AI.news
主页教程研究工具模型AI创业讨论新闻WIKI🚀 创业库★ 投稿
AI+医疗机器人教育金融能源健康娱乐思考

VFEAgent: A Multimodal Agent Framework for End-to-End Automated Finite Element Analysis

arxiv.org
分享到

View PDF HTML (experimental)

Abstract:Finite Element Analysis (FEA) serves as the cornerstone of modern engineering design. However, its workflow is inherently complex and relies heavily on domain expertise. Although recent efforts have integrated Large Language Models (LLMs) into FEA, existing approaches face limitations in handling multimodal inputs and executing complex tasks. To address these limitations, we propose VFEAgent, an end-to-end multi-agent system designed to automate FEA modeling and simulation directly from input images and problem descriptions. Our methodology integrates two core components: (1) a multimodal vision-language multi-agent pipeline that employs ReAct-driven reasoning to extract structured FEA specifications from heterogeneous inputs and (2) a verification-first code synthesis framework, incorporating robust self-debugging and fallback mechanisms to ensure executability and physical validity. We systematically evaluated the system across various engineering mechanics scenarios. The results demonstrate that VFEAgent achieves a high success rate in generating complete and physically valid simulations, outperforming LLM-based baseline methods in reliability and correctness. These findings validate the feasibility of automating the complete FEA workflow, highlighting the framework's potential to liberate engineers from tedious manual analysis.

Submission history

From: Jiachen Zhang [view email]
[v1] Wed, 27 May 2026 18:34:04 UTC (11,350 KB)