An improved Stress-Influence-Function (ISIF) based method for continuum structural topology optimization with stress constraints

IF 2.4 2区数学 Q1 MATHEMATICS, APPLIED

Journal of Computational and Applied Mathematics Pub Date : 2026-10-01 Epub Date: 2026-02-09 DOI:10.1016/j.cam.2026.117429

Zhenxian Luo , Haijun Xia , Linyuan Li

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引用次数: 0

Abstract

The topology optimization of continuum structures considering stress constraints is a classic hotspot. Recently, the Stress-Influence-Function with adaptive strength feature (SIF-ASF) approach was proposed for stress constrained continuum topology optimization. The stress influence function sets strong penalization on the local strength failure to achieve the stress constraints. However, this strong penalization may lead to oscillation or divergence due to a sharp barrier of the stress. In this study, an improved stress influence function, which has good boundedness and smoothness, is presented to alleviate nonlinearity in optimization and ensure numerical stability of optimization iterations. In addition, a new adaptive strategy for the strength feature factor is proposed to achieve good control on the maximum stress. By comparing with existing methods through two numerical examples, the advantages of the proposed method on numerical stability and weight reduction are verified. Finally, some useful conclusions are given objectively.

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基于改进应力影响函数的应力约束连续体结构拓扑优化方法

考虑应力约束的连续体结构拓扑优化是一个经典的研究热点。近年来，针对应力约束连续体拓扑优化问题，提出了具有自适应强度特征的应力影响函数（SIF-ASF）方法。应力影响函数对局部强度失效设置强惩罚，实现应力约束。然而，这种强烈的惩罚可能导致振荡或发散由于一个尖锐的障碍的压力。本文提出了一种改进的应力影响函数，该函数具有良好的有界性和光滑性，可以缓解优化过程中的非线性，保证优化迭代的数值稳定性。此外，提出了一种新的强度特征因子自适应策略，以实现对最大应力的良好控制。通过两个算例与现有方法进行比较，验证了该方法在数值稳定性和减重方面的优势。最后，客观地给出了一些有益的结论。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Journal of Computational and Applied Mathematics 数学-应用数学

CiteScore

5.40

自引率

4.20%

发文量

437

审稿时长

3.0 months

期刊介绍： The Journal of Computational and Applied Mathematics publishes original papers of high scientific value in all areas of computational and applied mathematics. The main interest of the Journal is in papers that describe and analyze new computational techniques for solving scientific or engineering problems. Also the improved analysis, including the effectiveness and applicability, of existing methods and algorithms is of importance. The computational efficiency (e.g. the convergence, stability, accuracy, ...) should be proved and illustrated by nontrivial numerical examples. Papers describing only variants of existing methods, without adding significant new computational properties are not of interest. The audience consists of: applied mathematicians, numerical analysts, computational scientists and engineers.