基于知识的有限元模型理想化方法

V. Prabhakar, S. Sheppard
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引用次数: 7

摘要

有限元分析(FEA)预处理被认为是一门艺术形式,需要多年的经验,才能由人类分析人员获得必要的专业知识,以有效和可靠地开发数值模型。在“真实的”世界中,设计模型很少与FEA的学术环境中采用的简单方法相匹配。具有复杂边界和加载条件的复杂三维零件是常见的问题。模型理想化是有限元分析的一个重要预处理阶段,旨在创建一个简化的分析几何,同时准确地表示设计形式、功能和意图。开发了基于规则的专家系统ide - x,该系统集成了面向对象编程、基于CSG特征的设计表示系统和理想化规则系统,该系统使用启发式和程序化方法去除或简化从有限元角度看无关紧要的几何特征。
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A knowledge-based approach to model idealization in FEM
Finite element analysis (FEA) pre-processing is considered to be an art-form requiring many years of experience before the necessary expertise can be obtained by human analysts to efficiently and reliable develop a numerical model. In the "real" world, design models rarely match the simplistic approach adopted in an academic environment to FEA. Complex 3D parts with intricate boundary and loading conditions are commonly dealt with. Model idealization is an important pre-processing phase of FEA, intended to create a simplified analysis geometry while accurately representing the design form, function and intent. A rule-based expert system named DESIDE-X has been developed which integrates object-oriented programming, a CSG feature-based design representation system and an idealization rule-system that uses heuristic and procedural methods to remove or simplify geometric features that are insignificant from the FEA perspective.<>
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