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 form-finding process is implemented by solvin...
Saved in:
| Main Authors: | , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Wiley
2020-01-01
|
| Series: | Advances in Civil Engineering |
| Online Access: | http://dx.doi.org/10.1155/2020/1942373 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1832546888746795008 |
|---|---|
| author | Xiaodong Feng Wanpeng Zhang Yaozhi Luo Sergio Zlotnik |
| author_facet | Xiaodong Feng Wanpeng Zhang Yaozhi Luo Sergio Zlotnik |
| author_sort | Xiaodong Feng |
| collection | DOAJ |
| 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 form-finding process is implemented by solving a linear homogeneous system concerning the self-equilibrium system. The 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. The 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. |
| format | Article |
| id | doaj-art-89e1c41259c4458dabe8987dedcf84a6 |
| institution | Kabale University |
| issn | 1687-8086 1687-8094 |
| language | English |
| publishDate | 2020-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Advances in Civil Engineering |
| spelling | doaj-art-89e1c41259c4458dabe8987dedcf84a62025-02-03T06:46:55ZengWileyAdvances in Civil Engineering1687-80861687-80942020-01-01202010.1155/2020/19423731942373Optimal Prestress Investigation on Tensegrity Structures Using Artificial Fish Swarm AlgorithmXiaodong Feng0Wanpeng Zhang1Yaozhi Luo2Sergio Zlotnik3College of Civil Engineering, Shaoxing University, Shaoxing 312000, ChinaCollege of Civil Engineering, Shaoxing University, Shaoxing 312000, ChinaCollege of Civil Engineering and Architecture, Zhejiang University, Hangzhou 310058, ChinaLaboratori de Càlcul Numèric (LaCàN), E.T.S. Ingenieros de Caminos, Universitat Politècnica de Catalunya, Barcelona Tech, Barcelona 08034, SpainTo 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 form-finding process is implemented by solving a linear homogeneous system concerning the self-equilibrium system. The 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. The 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.http://dx.doi.org/10.1155/2020/1942373 |
| spellingShingle | Xiaodong Feng Wanpeng Zhang Yaozhi Luo Sergio Zlotnik Optimal Prestress Investigation on Tensegrity Structures Using Artificial Fish Swarm Algorithm Advances in Civil Engineering |
| title | 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_short | Optimal Prestress Investigation on Tensegrity Structures Using Artificial Fish Swarm Algorithm |
| title_sort | optimal prestress investigation on tensegrity structures using artificial fish swarm algorithm |
| url | http://dx.doi.org/10.1155/2020/1942373 |
| work_keys_str_mv | AT xiaodongfeng optimalprestressinvestigationontensegritystructuresusingartificialfishswarmalgorithm AT wanpengzhang optimalprestressinvestigationontensegritystructuresusingartificialfishswarmalgorithm AT yaozhiluo optimalprestressinvestigationontensegritystructuresusingartificialfishswarmalgorithm AT sergiozlotnik optimalprestressinvestigationontensegritystructuresusingartificialfishswarmalgorithm |