Qiangwei Zhao , Chong Wang , Tongxing Zuo , Qianglong Wang , Zhenyu Liu
{"title":"一种抑制动态拓扑优化中低密度元素引起的特征频率和特征模态误差的域演化方法","authors":"Qiangwei Zhao , Chong Wang , Tongxing Zuo , Qianglong Wang , Zhenyu Liu","doi":"10.1016/j.advengsoft.2025.104011","DOIUrl":null,"url":null,"abstract":"<div><div>In dynamic topology optimization involving eigenfrequencies, the solution of the direct problem is expected to reasonably reflect the mechanical performance of the real structure. However, due to the presence of low-density elements in the fixed design domain, there are always some errors compared to the real structure obtained through post-processing. These errors include errors in eigenfrequencies and eigenmodes, which may adversely affect the optimization process. This issue becomes especially pronounced when optimizing higher-order eigenfrequencies, where the errors can lead to discontinuities in the solution space and hinder convergence. To overcome this issue, this paper proposes a domain evolution method (DEM). In this method, the fixed design domain is divided into three domains: the solid domain, the narrow-band, and the low-density domain. The direct problem analysis is solved within the computational domain, which consists of the solid domain and the narrow-band, while the low-density domain remains inactive. Several examples are used to validate the proposed method. Numerical results indicate that the errors primarily arise during the form-finding process and become more significant with increasing order of eigenfrequency. The proposed method effectively mitigates these errors, ensuring stable convergence of the optimization process. Furthermore, a comparative analysis between the proposed method and the traditional approach shows that, in higher-order problems, low-density elements are closely related to classical issues in dynamic topology optimization, including localized modes, repeated eigenfrequencies, and mode switching phenomena. This provides further insight into the intrinsic difficulties of high-order eigenfrequency topology optimization.</div></div>","PeriodicalId":50866,"journal":{"name":"Advances in Engineering Software","volume":"210 ","pages":"Article 104011"},"PeriodicalIF":5.7000,"publicationDate":"2025-08-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A domain evolution method to suppress the eigenfrequency and eigenmode errors caused by low-density elements in dynamic topology optimization\",\"authors\":\"Qiangwei Zhao , Chong Wang , Tongxing Zuo , Qianglong Wang , Zhenyu Liu\",\"doi\":\"10.1016/j.advengsoft.2025.104011\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>In dynamic topology optimization involving eigenfrequencies, the solution of the direct problem is expected to reasonably reflect the mechanical performance of the real structure. However, due to the presence of low-density elements in the fixed design domain, there are always some errors compared to the real structure obtained through post-processing. These errors include errors in eigenfrequencies and eigenmodes, which may adversely affect the optimization process. This issue becomes especially pronounced when optimizing higher-order eigenfrequencies, where the errors can lead to discontinuities in the solution space and hinder convergence. To overcome this issue, this paper proposes a domain evolution method (DEM). In this method, the fixed design domain is divided into three domains: the solid domain, the narrow-band, and the low-density domain. The direct problem analysis is solved within the computational domain, which consists of the solid domain and the narrow-band, while the low-density domain remains inactive. Several examples are used to validate the proposed method. Numerical results indicate that the errors primarily arise during the form-finding process and become more significant with increasing order of eigenfrequency. The proposed method effectively mitigates these errors, ensuring stable convergence of the optimization process. Furthermore, a comparative analysis between the proposed method and the traditional approach shows that, in higher-order problems, low-density elements are closely related to classical issues in dynamic topology optimization, including localized modes, repeated eigenfrequencies, and mode switching phenomena. This provides further insight into the intrinsic difficulties of high-order eigenfrequency topology optimization.</div></div>\",\"PeriodicalId\":50866,\"journal\":{\"name\":\"Advances in Engineering Software\",\"volume\":\"210 \",\"pages\":\"Article 104011\"},\"PeriodicalIF\":5.7000,\"publicationDate\":\"2025-08-20\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Advances in Engineering Software\",\"FirstCategoryId\":\"5\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S0965997825001498\",\"RegionNum\":2,\"RegionCategory\":\"工程技术\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Advances in Engineering Software","FirstCategoryId":"5","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0965997825001498","RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS","Score":null,"Total":0}
A domain evolution method to suppress the eigenfrequency and eigenmode errors caused by low-density elements in dynamic topology optimization
In dynamic topology optimization involving eigenfrequencies, the solution of the direct problem is expected to reasonably reflect the mechanical performance of the real structure. However, due to the presence of low-density elements in the fixed design domain, there are always some errors compared to the real structure obtained through post-processing. These errors include errors in eigenfrequencies and eigenmodes, which may adversely affect the optimization process. This issue becomes especially pronounced when optimizing higher-order eigenfrequencies, where the errors can lead to discontinuities in the solution space and hinder convergence. To overcome this issue, this paper proposes a domain evolution method (DEM). In this method, the fixed design domain is divided into three domains: the solid domain, the narrow-band, and the low-density domain. The direct problem analysis is solved within the computational domain, which consists of the solid domain and the narrow-band, while the low-density domain remains inactive. Several examples are used to validate the proposed method. Numerical results indicate that the errors primarily arise during the form-finding process and become more significant with increasing order of eigenfrequency. The proposed method effectively mitigates these errors, ensuring stable convergence of the optimization process. Furthermore, a comparative analysis between the proposed method and the traditional approach shows that, in higher-order problems, low-density elements are closely related to classical issues in dynamic topology optimization, including localized modes, repeated eigenfrequencies, and mode switching phenomena. This provides further insight into the intrinsic difficulties of high-order eigenfrequency topology optimization.
期刊介绍:
The objective of this journal is to communicate recent and projected advances in computer-based engineering techniques. The fields covered include mechanical, aerospace, civil and environmental engineering, with an emphasis on research and development leading to practical problem-solving.
The scope of the journal includes:
• Innovative computational strategies and numerical algorithms for large-scale engineering problems
• Analysis and simulation techniques and systems
• Model and mesh generation
• Control of the accuracy, stability and efficiency of computational process
• Exploitation of new computing environments (eg distributed hetergeneous and collaborative computing)
• Advanced visualization techniques, virtual environments and prototyping
• Applications of AI, knowledge-based systems, computational intelligence, including fuzzy logic, neural networks and evolutionary computations
• Application of object-oriented technology to engineering problems
• Intelligent human computer interfaces
• Design automation, multidisciplinary design and optimization
• CAD, CAE and integrated process and product development systems
• Quality and reliability.