基于响应面法的纤维金属层合板抗弹性能优化设计

纤维金属层合板因其复合材料的各向异性和层合结构特征而具有较好的可设计性，开展金属纤维层合板的优化设计研究对其力学性能的增强和轻量化具有重要意义。为提高纤维金属层合板的抗弹性能，基于响应面分析法对纤维金属层合板的铺层方向和铺层厚度进行了优化设计。采用Box-Behnken方法进行方案设计，以纤维金属层合板各铺层相对厚度比为设计变量，以结构的比吸能为设计目标，根据设计的方案进行参数化建模获取样本点，在对设计样本进行方差分析和参数估计的基础上，建立了结构比吸能的响应面模型并验证了其精确度。采用遗传算法对响应面方程进行寻优分析，通过显式动力学计算程序ABAQUS/Explicit验证优化效果。最终，在最优的铺层方案下，层合板的质量减小了11.70%，能量吸收增加了19.40%，抗弹性能显著提升。

Optimal design of ballistic performance of fiber-metal laminates based on the response surface method

Fiber-metal laminates are highly designable due to the characteristics of their constituent materials and laminate structure. They have the characteristics of anisotropy, large interface differences, and flexible design. Optimizing the design of fiber-metal laminates is of great significance to the enhancement of its mechanical properties and weight reduction. In order to improve the ballistic performance of fiber-metal laminates, of which the layer direction and layer thickness are optimized based on the response surface analysis method. For layup direction optimization, several layup directions are designed based on the corresponding principles according to the composite material layup optimization design requirements, and the energy absorptions of the corresponding structures are calculated, respectively, then the design plan for the better layup direction is screened out. For the optimization of ply thickness, the relative thickness ratio of each ply of the fiber-metal laminate is used as the design variable, and the specific energy absorption of the structure is the design goal. The Box-Behnken method is used to design the experiment. According to the test plan, the explicit dynamic calculation program ABAQUS/Explicit is used for parametric modeling to obtain test sample points, and the design test samples are analyzed by using variance analysis and parameter estimation, and the response surface model of structural specific energy absorption (SEA) is established. The errors between the experimental values and the predicted values are compared, and the model can be used for prediction; the genetic algorithm is used to optimize the obtained response surface equation, and the optimization effect is verified by ABAQUS/Explicit. The optimization result shows that the accuracy of the obtained response surface model is high. Under the premise of not increasing the thickness and weight of the laminate, the best layup plan is finally obtained, which improves the energy absorption capacity of the laminate. Finally, the mass of laminates decreases by 11.70% and the energy absorption increases by 19.40% under the optimal lamination scheme.