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Knowledge-guided lightweight method for large complex component based on geometric-stress feature correlation response

机译:基于几何应力特征相关响应的大型复合成分的知识引导的轻量级方法

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Complex geometric features and stress features as well as their intricate relationships are the important factors causing the complexity of lightweight for large component.In order to better coordinate the stress distribution with lightweight goal,a knowledge-guided lightweight method based on geometric-stress feature correlation response is proposed.Multistage decomposition and three-steps feature express strategy is utilized to construct the geometric features relationship model firstly.By combining the influence significance for stress features with the association grade for geometric features,and reasoning under lightweight expectations,the geometric-stress correlation knowledge is extracted.Furthermore,a knowledge-guided lightweight algorithm integrated knowledge correlation response with intelligent searching is proposed.Finally,the lightweight of X-type caterpillar frame is taken as example to demonstrate the effectiveness of this method.
机译:复杂的几何特征和压力特征以及它们复杂的关系是导致大型元件的重量重量复杂的重要因素。为了更好地协调轻量级目标,基于几何应力特征相关的知识引导的轻量级方法提出了响应.Muttage分解和三步特征表达策略首先构造几何特征关系模型。在几何特征与关联等级的关联等级相结合的影响意义,以及在轻量级期望下的推理,几何应力提取相关知识。提出了一种具有智能搜索的知识引导的轻量级算法集成知识相关响应。最后,X型毛毛虫帧的轻量级作为展示该方法的有效性。

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