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Research Article | Open Access

The asymptotic concentration approach combined with isogeometric analysis for topology optimization of two-dimensional linear elasticity structures

Mingtao Cui1,2,3( )Wang Li1,2Guang Li1,2Xiaobo Wang1,2
Research Center for Applied Mechanics, School of Mechano-electronic Engineering, Xidian University, Xi'an 710071, China
Shaanxi Key Laboratory of Space Extreme Detection, Xi'an 710071, China
Department of Mechanical Engineering, McGill University, Montreal H3A 2K6, QC, Canada
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Abstract

We propose an asymptotic concentration approach combined with isogeometric analysis (IGA) for the topology optimization of two-dimensional (2D) linear elasticity structures under the commonly-used framework of the solid isotropic materials and penalty (SIMP) model. Based on the SIMP framework, the B-splines are used as basis functions to describe geometric model in structural finite element analysis, which closely combines geometric modeling with structural analysis. Isogeometric analysis is utilized to define the geometric characteristics of the 2D linear elasticity structures, which can greatly improve the calculation accuracy. In addition, to eliminate the gray-scale intervals usually caused by the intermediate density in the SIMP approach, we utilize the asymptotic concentration method to concentrate the intermediate density values on either 0 or 1 gradually. Consequently, the intermediate densities representing gray-scale intervals in topology optimization results are sufficiently eliminated by virtue of the asymptotic concentration method. The effectiveness and applicability of the proposed method are illustrated by several typical examples.

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Electronic Research Archive
Pages 3848-3878

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Cite this article:
Cui M, Li W, Li G, et al. The asymptotic concentration approach combined with isogeometric analysis for topology optimization of two-dimensional linear elasticity structures. Electronic Research Archive, 2023, 31(7): 3848-3878. https://doi.org/10.3934/era.2023196

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Received: 26 February 2023
Revised: 01 May 2023
Accepted: 06 May 2023
Published: 15 July 2023
©2023 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)