Stacking sequence optimization of composite cylindrical panels by sequential permutation search and Rayleigh-Ritz method

Stacking sequence optimization of composite cylindrical panels by sequential permutation search and Rayleigh-Ritz method
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DOI:
10.1016/j.euromechsol.2021.104262
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发表时间:
2021-03
期刊:
European Journal of Mechanics - A/Solids
影响因子:
--
通讯作者:
Zhao Jing;Qin Sun;Yongjie Zhang;K. Liang;Xu Li
Zhao Jing;Qin Sun;Yongjie Zhang;K. Liang;Xu Li
中科院分区:
其他
文献类型:
--
作者:
Zhao Jing;Qin Sun;Yongjie Zhang;K. Liang;Xu Li

文献摘要

相似文献

提出了一种新的顺序排列搜索(SPS)优化算法,用于复合材料圆柱板的铺层顺序设计,以最大化基频。该方法充分利用了复合材料层合板弯曲刚度的敏感信息、层合板参数的凸性以及层合板的弯扭耦合特性。通过在相应的堆叠位置处分配相同的层取向并且独立地设计符号配置,识别良好的初始点。随后,在最内侧位置或特定堆叠位置处检测敏感铺层取向,并且采用该敏感铺层取向来替代从内侧到外侧位置的其他现有铺层取向以寻求最优。重复这样的过程,直到在任何堆叠位置处没有敏感的层片取向可用。此外,符号优化算法(SOA)耦合在SPS调节弯扭耦合效应。Rayleigh-Ritz方法被开发来评估振动频率,可以容纳任意的边界。与分层优化方法(LOA)和遗传算法(GA)的优化结果进行了比较,证明了SPS的鲁棒性和有效性。
A novel sequential permutation search (SPS) optimization algorithm is proposed for the stacking sequence design of composite cylindrical panels to maximize the fundamental frequency. The SPS exploits the sensitive information of bending stiffness, the convex property of lamination parameters, and the bending-twisting coupling feature of composite laminates. By assigning identical ply orientation at respective stacking positions and designing the sign configuration independently, a good initial point is identified. Subsequently, sensitive ply orientation is detected at the innermost position or a specific stacking position, and this sensitive ply orientation is adopted to replace other existing ply orientations from the inner to the outer position to seek the optimum. Such procedures are repeated till no sensitive ply orientation is available at any stacking position. In addition, the sign optimization algorithm (SOA) is coupled in the SPS to regulate the bending-twisting coupling effects. The Rayleigh-Ritz method is developed to assess the vibration frequencies which can accommodate arbitrary boundaries. The optimal results of the SPS are compared with those of layerwise optimization approach (LOA) and genetic algorithm (GA), demonstrating the robustness and efficiency of SPS.