Abstract

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.

Highlights

  • For the past decades, methods of topology optimization have achieved significant development and have been applied to a wide variety of industries

  • The implementation of topology optimization is driven by structural analysis, while the description of structure topology varies from voxels to topological

  • Because the value of the level set function is fully determined by the expansion coefficient a, it successfully avoids the difficulties of the updating scheme based on a spacial difference in unstructured meshes for the conventional level set method

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Summary

Introduction

Methods of topology optimization have achieved significant development and have been applied to a wide variety of industries. The refined 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. Both the coarse representation and the refined representation are interpolated by the prescribed RBFs and their according coefficients. The refined representation does not have to be involved in the optimization process and it can be used as a postoptimization process based on obtained optimal design variables rather than some heuristic schemes In other words, this decoupling way will not add to the computational burden of structural analysis while maintaining a smoother and more precise description.

RBFs parameterized level set method
Topology optimization formulation
Numerical examples
Numerical examples in two-dimension
Numerical examples in three-dimension
Conclusions and future works
Full Text
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