超临界翼型稳健型优化设计研究

The research of robust supercritical airfoil design optimization

基于标准遗传算法、RBF神经网络以及类函数/型函数变形技术建立了翼型气动优化设计系统,在选取3次CST方法即分别对翼型上下表面采用4个设计变量进行参数化,对某型客机基本翼型在给定设计指标下进行优化设计,分别研究了巡航状态下的气动优化,以及结合蒙特卡洛分析方法马赫数随机平均分布下的翼型稳健型优化设计。结果显示,优化后的翼型的气动特性有着显著提高。

Airfoil optimization design system is built,based on the standard genetic algorithm,RBF neural network and the class functions / shape function distortion technology.The thrice CST method which has four design variables is utilized to parameterize the upper and lower shape of the airfoil.Then the optimal airfoil design of a typical aircraft is done on condition that the design index is given.The aerodynamic optimization under the state of cruise and the robust airfoil shape optimization on the basis of Mach number average distribution under Monte Carlo analysis are studied.The results show that the aerodynamic characteristics of the optimized airfoil has improved significantly.