基于遗传算法的升力体外形优化设计

升力体由于低热流率再入物理特性和高效的内部容积利用率,是高超声速飞行器气动外形的一种典型布局.文章对升力体飞行器进行参数化数值建模,并提取其表征外形的参数作为设计变量,综合考虑飞行器再入过程中的气动力、气动热、容积利用率及稳定性等性能指标.运用多目标混合遗传算法对升力体进行了多变量、多约束下的气动外形优化设计,获得了再入飞行器外形的最优Pareto解.数值模拟结果表明,典型状态下最优Pareto解与CFD结果相差12%,验证了优化结果的准确性.

Configuration Design of Lifting Body Based on Genetic Algorithm

Lifting body is a typical layout of hypersonic vehicle because of its low heat flux and high volumetric efficiency. This paper established a numerical modeling of lifting body to calculate these performance indexes, such as the aerodynamic force, the aerodynamic heating, the volumetric efficiency and the stability. The multi-objective hybrid genetic algorithm was used to optimize the aerodynamic configuration of lifting body under multiple variables and multiple constraints. The optimal Pareto solution of reentry vehicle configuration was obtained. The results of numerical simulation indicate that the difference between Pareto optimal solution and CFD results was about 12%, the accuracy was verified by CFD.