Stress-based bi-directional evolutionary topology optimization for structures with multiple materials

IF 8.7 2区 工程技术 Q1 Mathematics Engineering with Computers Pub Date : 2024-03-08 DOI:10.1007/s00366-024-01953-9
{"title":"Stress-based bi-directional evolutionary topology optimization for structures with multiple materials","authors":"","doi":"10.1007/s00366-024-01953-9","DOIUrl":null,"url":null,"abstract":"<h3>Abstract</h3> <p>Both multi-material and stress-based topology optimization problems have been extensively investigated. However, there are few studies on the stress-based topology optimization of multi-material structures. Hence, this work proposes a novel topology optimization method for minimizing the maximum von Mises stress of structures with multiple materials under volume constraints. An extended Bi-directional Evolutionary Structural Optimization (BESO) method based on discrete variables which can mitigate the well-known stress singularity problem is adopted. The global von Mises stress is established with the <em>p</em>-norm function, and the adjoint sensitivity analysis is derived. Two benchmark numerical examples are investigated to validate the effectiveness of the proposed method. The effects of key parameters including <em>p</em>-norm, sensitivity and density filter radii on the optimized results and the stress distributions are discussed. The influence of varying mesh densities on the optimized topologies are investigated in comparison with the multi-material stiffness maximization design. The topological results, for multi-material stress design, indicate that the maximum stress can be reduced compared with multi-material stiffness design. It concludes that the proposed approach can achieve a reasonable design that effectively controls the stress level and reduces the stress concentration effect at the critical stress areas of multi-material structures.</p>","PeriodicalId":11696,"journal":{"name":"Engineering with Computers","volume":"44 1","pages":""},"PeriodicalIF":8.7000,"publicationDate":"2024-03-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Engineering with Computers","FirstCategoryId":"5","ListUrlMain":"https://doi.org/10.1007/s00366-024-01953-9","RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"Mathematics","Score":null,"Total":0}
引用次数: 0

Abstract

Both multi-material and stress-based topology optimization problems have been extensively investigated. However, there are few studies on the stress-based topology optimization of multi-material structures. Hence, this work proposes a novel topology optimization method for minimizing the maximum von Mises stress of structures with multiple materials under volume constraints. An extended Bi-directional Evolutionary Structural Optimization (BESO) method based on discrete variables which can mitigate the well-known stress singularity problem is adopted. The global von Mises stress is established with the p-norm function, and the adjoint sensitivity analysis is derived. Two benchmark numerical examples are investigated to validate the effectiveness of the proposed method. The effects of key parameters including p-norm, sensitivity and density filter radii on the optimized results and the stress distributions are discussed. The influence of varying mesh densities on the optimized topologies are investigated in comparison with the multi-material stiffness maximization design. The topological results, for multi-material stress design, indicate that the maximum stress can be reduced compared with multi-material stiffness design. It concludes that the proposed approach can achieve a reasonable design that effectively controls the stress level and reduces the stress concentration effect at the critical stress areas of multi-material structures.

查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
基于应力的多材料结构双向进化拓扑优化
摘要 多材料和基于应力的拓扑优化问题已得到广泛研究。然而,基于应力的多材料结构拓扑优化研究却很少。因此,本研究提出了一种新的拓扑优化方法,用于在体积约束条件下最小化多材料结构的最大 von Mises 应力。本文采用了一种基于离散变量的扩展双向进化结构优化(BESO)方法,该方法可以缓解众所周知的应力奇异性问题。利用 p-norm 函数建立了全局 von Mises 应力,并推导出了临界灵敏度分析。研究了两个基准数值实例,以验证所提方法的有效性。讨论了关键参数(包括 p-norm、灵敏度和密度滤波器半径)对优化结果和应力分布的影响。与多材料刚度最大化设计相比,研究了不同网格密度对优化拓扑结构的影响。多材料应力设计的拓扑结果表明,与多材料刚度设计相比,最大应力可以减小。结论是所提出的方法可以实现合理的设计,有效控制应力水平,并减少多材料结构关键应力区域的应力集中效应。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
Engineering with Computers
Engineering with Computers 工程技术-工程:机械
CiteScore
16.50
自引率
2.30%
发文量
203
审稿时长
9 months
期刊介绍: Engineering with Computers is an international journal dedicated to simulation-based engineering. It features original papers and comprehensive reviews on technologies supporting simulation-based engineering, along with demonstrations of operational simulation-based engineering systems. The journal covers various technical areas such as adaptive simulation techniques, engineering databases, CAD geometry integration, mesh generation, parallel simulation methods, simulation frameworks, user interface technologies, and visualization techniques. It also encompasses a wide range of application areas where engineering technologies are applied, spanning from automotive industry applications to medical device design.
期刊最新文献
A universal material model subroutine for soft matter systems A second-generation URANS model (STRUCT- $$\epsilon $$ ) applied to a generic side mirror and its impact on sound generation Multiphysics discovery with moving boundaries using Ensemble SINDy and peridynamic differential operator Adaptive Kriging-based method with learning function allocation scheme and hybrid convergence criterion for efficient structural reliability analysis A new kernel-based approach for solving general fractional (integro)-differential-algebraic equations
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1