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Autori principali: Chen, Huangxin, Dong, Piaopiao, Wang, Dong, Wang, Xiao-Ping
Natura: Preprint
Pubblicazione: 2024
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Accesso online:https://arxiv.org/abs/2401.01069
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author Chen, Huangxin
Dong, Piaopiao
Wang, Dong
Wang, Xiao-Ping
author_facet Chen, Huangxin
Dong, Piaopiao
Wang, Dong
Wang, Xiao-Ping
contents In this paper, we propose an iterative convolution-thresholding method (ICTM) based on prediction-correction for solving the topology optimization problem in steady-state heat transfer equations. The problem is formulated as a constrained minimization problem of the complementary energy, incorporating a perimeter/surface-area regularization term, while satisfying a steady-state heat transfer equation. The decision variables of the optimization problem represent the domains of different materials and are represented by indicator functions. The perimeter/surface-area term of the domain is approximated using Gaussian kernel convolution with indicator functions. In each iteration, the indicator function is updated using a prediction-correction approach. The prediction step is based on the variation of the objective functional by imposing the constraints, while the correction step ensures the monotonically decreasing behavior of the objective functional. Numerical results demonstrate the efficiency and robustness of our proposed method, particularly when compared to classical approaches based on the ICTM.
format Preprint
id arxiv_https___arxiv_org_abs_2401_01069
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle A prediction-correction based iterative convolution-thresholding method for topology optimization of heat transfer problems
Chen, Huangxin
Dong, Piaopiao
Wang, Dong
Wang, Xiao-Ping
Numerical Analysis
Computational Engineering, Finance, and Science
In this paper, we propose an iterative convolution-thresholding method (ICTM) based on prediction-correction for solving the topology optimization problem in steady-state heat transfer equations. The problem is formulated as a constrained minimization problem of the complementary energy, incorporating a perimeter/surface-area regularization term, while satisfying a steady-state heat transfer equation. The decision variables of the optimization problem represent the domains of different materials and are represented by indicator functions. The perimeter/surface-area term of the domain is approximated using Gaussian kernel convolution with indicator functions. In each iteration, the indicator function is updated using a prediction-correction approach. The prediction step is based on the variation of the objective functional by imposing the constraints, while the correction step ensures the monotonically decreasing behavior of the objective functional. Numerical results demonstrate the efficiency and robustness of our proposed method, particularly when compared to classical approaches based on the ICTM.
title A prediction-correction based iterative convolution-thresholding method for topology optimization of heat transfer problems
topic Numerical Analysis
Computational Engineering, Finance, and Science
url https://arxiv.org/abs/2401.01069