Lightweight design of cylindrical stiffened shells in launch vehicles by a dual-elite population sequential approximation optimization approach
Zhixiang Wang, Yongjun Lei, Zeping Wu, Xing Ouyang, Dapeng Zhang, Guanri Liu
Abstract
A nonlinear displacement-controlled loading dynamic method is employed to investigate the deformed shape evolution of stiffened shells from prebuckling to postbuckling field until collapse. Because of the time-consuming postbuckling analysis, the dual-elite population sequential approximation optimization (SAO) approach is proposed. A novel determination method of Gaussian kernel widths based on moment estimates is proposed to enhance the augmented radial basis function surrogate model. A novel adaptive parallel infilling strategy is then developed to balance the capabilities of local and global optimization. A dual-elite population strategy is further developed to exploit the information from already acquired sampling points. Finally, the framework of the proposed SAO approach, which is implemented in a distributed parallel way on high-performance clusters to further diminish computation costs, is presented. The efficiency of the algorithm is validated by the postbuckling lightweight optimization of a cylindrical stiffened shell, resulting in a reduction of 12.3% of the initial weight.