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Leveraging past FEA cases can improve accuracy and efficiency in analyzing new complex tasks. However, current engineering case retrieval methods struggle to measure semantic similarity between FEA cases. Therefore, this article proposed a method for measuring the similarity of FEA cases based on ontology semantic trees. FEA tasks are used as indexes for FEA cases, and an FEA case ontology is constructed. By using named entity recognition technology, pivotal entities are extracted from FEA tasks, enabling the instantiation of the FEA case ontology and the creation of a structured representation for FEA cases. Then, a multitree algorithm is used to calculate the semantic similarity of FEA cases. Finally, the correctness of this method was confirmed through an FEA case retrieval experiment on a pressure vessel. 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