Optimal prestress investigation on tensegrity structures using artificial fish swarm algorithm

To obtain the optimal uniform prestress of a tensegrity structure with geometric configuration given, a novel method is developed for prestress design of tensegrity structures by utilizing the artificial fish swarm algorithm (AFSA). In the beginning, the formfinding process is implemented by solving...

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Detalles Bibliográficos
Autores: Feng, Xiaodong, Zhang, Wanpeng, Luo, Yaozhi, Zlotnik, Sergio|||0000-0001-9674-8950
Tipo de recurso: artículo
Fecha de publicación:2020
País:España
Institución:Universitat Politècnica de Catalunya (UPC)
Repositorio:UPCommons. Portal del coneixement obert de la UPC
Idioma:inglés
OAI Identifier:oai:upcommons.upc.edu:2117/335981
Acceso en línea:https://hdl.handle.net/2117/335981
https://dx.doi.org/10.1155/2020/1942373
Access Level:acceso abierto
Palabra clave:Strength of materials
Resistència de materials
Classificació AMS::74 Mechanics of deformable solids::74S Numerical methods
Àrees temàtiques de la UPC::Matemàtiques i estadística::Anàlisi numèrica::Mètodes numèrics
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oai_identifier_str oai:upcommons.upc.edu:2117/335981
network_acronym_str ES
network_name_str España
repository_id_str
spelling Optimal prestress investigation on tensegrity structures using artificial fish swarm algorithmFeng, XiaodongZhang, WanpengLuo, YaozhiZlotnik, Sergio|||0000-0001-9674-8950Strength of materialsResistència de materialsClassificació AMS::74 Mechanics of deformable solids::74S Numerical methodsÀrees temàtiques de la UPC::Matemàtiques i estadística::Anàlisi numèrica::Mètodes numèricsTo obtain the optimal uniform prestress of a tensegrity structure with geometric configuration given, a novel method is developed for prestress design of tensegrity structures by utilizing the artificial fish swarm algorithm (AFSA). In the beginning, the formfinding process is implemented by solving a linear homogeneous system concerning the self-equilibrium system. )e issue is subsequently performed as a minimum problem by regulating the value of an objective function where the unilateral condition and the stress uniformity condition are entirely considered. )e AFSA is adopted to search for the global minimum, leading to a set of initial prestresses that guarantee all the above conditions. Two illustrative examples have been fully studied to prove the accuracy and efficiency of the presented approach in prestress design of tensegrities according to the practical requirements. Furthermore, the numerical examples investigated in this paper confirm that the AFSA has explicit advantages of rapid convergence and overcoming the local minima.Peer ReviewedHindawi20202020-09-0820212021-01-26journal articlehttp://purl.org/coar/resource_type/c_6501AMhttp://purl.org/coar/version/c_ab4af688f83e57aainfo:eu-repo/semantics/articleapplication/pdfhttps://hdl.handle.net/2117/335981https://dx.doi.org/10.1155/2020/1942373reponame:UPCommons. Portal del coneixement obert de la UPCinstname:Universitat Politècnica de Catalunya (UPC)Inglésengopen accesshttp://purl.org/coar/access_right/c_abf2info:eu-repo/semantics/openAccessoai:upcommons.upc.edu:2117/3359812026-05-27T15:37:01Z
dc.title.none.fl_str_mv Optimal prestress investigation on tensegrity structures using artificial fish swarm algorithm
title Optimal prestress investigation on tensegrity structures using artificial fish swarm algorithm
spellingShingle Optimal prestress investigation on tensegrity structures using artificial fish swarm algorithm
Feng, Xiaodong
Strength of materials
Resistència de materials
Classificació AMS::74 Mechanics of deformable solids::74S Numerical methods
Àrees temàtiques de la UPC::Matemàtiques i estadística::Anàlisi numèrica::Mètodes numèrics
title_short Optimal prestress investigation on tensegrity structures using artificial fish swarm algorithm
title_full Optimal prestress investigation on tensegrity structures using artificial fish swarm algorithm
title_fullStr Optimal prestress investigation on tensegrity structures using artificial fish swarm algorithm
title_full_unstemmed Optimal prestress investigation on tensegrity structures using artificial fish swarm algorithm
title_sort Optimal prestress investigation on tensegrity structures using artificial fish swarm algorithm
dc.creator.none.fl_str_mv Feng, Xiaodong
Zhang, Wanpeng
Luo, Yaozhi
Zlotnik, Sergio|||0000-0001-9674-8950
author Feng, Xiaodong
author_facet Feng, Xiaodong
Zhang, Wanpeng
Luo, Yaozhi
Zlotnik, Sergio|||0000-0001-9674-8950
author_role author
author2 Zhang, Wanpeng
Luo, Yaozhi
Zlotnik, Sergio|||0000-0001-9674-8950
author2_role author
author
author
dc.subject.none.fl_str_mv Strength of materials
Resistència de materials
Classificació AMS::74 Mechanics of deformable solids::74S Numerical methods
Àrees temàtiques de la UPC::Matemàtiques i estadística::Anàlisi numèrica::Mètodes numèrics
topic Strength of materials
Resistència de materials
Classificació AMS::74 Mechanics of deformable solids::74S Numerical methods
Àrees temàtiques de la UPC::Matemàtiques i estadística::Anàlisi numèrica::Mètodes numèrics
description To obtain the optimal uniform prestress of a tensegrity structure with geometric configuration given, a novel method is developed for prestress design of tensegrity structures by utilizing the artificial fish swarm algorithm (AFSA). In the beginning, the formfinding process is implemented by solving a linear homogeneous system concerning the self-equilibrium system. )e issue is subsequently performed as a minimum problem by regulating the value of an objective function where the unilateral condition and the stress uniformity condition are entirely considered. )e AFSA is adopted to search for the global minimum, leading to a set of initial prestresses that guarantee all the above conditions. Two illustrative examples have been fully studied to prove the accuracy and efficiency of the presented approach in prestress design of tensegrities according to the practical requirements. Furthermore, the numerical examples investigated in this paper confirm that the AFSA has explicit advantages of rapid convergence and overcoming the local minima.
publishDate 2020
dc.date.none.fl_str_mv 2020
2020-09-08
2021
2021-01-26
dc.type.none.fl_str_mv journal article
http://purl.org/coar/resource_type/c_6501
AM
http://purl.org/coar/version/c_ab4af688f83e57aa
dc.type.openaire.fl_str_mv info:eu-repo/semantics/article
format article
dc.identifier.none.fl_str_mv https://hdl.handle.net/2117/335981
https://dx.doi.org/10.1155/2020/1942373
url https://hdl.handle.net/2117/335981
https://dx.doi.org/10.1155/2020/1942373
dc.language.none.fl_str_mv Inglés
eng
language_invalid_str_mv Inglés
language eng
dc.rights.none.fl_str_mv open access
http://purl.org/coar/access_right/c_abf2
dc.rights.openaire.fl_str_mv info:eu-repo/semantics/openAccess
rights_invalid_str_mv open access
http://purl.org/coar/access_right/c_abf2
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Hindawi
publisher.none.fl_str_mv Hindawi
dc.source.none.fl_str_mv reponame:UPCommons. Portal del coneixement obert de la UPC
instname:Universitat Politècnica de Catalunya (UPC)
instname_str Universitat Politècnica de Catalunya (UPC)
reponame_str UPCommons. Portal del coneixement obert de la UPC
collection UPCommons. Portal del coneixement obert de la UPC
repository.name.fl_str_mv
repository.mail.fl_str_mv
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score 15.301603

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