涵道气动优化设计方法

基于动量源方法进行涵道气动力的计算,分别采用响应面模型和基于神经网络模型对NASA涵道构型进行优化设计,并对优化结果采用CFD进行验证,优化结果表明两种优化方法均取得了一定的优化效果,悬停状态下,基于响应面方法,涵道拉力增加了19.4%,基于神经网络方法,涵道拉力增加了21.2%.并为了较为细致地研究涵道拉力产生的机理,在对涵道进行建模时,采用一种分区的方法,将涵道划分为6个区域,并得到了涵道拉力在此6个区域上的分布.计算结果表明:涵道唇口形成的负压是产生涵道附加拉力的主要因素,且靠近涵道内侧唇口提供的拉力占比重较大.该优化方法可以有效地应用于涵道外形的气动优化设计中. 

Aerodynamic optimization method for duct design

Based on momentum source method of calculating the ducted fan aerodynamic performance,the response surface method and neural network method were applied to aerodynamic optimization design of the NASA duct,and the optimization results were verified by CFD method.The optimization design results show that the two methods have achieved good effect.In the state of hovering,compared with the original duct,duct lift increased by 19.4% based on the response surface method,and duct lift increased by 21.2% based on the neural network method.In addition,in order to study the mechanism of duct lift more carefully,the duct was modeled,and partitioning method was adopted to divide the duct into 6 zones to obtain the duct lift distribution in the 6 regions.This shows that negative pressure formed on duct lip is a main factor to produce additional duct lift,and the duct lip near the interior duct provides higher lift.This optimization method can be effectively applied to the ducted fan aerodynamic optimization design.