Python notebooks and scripts for analyzing civil engineering laboratory data — concrete strength, soil mechanics, and materials testing. Developed alongside my Master's studies in Civil & Environmental Engineering at Technische Hochschule Deggendorf.
- Provide clean, reproducible analysis pipelines for typical civil engineering lab experiments.
- Practice Python data analysis on real engineering problems (numpy, pandas, matplotlib, scipy).
- Build a reusable toolbox for upcoming master thesis and coursework projects.
| Module | Topic | Status |
|---|---|---|
concrete/ |
Compressive strength tests (DIN EN 12390-3), cube vs. cylinder conversion | Planned |
soil/ |
Sieve analysis, Atterberg limits, Proctor compaction | Planned |
corrosion/ |
KKS (kathodischer Korrosionsschutz) potential measurements | Planned |
rehabilitation/ |
Carbonation depth & chloride profiles for existing structures | Planned |
- Python 3.11+
- Jupyter Lab
- pandas, numpy, scipy, matplotlib, seaborn
git clone https://github.com/koosha77/civil-lab-data-analysis.git
cd civil-lab-data-analysis
python -m venv .venv
source .venv/bin/activate # Windows: .venv\Scripts\activate
pip install -r requirements.txt
jupyter lab- DIN EN 12390 — Testing hardened concrete
- DIN 18196 — Soil classification
- HOAI / DIN 276 — German construction cost framework (context for rehab studies)
MIT — see LICENSE.