用自然语言一键自动完成复杂流体仿真全流程，降低工程门槛。
Foam-Agent 2.0: An End-to-End Composable Multi-Agent Framework for Automating CFD Simulation in OpenFOAM
- 多智能体框架通过分解任务实现端到端自动化，支持建模、求解与可视化。
- 在110个任务上成功率达88.2%，远超现有系统（55.5%）。
- 模块化设计适合集成到其他智能体系统，助力科研探索。
计算流体动力学（CFD）是工程领域的关键仿真工具，但学习成本高、手动设置复杂。为此，我们提出Foam-Agent，一个基于自然语言提示的多智能体框架，可全自动完成OpenFOAM全流程仿真。其核心创新包括：1）首次实现从建模到可视化的全链路自动化，包含由Meshing Agent处理外部网格或生成新几何（使用Gmsh），自动生成高性能计算提交脚本，以及通过ParaView进行后处理；2）采用模型上下文协议（MCP）构建可组合服务架构，将核心功能拆分为独立可调用工具，便于与其他智能体系统（如Claude-code）集成；3）利用分层多索引检索增强生成（Hierarchical Multi-Index RAG）和依赖感知生成流程，确保配置准确性。在包含110个任务的基准测试中，使用Claude 3.5 Sonnet时成功率达88.2%，显著优于现有框架（MetaOpenFOAM为55.5%）。该系统大幅降低了CFD应用门槛，展示了专用多智能体系统在科学计算中的潜力。代码已开源：https://github.com/csml-rpi/Foam-Agent。
原文摘要 · Abstract (English)
Computational Fluid Dynamics (CFD) is an essential simulation tool in engineering, yet its steep learning curve and complex manual setup create significant barriers. To address these challenges, we introduce Foam-Agent, a multi-agent framework that automates the entire end-to-end OpenFOAM workflow from a single natural language prompt. Our key innovations address critical gaps in existing systems: 1. An Comprehensive End-to-End Simulation Automation: Foam-Agent is the first system to manage the full simulation pipeline, including advanced pre-processing with a versatile Meshing Agent capable of handling external mesh files and generating new geometries via Gmsh, automatic generation of HPC submission scripts, and post-simulation visualization via ParaView. 2. Composable Service Architecture: Going beyond a monolithic agent, the framework uses Model Context Protocol (MCP) to expose its core functions as discrete, callable tools. This allows for flexible integration and use by other agentic systems, such as Claude-code, for more exploratory workflows. 3. High-Fidelity Configuration Generation: We achieve superior accuracy through a Hierarchical Multi-Index RAG for precise context retrieval and a dependency-aware generation process that ensures configuration consistency. Evaluated on a benchmark of 110 simulation tasks, Foam-Agent achieves an 88.2% success rate with Claude 3.5 Sonnet, significantly outperforming existing frameworks (55.5% for MetaOpenFOAM). Foam-Agent dramatically lowers the expertise barrier for CFD, demonstrating how specialized multi-agent systems can democratize complex scientific computing. The code is public at https://github.com/csml-rpi/Foam-Agent.
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