{"title":"A modified dynamic relaxation form-finding method for symmetrical tensegrity structures with group theory and fuzzy clustering","authors":"","doi":"10.1016/j.mechrescom.2024.104310","DOIUrl":null,"url":null,"abstract":"<div><p>For tensegrity structures, there are many groups of cables and bars with symmetrical structures or similar internal forces. In this paper, an application of a fuzzy clustering algorithm in the context of form-finding processes for symmetric tensegrity structures is proposed. This algorithm aims to automate grouping, optimize form-finding strategies, and expedite convergence. Point sets are generated through the segmentation of structural components, and Hausdorff distance is used to extract spatial features. Following this, fuzzy clustering automatically groups components with geometric symmetry. The resultant clustering matrix facilitates the refinement of form-finding processes, thus reducing the computational load associated with solving the equilibrium matrix for internal forces within tensegrity structures. By clustering components with analogous internal forces, computational efficiency is enhanced. Additionally, this methodology refines numerical form-finding outcomes based on symmetrical attributes, improving form-finding precision.</p></div>","PeriodicalId":49846,"journal":{"name":"Mechanics Research Communications","volume":null,"pages":null},"PeriodicalIF":1.9000,"publicationDate":"2024-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Mechanics Research Communications","FirstCategoryId":"5","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0093641324000703","RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"MECHANICS","Score":null,"Total":0}
引用次数: 0
Abstract
For tensegrity structures, there are many groups of cables and bars with symmetrical structures or similar internal forces. In this paper, an application of a fuzzy clustering algorithm in the context of form-finding processes for symmetric tensegrity structures is proposed. This algorithm aims to automate grouping, optimize form-finding strategies, and expedite convergence. Point sets are generated through the segmentation of structural components, and Hausdorff distance is used to extract spatial features. Following this, fuzzy clustering automatically groups components with geometric symmetry. The resultant clustering matrix facilitates the refinement of form-finding processes, thus reducing the computational load associated with solving the equilibrium matrix for internal forces within tensegrity structures. By clustering components with analogous internal forces, computational efficiency is enhanced. Additionally, this methodology refines numerical form-finding outcomes based on symmetrical attributes, improving form-finding precision.
期刊介绍：
Mechanics Research Communications publishes, as rapidly as possible, peer-reviewed manuscripts of high standards but restricted length. It aims to provide:
• a fast means of communication
• an exchange of ideas among workers in mechanics
• an effective method of bringing new results quickly to the public
• an informal vehicle for the discussion
• of ideas that may still be in the formative stages
The field of Mechanics will be understood to encompass the behavior of continua, fluids, solids, particles and their mixtures. Submissions must contain a strong, novel contribution to the field of mechanics, and ideally should be focused on current issues in the field involving theoretical, experimental and/or applied research, preferably within the broad expertise encompassed by the Board of Associate Editors. Deviations from these areas should be discussed in advance with the Editor-in-Chief.
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