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The document introduces FEABench, a benchmark designed to evaluate large language models (LLMs) and LLM agents on their ability to simulate and solve physics, mathematics, and engineering problems using finite element analysis (FEA). It presents a comprehensive evaluation scheme, including 15 verified problems and a larger set of 200 tasks, to assess the reasoning and problem-solving capabilities of LLMs in engineering contexts. The benchmark aims to advance automation in engineering by enabling LLMs to int

Author

Rosó Péraz

Language

EN