基于鲁棒性的概率优化设计在薄壁构件耐撞性中的应用

汽车结构的耐撞性及碰撞吸能优化是现代汽车工业重要的研究内容。耐撞性的优化涉及材料与结构的众多参数，传统的确定性优化设计、碰撞仿真及实验往往只能在一定程度上改善结构的碰撞性能，而无法评估设计参数的可靠性和目标函数的鲁棒性，以及在给定可靠性约束条件下使目标函数的鲁棒性达到最优状态。将实验设计、响应面模型和蒙特卡罗模拟技术相结合，构造了基于产品质量工程的6σ鲁棒性优化设计方法，实现了对设计目标的优化，并提高了设计变量的可靠性和目标函数的鲁棒性。

Application Study on Robust-based Probabilistic Optimization Design in Thin-walled Structure of Crashworthiness

In the automotive industry, structural optimization in crashworthiness and energy absorption capability is of special importance. Optimization in crashworthiness concerns with many parameters of material and structure. However, conventional design, crash simulation and experiment can only improve the structural crashworthiness to some extent, which can not assess the reliability of design parameters and the robust of objective function, at the same time, nor achieve a global optimization performance subjected to the preassigned probabilistie constraints. Through the applications of design of experiments and response surface models and Monte Carlo simulation technique into the design optimization, the paper established a 6a based probabilistic design optimization method. The method searches the optimum results for the design object,and improves the reliability of the design parameters and the robust of objective function.