Foam-Agent

You can visit https://deepwiki.com/csml-rpi/Foam-Agent for a comprehensive introduction and to ask any questions interactively.

Introduction

Foam-Agent is a multi-agent framework that automates complex OpenFOAM-based CFD simulation workflows from natural language inputs. By leveraging advanced AI techniques, Foam-Agent significantly lowers the expertise barrier for Computational Fluid Dynamics while maintaining modeling accuracy.

Our framework offers three key innovations:

• Hierarchical multi-index retrieval system with specialized indices for different simulation aspects
• Dependency-aware file generation system ensuring consistency across configuration files
• Iterative error correction mechanism that diagnoses and resolves simulation failures without human intervention

Features

🔍 Enhanced Retrieval System

• Hierarchical retrieval covering case files, directory structures, and dependencies
• Specialized vector index architecture for improved information retrieval
• Context-specific knowledge retrieval at different simulation stages

🤖 Multi-Agent Workflow Optimization

• Architect Agent interprets requirements and plans file structures
• Input Writer Agent generates configuration files with consistency management
• Runner Agent executes simulations and captures outputs
• Reviewer Agent analyzes errors and proposes corrections

🛠️ Intelligent Error Correction

• Error pattern recognition for common simulation failures
• Automatic diagnosis and resolution of configuration issues
• Iterative refinement process that progressively improves simulation configurations

📐 External Mesh File Support

• Custom mesh integration with GMSH .msh files
• Boundary condition specification through natural language requirements
• Currently supports GMSH ASCII 2.2 format mesh files
• Seamless workflow from mesh import to simulation execution

Example Usage:

python foambench_main.py --openfoam_path $WM_PROJECT_DIR --output ./output --prompt_path ./user_requirement.txt --custom_mesh_path ./tandem_wing.msh

Example Mesh File: The geometry.msh file in this repository is taken from the tandem wing tutorial and demonstrates a 3D tandem wing simulation with NACA 0012 airfoils.

Requirements Format: In your user_req_tandem_wing.txt, describe the boundary conditions and physical parameters for your custom mesh. The agent will automatically detect the mesh type and generate appropriate OpenFOAM configuration files.

Getting Started

1. Clone the repository and install dependencies

git clone https://github.com/csml-rpi/Foam-Agent.git
cd Foam-Agent
git checkout v1.0.0
conda env create -f environment.yml
conda activate openfoamAgent

2. Install and configure OpenFOAM v10

Foam-Agent requires OpenFOAM v10. Please follow the official installation guide for your operating system:

• Official installation: https://openfoam.org/version/10/

Verify your installation with:

echo $WM_PROJECT_DIR

and the result should be

/opt/openfoam10

or something similar.

WM_PROJECT_DIR is an environment variable that comes with your OpenFOAM installation, indicating the location of OpenFOAM on your computer.

3. Database preprocessing (first-time setup)

Before running any workflow, you must preprocess the OpenFOAM tutorial and command database. This can be done automatically or manually.

Recommended: Automatic preprocessing

python foambench_main.py --openfoam_path $WM_PROJECT_DIR --output ./output --prompt_path ./user_requirement.txt

This script will automatically run all necessary preprocessing scripts in database/script/ and then launch the main workflow.

Manual preprocessing (advanced)

If you prefer to run preprocessing scripts manually, execute the following:

python database/script/tutorial_parser.py --output_dir=./database/raw --wm_project_dir=$WM_PROJECT_DIR
python database/script/faiss_command_help.py --database_path=./database
python database/script/faiss_allrun_scripts.py --database_path=./database
python database/script/faiss_tutorials_structure.py --database_path=./database
python database/script/faiss_tutorials_details.py --database_path=./database

4. Run a demo workflow

Option 1: Automated benchmark (recommended)

python foambench_main.py --openfoam_path $WM_PROJECT_DIR --output ./output --prompt_path ./user_requirement.txt

Option 2: Directly run the main agent

python src/main.py --prompt_path ./user_requirement.txt --output_dir ./output

• You can also specify a custom mesh:

python src/main.py --prompt_path ./user_requirement.txt --output_dir ./output --custom_mesh_path ./my_mesh.msh

Example user_requirement.txt

do a Reynolds-Averaged Simulation (RAS) pitzdaily simulation. Use PIMPLE algorithm. The domain is a 2D millimeter-scale channel geometry. Boundary conditions specify a fixed velocity of 10m/s at the inlet (left), zero gradient pressure at the outlet (right), and no-slip conditions for walls. Use timestep of 0.0001 and output every 0.01. Finaltime is 0.3. use nu value of 1e-5.

5. Configuration and environment variables

• Default configuration is in src/config.py. You can modify model provider, database path, and other parameters there.
• You must set the OPENAI_API_KEY environment variable if using OpenAI/Bedrock models.

6. Troubleshooting

• OpenFOAM environment not found: Ensure you have sourced the OpenFOAM bashrc and restarted your terminal.
• Database not initialized: Make sure you have run foambench_main.py or all scripts in database/script/.
• Missing dependencies: After activating the environment, run pip install -r requirements.txt if needed.
• API key errors: Ensure OPENAI_API_KEY is set in your environment.

Citation

If you use Foam-Agent in your research, please cite our paper:

@article{yue2025foam,
  title={Foam-Agent: Towards Automated Intelligent CFD Workflows},
  author={Yue, Ling and Somasekharan, Nithin and Cao, Yadi and Pan, Shaowu},
  journal={arXiv preprint arXiv:2505.04997},
  year={2025}
}