When composite laminated panels under compression are allowed to continuously loaded into the moderately deep postbuckling regime, further weight savings can be achieved. For this purpose, this work presents an optimization scheme for the design of postbuckling behavior of composite laminates. An efficient tool, termed the Koiter perturbation-based approximation FE method, is developed to obtain the postbuckling behavior of composite laminated panel. The initial postbuckling response is represented by the nonlinear predictor solved by the reduced order model, while the deformations in the moderately deep postbuckling regime are obtained by applying the correction phase under the design load. Five different indices, including the critical buckling load, postbuckling stiffness, stiffness residual, and in-plane and out-of-plane deformations under the design load, are proposed to assess various postbuckling performances of the compressed panel. The postbuckling indices can be flexibly selected to be either the objective or the nonlinear constraints in the lamination optimization. A genetic algorithm is subsequently used to determine the optimal lamination configuration for the most favorable postbuckling performance. The optimizations of composite laminates under uniaxial and biaxial compression for different boundary conditions are carefully studied and discussed with the consideration of initial geometric imperfections.

当复合层压板在压缩状态下连续加载到中等深度的后屈曲状态时，可以进一步减轻重量。为此，这项工作提出了一种优化方案，用于设计复合材料层压板的后屈曲性能。开发了一种有效的工具，称为基于Koiter摄动的近似有限元方法，以获得复合层压板的后屈曲特性。初始后屈曲响应由降阶模型求解的非线性预测器表示，而中等深度后屈曲状态的变形是通过在设计载荷下应用校正阶段获得的。五个不同指标，包括临界屈曲载荷，屈曲后刚度，刚度残差，提出了在设计载荷下的平面内和平面外变形，以评估压缩面板的各种后屈曲性能。在层压优化中，可以灵活选择后屈曲指数作为目标约束或非线性约束。随后使用遗传算法来确定最佳层压结构，以实现最佳的后屈曲性能。在考虑初始几何缺陷的情况下，仔细研究和讨论了复合层压板在单轴和双轴压缩下针对不同边界条件的优化问题。在层压优化中，可以灵活选择后屈曲指数作为目标约束或非线性约束。随后使用遗传算法来确定最佳层压结构，以实现最佳的后屈曲性能。在考虑初始几何缺陷的情况下，仔细研究和讨论了复合层压板在单轴和双轴压缩下针对不同边界条件的优化问题。可以在层压优化中灵活选择后屈曲指数作为目标约束或非线性约束。随后使用遗传算法来确定最佳层压结构，以实现最佳的后屈曲性能。在考虑初始几何缺陷的情况下，仔细研究和讨论了复合层压板在单轴和双轴压缩下针对不同边界条件的优化问题。