Non-linear static and dynamic buckling analysis of laminated composite cylindrical shell embedded in non-linear elastic foundation using the swarm-based metaheuristic algorithms

被引:15
作者
Foroutan, Kamran [1 ]
Varedi-Koulaei, Seyyed Mojtaba [1 ]
Duc, Nguyen Dinh [2 ,3 ,4 ]
Ahmadi, Habib [1 ]
机构
[1] Shahrood Univ Technol, Fac Mech & Mechatron Engn, Shahrood, Iran
[2] Hanoi Univ Engn & Technol UET, Vietnam Natl Univ, Dept Technol & Engn Construct & Transportat, Hanoi, Vietnam
[3] Nguyen Tat Thanh Univ, NTT Inst High Technol, Dist 4, Ho Chi Minh City, Vietnam
[4] Sejong Univ, Dept Civil & Environm Engn, Natl Res Lab, 209 Neungdong Ro, Seoul 05006, South Korea
关键词
Laminated composite cylindrical shell; Non-linear elastic foundation; Grey wolf optimizer; Whale optimization algorithm; Grasshopper optimization algorithm; Salp swarm algorithm; Non-linear static and dynamic buckling; GRASSHOPPER OPTIMIZATION ALGORITHM; COMBINED EXTERNAL-PRESSURE; THIN SHELLS; FGM; VIBRATIONS; STABILITY;
D O I
10.1016/j.euromechsol.2021.104420
中图分类号
O3 [力学];
学科分类号
08 ; 0801 ;
摘要
In this paper, by determining the optimal fiber's angles for maximum critical buckling load, the non-linear static and dynamic buckling analyses of laminated composite cylindrical shells resting on non-linear elastic foundation subjected to external loading are investigated. The laminated composite cylindrical with three, four, and five layers is considered. In the present study, first, the optimal fiber's angles are found using the swarm-based metaheuristic algorithms, then, the non-linear static and dynamic buckling analyses are carried out at optimum fiber directions. According to classical shell theory, von-Karman equation, and Hooke's law, the stressstrain relations are derived for the laminated composite cylindrical shell. Then, based on the Galerkin's method, the discretized motion equation is obtained. For the optimization problem, the design variables are ply angles, and the objective function is maximizing the critical buckling load. Four recently developed swarm-based metaheuristic algorithms including, grey wolf optimizer (GWO), whale optimization algorithm (WOA), grasshopper optimization algorithm (GOA), and salp swarm algorithm (SSA), are utilized to solve these optimization problems. Based on the results, the optimization algorithms have improved the value of the critical buckling load significantly. Also, the WOA algorithm had better results than the others, while the GOA was the weakest.
引用
收藏
页数:20
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