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文章以数值仿真为手段,研究了气囊缓冲登陆系统的冲击动力学多目标优化问题。首先,以类似于“猎兔犬”着陆缓冲系统为对象,确立了以囊内初始气压与收缩绳刚度为设计变量,以缓冲系统的首次冲击最大过载和囊体织物最大应力为目标函数的多目标优化问题。随后基于D最优试验设计,采用移动最小二乘(Moving Least Square,MLS)构建了各个目标函数的代理模型,并对目标函数随设计变量的变化规律进行了探讨。最后,采用遗传算法完成了缓冲系统的冲击性能优化,并给出设计空间中关于最大过载与织物最大应力的Pareto前沿。研究结果表明,MLS模型优化算法十分适用于解决非线性程度较高的冲击动力学优化问题,并且在替代真实模型仿真计算时不仅具有较高的近似精度而且具有高速的分析效率。
In this paper, by means of numerical simulation, the impact dynamics multi-objective optimization problem of airbag cushion landing system is studied. First, aiming at the design of landing pressure bump system similar to that of Beagle dog, the initial pressure of air bag and the stiffness of shrink rope are established as the design variables to buffer the maximum impact of the system and the maximum stress of the fabric Multi-objective optimization problem. Then based on the D-optimal experimental design, the agent model of each objective function is constructed by Moving Least Square (MLS), and the variation of the objective function with the design variables is discussed. Finally, using the genetic algorithm, the impact performance of the buffer system is optimized, and the Pareto frontier in the design space about the maximum overload and the maximum fabric stress is given. The results show that MLS model optimization algorithm is very suitable for solving the problem of impact dynamics optimization with high nonlinearity, and it not only has high approximate accuracy but also has high-speed analysis efficiency when it replaces the real model.