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A multi-discretization scheme for topology optimization based on the parameterized level set method

机译:基于参数化级别设置方法的拓扑优化多离散化方案

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摘要

In the framework of the parameterized level set method, the structural analysis and topology representation can be implemented in a decoupling way. A parameterized level set function, typically, using radial basis functions (RBFs), is a linear combination of a set of prescribed RBFs and coefficients. Once the coefficients are determined, the theoretical level set function is determined. Exploiting this inherent property, we propose a multi-discretization method based on the parameterized level set method. In this approach, a coarse discretization is applied to do the structural analysis whereas another dense discretization is employed to represent the structure topology. As a result, both efficient analysis and high-resolution topological design are available. Note that the dense discretization only accounts for a more precise and smooth description of the theoretical level set function rather than introduce extra design freedom or incur interference to structural analysis or the optimization process. In other words, this decoupling way will not add to the computational burden of structural analysis or result in non-uniqueness of converged results for a particular analysis setting. Numerical examples in both two-dimension and three-dimension show effectiveness and applicability of the proposed method.
机译:在参数化级别设置方法的框架中,结构分析和拓扑表示可以以解耦方式实现。参数化级别设置功能通常使用径向基函数(RBF)是一组规定的RBF和系数的线性组合。一旦确定系数,确定理论级别集合函数。利用这种固有的属性,我们提出了一种基于参数化级别设置方法的多离散化方法。在这种方法中,施加粗略离散化以进行结构分析,而采用另一种密集的离散化来表示结构拓扑。因此,有效的分析和高分辨率拓扑设计都可提供。请注意,密集的离散化仅占理论级别设定功能的更精确和平滑描述,而不是引入额外的设计自由或对结构分析或优化过程的干扰。换句话说,这种解耦方式不会增加结构分析的计算负担,或者导致特定分析设置的融合结果的非唯一性。两维和三维的数值例示表所提出的方法的有效性和适用性。

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