高超声速飞行器多目标气动优化设计  

Multi-objective aerodynamic optimization design of hypersonic vehicle

作　　者：吴春晖 刘俊 刘庆豪 张鑫帅 罗世彬 WU Chunhui;LIU Jun;LIU Qinghao;ZHANG Xinshuai;LUO Shibin(School of Aeronautics and Astronautics,Central South University,Changsha 410083,China;School of Aeronautics and Astronautics,Zhejiang University,Hangzhou 310027,China)

机构地区：[1]中南大学航空航天学院,湖南长沙410083 [2]浙江大学航空航天学院,浙江杭州310027

出　　处：《飞行力学》2020年第1期8-13,共6页Flight Dynamics

摘　　要：随着高超声速飞行器的发展,其外形优化受到了广泛关注。应用一种新型的改进多目标布谷鸟优化搜索算法(IMOCS),采用修正的牛顿法与面元法相结合来获得高超声速飞行器的气动性能,采用自由变形参数化方法(FFD)来进行外形的参数化,以最大化容积率和升阻比为设计目标,开展了高超声速滑翔飞行器的多目标气动外形优化设计,获得了综合容积率及升阻比性能更高的气动外形,验证了方法的有效性。最后,将IMOCS算法和当前主流的多目标优化算法NSGA-Ⅱ进行了对比,结果表明,IMOCS算法的效果明显优于NSGA-Ⅱ。With the rapid development of hypersonic vehicle in industry, the aerodynamic shape design optimization is causes extensive attention in the research field. In this paper, a recently proposed improved multi-objective cuckoo search algorithm(IMOCS) was applied to the multi-objective optimization of a hypersonic gliding vehicle. In this optimization, the Newton method and panel method is combined to achieve the aerodynamic performance and free-form deformation(FFD) is used to parameterize the aerodynamic shape, the volume ratio and lift-to-drag ratio were maximized synchronously. The result verifies the effectiveness of the method. Finally, the IMOCS algorithm was compared to the well-known NSGA-Ⅱ optimization algorithm and the results shows that IMOCS outperforms NSGA-Ⅱ significantly.

关 键 词：高超声速飞行器 改进多目标布谷鸟算法 气动优化设计 多目标优化 

分 类 号：V221.3[航空宇航科学与技术—飞行器设计] V423