高超声速飞行器多目标气动优化设计

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。

Multi-objective aerodynamic optimization design of hypersonic vehicle

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.