基于Isight的自适应翼型前缘气动优化设计  

Aerodynamic Optimization Design of Adaptive Airfoil Leading Edge Based on Isight

作　　者：周晨[1] 王志瑾[1] 支骄杨 

机构地区：[1]南京航空航天大学飞行器先进设计技术国防重点学科实验室,南京210016

出　　处：《上海交通大学学报》2014年第8期1122-1126,1133,共6页Journal of Shanghai Jiaotong University

基　　金：江苏省普通高校研究生科研创新计划资助项目(CXLX13_163);中央高校基本科研业务费专项资金资助;江苏高校优势学科建设工程资助项目

摘　　要：为了兼顾翼型在各个飞行状态下的气动效率,基于Isight优化设计平台对自适应翼型前缘进行了气动优化设计研究.首先对Hicks-Henne型函数进行了改进,实现了翼型前缘的参数化描述;然后采用拉丁超立方实验设计方法生成样本点,并运用CFD软件进行翼型流场的气动计算,进而利用该样本数据完成对RBF神经网络的训练;最后对神经网络近似模型应用多岛遗传算法进行优化.以NACA 0006翼型为例,采用上述组合优化策略以升阻比为目标函数进行优化设计.仿真结果表明:改进后的Hicks-Henne型函数较好地描述了翼型前缘;组合优化方法显著提高了翼型气动优化效率.Aimed to gain a high aerodynamic efficiency in various flight conditions,the aerodynamic optimization of the adaptive airfoil leading edge was conducted based on Isight platform.First,a modified method of original Hicks-Henne shape function was adopted to parametrically describe the leading edge.Then,Latin hypercube sampling was applied to generate the samples,whose aerodynamic performances were obtained from a series of CFD simulations.Subsequently,those simulated data sets were used to train the RBF neural network.Finally,the optimization of the objective function using the multi-island genetic algorithm（MIGA）based on the neural network approximation model was performed to achieve the optimal results.The lift to drag ratio optimization design of NACA 0006 was performed as an example using this combined strategy.The results show that the modified Hicks-Henne shape function describes the airfoil leading edge with satisfaction.The combined optimization method evidently improves the efficiency of the airfoil aerodynamic optimization procedure.

关 键 词：翼型气动优化 实验设计 神经网络 遗传算法 Hicks-Henne型函数 

分 类 号：V211.3[航空宇航科学与技术—航空宇航推进理论与工程]