{"title":"基于nurbs的构件投影的柔性特征映射拓扑优化。","authors":"Reinier Giele, Can Ayas, Matthijs Langelaar","doi":"10.1007/s00158-025-04047-2","DOIUrl":null,"url":null,"abstract":"<p><p>A novel feature mapping topology optimization method is presented, allowing for the creation of features with highly flexible shapes. The method easily integrates with conventional density-based formulations. Feature shapes are implicitly described by NURBS control points. The feature shape dictates the locations of two sets of projection points to represent the solid void boundaries. At these projection points, density values are projected onto a finite element mesh. The method optimizes feature shapes in a gradient-based manner, while allowing more specific control of the feature shapes than classical level set methods. Several feature fields can be combined to create a final output design. It is found that the eminent flexibility of the NURBS-based feature definition is a benefit but also requires additional regularization to guarantee stability of the optimization.</p>","PeriodicalId":21994,"journal":{"name":"Structural and Multidisciplinary Optimization","volume":"68 6","pages":"126"},"PeriodicalIF":3.6000,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12241164/pdf/","citationCount":"0","resultStr":"{\"title\":\"Flexible feature mapping topology optimization using NURBS-based component projection.\",\"authors\":\"Reinier Giele, Can Ayas, Matthijs Langelaar\",\"doi\":\"10.1007/s00158-025-04047-2\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>A novel feature mapping topology optimization method is presented, allowing for the creation of features with highly flexible shapes. The method easily integrates with conventional density-based formulations. Feature shapes are implicitly described by NURBS control points. The feature shape dictates the locations of two sets of projection points to represent the solid void boundaries. At these projection points, density values are projected onto a finite element mesh. The method optimizes feature shapes in a gradient-based manner, while allowing more specific control of the feature shapes than classical level set methods. Several feature fields can be combined to create a final output design. It is found that the eminent flexibility of the NURBS-based feature definition is a benefit but also requires additional regularization to guarantee stability of the optimization.</p>\",\"PeriodicalId\":21994,\"journal\":{\"name\":\"Structural and Multidisciplinary Optimization\",\"volume\":\"68 6\",\"pages\":\"126\"},\"PeriodicalIF\":3.6000,\"publicationDate\":\"2025-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12241164/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Structural and Multidisciplinary Optimization\",\"FirstCategoryId\":\"5\",\"ListUrlMain\":\"https://doi.org/10.1007/s00158-025-04047-2\",\"RegionNum\":2,\"RegionCategory\":\"工程技术\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2025/7/9 0:00:00\",\"PubModel\":\"Epub\",\"JCR\":\"Q2\",\"JCRName\":\"COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Structural and Multidisciplinary Optimization","FirstCategoryId":"5","ListUrlMain":"https://doi.org/10.1007/s00158-025-04047-2","RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2025/7/9 0:00:00","PubModel":"Epub","JCR":"Q2","JCRName":"COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS","Score":null,"Total":0}
Flexible feature mapping topology optimization using NURBS-based component projection.
A novel feature mapping topology optimization method is presented, allowing for the creation of features with highly flexible shapes. The method easily integrates with conventional density-based formulations. Feature shapes are implicitly described by NURBS control points. The feature shape dictates the locations of two sets of projection points to represent the solid void boundaries. At these projection points, density values are projected onto a finite element mesh. The method optimizes feature shapes in a gradient-based manner, while allowing more specific control of the feature shapes than classical level set methods. Several feature fields can be combined to create a final output design. It is found that the eminent flexibility of the NURBS-based feature definition is a benefit but also requires additional regularization to guarantee stability of the optimization.
期刊介绍:
The journal’s scope ranges from mathematical foundations of the field to algorithm and software development, and from benchmark examples to case studies of practical applications in structural, aero-space, mechanical, civil, chemical, naval and bio-engineering.
Fields such as computer-aided design and manufacturing, uncertainty quantification, artificial intelligence, system identification and modeling, inverse processes, computer simulation, bio-mechanics, bio-medical applications, nano-technology, MEMS, optics, chemical processes, computational biology, meta-modeling, DOE and active control of structures are covered when the topic is closely related to the optimization of structures or fluids.
Structural and Multidisciplinary Optimization publishes original research papers, review articles, industrial applications, brief notes, educational articles, book reviews, conference diary, forum section, discussions on papers, authors´ replies, obituaries, announcements and society news.