Automated Multi-part CHT Design Optimization Workflow

This repository contains an end-to-end automated framework for the design optimization of Conjugate Heat Transfer (CHT) systems. The workflow integrates parametric CAD, automated meshing, and high-fidelity CFD within a Bayesian Optimization (BO) loop.

🚀 Project Status: Early Research Phase

Note: This is an initial implementation developed for experimental research. Some components are optimized for a specific local environment and may require adjustment for different hardware setups.

🛠️ Automated Pipeline Overview

The framework executes a complete "CAD-to-Opt" cycle:

1. Parametric CAD: (FreeCAD & CadQuery)
2. Assembly & Geometry: Volume extraction and Share Topology (Ansys SpaceClaim)
3. Automated Meshing: Conformal mesh generation (PyPrimeMesh)
4. CFD Analysis: CHT simulation (Ansys PyFluent)
5. Optimization: Bayesian active learning (Scikit-Learn/Scipy)

⚙️ Critical Prerequisites

• Python 3.11 (⚠️ Mandatory: Required for compatibility with the FreeCAD Python API/library).
• Ansys Ecosystem: SpaceClaim, PrimeMesh, Fluent (accessed via PyAnsys).
• FreeCAD & CadQuery: For parametric geometry generation.

📂 Key Files

• AutoFlow_2.py: The main execution script. This file contains the complete automated optimization loop.
  • Usage: Refer to the internal comments for configuration.
• Helper Functions: Modularized functions (e.g., Function_BO.py, Funciton_automesh.py) are included.

📄 Citation

If you find this framework useful for your research, please acknowledge the corresponding paper (to be published).