A Penalty Method for Non-Self-Adjoint Topology Optimization

Fuente: arXiv
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Autores principales: Gong, Wei, Ye, Yuanda
Formato: Preprint
Publicado: 2026
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author Gong, Wei
Ye, Yuanda
author_facet Gong, Wei
Ye, Yuanda
contents We propose a novel penalty method framework for the non-self-adjoint topology optimization problems, taking compliant mechanism problems as an example, by incorporating a convex nonlocal perimeter approximation scheme. We rigorously analyze the existence of solutions to the optimization problem derived from the penalty method. Furthermore, we establish that the discrete problem \(Γ\)-converges to the continuous problem, ensuring consistency across scales. To solve the discrete problem, we develop a projected gradient method that guarantees strict monotonic descent of the objective function. We also extend the framework to the heat dissipation problem and propose a generalized material interpolation function (GMIF), which allows for a targeted control of the topological connectivity in the resulting optimal design. Numerical experiments on the compliant mechanism and heat dissipation problems validate the effectiveness of the proposed method. This framework provides a robust approach to addressing complex optimization challenges in computational mathematics with potential applications in engineering design.
format Preprint
id arxiv_https___arxiv_org_abs_2603_00962
institution arXiv
publishDate 2026
record_format arxiv
spellingShingle A Penalty Method for Non-Self-Adjoint Topology Optimization
Gong, Wei
Ye, Yuanda
Optimization and Control
Numerical Analysis
65, 93
We propose a novel penalty method framework for the non-self-adjoint topology optimization problems, taking compliant mechanism problems as an example, by incorporating a convex nonlocal perimeter approximation scheme. We rigorously analyze the existence of solutions to the optimization problem derived from the penalty method. Furthermore, we establish that the discrete problem \(Γ\)-converges to the continuous problem, ensuring consistency across scales. To solve the discrete problem, we develop a projected gradient method that guarantees strict monotonic descent of the objective function. We also extend the framework to the heat dissipation problem and propose a generalized material interpolation function (GMIF), which allows for a targeted control of the topological connectivity in the resulting optimal design. Numerical experiments on the compliant mechanism and heat dissipation problems validate the effectiveness of the proposed method. This framework provides a robust approach to addressing complex optimization challenges in computational mathematics with potential applications in engineering design.
title A Penalty Method for Non-Self-Adjoint Topology Optimization
topic Optimization and Control
Numerical Analysis
65, 93
url https://arxiv.org/abs/2603.00962