FreeCAD Genetic Algorithm FEA

This repository contains scripts and utilities to run parametric and genetic algorithm-based finite element analysis (FEA) using FreeCAD. The project is designed to automate the exploration of optimized designs by sweeping parameter values or employing a genetic algorithm to minimize von Mises stress.

Features

• Parametric FEA: Automate parameter sweeps to run FEA on multiple design configurations and analyze the results.
• Genetic Algorithm: Leverage a genetic algorithm to optimize designs based on von Mises stress results.
• FreeCAD Integration: Scripts dynamically interact with FreeCAD, utilizing its Python API for CAD model manipulation and FEA.
• CSV Output: Results are saved in CSV format, including von Mises stress and the corresponding parameters for easy post-analysis.
• Logging: Comprehensive logging to help monitor progress and debug issues.

Requirements

• Python 3.8+
• FreeCAD 0.21+

The project uses Poetry and Pipenv for dependency management. You can choose either to manage the dependencies.

Setup with Poetry

1. Install Poetry:

   curl -sSL https://install.python-poetry.org | python3 -

2. Clone this repository:

   git clone https://github.com/pepperumo/FreeCAD-genetic-algorithm_FEA.git
   cd FreeCAD-genetic-algorithm_FEA

3. Install dependencies using Poetry:

   poetry install

4. Activate the environment:

   poetry shell

Setup with Pipenv

1. Install Pipenv:

   pip install pipenv

2. Install dependencies using Pipenv:

   pipenv install

3. Activate the environment:

   pipenv shell

Running the Project

1. Adjust the FREECAD_PATH in the scripts (run_all.py, genetic_algorithm.py, etc.) to point to your FreeCAD installation path.

2. To run a parametric analysis or genetic algorithm, execute:

   python main.py

   Choose between RunAll or GeneticAlgorithm methods when prompted.

Parametric Analysis

The parametric analysis will sweep through all specified parameter ranges and save the results to a CSV file.

Genetic Algorithm

The genetic algorithm will iterate over generations to minimize von Mises stress, saving the best model configuration and results at the end.

Project Structure

• main.py: Entry point to choose between parametric analysis and genetic algorithm.
• run_all.py: Runs the parametric FEA analysis over a range of parameters.
• genetic_algorithm.py: Implements the genetic algorithm for design optimization.
• parametric.py: Handles high-level parametric FEA functions.
• freecadmodel.py: Manages interaction with FreeCAD, including model parameter changes and FEA execution.
• loghandler.py: Configures logging.
• Makefile: Makefile for automating common tasks.
• pyproject.toml: Defines the project's dependencies and setup for Poetry.
• Pipfile and Pipfile.lock: Define dependencies for Pipenv.

Logs

All logs are stored in freecadparametricfea.log for debugging and tracking execution. Ensure you check this log if any issues arise during the execution of FEA or genetic algorithm runs.

Licence

This project is licensed under the MIT License. See the LICENSE.md file for more details.