This study increases the strength of a honeycomb structure under a static load using an innovative and integrated multi-objective optimization procedure. Using a uniform design of experiment, a group of simulation experiments is generated. Finite-element analysis is utilized to determine the maximum von Mises stresses in the honeycomb core for three ASTM testing simulations. Kriging interpolation is used to produce three surrogate models that correspond to the three maximum von Mises stresses using the results of the simulation experiments in the uniform design. To allow three maximum von Mises stresses be reduced simultaneously, grey relational analysis, entropy weighting analysis and a genetic algorithm are used to resolve this multi-objective optimization problem. Compared with the original design, the optimal design induces 5.07, 17.31 and 10.54% improvements for ASTM C297, C364 and C365 testing simulations, respectively. Consequently, the integrated multi-objective optimization technique produces a stronger honeycomb core in the honeycomb structure.

本研究使用创新的集成多目标优化程序提高了静载荷下蜂窝结构的强度。使用统一的实验设计，生成一组模拟实验。有限元分析用于确定蜂窝芯中的最大 von Mises 应力，用于三个 ASTM 测试模拟。使用统一设计中的模拟实验结果，使用克里金插值法生成三个替代模型，这些模型对应于三个最大 von Mises 应力。为了同时减少三个最大冯米塞斯应力，采用灰色关联分析、熵加权分析和遗传算法来解决这个多目标优化问题。与原设计相比，最优设计引出 5.07、17.31 和 10。ASTM C297、C364 和 C365 测试模拟分别提高了 54%。因此，集成多目标优化技术在蜂窝结构中产生更强的蜂窝芯。