Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/109383
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dc.contributorDepartment of Building and Real Estateen_US
dc.creatorZhuang, Zen_US
dc.creatorXu, Fen_US
dc.creatorYe, Jen_US
dc.creatorTong, Wen_US
dc.creatorChen, Zen_US
dc.creatorWeng, Yen_US
dc.date.accessioned2024-10-08T03:25:04Z-
dc.date.available2024-10-08T03:25:04Z-
dc.identifier.issn1615-147Xen_US
dc.identifier.urihttp://hdl.handle.net/10397/109383-
dc.language.isoenen_US
dc.publisherSpringeren_US
dc.rights© The Author(s) 2024en_US
dc.rightsThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.en_US
dc.rightsThe following publication Zhuang, Z., Xu, F., Ye, J. et al. A 262-line Matlab code for the level set topology optimization based on the estimated gradient field in the body-fitted mesh. Struct Multidisc Optim 67, 171 (2024) is available at https://doi.org/10.1007/s00158-024-03891-y.en_US
dc.subjectBody-fitted meshen_US
dc.subjectEducational Matlab codeen_US
dc.subjectGradient field estimationen_US
dc.subjectLevel set methoden_US
dc.subjectTopology optimizationen_US
dc.titleA 262-line Matlab code for the level set topology optimization based on the estimated gradient field in the body-fitted meshen_US
dc.typeJournal/Magazine Articleen_US
dc.identifier.volume67en_US
dc.identifier.issue9en_US
dc.identifier.doi10.1007/s00158-024-03891-yen_US
dcterms.abstractTopology optimization is an influential technique engineers and designers employ to achieve desirable material distribution within a designated domain. This educational article introduces a concise and efficient Matlab code, comprising only 262 lines, developed explicitly for the Level Set topology optimization based on the estimated Gradient Field (GFLS) in the body-fitted mesh. Unlike conventional level set methods that rely on the upwind scheme employed in the structured meshes, the proposed algorithm adopts the per-cell linear estimation of the discrete gradient vectors in the body-fitted mesh framework to obtain the velocity field and update the level set function. The Matlab code, named GFLS262, consists of a 62-line main program, 41-line finite element analysis function, and 48-line sub-functions, enabling the implementation of the GFLS method in 2D scenarios. Additionally, a 111-line function describes an improved mesh generator incorporated in the code to facilitate the generation of body-fitted meshes. The superiority of this innovative approach over the previous optimization methods with invariant meshes is demonstrated through various benchmark examples. For ease of access and further learning, the educational Matlab code is available on the website and can also be found in the Appendix section of this article.en_US
dcterms.accessRightsopen accessen_US
dcterms.bibliographicCitationStructural and multidisciplinary optimization, Sept 2024, v. 67, no. 9, 171en_US
dcterms.isPartOfStructural and multidisciplinary optimizationen_US
dcterms.issued2024-09-
dc.identifier.eissn1615-1488en_US
dc.identifier.artn171en_US
dc.description.validate202410 bcchen_US
dc.description.oaVersion of Recorden_US
dc.identifier.FolderNumberOA_TA-
dc.description.fundingSourceOthersen_US
dc.description.fundingTextHong Kong Polytechnic Universityen_US
dc.description.pubStatusPublisheden_US
dc.description.TASpringer Nature (2024)en_US
dc.description.oaCategoryTAen_US
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