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

发布时间：2018-12-09 16:57

【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。
[Abstract]:Under the premise of high volume loading fraction, how to improve the structural integrity of solid rocket motor is the main problem in the optimization design of solid rocket motor. Based on particle swarm optimization algorithm (PSO), a fast optimization design method for 3D solid rocket motor (SSRM) was proposed, and the parametric modeling of a 3D solid rocket motor (SRM) was realized by using PCL, a secondary development tool of MSC.Patran. Without changing the volume loading fraction, PSO algorithm and genetic algorithm (GA) are used to complete the optimization design of the engine configuration. The results show that both of the two methods can meet the requirements of optimization design, but the computational time of PSO algorithm is 42 shorter than that of GA algorithm, and the proposed method can quickly realize the optimization design of solid rocket motor. Improve the structural integrity of complex three-dimensional solid rocket motor.
【作者单位】：国防科技大学航天科学与工程学院;
【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)
【分类号】：V435.21

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