基于粒子群算法的三维固体火箭发动机药形快速优化方法  

Fast Optimization Method of 3D Solid Rocket Motor Grain Based on Particle Swarm Algorithm

作　　者：崔辉如 唐国金[1] 

机构地区：[1]国防科技大学航天科学与工程学院,长沙410073

出　　处：《导弹与航天运载技术》2016年第3期19-23,共5页Missiles and Space Vehicles

基　　金：国家自然科学基金(11272348);国防科技大学科研计划资助项目(JC13-01-03)

摘　　要：在高体积装填分数前提下,如何提高发动机的结构完整性是固体火箭发动机药形优化设计面临的主要问题。通过提出基于粒子群优化算法(PSO)的三维固体火箭发动机药形快速优化设计方法,采用MSC.Patran的二次开发工具PCL实现某三维固体火箭发动机药柱的参数化建模,在不改变体积装填分数的前提下,分别采用PSO算法和遗传算法(GA)完成该发动机药形的优化设计。结果表明,两种方法均能满足优化设计要求,但PSO算法比GA算法的计算时间缩短了42%,所提方法可快速实现固体火箭发动机药形优化设计,提高复杂三维固体火箭发动机的结构完整性能。How to improve the structural integrity of solid rocket motor （SRM） with high loading fraction was one of the main problems during its configuration optimization design. Based on the particle swarm optimization（PSO）, a fast optimization method is proposed to obtain the best 3D SRM grain configuration. Parameterized model of a 3D SRM grain was created with patran command language （PCL）, the optimal project of grain configuration was done by using the PSO and Genetic Algorithm（GA） respectively without changing its volumetric loading fraction. The results showed that both of optimization methods met the requirements of optimization design, but the computation time of PSO was reduced by 42 % compared with GA. The method proposed could realize optimization design of SRM grain configuration efficiently, and the structural integrity of actual complex 3D SRM could be improved.

关 键 词：药形优化 粒子群优化算法 体积装填分数 结构完整性 

分 类 号：V435.21[航空宇航科学与技术—航空宇航推进理论与工程]