基于代理模型的空投装备气囊缓冲系统多目标优化

基于有限元法和控制体积法建立装备-气囊系统有限元模型,并采用试验数据对模型进行验证。复杂气囊系统着陆缓冲过程仿真计算资源消耗大,难以应用传统迭代方法进行参数优化。为克服这些问题,结合扩展拉丁超立方设计,以最大着陆冲击加速度和最大翻转角度为响应,采用径向基函数构建代理模型。在代理模型基础上,利用多目标遗传算法对主气囊高度、横向宽度及排气孔面积等气囊缓冲系统参数进行了多目标优化。优化结果表明:优化后最大冲击加速度减小了15.5%,最大翻转角度减小了70.3%,缓冲性能与横向稳定性均有所提高。

Multi-objective optimization of an airbag cushion system for airdropping equipment based on surrogate model

Based on finite element method and control volume method, a finite element model of equipment and its airbag cushion system were established and verified experimentally. The simulation of an impact of a few tenths of a second duration typically required tens of hours of CPU time. As a result, the optimization of the design based on a nonlinear model was very difficult by traditional iterative approach method. In order to overcome this problem with the design optimization of airbag cushion system for airdropping equipment, surrogate models were employed instead of the complex finite element model based on Extended Latin Hypercube method and Radial Basis Function. The height of airbag, the width of airbag and the area of vent hole were chosen as design variables. Then Pareto optimal solution sets based on response surfaces were obtained by multi-objective Genetic Algorithm. After optimization, the maximum acceleration reduces 19%, while the maximum attitude angle reduces 1%.The results show that the cushion performance and stability of airbags cushion system are obviously improved through optimization.