IntermediatePythonCFD
Automate CFD Post-Processing with Python
Batch-read solver monitors, compute averaged quantities and generate a comparison report.
Estimated completion: 50 min
Objective
Turn a folder of simulation runs into a single reviewed summary table and set of plots.
Required knowledge
- Python basics
- Familiarity with CFD outputs
Software and tools
- Python 3.11
- pandas
- matplotlib
Files and resources
- Example run folder
- Script template
Step-by-step instructions
- 1
Map the run folders
Use pathlib to discover every monitor file and record the case name alongside it.
- 2
Parse the monitors
Load each file with pandas and average the last portion of the signal once it is statistically stationary.
- 3
Build the summary table
Assemble a DataFrame with one row per case and export it to Excel or CSV.
- 4
Plot comparisons
Generate one figure per quantity with consistent axes so cases can be compared at a glance.
- 5
Automate the run
Wrap the script in a CLI entry point so it can be executed after every batch of simulations.
Expected result
A reproducible script producing an up-to-date summary table and plots for any run folder.
Troubleshooting
| Problem | How to fix it |
|---|---|
| Averages fluctuate between runs | Increase the averaging window or check that the solution reached a statistically steady state. |
| Missing columns in some files | Normalise headers on load and fail loudly rather than silently dropping cases. |
Final checklist
- All cases discovered
- Averaging window justified
- Figures use consistent scales
- Script runs from a clean checkout