From 7322c0824bf4586f9b69acbbc3338419eee612e0 Mon Sep 17 00:00:00 2001 From: "Butterworth, Evan" Date: Tue, 9 Jun 2026 10:32:06 -0600 Subject: [PATCH 01/12] Updating case to new name: val-2l Ref #405 --- .../verification_and_validation/val-2l.md | 0 test/tests/val-2l/comparison_val-2l.py | 294 ++++++++++++++ .../tests/val-2l/plot_subplots_at_timestep.py | 80 ++++ test/tests/val-2l/subplots_animation.py | 86 ++++ test/tests/val-2l/tests | 25 ++ test/tests/val-2l/val-2l.i | 378 ++++++++++++++++++ 6 files changed, 863 insertions(+) create mode 100644 doc/content/verification_and_validation/val-2l.md create mode 100644 test/tests/val-2l/comparison_val-2l.py create mode 100644 test/tests/val-2l/plot_subplots_at_timestep.py create mode 100644 test/tests/val-2l/subplots_animation.py create mode 100644 test/tests/val-2l/tests create mode 100644 test/tests/val-2l/val-2l.i diff --git a/doc/content/verification_and_validation/val-2l.md b/doc/content/verification_and_validation/val-2l.md new file mode 100644 index 000000000..e69de29bb diff --git a/test/tests/val-2l/comparison_val-2l.py b/test/tests/val-2l/comparison_val-2l.py new file mode 100644 index 000000000..4581d78d4 --- /dev/null +++ b/test/tests/val-2l/comparison_val-2l.py @@ -0,0 +1,294 @@ +import matplotlib.pyplot as plt +import numpy as np +from matplotlib import gridspec +import pandas as pd +from scipy import special +import scipy.stats as stats +import os + +# Changes working directory to script directory (for consistent MooseDocs usage) +script_folder = os.path.dirname(__file__) +os.chdir(script_folder) + + +# ================================= Functions ================================ # + + +def read_csv_from_TMAP8(file_name, parameter_names): + """Read simulation output columns from a gold CSV file into a numpy array + + Args: + file_name (str): name of the CSV file in the gold directory + parameter_names (list of str): column names to extract, in desired order + + Returns: + ndarray: 2D array of shape (len(parameter_names), n_timesteps) + """ + if "/tmap8/doc/" in script_folder.lower(): # if in documentation folder + csv_folder = f"../../../../test/tests/mini_canister/gold/{file_name}" + + else: # if in test folder + # csv_folder = f"./gold/{file_name}" + csv_folder = f"./{file_name}" + simulation_data = pd.read_csv(csv_folder) + return np.array([simulation_data[name] for name in parameter_names]) + + +def numerical_solution_on_experiment_input(experiment_input, tmap_input, tmap_output): + """Get new numerical solution based on the experimental input data points + + Args: + experiment_input (float, ndarray): experimental input data points + tmap_input (float, ndarray): numerical input data points + tmap_output (float, ndarray): numerical output data points + + Returns: + float, ndarray: updated tmap_output based on the data points in experiment_input + """ + new_tmap_output = np.zeros(len(experiment_input)) + for i in range(len(experiment_input)): + left_limit = np.argwhere((np.diff(tmap_input < experiment_input[i])))[0][0] + right_limit = left_limit + 1 + new_tmap_output[i] = (experiment_input[i] - tmap_input[left_limit]) / ( + tmap_input[right_limit] - tmap_input[left_limit] + ) * (tmap_output[right_limit] - tmap_output[left_limit]) + tmap_output[ + left_limit + ] + return new_tmap_output + + +def compute_rmspe(simulated, reference): + """Compute the Root Mean Square Percentage Error between two arrays + + Args: + simulated (float, ndarray): simulated values + reference (float, ndarray): reference values used as the denominator + + Returns: + float: RMSPE in percent + """ + RMSE = np.sqrt(np.mean((simulated - reference) ** 2)) + return RMSE * 100 / np.mean(reference) + + +def annotate_rmspe(simulated, reference, x_pos, y_pos): + """Compute RMSPE and annotate it as bold text on the current matplotlib axes + + Args: + simulated (float, ndarray): simulated values + reference (float, ndarray): reference values used as the denominator + x_pos (float): x-coordinate of the annotation + y_pos (float): y-coordinate of the annotation + """ + RMSPE = compute_rmspe(simulated, reference) + plt.text(x_pos, y_pos, "RMSPE = %.2f %%" % RMSPE, fontweight="bold") + + +def plot_conservation_of_mass(t, flux, mass, flux_label, title, filename): + """Plot accumulated boundary flux against total mass to verify conservation + + Args: + t (float, ndarray): time array in days + flux (float, ndarray): accumulated boundary flux in µmol H + mass (float, ndarray): total H mass in domain in µmol H + flux_label (str): legend label for the flux line + title (str): plot title + filename (str): output PNG filename + """ + fig = plt.figure(figsize=(10, 6)) + plt.plot(t, flux, label=flux_label) + plt.plot(t, mass, label="H Total Mass") + annotate_rmspe(flux, mass, t[-1] / 2, mass[-1] / 4) + plt.xlabel("Time (Days)") + plt.ylabel(r"$\mu$mol H") + plt.title(title) + plt.xlim(0, t.max()) + plt.ylim(0) + plt.legend() + plt.grid(True) + plt.savefig(filename, bbox_inches="tight", dpi=300) + plt.close(fig) + + +def plot_validation(t_sim, sim_data, t_exp, exp_data, ylabel, title, filename): + """Plot simulation results against SRNL experimental data with RMSPE annotation + + Args: + t_sim (float, ndarray): simulation time array in days + sim_data (float, ndarray): simulation output values + t_exp (float, ndarray): experimental time array in days + exp_data (float, ndarray): experimental measurement values + ylabel (str): y-axis label + title (str): plot title + filename (str): output PNG filename + """ + fig = plt.figure(figsize=(10, 6)) + plt.plot(t_sim, sim_data, label="Simulation") + plt.plot(t_exp, exp_data, "ro", label="Experimental Data") + mapped = numerical_solution_on_experiment_input(t_exp, t_sim, sim_data) + annotate_rmspe(mapped, exp_data, t_sim[-1] / 2, sim_data[-1] / 4) + plt.ylabel(ylabel) + plt.xlabel("Time (Days)") + plt.title(title) + plt.xlim(0) + plt.ylim(0) + plt.legend() + plt.grid(True) + plt.savefig(filename, bbox_inches="tight", dpi=300) + plt.close(fig) + + +def plot_source_function(depth, width, flux, filename, n_widths=6): + """Plot the Gaussian implantation source term centered around the implantation depth + + The source rate evaluated at position x (µm) is: + S(x) = flux / (width * sqrt(2*pi)) * exp(-0.5 * ((x - depth) / width)^2) + + Args: + depth (float): mean implantation depth in µm + width (float): standard deviation (sigma) of the implantation profile in µm + flux (float): incident surface flux in at/µm²/s + filename (str): output PNG filename + n_widths (int): half-width of the x-axis expressed in number of sigmas + """ + x_lo = max(0.0, depth - n_widths * width) + x_hi = depth + n_widths * width + x = np.linspace(x_lo, x_hi, 2000) + source = flux / (width * np.sqrt(2 * np.pi)) * np.exp(-0.5 * ((x - depth) / width) ** 2) + + fig, ax = plt.subplots(figsize=(8, 5)) + ax.plot(x, source, color="steelblue", linewidth=2, label="Source rate") + ax.axvline(depth, color="k", linestyle="--", linewidth=1, label=f"Depth = {depth:.4f} µm") + ax.set_xlabel(r"Depth ($\mu$m)") + ax.set_ylabel(r"Source rate (at/$\mu$m$^3$/s)") + ax.set_title("Gaussian implantation source profile") + ax.set_xlim(x_lo, x_hi) + ax.set_ylim(bottom=0) + ax.legend() + ax.grid(True) + plt.tight_layout() + plt.savefig(filename, bbox_inches="tight", dpi=300) + plt.close(fig) + +# =========================== TMAP8 steel-only simulation data extraction ========================== # + +# ( +# steel_only_t, +# steel_only_total_mass_steel, +# steel_only_flux_steel, +# steel_only_exact_diffusion_length, +# steel_only_simulated_diffusion_length, +# ) = read_csv_from_TMAP8( +# "steel_only_out.csv", +# [ +# "time", +# "annular_cylinder_total_mass_steel", +# "annular_cylinder_time_integrated_flux", +# "exact_diffusion_length", +# "simulated_diffusion_length", +# ], +# ) +csv_folder = "val-2l_out.csv" +simulation_TMAP8_data = pd.read_csv(csv_folder) +simulation_time_TMAP8 = simulation_TMAP8_data["time"] +# simulation_recom_flux_left_TMAP8 = simulation_TMAP8_data[ + # "scaled_recombination_flux_left" +# ] +# simulation_recom_flux_right_TMAP8 = simulation_TMAP8_data[ + # "scaled_recombination_flux_right" +# ] + +### Conservation of Mass ### +time_integrated_flux_difference = simulation_TMAP8_data['time_integrated_desorbed_flux_difference'] +total_deuterium_retention = simulation_TMAP8_data['total_deuterium_retention'] + +# Measure and Plot Conservation of Mass +plt.figure(figsize=(10, 6)) +plt.plot(simulation_time_TMAP8, time_integrated_flux_difference, label = 'Time-Accumulated Boundary Flux') +plt.plot(simulation_time_TMAP8,total_deuterium_retention, label = 'Total Concentration in Tungsten') +RMSE = np.sqrt(np.mean((total_deuterium_retention-time_integrated_flux_difference)**2) ) +RMSPE = RMSE*100/np.mean(total_deuterium_retention) +print(f'RMSPE = %.2f '%RMSPE+'%') +plt.text(60,0.02, 'RMSPE = %.2f '%RMSPE+'%',fontweight='bold') +plt.xlabel('Time (s)') +plt.ylabel(r'atom/$\mu m^2$') +plt.title(f'Conservation of Mass') +plt.xlim(0,simulation_time_TMAP8.max()) +plt.ylim(0) +plt.legend() +plt.grid(True) +plt.tight_layout() +plt.show() + +difference = abs(time_integrated_flux_difference-total_deuterium_retention) +plt.figure(figsize=(10, 6)) +plt.plot(simulation_time_TMAP8,difference) +plt.xlabel('Time (s)') +plt.ylabel(r'atom/$\mu m^2$') +plt.title(f'Conservation of Mass Difference') +plt.xlim(0,simulation_time_TMAP8.max()) +plt.grid(True) +plt.tight_layout() +plt.show() +# Read experiment data +# if "/tmap8/doc/" in script_folder.lower(): # if in documentation folder +# csv_folder = "../../../../test/tests/val-2l/gold/experiment_data_paper.csv" +# else: # if in test folder +# csv_folder = "./gold/experiment_data_paper.csv" +# experiment_TMAP4_data = pd.read_csv(csv_folder) +# experiment_time_TMAP4 = experiment_TMAP4_data["time (s)"] +# experiment_flux_TMAP4 = experiment_TMAP4_data["permeation flux (atom/m^2/s)"] + +TMAP8_file_base = "val-2l_comparison" +############################ recombination flux - atom/m$^2$/s ############################ +# fig = plt.figure(figsize=[6.5, 5.5]) +# gs = gridspec.GridSpec(1, 1) +# ax = fig.add_subplot(gs[0]) + +# ax.plot( +# simulation_time_TMAP8 / 3600, +# simulation_recom_flux_right_TMAP8, +# linestyle="-", +# label=r"TMAP8", +# c="tab:gray", +# ) +# ax.plot( +# experiment_time_TMAP4 / 3600, +# experiment_flux_TMAP4, +# linestyle="--", +# label=r"Experiment", +# c="k", +# ) + +# ax.set_xlabel("Time (hr)") +# ax.set_ylabel("Deuterium flux (atom/m$^2$/s)") +# ax.legend(loc="best") +# ax.set_ylim(bottom=0) +# ax.set_xlim(left=-0.1, right=2e4 / 3600) +# plt.grid(visible=True, which="major", color="0.65", linestyle="--", alpha=0.3) +# tmap_flux_for_rmspe = numerical_solution_on_experiment_input( +# experiment_time_TMAP4, simulation_time_TMAP8, simulation_recom_flux_right_TMAP8 +# ) +# RMSE = np.sqrt(np.mean((tmap_flux_for_rmspe - experiment_flux_TMAP4) ** 2)) +# RMSPE = RMSE * 100 / np.mean(experiment_flux_TMAP4) +# ax.text(1e4 / 3600.0, 40e15, "RMSPE = %.2f " % RMSPE + "%", fontweight="bold") +# ax.minorticks_on() +# ax.ticklabel_format(axis="y", style="sci", scilimits=(15, 15)) +# plt.savefig(f"{TMAP8_file_base}.png", bbox_inches="tight", dpi=300) +# plt.close(fig) + + +############################ implantation - atom/m$^2$/s ############################ +# Use VPP to pull this from MOOSE simulation??? + +# Parameters from val-2l.i converted to µm +depth_um = 2.64e-9 * 1e6 # ${units 2.64e-9 m -> mum} +width_um = 3.58e-9 * 1e6 # ${units 3.58e-9 m -> mum} +flux_um = 5e21 * 1e-12 # ${units 5e21 at/m^2/s -> at/mum^2/s} + +plot_source_function( + depth=depth_um, + width=width_um, + flux=flux_um, + filename="val-2l_comparison_normal_distribution.png", +) diff --git a/test/tests/val-2l/plot_subplots_at_timestep.py b/test/tests/val-2l/plot_subplots_at_timestep.py new file mode 100644 index 000000000..6030fe3ac --- /dev/null +++ b/test/tests/val-2l/plot_subplots_at_timestep.py @@ -0,0 +1,80 @@ +import pandas as pd +import matplotlib.pyplot as plt +import matplotlib.animation as animation +import os + +def subplot_bar_profile(timestep, data_dir='csv_data'): + # Load the data + gas_path = os.path.join(data_dir, f"verification_RZ_solution_profile_gas_{timestep:04d}.csv") + steel_path = os.path.join(data_dir, f"verification_RZ_solution_profile_steel_{timestep:04d}.csv") + + gas_df = pd.read_csv(gas_path, skipinitialspace=True) + steel_df = pd.read_csv(steel_path, skipinitialspace=True) + total_df = pd.read_csv(os.path.join(data_dir,"verification_RZ.csv"), skipinitialspace = True) + + # Replace Correct Data point for gas concentration at interface due to bug in vpp + # print('Testing Gas') + # print(gas_df['H_mobile_gas'].iloc[-1]) + # print("Did Value Change???") + # gas_df.iloc[-1, gas_df.columns.get_loc('H_mobile_gas')] = corrective_df.iloc[timestep-1,corrective_df.columns.get_loc('Mobile_gas_interface')] + # print(gas_df['H_mobile_gas'].iloc[-1]) + + # print('Testing Steel') + # print(steel_df['H_mobile_steel'].iloc[-1]) + # print("Did Value Change???") + # steel_df.iloc[-1, steel_df.columns.get_loc('H_mobile_steel')] = corrective_df.iloc[timestep-1,corrective_df.columns.get_loc('Mobile_steel_edge_air')] + # print(steel_df['H_mobile_steel'].iloc[-1]) + + time = total_df['time'] + + # Get spatial coordinates + gas_x = gas_df['x'] + # print(type(gas_x)) + steel_x = steel_df['x'] + # print(gas_x) + # print(steel_x) + + # Extract variable names + gas_var = gas_df.columns[0] + steel_var = steel_df.columns[0] + # print(gas_var) + # print(steel_var) + + # Extract variable values + gas_values = gas_df[gas_var] + steel_values = steel_df[steel_var] + # print(gas_values) + # print(steel_values) + + # Plotting + fig, (ax1, ax2) = plt.subplots(2, 1, figsize=(12, 8), sharex=False) + + # Gas phase plot + ax1.plot(gas_x, gas_values, color='blue') + ax1.set_xlim(gas_x.min(), gas_x.max()) + ax1.set_ylim(gas_values.min()*0.995, gas_values.max()*1.005) + ax1.set_ylabel(r'Molecular H$_2$ Concentration in Gas ($\mu$mol/mm$^3$)') + ax1.set_title(f'Timestep {timestep} at Time: {time[timestep-1]:01.2f} days') + ax1.grid(True) + + # Steel phase plot + ax2.plot(steel_x, steel_values, color='green') + ax2.set_xlim(steel_x.min(), steel_x.max()) + ax2.set_ylim(steel_values.min(), steel_values.max()) + ax2.set_ylabel(r'Atomic H Concentration in Steel ($\mu$mol/mm^3)') + ax2.set_xlabel('Distance from Canister Center (mm)') + # ax2.set_title(f'Steel - Timestep {timestep}') + ax2.grid(True) + + plt.tight_layout() + plt.show() + +if __name__ == "__main__": + import argparse + + parser = argparse.ArgumentParser(description="Plot gas and steel concentration profiles for a given timestep.") + parser.add_argument("timestep", type=int, help="Timestep number (e.g., 1 for _0001.csv)") + parser.add_argument("--data_dir", type=str, default="csv_data", help="Directory containing the CSV files") + + args = parser.parse_args() + subplot_bar_profile(args.timestep, data_dir=args.data_dir) diff --git a/test/tests/val-2l/subplots_animation.py b/test/tests/val-2l/subplots_animation.py new file mode 100644 index 000000000..0b12ebb84 --- /dev/null +++ b/test/tests/val-2l/subplots_animation.py @@ -0,0 +1,86 @@ +import pandas as pd +import matplotlib.pyplot as plt +import matplotlib.animation as animation +import os +import glob + +script_folder = os.path.dirname(__file__) +os.chdir(script_folder) + +# Filter out empty files — MOOSE writes a header-only file for the INITIAL step +all_files = sorted(glob.glob("concentration_profile/val-2k_out_concentration_profile_*.csv")) +profile_files = [ + f for f in all_files + if pd.read_csv(f, skipinitialspace=True).shape[0] > 0 +] +num_timesteps = len(profile_files) + +if num_timesteps == 0: + raise FileNotFoundError( + "No non-empty concentration profile CSV files found. " + "Run the simulation with VectorPostprocessors enabled." + ) + +global_data = pd.read_csv("val-2k_out.csv") +times = global_data["time"].values + +near_surface_limit_um = 1.0 # μm shown in lower subplot + +# Pre-scan non-empty files for fixed axis limits across all frames +c_max = 0.0 +for f in profile_files: + df = pd.read_csv(f, skipinitialspace=True) + c_max = max(c_max, df["concentration"].max()) +c_max *= 1.05 + +x_max_um = pd.read_csv(profile_files[0], skipinitialspace=True)["x"].max() + +fig, (ax1, ax2) = plt.subplots(2, 1, figsize=(10, 8), constrained_layout=True) + + +def animate(frame): + ax1.clear() + ax2.clear() + + df = pd.read_csv(profile_files[frame], skipinitialspace=True) + x = df["x"].values # μm + c = df["concentration"].values # at/μm³ + + time_s = times[frame] if frame < len(times) else times[-1] + + # Full-domain profile + ax1.plot(x, c, color="steelblue", linewidth=1.5) + ax1.set_xlim(0, x_max_um) + ax1.set_ylim(0, c_max) + ax1.set_xlabel(r"Depth ($\mu$m)") + ax1.set_ylabel(r"Concentration (at/$\mu$m$^3$)") + ax1.set_title(f"Deuterium in Tungsten — t = {time_s:.2f} s") + ax1.grid(True) + + # Near-surface zoom + mask = x <= near_surface_limit_um + ax2.plot(x[mask], c[mask], color="darkorange", linewidth=1.5) + ax2.set_xlim(0, near_surface_limit_um) + ax2.set_ylim(0, c_max) + ax2.set_xlabel(r"Depth ($\mu$m)") + ax2.set_ylabel(r"Concentration (at/$\mu$m$^3$)") + ax2.set_title(f"Near-surface (0 – {near_surface_limit_um} $\\mu$m)") + ax2.grid(True) + + return ax1, ax2 + + +ani = animation.FuncAnimation( + fig, animate, frames=num_timesteps, interval=100, blit=False +) + +# Use ffmpeg if available, otherwise fall back to Pillow (gif) +if animation.writers.is_available("ffmpeg"): + output_file = "val-2k_concentration_animation.mp4" + ani.save(output_file, writer="ffmpeg", fps=10) +else: + output_file = "val-2k_concentration_animation.gif" + ani.save(output_file, writer="pillow", fps=10) + +plt.close(fig) +print(f"Saved {output_file} ({num_timesteps} frames)") diff --git a/test/tests/val-2l/tests b/test/tests/val-2l/tests new file mode 100644 index 000000000..e9827f516 --- /dev/null +++ b/test/tests/val-2l/tests @@ -0,0 +1,25 @@ +[Tests] + # design = 'MatNeumannBC.md' + issues = '#405' + validation = 'val-2l.md' + [val-2l_csvdiff] + type = CSVDiff + input = 'val-2l.i' + csvdiff = val-2l_out.csv + requirement = 'The system shall be able to model deuterium transport through irradiated tungsten for comparison with experimental results.' + [] + [val-2l_exodiff] + type = Exodiff + input = 'val-2l.i' + exodiff = val-2l_out.e + prereq = val-2l_csvdiff + should_execute = false # this test relies on the output files from val-2a_csvdiff, so it shouldn't be run twice + requirement = 'The system shall be able to model deuterium transport through irradiated tungsten for comparison with experimental results.' + [] + [val-2l_comparison] + type = RunCommand + command = 'python3 comparison_val-2l.py' + requirement = 'The system shall be able to generate comparison plots between the analytical solution and simulated solution of validation case 2l' + required_python_packages = 'matplotlib numpy pandas os' + [] +[] diff --git a/test/tests/val-2l/val-2l.i b/test/tests/val-2l/val-2l.i new file mode 100644 index 000000000..b997c2dbb --- /dev/null +++ b/test/tests/val-2l/val-2l.i @@ -0,0 +1,378 @@ +# Validation Problem #2l from TMAP4/TMAP7 V&V document + +# !include val-2l.params + +# General parameters +kB = '${units 1.380649e-23 J/K}' # Boltzmann constant (from PhysicalConstants.h - https://physics.nist.gov/cgi-bin/cuu/Value?r) + +# Mesh and solver controls +nx_scale = 5 # mesh refinement multiplier (see [Mesh]); increase for convergence studies +dt_max = '${units 4 s}' +simulation_time = '${units 0.5 h -> s}' # 2 h plasma implantation + temperature ramp + +# Geometry +tungsten_thickness = '${units 0.2 mm -> mum}' # Tungsten disc thickness, Shimada et al. 2010 (p. S667, Section 2.1) +# near_surface_length = '${units 1 mum}' +# bulk_material_length = '${units 6 mum}' +# deep_material_length = '${fparse total_length - bulk_material_length - near_surface_length}' + +# Diffusion parameters +# Temperature-dependent deuterium diffusivity from Shimada et al. 2010 (p. S668, Section 3): D = 2.9e-7 * exp(-0.39 eV / kB / T) (m^2/s) +diffusivity_coefficient = '${units 2.9e-7 m^2/s -> mum^2/s}' # D0 prefactor, Shimada et al. 2010 (p. S668) +E_D = '${units 0.39 eV -> J}' # Diffusion activation energy, Shimada et al. 2010 (p. S668) + +# Recombination parameters +# recombination_parameter = '${units ${fparse 3.2e-15*exp(-1.16)} m^4/at/s -> mum^4/at/s}' # Shimada et al. 2010 (p. S668), for recombination BC option +# recombination_parameter_enclos2 = '${units 2e-31 m^4/at/s -> mum^4/at/s}' +# recombination_coefficient_parameter_enclos1_TMAP4 = '${units 1e-27 m^4/at/s -> mum^4/at/s}' + +# Implantation source parameters +# NOTE: the implantation depth and width are NOT reported in Shimada et al. 2010. Pulled from val-2i +width = '${units 3.58e-9 m -> mum}' # implantation profile standard deviation +depth = '${units 2.64e-9 m -> mum}' # implantation mean depth +flux_high = '${units 5e21 at/m^2/s -> at/mum^2/s}' # Incident D ion flux, Shimada et al. 2010 (p. S667, Section 2.3) +TPE_hold_time = '${units 2 h -> s}' # Deuterium plasma implantation for 2 h, Shimada et al. 2010 (p. S667, Section 2.3 & Fig. 1) + +# Thermal parameters +# Plasma exposure is held at 473 K; after transfer (Section 2.4) the TDS ramp runs from room +# temperature to 1173 K at 10 K/min, per Shimada et al. 2010 (p. S668, Section 2.3 & Fig. 1) +temperature_implantation = '${units 473 K}' # Plasma exposure temperature, Shimada et al. 2010 (p. S668, Section 2.3 & Fig. 1) +temperature_tds_start = '${units 300 K}' # TDS ramp start (room temperature), Shimada et al. 2010 (p. S668, Figs. 2-4) +temperature_high = '${units 1173 K}' # TDS ramp peak temperature, Shimada et al. 2010 (p. S668, Fig. 1) +temperature_rate = '${units ${fparse 10 / 60} K/s}' # TDS ramp rate of 10 K/min, Shimada et al. 2010 (p. S668, Fig. 1) + +[Variables] + # Concentration of deuterium in tungsten (atoms/mum^3) + [concentration] + [] +[] + +[Mesh] + # coord_type = 'RZ' # Look into how mesh axis and axis of symmetry being same effects postprocessor calculations + # rz_coord_axis = X # Specifies x axis is axis of symmetry of y axis is radial direction + # Graded mesh: sub-nm elements near the upstream surface to resolve the implantation Gaussian + # (mean 2.64 nm, sigma 3.58 nm), coarsening into the bulk where the concentration is ~ 0. + # Region lengths (near surface -> bulk): 20 nm, 80 nm, 0.9 um, 9 um, remainder to tungsten_thickness. + [cartesian] + type = CartesianMeshGenerator + dim = 1 + dx = '${units 2e-8 m -> mum} + ${units 8e-8 m -> mum} + ${units 9e-7 m -> mum} + ${units 9e-6 m -> mum} + ${fparse ${tungsten_thickness} - ${units 1e-5 m -> mum}}' + ix = '${fparse 8 * nx_scale} + ${fparse 4 * nx_scale} + ${fparse 4 * nx_scale} + ${fparse 4 * nx_scale} + ${fparse 4 * nx_scale}' + [] + [tungsten_disc] # Cross section through thickness of disk. Can scale measurements by 9*pi mm for full sample metrics + type = RenameBoundaryGenerator + input = cartesian + old_boundary = 'left right' + new_boundary = 'upstream downstream' + [] +[] + +[Problem] + # Reference-based convergence: compare each variable's residual to the magnitude of the physical + # terms (diffusion + time derivative + source, tagged 'ref') rather than to the initial residual + type = ReferenceResidualProblem + extra_tag_vectors = 'ref' + reference_vector = 'ref' +[] + +[Kernels] + [diffusion] + type = ADMatDiffusion + variable = concentration + diffusivity = diffusivity_D + extra_vector_tags = 'ref' + [] + [time_diffusion] + type = ADTimeDerivative + variable = concentration + extra_vector_tags = 'ref' + [] + [source] + type = ADBodyForce + variable = concentration + function = concentration_source_norm_func + extra_vector_tags = 'ref' + [] +[] + +[AuxVariables] + # Source term profile used for postprocessing + [concentration_source] + [] + # # Time-dependent recombination coefficient on the upstream side + # [recombination_TMAP4] + # [] +[] + +[AuxKernels] + [concentration_source_aux] + type = FunctionAux + variable = concentration_source + function = concentration_source_norm_func + execute_on = 'INITIAL TIMESTEP_END' + [] + # [recombination_aux_TMAP4] + # type = FunctionAux + # variable = recombination_TMAP4 + # function = '${recombination_coefficient_parameter_enclos1_TMAP4}' + # execute_on = 'INITIAL TIMESTEP_END' + # [] +[] + +[BCs] + # Assume infinite recombination on upstream and downstream surfaces + [left] + type = ADDirichletBC + boundary = upstream + value = 0 + variable = concentration + [] + [right] + type = ADDirichletBC + boundary = downstream + value = 0 + variable = concentration + [] + + # Flux balance from recombination on upstream surface (left) + # [left] + # type = ADMatNeumannBC + # variable = concentration + # boundary = upstream + # value = 1 + # boundary_material = flux_on_upstream + # [] + # # Flux balance from recombination on downstream surface (right) + # [right] + # type = ADMatNeumannBC + # variable = concentration + # boundary = downstream + # value = 1 + # boundary_material = flux_on_downstream + # [] +[] + +[Materials] + # Temperature-dependent deuterium diffusivity in tungsten + [diffusivity_D] + type = ADDerivativeParsedMaterial + property_name = 'diffusivity_D' + functor_names = 'Temperature_function' + functor_symbols = 'temperature' + expression = '${diffusivity_coefficient} * exp(- ${E_D} / ${kB} / temperature)' + output_properties = 'diffusivity_D' + outputs = 'exodus' + [] + # # Recombination-driven flux on upstream boundary (left) + # [flux_on_upstream] + # type = ADDerivativeParsedMaterial + # coupled_variables = 'concentration' + # property_name = 'flux_on_upstream' + # functor_names = 'Kr_upstream_func' + # functor_symbols = 'Kr_upstream_func' + # expression = '- 2 * Kr_upstream_func * concentration ^ 2' + # [] + # # # Recombination-driven flux on downstream boundary (right) + # [flux_on_downstream] + # type = ADDerivativeParsedMaterial + # coupled_variables = 'concentration' + # property_name = 'flux_on_downstream' + # expression = '- 2 * ${recombination_parameter_enclos2} * concentration ^ 2' + # [] +[] + +[Functions] + # Temperature history (K): hold at the implantation temperature while the beam is on, then an + # instantaneous cooldown to room temperature at the end of implantation (approximating the air + # transfer in Section 2.4), followed by a linear TDS ramp to the peak temperature and a hold + [Temperature_function] + type = ParsedFunction + expression = 'if(t<${TPE_hold_time}, ${temperature_implantation}, + if(t<${TPE_hold_time} + (${temperature_high} - ${temperature_tds_start}) / + ${temperature_rate}, ${temperature_tds_start} + ${temperature_rate} * (t - ${TPE_hold_time}), + ${temperature_high}))' + [] + # Upstream recombination coefficient (time-dependent exponential) in microns^4/at/s + # [Kr_upstream_func] + # type = ParsedFunction + # expression = '${recombination_coefficient_parameter_enclos1_TMAP4} * (1 - 0.9999 * exp(-6e-5 * t))' + # [] + # Beam flux schedule applied to upstream surface (atoms/mum^2/s) + [surface_flux_func] + type = ParsedFunction + expression = 'if(t<${TPE_hold_time}, ${flux_high}, 0)' + [] + # Normalized implantation distribution across tungsten thickness + [source_distribution] # (-) + type = ParsedFunction + # expression = '1.5 / (${width} * sqrt(2 * pi)) * exp(-0.5 * ((x - ${depth}) / ${width})^2)' + expression = '1 / ( ${width} * sqrt(2 * pi) ) * exp(-0.5 * ((x - ${depth}) / ${width} ) ^ 2)' + [] + # Spatial-temporal source term from beam flux and implantation profile (atoms/microns^2/s) + [concentration_source_norm_func] # atoms/microns^2/s + type = ParsedFunction + symbol_names = 'source_distribution surface_flux_func' + symbol_values = 'source_distribution surface_flux_func' + expression = 'source_distribution * surface_flux_func' + # expression = 1e-5 + [] + + # Adaptive timestepper ceiling + [max_dt_size_func] # s + type = ParsedFunction + expression = ${dt_max} + [] +[] + +[Postprocessors] + + ### Conservation of Mass ### + + [total_deuterium_retention] # atoms / mum^2 + type = ElementIntegralVariablePostprocessor + variable = concentration + outputs = csv + [] + + [upstream_flux] + type = ADSideDiffusiveFluxIntegral + boundary = 'upstream' + variable = concentration + diffusivity = diffusivity_D + outputs = csv + [] + + [downstream_flux] + type = ADSideDiffusiveFluxIntegral + boundary = 'downstream' + variable = concentration + diffusivity = diffusivity_D + outputs = csv + [] + + [deuterium_source] # Integral of Source function gives atoms/mum^2/s + type = FunctionElementIntegral + function = concentration_source_norm_func + outputs = csv + [] + + # [analytical_total_mass_source] + # type = FunctionValuePostprocessor + # function = analytical_total_mass_fun + # [] + + [flux_difference_plus_source] + type = ParsedPostprocessor + expression = 'deuterium_source - upstream_flux - downstream_flux' + pp_names = 'deuterium_source upstream_flux downstream_flux' + outputs = csv + [] + + [time_integrated_desorbed_flux_difference] + type = TimeIntegratedPostprocessor + value = flux_difference_plus_source + time_integration_scheme = trapezoidal-rule + outputs = csv + [] + + ### Desorbed Flux on Upstream and Downstream Surfaces + + # Average flux on upstream surface (left) from recombination + # [dcdx_upstream] + # type = ADSideAverageMaterialProperty + # boundary = upstream + # property = flux_on_upstream + # outputs = none + # [] + # Output upstream recombination flux (scaled to atoms/mum^2/s) + # [scaled_recombination_flux_upstream] + # type = ScalePostprocessor + # scaling_factor = '${fparse -1 * ${units 1 m^2 -> mum^2}}' + # value = dcdx_upstream + # execute_on = 'initial nonlinear linear timestep_end' + # outputs = 'console csv exodus' + # [] + # Average flux on downstream surface (right) from recombination + # [dcdx_downstream] + # type = ADSideAverageMaterialProperty + # boundary = downstream + # property = flux_on_downstream + # outputs = none + # [] + # # Output downstream recombination flux (scaled to atoms/mum^2/s) + # [scaled_recombination_flux_downstream] + # type = ScalePostprocessor + # scaling_factor = '${fparse -1 * ${units 1 m^2 -> mum^2}}' + # value = dcdx_downstream + # execute_on = 'initial nonlinear linear timestep_end' + # outputs = 'console csv exodus' + # [] + # Limit timestep size according to beam on/off schedule + [max_time_step_size] + type = FunctionValuePostprocessor + function = max_dt_size_func + execute_on = 'initial nonlinear linear timestep_end' + outputs = none + [] +[] + +[VectorPostprocessors] + [concentration_profile] + type = LineValueSampler + variable = concentration + start_point = '0 0 0' + end_point = '${tungsten_thickness} 0 0' + num_points = 500 + sort_by = x + execute_on = 'TIMESTEP_END' + outputs = profile_csv + [] +[] + +[Outputs] + file_base = 'val-2l_out' + csv = true + [exodus] + type = Exodus + output_material_properties = true + # time_step_interval = 2 + [] + [profile_csv] + type = CSV + file_base = 'concentration_profile/val-2l_out' + [] +[] + +[Preconditioning] + [SMP] + type = SMP + full = true + [] +[] + +[Executioner] + type = Transient + scheme = bdf2 + solve_type = NEWTON + petsc_options_iname = '-pc_type' + petsc_options_value = 'lu' + end_time = ${simulation_time} + automatic_scaling = true + # nl_rel_tol = 5e-7 # Borrowed from Val 2-a + [TimeStepper] + type = IterationAdaptiveDT + dt = 1.0 + optimal_iterations = 6 + growth_factor = 1.1 + cutback_factor_at_failure = 0.9 + timestep_limiting_postprocessor = max_time_step_size + [] +[] From 6407cab452084bf00e735c5d0fe251f5ef45a644 Mon Sep 17 00:00:00 2001 From: "Butterworth, Evan" Date: Mon, 13 Jul 2026 14:00:56 -0600 Subject: [PATCH 02/12] Making requested changes to plots and animations. Updated input file to remove source term and instead use initial condition to represent distribution of deuterium due to ion flux. --- test/tests/val-2l/comparison_val-2l.py | 344 ++++++++++++++---------- test/tests/val-2l/subplots_animation.py | 121 ++++----- test/tests/val-2l/val-2l.i | 341 +++++++++-------------- 3 files changed, 388 insertions(+), 418 deletions(-) diff --git a/test/tests/val-2l/comparison_val-2l.py b/test/tests/val-2l/comparison_val-2l.py index 4581d78d4..b74f22706 100644 --- a/test/tests/val-2l/comparison_val-2l.py +++ b/test/tests/val-2l/comparison_val-2l.py @@ -1,6 +1,7 @@ import matplotlib.pyplot as plt import numpy as np from matplotlib import gridspec +from matplotlib.patches import Patch import pandas as pd from scipy import special import scipy.stats as stats @@ -25,7 +26,7 @@ def read_csv_from_TMAP8(file_name, parameter_names): ndarray: 2D array of shape (len(parameter_names), n_timesteps) """ if "/tmap8/doc/" in script_folder.lower(): # if in documentation folder - csv_folder = f"../../../../test/tests/mini_canister/gold/{file_name}" + csv_folder = f"../../../../test/tests/val-2l/gold/{file_name}" else: # if in test folder # csv_folder = f"./gold/{file_name}" @@ -138,157 +139,224 @@ def plot_validation(t_sim, sim_data, t_exp, exp_data, ylabel, title, filename): plt.close(fig) -def plot_source_function(depth, width, flux, filename, n_widths=6): - """Plot the Gaussian implantation source term centered around the implantation depth +def plot_diffusivity_vs_temperature( + simulation_file="val-2l_out.csv", + filename="val-2l_diffusivity_vs_temperature.png", +): + """Plot the deuterium diffusivity in tungsten against temperature - The source rate evaluated at position x (µm) is: - S(x) = flux / (width * sqrt(2*pi)) * exp(-0.5 * ((x - depth) / width)^2) + The diffusivity is spatially uniform (it depends only on temperature), so the + ``diffusivity_pp`` and ``temperature`` postprocessors from the TMAP8 output fully + describe D(T) over the simulated TDS ramp. Reading them straight from the CSV + keeps the Arrhenius law defined in exactly one place (val-2l.i). It is the + Frauenfelder relation corrected for deuterium, Shimada et al. 2010 + (p. S668, Section 3): D = 2.9e-7 * exp(-0.39 eV / (k_B T)) m^2/s. Args: - depth (float): mean implantation depth in µm - width (float): standard deviation (sigma) of the implantation profile in µm - flux (float): incident surface flux in at/µm²/s + simulation_file (str): TMAP8 CSV with "temperature" (K) and "diffusivity_pp" + (µm²/s) columns filename (str): output PNG filename - n_widths (int): half-width of the x-axis expressed in number of sigmas """ - x_lo = max(0.0, depth - n_widths * width) - x_hi = depth + n_widths * width - x = np.linspace(x_lo, x_hi, 2000) - source = flux / (width * np.sqrt(2 * np.pi)) * np.exp(-0.5 * ((x - depth) / width) ** 2) + temperature, diffusivity = read_csv_from_TMAP8( + simulation_file, ["temperature", "diffusivity_pp"] + ) + # Drop the INITIAL row (t = 0), where postprocessors are still 0, then sort by T. + valid = diffusivity > 0 + temperature, diffusivity = temperature[valid], diffusivity[valid] + order = np.argsort(temperature) + temperature, diffusivity = temperature[order], diffusivity[order] + diffusivity_m2_s = diffusivity * 1e-12 # µm²/s -> m²/s + + reciprocal_temperature = 1000.0 / temperature # 1000/T (1/K) fig, ax = plt.subplots(figsize=(8, 5)) - ax.plot(x, source, color="steelblue", linewidth=2, label="Source rate") - ax.axvline(depth, color="k", linestyle="--", linewidth=1, label=f"Depth = {depth:.4f} µm") - ax.set_xlabel(r"Depth ($\mu$m)") - ax.set_ylabel(r"Source rate (at/$\mu$m$^3$/s)") - ax.set_title("Gaussian implantation source profile") - ax.set_xlim(x_lo, x_hi) - ax.set_ylim(bottom=0) - ax.legend() - ax.grid(True) + ax.semilogy(reciprocal_temperature, diffusivity_m2_s, color="steelblue", linewidth=2) + ax.set_xlabel(r"Reciprocal temperature 1000/T (K$^{-1}$)") + ax.set_ylabel(r"Diffusivity (m$^2$/s)") + ax.set_title("Deuterium diffusivity in tungsten TMAP8 Material") + ax.grid(True, which="both", linestyle="--", alpha=0.4) plt.tight_layout() plt.savefig(filename, bbox_inches="tight", dpi=300) plt.close(fig) -# =========================== TMAP8 steel-only simulation data extraction ========================== # - -# ( -# steel_only_t, -# steel_only_total_mass_steel, -# steel_only_flux_steel, -# steel_only_exact_diffusion_length, -# steel_only_simulated_diffusion_length, -# ) = read_csv_from_TMAP8( -# "steel_only_out.csv", -# [ -# "time", -# "annular_cylinder_total_mass_steel", -# "annular_cylinder_time_integrated_flux", -# "exact_diffusion_length", -# "simulated_diffusion_length", -# ], -# ) + +def plot_unirradiated_desorption( + experiment_file="unirradiated_data.csv", + simulation_file="val-2l_out.csv", + simulation_flux_column="upstream_flux", + experiment_plot="val-2l_experimental_desorption.png", + simulation_plot="val-2l_simulated_desorption.png", + comparison_plot="val-2l_comparison_desorption.png", +): + """Plot the Shimada (2010) unirradiated desorption data and the TMAP8 comparison + + Produces three figures: + 1. The digitized experimental desorbed-flux history (Shimada 2010, + unirradiated / 0 dpa): time (s) versus desorbed flux (m^-2 s^-1), with + the y-axis written in scientific notation. + 2. The raw TMAP8 simulated desorbed-flux history on its own time grid: + time (s) versus desorbed flux (m^-2 s^-1). + 3. The TMAP8 simulated desorbed flux mapped onto the experimental time + points with numerical_solution_on_experiment_input, overlaid on the + experimental data and annotated with the RMSPE via annotate_rmspe. + + The paper reports an areal desorption flux in m^-2 s^-1 (Shimada 2010, + Figs. 2-4), so the 1D model's areal flux is compared directly: the face area + cancels and no pi*r^2 scaling is needed (same convention as val-2d). + + Args: + experiment_file (str): two-column, header-less CSV of + (time [s], desorbed flux [m^-2 s^-1]) + simulation_file (str): TMAP8 CSV output holding a "time" column and the + desorbed-flux column + simulation_flux_column (str): name of the desorbed-flux column in + simulation_file. TMAP8 reports it in at/mum^2/s; it is converted to + at/m^2/s to match the experiment. + experiment_plot (str): output PNG filename for plot 1 + simulation_plot (str): output PNG filename for plot 2 + comparison_plot (str): output PNG filename for plot 3 + """ + # experiment: header-less (time [s], desorbed flux [m^-2 s^-1]) + experiment = np.loadtxt(experiment_file, delimiter=",") + experiment_time, experiment_flux = experiment[:, 0], experiment[:, 1] + + # ---- Plot 1: experimental desorption history ---- + plt.figure(figsize=(10, 6)) + plt.plot(experiment_time, experiment_flux, "ro", label="Experiment (Shimada 2010, 0 dpa)") + plt.xlabel("Time (s)") + plt.ylabel(r"Desorbed flux (m$^{-2}$s$^{-1}$)") + plt.title("Unirradiated deuterium desorption") + plt.xlim(0, experiment_time.max()) + plt.ylim(0) + plt.ticklabel_format(axis="y", style="sci", scilimits=(0, 0)) + plt.legend() + plt.grid(True) + plt.tight_layout() + plt.savefig(experiment_plot, bbox_inches="tight", dpi=300) + # plt.show() + + # simulation desorbed rate, mapped onto experiment times + simulation_time, simulation_flux = read_csv_from_TMAP8( + simulation_file, ["time", simulation_flux_column] + ) + # at/mum^2/s -> at/m^2/s (x1e12); atomic D flux -> molecular D2 flux (/2) to match the + # RGA, which detects D2 (mass 4) and HD (mass 3) -- same convention as val-2d + simulation_flux = simulation_flux * 1e12 / 2 + + # ---- Plot 2: raw simulated desorption history ---- + plt.figure(figsize=(10, 6)) + plt.plot(simulation_time, simulation_flux, "b-", label="TMAP8 (0 dpa)") + plt.xlabel("Time (s)") + plt.ylabel(r"Desorbed flux (m$^{-2}$s$^{-1}$)") + plt.title("Unirradiated deuterium desorption: TMAP8") + plt.xlim(0, simulation_time.max()) + plt.ylim(0) + plt.ticklabel_format(axis="y", style="sci", scilimits=(0, 0)) + plt.legend() + plt.grid(True) + plt.tight_layout() + plt.savefig(simulation_plot, bbox_inches="tight", dpi=300) + # plt.show() + + mapped_simulation_flux = numerical_solution_on_experiment_input( + experiment_time, simulation_time, simulation_flux + ) + + # ---- Plot 3: simulation vs experiment with RMSPE ---- + plt.figure(figsize=(10, 6)) + plt.plot(experiment_time, experiment_flux, "ro", label="Experiment (Shimada 2010, 0 dpa)") + plt.plot(simulation_time, simulation_flux, "b-", label="TMAP8") + annotate_rmspe( + mapped_simulation_flux, experiment_flux, experiment_time.max() / 2, experiment_flux.max() / 4 + ) + plt.xlabel("Time (s)") + plt.ylabel(r"Desorbed flux (m$^{-2}$s$^{-1}$)") + plt.title("Unirradiated deuterium desorption: TMAP8 vs experiment") + plt.xlim(0, experiment_time.max()) + plt.ylim(0) + plt.ticklabel_format(axis="y", style="sci", scilimits=(0, 0)) + plt.legend() + plt.grid(True) + plt.tight_layout() + plt.savefig(comparison_plot, bbox_inches="tight", dpi=300) + # plt.show() + +# =========================== TMAP8 simulation data extraction ========================== # + csv_folder = "val-2l_out.csv" simulation_TMAP8_data = pd.read_csv(csv_folder) simulation_time_TMAP8 = simulation_TMAP8_data["time"] -# simulation_recom_flux_left_TMAP8 = simulation_TMAP8_data[ - # "scaled_recombination_flux_left" -# ] -# simulation_recom_flux_right_TMAP8 = simulation_TMAP8_data[ - # "scaled_recombination_flux_right" -# ] - -### Conservation of Mass ### -time_integrated_flux_difference = simulation_TMAP8_data['time_integrated_desorbed_flux_difference'] -total_deuterium_retention = simulation_TMAP8_data['total_deuterium_retention'] -# Measure and Plot Conservation of Mass -plt.figure(figsize=(10, 6)) -plt.plot(simulation_time_TMAP8, time_integrated_flux_difference, label = 'Time-Accumulated Boundary Flux') -plt.plot(simulation_time_TMAP8,total_deuterium_retention, label = 'Total Concentration in Tungsten') -RMSE = np.sqrt(np.mean((total_deuterium_retention-time_integrated_flux_difference)**2) ) -RMSPE = RMSE*100/np.mean(total_deuterium_retention) -print(f'RMSPE = %.2f '%RMSPE+'%') -plt.text(60,0.02, 'RMSPE = %.2f '%RMSPE+'%',fontweight='bold') -plt.xlabel('Time (s)') -plt.ylabel(r'atom/$\mu m^2$') -plt.title(f'Conservation of Mass') -plt.xlim(0,simulation_time_TMAP8.max()) -plt.ylim(0) -plt.legend() -plt.grid(True) -plt.tight_layout() -plt.show() - -difference = abs(time_integrated_flux_difference-total_deuterium_retention) -plt.figure(figsize=(10, 6)) -plt.plot(simulation_time_TMAP8,difference) -plt.xlabel('Time (s)') -plt.ylabel(r'atom/$\mu m^2$') -plt.title(f'Conservation of Mass Difference') -plt.xlim(0,simulation_time_TMAP8.max()) -plt.grid(True) -plt.tight_layout() -plt.show() -# Read experiment data -# if "/tmap8/doc/" in script_folder.lower(): # if in documentation folder -# csv_folder = "../../../../test/tests/val-2l/gold/experiment_data_paper.csv" -# else: # if in test folder -# csv_folder = "./gold/experiment_data_paper.csv" -# experiment_TMAP4_data = pd.read_csv(csv_folder) -# experiment_time_TMAP4 = experiment_TMAP4_data["time (s)"] -# experiment_flux_TMAP4 = experiment_TMAP4_data["permeation flux (atom/m^2/s)"] +### Conservation of Mass (replicating val-2k) ### +# val-2k computes the conservation residual in MOOSE (deuterium_mass_conservation_residual = +# inventory_change + released), then in Python normalizes it by the fixed initial inventory M(0) and +# plots the relative residual over time. We follow the same recipe here. M(0) is read from the t=0 row +# of total_deuterium_retention, which runs on INITIAL (cf. val-2k reading +# deuterium_inventory_in_sample_physical.iloc[0]). +total_deuterium_retention = simulation_TMAP8_data['total_deuterium_retention'] +temperature_history = simulation_TMAP8_data['temperature'] +mass_conservation_residual = simulation_TMAP8_data['deuterium_mass_conservation_residual'] +initial_inventory = total_deuterium_retention.iloc[0] +relative_mass_conservation_residual = mass_conservation_residual / initial_inventory + +# --- Total deuterium inventory with temperature history (cf. val-2k Fig. 8 / comparison_val-2k.py +# Stage 5) --- Built from a list of (label, values, color) contributions stacked with fill_between, so +# trapped-inventory series can be appended here once traps are added; for now mobile D is the only +# contribution and equals the total. +inventory_series = [ + ("Mobile D", total_deuterium_retention, plt.get_cmap("viridis")(0.95)), +] + +fig, ax = plt.subplots(figsize=(6.5, 5.5)) +inventory_bottom = np.zeros_like(total_deuterium_retention) +legend_patches = [] +for label, values, color in inventory_series: + ax.fill_between(simulation_time_TMAP8, inventory_bottom, inventory_bottom + values, + color=color, alpha=0.3) + ax.plot(simulation_time_TMAP8, inventory_bottom + values, color=color, linewidth=1.0) + inventory_bottom = inventory_bottom + values + legend_patches.append(Patch(color=color, alpha=0.5, label=label)) + +total_inventory = inventory_bottom +total_handle = ax.plot(simulation_time_TMAP8, total_inventory, color="tab:green", linewidth=1.5, + label="Total D inventory")[0] + +ax_temperature = ax.twinx() +temperature_handle = ax_temperature.plot(simulation_time_TMAP8, temperature_history, linestyle="-", + color="k", linewidth=1.5, label="TMAP8 temperature history")[0] + +ax.set_xlabel("Time (s)") +ax.set_ylabel(r"Deuterium inventory (atoms/$\mu m^2$)") +ax.set_xlim(0, simulation_time_TMAP8.max()) +ax.set_ylim(bottom=0) +ax.grid(visible=True, which="major", color="0.65", linestyle="--", alpha=0.3) +ax_temperature.set_ylabel("Temperature (K)") +ax.legend(handles=[total_handle, temperature_handle] + legend_patches[::-1], loc="lower right") +ax.minorticks_on() +plt.savefig("val-2l_inventory.png", bbox_inches="tight", dpi=300) +# plt.show() +plt.close(fig) + +# --- Relative deuterium mass-balance residual over time (cf. comparison_val-2k.py Stage 6) --- +fig, ax = plt.subplots(figsize=(6.5, 4.8)) +ax.plot(simulation_time_TMAP8, relative_mass_conservation_residual, color="tab:blue", linewidth=1.8) +ax.axhline(0.0, color="0.35", linewidth=1.0, linestyle="--") +ax.set_xlabel("Time (s)") +ax.set_ylabel("Deuterium mass-balance residual / initial inventory (-)") +ax.set_xlim(0, simulation_time_TMAP8.max()) +ax.ticklabel_format(axis="y", style="sci", scilimits=(0, 0)) +ax.grid(visible=True, which="major", color="0.65", linestyle="--", alpha=0.3) +ax.minorticks_on() +plt.savefig("val-2l_mass_conservation.png", bbox_inches="tight", dpi=300) +# plt.show() +plt.close(fig) TMAP8_file_base = "val-2l_comparison" -############################ recombination flux - atom/m$^2$/s ############################ -# fig = plt.figure(figsize=[6.5, 5.5]) -# gs = gridspec.GridSpec(1, 1) -# ax = fig.add_subplot(gs[0]) - -# ax.plot( -# simulation_time_TMAP8 / 3600, -# simulation_recom_flux_right_TMAP8, -# linestyle="-", -# label=r"TMAP8", -# c="tab:gray", -# ) -# ax.plot( -# experiment_time_TMAP4 / 3600, -# experiment_flux_TMAP4, -# linestyle="--", -# label=r"Experiment", -# c="k", -# ) - -# ax.set_xlabel("Time (hr)") -# ax.set_ylabel("Deuterium flux (atom/m$^2$/s)") -# ax.legend(loc="best") -# ax.set_ylim(bottom=0) -# ax.set_xlim(left=-0.1, right=2e4 / 3600) -# plt.grid(visible=True, which="major", color="0.65", linestyle="--", alpha=0.3) -# tmap_flux_for_rmspe = numerical_solution_on_experiment_input( -# experiment_time_TMAP4, simulation_time_TMAP8, simulation_recom_flux_right_TMAP8 -# ) -# RMSE = np.sqrt(np.mean((tmap_flux_for_rmspe - experiment_flux_TMAP4) ** 2)) -# RMSPE = RMSE * 100 / np.mean(experiment_flux_TMAP4) -# ax.text(1e4 / 3600.0, 40e15, "RMSPE = %.2f " % RMSPE + "%", fontweight="bold") -# ax.minorticks_on() -# ax.ticklabel_format(axis="y", style="sci", scilimits=(15, 15)) -# plt.savefig(f"{TMAP8_file_base}.png", bbox_inches="tight", dpi=300) -# plt.close(fig) - - -############################ implantation - atom/m$^2$/s ############################ -# Use VPP to pull this from MOOSE simulation??? - -# Parameters from val-2l.i converted to µm -depth_um = 2.64e-9 * 1e6 # ${units 2.64e-9 m -> mum} -width_um = 3.58e-9 * 1e6 # ${units 3.58e-9 m -> mum} -flux_um = 5e21 * 1e-12 # ${units 5e21 at/m^2/s -> at/mum^2/s} - -plot_source_function( - depth=depth_um, - width=width_um, - flux=flux_um, - filename="val-2l_comparison_normal_distribution.png", -) + +############################ diffusivity vs temperature ############################ +# D(T) over the simulated TDS ramp, read from the temperature/diffusivity postprocessors +plot_diffusivity_vs_temperature() + +############################ desorption: experiment + TMAP8 comparison ############################ +# Shimada 2010, unirradiated / 0 dpa (unirradiated_data.csv) +plot_unirradiated_desorption() diff --git a/test/tests/val-2l/subplots_animation.py b/test/tests/val-2l/subplots_animation.py index 0b12ebb84..490054fda 100644 --- a/test/tests/val-2l/subplots_animation.py +++ b/test/tests/val-2l/subplots_animation.py @@ -7,80 +7,81 @@ script_folder = os.path.dirname(__file__) os.chdir(script_folder) -# Filter out empty files — MOOSE writes a header-only file for the INITIAL step -all_files = sorted(glob.glob("concentration_profile/val-2k_out_concentration_profile_*.csv")) -profile_files = [ - f for f in all_files - if pd.read_csv(f, skipinitialspace=True).shape[0] > 0 -] -num_timesteps = len(profile_files) - -if num_timesteps == 0: - raise FileNotFoundError( - "No non-empty concentration profile CSV files found. " - "Run the simulation with VectorPostprocessors enabled." - ) - -global_data = pd.read_csv("val-2k_out.csv") -times = global_data["time"].values - -near_surface_limit_um = 1.0 # μm shown in lower subplot - -# Pre-scan non-empty files for fixed axis limits across all frames -c_max = 0.0 -for f in profile_files: +# LineValueSampler output lives in a directory named after the VectorPostprocessor +# (val-2l.i: [VectorPostprocessors]/deuterium_mobile_concentration_profile). +profile_files = sorted(glob.glob( + "deuterium_mobile_concentration_profile/" + "val-2l_out_deuterium_mobile_concentration_profile_*.csv" +)) +near_surface_limit_um = 20.0 # depth (um) shown in the lower zoom subplot +frame_stride = 5 # show every Nth timestep — keeps the movie fast to encode and compact + +# Time of each profile: file index i aligns with row i of the global CSV +# (both include the INITIAL step at t = 0). +times = pd.read_csv("val-2l_out.csv")["time"].values + +# Read each kept profile exactly once and cache its arrays, so the rest of the +# script (axis limits + every animation frame) reuses the data instead of +# re-parsing the CSVs. MOOSE writes a header-only file for the INITIAL step, so +# skip empties; subsample by frame_stride to avoid reading files we won't show. +frames = [] +for i, f in enumerate(profile_files): + if i >= len(times) or i % frame_stride != 0: + continue df = pd.read_csv(f, skipinitialspace=True) - c_max = max(c_max, df["concentration"].max()) -c_max *= 1.05 + if df.shape[0] == 0: + continue + frames.append((df["x"].values, df["deuterium_mobile_concentration"].values, times[i])) +if not frames: + raise FileNotFoundError("No non-empty concentration profile CSV files found.") -x_max_um = pd.read_csv(profile_files[0], skipinitialspace=True)["x"].max() +# Fixed axis limits across all frames (computed from the cached arrays). +c_max = max(c.max() for _, c, _ in frames) * 1.05 +x_max_um = frames[0][0].max() fig, (ax1, ax2) = plt.subplots(2, 1, figsize=(10, 8), constrained_layout=True) +# Build the line artists and static styling ONCE. The animation then only updates +# each line's data per frame instead of clearing and re-styling both axes. +# Markers sit on each mesh node (the NodalValueSampler points), so they reveal the +# graded element layout: dense at the surface, sparse in the bulk. +lines = [] +for ax, xlim, color in ((ax1, x_max_um, "steelblue"), + (ax2, near_surface_limit_um, "darkorange")): + (line,) = ax.plot([], [], color=color, linewidth=1.5, + marker="o", markersize=4, markerfacecolor="white", + markeredgecolor=color, markeredgewidth=1.0) + ax.set_xlim(0, xlim) + ax.set_ylim(0, c_max) + ax.set_xlabel(r"Depth ($\mu$m)") + ax.set_ylabel(r"Concentration (at/$\mu$m$^3$)") + ax.grid(True) + lines.append((line, xlim)) +ax2.set_title(f"Near-surface (0 – {near_surface_limit_um:g} $\\mu$m)") +title = ax1.set_title("") -def animate(frame): - ax1.clear() - ax2.clear() - - df = pd.read_csv(profile_files[frame], skipinitialspace=True) - x = df["x"].values # μm - c = df["concentration"].values # at/μm³ - - time_s = times[frame] if frame < len(times) else times[-1] - - # Full-domain profile - ax1.plot(x, c, color="steelblue", linewidth=1.5) - ax1.set_xlim(0, x_max_um) - ax1.set_ylim(0, c_max) - ax1.set_xlabel(r"Depth ($\mu$m)") - ax1.set_ylabel(r"Concentration (at/$\mu$m$^3$)") - ax1.set_title(f"Deuterium in Tungsten — t = {time_s:.2f} s") - ax1.grid(True) - # Near-surface zoom - mask = x <= near_surface_limit_um - ax2.plot(x[mask], c[mask], color="darkorange", linewidth=1.5) - ax2.set_xlim(0, near_surface_limit_um) - ax2.set_ylim(0, c_max) - ax2.set_xlabel(r"Depth ($\mu$m)") - ax2.set_ylabel(r"Concentration (at/$\mu$m$^3$)") - ax2.set_title(f"Near-surface (0 – {near_surface_limit_um} $\\mu$m)") - ax2.grid(True) - - return ax1, ax2 +def animate(frame): + x, c, t = frames[frame] + artists = [] + for line, xlim in lines: + mask = x <= xlim + line.set_data(x[mask], c[mask]) + artists.append(line) + title.set_text(f"Deuterium in Tungsten — t = {t:7.1f} s") + artists.append(title) + return artists -ani = animation.FuncAnimation( - fig, animate, frames=num_timesteps, interval=100, blit=False -) +ani = animation.FuncAnimation(fig, animate, frames=len(frames), interval=100, blit=True) # Use ffmpeg if available, otherwise fall back to Pillow (gif) if animation.writers.is_available("ffmpeg"): - output_file = "val-2k_concentration_animation.mp4" + output_file = "val-2l_concentration_animation.mp4" ani.save(output_file, writer="ffmpeg", fps=10) else: - output_file = "val-2k_concentration_animation.gif" + output_file = "val-2l_concentration_animation.gif" ani.save(output_file, writer="pillow", fps=10) plt.close(fig) -print(f"Saved {output_file} ({num_timesteps} frames)") +print(f"Saved {output_file} ({len(frames)} frames)") diff --git a/test/tests/val-2l/val-2l.i b/test/tests/val-2l/val-2l.i index b997c2dbb..bf4e3bd89 100644 --- a/test/tests/val-2l/val-2l.i +++ b/test/tests/val-2l/val-2l.i @@ -3,73 +3,69 @@ # !include val-2l.params # General parameters -kB = '${units 1.380649e-23 J/K}' # Boltzmann constant (from PhysicalConstants.h - https://physics.nist.gov/cgi-bin/cuu/Value?r) +kB = '${units 1.380649e-23 J/K}' # Boltzmann constant # Mesh and solver controls -nx_scale = 5 # mesh refinement multiplier (see [Mesh]); increase for convergence studies +simulation_time = '${units 2 h -> s}' # 2 h TDS with temperature ramp +nx_scale = 5 +dt_start = '${units 1 s}' dt_max = '${units 4 s}' -simulation_time = '${units 0.5 h -> s}' # 2 h plasma implantation + temperature ramp +dt_min = '${units 1e-6 s}' # Geometry tungsten_thickness = '${units 0.2 mm -> mum}' # Tungsten disc thickness, Shimada et al. 2010 (p. S667, Section 2.1) -# near_surface_length = '${units 1 mum}' -# bulk_material_length = '${units 6 mum}' -# deep_material_length = '${fparse total_length - bulk_material_length - near_surface_length}' -# Diffusion parameters -# Temperature-dependent deuterium diffusivity from Shimada et al. 2010 (p. S668, Section 3): D = 2.9e-7 * exp(-0.39 eV / kB / T) (m^2/s) +# Gaussian-hill initial condition (diagnostic profile; not from Shimada et al. 2010). +gaussian_amplitude = '${units 1e26 at/m^3 -> at/mum^3}' # Peak concentration at the center (= 1 at/mum^3) +gaussian_center = '${fparse ${tungsten_thickness} / 5}' # Hill center (20 mum) +gaussian_sigma = '${fparse ${tungsten_thickness} / 20}' # Hill standard deviation (10 mum) + +# Temperature-dependent deuterium diffusivity used by Shimada et al. 2010 (p. S668, Section 3) diffusivity_coefficient = '${units 2.9e-7 m^2/s -> mum^2/s}' # D0 prefactor, Shimada et al. 2010 (p. S668) E_D = '${units 0.39 eV -> J}' # Diffusion activation energy, Shimada et al. 2010 (p. S668) -# Recombination parameters -# recombination_parameter = '${units ${fparse 3.2e-15*exp(-1.16)} m^4/at/s -> mum^4/at/s}' # Shimada et al. 2010 (p. S668), for recombination BC option +# Recombination parameters: Shimada et al. 2010 (p. S668) +# recombination_parameter = '${units ${fparse 3.2e-15*exp(-1.16)} m^4/at/s -> mum^4/at/s}' # recombination_parameter_enclos2 = '${units 2e-31 m^4/at/s -> mum^4/at/s}' # recombination_coefficient_parameter_enclos1_TMAP4 = '${units 1e-27 m^4/at/s -> mum^4/at/s}' -# Implantation source parameters -# NOTE: the implantation depth and width are NOT reported in Shimada et al. 2010. Pulled from val-2i -width = '${units 3.58e-9 m -> mum}' # implantation profile standard deviation -depth = '${units 2.64e-9 m -> mum}' # implantation mean depth -flux_high = '${units 5e21 at/m^2/s -> at/mum^2/s}' # Incident D ion flux, Shimada et al. 2010 (p. S667, Section 2.3) -TPE_hold_time = '${units 2 h -> s}' # Deuterium plasma implantation for 2 h, Shimada et al. 2010 (p. S667, Section 2.3 & Fig. 1) - # Thermal parameters -# Plasma exposure is held at 473 K; after transfer (Section 2.4) the TDS ramp runs from room -# temperature to 1173 K at 10 K/min, per Shimada et al. 2010 (p. S668, Section 2.3 & Fig. 1) -temperature_implantation = '${units 473 K}' # Plasma exposure temperature, Shimada et al. 2010 (p. S668, Section 2.3 & Fig. 1) temperature_tds_start = '${units 300 K}' # TDS ramp start (room temperature), Shimada et al. 2010 (p. S668, Figs. 2-4) -temperature_high = '${units 1173 K}' # TDS ramp peak temperature, Shimada et al. 2010 (p. S668, Fig. 1) +temperature_tds_end = '${units 1173 K}' # TDS ramp peak temperature, Shimada et al. 2010 (p. S668, Fig. 1) temperature_rate = '${units ${fparse 10 / 60} K/s}' # TDS ramp rate of 10 K/min, Shimada et al. 2010 (p. S668, Fig. 1) [Variables] - # Concentration of deuterium in tungsten (atoms/mum^3) - [concentration] + [deuterium_mobile_concentration] + [] +[] + +[ICs] + # Gaussian hill centered on the sample midplane (diagnostic, see header). + [deuterium_mobile_concentration_ic] + type = FunctionIC + variable = deuterium_mobile_concentration + function = gaussian_hill_initial_condition [] [] [Mesh] - # coord_type = 'RZ' # Look into how mesh axis and axis of symmetry being same effects postprocessor calculations - # rz_coord_axis = X # Specifies x axis is axis of symmetry of y axis is radial direction - # Graded mesh: sub-nm elements near the upstream surface to resolve the implantation Gaussian - # (mean 2.64 nm, sigma 3.58 nm), coarsening into the bulk where the concentration is ~ 0. - # Region lengths (near surface -> bulk): 20 nm, 80 nm, 0.9 um, 9 um, remainder to tungsten_thickness. - [cartesian] + + [temp_mesh] type = CartesianMeshGenerator dim = 1 - dx = '${units 2e-8 m -> mum} - ${units 8e-8 m -> mum} - ${units 9e-7 m -> mum} - ${units 9e-6 m -> mum} - ${fparse ${tungsten_thickness} - ${units 1e-5 m -> mum}}' - ix = '${fparse 8 * nx_scale} - ${fparse 4 * nx_scale} - ${fparse 4 * nx_scale} - ${fparse 4 * nx_scale} - ${fparse 4 * nx_scale}' + # Graded mesh: fine at the upstream surface, coarse in the bulk. The last block fills the + # remainder of the disc so the total thickness equals tungsten_thickness (0.2 mm). + dx = '${fparse 5 * ${units 4e-9 m -> mum}} ${units 1e-8 m -> mum} ${units 1e-7 m -> mum} + ${units 1e-6 m -> mum} ${units 1e-5 m -> mum} + ${fparse ${tungsten_thickness} - 5 * ${units 4e-9 m -> mum} - ${units 1e-8 m -> mum} + - ${units 1e-7 m -> mum} - ${units 1e-6 m -> mum} - ${units 1e-5 m -> mum}}' + ix = '${fparse 5 * ${nx_scale}} ${nx_scale} ${nx_scale} + ${nx_scale} ${nx_scale} ${fparse 10 * ${nx_scale}}' [] - [tungsten_disc] # Cross section through thickness of disk. Can scale measurements by 9*pi mm for full sample metrics + + [tungsten_disc] type = RenameBoundaryGenerator - input = cartesian + input = temp_mesh old_boundary = 'left right' new_boundary = 'upstream downstream' [] @@ -86,45 +82,15 @@ temperature_rate = '${units ${fparse 10 / 60} K/s}' # TDS ramp rate of 10 K/min, [Kernels] [diffusion] type = ADMatDiffusion - variable = concentration - diffusivity = diffusivity_D + variable = deuterium_mobile_concentration + diffusivity = diffusivity_mat extra_vector_tags = 'ref' [] [time_diffusion] type = ADTimeDerivative - variable = concentration + variable = deuterium_mobile_concentration extra_vector_tags = 'ref' [] - [source] - type = ADBodyForce - variable = concentration - function = concentration_source_norm_func - extra_vector_tags = 'ref' - [] -[] - -[AuxVariables] - # Source term profile used for postprocessing - [concentration_source] - [] - # # Time-dependent recombination coefficient on the upstream side - # [recombination_TMAP4] - # [] -[] - -[AuxKernels] - [concentration_source_aux] - type = FunctionAux - variable = concentration_source - function = concentration_source_norm_func - execute_on = 'INITIAL TIMESTEP_END' - [] - # [recombination_aux_TMAP4] - # type = FunctionAux - # variable = recombination_TMAP4 - # function = '${recombination_coefficient_parameter_enclos1_TMAP4}' - # execute_on = 'INITIAL TIMESTEP_END' - # [] [] [BCs] @@ -133,204 +99,138 @@ temperature_rate = '${units ${fparse 10 / 60} K/s}' # TDS ramp rate of 10 K/min, type = ADDirichletBC boundary = upstream value = 0 - variable = concentration + variable = deuterium_mobile_concentration [] [right] type = ADDirichletBC boundary = downstream value = 0 - variable = concentration + variable = deuterium_mobile_concentration [] - - # Flux balance from recombination on upstream surface (left) - # [left] - # type = ADMatNeumannBC - # variable = concentration - # boundary = upstream - # value = 1 - # boundary_material = flux_on_upstream - # [] - # # Flux balance from recombination on downstream surface (right) - # [right] - # type = ADMatNeumannBC - # variable = concentration - # boundary = downstream - # value = 1 - # boundary_material = flux_on_downstream - # [] [] [Materials] # Temperature-dependent deuterium diffusivity in tungsten - [diffusivity_D] + [diffusivity_mat] type = ADDerivativeParsedMaterial - property_name = 'diffusivity_D' + property_name = 'diffusivity_mat' functor_names = 'Temperature_function' functor_symbols = 'temperature' expression = '${diffusivity_coefficient} * exp(- ${E_D} / ${kB} / temperature)' - output_properties = 'diffusivity_D' + output_properties = 'diffusivity_mat' outputs = 'exodus' [] - # # Recombination-driven flux on upstream boundary (left) - # [flux_on_upstream] - # type = ADDerivativeParsedMaterial - # coupled_variables = 'concentration' - # property_name = 'flux_on_upstream' - # functor_names = 'Kr_upstream_func' - # functor_symbols = 'Kr_upstream_func' - # expression = '- 2 * Kr_upstream_func * concentration ^ 2' - # [] - # # # Recombination-driven flux on downstream boundary (right) - # [flux_on_downstream] - # type = ADDerivativeParsedMaterial - # coupled_variables = 'concentration' - # property_name = 'flux_on_downstream' - # expression = '- 2 * ${recombination_parameter_enclos2} * concentration ^ 2' - # [] [] [Functions] - # Temperature history (K): hold at the implantation temperature while the beam is on, then an - # instantaneous cooldown to room temperature at the end of implantation (approximating the air - # transfer in Section 2.4), followed by a linear TDS ramp to the peak temperature and a hold - [Temperature_function] - type = ParsedFunction - expression = 'if(t<${TPE_hold_time}, ${temperature_implantation}, - if(t<${TPE_hold_time} + (${temperature_high} - ${temperature_tds_start}) / - ${temperature_rate}, ${temperature_tds_start} + ${temperature_rate} * (t - ${TPE_hold_time}), - ${temperature_high}))' - [] - # Upstream recombination coefficient (time-dependent exponential) in microns^4/at/s - # [Kr_upstream_func] - # type = ParsedFunction - # expression = '${recombination_coefficient_parameter_enclos1_TMAP4} * (1 - 0.9999 * exp(-6e-5 * t))' - # [] - # Beam flux schedule applied to upstream surface (atoms/mum^2/s) - [surface_flux_func] + # Gaussian hill, peak gaussian_amplitude at gaussian_center, standard deviation gaussian_sigma: + # c(x) = A * exp(-(x - x0)^2 / (2 sigma^2)) + [gaussian_hill_initial_condition] type = ParsedFunction - expression = 'if(t<${TPE_hold_time}, ${flux_high}, 0)' - [] - # Normalized implantation distribution across tungsten thickness - [source_distribution] # (-) - type = ParsedFunction - # expression = '1.5 / (${width} * sqrt(2 * pi)) * exp(-0.5 * ((x - ${depth}) / ${width})^2)' - expression = '1 / ( ${width} * sqrt(2 * pi) ) * exp(-0.5 * ((x - ${depth}) / ${width} ) ^ 2)' - [] - # Spatial-temporal source term from beam flux and implantation profile (atoms/microns^2/s) - [concentration_source_norm_func] # atoms/microns^2/s - type = ParsedFunction - symbol_names = 'source_distribution surface_flux_func' - symbol_values = 'source_distribution surface_flux_func' - expression = 'source_distribution * surface_flux_func' - # expression = 1e-5 + expression = '${gaussian_amplitude} * exp(-(x - ${gaussian_center})^2 / (2 * ${gaussian_sigma}^2))' [] - # Adaptive timestepper ceiling - [max_dt_size_func] # s + # Linear TDS ramp from temperature_tds_start to temperature_tds_end and hold until end of simulation + [Temperature_function] type = ParsedFunction - expression = ${dt_max} + expression = 'if(t<(${temperature_tds_end} - ${temperature_tds_start}) / + ${temperature_rate}, ${temperature_tds_start} + ${temperature_rate} * t, + ${temperature_tds_end})' [] [] [Postprocessors] - ### Conservation of Mass ### + ### Temperature ramp and resulting diffusivity (for post-processing/plots) ### + [temperature] # K + type = FunctionValuePostprocessor + function = Temperature_function + outputs = csv + [] + + [diffusivity_pp] # mum^2/s; uniform in space, depends only on temperature + type = ADElementAverageMaterialProperty + mat_prop = diffusivity_mat + outputs = csv + [] + + ### Conservation of Mass (replicates val-2k_base.i: residual computed in MOOSE) ### + + # Total deuterium inventory currently in the sample, M(t) (cf. val-2k deuterium_inventory_in_sample). + # Runs on INITIAL so its t=0 row is the initial inventory M(0), which the comparison script reads to + # normalize the residual. [total_deuterium_retention] # atoms / mum^2 type = ElementIntegralVariablePostprocessor - variable = concentration + variable = deuterium_mobile_concentration + execute_on = 'INITIAL TIMESTEP_END' outputs = csv [] + # Desorption flux through each face (upstream_flux is also used for the experimental desorption + # comparison). With c = 0 Dirichlet faces and c > 0 inside, -D grad(c).n is positive (outward) on + # each face, so the two are the per-face desorption rates. [upstream_flux] type = ADSideDiffusiveFluxIntegral boundary = 'upstream' - variable = concentration - diffusivity = diffusivity_D + variable = deuterium_mobile_concentration + diffusivity = diffusivity_mat + execute_on = 'INITIAL TIMESTEP_END' outputs = csv [] [downstream_flux] type = ADSideDiffusiveFluxIntegral boundary = 'downstream' - variable = concentration - diffusivity = diffusivity_D - outputs = csv - [] - - [deuterium_source] # Integral of Source function gives atoms/mum^2/s - type = FunctionElementIntegral - function = concentration_source_norm_func + variable = deuterium_mobile_concentration + diffusivity = diffusivity_mat + execute_on = 'INITIAL TIMESTEP_END' outputs = csv [] - # [analytical_total_mass_source] - # type = FunctionValuePostprocessor - # function = analytical_total_mass_fun - # [] - - [flux_difference_plus_source] - type = ParsedPostprocessor - expression = 'deuterium_source - upstream_flux - downstream_flux' - pp_names = 'deuterium_source upstream_flux downstream_flux' - outputs = csv + # Total desorption rate through both faces (cf. val-2k deuterium_release_flux_total). + [deuterium_release_flux_total] # atoms / mum^2 / s + type = SumPostprocessor + values = 'upstream_flux downstream_flux' + execute_on = 'INITIAL TIMESTEP_END' + outputs = none [] - [time_integrated_desorbed_flux_difference] + # Cumulative deuterium released through both faces (time-integrated release rate), = M(0) - M(t). + [deuterium_released_physical] # atoms / mum^2 type = TimeIntegratedPostprocessor - value = flux_difference_plus_source + value = deuterium_release_flux_total time_integration_scheme = trapezoidal-rule + execute_on = 'INITIAL TIMESTEP_END' outputs = csv [] - ### Desorbed Flux on Upstream and Downstream Surfaces - - # Average flux on upstream surface (left) from recombination - # [dcdx_upstream] - # type = ADSideAverageMaterialProperty - # boundary = upstream - # property = flux_on_upstream - # outputs = none - # [] - # Output upstream recombination flux (scaled to atoms/mum^2/s) - # [scaled_recombination_flux_upstream] - # type = ScalePostprocessor - # scaling_factor = '${fparse -1 * ${units 1 m^2 -> mum^2}}' - # value = dcdx_upstream - # execute_on = 'initial nonlinear linear timestep_end' - # outputs = 'console csv exodus' - # [] - # Average flux on downstream surface (right) from recombination - # [dcdx_downstream] - # type = ADSideAverageMaterialProperty - # boundary = downstream - # property = flux_on_downstream - # outputs = none - # [] - # # Output downstream recombination flux (scaled to atoms/mum^2/s) - # [scaled_recombination_flux_downstream] - # type = ScalePostprocessor - # scaling_factor = '${fparse -1 * ${units 1 m^2 -> mum^2}}' - # value = dcdx_downstream - # execute_on = 'initial nonlinear linear timestep_end' - # outputs = 'console csv exodus' - # [] - # Limit timestep size according to beam on/off schedule - [max_time_step_size] - type = FunctionValuePostprocessor - function = max_dt_size_func - execute_on = 'initial nonlinear linear timestep_end' + # Change in domain inventory relative to the initial state, M(t) - M(0). + [deuterium_inventory_change] # atoms / mum^2 + type = ChangeOverTimePostprocessor + postprocessor = total_deuterium_retention + change_with_respect_to_initial = true + execute_on = 'INITIAL TIMESTEP_END' outputs = none [] + + # Conservation residual = (M(t) - M(0)) + released; ideally 0 at all times. The comparison script + # divides this by the initial inventory M(0) to report the relative mass-balance residual (cf. + # val-2k deuterium_mass_conservation_residual). The decomposition generalizes directly to + # trapped + mobile once traps land: sum them into total_deuterium_retention. + [deuterium_mass_conservation_residual] # atoms / mum^2 + type = ParsedPostprocessor + expression = 'deuterium_inventory_change + deuterium_released_physical' + pp_names = 'deuterium_inventory_change deuterium_released_physical' + execute_on = 'INITIAL TIMESTEP_END' + outputs = 'csv' + [] [] [VectorPostprocessors] - [concentration_profile] - type = LineValueSampler - variable = concentration - start_point = '0 0 0' - end_point = '${tungsten_thickness} 0 0' - num_points = 500 + [deuterium_mobile_concentration_profile] + type = NodalValueSampler + variable = deuterium_mobile_concentration sort_by = x execute_on = 'TIMESTEP_END' outputs = profile_csv @@ -343,11 +243,10 @@ temperature_rate = '${units ${fparse 10 / 60} K/s}' # TDS ramp rate of 10 K/min, [exodus] type = Exodus output_material_properties = true - # time_step_interval = 2 [] [profile_csv] type = CSV - file_base = 'concentration_profile/val-2l_out' + file_base = 'deuterium_mobile_concentration_profile/val-2l_out' [] [] @@ -362,17 +261,19 @@ temperature_rate = '${units ${fparse 10 / 60} K/s}' # TDS ramp rate of 10 K/min, type = Transient scheme = bdf2 solve_type = NEWTON + line_search = 'none' + nl_abs_tol = 1e-10 petsc_options_iname = '-pc_type' petsc_options_value = 'lu' end_time = ${simulation_time} automatic_scaling = true - # nl_rel_tol = 5e-7 # Borrowed from Val 2-a + dtmin = ${dt_min} + dtmax = ${dt_max} [TimeStepper] type = IterationAdaptiveDT - dt = 1.0 - optimal_iterations = 6 + dt = ${dt_start} # initial step only + optimal_iterations = 5 growth_factor = 1.1 cutback_factor_at_failure = 0.9 - timestep_limiting_postprocessor = max_time_step_size [] [] From 74747d83f2a771d5bd5c29e8507069ab9ffc2952 Mon Sep 17 00:00:00 2001 From: "Butterworth, Evan" Date: Wed, 29 Jul 2026 17:01:36 -0600 Subject: [PATCH 03/12] Added trapping with parameters from paper and val-2d as well as multiple comparison and animation script improvements (Ref. #405) --- test/tests/val-2l/comparison_val-2l.py | 137 ++++--- .../tests/val-2l/trapped_profile_animation.py | 203 ++++++++++ test/tests/val-2l/val-2l.i | 350 ++++++++++++++---- 3 files changed, 543 insertions(+), 147 deletions(-) create mode 100644 test/tests/val-2l/trapped_profile_animation.py diff --git a/test/tests/val-2l/comparison_val-2l.py b/test/tests/val-2l/comparison_val-2l.py index b74f22706..e6d3808e8 100644 --- a/test/tests/val-2l/comparison_val-2l.py +++ b/test/tests/val-2l/comparison_val-2l.py @@ -11,6 +11,8 @@ script_folder = os.path.dirname(__file__) os.chdir(script_folder) +# Must match val-2l.i: trap_per_free = ... (rescaling factor for trapped variable) +trap_per_free = 1e4 # update this if val-2l.i changes # ================================= Functions ================================ # @@ -110,35 +112,6 @@ def plot_conservation_of_mass(t, flux, mass, flux_label, title, filename): plt.savefig(filename, bbox_inches="tight", dpi=300) plt.close(fig) - -def plot_validation(t_sim, sim_data, t_exp, exp_data, ylabel, title, filename): - """Plot simulation results against SRNL experimental data with RMSPE annotation - - Args: - t_sim (float, ndarray): simulation time array in days - sim_data (float, ndarray): simulation output values - t_exp (float, ndarray): experimental time array in days - exp_data (float, ndarray): experimental measurement values - ylabel (str): y-axis label - title (str): plot title - filename (str): output PNG filename - """ - fig = plt.figure(figsize=(10, 6)) - plt.plot(t_sim, sim_data, label="Simulation") - plt.plot(t_exp, exp_data, "ro", label="Experimental Data") - mapped = numerical_solution_on_experiment_input(t_exp, t_sim, sim_data) - annotate_rmspe(mapped, exp_data, t_sim[-1] / 2, sim_data[-1] / 4) - plt.ylabel(ylabel) - plt.xlabel("Time (Days)") - plt.title(title) - plt.xlim(0) - plt.ylim(0) - plt.legend() - plt.grid(True) - plt.savefig(filename, bbox_inches="tight", dpi=300) - plt.close(fig) - - def plot_diffusivity_vs_temperature( simulation_file="val-2l_out.csv", filename="val-2l_diffusivity_vs_temperature.png", @@ -183,7 +156,7 @@ def plot_diffusivity_vs_temperature( def plot_unirradiated_desorption( experiment_file="unirradiated_data.csv", simulation_file="val-2l_out.csv", - simulation_flux_column="upstream_flux", + simulation_flux_column="deuterium_release_flux_total", experiment_plot="val-2l_experimental_desorption.png", simulation_plot="val-2l_simulated_desorption.png", comparison_plot="val-2l_comparison_desorption.png", @@ -192,23 +165,18 @@ def plot_unirradiated_desorption( Produces three figures: 1. The digitized experimental desorbed-flux history (Shimada 2010, - unirradiated / 0 dpa): time (s) versus desorbed flux (m^-2 s^-1), with - the y-axis written in scientific notation. - 2. The raw TMAP8 simulated desorbed-flux history on its own time grid: - time (s) versus desorbed flux (m^-2 s^-1). - 3. The TMAP8 simulated desorbed flux mapped onto the experimental time - points with numerical_solution_on_experiment_input, overlaid on the - experimental data and annotated with the RMSPE via annotate_rmspe. - - The paper reports an areal desorption flux in m^-2 s^-1 (Shimada 2010, - Figs. 2-4), so the 1D model's areal flux is compared directly: the face area - cancels and no pi*r^2 scaling is needed (same convention as val-2d). + unirradiated / 0 dpa): temperature (K) versus desorbed flux (m^-2 s^-1). + Experimental times are mapped to temperatures via the simulation's T(t) ramp. + 2. The raw TMAP8 simulated desorbed-flux history: temperature (K) versus + desorbed flux (m^-2 s^-1). + 3. The TMAP8 simulated desorbed flux mapped onto the experimental temperature + points, overlaid on the experimental data and annotated with the RMSPE. Args: experiment_file (str): two-column, header-less CSV of (time [s], desorbed flux [m^-2 s^-1]) - simulation_file (str): TMAP8 CSV output holding a "time" column and the - desorbed-flux column + simulation_file (str): TMAP8 CSV output holding "time", "temperature", and + the desorbed-flux column simulation_flux_column (str): name of the desorbed-flux column in simulation_file. TMAP8 reports it in at/mum^2/s; it is converted to at/m^2/s to match the experiment. @@ -220,13 +188,30 @@ def plot_unirradiated_desorption( experiment = np.loadtxt(experiment_file, delimiter=",") experiment_time, experiment_flux = experiment[:, 0], experiment[:, 1] + # simulation data: time, temperature, and desorbed flux + simulation_time, simulation_temperature, simulation_flux = read_csv_from_TMAP8( + simulation_file, ["time", "temperature", simulation_flux_column] + ) + # at/mum^2/s -> at/m^2/s (x1e12); atomic D flux -> molecular D2 flux (/2) to match the + # RGA, which detects D2 (mass 4) and HD (mass 3) -- same convention as val-2d + simulation_flux = simulation_flux * 1e12 / 2 + + # Map experimental times to temperatures using the simulation's T(t) ramp, + # then truncate to the simulation time range to avoid extrapolation. + in_sim_range = experiment_time <= simulation_time.max() + experiment_time = experiment_time[in_sim_range] + experiment_flux = experiment_flux[in_sim_range] + experiment_temperature = numerical_solution_on_experiment_input( + experiment_time, simulation_time, simulation_temperature + ) + # ---- Plot 1: experimental desorption history ---- plt.figure(figsize=(10, 6)) - plt.plot(experiment_time, experiment_flux, "ro", label="Experiment (Shimada 2010, 0 dpa)") - plt.xlabel("Time (s)") + plt.plot(experiment_temperature, experiment_flux, "ro", label="Experiment (Shimada 2010, 0 dpa)") + plt.xlabel("Temperature (K)") plt.ylabel(r"Desorbed flux (m$^{-2}$s$^{-1}$)") plt.title("Unirradiated deuterium desorption") - plt.xlim(0, experiment_time.max()) + plt.xlim(experiment_temperature.min(), experiment_temperature.max()) plt.ylim(0) plt.ticklabel_format(axis="y", style="sci", scilimits=(0, 0)) plt.legend() @@ -235,21 +220,13 @@ def plot_unirradiated_desorption( plt.savefig(experiment_plot, bbox_inches="tight", dpi=300) # plt.show() - # simulation desorbed rate, mapped onto experiment times - simulation_time, simulation_flux = read_csv_from_TMAP8( - simulation_file, ["time", simulation_flux_column] - ) - # at/mum^2/s -> at/m^2/s (x1e12); atomic D flux -> molecular D2 flux (/2) to match the - # RGA, which detects D2 (mass 4) and HD (mass 3) -- same convention as val-2d - simulation_flux = simulation_flux * 1e12 / 2 - # ---- Plot 2: raw simulated desorption history ---- plt.figure(figsize=(10, 6)) - plt.plot(simulation_time, simulation_flux, "b-", label="TMAP8 (0 dpa)") - plt.xlabel("Time (s)") + plt.plot(simulation_temperature, simulation_flux, "b-", label="TMAP8 (0 dpa)") + plt.xlabel("Temperature (K)") plt.ylabel(r"Desorbed flux (m$^{-2}$s$^{-1}$)") plt.title("Unirradiated deuterium desorption: TMAP8") - plt.xlim(0, simulation_time.max()) + plt.xlim(simulation_temperature.min(), simulation_temperature.max()) plt.ylim(0) plt.ticklabel_format(axis="y", style="sci", scilimits=(0, 0)) plt.legend() @@ -258,21 +235,33 @@ def plot_unirradiated_desorption( plt.savefig(simulation_plot, bbox_inches="tight", dpi=300) # plt.show() + # Map simulated flux onto experimental temperature points for RMSPE mapped_simulation_flux = numerical_solution_on_experiment_input( - experiment_time, simulation_time, simulation_flux + experiment_temperature, simulation_temperature, simulation_flux ) + tmin = 1000 + tmax = 2600 + rmspe_region = (experiment_time >= tmin) & (experiment_time <= tmax) # ---- Plot 3: simulation vs experiment with RMSPE ---- plt.figure(figsize=(10, 6)) - plt.plot(experiment_time, experiment_flux, "ro", label="Experiment (Shimada 2010, 0 dpa)") - plt.plot(simulation_time, simulation_flux, "b-", label="TMAP8") - annotate_rmspe( - mapped_simulation_flux, experiment_flux, experiment_time.max() / 2, experiment_flux.max() / 4 - ) - plt.xlabel("Time (s)") + plt.plot(experiment_temperature, experiment_flux, "ro", label="Experiment (Shimada 2010, 0 dpa)") + plt.plot(simulation_temperature, simulation_flux, "b-", label="TMAP8") + if rmspe_region.any(): + plt.axvline(experiment_temperature[rmspe_region].min(), color="green", linestyle="--", + linewidth=1.2, label="RMSPE region") + plt.axvline(experiment_temperature[rmspe_region].max(), color="green", linestyle="--", + linewidth=1.2) + annotate_rmspe( + mapped_simulation_flux[rmspe_region], + experiment_flux[rmspe_region], + experiment_temperature.mean(), + experiment_flux.max() / 4, + ) + plt.xlabel("Temperature (K)") plt.ylabel(r"Desorbed flux (m$^{-2}$s$^{-1}$)") plt.title("Unirradiated deuterium desorption: TMAP8 vs experiment") - plt.xlim(0, experiment_time.max()) + plt.xlim(experiment_temperature.min(), experiment_temperature.max()) plt.ylim(0) plt.ticklabel_format(axis="y", style="sci", scilimits=(0, 0)) plt.legend() @@ -299,12 +288,20 @@ def plot_unirradiated_desorption( initial_inventory = total_deuterium_retention.iloc[0] relative_mass_conservation_residual = mass_conservation_residual / initial_inventory -# --- Total deuterium inventory with temperature history (cf. val-2k Fig. 8 / comparison_val-2k.py -# Stage 5) --- Built from a list of (label, values, color) contributions stacked with fill_between, so -# trapped-inventory series can be appended here once traps are added; for now mobile D is the only -# contribution and equals the total. +# --- Read individual mobile and trapped integrals for the stacked inventory plot --- +# total_mobile_retention : physical mobile inventory (at/µm²), no scaling needed +# total_trapped_retention : MOOSE stores the *rescaled* variable, so multiply by +# trap_per_free to recover the physical trapped inventory. +total_mobile_retention = simulation_TMAP8_data["total_mobile_retention"] +total_trapped_retention = simulation_TMAP8_data["total_trapped_retention"] * trap_per_free + +# --- Total deuterium inventory with temperature history --- +# Add one entry per species to inventory_series. They are stacked bottom-up with +# fill_between, so order matters: put the largest / most stable contribution first. +# Append a new tuple here when additional trap populations are added. inventory_series = [ - ("Mobile D", total_deuterium_retention, plt.get_cmap("viridis")(0.95)), + ("Trapped D (trap 1, 1.35 eV)", total_trapped_retention, plt.get_cmap("viridis")(0.45)), + ("Mobile D", total_mobile_retention, plt.get_cmap("viridis")(0.95)), ] fig, ax = plt.subplots(figsize=(6.5, 5.5)) diff --git a/test/tests/val-2l/trapped_profile_animation.py b/test/tests/val-2l/trapped_profile_animation.py new file mode 100644 index 000000000..8bc85a280 --- /dev/null +++ b/test/tests/val-2l/trapped_profile_animation.py @@ -0,0 +1,203 @@ +""" +animate_profiles_val-2l.py +Animates mobile and trapped deuterium concentration profiles over the TDS ramp. + +Layout (2 x 2): + [0,0] Mobile – whole domain (0–200 µm) + [0,1] Mobile – near surface (0–1 µm) + [1,0] Trapped – bulk & near surface (0–7 µm) + [1,1] Trapped – near surface (0–1 µm) + +A temperature-ramp axes sits above the panels; a marker tracks the current frame. +""" + +import os +import glob +import argparse +import numpy as np +import pandas as pd +import matplotlib.pyplot as plt +import matplotlib.animation as animation + +# ── Must match val-2l.i ───────────────────────────────────────────────────── # +TRAP_PER_FREE = 1 +FRAME_STRIDE = 2 +TRAP_BOUNDARY = 0.7 # µm: spatial extent of 1.35 eV trap (TMAP fit A) + +# ── File paths ────────────────────────────────────────────────────────────── # +MOBILE_DIR = "deuterium_mobile_concentration_profile" +TRAPPED_DIR = "deuterium_trapped_concentration_profile" +MOBILE_COL = "mobile" +TRAPPED_COL = "trapped_1" +MAIN_CSV = "val-2l_out.csv" +OUTPUT_FILE = "val-2l_profile_animation.gif" + +# ── Panel definitions ─────────────────────────────────────────────────────── # +# Each entry: (row, col, species, label, x_min, x_max) +PANELS = [ + (0, 0, "mobile", "Mobile – whole domain", 0.0, 200.0), + (0, 1, "mobile", "Mobile – near surface", 0.0, 1.0), + (1, 0, "trapped", "Trapped – bulk & near surface", 0.0, 7.0), + (1, 1, "trapped", "Trapped – near surface", 0.0, 1.0), +] + +COLOR_MOBILE = "steelblue" +COLOR_TRAPPED = "darkorange" +COLOR_TRAP_BOUNDARY = "dimgray" + + +# ── Helpers ───────────────────────────────────────────────────────────────── # + +def detect_value_column(df, hint): + cols = list(df.columns) + if hint in cols: + return hint + matches = [c for c in cols if hint in c] + if matches: + return matches[0] + candidates = [c for c in cols if c not in ("x", "id")] + if candidates: + print(f" Warning: '{hint}' not found; using '{candidates[0]}'.") + return candidates[0] + raise KeyError(f"Cannot find value column in {cols}; expected '{hint}'.") + + +def load_profile_series(directory, col_hint, scale=1.0): + pattern = os.path.join(directory, "val-2l_out_*.csv") + files = sorted(glob.glob(pattern)) + if not files: + raise FileNotFoundError( + f"No profile CSVs found in '{directory}'.\n" + "Check that the VectorPostprocessor output block is active in val-2l.i." + ) + xs, cs = [], [] + col_name = None + for f in files: + df = pd.read_csv(f, skipinitialspace=True).sort_values("x") + if col_name is None: + col_name = detect_value_column(df, col_hint) + xs.append(df["x"].values) + cs.append(df[col_name].values * scale) + return xs, cs + + +def global_ylim(c_series, x_series, x_min, x_max, pad=0.08): + masked = [c[(x >= x_min) & (x <= x_max)] for c, x in zip(c_series, x_series)] + g_max = max((v.max() for v in masked if v.size), default=0.0) + return 0.0, max(g_max * (1.0 + pad), 1e-30) + + +def region_mask(x, x_min, x_max): + return (x >= x_min) & (x <= x_max) + + +# ── Main ──────────────────────────────────────────────────────────────────── # + +def build_animation(show=False): + # ── Scalar CSV for time / temperature ────────────────────────────────── # + main_df = pd.read_csv(MAIN_CSV) + all_times = main_df["time"].values + all_temps = main_df["temperature"].values + + time_offset = 1 if all_times[0] == 0.0 else 0 + + def frame_metadata(i): + row = min(i + time_offset, len(all_times) - 1) + return all_times[row], all_temps[row] + + # ── Load profile series ───────────────────────────────────────────────── # + mob_xs, mob_cs = load_profile_series(MOBILE_DIR, MOBILE_COL, scale=1.0) + trp_xs, trp_cs = load_profile_series(TRAPPED_DIR, TRAPPED_COL, scale=TRAP_PER_FREE) + n_frames = min(len(mob_xs), len(trp_xs)) + frame_indices = range(0, n_frames, FRAME_STRIDE) + + series = { + "mobile": (mob_xs, mob_cs, COLOR_MOBILE), + "trapped": (trp_xs, trp_cs, COLOR_TRAPPED), + } + + # ── Figure: temperature ramp on top, 2x2 panels below ────────────────── # + fig = plt.figure(figsize=(12, 9)) + # Reserve top 15% for temperature axes, bottom 85% for the 2x2 grid + temp_ax = fig.add_axes([0.10, 0.88, 0.82, 0.09]) + gs = fig.add_gridspec(2, 2, left=0.10, right=0.92, + top=0.82, bottom=0.07, + hspace=0.45, wspace=0.35) + axes = gs.subplots() + + # ── Temperature ramp axes ─────────────────────────────────────────────── # + temp_ax.plot(all_times, all_temps, color="firebrick", linewidth=1.5) + temp_marker, = temp_ax.plot(all_times[0], all_temps[0], "o", + color="firebrick", markersize=6, zorder=5) + temp_ax.set_xlim(0, all_times[-1]) + temp_ax.set_ylim(all_temps.min() * 0.95, all_temps.max() * 1.05) + temp_ax.set_xlabel("Time (s)", fontsize=8) + temp_ax.set_ylabel("T (K)", fontsize=8) + temp_ax.tick_params(labelsize=7) + temp_ax.grid(True, linestyle="--", alpha=0.35) + + # ── Concentration panels ──────────────────────────────────────────────── # + lines = {} + + for row, col, species, label, xlo, xhi in PANELS: + xs, cs, color = series[species] + ax = axes[row, col] + + ylim = global_ylim(cs, xs, xlo, xhi) + mask = region_mask(xs[0], xlo, xhi) + (ln,) = ax.plot(xs[0][mask], cs[0][mask], color=color, linewidth=1.6) + lines[(row, col)] = ln + + ax.set_xlim(xlo, xhi) + ax.set_ylim(*ylim) + ax.set_title(label, fontsize=9, pad=4) + ax.set_xlabel("Position (µm)", fontsize=8) + ax.set_ylabel("Concentration (at·µm⁻³)", fontsize=8) + ax.grid(True, linestyle="--", alpha=0.35) + ax.ticklabel_format(axis="y", style="sci", scilimits=(0, 0)) + + if xlo <= TRAP_BOUNDARY <= xhi: + ax.axvline(TRAP_BOUNDARY, color=COLOR_TRAP_BOUNDARY, + linestyle=":", linewidth=1.1, + label=f"Trap edge ({TRAP_BOUNDARY} µm)") + ax.legend(fontsize=7, loc="upper right") + + + + # ── Animation update ──────────────────────────────────────────────────── # + def update(frame): + t, T = frame_metadata(frame) + temp_marker.set_data([t], [T]) + + for row, col, species, _, xlo, xhi in PANELS: + xs, cs, _ = series[species] + mask = region_mask(xs[frame], xlo, xhi) + lines[(row, col)].set_data(xs[frame][mask], cs[frame][mask]) + + return list(lines.values()) + [temp_marker] + + ani = animation.FuncAnimation( + fig, update, + frames=frame_indices, + interval=50, + blit=True, + ) + + if show: + plt.show() + else: + print(f"Saving animation to {OUTPUT_FILE} …") + ani.save(OUTPUT_FILE, writer="pillow", fps=20, dpi=140) + print("Done.") + + plt.close(fig) + + +if __name__ == "__main__": + parser = argparse.ArgumentParser( + description="Animate mobile and trapped D profiles from val-2l TMAP8 output." + ) + parser.add_argument("--show", action="store_true", + help="Preview interactively instead of saving to file.") + args = parser.parse_args() + build_animation(show=args.show) diff --git a/test/tests/val-2l/val-2l.i b/test/tests/val-2l/val-2l.i index bf4e3bd89..0255dffe3 100644 --- a/test/tests/val-2l/val-2l.i +++ b/test/tests/val-2l/val-2l.i @@ -2,12 +2,14 @@ # !include val-2l.params -# General parameters -kB = '${units 1.380649e-23 J/K}' # Boltzmann constant - -# Mesh and solver controls -simulation_time = '${units 2 h -> s}' # 2 h TDS with temperature ramp -nx_scale = 5 +# Physical constants +kb = '${units 1.380649e-23 J/K}' # Boltzmann constant J/K - from PhysicalConstants.h +eV_to_J = '${units 1.602176634e-19 J/eV}' # Conversion coefficient from eV to Joules - from PhysicalConstants.h +kb_eV = '${units ${fparse kb / eV_to_J} eV/K}' # Boltzmann constant eV/K + +# Temporal Parameters +# simulation_time = '${units 2 h -> s}' # 2 h TDS with temperature ramp +simulation_time = '${units 1 h -> s}' # Should be enough time to model unirradiated case dt_start = '${units 1 s}' dt_max = '${units 4 s}' dt_min = '${units 1e-6 s}' @@ -17,52 +19,84 @@ tungsten_thickness = '${units 0.2 mm -> mum}' # Tungsten disc thickness, Shimada # Gaussian-hill initial condition (diagnostic profile; not from Shimada et al. 2010). gaussian_amplitude = '${units 1e26 at/m^3 -> at/mum^3}' # Peak concentration at the center (= 1 at/mum^3) -gaussian_center = '${fparse ${tungsten_thickness} / 5}' # Hill center (20 mum) -gaussian_sigma = '${fparse ${tungsten_thickness} / 20}' # Hill standard deviation (10 mum) +gaussian_center = '${fparse ${tungsten_thickness} / 5}' # Hill center +gaussian_sigma = '${fparse ${tungsten_thickness} / 20}' # Hill standard deviation # Temperature-dependent deuterium diffusivity used by Shimada et al. 2010 (p. S668, Section 3) -diffusivity_coefficient = '${units 2.9e-7 m^2/s -> mum^2/s}' # D0 prefactor, Shimada et al. 2010 (p. S668) -E_D = '${units 0.39 eV -> J}' # Diffusion activation energy, Shimada et al. 2010 (p. S668) +diffusivity_preexponential_factor = '${units 2.9e-7 m^2/s -> mum^2/s}' # D0 prefactor, Shimada et al. 2010 (p. S668) +diffusivity_activation_energy = '${units 0.39 eV}' # Diffusion activation energy, Shimada et al. 2010 (p. S668) # Recombination parameters: Shimada et al. 2010 (p. S668) -# recombination_parameter = '${units ${fparse 3.2e-15*exp(-1.16)} m^4/at/s -> mum^4/at/s}' -# recombination_parameter_enclos2 = '${units 2e-31 m^4/at/s -> mum^4/at/s}' -# recombination_coefficient_parameter_enclos1_TMAP4 = '${units 1e-27 m^4/at/s -> mum^4/at/s}' +recombination_preexponential_factor = '${units 3.2e-15 m^4/at/s -> mum^4/at/s}' +recombination_energy = '${units 1.16 eV}' # Thermal parameters temperature_tds_start = '${units 300 K}' # TDS ramp start (room temperature), Shimada et al. 2010 (p. S668, Figs. 2-4) temperature_tds_end = '${units 1173 K}' # TDS ramp peak temperature, Shimada et al. 2010 (p. S668, Fig. 1) temperature_rate = '${units ${fparse 10 / 60} K/s}' # TDS ramp rate of 10 K/min, Shimada et al. 2010 (p. S668, Fig. 1) -[Variables] - [deuterium_mobile_concentration] - [] -[] - -[ICs] - # Gaussian hill centered on the sample midplane (diagnostic, see header). - [deuterium_mobile_concentration_ic] - type = FunctionIC - variable = deuterium_mobile_concentration - function = gaussian_hill_initial_condition - [] -[] +# Trapping Parameters +trap_depth = '${units 0.7 mum}' +tungsten_density = '${units 6.25e28 at/m^3 -> at/mum^3}' # Ambrosek and Longhurst 2008 +trap_fraction = 0.04 +trap_site_density = '${fparse ${trap_fraction} * ${tungsten_density}}' +alpha_t_0 = '${units 9.1316e12 1/s}' # Pulled from val-2d since it is a similar example +trapping_energy = '${units ${fparse 0.39 / kb_eV} K}' # pulled from val-2d +trap_per_free = 1e4 # User specified + +# Detrapping Parameters +alpha_r_0 = '${units 8.4e12 1/s}' # val-2d +detrapping_energy = '${units ${fparse 1.35 / kb_eV} K}' # Unclear if Shimida 2011 means trapping or detrapping energy + +# TMAP7 fit A Trapping Parameters + +# Mesh Parameters (Ensure that all trap endpoints have a node) +depth_A = '${units 0.7 mum}' # TMAP fit A trap boundary +depth_C = '${units 1.2 mum}' # TMAP fit C trap boundary (near-surface region end) +depth_E = '${units 2.5 mum}' # TMAP fit E trap boundary (neutron-irradiated) +near_end = '${units 1.0 mum}' # near-surface / bulk interface +bulk_end = '${units 7.0 mum}' # bulk / deep-material interface and TMAP fit B trap boundary + +# ── Segment widths (derived — do not edit directly) ──────────────────────── +# Segment layout: +# [0, depth_A ] : near-surface fine (0.7 mum) +# [depth_A, near_end] : near-surface remainder (0.3 mum) +# [near_end, depth_C] : bulk start (0.2 mum) +# [depth_C, depth_E ] : bulk middle (1.3 mum) +# [depth_E, bulk_end] : bulk end (4.5 mum) +# [bulk_end, W_thick] : deep material (193 mum) + seg1 = '${fparse ${depth_A}}' + seg2 = '${fparse ${near_end} - ${depth_A}}' + seg3 = '${fparse ${depth_C} - ${near_end}}' + seg4 = '${fparse ${depth_E} - ${depth_C}}' + seg5 = '${fparse ${bulk_end} - ${depth_E}}' + seg6 = '${fparse ${tungsten_thickness} - ${bulk_end}}' + + # ── Element counts ───────────────────────────────────────────────────────── + # nx_scale uniformly refines all segments. Per-segment multipliers set the + # relative resolution. Approximate element size at nx_scale = 1 shown below. + # seg1: 0.7 mum / (7 * nx_scale) ~ 100 nm/element + # seg2: 0.3 mum / (3 * nx_scale) ~ 100 nm/element + # seg3: 0.2 mum / (2 * nx_scale) ~ 100 nm/element + # seg4: 1.3 mum / (5 * nx_scale) ~ 260 nm/element + # seg5: 4.5 mum / (5 * nx_scale) ~ 900 nm/element + # seg6: 193 mum / (10 * nx_scale) ~ 19.3 mum/element + nx_scale = 10 [Mesh] - [temp_mesh] type = CartesianMeshGenerator dim = 1 - # Graded mesh: fine at the upstream surface, coarse in the bulk. The last block fills the - # remainder of the disc so the total thickness equals tungsten_thickness (0.2 mm). - dx = '${fparse 5 * ${units 4e-9 m -> mum}} ${units 1e-8 m -> mum} ${units 1e-7 m -> mum} - ${units 1e-6 m -> mum} ${units 1e-5 m -> mum} - ${fparse ${tungsten_thickness} - 5 * ${units 4e-9 m -> mum} - ${units 1e-8 m -> mum} - - ${units 1e-7 m -> mum} - ${units 1e-6 m -> mum} - ${units 1e-5 m -> mum}}' - ix = '${fparse 5 * ${nx_scale}} ${nx_scale} ${nx_scale} - ${nx_scale} ${nx_scale} ${fparse 10 * ${nx_scale}}' - [] + dx = '${seg1} ${seg2} ${seg3} ${seg4} ${seg5} ${seg6}' + ix = '${fparse 50 * ${nx_scale}} + ${fparse 3 * ${nx_scale}} + ${fparse 2 * ${nx_scale}} + ${fparse 5 * ${nx_scale}} + ${fparse 5 * ${nx_scale}} + ${fparse 10 * ${nx_scale}}' + # subdomain_id = '1 2 2 2 2 2' # block 1 = trap region, block 2 = bulk + [] [tungsten_disc] type = RenameBoundaryGenerator input = temp_mesh @@ -71,55 +105,168 @@ temperature_rate = '${units ${fparse 10 / 60} K/s}' # TDS ramp rate of 10 K/min, [] [] -[Problem] - # Reference-based convergence: compare each variable's residual to the magnitude of the physical - # terms (diffusion + time derivative + source, tagged 'ref') rather than to the initial residual - type = ReferenceResidualProblem - extra_tag_vectors = 'ref' - reference_vector = 'ref' + +[Variables] + [mobile] + [] + [trapped_1] + [] [] +[ICs] + # # Gaussian hill centered on the sample midplane (diagnostic, see header). + # [mobile_ic] + # type = FunctionIC + # variable = mobile + # function = gaussian_hill_initial_condition + # [] + [trapped_ic] + type = FunctionIC + function = trapped_initial_condition + variable = trapped_1 + [] +[] + +# [Problem] +# # Reference-based convergence: compare each variable's residual to the magnitude of the physical +# # terms (diffusion + time derivative + source, tagged 'ref') rather than to the initial residual +# type = ReferenceResidualProblem +# extra_tag_vectors = 'ref' +# reference_vector = 'ref' +# [] + [Kernels] - [diffusion] + [mobile_time_derivative] + type = ADTimeDerivative + variable = mobile + # extra_vector_tags = 'ref' + [] + [mobile_diffusion] type = ADMatDiffusion - variable = deuterium_mobile_concentration + variable = mobile diffusivity = diffusivity_mat - extra_vector_tags = 'ref' + # extra_vector_tags = 'ref' [] - [time_diffusion] - type = ADTimeDerivative - variable = deuterium_mobile_concentration - extra_vector_tags = 'ref' + [coupled_time] + type = ADCoefCoupledTimeDerivative + variable = mobile + v = trapped_1 + coef = ${trap_per_free} + # extra_vector_tags = 'ref' + [] +[] + +[NodalKernels] + [time_1] + type = TimeDerivativeNodalKernel + variable = trapped_1 + [] + [trapping_1] + type = TrappingNodalKernel + variable = trapped_1 + mobile_concentration = mobile + alpha_t = '${alpha_t_0}' + trapping_energy = '${trapping_energy}' + N = '${tungsten_density}' + Ct0 = 'trap_distribution_function' + temperature = 'temperature' + trap_per_free = ${trap_per_free} + # extra_vector_tags = ref + [] + [release_1] + type = ReleasingNodalKernel + variable = trapped_1 + # alpha_r = '${alpha_r_0}' + alpha_r = '${alpha_r_0}' # Trapping is restricted to trapped region, so this variable beyond the trapped region will have no deuterium to release. + detrapping_energy = '${detrapping_energy}' + temperature = 'temperature' + [] +[] + +[AuxVariables] + [temperature] + initial_condition = ${temperature_tds_start} [] [] +[AuxKernels] + [temperature_aux] + type = FunctionAux + variable = temperature + function = temperature_function + execute_on = 'INITIAL LINEAR TIMESTEP_END' + [] +[] + + [BCs] - # Assume infinite recombination on upstream and downstream surfaces + active = 'left_recombination_flux right_recombination_flux' + # active = 'left right' + + # Infinite recombination [left] type = ADDirichletBC boundary = upstream value = 0 - variable = deuterium_mobile_concentration + variable = mobile [] [right] type = ADDirichletBC boundary = downstream value = 0 - variable = deuterium_mobile_concentration + variable = mobile + [] + + # Finite recombination + [left_recombination_flux] + type = ADMatNeumannBC + variable = mobile + boundary = upstream + value = 1 + boundary_material = flux_recombination_surface + # extra_vector_tags = 'ref' + [] + + [right_recombination_flux] + type = ADMatNeumannBC + variable = mobile + boundary = downstream + value = 1 + boundary_material = flux_recombination_surface + # extra_vector_tags = 'ref' [] [] [Materials] + # Temperature-dependent deuterium diffusivity in tungsten [diffusivity_mat] type = ADDerivativeParsedMaterial property_name = 'diffusivity_mat' - functor_names = 'Temperature_function' + functor_names = 'temperature_function' functor_symbols = 'temperature' - expression = '${diffusivity_coefficient} * exp(- ${E_D} / ${kB} / temperature)' + expression = '${diffusivity_preexponential_factor} * exp(- ${diffusivity_activation_energy} / ${kb_eV} / temperature)' output_properties = 'diffusivity_mat' outputs = 'exodus' [] + + # Temperature-dependent recombination coefficient + [recombination_rate_surface] + type = ADDerivativeParsedMaterial + property_name = 'Kr' + functor_names = 'temperature_function' + functor_symbols = 'temperature' + expression = '${recombination_preexponential_factor} * exp(- ${recombination_energy} / ${kb_eV} / temperature)' + [] + + # Finite recombination Boundary Material + [flux_recombination_surface] + type = ADDerivativeParsedMaterial + coupled_variables = 'mobile' + property_name = 'flux_recombination_surface' + material_property_names = 'Kr' + expression = '- 2 * Kr * mobile ^ 2' + [] [] [Functions] @@ -131,22 +278,42 @@ temperature_rate = '${units ${fparse 10 / 60} K/s}' # TDS ramp rate of 10 K/min, [] # Linear TDS ramp from temperature_tds_start to temperature_tds_end and hold until end of simulation - [Temperature_function] + [temperature_function] type = ParsedFunction expression = 'if(t<(${temperature_tds_end} - ${temperature_tds_start}) / ${temperature_rate}, ${temperature_tds_start} + ${temperature_rate} * t, ${temperature_tds_end})' [] + + [trapped_initial_condition] + type = ParsedFunction + expression = 'if(x < ${trap_depth}, ${trap_site_density} / ${trap_per_free}, 0.0)' + [] + + # Fed to TrappingNodalKernel + [trap_distribution_function] + type = ParsedFunction + expression = 'if(x < ${trap_depth}, ${trap_fraction}, 0.0)' + [] + [] [Postprocessors] + [trap_region] + type = ConstantPostprocessor + value = ${trap_depth} + execute_on = 'initial' + outputs = csv + [] + ### Temperature ramp and resulting diffusivity (for post-processing/plots) ### [temperature] # K type = FunctionValuePostprocessor - function = Temperature_function + function = temperature_function outputs = csv + execute_on = 'INITIAL TIMESTEP_END' [] [diffusivity_pp] # mum^2/s; uniform in space, depends only on temperature @@ -160,9 +327,26 @@ temperature_rate = '${units ${fparse 10 / 60} K/s}' # TDS ramp rate of 10 K/min, # Total deuterium inventory currently in the sample, M(t) (cf. val-2k deuterium_inventory_in_sample). # Runs on INITIAL so its t=0 row is the initial inventory M(0), which the comparison script reads to # normalize the residual. - [total_deuterium_retention] # atoms / mum^2 + + [total_mobile_retention] type = ElementIntegralVariablePostprocessor - variable = deuterium_mobile_concentration + variable = mobile + execute_on = 'INITIAL TIMESTEP_END' + [] + + [total_trapped_retention] + type = ElementIntegralVariablePostprocessor + variable = trapped_1 + # Physical concentration = variable * trap_per_free + # Handle scaling in post-processing script, or use ParsedPostprocessor to multiply. + execute_on = 'INITIAL TIMESTEP_END' + [] + + # Replace old total_deuterium_retention: + [total_deuterium_retention] + type = ParsedPostprocessor + expression = 'total_mobile_retention + total_trapped_retention * ${trap_per_free}' + pp_names = 'total_mobile_retention total_trapped_retention' execute_on = 'INITIAL TIMESTEP_END' outputs = csv [] @@ -173,35 +357,35 @@ temperature_rate = '${units ${fparse 10 / 60} K/s}' # TDS ramp rate of 10 K/min, [upstream_flux] type = ADSideDiffusiveFluxIntegral boundary = 'upstream' - variable = deuterium_mobile_concentration + variable = mobile diffusivity = diffusivity_mat - execute_on = 'INITIAL TIMESTEP_END' - outputs = csv + execute_on = 'TIMESTEP_END' + # outputs = csv [] [downstream_flux] type = ADSideDiffusiveFluxIntegral boundary = 'downstream' - variable = deuterium_mobile_concentration + variable = mobile diffusivity = diffusivity_mat - execute_on = 'INITIAL TIMESTEP_END' - outputs = csv + execute_on = 'TIMESTEP_END' + # outputs = csv [] # Total desorption rate through both faces (cf. val-2k deuterium_release_flux_total). [deuterium_release_flux_total] # atoms / mum^2 / s type = SumPostprocessor values = 'upstream_flux downstream_flux' - execute_on = 'INITIAL TIMESTEP_END' - outputs = none + execute_on = 'TIMESTEP_END' + outputs = csv [] # Cumulative deuterium released through both faces (time-integrated release rate), = M(0) - M(t). [deuterium_released_physical] # atoms / mum^2 type = TimeIntegratedPostprocessor value = deuterium_release_flux_total - time_integration_scheme = trapezoidal-rule - execute_on = 'INITIAL TIMESTEP_END' + time_integration_scheme = IMPLICIT-EULER + execute_on = 'TIMESTEP_END' outputs = csv [] @@ -222,19 +406,26 @@ temperature_rate = '${units ${fparse 10 / 60} K/s}' # TDS ramp rate of 10 K/min, type = ParsedPostprocessor expression = 'deuterium_inventory_change + deuterium_released_physical' pp_names = 'deuterium_inventory_change deuterium_released_physical' - execute_on = 'INITIAL TIMESTEP_END' + execute_on = 'TIMESTEP_END' outputs = 'csv' [] [] [VectorPostprocessors] - [deuterium_mobile_concentration_profile] + [mobile_profile] type = NodalValueSampler - variable = deuterium_mobile_concentration + variable = mobile sort_by = x execute_on = 'TIMESTEP_END' outputs = profile_csv [] + [trapped_1_profile] + type = NodalValueSampler + variable = trapped_1 + sort_by = x + execute_on = 'TIMESTEP_END' + outputs = trapped_profile_csv + [] [] [Outputs] @@ -248,6 +439,10 @@ temperature_rate = '${units ${fparse 10 / 60} K/s}' # TDS ramp rate of 10 K/min, type = CSV file_base = 'deuterium_mobile_concentration_profile/val-2l_out' [] + [trapped_profile_csv] + type = CSV + file_base = 'deuterium_trapped_concentration_profile/val-2l_out' + [] [] [Preconditioning] @@ -262,7 +457,8 @@ temperature_rate = '${units ${fparse 10 / 60} K/s}' # TDS ramp rate of 10 K/min, scheme = bdf2 solve_type = NEWTON line_search = 'none' - nl_abs_tol = 1e-10 + nl_abs_tol = 1e-12 + nl_rel_tol = 1e-6 petsc_options_iname = '-pc_type' petsc_options_value = 'lu' end_time = ${simulation_time} @@ -270,10 +466,10 @@ temperature_rate = '${units ${fparse 10 / 60} K/s}' # TDS ramp rate of 10 K/min, dtmin = ${dt_min} dtmax = ${dt_max} [TimeStepper] - type = IterationAdaptiveDT - dt = ${dt_start} # initial step only - optimal_iterations = 5 - growth_factor = 1.1 - cutback_factor_at_failure = 0.9 + type = IterationAdaptiveDT + dt = ${dt_start} + optimal_iterations = 5 + growth_factor = 1.1 + cutback_factor_at_failure = 0.9 [] [] From f89ac59a5be3e045479d3546ec9525c20554d11a Mon Sep 17 00:00:00 2001 From: "Butterworth, Evan" Date: Thu, 30 Jul 2026 09:10:53 -0600 Subject: [PATCH 04/12] Further debugging and improvements to input file and comparison scripts (Ref. #405) --- test/tests/val-2l/comparison_val-2l.py | 2 +- .../tests/val-2l/trapped_profile_animation.py | 2 +- test/tests/val-2l/val-2l.i | 34 +++++++++---------- 3 files changed, 18 insertions(+), 20 deletions(-) diff --git a/test/tests/val-2l/comparison_val-2l.py b/test/tests/val-2l/comparison_val-2l.py index e6d3808e8..d04179a88 100644 --- a/test/tests/val-2l/comparison_val-2l.py +++ b/test/tests/val-2l/comparison_val-2l.py @@ -194,7 +194,7 @@ def plot_unirradiated_desorption( ) # at/mum^2/s -> at/m^2/s (x1e12); atomic D flux -> molecular D2 flux (/2) to match the # RGA, which detects D2 (mass 4) and HD (mass 3) -- same convention as val-2d - simulation_flux = simulation_flux * 1e12 / 2 + simulation_flux = simulation_flux * 1e12 /2 # Map experimental times to temperatures using the simulation's T(t) ramp, # then truncate to the simulation time range to avoid extrapolation. diff --git a/test/tests/val-2l/trapped_profile_animation.py b/test/tests/val-2l/trapped_profile_animation.py index 8bc85a280..86bc9e3e4 100644 --- a/test/tests/val-2l/trapped_profile_animation.py +++ b/test/tests/val-2l/trapped_profile_animation.py @@ -21,7 +21,7 @@ # ── Must match val-2l.i ───────────────────────────────────────────────────── # TRAP_PER_FREE = 1 -FRAME_STRIDE = 2 +FRAME_STRIDE = 10 TRAP_BOUNDARY = 0.7 # µm: spatial extent of 1.35 eV trap (TMAP fit A) # ── File paths ────────────────────────────────────────────────────────────── # diff --git a/test/tests/val-2l/val-2l.i b/test/tests/val-2l/val-2l.i index 0255dffe3..ec7804a1e 100644 --- a/test/tests/val-2l/val-2l.i +++ b/test/tests/val-2l/val-2l.i @@ -8,10 +8,10 @@ eV_to_J = '${units 1.602176634e-19 J/eV}' # Conversion coefficient from eV to Jo kb_eV = '${units ${fparse kb / eV_to_J} eV/K}' # Boltzmann constant eV/K # Temporal Parameters -# simulation_time = '${units 2 h -> s}' # 2 h TDS with temperature ramp -simulation_time = '${units 1 h -> s}' # Should be enough time to model unirradiated case -dt_start = '${units 1 s}' -dt_max = '${units 4 s}' +simulation_time = '${units 2 h -> s}' # 2 h TDS with temperature ramp +# simulation_time = '${units 1 h -> s}' # Should be enough time to model unirradiated case +dt_start = '${units 0.25 s}' +dt_max = '${units 1 s}' dt_min = '${units 1e-6 s}' # Geometry @@ -74,28 +74,22 @@ bulk_end = '${units 7.0 mum}' # bulk / deep-material interface and TMAP fit B # ── Element counts ───────────────────────────────────────────────────────── # nx_scale uniformly refines all segments. Per-segment multipliers set the - # relative resolution. Approximate element size at nx_scale = 1 shown below. - # seg1: 0.7 mum / (7 * nx_scale) ~ 100 nm/element - # seg2: 0.3 mum / (3 * nx_scale) ~ 100 nm/element - # seg3: 0.2 mum / (2 * nx_scale) ~ 100 nm/element - # seg4: 1.3 mum / (5 * nx_scale) ~ 260 nm/element - # seg5: 4.5 mum / (5 * nx_scale) ~ 900 nm/element - # seg6: 193 mum / (10 * nx_scale) ~ 19.3 mum/element - nx_scale = 10 + # relative resolution. + + nx_scale = 20 [Mesh] [temp_mesh] type = CartesianMeshGenerator dim = 1 dx = '${seg1} ${seg2} ${seg3} ${seg4} ${seg5} ${seg6}' - ix = '${fparse 50 * ${nx_scale}} + ix = '${fparse 10 * ${nx_scale}} ${fparse 3 * ${nx_scale}} ${fparse 2 * ${nx_scale}} ${fparse 5 * ${nx_scale}} ${fparse 5 * ${nx_scale}} ${fparse 10 * ${nx_scale}}' # subdomain_id = '1 2 2 2 2 2' # block 1 = trap region, block 2 = bulk - [] [tungsten_disc] type = RenameBoundaryGenerator @@ -360,7 +354,6 @@ bulk_end = '${units 7.0 mum}' # bulk / deep-material interface and TMAP fit B variable = mobile diffusivity = diffusivity_mat execute_on = 'TIMESTEP_END' - # outputs = csv [] [downstream_flux] @@ -369,7 +362,6 @@ bulk_end = '${units 7.0 mum}' # bulk / deep-material interface and TMAP fit B variable = mobile diffusivity = diffusivity_mat execute_on = 'TIMESTEP_END' - # outputs = csv [] # Total desorption rate through both faces (cf. val-2k deuterium_release_flux_total). @@ -384,7 +376,7 @@ bulk_end = '${units 7.0 mum}' # bulk / deep-material interface and TMAP fit B [deuterium_released_physical] # atoms / mum^2 type = TimeIntegratedPostprocessor value = deuterium_release_flux_total - time_integration_scheme = IMPLICIT-EULER + time_integration_scheme = TRAPEZOIDAL-RULE execute_on = 'TIMESTEP_END' outputs = csv [] @@ -470,6 +462,12 @@ bulk_end = '${units 7.0 mum}' # bulk / deep-material interface and TMAP fit B dt = ${dt_start} optimal_iterations = 5 growth_factor = 1.1 - cutback_factor_at_failure = 0.9 + cutback_factor_at_failure = 0.5 + # timestep_limiting_function = temperature_function + # max_function_change = 0.2 [] + # [TimeStepper] + # type = ConstantDT + # dt = ${dt_start} + # [] [] From 2bac609eef9135b65df98f2a87351b6a22f9ea91 Mon Sep 17 00:00:00 2001 From: "Butterworth, Evan" Date: Mon, 17 Aug 2026 11:19:52 -0600 Subject: [PATCH 05/12] Adding python black formatting to requested files --- test/tests/val-2l/comparison_val-2l.py | 104 ++++++++++++++---- .../tests/val-2l/plot_subplots_at_timestep.py | 51 ++++++--- test/tests/val-2l/subplots_animation.py | 34 ++++-- .../tests/val-2l/trapped_profile_animation.py | 67 ++++++----- 4 files changed, 176 insertions(+), 80 deletions(-) diff --git a/test/tests/val-2l/comparison_val-2l.py b/test/tests/val-2l/comparison_val-2l.py index d04179a88..3544dce7a 100644 --- a/test/tests/val-2l/comparison_val-2l.py +++ b/test/tests/val-2l/comparison_val-2l.py @@ -112,6 +112,7 @@ def plot_conservation_of_mass(t, flux, mass, flux_label, title, filename): plt.savefig(filename, bbox_inches="tight", dpi=300) plt.close(fig) + def plot_diffusivity_vs_temperature( simulation_file="val-2l_out.csv", filename="val-2l_diffusivity_vs_temperature.png", @@ -143,7 +144,9 @@ def plot_diffusivity_vs_temperature( reciprocal_temperature = 1000.0 / temperature # 1000/T (1/K) fig, ax = plt.subplots(figsize=(8, 5)) - ax.semilogy(reciprocal_temperature, diffusivity_m2_s, color="steelblue", linewidth=2) + ax.semilogy( + reciprocal_temperature, diffusivity_m2_s, color="steelblue", linewidth=2 + ) ax.set_xlabel(r"Reciprocal temperature 1000/T (K$^{-1}$)") ax.set_ylabel(r"Diffusivity (m$^2$/s)") ax.set_title("Deuterium diffusivity in tungsten TMAP8 Material") @@ -194,7 +197,7 @@ def plot_unirradiated_desorption( ) # at/mum^2/s -> at/m^2/s (x1e12); atomic D flux -> molecular D2 flux (/2) to match the # RGA, which detects D2 (mass 4) and HD (mass 3) -- same convention as val-2d - simulation_flux = simulation_flux * 1e12 /2 + simulation_flux = simulation_flux * 1e12 / 2 # Map experimental times to temperatures using the simulation's T(t) ramp, # then truncate to the simulation time range to avoid extrapolation. @@ -207,7 +210,12 @@ def plot_unirradiated_desorption( # ---- Plot 1: experimental desorption history ---- plt.figure(figsize=(10, 6)) - plt.plot(experiment_temperature, experiment_flux, "ro", label="Experiment (Shimada 2010, 0 dpa)") + plt.plot( + experiment_temperature, + experiment_flux, + "ro", + label="Experiment (Shimada 2010, 0 dpa)", + ) plt.xlabel("Temperature (K)") plt.ylabel(r"Desorbed flux (m$^{-2}$s$^{-1}$)") plt.title("Unirradiated deuterium desorption") @@ -245,13 +253,27 @@ def plot_unirradiated_desorption( # ---- Plot 3: simulation vs experiment with RMSPE ---- plt.figure(figsize=(10, 6)) - plt.plot(experiment_temperature, experiment_flux, "ro", label="Experiment (Shimada 2010, 0 dpa)") + plt.plot( + experiment_temperature, + experiment_flux, + "ro", + label="Experiment (Shimada 2010, 0 dpa)", + ) plt.plot(simulation_temperature, simulation_flux, "b-", label="TMAP8") if rmspe_region.any(): - plt.axvline(experiment_temperature[rmspe_region].min(), color="green", linestyle="--", - linewidth=1.2, label="RMSPE region") - plt.axvline(experiment_temperature[rmspe_region].max(), color="green", linestyle="--", - linewidth=1.2) + plt.axvline( + experiment_temperature[rmspe_region].min(), + color="green", + linestyle="--", + linewidth=1.2, + label="RMSPE region", + ) + plt.axvline( + experiment_temperature[rmspe_region].max(), + color="green", + linestyle="--", + linewidth=1.2, + ) annotate_rmspe( mapped_simulation_flux[rmspe_region], experiment_flux[rmspe_region], @@ -270,6 +292,7 @@ def plot_unirradiated_desorption( plt.savefig(comparison_plot, bbox_inches="tight", dpi=300) # plt.show() + # =========================== TMAP8 simulation data extraction ========================== # csv_folder = "val-2l_out.csv" @@ -282,9 +305,11 @@ def plot_unirradiated_desorption( # plots the relative residual over time. We follow the same recipe here. M(0) is read from the t=0 row # of total_deuterium_retention, which runs on INITIAL (cf. val-2k reading # deuterium_inventory_in_sample_physical.iloc[0]). -total_deuterium_retention = simulation_TMAP8_data['total_deuterium_retention'] -temperature_history = simulation_TMAP8_data['temperature'] -mass_conservation_residual = simulation_TMAP8_data['deuterium_mass_conservation_residual'] +total_deuterium_retention = simulation_TMAP8_data["total_deuterium_retention"] +temperature_history = simulation_TMAP8_data["temperature"] +mass_conservation_residual = simulation_TMAP8_data[ + "deuterium_mass_conservation_residual" +] initial_inventory = total_deuterium_retention.iloc[0] relative_mass_conservation_residual = mass_conservation_residual / initial_inventory @@ -292,35 +317,59 @@ def plot_unirradiated_desorption( # total_mobile_retention : physical mobile inventory (at/µm²), no scaling needed # total_trapped_retention : MOOSE stores the *rescaled* variable, so multiply by # trap_per_free to recover the physical trapped inventory. -total_mobile_retention = simulation_TMAP8_data["total_mobile_retention"] -total_trapped_retention = simulation_TMAP8_data["total_trapped_retention"] * trap_per_free +total_mobile_retention = simulation_TMAP8_data["total_mobile_retention"] +total_trapped_retention = ( + simulation_TMAP8_data["total_trapped_retention"] * trap_per_free +) # --- Total deuterium inventory with temperature history --- # Add one entry per species to inventory_series. They are stacked bottom-up with # fill_between, so order matters: put the largest / most stable contribution first. # Append a new tuple here when additional trap populations are added. inventory_series = [ - ("Trapped D (trap 1, 1.35 eV)", total_trapped_retention, plt.get_cmap("viridis")(0.45)), - ("Mobile D", total_mobile_retention, plt.get_cmap("viridis")(0.95)), + ( + "Trapped D (trap 1, 1.35 eV)", + total_trapped_retention, + plt.get_cmap("viridis")(0.45), + ), + ("Mobile D", total_mobile_retention, plt.get_cmap("viridis")(0.95)), ] fig, ax = plt.subplots(figsize=(6.5, 5.5)) inventory_bottom = np.zeros_like(total_deuterium_retention) legend_patches = [] for label, values, color in inventory_series: - ax.fill_between(simulation_time_TMAP8, inventory_bottom, inventory_bottom + values, - color=color, alpha=0.3) - ax.plot(simulation_time_TMAP8, inventory_bottom + values, color=color, linewidth=1.0) + ax.fill_between( + simulation_time_TMAP8, + inventory_bottom, + inventory_bottom + values, + color=color, + alpha=0.3, + ) + ax.plot( + simulation_time_TMAP8, inventory_bottom + values, color=color, linewidth=1.0 + ) inventory_bottom = inventory_bottom + values legend_patches.append(Patch(color=color, alpha=0.5, label=label)) total_inventory = inventory_bottom -total_handle = ax.plot(simulation_time_TMAP8, total_inventory, color="tab:green", linewidth=1.5, - label="Total D inventory")[0] +total_handle = ax.plot( + simulation_time_TMAP8, + total_inventory, + color="tab:green", + linewidth=1.5, + label="Total D inventory", +)[0] ax_temperature = ax.twinx() -temperature_handle = ax_temperature.plot(simulation_time_TMAP8, temperature_history, linestyle="-", - color="k", linewidth=1.5, label="TMAP8 temperature history")[0] +temperature_handle = ax_temperature.plot( + simulation_time_TMAP8, + temperature_history, + linestyle="-", + color="k", + linewidth=1.5, + label="TMAP8 temperature history", +)[0] ax.set_xlabel("Time (s)") ax.set_ylabel(r"Deuterium inventory (atoms/$\mu m^2$)") @@ -328,7 +377,9 @@ def plot_unirradiated_desorption( ax.set_ylim(bottom=0) ax.grid(visible=True, which="major", color="0.65", linestyle="--", alpha=0.3) ax_temperature.set_ylabel("Temperature (K)") -ax.legend(handles=[total_handle, temperature_handle] + legend_patches[::-1], loc="lower right") +ax.legend( + handles=[total_handle, temperature_handle] + legend_patches[::-1], loc="lower right" +) ax.minorticks_on() plt.savefig("val-2l_inventory.png", bbox_inches="tight", dpi=300) # plt.show() @@ -336,7 +387,12 @@ def plot_unirradiated_desorption( # --- Relative deuterium mass-balance residual over time (cf. comparison_val-2k.py Stage 6) --- fig, ax = plt.subplots(figsize=(6.5, 4.8)) -ax.plot(simulation_time_TMAP8, relative_mass_conservation_residual, color="tab:blue", linewidth=1.8) +ax.plot( + simulation_time_TMAP8, + relative_mass_conservation_residual, + color="tab:blue", + linewidth=1.8, +) ax.axhline(0.0, color="0.35", linewidth=1.0, linestyle="--") ax.set_xlabel("Time (s)") ax.set_ylabel("Deuterium mass-balance residual / initial inventory (-)") diff --git a/test/tests/val-2l/plot_subplots_at_timestep.py b/test/tests/val-2l/plot_subplots_at_timestep.py index 6030fe3ac..8bedf81bd 100644 --- a/test/tests/val-2l/plot_subplots_at_timestep.py +++ b/test/tests/val-2l/plot_subplots_at_timestep.py @@ -3,14 +3,21 @@ import matplotlib.animation as animation import os -def subplot_bar_profile(timestep, data_dir='csv_data'): + +def subplot_bar_profile(timestep, data_dir="csv_data"): # Load the data - gas_path = os.path.join(data_dir, f"verification_RZ_solution_profile_gas_{timestep:04d}.csv") - steel_path = os.path.join(data_dir, f"verification_RZ_solution_profile_steel_{timestep:04d}.csv") + gas_path = os.path.join( + data_dir, f"verification_RZ_solution_profile_gas_{timestep:04d}.csv" + ) + steel_path = os.path.join( + data_dir, f"verification_RZ_solution_profile_steel_{timestep:04d}.csv" + ) gas_df = pd.read_csv(gas_path, skipinitialspace=True) steel_df = pd.read_csv(steel_path, skipinitialspace=True) - total_df = pd.read_csv(os.path.join(data_dir,"verification_RZ.csv"), skipinitialspace = True) + total_df = pd.read_csv( + os.path.join(data_dir, "verification_RZ.csv"), skipinitialspace=True + ) # Replace Correct Data point for gas concentration at interface due to bug in vpp # print('Testing Gas') @@ -25,12 +32,12 @@ def subplot_bar_profile(timestep, data_dir='csv_data'): # steel_df.iloc[-1, steel_df.columns.get_loc('H_mobile_steel')] = corrective_df.iloc[timestep-1,corrective_df.columns.get_loc('Mobile_steel_edge_air')] # print(steel_df['H_mobile_steel'].iloc[-1]) - time = total_df['time'] + time = total_df["time"] # Get spatial coordinates - gas_x = gas_df['x'] + gas_x = gas_df["x"] # print(type(gas_x)) - steel_x = steel_df['x'] + steel_x = steel_df["x"] # print(gas_x) # print(steel_x) @@ -50,31 +57,41 @@ def subplot_bar_profile(timestep, data_dir='csv_data'): fig, (ax1, ax2) = plt.subplots(2, 1, figsize=(12, 8), sharex=False) # Gas phase plot - ax1.plot(gas_x, gas_values, color='blue') + ax1.plot(gas_x, gas_values, color="blue") ax1.set_xlim(gas_x.min(), gas_x.max()) - ax1.set_ylim(gas_values.min()*0.995, gas_values.max()*1.005) - ax1.set_ylabel(r'Molecular H$_2$ Concentration in Gas ($\mu$mol/mm$^3$)') - ax1.set_title(f'Timestep {timestep} at Time: {time[timestep-1]:01.2f} days') + ax1.set_ylim(gas_values.min() * 0.995, gas_values.max() * 1.005) + ax1.set_ylabel(r"Molecular H$_2$ Concentration in Gas ($\mu$mol/mm$^3$)") + ax1.set_title(f"Timestep {timestep} at Time: {time[timestep-1]:01.2f} days") ax1.grid(True) # Steel phase plot - ax2.plot(steel_x, steel_values, color='green') + ax2.plot(steel_x, steel_values, color="green") ax2.set_xlim(steel_x.min(), steel_x.max()) ax2.set_ylim(steel_values.min(), steel_values.max()) - ax2.set_ylabel(r'Atomic H Concentration in Steel ($\mu$mol/mm^3)') - ax2.set_xlabel('Distance from Canister Center (mm)') + ax2.set_ylabel(r"Atomic H Concentration in Steel ($\mu$mol/mm^3)") + ax2.set_xlabel("Distance from Canister Center (mm)") # ax2.set_title(f'Steel - Timestep {timestep}') ax2.grid(True) plt.tight_layout() plt.show() + if __name__ == "__main__": import argparse - parser = argparse.ArgumentParser(description="Plot gas and steel concentration profiles for a given timestep.") - parser.add_argument("timestep", type=int, help="Timestep number (e.g., 1 for _0001.csv)") - parser.add_argument("--data_dir", type=str, default="csv_data", help="Directory containing the CSV files") + parser = argparse.ArgumentParser( + description="Plot gas and steel concentration profiles for a given timestep." + ) + parser.add_argument( + "timestep", type=int, help="Timestep number (e.g., 1 for _0001.csv)" + ) + parser.add_argument( + "--data_dir", + type=str, + default="csv_data", + help="Directory containing the CSV files", + ) args = parser.parse_args() subplot_bar_profile(args.timestep, data_dir=args.data_dir) diff --git a/test/tests/val-2l/subplots_animation.py b/test/tests/val-2l/subplots_animation.py index 490054fda..40fe08429 100644 --- a/test/tests/val-2l/subplots_animation.py +++ b/test/tests/val-2l/subplots_animation.py @@ -9,10 +9,12 @@ # LineValueSampler output lives in a directory named after the VectorPostprocessor # (val-2l.i: [VectorPostprocessors]/deuterium_mobile_concentration_profile). -profile_files = sorted(glob.glob( - "deuterium_mobile_concentration_profile/" - "val-2l_out_deuterium_mobile_concentration_profile_*.csv" -)) +profile_files = sorted( + glob.glob( + "deuterium_mobile_concentration_profile/" + "val-2l_out_deuterium_mobile_concentration_profile_*.csv" + ) +) near_surface_limit_um = 20.0 # depth (um) shown in the lower zoom subplot frame_stride = 5 # show every Nth timestep — keeps the movie fast to encode and compact @@ -31,7 +33,9 @@ df = pd.read_csv(f, skipinitialspace=True) if df.shape[0] == 0: continue - frames.append((df["x"].values, df["deuterium_mobile_concentration"].values, times[i])) + frames.append( + (df["x"].values, df["deuterium_mobile_concentration"].values, times[i]) + ) if not frames: raise FileNotFoundError("No non-empty concentration profile CSV files found.") @@ -46,11 +50,21 @@ # Markers sit on each mesh node (the NodalValueSampler points), so they reveal the # graded element layout: dense at the surface, sparse in the bulk. lines = [] -for ax, xlim, color in ((ax1, x_max_um, "steelblue"), - (ax2, near_surface_limit_um, "darkorange")): - (line,) = ax.plot([], [], color=color, linewidth=1.5, - marker="o", markersize=4, markerfacecolor="white", - markeredgecolor=color, markeredgewidth=1.0) +for ax, xlim, color in ( + (ax1, x_max_um, "steelblue"), + (ax2, near_surface_limit_um, "darkorange"), +): + (line,) = ax.plot( + [], + [], + color=color, + linewidth=1.5, + marker="o", + markersize=4, + markerfacecolor="white", + markeredgecolor=color, + markeredgewidth=1.0, + ) ax.set_xlim(0, xlim) ax.set_ylim(0, c_max) ax.set_xlabel(r"Depth ($\mu$m)") diff --git a/test/tests/val-2l/trapped_profile_animation.py b/test/tests/val-2l/trapped_profile_animation.py index 86bc9e3e4..0c9d7b72b 100644 --- a/test/tests/val-2l/trapped_profile_animation.py +++ b/test/tests/val-2l/trapped_profile_animation.py @@ -21,33 +21,34 @@ # ── Must match val-2l.i ───────────────────────────────────────────────────── # TRAP_PER_FREE = 1 -FRAME_STRIDE = 10 -TRAP_BOUNDARY = 0.7 # µm: spatial extent of 1.35 eV trap (TMAP fit A) +FRAME_STRIDE = 10 +TRAP_BOUNDARY = 0.7 # µm: spatial extent of 1.35 eV trap (TMAP fit A) # ── File paths ────────────────────────────────────────────────────────────── # -MOBILE_DIR = "deuterium_mobile_concentration_profile" +MOBILE_DIR = "deuterium_mobile_concentration_profile" TRAPPED_DIR = "deuterium_trapped_concentration_profile" -MOBILE_COL = "mobile" +MOBILE_COL = "mobile" TRAPPED_COL = "trapped_1" -MAIN_CSV = "val-2l_out.csv" +MAIN_CSV = "val-2l_out.csv" OUTPUT_FILE = "val-2l_profile_animation.gif" # ── Panel definitions ─────────────────────────────────────────────────────── # # Each entry: (row, col, species, label, x_min, x_max) PANELS = [ - (0, 0, "mobile", "Mobile – whole domain", 0.0, 200.0), - (0, 1, "mobile", "Mobile – near surface", 0.0, 1.0), - (1, 0, "trapped", "Trapped – bulk & near surface", 0.0, 7.0), - (1, 1, "trapped", "Trapped – near surface", 0.0, 1.0), + (0, 0, "mobile", "Mobile – whole domain", 0.0, 200.0), + (0, 1, "mobile", "Mobile – near surface", 0.0, 1.0), + (1, 0, "trapped", "Trapped – bulk & near surface", 0.0, 7.0), + (1, 1, "trapped", "Trapped – near surface", 0.0, 1.0), ] -COLOR_MOBILE = "steelblue" -COLOR_TRAPPED = "darkorange" +COLOR_MOBILE = "steelblue" +COLOR_TRAPPED = "darkorange" COLOR_TRAP_BOUNDARY = "dimgray" # ── Helpers ───────────────────────────────────────────────────────────────── # + def detect_value_column(df, hint): cols = list(df.columns) if hint in cols: @@ -93,9 +94,10 @@ def region_mask(x, x_min, x_max): # ── Main ──────────────────────────────────────────────────────────────────── # + def build_animation(show=False): # ── Scalar CSV for time / temperature ────────────────────────────────── # - main_df = pd.read_csv(MAIN_CSV) + main_df = pd.read_csv(MAIN_CSV) all_times = main_df["time"].values all_temps = main_df["temperature"].values @@ -106,29 +108,30 @@ def frame_metadata(i): return all_times[row], all_temps[row] # ── Load profile series ───────────────────────────────────────────────── # - mob_xs, mob_cs = load_profile_series(MOBILE_DIR, MOBILE_COL, scale=1.0) + mob_xs, mob_cs = load_profile_series(MOBILE_DIR, MOBILE_COL, scale=1.0) trp_xs, trp_cs = load_profile_series(TRAPPED_DIR, TRAPPED_COL, scale=TRAP_PER_FREE) - n_frames = min(len(mob_xs), len(trp_xs)) + n_frames = min(len(mob_xs), len(trp_xs)) frame_indices = range(0, n_frames, FRAME_STRIDE) series = { - "mobile": (mob_xs, mob_cs, COLOR_MOBILE), + "mobile": (mob_xs, mob_cs, COLOR_MOBILE), "trapped": (trp_xs, trp_cs, COLOR_TRAPPED), } # ── Figure: temperature ramp on top, 2x2 panels below ────────────────── # fig = plt.figure(figsize=(12, 9)) # Reserve top 15% for temperature axes, bottom 85% for the 2x2 grid - temp_ax = fig.add_axes([0.10, 0.88, 0.82, 0.09]) - gs = fig.add_gridspec(2, 2, left=0.10, right=0.92, - top=0.82, bottom=0.07, - hspace=0.45, wspace=0.35) + temp_ax = fig.add_axes([0.10, 0.88, 0.82, 0.09]) + gs = fig.add_gridspec( + 2, 2, left=0.10, right=0.92, top=0.82, bottom=0.07, hspace=0.45, wspace=0.35 + ) axes = gs.subplots() # ── Temperature ramp axes ─────────────────────────────────────────────── # temp_ax.plot(all_times, all_temps, color="firebrick", linewidth=1.5) - temp_marker, = temp_ax.plot(all_times[0], all_temps[0], "o", - color="firebrick", markersize=6, zorder=5) + (temp_marker,) = temp_ax.plot( + all_times[0], all_temps[0], "o", color="firebrick", markersize=6, zorder=5 + ) temp_ax.set_xlim(0, all_times[-1]) temp_ax.set_ylim(all_temps.min() * 0.95, all_temps.max() * 1.05) temp_ax.set_xlabel("Time (s)", fontsize=8) @@ -157,13 +160,15 @@ def frame_metadata(i): ax.ticklabel_format(axis="y", style="sci", scilimits=(0, 0)) if xlo <= TRAP_BOUNDARY <= xhi: - ax.axvline(TRAP_BOUNDARY, color=COLOR_TRAP_BOUNDARY, - linestyle=":", linewidth=1.1, - label=f"Trap edge ({TRAP_BOUNDARY} µm)") + ax.axvline( + TRAP_BOUNDARY, + color=COLOR_TRAP_BOUNDARY, + linestyle=":", + linewidth=1.1, + label=f"Trap edge ({TRAP_BOUNDARY} µm)", + ) ax.legend(fontsize=7, loc="upper right") - - # ── Animation update ──────────────────────────────────────────────────── # def update(frame): t, T = frame_metadata(frame) @@ -177,7 +182,8 @@ def update(frame): return list(lines.values()) + [temp_marker] ani = animation.FuncAnimation( - fig, update, + fig, + update, frames=frame_indices, interval=50, blit=True, @@ -197,7 +203,10 @@ def update(frame): parser = argparse.ArgumentParser( description="Animate mobile and trapped D profiles from val-2l TMAP8 output." ) - parser.add_argument("--show", action="store_true", - help="Preview interactively instead of saving to file.") + parser.add_argument( + "--show", + action="store_true", + help="Preview interactively instead of saving to file.", + ) args = parser.parse_args() build_animation(show=args.show) From bffe8b6e619c70dfe6a24c4ff7abd1e74c946690 Mon Sep 17 00:00:00 2001 From: "Butterworth, Evan" Date: Mon, 17 Aug 2026 13:39:16 -0600 Subject: [PATCH 06/12] Added volumetric calculations for total inventory plot to calculate atoms --- test/tests/val-2l/comparison_val-2l.py | 17 +++++++++-------- test/tests/val-2l/val-2l.i | 2 +- 2 files changed, 10 insertions(+), 9 deletions(-) diff --git a/test/tests/val-2l/comparison_val-2l.py b/test/tests/val-2l/comparison_val-2l.py index 3544dce7a..23ce73a4a 100644 --- a/test/tests/val-2l/comparison_val-2l.py +++ b/test/tests/val-2l/comparison_val-2l.py @@ -14,6 +14,8 @@ # Must match val-2l.i: trap_per_free = ... (rescaling factor for trapped variable) trap_per_free = 1e4 # update this if val-2l.i changes +# Geometry +disc_area = np.pi*(3e3)**2 # 6 mm diameter gives 3e3 mum radius # ================================= Functions ================================ # @@ -195,9 +197,8 @@ def plot_unirradiated_desorption( simulation_time, simulation_temperature, simulation_flux = read_csv_from_TMAP8( simulation_file, ["time", "temperature", simulation_flux_column] ) - # at/mum^2/s -> at/m^2/s (x1e12); atomic D flux -> molecular D2 flux (/2) to match the - # RGA, which detects D2 (mass 4) and HD (mass 3) -- same convention as val-2d - simulation_flux = simulation_flux * 1e12 / 2 + # at/mum^2/s -> at/m^2/s (x1e12); + simulation_flux = simulation_flux * 1e12 # Map experimental times to temperatures using the simulation's T(t) ramp, # then truncate to the simulation time range to avoid extrapolation. @@ -314,12 +315,12 @@ def plot_unirradiated_desorption( relative_mass_conservation_residual = mass_conservation_residual / initial_inventory # --- Read individual mobile and trapped integrals for the stacked inventory plot --- -# total_mobile_retention : physical mobile inventory (at/µm²), no scaling needed +# total_mobile_retention : physical mobile inventory (at/µm²), so scale by disc cross-sectional area # total_trapped_retention : MOOSE stores the *rescaled* variable, so multiply by -# trap_per_free to recover the physical trapped inventory. -total_mobile_retention = simulation_TMAP8_data["total_mobile_retention"] +# trap_per_free and the cross-sectional area to recover the physical trapped inventory. +total_mobile_retention = simulation_TMAP8_data["total_mobile_retention"] * disc_area total_trapped_retention = ( - simulation_TMAP8_data["total_trapped_retention"] * trap_per_free + simulation_TMAP8_data["total_trapped_retention"] * trap_per_free * disc_area ) # --- Total deuterium inventory with temperature history --- @@ -372,7 +373,7 @@ def plot_unirradiated_desorption( )[0] ax.set_xlabel("Time (s)") -ax.set_ylabel(r"Deuterium inventory (atoms/$\mu m^2$)") +ax.set_ylabel(r"Deuterium inventory (atoms)") ax.set_xlim(0, simulation_time_TMAP8.max()) ax.set_ylim(bottom=0) ax.grid(visible=True, which="major", color="0.65", linestyle="--", alpha=0.3) diff --git a/test/tests/val-2l/val-2l.i b/test/tests/val-2l/val-2l.i index ec7804a1e..30f5a7d52 100644 --- a/test/tests/val-2l/val-2l.i +++ b/test/tests/val-2l/val-2l.i @@ -450,7 +450,7 @@ bulk_end = '${units 7.0 mum}' # bulk / deep-material interface and TMAP fit B solve_type = NEWTON line_search = 'none' nl_abs_tol = 1e-12 - nl_rel_tol = 1e-6 + nl_rel_tol = 1e-5 petsc_options_iname = '-pc_type' petsc_options_value = 'lu' end_time = ${simulation_time} From ede40af6af6c5ee420ea7162c121325ec0b7f5f5 Mon Sep 17 00:00:00 2001 From: "Butterworth, Evan" Date: Tue, 18 Aug 2026 10:15:21 -0600 Subject: [PATCH 07/12] Incorporating changes from code review: Removed deprecated animation plots, Added parameter file, Added headers to files to indicate their purpose, removed commented out lines from input file, fixed local python black formatting issues, To do: documentation, gold folder, V&V index page --- test/tests/val-2l/comparison_val-2l.py | 329 ++++++++++-------- .../tests/val-2l/plot_subplots_at_timestep.py | 97 ------ test/tests/val-2l/subplots_animation.py | 101 ------ .../tests/val-2l/trapped_profile_animation.py | 17 +- test/tests/val-2l/val-2l.i | 181 ++-------- test/tests/val-2l/val-2l.params | 64 ++++ 6 files changed, 287 insertions(+), 502 deletions(-) delete mode 100644 test/tests/val-2l/plot_subplots_at_timestep.py delete mode 100644 test/tests/val-2l/subplots_animation.py create mode 100644 test/tests/val-2l/val-2l.params diff --git a/test/tests/val-2l/comparison_val-2l.py b/test/tests/val-2l/comparison_val-2l.py index 23ce73a4a..45f88594d 100644 --- a/test/tests/val-2l/comparison_val-2l.py +++ b/test/tests/val-2l/comparison_val-2l.py @@ -1,3 +1,11 @@ +# This is the main comparison script for val-2l, and computes the following plots: + +# 1: plot_temperature_history() shows the temperature profile over the entire time of experiment, as well as an inlet graph that zooms in on temperature anomolies observed during the experiment +# 2: plot_mass_conservation() shows the evolution of the mass conservation residual relative to the initial mass at the start of the TDS experiment +# 3: plot_inventory() shows the deuterium present in traps and as a mobile concentration +# 4: plot_diffusivity_vs_temperature() shows the diffusivity as a function of reciprocal temperature, which should be linear +# 5: plot_unirradiated_desorption() plots the simulated against experimental desorbed flux from the upstream and downstream surfaces, performing RMSPE calculations to measure the goodness of fit + import matplotlib.pyplot as plt import numpy as np from matplotlib import gridspec @@ -11,11 +19,13 @@ script_folder = os.path.dirname(__file__) os.chdir(script_folder) -# Must match val-2l.i: trap_per_free = ... (rescaling factor for trapped variable) -trap_per_free = 1e4 # update this if val-2l.i changes +# Read trap_per_free directly from the simulation output (ConstantPostprocessor, +# execute_on = 'initial'), so this script stays in sync with val-2l.i automatically. +trap_per_free = pd.read_csv("val-2l_out.csv")["trap_per_free"].iloc[0] # Geometry -disc_area = np.pi*(3e3)**2 # 6 mm diameter gives 3e3 mum radius +disc_area = np.pi * (3e3) ** 2 # 6 mm diameter gives 3e3 mum radius + # ================================= Functions ================================ # @@ -31,9 +41,7 @@ def read_csv_from_TMAP8(file_name, parameter_names): """ if "/tmap8/doc/" in script_folder.lower(): # if in documentation folder csv_folder = f"../../../../test/tests/val-2l/gold/{file_name}" - else: # if in test folder - # csv_folder = f"./gold/{file_name}" csv_folder = f"./{file_name}" simulation_data = pd.read_csv(csv_folder) return np.array([simulation_data[name] for name in parameter_names]) @@ -89,28 +97,159 @@ def annotate_rmspe(simulated, reference, x_pos, y_pos): plt.text(x_pos, y_pos, "RMSPE = %.2f %%" % RMSPE, fontweight="bold") -def plot_conservation_of_mass(t, flux, mass, flux_label, title, filename): - """Plot accumulated boundary flux against total mass to verify conservation +def plot_temperature_history( + simulation_file="val-2l_out.csv", + filename="val-2l_temperature_history.png", + zoom_end=350, + zoom_ylim=(270, 370), +): + """Plot the simulated temperature ramp versus time with a zoomed inset + + The inset is placed in the lower-right corner of the main axes and shows + the first zoom_end seconds with fixed y-limits to highlight the early-time + deviation from the analytic ramp. Args: - t (float, ndarray): time array in days - flux (float, ndarray): accumulated boundary flux in µmol H - mass (float, ndarray): total H mass in domain in µmol H - flux_label (str): legend label for the flux line - title (str): plot title + simulation_file (str): TMAP8 CSV with "time" (s) and "temperature" (K) columns filename (str): output PNG filename + zoom_end (float): upper time limit (s) for the inset + zoom_ylim (tuple): (y_min, y_max) in K for the inset y-axis """ - fig = plt.figure(figsize=(10, 6)) - plt.plot(t, flux, label=flux_label) - plt.plot(t, mass, label="H Total Mass") - annotate_rmspe(flux, mass, t[-1] / 2, mass[-1] / 4) - plt.xlabel("Time (Days)") - plt.ylabel(r"$\mu$mol H") - plt.title(title) - plt.xlim(0, t.max()) - plt.ylim(0) - plt.legend() - plt.grid(True) + time, temperature = read_csv_from_TMAP8(simulation_file, ["time", "temperature"]) + + # ---- Full history ---- + fig, ax = plt.subplots(figsize=(6.5, 4.8)) + ax.plot( + time, + temperature, + color="tab:red", + linewidth=1.8, + label="TMAP8 temperature ramp", + ) + ax.set_xlabel("Time (s)") + ax.set_ylabel("Temperature (K)") + ax.set_xlim(0, time.max()) + ax.set_ylim(bottom=0) + ax.grid(visible=True, which="major", color="0.65", linestyle="--", alpha=0.3) + ax.minorticks_on() + ax.legend() + + # ---- Inset: lower-right, first zoom_end seconds ---- + # Coordinates are in axes-fraction space: [left, bottom, width, height] + ax_inset = ax.inset_axes([0.55, 0.05, 0.42, 0.42]) + mask = time <= zoom_end + ax_inset.plot(time[mask], temperature[mask], color="tab:red", linewidth=1.2) + ax_inset.set_xlim(0, zoom_end) + ax_inset.set_ylim(*zoom_ylim) + ax_inset.set_xlabel("Time (s)", fontsize=7) + ax_inset.set_ylabel("Temperature (K)", fontsize=7) + ax_inset.tick_params(labelsize=7) + ax_inset.grid(visible=True, which="major", color="0.65", linestyle="--", alpha=0.3) + + plt.tight_layout() + plt.savefig(filename, bbox_inches="tight", dpi=300) + plt.close(fig) + + +def plot_mass_conservation( + simulation_file="val-2l_out.csv", + filename="val-2l_mass_conservation.png", +): + """Plot the relative deuterium mass-balance residual over time + + The residual (inventory_change + released) is normalized by the initial inventory + M(0) and should remain close to zero if mass is conserved (cf. val-2k Stage 6). + + Args: + simulation_file (str): TMAP8 CSV with "time", "total_deuterium_retention", and + "deuterium_mass_conservation_residual" columns + filename (str): output PNG filename + """ + time, total_retention, residual = read_csv_from_TMAP8( + simulation_file, + ["time", "total_deuterium_retention", "deuterium_mass_conservation_residual"], + ) + initial_inventory = total_retention[0] + relative_residual = residual / initial_inventory + + fig, ax = plt.subplots(figsize=(6.5, 4.8)) + ax.plot(time, relative_residual, color="tab:blue", linewidth=1.8) + ax.axhline(0.0, color="0.35", linewidth=1.0, linestyle="--") + ax.set_xlabel("Time (s)") + ax.set_ylabel("Deuterium mass-balance residual / initial inventory (-)") + ax.set_xlim(0, time.max()) + ax.ticklabel_format(axis="y", style="sci", scilimits=(0, 0)) + ax.grid(visible=True, which="major", color="0.65", linestyle="--", alpha=0.3) + ax.minorticks_on() + plt.tight_layout() + plt.savefig(filename, bbox_inches="tight", dpi=300) + plt.close(fig) + + +def plot_inventory( + simulation_file="val-2l_out.csv", + filename="val-2l_inventory.png", +): + """Plot the stacked deuterium inventory (mobile + trapped) with temperature history + + The MOOSE postprocessors output surface densities (at/µm²). The mobile retention + is converted to atoms by multiplying by disc_area. The trapped variable is stored + rescaled by 1/trap_per_free in MOOSE, so it is multiplied by both trap_per_free + and disc_area to recover the physical atom count. + + Args: + simulation_file (str): TMAP8 CSV with "time", "temperature", + "total_mobile_retention", and "total_trapped_retention" columns + filename (str): output PNG filename + """ + time, temperature, mobile_raw, trapped_raw = read_csv_from_TMAP8( + simulation_file, + ["time", "temperature", "total_mobile_retention", "total_trapped_retention"], + ) + mobile = mobile_raw * disc_area + trapped = trapped_raw * trap_per_free * disc_area + + # Stacked bottom-up: largest / most stable contribution first + inventory_series = [ + ("Trapped D (trap 1, 1.35 eV)", trapped, plt.get_cmap("viridis")(0.45)), + ("Mobile D", mobile, plt.get_cmap("viridis")(0.95)), + ] + + fig, ax = plt.subplots(figsize=(6.5, 5.5)) + bottom = np.zeros_like(time) + legend_patches = [] + for label, values, color in inventory_series: + ax.fill_between(time, bottom, bottom + values, color=color, alpha=0.3) + ax.plot(time, bottom + values, color=color, linewidth=1.0) + bottom = bottom + values + legend_patches.append(Patch(color=color, alpha=0.5, label=label)) + + total_handle = ax.plot( + time, bottom, color="tab:green", linewidth=1.5, label="Total D inventory" + )[0] + + ax_T = ax.twinx() + temperature_handle = ax_T.plot( + time, + temperature, + linestyle="-", + color="k", + linewidth=1.5, + label="TMAP8 temperature history", + )[0] + + ax.set_xlabel("Time (s)") + ax.set_ylabel(r"Deuterium inventory (atoms)") + ax.set_xlim(0, time.max()) + ax.set_ylim(bottom=0) + ax.grid(visible=True, which="major", color="0.65", linestyle="--", alpha=0.3) + ax_T.set_ylabel("Temperature (K)") + ax.legend( + handles=[total_handle, temperature_handle] + legend_patches[::-1], + loc="lower right", + ) + ax.minorticks_on() + plt.tight_layout() plt.savefig(filename, bbox_inches="tight", dpi=300) plt.close(fig) @@ -142,7 +281,6 @@ def plot_diffusivity_vs_temperature( order = np.argsort(temperature) temperature, diffusivity = temperature[order], diffusivity[order] diffusivity_m2_s = diffusivity * 1e-12 # µm²/s -> m²/s - reciprocal_temperature = 1000.0 / temperature # 1000/T (1/K) fig, ax = plt.subplots(figsize=(8, 5)) @@ -197,7 +335,7 @@ def plot_unirradiated_desorption( simulation_time, simulation_temperature, simulation_flux = read_csv_from_TMAP8( simulation_file, ["time", "temperature", simulation_flux_column] ) - # at/mum^2/s -> at/m^2/s (x1e12); + # at/mum^2/s -> at/m^2/s (x1e12) simulation_flux = simulation_flux * 1e12 # Map experimental times to temperatures using the simulation's T(t) ramp, @@ -227,7 +365,6 @@ def plot_unirradiated_desorption( plt.grid(True) plt.tight_layout() plt.savefig(experiment_plot, bbox_inches="tight", dpi=300) - # plt.show() # ---- Plot 2: raw simulated desorption history ---- plt.figure(figsize=(10, 6)) @@ -242,14 +379,14 @@ def plot_unirradiated_desorption( plt.grid(True) plt.tight_layout() plt.savefig(simulation_plot, bbox_inches="tight", dpi=300) - # plt.show() - # Map simulated flux onto experimental temperature points for RMSPE - mapped_simulation_flux = numerical_solution_on_experiment_input( - experiment_temperature, simulation_temperature, simulation_flux + # Map simulated flux onto experimental time points for RMSPE. + # Interpolating over time (strictly monotone) rather than temperature avoids + # failures caused by flat holds or steps in the modified temperature profile. + mapped_simulation_flux = np.interp( + experiment_time, simulation_time, simulation_flux ) - tmin = 1000 - tmax = 2600 + tmin, tmax = 1000, 2600 rmspe_region = (experiment_time >= tmin) & (experiment_time <= tmax) # ---- Plot 3: simulation vs experiment with RMSPE ---- @@ -291,126 +428,12 @@ def plot_unirradiated_desorption( plt.grid(True) plt.tight_layout() plt.savefig(comparison_plot, bbox_inches="tight", dpi=300) - # plt.show() - - -# =========================== TMAP8 simulation data extraction ========================== # - -csv_folder = "val-2l_out.csv" -simulation_TMAP8_data = pd.read_csv(csv_folder) -simulation_time_TMAP8 = simulation_TMAP8_data["time"] - -### Conservation of Mass (replicating val-2k) ### -# val-2k computes the conservation residual in MOOSE (deuterium_mass_conservation_residual = -# inventory_change + released), then in Python normalizes it by the fixed initial inventory M(0) and -# plots the relative residual over time. We follow the same recipe here. M(0) is read from the t=0 row -# of total_deuterium_retention, which runs on INITIAL (cf. val-2k reading -# deuterium_inventory_in_sample_physical.iloc[0]). -total_deuterium_retention = simulation_TMAP8_data["total_deuterium_retention"] -temperature_history = simulation_TMAP8_data["temperature"] -mass_conservation_residual = simulation_TMAP8_data[ - "deuterium_mass_conservation_residual" -] -initial_inventory = total_deuterium_retention.iloc[0] -relative_mass_conservation_residual = mass_conservation_residual / initial_inventory - -# --- Read individual mobile and trapped integrals for the stacked inventory plot --- -# total_mobile_retention : physical mobile inventory (at/µm²), so scale by disc cross-sectional area -# total_trapped_retention : MOOSE stores the *rescaled* variable, so multiply by -# trap_per_free and the cross-sectional area to recover the physical trapped inventory. -total_mobile_retention = simulation_TMAP8_data["total_mobile_retention"] * disc_area -total_trapped_retention = ( - simulation_TMAP8_data["total_trapped_retention"] * trap_per_free * disc_area -) - -# --- Total deuterium inventory with temperature history --- -# Add one entry per species to inventory_series. They are stacked bottom-up with -# fill_between, so order matters: put the largest / most stable contribution first. -# Append a new tuple here when additional trap populations are added. -inventory_series = [ - ( - "Trapped D (trap 1, 1.35 eV)", - total_trapped_retention, - plt.get_cmap("viridis")(0.45), - ), - ("Mobile D", total_mobile_retention, plt.get_cmap("viridis")(0.95)), -] - -fig, ax = plt.subplots(figsize=(6.5, 5.5)) -inventory_bottom = np.zeros_like(total_deuterium_retention) -legend_patches = [] -for label, values, color in inventory_series: - ax.fill_between( - simulation_time_TMAP8, - inventory_bottom, - inventory_bottom + values, - color=color, - alpha=0.3, - ) - ax.plot( - simulation_time_TMAP8, inventory_bottom + values, color=color, linewidth=1.0 - ) - inventory_bottom = inventory_bottom + values - legend_patches.append(Patch(color=color, alpha=0.5, label=label)) - -total_inventory = inventory_bottom -total_handle = ax.plot( - simulation_time_TMAP8, - total_inventory, - color="tab:green", - linewidth=1.5, - label="Total D inventory", -)[0] - -ax_temperature = ax.twinx() -temperature_handle = ax_temperature.plot( - simulation_time_TMAP8, - temperature_history, - linestyle="-", - color="k", - linewidth=1.5, - label="TMAP8 temperature history", -)[0] - -ax.set_xlabel("Time (s)") -ax.set_ylabel(r"Deuterium inventory (atoms)") -ax.set_xlim(0, simulation_time_TMAP8.max()) -ax.set_ylim(bottom=0) -ax.grid(visible=True, which="major", color="0.65", linestyle="--", alpha=0.3) -ax_temperature.set_ylabel("Temperature (K)") -ax.legend( - handles=[total_handle, temperature_handle] + legend_patches[::-1], loc="lower right" -) -ax.minorticks_on() -plt.savefig("val-2l_inventory.png", bbox_inches="tight", dpi=300) -# plt.show() -plt.close(fig) - -# --- Relative deuterium mass-balance residual over time (cf. comparison_val-2k.py Stage 6) --- -fig, ax = plt.subplots(figsize=(6.5, 4.8)) -ax.plot( - simulation_time_TMAP8, - relative_mass_conservation_residual, - color="tab:blue", - linewidth=1.8, -) -ax.axhline(0.0, color="0.35", linewidth=1.0, linestyle="--") -ax.set_xlabel("Time (s)") -ax.set_ylabel("Deuterium mass-balance residual / initial inventory (-)") -ax.set_xlim(0, simulation_time_TMAP8.max()) -ax.ticklabel_format(axis="y", style="sci", scilimits=(0, 0)) -ax.grid(visible=True, which="major", color="0.65", linestyle="--", alpha=0.3) -ax.minorticks_on() -plt.savefig("val-2l_mass_conservation.png", bbox_inches="tight", dpi=300) -# plt.show() -plt.close(fig) - -TMAP8_file_base = "val-2l_comparison" - -############################ diffusivity vs temperature ############################ -# D(T) over the simulated TDS ramp, read from the temperature/diffusivity postprocessors -plot_diffusivity_vs_temperature() -############################ desorption: experiment + TMAP8 comparison ############################ -# Shimada 2010, unirradiated / 0 dpa (unirradiated_data.csv) + +# ========================== Plot calls ========================== # + +plot_temperature_history() +plot_mass_conservation() +plot_inventory() +plot_diffusivity_vs_temperature() plot_unirradiated_desorption() diff --git a/test/tests/val-2l/plot_subplots_at_timestep.py b/test/tests/val-2l/plot_subplots_at_timestep.py deleted file mode 100644 index 8bedf81bd..000000000 --- a/test/tests/val-2l/plot_subplots_at_timestep.py +++ /dev/null @@ -1,97 +0,0 @@ -import pandas as pd -import matplotlib.pyplot as plt -import matplotlib.animation as animation -import os - - -def subplot_bar_profile(timestep, data_dir="csv_data"): - # Load the data - gas_path = os.path.join( - data_dir, f"verification_RZ_solution_profile_gas_{timestep:04d}.csv" - ) - steel_path = os.path.join( - data_dir, f"verification_RZ_solution_profile_steel_{timestep:04d}.csv" - ) - - gas_df = pd.read_csv(gas_path, skipinitialspace=True) - steel_df = pd.read_csv(steel_path, skipinitialspace=True) - total_df = pd.read_csv( - os.path.join(data_dir, "verification_RZ.csv"), skipinitialspace=True - ) - - # Replace Correct Data point for gas concentration at interface due to bug in vpp - # print('Testing Gas') - # print(gas_df['H_mobile_gas'].iloc[-1]) - # print("Did Value Change???") - # gas_df.iloc[-1, gas_df.columns.get_loc('H_mobile_gas')] = corrective_df.iloc[timestep-1,corrective_df.columns.get_loc('Mobile_gas_interface')] - # print(gas_df['H_mobile_gas'].iloc[-1]) - - # print('Testing Steel') - # print(steel_df['H_mobile_steel'].iloc[-1]) - # print("Did Value Change???") - # steel_df.iloc[-1, steel_df.columns.get_loc('H_mobile_steel')] = corrective_df.iloc[timestep-1,corrective_df.columns.get_loc('Mobile_steel_edge_air')] - # print(steel_df['H_mobile_steel'].iloc[-1]) - - time = total_df["time"] - - # Get spatial coordinates - gas_x = gas_df["x"] - # print(type(gas_x)) - steel_x = steel_df["x"] - # print(gas_x) - # print(steel_x) - - # Extract variable names - gas_var = gas_df.columns[0] - steel_var = steel_df.columns[0] - # print(gas_var) - # print(steel_var) - - # Extract variable values - gas_values = gas_df[gas_var] - steel_values = steel_df[steel_var] - # print(gas_values) - # print(steel_values) - - # Plotting - fig, (ax1, ax2) = plt.subplots(2, 1, figsize=(12, 8), sharex=False) - - # Gas phase plot - ax1.plot(gas_x, gas_values, color="blue") - ax1.set_xlim(gas_x.min(), gas_x.max()) - ax1.set_ylim(gas_values.min() * 0.995, gas_values.max() * 1.005) - ax1.set_ylabel(r"Molecular H$_2$ Concentration in Gas ($\mu$mol/mm$^3$)") - ax1.set_title(f"Timestep {timestep} at Time: {time[timestep-1]:01.2f} days") - ax1.grid(True) - - # Steel phase plot - ax2.plot(steel_x, steel_values, color="green") - ax2.set_xlim(steel_x.min(), steel_x.max()) - ax2.set_ylim(steel_values.min(), steel_values.max()) - ax2.set_ylabel(r"Atomic H Concentration in Steel ($\mu$mol/mm^3)") - ax2.set_xlabel("Distance from Canister Center (mm)") - # ax2.set_title(f'Steel - Timestep {timestep}') - ax2.grid(True) - - plt.tight_layout() - plt.show() - - -if __name__ == "__main__": - import argparse - - parser = argparse.ArgumentParser( - description="Plot gas and steel concentration profiles for a given timestep." - ) - parser.add_argument( - "timestep", type=int, help="Timestep number (e.g., 1 for _0001.csv)" - ) - parser.add_argument( - "--data_dir", - type=str, - default="csv_data", - help="Directory containing the CSV files", - ) - - args = parser.parse_args() - subplot_bar_profile(args.timestep, data_dir=args.data_dir) diff --git a/test/tests/val-2l/subplots_animation.py b/test/tests/val-2l/subplots_animation.py deleted file mode 100644 index 40fe08429..000000000 --- a/test/tests/val-2l/subplots_animation.py +++ /dev/null @@ -1,101 +0,0 @@ -import pandas as pd -import matplotlib.pyplot as plt -import matplotlib.animation as animation -import os -import glob - -script_folder = os.path.dirname(__file__) -os.chdir(script_folder) - -# LineValueSampler output lives in a directory named after the VectorPostprocessor -# (val-2l.i: [VectorPostprocessors]/deuterium_mobile_concentration_profile). -profile_files = sorted( - glob.glob( - "deuterium_mobile_concentration_profile/" - "val-2l_out_deuterium_mobile_concentration_profile_*.csv" - ) -) -near_surface_limit_um = 20.0 # depth (um) shown in the lower zoom subplot -frame_stride = 5 # show every Nth timestep — keeps the movie fast to encode and compact - -# Time of each profile: file index i aligns with row i of the global CSV -# (both include the INITIAL step at t = 0). -times = pd.read_csv("val-2l_out.csv")["time"].values - -# Read each kept profile exactly once and cache its arrays, so the rest of the -# script (axis limits + every animation frame) reuses the data instead of -# re-parsing the CSVs. MOOSE writes a header-only file for the INITIAL step, so -# skip empties; subsample by frame_stride to avoid reading files we won't show. -frames = [] -for i, f in enumerate(profile_files): - if i >= len(times) or i % frame_stride != 0: - continue - df = pd.read_csv(f, skipinitialspace=True) - if df.shape[0] == 0: - continue - frames.append( - (df["x"].values, df["deuterium_mobile_concentration"].values, times[i]) - ) -if not frames: - raise FileNotFoundError("No non-empty concentration profile CSV files found.") - -# Fixed axis limits across all frames (computed from the cached arrays). -c_max = max(c.max() for _, c, _ in frames) * 1.05 -x_max_um = frames[0][0].max() - -fig, (ax1, ax2) = plt.subplots(2, 1, figsize=(10, 8), constrained_layout=True) - -# Build the line artists and static styling ONCE. The animation then only updates -# each line's data per frame instead of clearing and re-styling both axes. -# Markers sit on each mesh node (the NodalValueSampler points), so they reveal the -# graded element layout: dense at the surface, sparse in the bulk. -lines = [] -for ax, xlim, color in ( - (ax1, x_max_um, "steelblue"), - (ax2, near_surface_limit_um, "darkorange"), -): - (line,) = ax.plot( - [], - [], - color=color, - linewidth=1.5, - marker="o", - markersize=4, - markerfacecolor="white", - markeredgecolor=color, - markeredgewidth=1.0, - ) - ax.set_xlim(0, xlim) - ax.set_ylim(0, c_max) - ax.set_xlabel(r"Depth ($\mu$m)") - ax.set_ylabel(r"Concentration (at/$\mu$m$^3$)") - ax.grid(True) - lines.append((line, xlim)) -ax2.set_title(f"Near-surface (0 – {near_surface_limit_um:g} $\\mu$m)") -title = ax1.set_title("") - - -def animate(frame): - x, c, t = frames[frame] - artists = [] - for line, xlim in lines: - mask = x <= xlim - line.set_data(x[mask], c[mask]) - artists.append(line) - title.set_text(f"Deuterium in Tungsten — t = {t:7.1f} s") - artists.append(title) - return artists - - -ani = animation.FuncAnimation(fig, animate, frames=len(frames), interval=100, blit=True) - -# Use ffmpeg if available, otherwise fall back to Pillow (gif) -if animation.writers.is_available("ffmpeg"): - output_file = "val-2l_concentration_animation.mp4" - ani.save(output_file, writer="ffmpeg", fps=10) -else: - output_file = "val-2l_concentration_animation.gif" - ani.save(output_file, writer="pillow", fps=10) - -plt.close(fig) -print(f"Saved {output_file} ({len(frames)} frames)") diff --git a/test/tests/val-2l/trapped_profile_animation.py b/test/tests/val-2l/trapped_profile_animation.py index 0c9d7b72b..1485c81be 100644 --- a/test/tests/val-2l/trapped_profile_animation.py +++ b/test/tests/val-2l/trapped_profile_animation.py @@ -1,14 +1,14 @@ """ -animate_profiles_val-2l.py -Animates mobile and trapped deuterium concentration profiles over the TDS ramp. +This script animates mobile and trapped deuterium concentration profiles over the TDS ramp. -Layout (2 x 2): +Current Layout (2 x 2): [0,0] Mobile – whole domain (0–200 µm) [0,1] Mobile – near surface (0–1 µm) [1,0] Trapped – bulk & near surface (0–7 µm) [1,1] Trapped – near surface (0–1 µm) A temperature-ramp axes sits above the panels; a marker tracks the current frame. +This script is modular, so add and remove panels as traps are changed and added. """ import os @@ -19,10 +19,11 @@ import matplotlib.pyplot as plt import matplotlib.animation as animation -# ── Must match val-2l.i ───────────────────────────────────────────────────── # -TRAP_PER_FREE = 1 -FRAME_STRIDE = 10 -TRAP_BOUNDARY = 0.7 # µm: spatial extent of 1.35 eV trap (TMAP fit A) +# ── Trap information from val-2l.i ───────────────────────────────────────────────────── # +trap_per_free = pd.read_csv("val-2l_out.csv")["trap_per_free"].iloc[0] +TRAP_BOUNDARY = pd.read_csv("val-2l_out.csv")["trap_depth"].iloc[0] +FRAME_STRIDE = 25 # Add frame to animation every "FRAME_STRIDE"th timestep + # ── File paths ────────────────────────────────────────────────────────────── # MOBILE_DIR = "deuterium_mobile_concentration_profile" @@ -109,7 +110,7 @@ def frame_metadata(i): # ── Load profile series ───────────────────────────────────────────────── # mob_xs, mob_cs = load_profile_series(MOBILE_DIR, MOBILE_COL, scale=1.0) - trp_xs, trp_cs = load_profile_series(TRAPPED_DIR, TRAPPED_COL, scale=TRAP_PER_FREE) + trp_xs, trp_cs = load_profile_series(TRAPPED_DIR, TRAPPED_COL, scale=trap_per_free) n_frames = min(len(mob_xs), len(trp_xs)) frame_indices = range(0, n_frames, FRAME_STRIDE) diff --git a/test/tests/val-2l/val-2l.i b/test/tests/val-2l/val-2l.i index 30f5a7d52..4ac5abe04 100644 --- a/test/tests/val-2l/val-2l.i +++ b/test/tests/val-2l/val-2l.i @@ -1,82 +1,6 @@ -# Validation Problem #2l from TMAP4/TMAP7 V&V document - -# !include val-2l.params - -# Physical constants -kb = '${units 1.380649e-23 J/K}' # Boltzmann constant J/K - from PhysicalConstants.h -eV_to_J = '${units 1.602176634e-19 J/eV}' # Conversion coefficient from eV to Joules - from PhysicalConstants.h -kb_eV = '${units ${fparse kb / eV_to_J} eV/K}' # Boltzmann constant eV/K - -# Temporal Parameters -simulation_time = '${units 2 h -> s}' # 2 h TDS with temperature ramp -# simulation_time = '${units 1 h -> s}' # Should be enough time to model unirradiated case -dt_start = '${units 0.25 s}' -dt_max = '${units 1 s}' -dt_min = '${units 1e-6 s}' - -# Geometry -tungsten_thickness = '${units 0.2 mm -> mum}' # Tungsten disc thickness, Shimada et al. 2010 (p. S667, Section 2.1) - -# Gaussian-hill initial condition (diagnostic profile; not from Shimada et al. 2010). -gaussian_amplitude = '${units 1e26 at/m^3 -> at/mum^3}' # Peak concentration at the center (= 1 at/mum^3) -gaussian_center = '${fparse ${tungsten_thickness} / 5}' # Hill center -gaussian_sigma = '${fparse ${tungsten_thickness} / 20}' # Hill standard deviation - -# Temperature-dependent deuterium diffusivity used by Shimada et al. 2010 (p. S668, Section 3) -diffusivity_preexponential_factor = '${units 2.9e-7 m^2/s -> mum^2/s}' # D0 prefactor, Shimada et al. 2010 (p. S668) -diffusivity_activation_energy = '${units 0.39 eV}' # Diffusion activation energy, Shimada et al. 2010 (p. S668) - -# Recombination parameters: Shimada et al. 2010 (p. S668) -recombination_preexponential_factor = '${units 3.2e-15 m^4/at/s -> mum^4/at/s}' -recombination_energy = '${units 1.16 eV}' - -# Thermal parameters -temperature_tds_start = '${units 300 K}' # TDS ramp start (room temperature), Shimada et al. 2010 (p. S668, Figs. 2-4) -temperature_tds_end = '${units 1173 K}' # TDS ramp peak temperature, Shimada et al. 2010 (p. S668, Fig. 1) -temperature_rate = '${units ${fparse 10 / 60} K/s}' # TDS ramp rate of 10 K/min, Shimada et al. 2010 (p. S668, Fig. 1) - -# Trapping Parameters -trap_depth = '${units 0.7 mum}' -tungsten_density = '${units 6.25e28 at/m^3 -> at/mum^3}' # Ambrosek and Longhurst 2008 -trap_fraction = 0.04 -trap_site_density = '${fparse ${trap_fraction} * ${tungsten_density}}' -alpha_t_0 = '${units 9.1316e12 1/s}' # Pulled from val-2d since it is a similar example -trapping_energy = '${units ${fparse 0.39 / kb_eV} K}' # pulled from val-2d -trap_per_free = 1e4 # User specified - -# Detrapping Parameters -alpha_r_0 = '${units 8.4e12 1/s}' # val-2d -detrapping_energy = '${units ${fparse 1.35 / kb_eV} K}' # Unclear if Shimida 2011 means trapping or detrapping energy - -# TMAP7 fit A Trapping Parameters - -# Mesh Parameters (Ensure that all trap endpoints have a node) -depth_A = '${units 0.7 mum}' # TMAP fit A trap boundary -depth_C = '${units 1.2 mum}' # TMAP fit C trap boundary (near-surface region end) -depth_E = '${units 2.5 mum}' # TMAP fit E trap boundary (neutron-irradiated) -near_end = '${units 1.0 mum}' # near-surface / bulk interface -bulk_end = '${units 7.0 mum}' # bulk / deep-material interface and TMAP fit B trap boundary - -# ── Segment widths (derived — do not edit directly) ──────────────────────── -# Segment layout: -# [0, depth_A ] : near-surface fine (0.7 mum) -# [depth_A, near_end] : near-surface remainder (0.3 mum) -# [near_end, depth_C] : bulk start (0.2 mum) -# [depth_C, depth_E ] : bulk middle (1.3 mum) -# [depth_E, bulk_end] : bulk end (4.5 mum) -# [bulk_end, W_thick] : deep material (193 mum) - seg1 = '${fparse ${depth_A}}' - seg2 = '${fparse ${near_end} - ${depth_A}}' - seg3 = '${fparse ${depth_C} - ${near_end}}' - seg4 = '${fparse ${depth_E} - ${depth_C}}' - seg5 = '${fparse ${bulk_end} - ${depth_E}}' - seg6 = '${fparse ${tungsten_thickness} - ${bulk_end}}' - - # ── Element counts ───────────────────────────────────────────────────────── - # nx_scale uniformly refines all segments. Per-segment multipliers set the - # relative resolution. - - nx_scale = 20 +# This input file serves as the main phyiscs model of deuterium permeation in neutron-irradiated tungsten. + +!include val-2l.params [Mesh] [temp_mesh] @@ -89,7 +13,6 @@ bulk_end = '${units 7.0 mum}' # bulk / deep-material interface and TMAP fit B ${fparse 5 * ${nx_scale}} ${fparse 5 * ${nx_scale}} ${fparse 10 * ${nx_scale}}' - # subdomain_id = '1 2 2 2 2 2' # block 1 = trap region, block 2 = bulk [] [tungsten_disc] type = RenameBoundaryGenerator @@ -108,12 +31,6 @@ bulk_end = '${units 7.0 mum}' # bulk / deep-material interface and TMAP fit B [] [ICs] - # # Gaussian hill centered on the sample midplane (diagnostic, see header). - # [mobile_ic] - # type = FunctionIC - # variable = mobile - # function = gaussian_hill_initial_condition - # [] [trapped_ic] type = FunctionIC function = trapped_initial_condition @@ -170,8 +87,7 @@ bulk_end = '${units 7.0 mum}' # bulk / deep-material interface and TMAP fit B [release_1] type = ReleasingNodalKernel variable = trapped_1 - # alpha_r = '${alpha_r_0}' - alpha_r = '${alpha_r_0}' # Trapping is restricted to trapped region, so this variable beyond the trapped region will have no deuterium to release. + alpha_r = '${alpha_r_0}' detrapping_energy = '${detrapping_energy}' temperature = 'temperature' [] @@ -179,7 +95,6 @@ bulk_end = '${units 7.0 mum}' # bulk / deep-material interface and TMAP fit B [AuxVariables] [temperature] - initial_condition = ${temperature_tds_start} [] [] @@ -195,7 +110,6 @@ bulk_end = '${units 7.0 mum}' # bulk / deep-material interface and TMAP fit B [BCs] active = 'left_recombination_flux right_recombination_flux' - # active = 'left right' # Infinite recombination [left] @@ -264,19 +178,13 @@ bulk_end = '${units 7.0 mum}' # bulk / deep-material interface and TMAP fit B [] [Functions] - # Gaussian hill, peak gaussian_amplitude at gaussian_center, standard deviation gaussian_sigma: - # c(x) = A * exp(-(x - x0)^2 / (2 sigma^2)) - [gaussian_hill_initial_condition] - type = ParsedFunction - expression = '${gaussian_amplitude} * exp(-(x - ${gaussian_center})^2 / (2 * ${gaussian_sigma}^2))' - [] - # Linear TDS ramp from temperature_tds_start to temperature_tds_end and hold until end of simulation [temperature_function] - type = ParsedFunction - expression = 'if(t<(${temperature_tds_end} - ${temperature_tds_start}) / - ${temperature_rate}, ${temperature_tds_start} + ${temperature_rate} * t, - ${temperature_tds_end})' + type = PiecewiseLinear + data_file = temperature_data.csv + x_title = time + y_title = temperature + format = columns [] [trapped_initial_condition] @@ -284,7 +192,6 @@ bulk_end = '${units 7.0 mum}' # bulk / deep-material interface and TMAP fit B expression = 'if(x < ${trap_depth}, ${trap_site_density} / ${trap_per_free}, 0.0)' [] - # Fed to TrappingNodalKernel [trap_distribution_function] type = ParsedFunction expression = 'if(x < ${trap_depth}, ${trap_fraction}, 0.0)' @@ -294,33 +201,36 @@ bulk_end = '${units 7.0 mum}' # bulk / deep-material interface and TMAP fit B [Postprocessors] - [trap_region] + [trap_depth] type = ConstantPostprocessor value = ${trap_depth} execute_on = 'initial' outputs = csv [] - ### Temperature ramp and resulting diffusivity (for post-processing/plots) ### + [trap_per_free] + type = ConstantPostprocessor + value = ${trap_per_free} + execute_on = 'initial' + outputs = csv + [] - [temperature] # K + [temperature] type = FunctionValuePostprocessor function = temperature_function outputs = csv execute_on = 'INITIAL TIMESTEP_END' [] - [diffusivity_pp] # mum^2/s; uniform in space, depends only on temperature + [diffusivity_pp] type = ADElementAverageMaterialProperty mat_prop = diffusivity_mat outputs = csv [] - ### Conservation of Mass (replicates val-2k_base.i: residual computed in MOOSE) ### + ### Conservation of Mass ### - # Total deuterium inventory currently in the sample, M(t) (cf. val-2k deuterium_inventory_in_sample). - # Runs on INITIAL so its t=0 row is the initial inventory M(0), which the comparison script reads to - # normalize the residual. + # Total deuterium inventory currently in the sample, M(t) [total_mobile_retention] type = ElementIntegralVariablePostprocessor @@ -328,15 +238,12 @@ bulk_end = '${units 7.0 mum}' # bulk / deep-material interface and TMAP fit B execute_on = 'INITIAL TIMESTEP_END' [] - [total_trapped_retention] + [total_trapped_retention] # Physical concentration = variable * trap_per_free type = ElementIntegralVariablePostprocessor variable = trapped_1 - # Physical concentration = variable * trap_per_free - # Handle scaling in post-processing script, or use ParsedPostprocessor to multiply. execute_on = 'INITIAL TIMESTEP_END' [] - # Replace old total_deuterium_retention: [total_deuterium_retention] type = ParsedPostprocessor expression = 'total_mobile_retention + total_trapped_retention * ${trap_per_free}' @@ -345,9 +252,17 @@ bulk_end = '${units 7.0 mum}' # bulk / deep-material interface and TMAP fit B outputs = csv [] - # Desorption flux through each face (upstream_flux is also used for the experimental desorption - # comparison). With c = 0 Dirichlet faces and c > 0 inside, -D grad(c).n is positive (outward) on - # each face, so the two are the per-face desorption rates. + # Change in domain inventory relative to the initial mass, M(t) - M(0). + [deuterium_inventory_change] # atoms / mum^2 + type = ChangeOverTimePostprocessor + postprocessor = total_deuterium_retention + change_with_respect_to_initial = true + execute_on = 'INITIAL TIMESTEP_END' + outputs = none + [] + + # Desorption flux through upstream and downstream surfaces + [upstream_flux] type = ADSideDiffusiveFluxIntegral boundary = 'upstream' @@ -364,15 +279,14 @@ bulk_end = '${units 7.0 mum}' # bulk / deep-material interface and TMAP fit B execute_on = 'TIMESTEP_END' [] - # Total desorption rate through both faces (cf. val-2k deuterium_release_flux_total). - [deuterium_release_flux_total] # atoms / mum^2 / s + [deuterium_release_flux_total] type = SumPostprocessor values = 'upstream_flux downstream_flux' execute_on = 'TIMESTEP_END' outputs = csv [] - # Cumulative deuterium released through both faces (time-integrated release rate), = M(0) - M(t). + # Cumulative deuterium released through both surfaces [deuterium_released_physical] # atoms / mum^2 type = TimeIntegratedPostprocessor value = deuterium_release_flux_total @@ -381,25 +295,12 @@ bulk_end = '${units 7.0 mum}' # bulk / deep-material interface and TMAP fit B outputs = csv [] - # Change in domain inventory relative to the initial state, M(t) - M(0). - [deuterium_inventory_change] # atoms / mum^2 - type = ChangeOverTimePostprocessor - postprocessor = total_deuterium_retention - change_with_respect_to_initial = true - execute_on = 'INITIAL TIMESTEP_END' - outputs = none - [] - - # Conservation residual = (M(t) - M(0)) + released; ideally 0 at all times. The comparison script - # divides this by the initial inventory M(0) to report the relative mass-balance residual (cf. - # val-2k deuterium_mass_conservation_residual). The decomposition generalizes directly to - # trapped + mobile once traps land: sum them into total_deuterium_retention. + # Conservation residual = (M(t) - M(0)) + released; ideally 0 at all times. [deuterium_mass_conservation_residual] # atoms / mum^2 - type = ParsedPostprocessor - expression = 'deuterium_inventory_change + deuterium_released_physical' - pp_names = 'deuterium_inventory_change deuterium_released_physical' + type = SumPostprocessor + values = 'deuterium_inventory_change deuterium_released_physical' execute_on = 'TIMESTEP_END' - outputs = 'csv' + outputs = csv [] [] @@ -463,11 +364,5 @@ bulk_end = '${units 7.0 mum}' # bulk / deep-material interface and TMAP fit B optimal_iterations = 5 growth_factor = 1.1 cutback_factor_at_failure = 0.5 - # timestep_limiting_function = temperature_function - # max_function_change = 0.2 [] - # [TimeStepper] - # type = ConstantDT - # dt = ${dt_start} - # [] [] diff --git a/test/tests/val-2l/val-2l.params b/test/tests/val-2l/val-2l.params new file mode 100644 index 000000000..1c5df104e --- /dev/null +++ b/test/tests/val-2l/val-2l.params @@ -0,0 +1,64 @@ +# Database of physical and numerical constants used in simulation + +# Physical constants +kb = '${units 1.380649e-23 J/K}' # Boltzmann constant J/K - from PhysicalConstants.h +eV_to_J = '${units 1.602176634e-19 J/eV}' # Conversion coefficient from eV to Joules - from PhysicalConstants.h +kb_eV = '${units ${fparse kb / eV_to_J} eV/K}' # Boltzmann constant eV/K + +# Temporal Parameters +simulation_time = '${units 2 h -> s}' +dt_start = '${units 0.25 s}' +dt_max = '${units 1 s}' +dt_min = '${units 1e-6 s}' + +# Geometry +tungsten_thickness = '${units 0.2 mm -> mum}' # Tungsten disc sample thickness, Shimada et al. 2010 (p. S667, Section 2.1) + +# Temperature-dependent deuterium diffusivity from Causey 2002 +diffusivity_preexponential_factor = '${units 2.9e-7 m^2/s -> mum^2/s}' +diffusivity_activation_energy = '${units 0.39 eV}' + +# Recombination parameters: Anderl et al. 1992 +recombination_preexponential_factor = '${units 3.2e-15 m^4/at/s -> mum^4/at/s}' +recombination_energy = '${units 1.16 eV}' + +# Trapping Parameters +trap_depth = '${units 0.7 mum}' # TMAP7 fit A Shimida et al. 2010 +tungsten_density = '${units 6.25e28 at/m^3 -> at/mum^3}' # Ambrosek and Longhurst 2008 +trap_fraction = 0.04 # TMAP7 fit A Shimida et al. 2010 +trap_site_density = '${fparse ${trap_fraction} * ${tungsten_density}}' +alpha_t_0 = '${units 9.1316e12 1/s}' # Ambrosek and Longhurst 2008 (val-2d) +trapping_energy = '${units ${fparse 0.39 / kb_eV} K}' # Ambrosek and Longhurst 2008 (val-2d) +trap_per_free = 1e4 # User specified + +# Detrapping Parameters +alpha_r_0 = '${units 8.4e12 1/s}' # Ambrosek and Longhurst 2008 (val-2d) +detrapping_energy = '${units ${fparse 1.35 / kb_eV} K}' # TMAP7 fit A Shimida et al. 2010 + +# Mesh Parameters (Ensure that all trap endpoints have a node) +depth_A = '${units 0.7 mum}' # TMAP7 fit A trap boundary +depth_C = '${units 1.2 mum}' # TMAP7 fit C trap boundary (near-surface region end) +depth_E = '${units 2.5 mum}' # TMAP7 fit E trap boundary (neutron-irradiated) +near_end = '${units 1.0 mum}' # near-surface / bulk interface +bulk_end = '${units 7.0 mum}' # bulk / deep-material interface and TMAP fit B trap boundary + +# ── Segment widths (derived — do not edit directly) ──────────────────────── +# Segment layout: +# [0, depth_A ] : near-surface fine (0.7 mum) +# [depth_A, near_end] : near-surface remainder (0.3 mum) +# [near_end, depth_C] : bulk start (0.2 mum) +# [depth_C, depth_E ] : bulk middle (1.3 mum) +# [depth_E, bulk_end] : bulk end (4.5 mum) +# [bulk_end, W_thick] : deep material (193 mum) + seg1 = '${fparse ${depth_A}}' + seg2 = '${fparse ${near_end} - ${depth_A}}' + seg3 = '${fparse ${depth_C} - ${near_end}}' + seg4 = '${fparse ${depth_E} - ${depth_C}}' + seg5 = '${fparse ${bulk_end} - ${depth_E}}' + seg6 = '${fparse ${tungsten_thickness} - ${bulk_end}}' + + # ── Element counts ───────────────────────────────────────────────────────── + # nx_scale uniformly refines all segments. Per-segment multipliers set the + # relative resolution. + + nx_scale = 20 From a44663a9688e2003fe77254d1f7d0bad5f421b60 Mon Sep 17 00:00:00 2001 From: "Butterworth, Evan" Date: Fri, 28 Aug 2026 10:50:57 -0600 Subject: [PATCH 08/12] Added new case to validation index, and changed capitalization of titles to match verification and benchmarking cases. Cleaned up and added description to comparison python file, added gold file with current simulation results, modifying timestepper to keep test shorter while still capturing physics, added CSVDiff and RunApp tests --- .../verification_and_validation/index.md | 9 +- test/tests/val-2l/comparison_val-2l.py | 87 ++----- test/tests/val-2l/gold/val-2l_out.csv | 231 ++++++++++++++++++ test/tests/val-2l/tests | 8 - test/tests/val-2l/val-2l.i | 19 +- test/tests/val-2l/val-2l.params | 7 +- 6 files changed, 276 insertions(+), 85 deletions(-) create mode 100644 test/tests/val-2l/gold/val-2l_out.csv diff --git a/doc/content/verification_and_validation/index.md b/doc/content/verification_and_validation/index.md index 16d8977c7..0300c9eb5 100644 --- a/doc/content/verification_and_validation/index.md +++ b/doc/content/verification_and_validation/index.md @@ -43,8 +43,8 @@ TMAP8 also contains [example cases](examples/tmap_index.md), which showcase how | Case | Title | | ------- | ---------------------------------------------------------------------------------- | | ver-1fc | [Conduction in Composite Structure with Constant Surface Temperatures](ver-1fc.md) | -| fuel cycle 1 | [Tritium fuel cycle in fusion energy plant](examples/fuel_cycle_Abdou/index.md) from [!cite](Abdou2021) | -| fuel cycle 2 | [Tritium fuel cycle in fusion energy plant](examples/fuel_cycle_Meschini/index.md) from [!cite](meschini2023modeling) | +| fuel cycle 1 | [Tritium Fuel Cycle in Fusion Energy Plant](examples/fuel_cycle_Abdou/index.md) from [!cite](Abdou2021) | +| fuel cycle 2 | [Tritium Fuel Cycle in Fusion Energy Plant](examples/fuel_cycle_Meschini/index.md) from [!cite](meschini2023modeling) | # List of validation cases @@ -56,7 +56,8 @@ TMAP8 also contains [example cases](examples/tmap_index.md), which showcase how | val-2c | [Test Cell Release Experiment](val-2c.md) | | val-2d | [Thermal Desorption Spectroscopy on Tungsten](val-2d.md) | | val-2e | [Co-permeation of H$_2$ and D$_2$ through Pd](val-2e.md) | -| val-2f | [Modelling self-damaged tungsten effects on deuterium transport](val-2f.md) | +| val-2f | [Modelling Self-damaged Tungsten Effects on Deuterium Transport](val-2f.md) | | val-2g | [Deuterium Transport in Proton-Conducting Ceramics](val-2g.md) | -| val-2k | [Oxide effects on deuterium release from self-irradiated tungsten](val-2k.md) | +| val-2k | [Oxide Effects on Deuterium Release from Self-irradiated Tungsten](val-2k.md) | +| val-2l | [Deuterium Retention in Neutron-irradiated Tungsten](val-2l.md) | | val-2j | [Tritium TDS from Li$_2$TiO$_3$ Solid Breeder](val-2j.md) | diff --git a/test/tests/val-2l/comparison_val-2l.py b/test/tests/val-2l/comparison_val-2l.py index 45f88594d..fd32b4447 100644 --- a/test/tests/val-2l/comparison_val-2l.py +++ b/test/tests/val-2l/comparison_val-2l.py @@ -19,10 +19,6 @@ script_folder = os.path.dirname(__file__) os.chdir(script_folder) -# Read trap_per_free directly from the simulation output (ConstantPostprocessor, -# execute_on = 'initial'), so this script stays in sync with val-2l.i automatically. -trap_per_free = pd.read_csv("val-2l_out.csv")["trap_per_free"].iloc[0] - # Geometry disc_area = np.pi * (3e3) ** 2 # 6 mm diameter gives 3e3 mum radius @@ -202,12 +198,18 @@ def plot_inventory( "total_mobile_retention", and "total_trapped_retention" columns filename (str): output PNG filename """ - time, temperature, mobile_raw, trapped_raw = read_csv_from_TMAP8( + time, temperature, mobile_raw, trapped_raw, trap_per_free = read_csv_from_TMAP8( simulation_file, - ["time", "temperature", "total_mobile_retention", "total_trapped_retention"], + [ + "time", + "temperature", + "total_mobile_retention", + "total_trapped_retention", + "trap_per_free", + ], ) mobile = mobile_raw * disc_area - trapped = trapped_raw * trap_per_free * disc_area + trapped = trapped_raw * trap_per_free[0] * disc_area # Stacked bottom-up: largest / most stable contribution first inventory_series = [ @@ -300,20 +302,12 @@ def plot_unirradiated_desorption( experiment_file="unirradiated_data.csv", simulation_file="val-2l_out.csv", simulation_flux_column="deuterium_release_flux_total", - experiment_plot="val-2l_experimental_desorption.png", - simulation_plot="val-2l_simulated_desorption.png", comparison_plot="val-2l_comparison_desorption.png", ): - """Plot the Shimada (2010) unirradiated desorption data and the TMAP8 comparison + """Plot the Shimada (2010) unirradiated desorption data against TMAP8 - Produces three figures: - 1. The digitized experimental desorbed-flux history (Shimada 2010, - unirradiated / 0 dpa): temperature (K) versus desorbed flux (m^-2 s^-1). - Experimental times are mapped to temperatures via the simulation's T(t) ramp. - 2. The raw TMAP8 simulated desorbed-flux history: temperature (K) versus - desorbed flux (m^-2 s^-1). - 3. The TMAP8 simulated desorbed flux mapped onto the experimental temperature - points, overlaid on the experimental data and annotated with the RMSPE. + The simulated and experimental desorbed fluxes are plotted versus temperature, + with the RMSPE annotated over the region tmin–tmax seconds. Args: experiment_file (str): two-column, header-less CSV of @@ -321,25 +315,18 @@ def plot_unirradiated_desorption( simulation_file (str): TMAP8 CSV output holding "time", "temperature", and the desorbed-flux column simulation_flux_column (str): name of the desorbed-flux column in - simulation_file. TMAP8 reports it in at/mum^2/s; it is converted to - at/m^2/s to match the experiment. - experiment_plot (str): output PNG filename for plot 1 - simulation_plot (str): output PNG filename for plot 2 - comparison_plot (str): output PNG filename for plot 3 + simulation_file. TMAP8 reports it in at/µm^2/s; converted to at/m^2/s. + comparison_plot (str): output PNG filename """ - # experiment: header-less (time [s], desorbed flux [m^-2 s^-1]) experiment = np.loadtxt(experiment_file, delimiter=",") experiment_time, experiment_flux = experiment[:, 0], experiment[:, 1] - # simulation data: time, temperature, and desorbed flux simulation_time, simulation_temperature, simulation_flux = read_csv_from_TMAP8( simulation_file, ["time", "temperature", simulation_flux_column] ) - # at/mum^2/s -> at/m^2/s (x1e12) - simulation_flux = simulation_flux * 1e12 + simulation_flux = simulation_flux * 1e12 # at/µm^2/s -> at/m^2/s - # Map experimental times to temperatures using the simulation's T(t) ramp, - # then truncate to the simulation time range to avoid extrapolation. + # Truncate experiment to simulation time range, then map times to temperatures in_sim_range = experiment_time <= simulation_time.max() experiment_time = experiment_time[in_sim_range] experiment_flux = experiment_flux[in_sim_range] @@ -347,49 +334,13 @@ def plot_unirradiated_desorption( experiment_time, simulation_time, simulation_temperature ) - # ---- Plot 1: experimental desorption history ---- - plt.figure(figsize=(10, 6)) - plt.plot( - experiment_temperature, - experiment_flux, - "ro", - label="Experiment (Shimada 2010, 0 dpa)", - ) - plt.xlabel("Temperature (K)") - plt.ylabel(r"Desorbed flux (m$^{-2}$s$^{-1}$)") - plt.title("Unirradiated deuterium desorption") - plt.xlim(experiment_temperature.min(), experiment_temperature.max()) - plt.ylim(0) - plt.ticklabel_format(axis="y", style="sci", scilimits=(0, 0)) - plt.legend() - plt.grid(True) - plt.tight_layout() - plt.savefig(experiment_plot, bbox_inches="tight", dpi=300) - - # ---- Plot 2: raw simulated desorption history ---- - plt.figure(figsize=(10, 6)) - plt.plot(simulation_temperature, simulation_flux, "b-", label="TMAP8 (0 dpa)") - plt.xlabel("Temperature (K)") - plt.ylabel(r"Desorbed flux (m$^{-2}$s$^{-1}$)") - plt.title("Unirradiated deuterium desorption: TMAP8") - plt.xlim(simulation_temperature.min(), simulation_temperature.max()) - plt.ylim(0) - plt.ticklabel_format(axis="y", style="sci", scilimits=(0, 0)) - plt.legend() - plt.grid(True) - plt.tight_layout() - plt.savefig(simulation_plot, bbox_inches="tight", dpi=300) - - # Map simulated flux onto experimental time points for RMSPE. - # Interpolating over time (strictly monotone) rather than temperature avoids - # failures caused by flat holds or steps in the modified temperature profile. + # Interpolate simulated flux at experimental time points for RMSPE mapped_simulation_flux = np.interp( experiment_time, simulation_time, simulation_flux ) - tmin, tmax = 1000, 2600 + tmin, tmax = 800, 2800 rmspe_region = (experiment_time >= tmin) & (experiment_time <= tmax) - # ---- Plot 3: simulation vs experiment with RMSPE ---- plt.figure(figsize=(10, 6)) plt.plot( experiment_temperature, @@ -415,7 +366,7 @@ def plot_unirradiated_desorption( annotate_rmspe( mapped_simulation_flux[rmspe_region], experiment_flux[rmspe_region], - experiment_temperature.mean(), + experiment_temperature[rmspe_region].mean(), experiment_flux.max() / 4, ) plt.xlabel("Temperature (K)") diff --git a/test/tests/val-2l/gold/val-2l_out.csv b/test/tests/val-2l/gold/val-2l_out.csv new file mode 100644 index 000000000..f83ad05d8 --- /dev/null +++ b/test/tests/val-2l/gold/val-2l_out.csv @@ -0,0 +1,231 @@ +time,deuterium_mass_conservation_residual,deuterium_release_flux_total,deuterium_released_physical,diffusivity_pp,downstream_flux,temperature,total_deuterium_retention,total_mobile_retention,total_trapped_retention,trap_depth,trap_per_free,upstream_flux +0,0,0,0,0,0,300,1745625000,0,174562.5,0.7,10000,0 +60,-0.016543280869252,-0.00055141885378383,-0.016542565613515,0.081411612531829,3.4008919231526e-41,300,1745625000,18.124407239961,174562.49818756,0.7,10000,-0.00055141885378383 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a/test/tests/val-2l/tests b/test/tests/val-2l/tests index e9827f516..a12735307 100644 --- a/test/tests/val-2l/tests +++ b/test/tests/val-2l/tests @@ -8,14 +8,6 @@ csvdiff = val-2l_out.csv requirement = 'The system shall be able to model deuterium transport through irradiated tungsten for comparison with experimental results.' [] - [val-2l_exodiff] - type = Exodiff - input = 'val-2l.i' - exodiff = val-2l_out.e - prereq = val-2l_csvdiff - should_execute = false # this test relies on the output files from val-2a_csvdiff, so it shouldn't be run twice - requirement = 'The system shall be able to model deuterium transport through irradiated tungsten for comparison with experimental results.' - [] [val-2l_comparison] type = RunCommand command = 'python3 comparison_val-2l.py' diff --git a/test/tests/val-2l/val-2l.i b/test/tests/val-2l/val-2l.i index 4ac5abe04..9ceaa34bc 100644 --- a/test/tests/val-2l/val-2l.i +++ b/test/tests/val-2l/val-2l.i @@ -197,6 +197,14 @@ expression = 'if(x < ${trap_depth}, ${trap_fraction}, 0.0)' [] + [timestep_limiting_function] + type = ParsedFunction + expression = 'if(T >= 450 & T <= 750, dt_fine, dt_max)' + symbol_names = 'T dt_fine dt_max' + symbol_values = 'temperature_function + ${dt_fine} + ${dt_max}' + [] [] [Postprocessors] @@ -324,9 +332,10 @@ [Outputs] file_base = 'val-2l_out' csv = true + perf_graph = true [exodus] type = Exodus - output_material_properties = true + # output_material_properties = true [] [profile_csv] type = CSV @@ -358,11 +367,17 @@ automatic_scaling = true dtmin = ${dt_min} dtmax = ${dt_max} - [TimeStepper] + [TimeSteppers] + [iteration_dt] type = IterationAdaptiveDT dt = ${dt_start} optimal_iterations = 5 growth_factor = 1.1 cutback_factor_at_failure = 0.5 + [] + [limiting_dt] + type = FunctionDT + function = timestep_limiting_function + [] [] [] diff --git a/test/tests/val-2l/val-2l.params b/test/tests/val-2l/val-2l.params index 1c5df104e..3057e8c6e 100644 --- a/test/tests/val-2l/val-2l.params +++ b/test/tests/val-2l/val-2l.params @@ -7,9 +7,10 @@ kb_eV = '${units ${fparse kb / eV_to_J} eV/K}' # Boltzmann constant eV/K # Temporal Parameters simulation_time = '${units 2 h -> s}' -dt_start = '${units 0.25 s}' -dt_max = '${units 1 s}' -dt_min = '${units 1e-6 s}' +dt_start = '${units 60 s}' +dt_max = '${units 300 s}' +dt_min = '${units 1e-4 s}' +dt_fine = '${units 10 s}' # Geometry tungsten_thickness = '${units 0.2 mm -> mum}' # Tungsten disc sample thickness, Shimada et al. 2010 (p. S667, Section 2.1) From ff65024d679dc197bcd88449a4e811df22d4931e Mon Sep 17 00:00:00 2001 From: "Butterworth, Evan" Date: Fri, 28 Aug 2026 10:59:03 -0600 Subject: [PATCH 09/12] Putting V&V Cases in alphabetical order --- doc/content/verification_and_validation/index.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/doc/content/verification_and_validation/index.md b/doc/content/verification_and_validation/index.md index 0300c9eb5..d52aadedd 100644 --- a/doc/content/verification_and_validation/index.md +++ b/doc/content/verification_and_validation/index.md @@ -58,6 +58,6 @@ TMAP8 also contains [example cases](examples/tmap_index.md), which showcase how | val-2e | [Co-permeation of H$_2$ and D$_2$ through Pd](val-2e.md) | | val-2f | [Modelling Self-damaged Tungsten Effects on Deuterium Transport](val-2f.md) | | val-2g | [Deuterium Transport in Proton-Conducting Ceramics](val-2g.md) | +| val-2j | [Tritium TDS from Li$_2$TiO$_3$ Solid Breeder](val-2j.md) | | val-2k | [Oxide Effects on Deuterium Release from Self-irradiated Tungsten](val-2k.md) | | val-2l | [Deuterium Retention in Neutron-irradiated Tungsten](val-2l.md) | -| val-2j | [Tritium TDS from Li$_2$TiO$_3$ Solid Breeder](val-2j.md) | From 8083364c3191d88017b15197152d82e35f620868 Mon Sep 17 00:00:00 2001 From: "Butterworth, Evan" Date: Fri, 28 Aug 2026 14:58:33 -0600 Subject: [PATCH 10/12] Added new relevant sources and a documentation page. Cleaned up the comparison script and added digitized data to gold file --- doc/content/bib/tmap8.bib | 27 + .../verification_and_validation/val-2l.md | 174 + test/tests/val-2l/comparison_val-2l.py | 16 +- test/tests/val-2l/gold/temperature_data.csv | 6990 +++++++++++++++++ test/tests/val-2l/gold/unirradiated_data.csv | 126 + 5 files changed, 7329 insertions(+), 4 deletions(-) create mode 100644 test/tests/val-2l/gold/temperature_data.csv create mode 100644 test/tests/val-2l/gold/unirradiated_data.csv diff --git a/doc/content/bib/tmap8.bib b/doc/content/bib/tmap8.bib index d8d2cbb70..c0a459def 100644 --- a/doc/content/bib/tmap8.bib +++ b/doc/content/bib/tmap8.bib @@ -7,6 +7,20 @@ @book{Fogler1999 year = {1999}, } +@article{Shimada2011, +title = {First result of deuterium retention in neutron-irradiated tungsten exposed to high flux plasma in TPE}, +journal = {Journal of Nuclear Materials}, +volume = {415}, +number = {1, Supplement }, +pages = {S667-S671}, +year = {2011}, +note = {Proceedings of the 19th International Conference on Plasma-Surface Interactions in Controlled Fusion}, +issn = {0022-3115}, +doi = {https://doi.org/10.1016/j.jnucmat.2010.11.050}, +url = {https://www.sciencedirect.com/science/article/pii/S002231151000752X}, +author = {Masashi Shimada and Y. Hatano and P. Calderoni and T. Oda and Y. Oya and M. Sokolov and K. Zhang and G. Cao and R. Kolasinski and J.P. Sharpe}, +} + @article{CODATA2021552941, author = {Eite Tiesinga and Peter Mohr and David Newell and Barry Taylor}, title = {{CODATA} Recommended Values of the Fundamental Physical Constants: 2018}, @@ -131,6 +145,19 @@ @article{causey1990tritium publisher={Elsevier} } +@article{Causey2002, +title = {Hydrogen isotope retention and recycling in fusion reactor plasma-facing components}, +journal = {Journal of Nuclear Materials}, +volume = {300}, +number = {2}, +pages = {91-117}, +year = {2002}, +issn = {0022-3115}, +doi = {https://doi.org/10.1016/S0022-3115(01)00732-2}, +url = {https://www.sciencedirect.com/science/article/pii/S0022311501007322}, +author = {Rion A Causey}, +} + @article{macaulay1992thermal, title={{Thermal absorption and desorption of deuterium in beryllium and beryllium oxide}}, author={Macaulay-Newcombe, RG and Thompson, DA and Smeltzer, WW}, diff --git a/doc/content/verification_and_validation/val-2l.md b/doc/content/verification_and_validation/val-2l.md index e69de29bb..016ba82b1 100644 --- a/doc/content/verification_and_validation/val-2l.md +++ b/doc/content/verification_and_validation/val-2l.md @@ -0,0 +1,174 @@ +# Deuterium Retention in Neutron-irradiated Tungsten + + +## Case Description + +This validation case is based on the thermal desorption spectroscopy (TDS) experiments and TMAP7 analysis reported by [!cite](Shimada2011). The experiments compared deuterium release from unirradiated tungsten (0 dpa) and neutron-irradiated tungsten (0.025 dpa) after high-flux deuterium-plasma exposure. + +!alert note title=Scope of the current validation +The present implementation addresses only the unirradiated sample and benchmarks the TMAP8 result against TMAP7 fit A in Figure 3 of [!cite](Shimada2011). It does not yet validate the neutron-irradiated case. A future extension will add the trap populations required to model the irradiated sample. + +For the unirradiated sample, [!cite](Shimada2011) reported a narrow release spectrum between approximately 450 K and 700 K. Their TMAP7 Fit A validated against this spectra assuming a uniform concentration of 4 at.% 1.35 eV traps to a depth of 0.7 $\mu$m. + +The objectives of this first stage of `val-2l` are to: + +1. Reproduce the unirradiated TMAP7 Fit A model in TMAP8; +2. Compare the TMAP8 desorption flux with the digitized experimental TDS data; +3. Verify that the deuterium inventory and integrated surface release satisfy mass conservation; +4. Establish a model that can later be extended to the neutron-irradiated sample; and +5. Perform PSS optimization on that model characterize uncertainty in the chosen material properties in the simulations in [!cite](Shimada2011). + +## Experimental Description + +The tungsten specimens were 6 mm-diameter, 0.2 mm-thick discs made from 99.99 at.% polycrystalline tungsten. Both the unirradiated and irradiated specimens were exposed to 100 eV deuterons at a nominal flux of $5\times10^{21}$ m$^{-2}$ s$^{-1}$ and a fluence of $4\times10^{25}$ m$^{-2}$ while the specimen temperature was maintained at 473 K [!cite](Shimada2011). After exposure, deuterium release was measured using TDS. + +The measured temperature history is prescribed directly in the TMAP8 model rather than approximated by a constant heating rate. It is imperative that we capture the correct temperature history, as sharp TDS spectra coincide with temperature fluctuations between roughly 100-150 seconds and 200-250 seconds for the neutron-irradiated sample. The digitized version of this temperature history is found in [val-2l_temperature_history]. + +!media comparison_val-2l.py + image_name=val-2l_temperature_history.png + id=val-2l_temperature_history + style=width:50%;margin-bottom:2%;margin-left:auto;margin-right:auto + caption=Temperature history prescribed during the TDS simulation. The inset highlights the early-time temperature fluctuations reported during the experiment. + +## Model Description + +### Geometry and mesh + +TMAP8 models the tungsten disc as a one-dimensional domain through its full 0.2 mm thickness. The two ends of the domain represent the two exposed circular surfaces of the disc. The mesh is segmented and refined near the upstream surface so that the 0.7 micrometer Fit A trap boundary lies on a mesh node. The remaining thickness is progressively coarsened away from the trapped region. + +### Governing equations + +The physical mobile-species balance is + +!equation id=val-2l_mobile_balance +\frac{\partial C_M}{\partial t} - \nabla \cdot \left(D(T) \nabla C_M\right) + \sum_{i=1}^{N_{trap}}f_{T/M_i}\frac{\partial C_{T_i}}{\partial t} = 0, + +where $C_M$ and $C_{T_i}$ are the concentration of the mobile and trapped species, respectively, $t$ is the time, $D(T)$ is the temperature-dependent diffusivity of deuterium in tungsten, N_{trap} is the number of traps, and $f_{T/M}$ is a user-defined numerical scaling factor for better numerical convergence. The deuterium diffusivity follows the Frauenfelder [!cite](frauenfelder1969solution) relation corrected for deuterium and reported by [!cite](Causey2002): + +!equation id=val-2l_diffusivity +D(T)=D_0\exp\left(-\frac{E_D}{k_B T}\right). + +The trapped-species balance is represented by the TMAP8 trapping and release kernels, + +!equation id=val-2l_trap_balance +\frac{\partial C_{T_i}}{\partial t} = \alpha_t^i \frac{C_{T_i}^{\text{empty}} C_M}{(N f_{T/M,i})} - \alpha_r^i C_{T_i}, + +where the terms in the right-hand side represent trapping and release, respectively. $\alpha_r^i$ and $\alpha_t^i$ are the release and trapping rate coefficients for trap $i$, $N$ is the tungsten material density, and $C_{T_i}^{empty}$ is the concentration of empty trapping sites of type $i$, defined as + +\begin{equation} \label{eqn:trapping_empty} + C_{T_i}^{empty} = (C_{{T_i}0} N - f_{T/M,i} C_{T_i} ) , +\end{equation} + +where $C_{{T_i}0}$ is the fraction of host sites $i$ that can contribute to trapping. + +### Initial and boundary conditions + +The mobile concentration is initially zero. The single Fit A trap population is initially saturated and distributed uniformly from the upstream surface to a depth of 0.7 micrometers. No traps are assigned beyond that depth. + +Finite recombination boundary conditions are applied at the upstream and downstream surfaces: + +!equation id=val-2l_recombination +J = -D\nabla C_M = 2K_r(T)C_M^2, + +with $K_r$ selected by [!cite](Shimada2011) from [!cite](anderl1992deuterium), + +!equation id=val-2l_recombination_coefficient +K_r(T)=K_{r,0}\exp\left(-\frac{E_r}{k_B T}\right). + +The simulation begins at the first temperature in the digitized experimental temperature history and runs for 2 h. The plasma-exposure stage is not simulated; its effect is represented by the prescribed initial trapped-deuterium profile. + +## Case and Model Parameters + +The physical parameters currently used for the unirradiated Fit A benchmark are summarized in [val-2l_parameters]. + +!table id=val-2l_parameters caption=Experimental and physical model parameters for the current unirradiated TMAP7 Fit A benchmark. +| Parameter | Description | Value | Units | Reference | +| :- | :- | -: | :- | :- | +| $L$ | Tungsten thickness | 0.2 | mm | [!cite](Shimada2011) | +| $d$ | Disc diameter | 6 | mm | [!cite](Shimada2011) | +| $T_{\mathrm{exposure}}$ | Plasma-exposure temperature | 473 | K | [!cite](Shimada2011) | +| $D_0$ | Deuterium diffusivity prefactor | $2.9\times10^{-7}$ | m$^2$/s | [!cite](frauenfelder1969solution,Causey2002) | +| $E_D$ | Deuterium diffusion activation energy | 0.39 | eV | [!cite](frauenfelder1969solution,Causey2002) | +| $K_{r,0}$ | Recombination coefficient prefactor | $3.2\times10^{-15}$ | m$^4$/atom/s | [!cite](anderl1992deuterium) | +| $E_r$ | Recombination activation energy | 1.16 | eV | [!cite](anderl1992deuterium) | +| $f_t$ | TMAP7 Fit A trap atomic fraction | 0.04 | - | [!cite](Shimada2011) | +| $x_t$ | TMAP7 Fit A trap depth | 0.7 | $\mu$m | [!cite](Shimada2011) | +| $E_{\mathrm{detrap}}$ | Fit A detrapping energy | 1.35 | eV | [!cite](Shimada2011) | +| $N_W$ | Tungsten atomic density | $6.25\times10^{28}$ | atom/m$^3$ | [!cite](ambrosek2008verification) | +| $\alpha_{t,0}$ | Trapping prefactor | $9.1316\times10^{12}$ | s$^{-1}$ | [!cite](ambrosek2008verification) | +| $\alpha_{r,0}$ | Release prefactor | $8.4\times10^{12}$ | s$^{-1}$ | [!cite](ambrosek2008verification) | + +The concentration variables are rescaled internally by a factor of $10^4$ to improve nonlinear convergence. This scaling does not change the physical trap concentration reported above. + + +## Results + +### Temperature-dependent diffusivity + +[val-2l_diffusivity_plot] confirms that the TMAP8 material follows the prescribed Arrhenius relationship over the experimental temperature range. + +!media comparison_val-2l.py + image_name=val-2l_diffusivity_vs_temperature.png + style=width:50%;margin-bottom:2%;margin-left:auto;margin-right:auto + id=val-2l_diffusivity_plot + caption=Deuterium diffusivity in tungsten evaluated from the TMAP8 material model as a function of reciprocal temperature. + +### Unirradiated desorption benchmark + +[val-2l_comparison] compares the TMAP8 desorption flux with the digitized unirradiated experimental data from [!cite](Shimada2011). The comparison is evaluated over the interval from 800 s to 2800 s, which contains the primary desorption peak. + +!media comparison_val-2l.py + image_name=val-2l_comparison_desorption.png + id=val-2l_comparison + style=width:50%;margin-bottom:2%;margin-left:auto;margin-right:auto + caption=Comparison of the TMAP8 prediction using the TMAP7 Fit A parameters with the unirradiated experimental TDS data reported by [!cite](Shimada2011). + +The current comparison script calculates the mean-normalized root-mean-squared-percentage error, + +!equation id=val-2l_error_metric +\mathrm{RMSPE} = \frac{\sqrt{\sum_{i=1}^{n}\left(J_{\mathrm{TMAP8},i}-J_{\mathrm{exp},i}\right)^2/n}}{\sum_{i=1}^{n}J_{\mathrm{exp}}/n}\times100 + +### Deuterium inventory and mass conservation + +[val-2l_inventory] shows the simulated mobile and trapped inventories of deuterium over the duration of the TDS experiment along with the temperature profile. + +!media comparison_val-2l.py + image_name=val-2l_inventory.png + id=val-2l_inventory + style=width:50%;margin-bottom:2%;margin-left:auto;margin-right:auto + caption=Mobile, trapped, and total deuterium inventories during the unirradiated TDS calculation. + +The mass-balance residual is computed from the change in retained deuterium plus the time-integrated release through both surfaces. A value close to zero in [val-2l_mass_conservation] indicates that the numerical solution conserves mass. + +!media comparison_val-2l.py + image_name=val-2l_mass_conservation.png + id=val-2l_mass_conservation + style=width:50%;margin-bottom:2%;margin-left:auto;margin-right:auto + caption=Deuterium mass-balance residual normalized by the initial deuterium inventory. + +## Discussion and Limitations + +This stage of `val-2l` is intentionally limited to the unirradiated Fit A case. It exercises temperature-dependent diffusion, trapping and release, finite surface recombination, a measured temperature history, and inventory accounting in TMAP8. The comparison does not establish that the Fit A trap distribution is unique. In [!cite](Shimada2011), Fit A was calibrated to the TDS spectrum alone and did not reproduce the measured NRA depth profile. + +## PSS Optimization + +PSS optimization details will go here. + +### Planned extension to the neutron-irradiated case + +The neutron-irradiated specimen (0.025 dpa) exhibited a much broader desorption spectrum than the unirradiated specimen and required multiple trap populations in the TMAP7 analysis [!cite](Shimada2011). A later extension of `val-2l` will: + +1. add the irradiated experimental TDS and temperature-history data; +2. introduce multiple trap populations to attempt to capture multiple sharp spectra; +3. document the irradiation history and the assumptions required, exploring modeling techniques to represent damage to tungsten; +4. perform mass conservation and validation checks incrementally +5. optimize material properties for chosen trap distributions and types + +## Input Files + +The files used in the current unirradiated benchmark are: + +- [test/tests/val-2l/val-2l.params](val-2l.params), which contains the physical and numerical parameters; +- [test/tests/val-2l/val-2l.i](val-2l.i), which defines the one-dimensional transport, trapping, release, surface recombination, and postprocessing model; + +!bibtex bibliography diff --git a/test/tests/val-2l/comparison_val-2l.py b/test/tests/val-2l/comparison_val-2l.py index fd32b4447..6ed0f56ad 100644 --- a/test/tests/val-2l/comparison_val-2l.py +++ b/test/tests/val-2l/comparison_val-2l.py @@ -38,7 +38,7 @@ def read_csv_from_TMAP8(file_name, parameter_names): if "/tmap8/doc/" in script_folder.lower(): # if in documentation folder csv_folder = f"../../../../test/tests/val-2l/gold/{file_name}" else: # if in test folder - csv_folder = f"./{file_name}" + csv_folder = f"./gold/{file_name}" simulation_data = pd.read_csv(csv_folder) return np.array([simulation_data[name] for name in parameter_names]) @@ -127,6 +127,7 @@ def plot_temperature_history( ax.set_xlim(0, time.max()) ax.set_ylim(bottom=0) ax.grid(visible=True, which="major", color="0.65", linestyle="--", alpha=0.3) + ax.set_title("Unirradiated Sample: TDS Temperature History") ax.minorticks_on() ax.legend() @@ -177,6 +178,7 @@ def plot_mass_conservation( ax.ticklabel_format(axis="y", style="sci", scilimits=(0, 0)) ax.grid(visible=True, which="major", color="0.65", linestyle="--", alpha=0.3) ax.minorticks_on() + ax.set_title("Unirradiated Sample: Conservation of Mass") plt.tight_layout() plt.savefig(filename, bbox_inches="tight", dpi=300) plt.close(fig) @@ -244,6 +246,7 @@ def plot_inventory( ax.set_ylabel(r"Deuterium inventory (atoms)") ax.set_xlim(0, time.max()) ax.set_ylim(bottom=0) + ax.set_title("Unirradiated Sample: Deuterium Inventory") ax.grid(visible=True, which="major", color="0.65", linestyle="--", alpha=0.3) ax_T.set_ylabel("Temperature (K)") ax.legend( @@ -291,7 +294,7 @@ def plot_diffusivity_vs_temperature( ) ax.set_xlabel(r"Reciprocal temperature 1000/T (K$^{-1}$)") ax.set_ylabel(r"Diffusivity (m$^2$/s)") - ax.set_title("Deuterium diffusivity in tungsten TMAP8 Material") + ax.set_title("Deuterium Diffusivity in Tungsten") ax.grid(True, which="both", linestyle="--", alpha=0.4) plt.tight_layout() plt.savefig(filename, bbox_inches="tight", dpi=300) @@ -371,7 +374,7 @@ def plot_unirradiated_desorption( ) plt.xlabel("Temperature (K)") plt.ylabel(r"Desorbed flux (m$^{-2}$s$^{-1}$)") - plt.title("Unirradiated deuterium desorption: TMAP8 vs experiment") + plt.title("Unirradiated Sample: Deuterium Desorption: TMAP8 vs Experiment") plt.xlim(experiment_temperature.min(), experiment_temperature.max()) plt.ylim(0) plt.ticklabel_format(axis="y", style="sci", scilimits=(0, 0)) @@ -387,4 +390,9 @@ def plot_unirradiated_desorption( plot_mass_conservation() plot_inventory() plot_diffusivity_vs_temperature() -plot_unirradiated_desorption() +if "/tmap8/doc/" in script_folder.lower(): # if in documentation folder + unirradiated_data_file = "../../../../test/tests/val-2l/gold/unirradiated_data.csv" +else: # if in test folder + unirradiated_data_file = "./gold/unirradiated_data.csv" + +plot_unirradiated_desorption(experiment_file=unirradiated_data_file) diff --git a/test/tests/val-2l/gold/temperature_data.csv b/test/tests/val-2l/gold/temperature_data.csv new file mode 100644 index 000000000..89ad8f183 --- /dev/null +++ b/test/tests/val-2l/gold/temperature_data.csv @@ -0,0 +1,6990 @@ 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+4628.105725439898, 58553328280303620 +4752.658000996933, 59766033284343300 +4877.210276553968, 60978738288382460 +5001.779794362245, 60415491414468100 +5126.326322502199, 62220180377825280 +5250.8843454763155, 62840901422546940 +5375.442368450431, 63461622467268100 +5500.000391424546, 64082343511989760 +5624.5584143986625, 64703064556711420 +5749.119311081318, 65027793621773310 +5873.680207763975, 65352522686836740 +5998.249725572252, 64789275812922370 +6122.790506295125, 67185948735597570 +6247.348529269241, 67806669780318720 +6371.872067740872, 71979294580946430 +6496.430090714987, 72600015625668100 +6620.988113689103, 73220736670389250 +6745.546136663218, 73841457715110910 +6870.121401888576, 72686226881879550 +6994.708161948097, 70347028130012160 +7108.874854840206, 72099990339642370 From 97e3fe243ce1ba58e69387b8d830e9dfb3865c90 Mon Sep 17 00:00:00 2001 From: "Butterworth, Evan" Date: Fri, 28 Aug 2026 15:05:18 -0600 Subject: [PATCH 11/12] Remove commented out lines and unnecessary comments from input file --- test/tests/val-2l/val-2l.i | 37 ++++--------------------------------- 1 file changed, 4 insertions(+), 33 deletions(-) diff --git a/test/tests/val-2l/val-2l.i b/test/tests/val-2l/val-2l.i index 9ceaa34bc..1c9bba3ea 100644 --- a/test/tests/val-2l/val-2l.i +++ b/test/tests/val-2l/val-2l.i @@ -38,32 +38,21 @@ [] [] -# [Problem] -# # Reference-based convergence: compare each variable's residual to the magnitude of the physical -# # terms (diffusion + time derivative + source, tagged 'ref') rather than to the initial residual -# type = ReferenceResidualProblem -# extra_tag_vectors = 'ref' -# reference_vector = 'ref' -# [] - [Kernels] [mobile_time_derivative] type = ADTimeDerivative variable = mobile - # extra_vector_tags = 'ref' [] [mobile_diffusion] type = ADMatDiffusion variable = mobile diffusivity = diffusivity_mat - # extra_vector_tags = 'ref' [] [coupled_time] type = ADCoefCoupledTimeDerivative variable = mobile v = trapped_1 coef = ${trap_per_free} - # extra_vector_tags = 'ref' [] [] @@ -82,7 +71,6 @@ Ct0 = 'trap_distribution_function' temperature = 'temperature' trap_per_free = ${trap_per_free} - # extra_vector_tags = ref [] [release_1] type = ReleasingNodalKernel @@ -111,7 +99,6 @@ [BCs] active = 'left_recombination_flux right_recombination_flux' - # Infinite recombination [left] type = ADDirichletBC boundary = upstream @@ -125,14 +112,12 @@ variable = mobile [] - # Finite recombination [left_recombination_flux] type = ADMatNeumannBC variable = mobile boundary = upstream value = 1 boundary_material = flux_recombination_surface - # extra_vector_tags = 'ref' [] [right_recombination_flux] @@ -141,13 +126,11 @@ boundary = downstream value = 1 boundary_material = flux_recombination_surface - # extra_vector_tags = 'ref' [] [] [Materials] - # Temperature-dependent deuterium diffusivity in tungsten [diffusivity_mat] type = ADDerivativeParsedMaterial property_name = 'diffusivity_mat' @@ -158,7 +141,6 @@ outputs = 'exodus' [] - # Temperature-dependent recombination coefficient [recombination_rate_surface] type = ADDerivativeParsedMaterial property_name = 'Kr' @@ -167,7 +149,6 @@ expression = '${recombination_preexponential_factor} * exp(- ${recombination_energy} / ${kb_eV} / temperature)' [] - # Finite recombination Boundary Material [flux_recombination_surface] type = ADDerivativeParsedMaterial coupled_variables = 'mobile' @@ -236,17 +217,13 @@ outputs = csv [] - ### Conservation of Mass ### - - # Total deuterium inventory currently in the sample, M(t) - [total_mobile_retention] type = ElementIntegralVariablePostprocessor variable = mobile execute_on = 'INITIAL TIMESTEP_END' [] - [total_trapped_retention] # Physical concentration = variable * trap_per_free + [total_trapped_retention] type = ElementIntegralVariablePostprocessor variable = trapped_1 execute_on = 'INITIAL TIMESTEP_END' @@ -260,8 +237,7 @@ outputs = csv [] - # Change in domain inventory relative to the initial mass, M(t) - M(0). - [deuterium_inventory_change] # atoms / mum^2 + [deuterium_inventory_change] type = ChangeOverTimePostprocessor postprocessor = total_deuterium_retention change_with_respect_to_initial = true @@ -269,8 +245,6 @@ outputs = none [] - # Desorption flux through upstream and downstream surfaces - [upstream_flux] type = ADSideDiffusiveFluxIntegral boundary = 'upstream' @@ -294,8 +268,7 @@ outputs = csv [] - # Cumulative deuterium released through both surfaces - [deuterium_released_physical] # atoms / mum^2 + [deuterium_released_physical] type = TimeIntegratedPostprocessor value = deuterium_release_flux_total time_integration_scheme = TRAPEZOIDAL-RULE @@ -303,8 +276,7 @@ outputs = csv [] - # Conservation residual = (M(t) - M(0)) + released; ideally 0 at all times. - [deuterium_mass_conservation_residual] # atoms / mum^2 + [deuterium_mass_conservation_residual] type = SumPostprocessor values = 'deuterium_inventory_change deuterium_released_physical' execute_on = 'TIMESTEP_END' @@ -335,7 +307,6 @@ perf_graph = true [exodus] type = Exodus - # output_material_properties = true [] [profile_csv] type = CSV From b98f061699b2ffcb4fa42aff40e2729874cdd3bc Mon Sep 17 00:00:00 2001 From: "Butterworth, Evan" Date: Sun, 30 Aug 2026 14:19:49 -0600 Subject: [PATCH 12/12] Added a more sophisticated timestepper to shrink the timestep in critical temperature regions and regions with flux measured over a certain threshold. This refines the timestep in the critical simulation regions, allowing for the temperature piecewise linear function to have proper experimental curvature and for sharp TDS spectra to be measured properly. Added a timestep tracker to the comparison script. Tests will take too long using this timestepper --- test/tests/val-2l/comparison_val-2l.py | 197 +- test/tests/val-2l/gold/temperature_data.csv | 14190 +++++++++-------- test/tests/val-2l/gold/unirradiated_data.csv | 7327 ++++++++- test/tests/val-2l/gold/val-2l_out.csv | 2282 ++- test/tests/val-2l/val-2l.i | 95 +- test/tests/val-2l/val-2l.params | 8 +- 6 files changed, 16699 insertions(+), 7400 deletions(-) diff --git a/test/tests/val-2l/comparison_val-2l.py b/test/tests/val-2l/comparison_val-2l.py index 6ed0f56ad..b335f2cbd 100644 --- a/test/tests/val-2l/comparison_val-2l.py +++ b/test/tests/val-2l/comparison_val-2l.py @@ -1,10 +1,12 @@ -# This is the main comparison script for val-2l, and computes the following plots: - -# 1: plot_temperature_history() shows the temperature profile over the entire time of experiment, as well as an inlet graph that zooms in on temperature anomolies observed during the experiment -# 2: plot_mass_conservation() shows the evolution of the mass conservation residual relative to the initial mass at the start of the TDS experiment -# 3: plot_inventory() shows the deuterium present in traps and as a mobile concentration -# 4: plot_diffusivity_vs_temperature() shows the diffusivity as a function of reciprocal temperature, which should be linear -# 5: plot_unirradiated_desorption() plots the simulated against experimental desorbed flux from the upstream and downstream surfaces, performing RMSPE calculations to measure the goodness of fit +""" +This is the main comparison script for val-2l, and computes the following plots: +1: plot_timestep_behavior() visualizes the adaptive timestepper based on critical temperature regions and measured fluxes +1: plot_temperature_history() shows the temperature profile over the entire time of experiment, as well as an inlet graph that zooms in on temperature anomolies observed during the experiment +2: plot_mass_conservation() shows the evolution of the mass conservation residual relative to the initial mass at the start of the TDS experiment +3: plot_inventory() shows the deuterium present in traps and as a mobile concentration +4: plot_diffusivity_vs_temperature() shows the diffusivity as a function of reciprocal temperature, which should be linear +5: plot_unirradiated_desorption() plots the simulated against experimental desorbed flux from the upstream and downstream surfaces, performing RMSPE calculations to measure the goodness of fit +""" import matplotlib.pyplot as plt import numpy as np @@ -38,7 +40,9 @@ def read_csv_from_TMAP8(file_name, parameter_names): if "/tmap8/doc/" in script_folder.lower(): # if in documentation folder csv_folder = f"../../../../test/tests/val-2l/gold/{file_name}" else: # if in test folder - csv_folder = f"./gold/{file_name}" + csv_folder = f"./{file_name}" + # csv_folder = f"./gold/{file_name}" + simulation_data = pd.read_csv(csv_folder) return np.array([simulation_data[name] for name in parameter_names]) @@ -93,6 +97,140 @@ def annotate_rmspe(simulated, reference, x_pos, y_pos): plt.text(x_pos, y_pos, "RMSPE = %.2f %%" % RMSPE, fontweight="bold") +def plot_timestep_behavior( + simulation_file="val-2l_out.csv", + filename="val-2l_timestep_behavior.png", + temperature_window=(100.0, 350.0), +): + """Plot temperature, desorbed flux, and timestep size over time. + + The shaded regions identify the two timestep-limiting conditions: + + 1. The fixed temperature-resolution interval. + 2. Times when the magnitude of the desorbed flux exceeds the specified + threshold. + + Args: + simulation_file (str): TMAP8 CSV with "time", "dt", "temperature", and + "desorbed_flux" columns. + filename (str): Output PNG filename. + flux_threshold (float): Flux magnitude above which fine timesteps are used + in at/m^2/s. + temperature_window (tuple[float, float]): Start and end times of the fixed + fine-timestep interval in seconds. + """ + time, dt, temperature, desorbed_flux, flux_threshold = read_csv_from_TMAP8( + simulation_file, + ["time", "dt", "temperature", "deuterium_release_flux_total", "flux_threshold"], + ) + + # Remove a possible initial-output row where TimestepSize has not yet been set. + valid = ( + np.isfinite(time) + & np.isfinite(dt) + & np.isfinite(temperature) + & np.isfinite(desorbed_flux) + & (dt > 0.0) + ) + time = time[valid] + dt = dt[valid] + temperature = temperature[valid] + desorbed_flux = desorbed_flux[valid] + flux_threshold = flux_threshold[0] * 1e12 + + flux_active = np.abs(desorbed_flux) >= flux_threshold + temperature_start, temperature_end = temperature_window + + fig, axes = plt.subplots( + nrows=3, + ncols=1, + figsize=(7.0, 8.0), + sharex=True, + ) + ax_temperature, ax_flux, ax_dt = axes + + # Temperature history + ax_temperature.plot( + time, + temperature, + color="black", + linewidth=1.8, + ) + ax_temperature.set_ylabel("Temperature (K)") + ax_temperature.set_title("Unirradiated Sample: Timestep-Limiting Regions") + + # Desorbed flux history + ax_flux.plot( + time, + desorbed_flux * 1e12, + color="tab:green", + linewidth=1.8, + ) + ax_flux.axhline( + flux_threshold, + color="tab:red", + linewidth=1.1, + linestyle="--", + label=rf"Flux threshold: {flux_threshold:.1e} at/m$^2$/s", + ) + ax_flux.set_ylabel(r"Desorbed flux (at/m$^2$/s)") + ax_flux.ticklabel_format(axis="y", style="sci", scilimits=(0, 0)) + ax_flux.legend(loc="best") + + # Actual timestep used over each interval. + ax_dt.step( + time, + dt, + where="pre", + color="tab:blue", + linewidth=1.8, + ) + ax_dt.set_xlabel("Time (s)") + ax_dt.set_ylabel("Timestep size (s)") + + # A logarithmic axis makes reductions easier to see when dt spans + # multiple orders of magnitude. + ax_dt.set_yscale("log") + + # Shade the two timestep-limiting regions on every panel. + for index, ax in enumerate(axes): + ax.axvspan( + temperature_start, + temperature_end, + color="tab:orange", + alpha=0.14, + linewidth=0.0, + label="Temperature refinement" if index == 0 else None, + ) + ax.fill_between( + time, + 0.0, + 1.0, + where=flux_active, + step="pre", + transform=ax.get_xaxis_transform(), + color="tab:red", + alpha=0.09, + linewidth=0.0, + ) + + ax.grid( + visible=True, + which="major", + color="0.65", + linestyle="--", + alpha=0.3, + ) + ax.minorticks_on() + + ax_temperature.legend(loc="best") + ax_dt.set_xlim(0.0, time.max()) + + plt.tight_layout() + plt.savefig(filename, bbox_inches="tight", dpi=300) + plt.close(fig) + + def plot_temperature_history( simulation_file="val-2l_out.csv", filename="val-2l_temperature_history.png", @@ -309,13 +447,13 @@ def plot_unirradiated_desorption( ): """Plot the Shimada (2010) unirradiated desorption data against TMAP8 - The simulated and experimental desorbed fluxes are plotted versus temperature, + The simulated and experimental desorbed fluxes are plotted versus time, with the RMSPE annotated over the region tmin–tmax seconds. Args: experiment_file (str): two-column, header-less CSV of (time [s], desorbed flux [m^-2 s^-1]) - simulation_file (str): TMAP8 CSV output holding "time", "temperature", and + simulation_file (str): TMAP8 CSV output holding "time" and the desorbed-flux column simulation_flux_column (str): name of the desorbed-flux column in simulation_file. TMAP8 reports it in at/µm^2/s; converted to at/m^2/s. @@ -324,44 +462,41 @@ def plot_unirradiated_desorption( experiment = np.loadtxt(experiment_file, delimiter=",") experiment_time, experiment_flux = experiment[:, 0], experiment[:, 1] - simulation_time, simulation_temperature, simulation_flux = read_csv_from_TMAP8( - simulation_file, ["time", "temperature", simulation_flux_column] + simulation_time, simulation_flux = read_csv_from_TMAP8( + simulation_file, ["time", simulation_flux_column] ) simulation_flux = simulation_flux * 1e12 # at/µm^2/s -> at/m^2/s - # Truncate experiment to simulation time range, then map times to temperatures + # Truncate experiment to simulation time range in_sim_range = experiment_time <= simulation_time.max() experiment_time = experiment_time[in_sim_range] experiment_flux = experiment_flux[in_sim_range] - experiment_temperature = numerical_solution_on_experiment_input( - experiment_time, simulation_time, simulation_temperature - ) # Interpolate simulated flux at experimental time points for RMSPE mapped_simulation_flux = np.interp( experiment_time, simulation_time, simulation_flux ) - tmin, tmax = 800, 2800 + tmin, tmax = 500, 3000 rmspe_region = (experiment_time >= tmin) & (experiment_time <= tmax) plt.figure(figsize=(10, 6)) plt.plot( - experiment_temperature, + experiment_time, experiment_flux, "ro", label="Experiment (Shimada 2010, 0 dpa)", ) - plt.plot(simulation_temperature, simulation_flux, "b-", label="TMAP8") + plt.plot(simulation_time, simulation_flux, "b-", label="TMAP8") if rmspe_region.any(): plt.axvline( - experiment_temperature[rmspe_region].min(), + experiment_time[rmspe_region].min(), color="green", linestyle="--", linewidth=1.2, label="RMSPE region", ) plt.axvline( - experiment_temperature[rmspe_region].max(), + experiment_time[rmspe_region].max(), color="green", linestyle="--", linewidth=1.2, @@ -369,13 +504,13 @@ def plot_unirradiated_desorption( annotate_rmspe( mapped_simulation_flux[rmspe_region], experiment_flux[rmspe_region], - experiment_temperature[rmspe_region].mean(), + experiment_time[rmspe_region].mean(), experiment_flux.max() / 4, ) - plt.xlabel("Temperature (K)") + plt.xlabel("Time (s)") plt.ylabel(r"Desorbed flux (m$^{-2}$s$^{-1}$)") plt.title("Unirradiated Sample: Deuterium Desorption: TMAP8 vs Experiment") - plt.xlim(experiment_temperature.min(), experiment_temperature.max()) + plt.xlim(experiment_time.min(), experiment_time.max()) plt.ylim(0) plt.ticklabel_format(axis="y", style="sci", scilimits=(0, 0)) plt.legend() @@ -386,6 +521,8 @@ def plot_unirradiated_desorption( # ========================== Plot calls ========================== # +# plot_temperature_history(simulation_file="temperature_data.csv") +plot_timestep_behavior() plot_temperature_history() plot_mass_conservation() plot_inventory() @@ -396,3 +533,15 @@ def plot_unirradiated_desorption( unirradiated_data_file = "./gold/unirradiated_data.csv" plot_unirradiated_desorption(experiment_file=unirradiated_data_file) + +data = pd.read_csv("val-2l_out.csv") +flux_column = "deuterium_release_flux_total" + +i_max = data[flux_column].abs().idxmax() + +print( + data.loc[ + i_max, + ["time", "dt", "temperature", flux_column, "flux_threshold"], + ] +) diff --git a/test/tests/val-2l/gold/temperature_data.csv b/test/tests/val-2l/gold/temperature_data.csv index 89ad8f183..7b234d913 100644 --- a/test/tests/val-2l/gold/temperature_data.csv +++ b/test/tests/val-2l/gold/temperature_data.csv @@ -1,6990 +1,7202 @@ time,temperature -0.0,300.0 -1.0,300.0 -2.0,300.0 -3.0,300.0 -4.0,300.0 -5.0,300.0 -6.0,300.0 -7.0,300.0 -8.0,300.0 -9.0,300.0 -10.0,300.0 -11.0,300.0 -12.0,300.0 -13.0,300.0 -14.0,300.0 -15.0,300.0 -16.0,300.0 -17.0,300.0 -18.0,300.0 -19.0,300.0 -20.0,300.0 -21.0,300.0 -22.0,300.0 -23.0,300.0 -24.0,300.0 -25.0,300.0 -26.0,300.0 -27.0,300.0 -28.0,300.0 -29.0,300.0 -30.0,300.0 -31.0,300.0 -32.0,300.0 -33.0,300.0 -34.0,300.0 -35.0,300.0 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format = columns @@ -178,18 +177,36 @@ expression = 'if(x < ${trap_depth}, ${trap_fraction}, 0.0)' [] - [timestep_limiting_function] - type = ParsedFunction - expression = 'if(T >= 450 & T <= 750, dt_fine, dt_max)' - symbol_names = 'T dt_fine dt_max' - symbol_values = 'temperature_function - ${dt_fine} - ${dt_max}' - [] + # [timestep_limiting_function] + # type = ParsedFunction + # expression = 'min(if(t < 100, dt_max, if(t < 350, dt_fine, dt_max)), if(abs(flux) > flux_threshold, dt_fine, dt_max))' + # symbol_names = 'flux dt_max dt_fine flux_threshold' + # symbol_values = 'deuterium_release_flux_total ${dt_max} ${dt_fine} ${flux_threshold}' + # [] + # [timestep_limiting_function] + # type = ParsedFunction + # expression = 'if(T >= 450 & T <= 750, dt_fine, dt_max)' + # symbol_names = 'T dt_fine dt_max' + # symbol_values = 'temperature_function + # ${dt_fine} + # ${dt_max}' + # [] [] [Postprocessors] + [dt] + type = TimestepSize + execute_on = 'TIMESTEP_END' + [] + + [flux_threshold] + type = ConstantPostprocessor + value = ${flux_threshold} + execute_on = 'initial' + outputs = csv + [] + [trap_depth] type = ConstantPostprocessor value = ${trap_depth} @@ -268,6 +285,18 @@ outputs = csv [] + [dt_limit] + type = ParsedPostprocessor + expression = 'min(if(t < 350, dt_fine, dt_max), if(abs(flux) > flux_threshold, dt_fine, dt_max))' + pp_names = 'deuterium_release_flux_total' + pp_symbols = 'flux' + constant_names = 'dt_max dt_fine flux_threshold' + constant_expressions = '${dt_max} ${dt_fine} ${flux_threshold}' + use_t = true + execute_on = 'TIMESTEP_END' + outputs = csv +[] + [deuterium_released_physical] type = TimeIntegratedPostprocessor value = deuterium_release_flux_total @@ -305,9 +334,8 @@ file_base = 'val-2l_out' csv = true perf_graph = true - [exodus] - type = Exodus - [] + sync_times = '100 350' + exodus = true [profile_csv] type = CSV file_base = 'deuterium_mobile_concentration_profile/val-2l_out' @@ -336,19 +364,34 @@ petsc_options_value = 'lu' end_time = ${simulation_time} automatic_scaling = true + compute_scaling_once = 'false' dtmin = ${dt_min} dtmax = ${dt_max} - [TimeSteppers] - [iteration_dt] - type = IterationAdaptiveDT - dt = ${dt_start} - optimal_iterations = 5 - growth_factor = 1.1 - cutback_factor_at_failure = 0.5 - [] - [limiting_dt] - type = FunctionDT - function = timestep_limiting_function - [] - [] + [TimeStepper] + type = IterationAdaptiveDT + dt = ${dt_max} + growth_factor = 1.1 + cutback_factor_at_failure = 0.5 + timestep_limiting_postprocessor = dt_limit + reject_large_step = true + reject_large_step_threshold = 0.9 + [] + # [TimeStepper] + # type = FunctionDT + # function = timestep_limiting_function + # # growth_factor = 2 + # [] + # [TimeSteppers] + # [iteration_dt] + # type = IterationAdaptiveDT + # dt = ${dt_start} + # optimal_iterations = 5 + # growth_factor = 1.1 + # cutback_factor_at_failure = 0.5 + # [] + # [limiting_dt] + # type = FunctionDT + # function = timestep_limiting_function + # [] + # [] [] diff --git a/test/tests/val-2l/val-2l.params b/test/tests/val-2l/val-2l.params index 3057e8c6e..d83201ed0 100644 --- a/test/tests/val-2l/val-2l.params +++ b/test/tests/val-2l/val-2l.params @@ -7,10 +7,10 @@ kb_eV = '${units ${fparse kb / eV_to_J} eV/K}' # Boltzmann constant eV/K # Temporal Parameters simulation_time = '${units 2 h -> s}' -dt_start = '${units 60 s}' -dt_max = '${units 300 s}' -dt_min = '${units 1e-4 s}' -dt_fine = '${units 10 s}' +dt_max = '${units 60 s}' +dt_min = '${units 1e-2 s}' +dt_fine = '${units 1 s}' +flux_threshold = '${units 5e16 at/m^2/s -> at/mum^2/s}' # Geometry tungsten_thickness = '${units 0.2 mm -> mum}' # Tungsten disc sample thickness, Shimada et al. 2010 (p. S667, Section 2.1)