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Research Article | Open Access

A polygonal topology optimization method based on the alternating active-phase algorithm

Mingtao Cui1,3( )Wennan Cui2Wang Li1Xiaobo Wang1
Research Center for Applied Mechanics, School of Mechano-Electronic Engineering, Xidian University, Xi'an 710071, China
School of Electronic Engineering, Xi'an Shiyou University, Xi'an 710300, China
Department of Mechanical Engineering, McGill University, Montreal H3A 2K6, QC, Canada
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Abstract

We propose a polygonal topology optimization method combined with the alternating active-phase algorithm to address the multi-material problems. During the process of topology optimization, the polygonal elements generated by signed distance functions are utilized to discretize the structural design domain. The volume fraction of each material is considered as a design variable and mapped to its corresponding element variable through a filtering matrix. This method is used to solve a multi-material structural topology optimization problem of minimizing compliance, in which a descriptive model is established by using the alternating active-phase algorithm and the solid isotropic microstructure with penalty theory. This method can accomplish the topology optimization of multi-material structures with complex curve boundaries, eliminate the phenomena of checkerboard patterns and a one-node connection, and avoid sensitivity filtering. In addition, this method possesses fine numerical stability and high calculation accuracy compared to the topology optimization methods that use quadrilateral elements or triangle elements. The effectiveness and feasibility of this method are demonstrated through several commonly used and representative numerical examples.

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Electronic Research Archive
Pages 1191-1226

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Cite this article:
Cui M, Cui W, Li W, et al. A polygonal topology optimization method based on the alternating active-phase algorithm. Electronic Research Archive, 2024, 32(2): 1191-1226. https://doi.org/10.3934/era.2024057

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Received: 28 October 2023
Revised: 17 December 2023
Accepted: 21 December 2023
Published: 29 January 2024
©2024 the Author(s), licensee AIMS Press.

This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0)