摘要
为了提升爆炸冲击环境下车辆的防护性能,针对其底部防护结构设计中大规模计算、强非线性和多优化目标的特点,利用多物质单元与流-固耦合算法仿真车辆的动态响应。通过灵敏度分析,筛选底部结构中钣金件的厚度、几何形状等设计参数,并利用实验设计建立该问题的数学优化模型,结合帕累托最优的多目标遗传算法,得到该优化问题的帕累托解集空间曲面和一个最优设计方案,该方案在不增加结构质量的情况下,能显著提高车辆底部防护性能。
The multi-objective optimization of vehicle bottom structure under landmine explosion is a mass computation,strong-nonlinearity and high dimension multi-objective optimization problem. The protective vehicle structure response is simulated based on combination of LAE and FSI methods. The thickness and geometry parameters of vehicle bottom structure are screened with sensitivity analysis. A response surface is built by employing the experimental design and regression analysis. Eventually,the Pareto optimality,normal boundary intersection and multi-objective optimization genetic algorithms are applied to get the Pareto optimal front and an ideal solution which could give a comprehensive consideration of the contradiction between lightweight and protection capability.
出处
《兵工学报》
EI
CAS
CSCD
北大核心
2015年第6期1061-1066,共6页
Acta Armamentarii
基金
国家自然科学基金项目(51405232)
关键词
兵器科学与技术
防护型车辆
爆炸冲击波
帕累托最优
多目标优化
标准边界交叉法
ordnance science and technology
protective vehicle
blast wave
Pareto optimality
multiobjective optimization
normal-boundary intersection
