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A triple acceleration method for topology optimization

delete2019-03-08
delete37
PRE
AI
Z
Zhongyuan Liao
Y
Yu Zhang
王应军 (Yingjun Wang) *
W
Weihua Li
DOI:10.1007/s00158-019-02234-6delete
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Abstract

Abstract

En 中文
This paper presents a triple acceleration method (TAM) for the topology optimization (TO), which consists of three parts: multilevel mesh, initial-value-based preconditioned conjugate-gradient (PCG) method, and local-update strategy. The TAM accelerates TO in three aspects including reducing mesh scale, accelerating solving equations, and decreasing the number of updated elements. Three benchmark examples are presented to evaluate proposed method, and the result shows that the proposed TAM successfully reduces 35-80% computational time with faster convergence compared to the conventional TO while the consistent optimization results are obtained. Furthermore, the TAM is able to achieve a higher speedup for large-scale problems, especially for the 3D TOs, which demonstrates that the TAM is an effective method for accelerating large-scale TO problems.
Keywords:
Topology optimization
Triple acceleration
Multilevel mesh
Preconditioned conjugate-gradient method
Local update
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Journal

Structural and Multidisciplinary Optimization cover
Structural and Multidisciplinary Optimization
IF:
4
Papers:
4.8K
Citations:
1.7W

Organization

S
south china university of technology
Scholars:
6.6W
Papers: 5.0W
Citations: 85