摘要
翼型及机翼优化设计中,设计变量的个数对优化算法的收敛速度及代理模型的精度有很大的影响。因此,在精确描述翼型的同时,发展较少设计变量的翼型参数化方法对翼型优化设计有着重要的意义。本文基于CST(class function/shape function transformation)翼型参数化方法对Kriging模型的预测精度进行研究,并采用改进的粒子群优化算法构建气动优化设计系统。某亚声速机翼单点减阻设计及超临界翼型的稳健性设计表明该系统具有较高的设计质量,方法可靠,有较高的工程应用前景。
In the airfoil and wing optimizatioh design process, both the convergence speed of optimization algorithm and the precision of surrogate model will be greatly influenced by the number of design variables. So it is very important for airfoil optimization design to develop a precise airfoil parametric approach with less design variables. The precision of Kriging model was studied based on CST（class function/shape function transformation） airfoil parametric approach in this article. An optimization design system was developed based on improved particle swarm optimization algorithm. Through the subsonic wing＇s drag reduction design and robust design, the system has been proved to be reliable, useful and of high design quality in engineering.
出处
《空气动力学学报》
EI
CSCD
北大核心
2012年第4期443-449,共7页
Acta Aerodynamica Sinica
作者简介
李静（1985-），女，博士，研究方向：飞行器设计空气动力学．E—mail：jingself@163．com
