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
Descripción
Sumario: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.