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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).