_args = "ActionComponents/structure/property_names='a b c d e f g diff' ActionComponents/structure/temperature=100" detail = "both not specified but necessary to define the equations." - expect_err = "alpha_t: This parameter should be specified, in the Physics 'trapped' \(applying to all components\) or in component 'structure' using the property_name 'alpha_t'" + expect_err = "(trapping_energy)|(alpha_t): This parameter should be specified, in the Physics 'trapped' \(applying to all components\) or in component 'structure' using the property_name 'alpha_t'" [] [] [] diff --git a/test/tests/physics/exceptions/tests b/test/tests/physics/exceptions/tests index 8c6ca3876..c5bad433d 100644 --- a/test/tests/physics/exceptions/tests +++ b/test/tests/physics/exceptions/tests @@ -152,7 +152,9 @@ [alpha_t] type = RunException input = trapping.i - cli_args = "ActionComponents/structure/physics=mobile_diff" + cli_args = "ActionComponents/structure/physics=mobile_diff Physics/SpeciesTrapping/trapped/trapping_energy=0 + Physics/SpeciesTrapping/trapped/N=1 Physics/SpeciesTrapping/trapped/Ct0=1 + Physics/SpeciesTrapping/trapped/detrapping_energy=0 Physics/SpeciesTrapping/trapped/trap_per_free=1" detail = "the trapping coefficient is not specified," expect_err = "alpha_t: Should not be empty if not using Components" [] @@ -182,7 +184,8 @@ type = RunException input = trapping.i cli_args = "ActionComponents/structure/physics=mobile_diff Physics/SpeciesTrapping/trapped/alpha_t=1 - Physics/SpeciesTrapping/trapped/trapping_energy=0 Physics/SpeciesTrapping/trapped/N=1 Physics/SpeciesTrapping/trapped/Ct0=1" + Physics/SpeciesTrapping/trapped/trapping_energy=0 Physics/SpeciesTrapping/trapped/N=1 Physics/SpeciesTrapping/trapped/Ct0=1 + Physics/SpeciesTrapping/trapped/detrapping_energy=0" detail = "the number of traps filled per free particle trapped is not specified," expect_err = "trap_per_free: Should not be empty if not using Components" [] @@ -191,7 +194,8 @@ input = trapping.i cli_args = "ActionComponents/structure/physics=mobile_diff Physics/SpeciesTrapping/trapped/alpha_t=1 Physics/SpeciesTrapping/trapped/trapping_energy=0 Physics/SpeciesTrapping/trapped/N=1 - Physics/SpeciesTrapping/trapped/Ct0=1 Physics/SpeciesTrapping/trapped/trap_per_free=1" + Physics/SpeciesTrapping/trapped/Ct0=1 Physics/SpeciesTrapping/trapped/trap_per_free=1 + Physics/SpeciesTrapping/trapped/detrapping_energy=0" detail = "the release coefficient is not specified," expect_err = "alpha_r: Should not be empty if not using Components" [] diff --git a/test/tests/physics/more_species_on_component/gold/species_trapping_dimensionless_other_trap_out.csv b/test/tests/physics/more_species_on_component/gold/species_trapping_dimensionless_other_trap_out.csv new file mode 100644 index 000000000..ead887704 --- /dev/null +++ b/test/tests/physics/more_species_on_component/gold/species_trapping_dimensionless_other_trap_out.csv @@ -0,0 +1,7 @@ +time,ave_mobile,ave_trapped_a,ave_trapped_b,scale_trapped_a,scale_trapped_b,sum +0,0,0,0,0,0,0 +0.1,0.74137192247467,0.064657019381334,0.043104679587556,0.12931403876267,0.12931403876267,1 +0.2,0.55526906948844,0.11118273262789,0.074121821751927,0.22236546525578,0.22236546525578,1 +0.3,0.41902863228188,0.14524284192953,0.096828561286354,0.29048568385906,0.29048568385906,1 +0.4,0.31799986155078,0.1705000346123,0.11366668974154,0.34100006922461,0.34100006922461,1 +0.5,0.24235302594906,0.18941174351273,0.12627449567516,0.37882348702547,0.37882348702547,1 diff --git a/test/tests/physics/more_species_on_component/species_trapping_dimensionless_other_trap.i b/test/tests/physics/more_species_on_component/species_trapping_dimensionless_other_trap.i new file mode 100644 index 000000000..b05ca8d31 --- /dev/null +++ b/test/tests/physics/more_species_on_component/species_trapping_dimensionless_other_trap.i @@ -0,0 +1,123 @@ +# This input file tests the physics syntax and dimensionless capabilities with two traps. + +[ActionComponents] + [structure] + type = Structure1D + species = 'trapped_a trapped_b' + species_initial_concentrations = '0 0.5' + species_scaling_factors = '1 1' + + physics = 'trapped' + temperature = '1' + + # Material properties + property_names = 'dimensionless_trapping_rate_coefficient_trapped_a + dimensionless_trapping_rate_coefficient_trapped_b + N + Ct0_trapped_a + Ct0_trapped_b + trap_concentration_reference_trapped_a + trap_concentration_reference_trapped_b + trapping_energy_trapped_a + trapping_energy_trapped_b + dimensionless_release_rate_coefficient_trapped_a + dimensionless_release_rate_coefficient_trapped_b + detrapping_energy_trapped_a + detrapping_energy_trapped_b + mobile_concentration_reference' + property_values = '1 + 1 + 10 + 0.5 + 0.5 + 2 + 3 + 1 + 1 + 0 + 0 + 0 + 0 + 1' + + # Geometry + nx = 20 + xmax = 1 + length_unit_scaling = 1 + [] +[] + +[Variables] + [mobile] + initial_condition = 1 + [] +[] + +[Physics] + [SpeciesTrapping] + [trapped] + species = 'trapped_a trapped_b' + mobile = 'mobile mobile' + dimensionless_species = true + [] + [] +[] + +[Kernels] + [mobile_time] + type = TimeDerivative + variable = mobile + [] +[] + +[Preconditioning] + [smp] + type = SMP + full = true + [] +[] + +[Executioner] + type = Transient + solve_type = NEWTON + + num_steps = 5 + dt = 0.1 + + petsc_options_iname = '-pc_type -pc_factor_mat_solver_type' + petsc_options_value = 'lu mumps' +[] + +[Outputs] + csv = true +[] + +[Postprocessors] + [ave_mobile] + type = ElementAverageValue + variable = mobile + [] + [ave_trapped_a] + type = ElementAverageValue + variable = trapped_a + [] + [ave_trapped_b] + type = ElementAverageValue + variable = trapped_b + [] + [scale_trapped_a] + type = ScalePostprocessor + value = ave_trapped_a + scaling_factor = 2 + [] + [scale_trapped_b] + type = ScalePostprocessor + value = ave_trapped_b + scaling_factor = 3 + [] + [sum] + type = ParsedPostprocessor + expression = 'scale_trapped_a + scale_trapped_b + ave_mobile' + pp_names = 'scale_trapped_a scale_trapped_b ave_mobile' + [] +[] diff --git a/test/tests/physics/more_species_on_component/tests b/test/tests/physics/more_species_on_component/tests index 573106c5a..d3f45268c 100644 --- a/test/tests/physics/more_species_on_component/tests +++ b/test/tests/physics/more_species_on_component/tests @@ -14,4 +14,11 @@ design = 'SpeciesTrappingPhysics.md' requirement = 'The system shall be able to accept parameters for species trapping on a component with the trapping physics parameters defined for a single species.' [] + [trapping_dimensionless_other_trap] + type = CSVDiff + input = 'species_trapping_dimensionless_other_trap.i' + csvdiff = 'species_trapping_dimensionless_other_trap_out.csv' + design = 'SpeciesTrappingPhysics.md' + requirement = 'The system shall couple dimensionless trapped species on a component through shared trap occupancy using physics-syntax generated dimensionless trapping kernels.' + [] [] diff --git a/test/tests/val-2c/gold/val-2c_delay_calibrated_ie_out.csv b/test/tests/val-2c/gold/val-2c_delay_calibrated_ie_out.csv new file mode 100644 index 000000000..62b3df295 --- /dev/null +++ b/test/tests/val-2c/gold/val-2c_delay_calibrated_ie_out.csv @@ -0,0 +1,245 @@ 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b/test/tests/val-2c/gold/val-2c_immediate_injection_ie_out.e differ diff --git a/test/tests/val-2c/gold/val-2c_immediate_injection_out.e b/test/tests/val-2c/gold/val-2c_immediate_injection_out.e deleted file mode 100644 index 8738db7c8..000000000 Binary files a/test/tests/val-2c/gold/val-2c_immediate_injection_out.e and /dev/null differ diff --git a/test/tests/val-2c/gold/val-2c_pss_results_short/val-2c_pss_main_short_out.json b/test/tests/val-2c/gold/val-2c_pss_results_short/val-2c_pss_main_short_out.json index 8471ee51a..700f03a41 100644 --- a/test/tests/val-2c/gold/val-2c_pss_results_short/val-2c_pss_main_short_out.json +++ b/test/tests/val-2c/gold/val-2c_pss_results_short/val-2c_pss_main_short_out.json @@ -1,11 +1,11 @@ { "app_name": "main", - "current_time": "Fri Aug 1 14:20:10 2025", - "executable": "/Users/simopa/projects/TMAP8/tmap8-opt", - "executable_time": "Wed Jul 30 22:31:04 2025", + "current_time": "Tue Apr 7 14:30:01 2026", + "executable": "/Users/yangl/projects/TMAP8_tmp/tmap8-opt", + "executable_time": "Mon Apr 6 16:05:54 2026", "libmesh_version": "", - "moose_version": "git commit af6d54ecda on 2025-06-18", - "petsc_version": "3.23.0", + "moose_version": "git commit 59c9432dc9 on 2026-03-20", + "petsc_version": "3.24.5", "reporters": { "adaptive_MC": { "type": "AdaptiveMonteCarloDecision", @@ -34,7 +34,7 @@ } } }, - "slepc_version": "3.23.0", + "slepc_version": "3.24.0", "time_steps": [ { "adaptive_MC": { @@ -77,7 +77,7 @@ "adaptive_MC": { "inputs": [ [ - 2.4963608122190893e-11 + 2.4974758571600343e-11 ], [ 2.8506657131076936 @@ -96,7 +96,7 @@ ] ], "output_required": [ - 1255405793.596708 + 1254728920.0395682 ] }, "constant": { @@ -104,7 +104,7 @@ true ], "reporter_transfer:objective:value": [ - 1255405793.596708 + 1254728920.0395682 ] }, "time": 1.0, @@ -114,7 +114,7 @@ "adaptive_MC": { "inputs": [ [ - 2.6441967483600986e-11 + 2.6453778269095973e-11 ], [ 3.852092488673211 @@ -133,7 +133,7 @@ ] ], "output_required": [ - 1159943479.9546928 + 1160040561.1742628 ] }, "constant": { @@ -141,7 +141,7 @@ true ], "reporter_transfer:objective:value": [ - 1159943479.9546928 + 1160040561.1742628 ] }, "time": 2.0, diff --git a/test/tests/val-2c/tests b/test/tests/val-2c/tests index 1a5ca4185..b76908e5f 100644 --- a/test/tests/val-2c/tests +++ b/test/tests/val-2c/tests @@ -2,67 +2,60 @@ design = 'val-2c.md' validation = 'val-2c.md' issues = '#12 #98' - [val-2c_immediate_injection_csv] + # Check test data consistency across operating systems and core counts for heavy tests using `Executioner/scheme=implicit-euler` due to its high stability + [val-2c_immediate_injection_csv_implicit-euler] type = CSVDiff input = val-2c_immediate_injection.i - cli_args = 'Outputs/exodus=true' - csvdiff = val-2c_immediate_injection_csv.csv + cli_args = 'Executioner/scheme=implicit-euler Outputs/exodus=true Outputs/file_base=val-2c_immediate_injection_ie_out' + csvdiff = val-2c_immediate_injection_ie_out.csv requirement = 'The system shall be able to model the Test Cell Release Experiment (val-2c) with immediate T2 injection.' - max_parallel = 1 # see #200 - recover = false # see #196 + rel_err = 3e-5 [] - [val-2c_immediate_injection_exodus] + [val-2c_immediate_injection_exodus_implicit-euler] type = Exodiff input = val-2c_immediate_injection.i - cli_args = 'Outputs/exodus=true' - prereq = val-2c_immediate_injection_csv + cli_args = 'Executioner/scheme=implicit-euler Outputs/exodus=true Outputs/file_base=val-2c_immediate_injection_ie_out' + prereq = val-2c_immediate_injection_csv_implicit-euler should_execute = false # this test relies on the output files from val-2c_immediate_injection_csv, so it shouldn't be run twice - exodiff = val-2c_immediate_injection_out.e + exodiff = val-2c_immediate_injection_ie_out.e custom_cmp = 'val-2c_exodus.exodiff' requirement = 'The system shall be able to model the Test Cell Release Experiment (val-2c) with immediate T2 injection and properly compute the exodus file.' - max_parallel = 1 # see #200 - recover = false # see #196 [] - [val-2c_delay_csv] + [val-2c_delay_csv_implicit-euler] type = CSVDiff input = val-2c_delay.i - cli_args = 'Outputs/exodus=true' - csvdiff = val-2c_delay_csv.csv + cli_args = 'Executioner/scheme=implicit-euler Outputs/exodus=true Outputs/file_base=val-2c_delay_ie_out' + csvdiff = val-2c_delay_ie_out.csv requirement = 'The system shall be able to model the Test Cell Release Experiment (val-2c) with delayed T2 injection.' abs_zero = 1e-8 rel_err = 3e-5 - max_parallel = 1 # see #200 - recover = false # see #196 [] - [val-2c_delay_exodus] + [val-2c_delay_exodus_implicit-euler] type = Exodiff input = val-2c_delay.i - cli_args = 'Outputs/exodus=true' - prereq = val-2c_delay_csv + cli_args = 'Executioner/scheme=implicit-euler Outputs/exodus=true Outputs/file_base=val-2c_delay_ie_out' + prereq = val-2c_delay_csv_implicit-euler should_execute = false # this test relies on the output files from val-2c_delay_csv, so it shouldn't be run twice - exodiff = val-2c_delay_out.e + exodiff = val-2c_delay_ie_out.e custom_cmp = 'val-2c_exodus.exodiff' requirement = 'The system shall be able to model the Test Cell Release Experiment (val-2c) with delayed T2 injection and properly compute the exodus file.' - max_parallel = 1 # see #200 - recover = false # see #196 [] - [val-2c_delay_calibrated_csv] + [val-2c_delay_calibrated_csv_implicit-euler] type = CSVDiff input = 'val-2c_delay.i' - # the parameter values below are from gold/calibrated_parameter_values.txt + # the parameter values below are from gold/calibrated_parameter_values.txt cli_args = 'reaction_rate=2.8331901331213944e-11 diffusivity_elemental_tritium=3.8640662435310973 diffusivity_tritiated_water=0.017373835349450507 log_solubility_elemental_tritium=-3.683352919815223 log_solubility_tritiated_water=6.8938628913078555 time_injection_T2_end=9536.239653312441 - Outputs/file_base=val-2c_delay_calibrated_out' - csvdiff = val-2c_delay_calibrated_out.csv + Executioner/scheme=implicit-euler + Outputs/file_base=val-2c_delay_calibrated_ie_out' + csvdiff = val-2c_delay_calibrated_ie_out.csv requirement = 'The system shall be able to model the Test Cell Release Experiment (val-2c) with delayed T2 injection using calibrated model parameters.' abs_zero = 1e-8 - rel_err = 2e-5 - max_parallel = 1 # see #200 - recover = false # see #196 + rel_err = 3e-5 issues = '#266' [] [val-2c_delay_pss_study_csv] @@ -78,9 +71,9 @@ requirement = 'The system shall be able to perform a Parallel Subset Simulation study using a model of the Test Cell Release Experiment (val-2c) with delayed T2 injection.' abs_zero = 1e-8 rel_err = 1e-5 - max_parallel = 1 # see #200 - recover = false # see #196 + recover = false # moose#24460 and moose#32193 and #192 issues = '#266' + skip_keys = 'number_of_parts part' [] [val-2c_delay_comparison] type = RunCommand @@ -88,4 +81,36 @@ requirement = 'The system shall be able to generate comparison plots between simulated solutions and experimental data of validation cases val-2c, modeling a Test Cell Release Experiment.' required_python_packages = 'matplotlib numpy pandas scipy os json' [] + # Check the test data for the same heavy tests using 'Executioner/scheme=bdf2' for documentation. Since consistency has already been verified with `Executioner/scheme=implicit-euler` tests, the error tolerance can be relaxed. + [val-2c_immediate_injection_csv_bdf2] + type = CSVDiff + input = val-2c_immediate_injection.i + csvdiff = val-2c_immediate_injection_csv.csv + requirement = 'The system shall be able to model the Test Cell Release Experiment (val-2c) with immediate T2 injection to generate output data for documentation.' + rel_err = 3e-5 + [] + [val-2c_delay_csv_bdf2] + type = CSVDiff + input = val-2c_delay.i + csvdiff = val-2c_delay_csv.csv + requirement = 'The system shall be able to model the Test Cell Release Experiment (val-2c) with delayed T2 injection to generate output data for documentation.' + abs_zero = 2e-4 + rel_err = 5e-5 + [] + [val-2c_delay_calibrated_csv_bdf2] + type = CSVDiff + input = 'val-2c_delay.i' + csvdiff = val-2c_delay_calibrated_out.csv + # the parameter values below are from gold/calibrated_parameter_values.txt + cli_args = 'reaction_rate=2.8331901331213944e-11 + diffusivity_elemental_tritium=3.8640662435310973 + diffusivity_tritiated_water=0.017373835349450507 + log_solubility_elemental_tritium=-3.683352919815223 + log_solubility_tritiated_water=6.8938628913078555 + time_injection_T2_end=9536.239653312441 + Outputs/file_base=val-2c_delay_calibrated_out' + requirement = 'The system shall be able to model the Test Cell Release Experiment (val-2c) with delayed T2 injection using calibrated model parameters to generate output data for documentation.' + abs_zero = 2e-4 + rel_err = 5e-5 + [] [] diff --git a/test/tests/val-2c/val-2c_base.i b/test/tests/val-2c/val-2c_base.i index c173c63fb..2be7af90c 100644 --- a/test/tests/val-2c/val-2c_base.i +++ b/test/tests/val-2c/val-2c_base.i @@ -107,42 +107,42 @@ variable = bounds_dummy_t2_paint_concentration bounded_variable = t2_paint_concentration bound_type = lower - bound_value = ${lower_value_threshold} + bound_value = 0 [] [t2_enclosure_concentration_lower_bound] type = ConstantBounds variable = bounds_dummy_t2_enclosure_concentration bounded_variable = t2_enclosure_concentration bound_type = lower - bound_value = ${lower_value_threshold} + bound_value = 0 [] [hto_paint_concentration_lower_bound] type = ConstantBounds variable = bounds_dummy_hto_paint_concentration bounded_variable = hto_paint_concentration bound_type = lower - bound_value = ${lower_value_threshold} + bound_value = 0 [] [hto_enclosure_concentration_lower_bound] type = ConstantBounds variable = bounds_dummy_hto_enclosure_concentration bounded_variable = hto_enclosure_concentration bound_type = lower - bound_value = ${lower_value_threshold} + bound_value = 0 [] [h2o_paint_concentration_lower_bound] type = ConstantBounds variable = bounds_dummy_h2o_paint_concentration bounded_variable = h2o_paint_concentration bound_type = lower - bound_value = -1e-4 + bound_value = 0 [] [h2o_enclosure_concentration_lower_bound] type = ConstantBounds variable = bounds_dummy_h2o_enclosure_concentration bounded_variable = h2o_enclosure_concentration bound_type = lower - bound_value = -1e-4 + bound_value = 0 [] [] @@ -550,13 +550,12 @@ type = Transient solve_type = NEWTON scheme = 'bdf2' - - petsc_options_iname = '-pc_type -sub_pc_type -snes_type' - petsc_options_value = 'asm lu vinewtonrsls' # This petsc option helps prevent negative concentrations with bounds' + petsc_options_iname = '-pc_type -snes_type -pc_factor_mat_solver_type' + petsc_options_value = 'lu vinewtonrsls mumps' nl_rel_tol = 1.e-10 automatic_scaling = true - compute_scaling_once = false + compute_scaling_once = true end_time = ${time_end} dtmax = ${dtmax} @@ -573,7 +572,7 @@ [] [Outputs] - perf_graph = true + exodus = false [csv] type = CSV execute_on = 'initial timestep_end' diff --git a/test/tests/val-2c/val-2c_delay.params b/test/tests/val-2c/val-2c_delay.params index 2b572fd72..b2646481d 100644 --- a/test/tests/val-2c/val-2c_delay.params +++ b/test/tests/val-2c/val-2c_delay.params @@ -43,7 +43,6 @@ time_injection_T2_start = ${units 0 h -> s} time_injection_T2_end = ${units 3 h -> s} dtmax = ${units 1e3 s} dtmin = ${units 1 s} -lower_value_threshold = ${units -1e-20 at/mum^3} # lower limit for concentration injection_rate_T2 = ${units ${fparse initial_T2_concentration / (time_injection_T2_end-time_injection_T2_start)} at/mum^3/s} ## Inflow and outflow diff --git a/test/tests/val-2c/val-2c_exodus.exodiff b/test/tests/val-2c/val-2c_exodus.exodiff index 8ad896f13..d668faf8c 100644 --- a/test/tests/val-2c/val-2c_exodus.exodiff +++ b/test/tests/val-2c/val-2c_exodus.exodiff @@ -30,29 +30,29 @@ # TIME STEPS relative 1.e-6 floor 0.0 GLOBAL VARIABLES relative 5.5.e-6 floor 1e-10 - h2o_enclosure_edge_concentration - h2o_enclosure_inventory - h2o_paint_inventory - ht_enclosure_edge_concentration - ht_enclosure_inventory - ht_paint_inventory - hto_enclosure_edge_concentration - hto_enclosure_inventory - hto_paint_inventory - t2_enclosure_edge_concentration - t2_enclosure_inventory - t2_paint_inventory - tritium_total_inventory + h2o_enclosure_edge_concentration + h2o_enclosure_inventory + h2o_paint_inventory + ht_enclosure_edge_concentration + ht_enclosure_inventory + ht_paint_inventory + hto_enclosure_edge_concentration + hto_enclosure_inventory + hto_paint_inventory + t2_enclosure_edge_concentration + t2_enclosure_inventory + t2_paint_inventory + tritium_total_inventory NODAL VARIABLES relative 5.5.e-6 floor 1e-10 - h2o_enclosure_concentration - h2o_paint_concentration - ht_enclosure_concentration - ht_paint_concentration - hto_enclosure_concentration - hto_paint_concentration relative 1.0e-04 floor 7.e-6 - t2_enclosure_concentration - t2_paint_concentration + h2o_enclosure_concentration + h2o_paint_concentration + ht_enclosure_concentration + ht_paint_concentration + hto_enclosure_concentration + hto_paint_concentration relative 3e-04 floor 7.e-6 + t2_enclosure_concentration + t2_paint_concentration # No ELEMENT VARIABLES diff --git a/test/tests/val-2c/val-2c_immediate_injection.i b/test/tests/val-2c/val-2c_immediate_injection.i index 89e24cd7a..e9d914162 100644 --- a/test/tests/val-2c/val-2c_immediate_injection.i +++ b/test/tests/val-2c/val-2c_immediate_injection.i @@ -40,7 +40,6 @@ time_step = '${units 1 s}' time_end = '${units 180000 s}' dtmax = '${units 1e3 s}' dtmin = '${units 1 s}' -lower_value_threshold = '${units -1e-20 at/mum^3}' # lower limit for concentration ## Inflow and outflow inflow = '${units 0.54 m^3/h -> mum^3/s}' # inflow of normally moist (20% relative humidity) air at the same temperature as the enclosure diff --git a/test/tests/val-2f/gold/val-2f_heavy_desorption_inf_recombination_out.csv b/test/tests/val-2f/gold/val-2f_heavy_desorption_inf_recombination_out.csv new file mode 100644 index 000000000..6050b3c97 --- /dev/null +++ b/test/tests/val-2f/gold/val-2f_heavy_desorption_inf_recombination_out.csv @@ -0,0 +1,439 @@ 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+316172.40682991,5.3171707926061e+19,77804.928201904,1101908046.7943,-71407.629801376,0,63015.980696032,23767120.974556,22248603.010396,33409239.370003,41517131.03225,73780184.81882,167.51466156533,988.62034149541 +316239.10617814,5.3171707926061e+19,77804.928201904,1257786164.627,-36836.87675869,0,67800.066889321,23783009.808076,22317976.245216,33226498.194811,41201961.665929,71799552.639318,199.93961527438,991.95530890677 +316312.47546119,5.3171707926061e+19,77804.928201904,1432975411.1023,2088.7684387814,0,73199.054003195,23800487.524983,22394286.804048,34181486.838575,40189963.120125,70899064.376213,235.69884187388,995.62377305926 +316393.18167254,5.3171707926061e+19,77804.928201904,1630219276.6739,-50983.29566467,0,94007.061641065,23819713.013624,22478228.419371,35203582.759132,39671875.430287,68560815.209914,275.16881756729,999.659083627 +316400,5.3171707926061e+19,77804.928201904,1647101822.9725,-55541.115433276,0,96267.942965251,23821337.246445,22485320.084484,35332530.347769,39691466.595889,68512513.927488,278.57591057389,1000 diff --git a/test/tests/val-2f/parameters_val-2f.params b/test/tests/val-2f/parameters_val-2f.params index 64daebf8e..99b6804fd 100644 --- a/test/tests/val-2f/parameters_val-2f.params +++ b/test/tests/val-2f/parameters_val-2f.params @@ -19,7 +19,6 @@ desorption_heating_rate = '${units ${fparse 3/60} K/s}' charge_time = '${units 72 h -> s}' cooldown_duration = '${units 12 h -> s}' desorption_duration = '${fparse (temperature_desorption_max-temperature_desorption_min)/desorption_heating_rate}' -endtime = '${fparse charge_time + cooldown_duration + desorption_duration}' dt_init = 1e-8 # Materials properties @@ -45,7 +44,6 @@ dx1 = '${fparse 6*sigma}' dx2 = '${units 3e-6 m -> mum}' dx3 = '${units 7.997e-6 m -> mum}' dx4 = '${units 7.2e-5 m -> mum}' -dx5 = '${fparse sample_thickness - dx1 - dx2 - dx3 - dx4}' ix1 = 100 ix2 = 100 ix3 = 100 @@ -74,7 +72,7 @@ trap_density_01dpa_1 = '${units ${fparse -S_1/r_1 * exp(-r_1*damage_duration) + trapping_site_fraction_1 = '${fparse trap_density_01dpa_1 / tungsten_density}' trap_density_01dpa_1_inf = '${units 4.8e25 at/m^3 -> at/mum^3}' trapping_site_fraction_1_inf = '${fparse trap_density_01dpa_1_inf / tungsten_density}' -trap_per_free_1 = 1e7 # (-) +trap_concentration_reference_1 = '${fparse tungsten_density * 1e-8}' # Trap 2 parameters trapping_energy_2 = '${fparse trapping_energy}' @@ -91,7 +89,7 @@ trap_density_01dpa_2 = '${units ${fparse -S_2/r_2 * exp(-r_2*damage_duration) + trapping_site_fraction_2 = '${fparse trap_density_01dpa_2 / tungsten_density}' trap_density_01dpa_2_inf = '${units 3.8e25 at/m^3 -> at/mum^3}' trapping_site_fraction_2_inf = '${fparse trap_density_01dpa_2_inf / tungsten_density}' -trap_per_free_2 = 1e7 # (-) +trap_concentration_reference_2 = '${fparse tungsten_density * 1e-8}' # Trap 3 parameters trapping_energy_3 = '${fparse trapping_energy}' @@ -108,7 +106,7 @@ trap_density_01dpa_3 = '${units ${fparse -S_3/r_3 * exp(-r_3*damage_duration) + trapping_site_fraction_3 = '${fparse trap_density_01dpa_3 / tungsten_density}' trap_density_01dpa_3_inf = '${units 2.6e25 at/m^3 -> at/mum^3}' trapping_site_fraction_3_inf = '${fparse trap_density_01dpa_3_inf / tungsten_density}' -trap_per_free_3 = 1e7 # (-) +trap_concentration_reference_3 = '${fparse tungsten_density * 1e-8}' # Trap 4 parameters trapping_energy_4 = '${fparse trapping_energy}' @@ -125,7 +123,7 @@ trap_density_01dpa_4 = '${units ${fparse -S_4/r_4 * exp(-r_4*damage_duration) + trapping_site_fraction_4 = '${fparse trap_density_01dpa_4 / tungsten_density}' trap_density_01dpa_4_inf = '${units 3.6e25 at/m^3 -> at/mum^3}' trapping_site_fraction_4_inf = '${fparse trap_density_01dpa_4_inf / tungsten_density}' -trap_per_free_4 = 1e7 # (-) +trap_concentration_reference_4 = '${fparse tungsten_density * 1e-8}' # Trap 5 parameters trapping_energy_5 = '${fparse trapping_energy}' @@ -140,7 +138,7 @@ trap_density_01dpa_5 = '${units ${fparse -S_5/r_5 * exp(-r_5*damage_duration) + trapping_site_fraction_5 = '${fparse trap_density_01dpa_5 / tungsten_density}' trap_density_01dpa_5_inf = '${units 1.1e25 at/m^3 -> at/mum^3}' trapping_site_fraction_5_inf = '${fparse trap_density_01dpa_5_inf / tungsten_density}' -trap_per_free_5 = 1e7 # (-) +trap_concentration_reference_5 = '${fparse tungsten_density * 1e-8}' # Trap intrinsic parameters trapping_energy_intrinsic = '${fparse trapping_energy}' @@ -149,4 +147,47 @@ detrapping_energy_intrinsic = '${fparse ${units 1.04 eV -> J} / kb}' detrapping_prefactor_intrinsic = '${fparse detrapping_prefactor}' trap_density_01dpa_intrinsic = '${units 2.4e22 at/m^3 -> at/mum^3}' trapping_site_fraction_intrinsic = '${fparse trap_density_01dpa_intrinsic / tungsten_density}' -trap_per_free_intrinsic = 1e7 # (-) +trap_concentration_reference_intrinsic = '${fparse tungsten_density * 1e-11}' + +mobile_concentration_reference = '${fparse tungsten_density * 1e-12}' +length_reference = ${units 1 mum} +time_reference = ${units 1 s} + +# Dimensionless trap rate groups: k_t_hat = alpha_t * C_m_ref / N * t_ref +# (from nondimensionalizing dC_t/dt = alpha_t/N * C_m * (N*Ct0 - C_t)) +dimensionless_trapping_rate_coefficient_intrinsic = '${fparse trapping_prefactor_intrinsic * time_reference * mobile_concentration_reference / tungsten_density}' +dimensionless_trapping_rate_coefficient_1 = '${fparse trapping_prefactor_1 * time_reference * mobile_concentration_reference / tungsten_density}' +dimensionless_trapping_rate_coefficient_2 = '${fparse trapping_prefactor_2 * time_reference * mobile_concentration_reference / tungsten_density}' +dimensionless_trapping_rate_coefficient_3 = '${fparse trapping_prefactor_3 * time_reference * mobile_concentration_reference / tungsten_density}' +dimensionless_trapping_rate_coefficient_4 = '${fparse trapping_prefactor_4 * time_reference * mobile_concentration_reference / tungsten_density}' +dimensionless_trapping_rate_coefficient_5 = '${fparse trapping_prefactor_5 * time_reference * mobile_concentration_reference / tungsten_density}' + +dimensionless_release_rate_coefficient_intrinsic = '${fparse detrapping_prefactor_intrinsic * time_reference}' +dimensionless_release_rate_coefficient_1 = '${fparse detrapping_prefactor_1 * time_reference}' +dimensionless_release_rate_coefficient_2 = '${fparse detrapping_prefactor_2 * time_reference}' +dimensionless_release_rate_coefficient_3 = '${fparse detrapping_prefactor_3 * time_reference}' +dimensionless_release_rate_coefficient_4 = '${fparse detrapping_prefactor_4 * time_reference}' +dimensionless_release_rate_coefficient_5 = '${fparse detrapping_prefactor_5 * time_reference}' + +# Dimensionless geometry and time quantities used by val-2f-dimensionless. +sigma_hat = '${fparse sigma / length_reference}' +R_p_hat = '${fparse R_p / length_reference}' +depth_center_hat = '${fparse depth_center / length_reference}' +depth_width_hat = '${fparse depth_width / length_reference}' +sample_thickness_hat = '${fparse sample_thickness / length_reference}' +dx1_hat = '${fparse dx1 / length_reference}' +dx2_hat = '${fparse dx2 / length_reference}' +dx3_hat = '${fparse dx3 / length_reference}' +dx4_hat = '${fparse dx4 / length_reference}' +dx5_hat = '${fparse sample_thickness_hat - dx1_hat - dx2_hat - dx3_hat - dx4_hat}' +charge_time_hat = '${fparse charge_time / time_reference}' +cooldown_duration_hat = '${fparse cooldown_duration / time_reference}' +desorption_duration_hat = '${fparse desorption_duration / time_reference}' +endtime_hat = '${fparse charge_time_hat + cooldown_duration_hat + desorption_duration_hat}' +desorption_heating_rate_hat = '${fparse desorption_heating_rate * time_reference}' + +# Dimensionless mobile transport quantities. +diffusion_W_preexponential_hat = '${fparse diffusion_W_preexponential * time_reference / (length_reference^2)}' +surface_flux_hat = '${fparse flux * time_reference / (mobile_concentration_reference * length_reference)}' +recombination_coefficient_hat = '${fparse recombination_coefficient * mobile_concentration_reference * time_reference / length_reference}' +sieverts_boundary_hat = '${fparse 1e-10 / mobile_concentration_reference}' diff --git a/test/tests/val-2f/tests b/test/tests/val-2f/tests index 645d7c546..26a85ee15 100644 --- a/test/tests/val-2f/tests +++ b/test/tests/val-2f/tests @@ -5,57 +5,136 @@ [val-2f_light_csv] type = CSVDiff input = val-2f.i - cli_args = "sample_thickness='${units 0.9e-4 m -> mum}' ix1=1 ix2=1 ix3=1 ix4=1 ix5=1 charge_time='${units 1e-1 s}' cooldown_duration='${units 1e-1 s}' Executioner/TimeStepper/timestep_limiting_postprocessor=max_time_step_size_coarse Outputs/file_base=val-2f_light_out" + cli_args = "sample_thickness='${units 0.9e-4 m -> mum}' + ix1=8 ix2=8 ix3=8 ix4=8 ix5=8 + dt_init=2e-3 + charge_time='${units 1e-1 s}' cooldown_duration='${units 1e-1 s}' + Executioner/TimeStepper/timestep_limiting_postprocessor=max_time_step_size_coarse + Outputs/file_base=val-2f_light_out + Outputs/csv/start_time=0.2 + Executioner/TimeStepper/growth_factor=1.05 + Executioner/scheme=implicit-euler" csvdiff = val-2f_light_out.csv requirement = 'The system shall be able to model self-damaged tungsten effects on deuterium transport and generate CSV data output with a short runtime and coarse mesh testing.' - max_parallel = 1 # see #200 + rel_err = 1e-3 + override_columns = 'scaled_flux_surface_right scaled_flux_surface_left scaled_mobile_deuterium' + override_abs_zero = '1e4 1e6 1e7' + override_rel_err = '1e-3 1e-3 1e-3' + # Some relevant scales when considering diffs + # + # scaled_flux_surface_right O(1e12) + # scaled_flux_surface_left O(1e19) + # scaled_mobile_deuterium O(1e13) + # scaled_trapped_deuterium_intrinsic O(1e14) [] [val-2f_light_exodus] type = Exodiff input = val-2f.i - cli_args = "sample_thickness='${units 0.9e-4 m -> mum}' ix1=1 ix2=1 ix3=1 ix4=1 ix5=1 charge_time='${units 1e-1 s}' cooldown_duration='${units 1e-1 s}' Executioner/TimeStepper/timestep_limiting_postprocessor=max_time_step_size_coarse Outputs/file_base=val-2f_light_out" exodiff = val-2f_light_out.e prereq = val-2f_light_csv should_execute = false # this test relies on the output files from val-2f_light_csv, so it shouldn't be run twice requirement = 'The system shall be able to model self-damaged tungsten effects on deuterium transport with a short runtime and coarse mesh testing.' - max_parallel = 1 # see #200 + rel_err = 1e-3 + abs_zero = 1e-5 [] - [val-2f_heavy_csv] + # Check test data consistency across operating systems and core counts for heavy tests using `Executioner/scheme=implicit-euler` due to its high stability + [val-2f_heavy_csv_implicit-euler] type = CSVDiff input = val-2f.i - csvdiff = val-2f_out.csv + cli_args = "Outputs/csv/start_time='${fparse charge_time_hat + cooldown_duration_hat}' + Outputs/csv/time_step_interval=2 + Outputs/exodus/start_time='${fparse charge_time_hat + cooldown_duration_hat}' + Outputs/exodus/time_step_interval=400 + Outputs/file_base=val-2f_heavy_desorption_out + Executioner/scheme=implicit-euler" + csvdiff = val-2f_heavy_desorption_out.csv heavy = true - requirement = 'The system shall be able to model self-damaged tungsten effects on deuterium transport and generate CSV data output.' + requirement = 'The system shall be able to model self-damaged tungsten effects on deuterium transport and generate CSV data output. Only desorption phase data is compared with every other timestep.' max_time = 2000 [] - [val-2f_heavy_exodus] + [val-2f_heavy_exodus_implicit-euler] type = Exodiff input = val-2f.i - exodiff = val-2f_out.e + cli_args = "Outputs/csv/start_time='${fparse charge_time_hat + cooldown_duration_hat}' + Outputs/csv/time_step_interval=2 + Outputs/exodus/start_time='${fparse charge_time_hat + cooldown_duration_hat}' + Outputs/exodus/time_step_interval=400 + Outputs/file_base=val-2f_heavy_desorption_out + Executioner/scheme=implicit-euler" + exodiff = val-2f_heavy_desorption_out.e heavy = true - prereq = val-2f_heavy_csv + prereq = val-2f_heavy_csv_implicit-euler should_execute = false # this test relies on the output files from val-2f_heavy_csv, so it shouldn't be run twice - requirement = 'The system shall be able to model self-damaged tungsten effects on deuterium transport.' + requirement = 'The system shall be able to model self-damaged tungsten effects on deuterium transport. Only desorption phase data is compared with every other timestep.' + [] + [val-2f_heavy_csv_inf_recombination_implicit-euler] + type = CSVDiff + input = val-2f.i + cli_args = "ix1='${fparse 500}' ix4='${fparse 500}' + AuxVariables/active='bounds_dummy temperature' + BCs/active='left_concentration_sieverts right_concentration_sieverts' + Physics/SpeciesTrapping/trapping_1/Ct0='trap_distribution_function_1_inf' + Physics/SpeciesTrapping/trapping_2/Ct0='trap_distribution_function_2_inf' + Physics/SpeciesTrapping/trapping_3/Ct0='trap_distribution_function_3_inf' + Physics/SpeciesTrapping/trapping_4/Ct0='trap_distribution_function_4_inf' + Physics/SpeciesTrapping/trapping_5/Ct0='trap_distribution_function_5_inf' + Materials/active='diffusivity_W_func diffusivity_nonAD' + Postprocessors/active='integral_source_deuterium scaled_implanted_deuterium integral_deuterium_concentration scaled_mobile_deuterium flux_surface_left_sieverts scaled_flux_surface_left_sieverts flux_surface_right_sieverts scaled_flux_surface_right_sieverts temperature max_time_step_size max_time_step_size_coarse integral_trapped_concentration_1 scaled_trapped_deuterium_1 integral_trapped_concentration_2 scaled_trapped_deuterium_2 integral_trapped_concentration_3 scaled_trapped_deuterium_3 integral_trapped_concentration_4 scaled_trapped_deuterium_4 integral_trapped_concentration_5 scaled_trapped_deuterium_5 integral_trapped_concentration_intrinsic scaled_trapped_deuterium_intrinsic' + Postprocessors/max_time_step_size/function=max_dt_size_function_inf + Outputs/csv/start_time='${fparse charge_time_hat + cooldown_duration_hat}' + Outputs/csv/time_step_interval=2 + Outputs/file_base=val-2f_heavy_desorption_inf_recombination_out + Executioner/abort_on_solve_fail=false + Executioner/nl_abs_tol=5e-4 + Executioner/scheme=implicit-euler" + csvdiff = val-2f_heavy_desorption_inf_recombination_out.csv + heavy = true + requirement = 'The system shall be able to model self-damaged tungsten effects on deuterium transport and generate CSV data output, for the infinite recombination case. Only desorption phase data is compared with every other timestep.' + max_time = 3600 + [] + # Check the test data for the same heavy tests using 'Executioner/scheme=bdf2' for documentation. Since consistency has already been verified with `Executioner/scheme=implicit-euler` tests, the error tolerance can be relaxed. + [val-2f_heavy_csv_bdf2] + type = CSVDiff + input = val-2f.i + cli_args = "Outputs/csv/start_time='${fparse charge_time_hat + cooldown_duration_hat}' + Outputs/csv/sync_times='${fparse charge_time_hat + cooldown_duration_hat}'" + csvdiff = val-2f_out.csv + heavy = true + requirement = 'The system shall be able to model self-damaged tungsten effects on deuterium transport and generate CSV data output.' + max_time = 2000 + rel_err = 1e-4 + override_columns = 'scaled_flux_surface_right scaled_flux_surface_left scaled_mobile_deuterium scaled_trapped_deuterium_1 scaled_trapped_deuterium_2' + override_abs_zero = '1e4 1e6 1e4 1e9 1e4' + override_rel_err = '5e-3 1e-3 9e-3 5e-3 5e-3' [] - [val-2f_heavy_csv_inf_recombination] + [val-2f_heavy_csv_inf_recombination_bdf2] type = CSVDiff input = val-2f.i cli_args = "ix1='${fparse 500}' ix4='${fparse 500}' AuxVariables/active='bounds_dummy temperature' BCs/active='left_concentration_sieverts right_concentration_sieverts' - NodalKernels/trapping_1/Ct0='trap_distribution_function_1_inf' - NodalKernels/trapping_2/Ct0='trap_distribution_function_2_inf' - NodalKernels/trapping_3/Ct0='trap_distribution_function_3_inf' - NodalKernels/trapping_4/Ct0='trap_distribution_function_4_inf' - NodalKernels/trapping_5/Ct0='trap_distribution_function_5_inf' + Physics/SpeciesTrapping/trapping_1/Ct0='trap_distribution_function_1_inf' + Physics/SpeciesTrapping/trapping_2/Ct0='trap_distribution_function_2_inf' + Physics/SpeciesTrapping/trapping_3/Ct0='trap_distribution_function_3_inf' + Physics/SpeciesTrapping/trapping_4/Ct0='trap_distribution_function_4_inf' + Physics/SpeciesTrapping/trapping_5/Ct0='trap_distribution_function_5_inf' Materials/active='diffusivity_W_func diffusivity_nonAD' - Postprocessors/active='integral_source_deuterium scaled_implanted_deuterium integral_deuterium_concentration scaled_mobile_deuterium flux_surface_left_sieverts scaled_flux_surface_left_sieverts flux_surface_right_sieverts scaled_flux_surface_right_sieverts temperature diffusion_W max_time_step_size max_time_step_size_coarse integral_trapped_concentration_1 scaled_trapped_deuterium_1 integral_trapped_concentration_2 scaled_trapped_deuterium_2 integral_trapped_concentration_3 scaled_trapped_deuterium_3 integral_trapped_concentration_4 scaled_trapped_deuterium_4 integral_trapped_concentration_5 scaled_trapped_deuterium_5 integral_trapped_concentration_intrinsic scaled_trapped_deuterium_intrinsic' + Postprocessors/active='integral_source_deuterium scaled_implanted_deuterium integral_deuterium_concentration scaled_mobile_deuterium flux_surface_left_sieverts scaled_flux_surface_left_sieverts flux_surface_right_sieverts scaled_flux_surface_right_sieverts temperature diffusion_W_hat diffusion_W max_time_step_size max_time_step_size_coarse integral_trapped_concentration_1 scaled_trapped_deuterium_1 integral_trapped_concentration_2 scaled_trapped_deuterium_2 integral_trapped_concentration_3 scaled_trapped_deuterium_3 integral_trapped_concentration_4 scaled_trapped_deuterium_4 integral_trapped_concentration_5 scaled_trapped_deuterium_5 integral_trapped_concentration_intrinsic scaled_trapped_deuterium_intrinsic spatial_max_mobile_d2 spatial_max_trapped_1 spatial_max_trapped_2 spatial_max_trapped_3 spatial_max_trapped_4 spatial_max_trapped_5 spatial_max_trapped_intrinsic max_mobile_d2 max_trapped_1 max_trapped_2 max_trapped_3 max_trapped_4 max_trapped_5 max_trapped_intrinsic max_scaled_flux_surface_left_sieverts max_scaled_flux_surface_right_sieverts max_scaled_mobile_deuterium max_scaled_trapped_deuterium_intrinsic' Postprocessors/max_time_step_size/function=max_dt_size_function_inf - Outputs/file_base='val-2f_out_inf_recombination'" + Outputs/file_base='val-2f_out_inf_recombination' + Outputs/csv/start_time='${fparse charge_time_hat + cooldown_duration_hat}' + Outputs/csv/sync_times='${fparse charge_time_hat + cooldown_duration_hat}' + Executioner/abort_on_solve_fail=false + Executioner/nl_abs_tol=5e-4" csvdiff = val-2f_out_inf_recombination.csv heavy = true requirement = 'The system shall be able to model self-damaged tungsten effects on deuterium transport and generate CSV data output, for the infinite recombination case.' max_time = 3600 + rel_err = 1e-5 + abs_zero = 1e4 + override_columns = 'scaled_flux_surface_right_sieverts scaled_flux_surface_left_sieverts scaled_mobile_deuterium scaled_trapped_deuterium_1 scaled_trapped_deuterium_2 scaled_trapped_deuterium_3 scaled_trapped_deuterium_4 scaled_trapped_deuterium_5' + override_abs_zero = '1e6 1e9 1e6 1e9 1e9 1e9 1e9 1e10' + override_rel_err = '1e-3 3e-3 5e-3 1e-3 1e-3 3e-3 1e-3 5e-5' [] [val-2f_comparison] type = RunCommand diff --git a/test/tests/val-2f/val-2f.i b/test/tests/val-2f/val-2f.i index c84d6c3ed..a2e75a417 100644 --- a/test/tests/val-2f/val-2f.i +++ b/test/tests/val-2f/val-2f.i @@ -16,7 +16,7 @@ [cartesian_mesh] type = CartesianMeshGenerator dim = 1 - dx = '${dx1} ${dx2} ${dx3} ${dx4} ${dx5}' + dx = '${dx1_hat} ${dx2_hat} ${dx3_hat} ${dx4_hat} ${dx5_hat}' ix = '${ix1} ${ix2} ${ix3} ${ix4} ${ix5}' subdomain_id = '0 0 0 0 0' [] @@ -44,7 +44,7 @@ variable = bounds_dummy bounded_variable = deuterium_concentration_W bound_type = lower - bound_value = '${fparse -1e-20}' + bound_value = 0 [] [] @@ -94,13 +94,13 @@ # Sieverts boundary conditions [left_concentration_sieverts] type = ADDirichletBC - value = '${fparse 1e-10}' + value = '${sieverts_boundary_hat}' boundary = left variable = deuterium_concentration_W [] [right_concentration_sieverts] type = ADDirichletBC - value = '${fparse 1e-10}' + value = '${sieverts_boundary_hat}' boundary = right variable = deuterium_concentration_W [] @@ -109,17 +109,17 @@ [Functions] [temperature_bc_func] type = ParsedFunction - expression = 'if(t<${charge_time}, ${temperature_initial}, - if(t<${fparse charge_time + cooldown_duration}, ${temperature_cooldown}, - ${temperature_desorption_min}+${desorption_heating_rate}*(t-${fparse charge_time + cooldown_duration})))' + expression = 'if(t<${charge_time_hat}, ${temperature_initial}, + if(t<${fparse charge_time_hat + cooldown_duration_hat}, ${temperature_cooldown}, + ${temperature_desorption_min}+${desorption_heating_rate_hat}*(t-${fparse charge_time_hat + cooldown_duration_hat})))' [] [source_distribution] type = ParsedFunction - expression = '1 / (${sigma} * sqrt(2 * pi)) * exp(-0.5 * ((x - ${R_p}) / ${sigma}) ^ 2)' + expression = '1 / (${sigma_hat} * sqrt(2 * pi)) * exp(-0.5 * ((x - ${R_p_hat}) / ${sigma_hat}) ^ 2)' [] [surface_flux_func] type = ParsedFunction - expression = 'if(t<${charge_time}, ${flux}, 0)' + expression = 'if(t<${charge_time_hat}, ${surface_flux_hat}, 0)' [] [source_deuterium] type = ParsedFunction @@ -129,36 +129,36 @@ [] [max_dt_size_function] type = ParsedFunction - expression = 'if(t<${fparse 5}, ${fparse 1e-2}, - if(t<${fparse 8}, ${fparse 1e2}, - if(t<${fparse 12}, ${fparse 1e-2}, - if(t<${fparse 20}, ${fparse 1e2}, - if(t<${fparse 35}, ${fparse 1e-2}, - if(t<${fparse 450}, ${fparse 1e2}, - if(t<${fparse 5000}, ${fparse 1e1}, - if(t<${fparse 11000}, ${fparse 1e2}, - if(t<${fparse 13000}, ${fparse 1e1}, - if(t<${fparse charge_time + cooldown_duration + 4500}, ${fparse 1e2}, - if(t<${fparse 313000}, ${fparse 1e2}, - if(t<${fparse 315000}, ${fparse 1e1}, ${fparse 1e3}))))))))))))' + expression = 'if(t<${fparse 5 / time_reference}, ${fparse 1e-2 / time_reference}, + if(t<${fparse 8 / time_reference}, ${fparse 1e2 / time_reference}, + if(t<${fparse 12 / time_reference}, ${fparse 1e-2 / time_reference}, + if(t<${fparse 20 / time_reference}, ${fparse 1e2 / time_reference}, + if(t<${fparse 35 / time_reference}, ${fparse 1e-2 / time_reference}, + if(t<${fparse 450 / time_reference}, ${fparse 1e2 / time_reference}, + if(t<${fparse 5000 / time_reference}, ${fparse 1e1 / time_reference}, + if(t<${fparse 11000 / time_reference}, ${fparse 1e2 / time_reference}, + if(t<${fparse 13000 / time_reference}, ${fparse 1e1 / time_reference}, + if(t<${fparse (charge_time + cooldown_duration + 4500) / time_reference}, ${fparse 1e2 / time_reference}, + if(t<${fparse 313000 / time_reference}, ${fparse 1e2 / time_reference}, + if(t<${fparse 315000 / time_reference}, ${fparse 1e1 / time_reference}, ${fparse 1e3 / time_reference}))))))))))))' [] [max_dt_size_function_inf] type = ParsedFunction - expression = 'if(t<${fparse 5}, ${fparse 1e-2}, - if(t<${fparse 8}, ${fparse 1e2}, - if(t<${fparse 12}, ${fparse 1e-2}, - if(t<${fparse 20}, ${fparse 1e2}, - if(t<${fparse 35}, ${fparse 1e-2}, - if(t<${fparse 450}, ${fparse 1e2}, - if(t<${fparse 5000}, ${fparse 1e1}, - if(t<${fparse 11000}, ${fparse 1e2}, - if(t<${fparse 13000}, ${fparse 1e1}, - if(t<${fparse charge_time + cooldown_duration + 4500}, ${fparse 1e2}, - if(t<${fparse 315000}, ${fparse 1e1}, ${fparse 1e3})))))))))))' + expression = 'if(t<${fparse 5 / time_reference}, ${fparse 1e-2 / time_reference}, + if(t<${fparse 8 / time_reference}, ${fparse 1e2 / time_reference}, + if(t<${fparse 12 / time_reference}, ${fparse 1e-2 / time_reference}, + if(t<${fparse 20 / time_reference}, ${fparse 1e2 / time_reference}, + if(t<${fparse 35 / time_reference}, ${fparse 1e-2 / time_reference}, + if(t<${fparse 450 / time_reference}, ${fparse 1e2 / time_reference}, + if(t<${fparse 5000 / time_reference}, ${fparse 1e1 / time_reference}, + if(t<${fparse 11000 / time_reference}, ${fparse 1e2 / time_reference}, + if(t<${fparse 13000 / time_reference}, ${fparse 1e1 / time_reference}, + if(t<${fparse (charge_time + cooldown_duration + 4500) / time_reference}, ${fparse 1e2 / time_reference}, + if(t<${fparse 315000 / time_reference}, ${fparse 1e1 / time_reference}, ${fparse 1e3 / time_reference})))))))))))' [] [max_dt_size_function_coarse] type = ParsedFunction - expression = 'if(t<${fparse 1e-1}, ${fparse 1e4}, ${fparse 1e5})' + expression = 'if(t<${fparse 1e-1 / time_reference}, ${fparse 1e4 / time_reference}, ${fparse 1e5 / time_reference})' [] [] @@ -169,8 +169,7 @@ property_name = 'diffusivity_W' functor_names = 'temperature_bc_func' functor_symbols = 'temperature' - expression = '${diffusion_W_preexponential} * exp(- ${diffusion_W_energy} / ${kb_eV} / temperature)' - output_properties = 'diffusivity_W' + expression = '${diffusion_W_preexponential_hat} * exp(- ${diffusion_W_energy} / ${kb_eV} / temperature)' [] [diffusivity_nonAD] type = MaterialADConverter @@ -182,8 +181,7 @@ property_name = 'Kr' functor_names = 'temperature_bc_func' functor_symbols = 'temperature' - expression = '${recombination_coefficient} * exp(- ${recombination_energy} / ${kb_eV} / temperature)' - output_properties = 'Kr' + expression = '${recombination_coefficient_hat} * exp(- ${recombination_energy} / ${kb_eV} / temperature)' [] [flux_recombination_surface] type = ADDerivativeParsedMaterial @@ -197,11 +195,14 @@ [Postprocessors] active = 'integral_source_deuterium scaled_implanted_deuterium integral_deuterium_concentration scaled_mobile_deuterium flux_surface_left scaled_flux_surface_left - flux_surface_right scaled_flux_surface_right temperature diffusion_W + flux_surface_right scaled_flux_surface_right temperature diffusion_W_hat diffusion_W max_time_step_size max_time_step_size_coarse integral_trapped_concentration_1 scaled_trapped_deuterium_1 integral_trapped_concentration_2 scaled_trapped_deuterium_2 integral_trapped_concentration_3 scaled_trapped_deuterium_3 integral_trapped_concentration_4 scaled_trapped_deuterium_4 integral_trapped_concentration_5 scaled_trapped_deuterium_5 - integral_trapped_concentration_intrinsic scaled_trapped_deuterium_intrinsic' + integral_trapped_concentration_intrinsic scaled_trapped_deuterium_intrinsic + spatial_max_mobile_d2 spatial_max_trapped_1 spatial_max_trapped_2 spatial_max_trapped_3 spatial_max_trapped_4 spatial_max_trapped_5 spatial_max_trapped_intrinsic + max_mobile_d2 max_trapped_1 max_trapped_2 max_trapped_3 max_trapped_4 max_trapped_5 max_trapped_intrinsic max_scaled_flux_surface_left max_scaled_flux_surface_right + max_scaled_mobile_deuterium max_scaled_trapped_deuterium_intrinsic' [integral_source_deuterium] type = FunctionElementIntegral function = source_deuterium @@ -209,7 +210,7 @@ [] [scaled_implanted_deuterium] type = ScalePostprocessor - scaling_factor = '${fparse ${units 1 m^2 -> mum^2}}' + scaling_factor = '${fparse mobile_concentration_reference * length_reference * ${units 1 m^2 -> mum^2} / time_reference}' value = integral_source_deuterium [] [integral_deuterium_concentration] @@ -219,9 +220,15 @@ [] [scaled_mobile_deuterium] type = ScalePostprocessor - scaling_factor = '${fparse ${units 1 m^2 -> mum^2}}' + scaling_factor = '${fparse mobile_concentration_reference * length_reference * ${units 1 m^2 -> mum^2}}' value = integral_deuterium_concentration [] + [max_scaled_mobile_deuterium] + type = TimeExtremeValue + postprocessor = scaled_mobile_deuterium + value_type = max + outputs = 'console' + [] [flux_surface_left] type = ADSideAverageMaterialProperty boundary = 'left' @@ -230,10 +237,16 @@ [] [scaled_flux_surface_left] type = ScalePostprocessor - scaling_factor = '${fparse -1 * ${units 1 m^2 -> mum^2}}' + scaling_factor = '${fparse -1 * mobile_concentration_reference * length_reference * ${units 1 m^2 -> mum^2} / time_reference}' value = flux_surface_left execute_on = 'initial nonlinear linear timestep_end' [] + [max_scaled_flux_surface_left] + type = TimeExtremeValue + postprocessor = scaled_flux_surface_left + execute_on = 'initial timestep_end' + outputs = 'console' + [] [flux_surface_left_sieverts] type = SideDiffusiveFluxAverage variable = deuterium_concentration_W @@ -243,10 +256,15 @@ [] [scaled_flux_surface_left_sieverts] type = ScalePostprocessor - scaling_factor = '${fparse ${units 1 m^2 -> mum^2}}' + scaling_factor = '${fparse mobile_concentration_reference * length_reference * ${units 1 m^2 -> mum^2} / time_reference}' value = flux_surface_left_sieverts execute_on = 'initial nonlinear linear timestep_end' [] + [max_scaled_flux_surface_left_sieverts] + type = TimeExtremeValue + postprocessor = scaled_flux_surface_left_sieverts + value_type = max + [] [flux_surface_right] type = ADSideAverageMaterialProperty boundary = 'right' @@ -255,10 +273,16 @@ [] [scaled_flux_surface_right] type = ScalePostprocessor - scaling_factor = '${fparse -1 * ${units 1 m^2 -> mum^2}}' + scaling_factor = '${fparse -1 * mobile_concentration_reference * length_reference * ${units 1 m^2 -> mum^2} / time_reference}' value = flux_surface_right execute_on = 'initial nonlinear linear timestep_end' [] + [max_scaled_flux_surface_right] + type = TimeExtremeValue + postprocessor = scaled_flux_surface_right + execute_on = 'initial timestep_end' + outputs = 'console' + [] [flux_surface_right_sieverts] type = SideDiffusiveFluxAverage variable = deuterium_concentration_W @@ -268,18 +292,29 @@ [] [scaled_flux_surface_right_sieverts] type = ScalePostprocessor - scaling_factor = '${fparse -1 * ${units 1 m^2 -> mum^2}}' + scaling_factor = '${fparse -1 * mobile_concentration_reference * length_reference * ${units 1 m^2 -> mum^2} / time_reference}' value = flux_surface_right_sieverts execute_on = 'initial nonlinear linear timestep_end' [] + [max_scaled_flux_surface_right_sieverts] + type = TimeExtremeValue + postprocessor = scaled_flux_surface_right_sieverts + value_type = max + [] [temperature] type = ElementAverageValue variable = temperature execute_on = 'initial timestep_end' [] + [diffusion_W_hat] + type = ElementAverageMaterialProperty + mat_prop = diffusivity_W_nonAD + outputs = none + [] [diffusion_W] - type = ElementAverageValue - variable = diffusivity_W + type = ScalePostprocessor + scaling_factor = '${fparse length_reference ^ 2 / time_reference}' + value = diffusion_W_hat outputs = none [] [max_time_step_size] @@ -294,6 +329,105 @@ execute_on = 'initial nonlinear linear timestep_end' outputs = none [] + + [spatial_max_mobile_d2] + type = NodalExtremeValue + value_type = 'max' + variable = deuterium_concentration_W + execute_on = 'initial timestep_end' + outputs = 'console' + [] + [spatial_max_trapped_1] + type = NodalExtremeValue + value_type = 'max' + variable = trapped_1 + execute_on = 'initial timestep_end' + outputs = 'console' + [] + [spatial_max_trapped_2] + type = NodalExtremeValue + value_type = 'max' + variable = trapped_2 + execute_on = 'initial timestep_end' + outputs = 'console' + [] + [spatial_max_trapped_3] + type = NodalExtremeValue + value_type = 'max' + variable = trapped_3 + execute_on = 'initial timestep_end' + outputs = 'console' + [] + [spatial_max_trapped_4] + type = NodalExtremeValue + value_type = 'max' + variable = trapped_4 + execute_on = 'initial timestep_end' + outputs = 'console' + [] + [spatial_max_trapped_5] + type = NodalExtremeValue + value_type = 'max' + variable = trapped_5 + execute_on = 'initial timestep_end' + outputs = 'console' + [] + [spatial_max_trapped_intrinsic] + type = NodalExtremeValue + value_type = 'max' + variable = trapped_intrinsic + execute_on = 'initial timestep_end' + outputs = 'console' + [] + [max_mobile_d2] + type = TimeExtremeValue + value_type = 'max' + postprocessor = spatial_max_mobile_d2 + execute_on = 'initial timestep_end' + outputs = 'console' + [] + [max_trapped_1] + type = TimeExtremeValue + value_type = 'max' + postprocessor = spatial_max_trapped_1 + execute_on = 'initial timestep_end' + outputs = 'console' + [] + [max_trapped_2] + type = TimeExtremeValue + value_type = 'max' + postprocessor = spatial_max_trapped_2 + execute_on = 'initial timestep_end' + outputs = 'console' + [] + [max_trapped_3] + type = TimeExtremeValue + value_type = 'max' + postprocessor = spatial_max_trapped_3 + execute_on = 'initial timestep_end' + outputs = 'console' + [] + [max_trapped_4] + type = TimeExtremeValue + value_type = 'max' + postprocessor = spatial_max_trapped_4 + execute_on = 'initial timestep_end' + outputs = 'console' + [] + [max_trapped_5] + type = TimeExtremeValue + value_type = 'max' + postprocessor = spatial_max_trapped_5 + execute_on = 'initial timestep_end' + outputs = 'console' + [] + [max_trapped_intrinsic] + type = TimeExtremeValue + value_type = 'max' + postprocessor = spatial_max_trapped_intrinsic + execute_on = 'initial timestep_end' + outputs = 'console' + [] [] [Preconditioning] @@ -307,28 +441,26 @@ type = Transient scheme = bdf2 solve_type = 'Newton' - petsc_options_iname = '-pc_type -sub_pc_type -snes_type' - petsc_options_value = 'asm lu vinewtonrsls' # This petsc option helps prevent negative concentrations with bounds' - end_time = ${endtime} - automatic_scaling = true - compute_scaling_once = false + petsc_options_iname = '-pc_type -pc_factor_mat_solver_type -snes_type' + petsc_options_value = 'lu mumps vinewtonrsls' + end_time = ${endtime_hat} line_search = 'none' - nl_rel_tol = 5e-7 - nl_abs_tol = 1e-10 + nl_rel_tol = 1e-8 + nl_abs_tol = 4e-5 nl_max_its = 34 [TimeStepper] type = IterationAdaptiveDT - dt = ${dt_init} - optimal_iterations = 25 + dt = '${fparse dt_init / time_reference}' growth_factor = 1.1 - cutback_factor = 0.9 - cutback_factor_at_failure = 0.9 timestep_limiting_postprocessor = max_time_step_size [] + [Predictor] + type = SimplePredictor + scale = 1.0 + [] [] [Debug] - show_var_residual = 'deuterium_concentration_W' show_var_residual_norms = true [] diff --git a/test/tests/val-2f/val-2f_trapping_1.i b/test/tests/val-2f/val-2f_trapping_1.i index cf8e4174f..cc478da40 100644 --- a/test/tests/val-2f/val-2f_trapping_1.i +++ b/test/tests/val-2f/val-2f_trapping_1.i @@ -1,75 +1,45 @@ # This input file adds the trapping sites 1 for validation case val-2f. # It is included in val-2f.i -[Variables] - [trapped_1] - order = FIRST - family = LAGRANGE - [] -[] - [Bounds] [trapped_1_lower_bound] type = ConstantBounds variable = bounds_dummy bounded_variable = trapped_1 bound_type = lower - bound_value = '${fparse -1e-20}' - [] -[] - -[Kernels] - # trapping 1 kernel - [coupled_time_trap_1] - type = ADCoefCoupledTimeDerivative - variable = deuterium_concentration_W - v = trapped_1 - coef = ${trap_per_free_1} - [] -[] - -[NodalKernels] - # First traps - [time_1] - type = TimeDerivativeNodalKernel - variable = trapped_1 - [] - [trapping_1] - type = TrappingNodalKernel - variable = trapped_1 - mobile_concentration = deuterium_concentration_W - alpha_t = '${trapping_prefactor_1}' - trapping_energy = '${trapping_energy_1}' - N = '${tungsten_density}' - Ct0 = 'trap_distribution_function_1' - temperature = 'temperature' - trap_per_free = ${trap_per_free_1} - [] - [release_1] - type = ReleasingNodalKernel - variable = trapped_1 - alpha_r = '${detrapping_prefactor_1}' - detrapping_energy = '${detrapping_energy_1}' - temperature = 'temperature' + bound_value = 0 [] [] [Functions] [trap_distribution_function_1] type = ParsedFunction - expression = '${trapping_site_fraction_1} / (1 + exp((x - ${depth_center}) / ${depth_width}))' + expression = '${trapping_site_fraction_1} / (1 + exp((x - ${depth_center_hat}) / ${depth_width_hat}))' [] [trap_distribution_function_1_inf] type = ParsedFunction - expression = '${trapping_site_fraction_1_inf} / (1 + exp((x - ${depth_center}) / ${depth_width}))' + expression = '${trapping_site_fraction_1_inf} / (1 + exp((x - ${depth_center_hat}) / ${depth_width_hat}))' [] [] -[Materials] - [trap_distribution_function_1] - type = GenericFunctionMaterial - prop_names = trap_distribution_function_1 - prop_values = trap_distribution_function_1 +[Physics] + [SpeciesTrapping] + [trapping_1] + species = 'trapped_1' + species_scaling_factors = '1' + species_initial_concentrations = '0' + mobile = 'deuterium_concentration_W' + dimensionless_trapping_rate_coefficient = '${dimensionless_trapping_rate_coefficient_1}' + trapping_energy = '${trapping_energy_1}' + N = ${tungsten_density} + Ct0 = 'trap_distribution_function_1' + trap_concentration_reference = '${trap_concentration_reference_1}' + mobile_concentration_reference = ${mobile_concentration_reference} + dimensionless_release_rate_coefficient = '${dimensionless_release_rate_coefficient_1}' + detrapping_energy = '${detrapping_energy_1}' + temperature = 'temperature' + dimensionless_species = true + [] [] [] @@ -81,7 +51,7 @@ [] [scaled_trapped_deuterium_1] type = ScalePostprocessor - scaling_factor = '${fparse ${trap_per_free_1} * ${units 1 m^2 -> mum^2}}' + scaling_factor = '${fparse trap_concentration_reference_1 * length_reference * ${units 1 m^2 -> mum^2}}' value = integral_trapped_concentration_1 [] [] diff --git a/test/tests/val-2f/val-2f_trapping_2.i b/test/tests/val-2f/val-2f_trapping_2.i index cfdbb4c2e..77560a9af 100644 --- a/test/tests/val-2f/val-2f_trapping_2.i +++ b/test/tests/val-2f/val-2f_trapping_2.i @@ -1,75 +1,45 @@ # This input file adds the trapping sites 2 for validation case val-2f. # It is included in val-2f.i -[Variables] - [trapped_2] - order = FIRST - family = LAGRANGE - [] -[] - [Bounds] [trapped_2_lower_bound] type = ConstantBounds variable = bounds_dummy bounded_variable = trapped_2 bound_type = lower - bound_value = '${fparse -1e-20}' - [] -[] - -[Kernels] - # trapping 2 kernel - [coupled_time_trap_2] - type = ADCoefCoupledTimeDerivative - variable = deuterium_concentration_W - v = trapped_2 - coef = ${trap_per_free_2} - [] -[] - -[NodalKernels] - # Second traps - [time_2] - type = TimeDerivativeNodalKernel - variable = trapped_2 - [] - [trapping_2] - type = TrappingNodalKernel - variable = trapped_2 - mobile_concentration = deuterium_concentration_W - alpha_t = '${trapping_prefactor_2}' - trapping_energy = '${trapping_energy_2}' - N = '${tungsten_density}' - Ct0 = 'trap_distribution_function_2' - temperature = 'temperature' - trap_per_free = ${trap_per_free_2} - [] - [release_2] - type = ReleasingNodalKernel - variable = trapped_2 - alpha_r = '${detrapping_prefactor_2}' - detrapping_energy = '${detrapping_energy_2}' - temperature = 'temperature' + bound_value = 0 [] [] [Functions] [trap_distribution_function_2] type = ParsedFunction - expression = '${trapping_site_fraction_2} / (1 + exp((x - ${depth_center}) / ${depth_width}))' + expression = '${trapping_site_fraction_2} / (1 + exp((x - ${depth_center_hat}) / ${depth_width_hat}))' [] [trap_distribution_function_2_inf] type = ParsedFunction - expression = '${trapping_site_fraction_2_inf} / (1 + exp((x - ${depth_center}) / ${depth_width}))' + expression = '${trapping_site_fraction_2_inf} / (1 + exp((x - ${depth_center_hat}) / ${depth_width_hat}))' [] [] -[Materials] - [trap_distribution_function_2] - type = GenericFunctionMaterial - prop_names = trap_distribution_function_2 - prop_values = trap_distribution_function_2 +[Physics] + [SpeciesTrapping] + [trapping_2] + species = 'trapped_2' + species_scaling_factors = '1' + species_initial_concentrations = '0' + mobile = 'deuterium_concentration_W' + dimensionless_trapping_rate_coefficient = '${dimensionless_trapping_rate_coefficient_2}' + trapping_energy = '${trapping_energy_2}' + N = ${tungsten_density} + Ct0 = 'trap_distribution_function_2' + trap_concentration_reference = '${trap_concentration_reference_2}' + mobile_concentration_reference = ${mobile_concentration_reference} + dimensionless_release_rate_coefficient = '${dimensionless_release_rate_coefficient_2}' + detrapping_energy = '${detrapping_energy_2}' + temperature = 'temperature' + dimensionless_species = true + [] [] [] @@ -81,7 +51,7 @@ [] [scaled_trapped_deuterium_2] type = ScalePostprocessor - scaling_factor = '${fparse ${trap_per_free_2} * ${units 1 m^2 -> mum^2}}' + scaling_factor = '${fparse trap_concentration_reference_2 * length_reference * ${units 1 m^2 -> mum^2}}' value = integral_trapped_concentration_2 [] [] diff --git a/test/tests/val-2f/val-2f_trapping_3.i b/test/tests/val-2f/val-2f_trapping_3.i index bf9153eaf..61efc8b39 100644 --- a/test/tests/val-2f/val-2f_trapping_3.i +++ b/test/tests/val-2f/val-2f_trapping_3.i @@ -1,74 +1,45 @@ # This input file adds the trapping sites 3 for validation case val-2f. # It is included in val-2f.i -[Variables] - [trapped_3] - order = FIRST - family = LAGRANGE - [] -[] - [Bounds] [trapped_3_lower_bound] type = ConstantBounds variable = bounds_dummy bounded_variable = trapped_3 bound_type = lower - bound_value = '${fparse -1e-20}' - [] -[] - -[Kernels] - # trapping 3 kernel - [coupled_time_trap_3] - type = ADCoefCoupledTimeDerivative - variable = deuterium_concentration_W - v = trapped_3 - coef = ${trap_per_free_3} - [] -[] - -[NodalKernels] - [time_3] - type = TimeDerivativeNodalKernel - variable = trapped_3 - [] - [trapping_3] - type = TrappingNodalKernel - variable = trapped_3 - mobile_concentration = deuterium_concentration_W - alpha_t = '${trapping_prefactor_3}' - trapping_energy = '${trapping_energy_3}' - N = '${tungsten_density}' - Ct0 = 'trap_distribution_function_3' - temperature = 'temperature' - trap_per_free = ${trap_per_free_3} - [] - [release_3] - type = ReleasingNodalKernel - variable = trapped_3 - alpha_r = '${detrapping_prefactor_3}' - detrapping_energy = '${detrapping_energy_3}' - temperature = 'temperature' + bound_value = 0 [] [] [Functions] [trap_distribution_function_3] type = ParsedFunction - expression = '${trapping_site_fraction_3} / (1 + exp((x - ${depth_center}) / ${depth_width}))' + expression = '${trapping_site_fraction_3} / (1 + exp((x - ${depth_center_hat}) / ${depth_width_hat}))' [] [trap_distribution_function_3_inf] type = ParsedFunction - expression = '${trapping_site_fraction_3_inf} / (1 + exp((x - ${depth_center}) / ${depth_width}))' + expression = '${trapping_site_fraction_3_inf} / (1 + exp((x - ${depth_center_hat}) / ${depth_width_hat}))' [] [] -[Materials] - [trap_distribution_function_3] - type = GenericFunctionMaterial - prop_names = trap_distribution_function_3 - prop_values = trap_distribution_function_3 +[Physics] + [SpeciesTrapping] + [trapping_3] + species = 'trapped_3' + species_scaling_factors = '1' + species_initial_concentrations = '0' + mobile = 'deuterium_concentration_W' + dimensionless_trapping_rate_coefficient = '${dimensionless_trapping_rate_coefficient_3}' + trapping_energy = '${trapping_energy_3}' + N = ${tungsten_density} + Ct0 = 'trap_distribution_function_3' + trap_concentration_reference = '${trap_concentration_reference_3}' + mobile_concentration_reference = ${mobile_concentration_reference} + dimensionless_release_rate_coefficient = '${dimensionless_release_rate_coefficient_3}' + detrapping_energy = '${detrapping_energy_3}' + temperature = 'temperature' + dimensionless_species = true + [] [] [] @@ -80,7 +51,7 @@ [] [scaled_trapped_deuterium_3] type = ScalePostprocessor - scaling_factor = '${fparse ${trap_per_free_3} * ${units 1 m^2 -> mum^2}}' + scaling_factor = '${fparse trap_concentration_reference_3 * length_reference * ${units 1 m^2 -> mum^2}}' value = integral_trapped_concentration_3 [] [] diff --git a/test/tests/val-2f/val-2f_trapping_4.i b/test/tests/val-2f/val-2f_trapping_4.i index ef976d72b..6e5c1dc0a 100644 --- a/test/tests/val-2f/val-2f_trapping_4.i +++ b/test/tests/val-2f/val-2f_trapping_4.i @@ -1,64 +1,45 @@ # This input file adds the trapping sites 4 for validation case val-2f. # It is included in val-2f.i -[Variables] - [trapped_4] - order = FIRST - family = LAGRANGE - [] -[] - -[Kernels] - # trapping 4 kernel - [coupled_time_trap_4] - type = ADCoefCoupledTimeDerivative - variable = deuterium_concentration_W - v = trapped_4 - coef = ${trap_per_free_4} - [] -[] - -[NodalKernels] - [time_4] - type = TimeDerivativeNodalKernel - variable = trapped_4 - [] - [trapping_4] - type = TrappingNodalKernel - variable = trapped_4 - mobile_concentration = deuterium_concentration_W - alpha_t = '${trapping_prefactor_4}' - trapping_energy = '${trapping_energy_4}' - N = '${tungsten_density}' - Ct0 = 'trap_distribution_function_4' - temperature = 'temperature' - trap_per_free = ${trap_per_free_4} - [] - [release_4] - type = ReleasingNodalKernel - variable = trapped_4 - alpha_r = '${detrapping_prefactor_4}' - detrapping_energy = '${detrapping_energy_4}' - temperature = 'temperature' +[Bounds] + [trapped_4_lower_bound] + type = ConstantBounds + variable = bounds_dummy + bounded_variable = trapped_4 + bound_type = lower + bound_value = 0 [] [] [Functions] [trap_distribution_function_4] type = ParsedFunction - expression = '${trapping_site_fraction_4} / (1 + exp((x - ${depth_center}) / ${depth_width}))' + expression = '${trapping_site_fraction_4} / (1 + exp((x - ${depth_center_hat}) / ${depth_width_hat}))' [] [trap_distribution_function_4_inf] type = ParsedFunction - expression = '${trapping_site_fraction_4_inf} / (1 + exp((x - ${depth_center}) / ${depth_width}))' + expression = '${trapping_site_fraction_4_inf} / (1 + exp((x - ${depth_center_hat}) / ${depth_width_hat}))' [] [] -[Materials] - [trap_distribution_function_4] - type = GenericFunctionMaterial - prop_names = trap_distribution_function_4 - prop_values = trap_distribution_function_4 +[Physics] + [SpeciesTrapping] + [trapping_4] + species = 'trapped_4' + species_scaling_factors = '1' + species_initial_concentrations = '0' + mobile = 'deuterium_concentration_W' + dimensionless_trapping_rate_coefficient = '${dimensionless_trapping_rate_coefficient_4}' + trapping_energy = '${trapping_energy_4}' + N = ${tungsten_density} + Ct0 = 'trap_distribution_function_4' + trap_concentration_reference = '${trap_concentration_reference_4}' + mobile_concentration_reference = ${mobile_concentration_reference} + dimensionless_release_rate_coefficient = '${dimensionless_release_rate_coefficient_4}' + detrapping_energy = '${detrapping_energy_4}' + temperature = 'temperature' + dimensionless_species = true + [] [] [] @@ -70,7 +51,7 @@ [] [scaled_trapped_deuterium_4] type = ScalePostprocessor - scaling_factor = '${fparse ${trap_per_free_4} * ${units 1 m^2 -> mum^2}}' + scaling_factor = '${fparse trap_concentration_reference_4 * length_reference * ${units 1 m^2 -> mum^2}}' value = integral_trapped_concentration_4 [] [] diff --git a/test/tests/val-2f/val-2f_trapping_5.i b/test/tests/val-2f/val-2f_trapping_5.i index 1ec2ed0c3..caec287bb 100644 --- a/test/tests/val-2f/val-2f_trapping_5.i +++ b/test/tests/val-2f/val-2f_trapping_5.i @@ -1,64 +1,45 @@ # This input file adds the trapping sites 5 for validation case val-2f. # It is included in val-2f.i -[Variables] - [trapped_5] - order = FIRST - family = LAGRANGE - [] -[] - -[Kernels] - # trapping 5 kernel - [coupled_time_trap_5] - type = ADCoefCoupledTimeDerivative - variable = deuterium_concentration_W - v = trapped_5 - coef = ${trap_per_free_5} - [] -[] - -[NodalKernels] - [time_5] - type = TimeDerivativeNodalKernel - variable = trapped_5 - [] - [trapping_5] - type = TrappingNodalKernel - variable = trapped_5 - mobile_concentration = deuterium_concentration_W - alpha_t = '${trapping_prefactor_5}' - trapping_energy = '${trapping_energy_5}' - N = '${tungsten_density}' - Ct0 = 'trap_distribution_function_5' - temperature = 'temperature' - trap_per_free = ${trap_per_free_5} - [] - [release_5] - type = ReleasingNodalKernel - variable = trapped_5 - alpha_r = '${detrapping_prefactor_5}' - detrapping_energy = '${detrapping_energy_5}' - temperature = 'temperature' +[Bounds] + [trapped_5_lower_bound] + type = ConstantBounds + variable = bounds_dummy + bounded_variable = trapped_5 + bound_type = lower + bound_value = 0 [] [] [Functions] [trap_distribution_function_5] type = ParsedFunction - expression = '${trapping_site_fraction_5} / (1 + exp((x - ${depth_center}) / ${depth_width}))' + expression = '${trapping_site_fraction_5} / (1 + exp((x - ${depth_center_hat}) / ${depth_width_hat}))' [] [trap_distribution_function_5_inf] type = ParsedFunction - expression = '${trapping_site_fraction_5_inf} / (1 + exp((x - ${depth_center}) / ${depth_width}))' + expression = '${trapping_site_fraction_5_inf} / (1 + exp((x - ${depth_center_hat}) / ${depth_width_hat}))' [] [] -[Materials] - [trap_distribution_function_5] - type = GenericFunctionMaterial - prop_names = trap_distribution_function_5 - prop_values = trap_distribution_function_5 +[Physics] + [SpeciesTrapping] + [trapping_5] + species = 'trapped_5' + species_scaling_factors = '1' + species_initial_concentrations = '0' + mobile = 'deuterium_concentration_W' + dimensionless_trapping_rate_coefficient = '${dimensionless_trapping_rate_coefficient_5}' + trapping_energy = '${trapping_energy_5}' + N = ${tungsten_density} + Ct0 = 'trap_distribution_function_5' + trap_concentration_reference = '${trap_concentration_reference_5}' + mobile_concentration_reference = ${mobile_concentration_reference} + dimensionless_release_rate_coefficient = '${dimensionless_release_rate_coefficient_5}' + detrapping_energy = '${detrapping_energy_5}' + temperature = 'temperature' + dimensionless_species = true + [] [] [] @@ -70,7 +51,7 @@ [] [scaled_trapped_deuterium_5] type = ScalePostprocessor - scaling_factor = '${fparse ${trap_per_free_5} * ${units 1 m^2 -> mum^2}}' + scaling_factor = '${fparse trap_concentration_reference_5 * length_reference * ${units 1 m^2 -> mum^2}}' value = integral_trapped_concentration_5 [] [] diff --git a/test/tests/val-2f/val-2f_trapping_intrinsic.i b/test/tests/val-2f/val-2f_trapping_intrinsic.i index e536aa678..831dd5fff 100644 --- a/test/tests/val-2f/val-2f_trapping_intrinsic.i +++ b/test/tests/val-2f/val-2f_trapping_intrinsic.i @@ -1,55 +1,34 @@ # This input file adds the intrinsic trapping sites for validation case val-2f. # It is included in val-2f.i -[Variables] - [trapped_intrinsic] - order = FIRST - family = LAGRANGE - [] -[] - [Bounds] [trapped_intrinsic_lower_bound] type = ConstantBounds variable = bounds_dummy bounded_variable = trapped_intrinsic bound_type = lower - bound_value = '${fparse -1e-20}' - [] -[] - -[Kernels] - # trapping intrinsic kernel - [coupled_time_trap_intrinsic] - type = ADCoefCoupledTimeDerivative - variable = deuterium_concentration_W - v = trapped_intrinsic - coef = ${trap_per_free_intrinsic} + bound_value = 0 [] [] -[NodalKernels] - [time_intrinsic] - type = TimeDerivativeNodalKernel - variable = trapped_intrinsic - [] - [trapping_intrinsic] - type = TrappingNodalKernel - variable = trapped_intrinsic - mobile_concentration = deuterium_concentration_W - alpha_t = '${trapping_prefactor_intrinsic}' - trapping_energy = '${trapping_energy_intrinsic}' - N = '${tungsten_density}' - Ct0 = '${trapping_site_fraction_intrinsic}' - temperature = 'temperature' - trap_per_free = ${trap_per_free_intrinsic} - [] - [release_intrinsic] - type = ReleasingNodalKernel - variable = trapped_intrinsic - alpha_r = '${detrapping_prefactor_intrinsic}' - detrapping_energy = '${detrapping_energy_intrinsic}' - temperature = 'temperature' +[Physics] + [SpeciesTrapping] + [trapping_intrinsic] + species = 'trapped_intrinsic' + species_scaling_factors = '1' + species_initial_concentrations = '0' + mobile = 'deuterium_concentration_W' + dimensionless_trapping_rate_coefficient = '${dimensionless_trapping_rate_coefficient_intrinsic}' + trapping_energy = '${trapping_energy_intrinsic}' + N = ${tungsten_density} + Ct0 = '${trapping_site_fraction_intrinsic}' + trap_concentration_reference = '${trap_concentration_reference_intrinsic}' + mobile_concentration_reference = ${mobile_concentration_reference} + dimensionless_release_rate_coefficient = '${dimensionless_release_rate_coefficient_intrinsic}' + detrapping_energy = '${detrapping_energy_intrinsic}' + temperature = 'temperature' + dimensionless_species = true + [] [] [] @@ -61,7 +40,13 @@ [] [scaled_trapped_deuterium_intrinsic] type = ScalePostprocessor - scaling_factor = '${fparse ${trap_per_free_intrinsic} * ${units 1 m^2 -> mum^2}}' + scaling_factor = '${fparse trap_concentration_reference_intrinsic * length_reference * ${units 1 m^2 -> mum^2}}' value = integral_trapped_concentration_intrinsic [] + [max_scaled_trapped_deuterium_intrinsic] + type = TimeExtremeValue + postprocessor = scaled_trapped_deuterium_intrinsic + value_type = max + outputs = 'console' + [] [] diff --git a/test/tests/yttrium_hydrogen_system/YHx_PCT.i b/test/tests/yttrium_hydrogen_system/YHx_PCT.i index 2f727b7ce..e3c4f1312 100644 --- a/test/tests/yttrium_hydrogen_system/YHx_PCT.i +++ b/test/tests/yttrium_hydrogen_system/YHx_PCT.i @@ -312,9 +312,11 @@ output_file_base = 'YHx_PCT_out' nl_abs_tol = 4e-12 scheme = 'bdf2' solve_type = 'Newton' - petsc_options_iname = '-pc_type -sub_pc_type -snes_type' - petsc_options_value = 'asm lu vinewtonrsls' # This petsc option helps prevent negative concentrations with bounds' + petsc_options_iname = '-pc_type -pc_factor_mat_solver_type -snes_type' + petsc_options_value = 'lu mumps vinewtonrsls' # This petsc option helps prevent negative concentrations with bounds' line_search = 'none' + automatic_scaling = true + compute_scaling_once = true [TimeStepper] type = IterationAdaptiveDT dt = ${dt_init} diff --git a/test/tests/yttrium_hydrogen_system/comparison_YHx_PCT.py b/test/tests/yttrium_hydrogen_system/comparison_YHx_PCT.py index f5b2d2769..a720c8da4 100644 --- a/test/tests/yttrium_hydrogen_system/comparison_YHx_PCT.py +++ b/test/tests/yttrium_hydrogen_system/comparison_YHx_PCT.py @@ -1,12 +1,16 @@ -# Import Required Libraries -# Import the necessary libraries, including pandas. - import matplotlib.pyplot as plt import numpy as np import pandas as pd from mpl_toolkits.mplot3d import Axes3D import os +from yhx_pct_metrics import ( + atom_ratio_eq_upper_func, + compute_prediction_rmspe, + load_prediction_points, + p0_lim_func, +) + # Changes working directory to script directory (for consistent MooseDocs usage) script_folder = os.path.dirname(__file__) os.chdir(script_folder) @@ -114,15 +118,6 @@ def calculate_derivative(expData, x_col, y_col): ] -# Define fitting function -def p0_lim_func(temperature): - return np.exp( - -26.1 - + 3.88 * 10 ** (-2) * np.array(temperature) - - 9.7 * 10 ** (-6) * np.square(temperature) - ) - - p0_lim = p0_lim_func(temperature_list) # Plot the fit along with the data from the plateau pressure as a function of temperature @@ -156,19 +151,6 @@ def p0_lim_func(temperature): # ============================================================================ # -# Fit the high pressures as a function of temperature -def atom_ratio_eq_upper_func(temperature, pressure): - return 2 - ( - 1 - + np.exp( - 21.6 - - 0.0225 * temperature - + (-0.0445 + 7.18 * 10 ** (-4) * temperature) - * (np.log(pressure - p0_lim_func(temperature))) - ) - ) ** (-1) - - # Create a meshgrid for the fit surface pressure_range = np.linspace( (min(list_expData[0].iloc[:, 1])), (max(list_expData[0].iloc[:, 1])), 100 @@ -186,62 +168,8 @@ def atom_ratio_eq_upper_func(temperature, pressure): else: # if in test folder csv_folder = "./gold/" -TMAP8_prediction_T1273_P3e3 = pd.read_csv(csv_folder + "YHx_PCT_T1273_P3e3_out.csv") -TMAP8_prediction_T1173_P1e3 = pd.read_csv(csv_folder + "YHx_PCT_T1173_P1e3_out.csv") -TMAP8_prediction_T1173_P1e4 = pd.read_csv(csv_folder + "YHx_PCT_T1173_P1e4_out.csv") -TMAP8_prediction_T1173_P5e4 = pd.read_csv(csv_folder + "YHx_PCT_T1173_P5e4_out.csv") - -TMAP8_prediction_T1273_P3e3_temperature = TMAP8_prediction_T1273_P3e3[ - "temperature" -].iat[-1] -TMAP8_prediction_T1273_P3e3_pressure = TMAP8_prediction_T1273_P3e3[ - "pressure_H2_enclosure_1_at_interface" -].iat[-1] -TMAP8_prediction_T1273_P3e3_atomic_fraction = TMAP8_prediction_T1273_P3e3[ - "atomic_fraction_H_enclosure_2_at_interface" -].iat[-1] -analytical_equation_T1273_P3e3_atomic_fraction = atom_ratio_eq_upper_func( - TMAP8_prediction_T1273_P3e3_temperature, TMAP8_prediction_T1273_P3e3_pressure -) - -TMAP8_prediction_T1173_P1e3_temperature = TMAP8_prediction_T1173_P1e3[ - "temperature" -].iat[-1] -TMAP8_prediction_T1173_P1e3_pressure = TMAP8_prediction_T1173_P1e3[ - "pressure_H2_enclosure_1_at_interface" -].iat[-1] -TMAP8_prediction_T1173_P1e3_atomic_fraction = TMAP8_prediction_T1173_P1e3[ - "atomic_fraction_H_enclosure_2_at_interface" -].iat[-1] -analytical_equation_T1173_P1e3_atomic_fraction = atom_ratio_eq_upper_func( - TMAP8_prediction_T1173_P1e3_temperature, TMAP8_prediction_T1173_P1e3_pressure -) - -TMAP8_prediction_T1173_P1e4_temperature = TMAP8_prediction_T1173_P1e4[ - "temperature" -].iat[-1] -TMAP8_prediction_T1173_P1e4_pressure = TMAP8_prediction_T1173_P1e4[ - "pressure_H2_enclosure_1_at_interface" -].iat[-1] -TMAP8_prediction_T1173_P1e4_atomic_fraction = TMAP8_prediction_T1173_P1e4[ - "atomic_fraction_H_enclosure_2_at_interface" -].iat[-1] -analytical_equation_T1173_P1e4_atomic_fraction = atom_ratio_eq_upper_func( - TMAP8_prediction_T1173_P1e4_temperature, TMAP8_prediction_T1173_P1e4_pressure -) - -TMAP8_prediction_T1173_P5e4_temperature = TMAP8_prediction_T1173_P5e4[ - "temperature" -].iat[-1] -TMAP8_prediction_T1173_P5e4_pressure = TMAP8_prediction_T1173_P5e4[ - "pressure_H2_enclosure_1_at_interface" -].iat[-1] -TMAP8_prediction_T1173_P5e4_atomic_fraction = TMAP8_prediction_T1173_P5e4[ - "atomic_fraction_H_enclosure_2_at_interface" -].iat[-1] -analytical_equation_T1173_P5e4_atomic_fraction = atom_ratio_eq_upper_func( - TMAP8_prediction_T1173_P5e4_temperature, TMAP8_prediction_T1173_P5e4_pressure -) +prediction_points = load_prediction_points(csv_folder) +prediction_rmspe = compute_prediction_rmspe(csv_folder) # ============================================================================ # @@ -334,74 +262,31 @@ def atom_ratio_eq_upper_func(temperature, pressure): ) # plot the TMAP8 predictions -error = ( - abs( - TMAP8_prediction_T1273_P3e3_atomic_fraction - - analytical_equation_T1273_P3e3_atomic_fraction - ) - / analytical_equation_T1273_P3e3_atomic_fraction - * 100 -) -plt.scatter( - TMAP8_prediction_T1273_P3e3_pressure, - TMAP8_prediction_T1273_P3e3_atomic_fraction, - label=f"{TMAP8_prediction_T1273_P3e3_temperature} K and {TMAP8_prediction_T1273_P3e3_pressure:.2f} Pa prediction (error: {error:.2f} %)", - marker="x", - color="k", - s=90, -) -error = ( - abs( - TMAP8_prediction_T1173_P1e3_atomic_fraction - - analytical_equation_T1173_P1e3_atomic_fraction - ) - / analytical_equation_T1173_P1e3_atomic_fraction - * 100 -) -plt.scatter( - TMAP8_prediction_T1173_P1e3_pressure, - TMAP8_prediction_T1173_P1e3_atomic_fraction, - label=f"{TMAP8_prediction_T1173_P1e3_temperature} K and {TMAP8_prediction_T1173_P1e3_pressure:.2f} Pa prediction (error: {error:.2f} %)", - marker="x", - color="k", - s=90, -) -error = ( - abs( - TMAP8_prediction_T1173_P1e4_atomic_fraction - - analytical_equation_T1173_P1e4_atomic_fraction - ) - / analytical_equation_T1173_P1e4_atomic_fraction - * 100 -) -plt.scatter( - TMAP8_prediction_T1173_P1e4_pressure, - TMAP8_prediction_T1173_P1e4_atomic_fraction, - label=f"{TMAP8_prediction_T1173_P1e4_temperature} K and {TMAP8_prediction_T1173_P1e4_pressure:.2f} Pa prediction (error: {error:.2f} %)", - marker="x", - color="k", - s=90, -) -error = ( - abs( - TMAP8_prediction_T1173_P5e4_atomic_fraction - - analytical_equation_T1173_P5e4_atomic_fraction +for point in prediction_points: + error = abs(point["prediction"] - point["reference"]) / point["reference"] * 100 + plt.scatter( + point["pressure"], + point["prediction"], + label=( + f'{point["temperature"]} K and {point["pressure"]:.2f} Pa prediction ' + f"(error: {error:.2f} %)" + ), + marker="x", + color="k", + s=90, ) - / analytical_equation_T1173_P5e4_atomic_fraction - * 100 -) -plt.scatter( - TMAP8_prediction_T1173_P5e4_pressure, - TMAP8_prediction_T1173_P5e4_atomic_fraction, - label=f"{TMAP8_prediction_T1173_P5e4_temperature} K and {TMAP8_prediction_T1173_P5e4_pressure:.2f} Pa prediction (error: {error:.2f} %)", - marker="x", - color="k", - s=90, -) plt.xlabel("Partial Pressure (Pa)") plt.ylabel("Atom Ratio (-)") plt.xscale("log") +plt.text( + 0.02, + 0.98, + f"TMAP8 prediction RMSPE = {prediction_rmspe:.3f} %", + transform=plt.gca().transAxes, + va="top", + bbox={"facecolor": "white", "alpha": 0.8, "edgecolor": "none"}, +) plt.legend(bbox_to_anchor=(1.1, 1.05)) plt.grid(True) plt.tight_layout() @@ -414,3 +299,4 @@ def atom_ratio_eq_upper_func(temperature, pressure): # print the average RMSE value average_rmse = np.mean(list(RMSE_values.values())) print(f"Average RMSE: {average_rmse:.2f}") +print(f"TMAP8 prediction RMSPE: {prediction_rmspe:.6f} %") diff --git a/test/tests/yttrium_hydrogen_system/gold/YHx_PCT_T1173_P1e3_out.csv b/test/tests/yttrium_hydrogen_system/gold/YHx_PCT_T1173_P1e3_out.csv index 83dac958f..1743d926a 100644 --- a/test/tests/yttrium_hydrogen_system/gold/YHx_PCT_T1173_P1e3_out.csv +++ b/test/tests/yttrium_hydrogen_system/gold/YHx_PCT_T1173_P1e3_out.csv @@ -1,152 +1,152 @@ time,atomic_fraction_H_enclosure_2_at_interface,concentration_H_encl_1_inventory,concentration_H_encl_2_inventory,concentration_H_enclosure_1_at_interface,concentration_H_enclosure_2_at_interface,concentration_ratio_H2,mass_conservation_sum_encl1_encl2,pressure_H2_enclosure_1,pressure_H2_enclosure_1_at_interface,temperature 0,1.55,0.10252086693324,37668.875,0.20504173386647,75337.75,0.00074702638750261,37668.977520867,1000,1000,1173.15 10,1.550000769607,0.10124047154326,37668.876349729,0.19614240347298,75337.787406748,0.00071460337348663,37668.977590201,987.51088019171,956.5974681072,1173.15 -22,1.5500012836652,0.10075527095138,37668.877251281,0.1961426777997,75337.812392547,0.0007146042544387,37668.978006552,982.77817936315,956.59880601398,1173.15 -36.4,1.5500017188832,0.10042645882878,37668.878014564,0.19614291546239,75337.833546317,0.00071460501998691,37668.978441023,979.5709091514,956.59996510817,1173.15 -53.68,1.5500021080353,0.10023859074612,37668.87869706,0.19614312712388,75337.852461058,0.00071460570142411,37668.978935651,977.73842286565,956.60099739311,1173.15 -74.416,1.5500024908921,0.10015994168662,37668.879368518,0.19614333555925,75337.871069811,0.00071460637255866,37668.979528459,976.97127114472,956.60201394407,1173.15 -99.2992,1.5500029073402,0.10015206573896,37668.88009889,0.19614356240842,75337.891311272,0.00071460710303637,37668.980250956,976.89444827057,956.60312030013,1173.15 -129.15904,1.5500033935981,0.10017762584919,37668.880951698,0.19614382734018,75337.914945834,0.00071460795616725,37668.981129324,977.14376444388,956.60441238714,1173.15 -164.990848,1.5500039809911,0.10020996762044,37668.881981882,0.19614414738361,75337.943496073,0.00071460898677186,37668.98219185,977.45922969711,956.60597325684,1173.15 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4151508.0823645,1.978117572057,5.0337724774749,45258.094599134,9.8830148795725,96146.404589831,0.03187299870141,45263.128371612,49099.979624178,48200.016129441,1173.15 4981809.6989703,1.978134697754,5.0362305322548,45272.098887259,9.8928463732221,96147.236984335,0.031904567434948,45277.135117791,49123.955765361,48247.964873651,1173.15 @@ -143,7 +143,7 @@ time,atomic_fraction_H_enclosure_2_at_interface,concentration_H_encl_1_inventory 113301978.83459,1.9785434187654,5.0962098502551,46118.859145353,10.132753167273,96167.102869094,0.032674894730178,46123.955355204,49709.000740053,49418.003721487,1173.15 123301978.83459,1.9785510597041,5.0973557179331,46167.785494615,10.137336587158,96167.474256916,0.032689611674382,46172.882850333,49720.177661516,49440.357316523,1173.15 133301978.83459,1.9785578762755,5.0983787375272,46214.821628814,10.141428624237,96167.805576368,0.032702750828096,46219.920007552,49730.156309031,49460.314410147,1173.15 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c501a8c41..23c58d312 100644 --- a/test/tests/yttrium_hydrogen_system/gold/YHx_PCT_T1273_P3e3_out.csv +++ b/test/tests/yttrium_hydrogen_system/gold/YHx_PCT_T1273_P3e3_out.csv @@ -3,97 +3,97 @@ time,atomic_fraction_H_enclosure_2_at_interface,concentration_H_encl_1_inventory 0.001,1.4099956470957,0.2905546066788,34266.517365926,0.77819161500342,68532.838427087,0.0029726048859534,34266.807920532,3075.6826650788,4118.7962698895,1273.15 0.0022,1.4099956266878,0.29080900287693,34266.517330135,0.77918231727915,68532.837435159,0.0029763892793222,34266.808139137,3078.37559081,4124.0398381305,1273.15 0.00364,1.4099956326374,0.29087061464503,34266.517340569,0.77883725639345,68532.837724343,0.0029750711790663,34266.808211184,3079.0277857598,4122.2135071067,1273.15 -0.005368,1.4099956310122,0.29090816114346,34266.517337719,0.7788343886168,68532.837645346,0.002975060226195,34266.80824588,3079.4252363997,4122.1983285986,1273.15 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+1000000000,1.887881372156,1.0018621310322,45736.320220026,2.0029092741391,91760.474093644,0.0066120092598694,45737.322082157,9995.934284413,9991.8685724291,1200 diff --git a/test/tests/yttrium_hydrogen_system/gold/YHx_PCT_out.e b/test/tests/yttrium_hydrogen_system/gold/YHx_PCT_out.e index 755e15567..466c0273a 100644 Binary files a/test/tests/yttrium_hydrogen_system/gold/YHx_PCT_out.e and b/test/tests/yttrium_hydrogen_system/gold/YHx_PCT_out.e differ diff --git a/test/tests/yttrium_hydrogen_system/test_yhx_pct_rmspe.py b/test/tests/yttrium_hydrogen_system/test_yhx_pct_rmspe.py new file mode 100644 index 000000000..e76b0777e --- /dev/null +++ b/test/tests/yttrium_hydrogen_system/test_yhx_pct_rmspe.py @@ -0,0 +1,28 @@ +# This python script tests if the RMSPE (between TMAP8 +# predictions and analytical expressions) is smaller than 0.1 + +import os +import unittest + +from yhx_pct_metrics import compute_prediction_rmspe + +PREDICTION_RMSPE_LIMIT = 0.1 + +SCRIPT_DIR = os.path.dirname(os.path.abspath(__file__)) + + +class TestYHxPCTRMSPE(unittest.TestCase): + def test_prediction_rmspe(self): + rmspe = compute_prediction_rmspe(SCRIPT_DIR) + self.assertLess( + rmspe, + PREDICTION_RMSPE_LIMIT, + msg=( + f"YHx PCT prediction RMSPE {rmspe:.6f}% exceeds " + f"{PREDICTION_RMSPE_LIMIT:.6f}%." + ), + ) + + +if __name__ == "__main__": + unittest.main(verbosity=2) diff --git a/test/tests/yttrium_hydrogen_system/tests b/test/tests/yttrium_hydrogen_system/tests index b564aa193..ad2bf9fcd 100644 --- a/test/tests/yttrium_hydrogen_system/tests +++ b/test/tests/yttrium_hydrogen_system/tests @@ -4,15 +4,15 @@ [YHx_PCT_csv] type = CSVDiff input = YHx_PCT.i - cli_args = 'InterfaceKernels/interface_reaction_YHx_PCT/silence_warnings=true' # should be removed once PCT curve implementation for low pressure is complete + cli_args = 'Executioner/nl_rel_tol=6e-6 Executioner/scheme="implicit-euler" InterfaceKernels/interface_reaction_YHx_PCT/silence_warnings=true' # should be removed once PCT curve implementation for low pressure is complete csvdiff = YHx_PCT_out.csv - max_parallel = 1 # see #200 + recover = false # see #196 requirement = 'The system shall be able to model the PCT curves of YHx to determine the surface atomic fraction as a function of pressure and temperature.' [] [YHx_PCT_exodus] type = Exodiff input = YHx_PCT.i - cli_args = 'InterfaceKernels/interface_reaction_YHx_PCT/silence_warnings=true' # should be removed once PCT curve implementation for low pressure is complete + cli_args = 'Executioner/nl_rel_tol=6e-6 Executioner/scheme="implicit-euler" InterfaceKernels/interface_reaction_YHx_PCT/silence_warnings=true' # should be removed once PCT curve implementation for low pressure is complete exodiff = YHx_PCT_out.e prereq = YHx_PCT_csv should_execute = false # this test relies on the output files from YHx_PCT_csv, so it shouldn't be run twice @@ -27,9 +27,10 @@ initial_pressure_H2_enclosure_1=1e3 initial_atomic_fraction=1.55 Executioner/num_steps=150 + Executioner/nl_rel_tol=8e-6 + Executioner/TimeStepper/growth_factor=1.1 InterfaceKernels/interface_reaction_YHx_PCT/silence_warnings=true' # should be removed once PCT curve implementation for low pressure is complete csvdiff = YHx_PCT_T1173_P1e3_out.csv - max_parallel = 1 # see #200 requirement = 'The system shall be able to model the PCT curves of YHx to determine the surface atomic fraction as a function of pressure and temperature for P=1e3 Pa and T=1173.15 K.' [] [YHx_PCT_T1173_P1e4_csv] @@ -40,6 +41,8 @@ initial_pressure_H2_enclosure_1=1e4 initial_atomic_fraction=1.65 Executioner/num_steps=200 + Executioner/nl_rel_tol=1e-6 + Executioner/TimeStepper/growth_factor=1.2 InterfaceKernels/interface_reaction_YHx_PCT/silence_warnings=true' # should be removed once PCT curve implementation for low pressure is complete csvdiff = YHx_PCT_T1173_P1e4_out.csv requirement = 'The system shall be able to model the PCT curves of YHx to determine the surface atomic fraction as a function of pressure and temperature for P=1e4 Pa and T=1173.15 K.' @@ -52,8 +55,11 @@ initial_pressure_H2_enclosure_1=5e4 initial_atomic_fraction=1.85 Executioner/num_steps=200 + Executioner/nl_rel_tol=5e-7 + Executioner/TimeStepper/growth_factor=1.2 InterfaceKernels/interface_reaction_YHx_PCT/silence_warnings=true' # should be removed once PCT curve implementation for low pressure is complete csvdiff = YHx_PCT_T1173_P5e4_out.csv + recover = false # see #196 requirement = 'The system shall be able to model the PCT curves of YHx to determine the surface atomic fraction as a function of pressure and temperature for P=5e4 Pa and T=1173.15 K.' [] [YHx_PCT_T1273_P3e3_csv] @@ -64,9 +70,10 @@ initial_pressure_H2_enclosure_1=3e3 initial_atomic_fraction=1.41 Executioner/num_steps=200 + Executioner/nl_rel_tol=9e-6 InterfaceKernels/interface_reaction_YHx_PCT/silence_warnings=true' # should be removed once PCT curve implementation for low pressure is complete csvdiff = YHx_PCT_T1273_P3e3_out.csv - max_parallel = 1 # see #200 + recover = false requirement = 'The system shall be able to model the PCT curves of YHx to determine the surface atomic fraction as a function of pressure and temperature for P=3e3 Pa and T=1273.15 K.' [] [YHx_PCT_comparison] diff --git a/test/tests/yttrium_hydrogen_system/yhx_pct_metrics.py b/test/tests/yttrium_hydrogen_system/yhx_pct_metrics.py new file mode 100644 index 000000000..290032c66 --- /dev/null +++ b/test/tests/yttrium_hydrogen_system/yhx_pct_metrics.py @@ -0,0 +1,63 @@ +# The python script compares the TMAP8 predictions against the +# analytical expression of the PCT curve + +import os + +import numpy as np +import pandas as pd + +PREDICTION_FILES = ( + "YHx_PCT_T1273_P3e3_out.csv", + "YHx_PCT_T1173_P1e3_out.csv", + "YHx_PCT_T1173_P1e4_out.csv", + "YHx_PCT_T1173_P5e4_out.csv", +) + + +def p0_lim_func(temperature): + return np.exp( + -26.1 + + 3.88 * 10 ** (-2) * np.array(temperature) + - 9.7 * 10 ** (-6) * np.square(temperature) + ) + + +def atom_ratio_eq_upper_func(temperature, pressure): + return 2 - ( + 1 + + np.exp( + 21.6 + - 0.0225 * temperature + + (-0.0445 + 7.18 * 10 ** (-4) * temperature) + * np.log(pressure - p0_lim_func(temperature)) + ) + ) ** (-1) + + +def load_prediction_points(csv_folder): + points = [] + for filename in PREDICTION_FILES: + dataframe = pd.read_csv(os.path.join(csv_folder, filename)) + temperature = dataframe["temperature"].iat[-1] + pressure = dataframe["pressure_H2_enclosure_1_at_interface"].iat[-1] + prediction = dataframe["atomic_fraction_H_enclosure_2_at_interface"].iat[-1] + reference = atom_ratio_eq_upper_func(temperature, pressure) + points.append( + { + "filename": filename, + "temperature": temperature, + "pressure": pressure, + "prediction": prediction, + "reference": reference, + } + ) + + return points + + +def compute_prediction_rmspe(csv_folder): + points = load_prediction_points(csv_folder) + predictions = np.array([point["prediction"] for point in points]) + references = np.array([point["reference"] for point in points]) + rmse = np.sqrt(np.mean((predictions - references) ** 2)) + return rmse * 100.0 / np.mean(references)