ABSTRACT Computational simulation is critical in the modern engineering design process. Currently, the use of simulation is limited by the time-consuming process of converting CAD assemblies into FEA models which are efficient to run and yet sufficiently accurate. In addition to the geometric representation of components, analysts require additional knowledge to describe the complete 3D simulation model. To speed up the generation of CAE models from CAD assemblies, we propose to capture high-level modelling and idealisation decisions, characterising the simulation intent, into a knowledge-based CAE model. In this framework, a simulation intent ontology formalises and structures the analysis parameters, the modelling and idealisation decisions. The ontological concepts and relations required to incorporate two of the key capabilities, cellular modelling and equivalencing, are described. Cellular modelling introduces the concept of cells, which subdivide the 3D space, and to which simulation attributes can be attached. Equivalencing maintains the link between different representations of the cells required for different analyses throughout the analysis lifecycle. Illustrative examples show how the knowledge-based CAE model is used to manage the idealisation decisions and to apply inference rules replicating current modelling practices.

中文翻译：

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在本体中捕获仿真意图：CAD 和 CAE 集成应用程序

摘要 计算仿真在现代工程设计过程中至关重要。目前，模拟的使用受到将 CAD 装配体转换为运行高效且足够准确的 FEA 模型的耗时过程的限制。除了组件的几何表示外，分析师还需要额外的知识来描述完整的 3D 仿真模型。为了加快从 CAD 组件生成 CAE 模型，我们建议将表征仿真意图的高级建模和理想化决策捕获到基于知识的 CAE 模型中。在这个框架中，模拟意图本体形式化和结构化分析参数、建模和理想化决策。包含两个关键能力所需的本体概念和关系，描述了细胞建模和等效。细胞建模引入了细胞的概念，它细分了 3D 空间，并且可以附加模拟属性。等效保持整个分析生命周期中不同分析所需的不同单元格表示之间的联系。说明性示例展示了如何使用基于知识的 CAE 模型来管理理想化决策并应用复制当前建模实践的推理规则。