%0 Journal Article
%T 基于弯掠参数控制的压气机动叶优化设计
%A 王忠义
%A 曲锋
%A 万雷
%A 王萌
%J 大连海事大学学报
%D 2018
%X 通过数值模拟方法对NASA Stage35单级轴流压气机原型性能进行计算，选取合理的Bezier和B样条拟合曲线控制点个数来完成压气机动叶参数化拟合，获得参数化叶型.基于人工神经网络和遗传算法相结合的优化设计体系，通过控制叶片的弯掠特性参数对动叶进行寻优计算，最终提高压气机绝热效率.对比发现，对动叶的弯掠特性进行优化可以改变激波位置，减小叶片表面附面层的分离区，优化流场通道内的流动结构，减少流动损失，从而有效提高压气机的绝热效率.</br>The performance of NASA Stage35 single stage axial compressor prototype was calculated by numerical simulation. The parameterized fitting of the rotor in the compressor was performed by selecting the reasonable number of the control points of Bezier and B-spline curve to produce a suitable parameterized geometric. Through controlling bending-swept characteristics parameter, the optimization design of compressor rotor was carried out by using artificial neural network and genetic algorithm for the purpose of adiabatic efficiency improvement. Compared with the reference blade, the aerodynamic performances of the optimized blade are improved obviously. The shock position can be changed by optimizing the bending-swept characteristics of the moving blade. The area of boundary layer and loss can be decreased, the structure of flow can be optimized, and the adiabatic efficiency of the compressor can be improved effectively.
%K 国家自然科学基金资助项目(51309063
%K 51679051)
%K 中央高校基本科研业务费专项资金资助项目(HEUCFP201720)．
%U http://xb.dlmu.edu.cn/CN/abstract/abstract505.shtml