多级涡轮多工况气动优化设计研究

Study on aerodynamic optimization design of multistage axial turbine under multiple working conditions

School of Energy Science and Engineering, Harbin Instituteof Technology, Harbin, 150001, China

摘要: 采用将准三维设计和多级局部优化联合的多级涡轮多工况气动优化设计流程对某三级航空发动机涡轮进行多级气动优化设计.优化联合采用人工神经网络和遗传算法对各列叶栅进行三维局部优化,流场计算采用全三维粘性流N-S方程求解.通过优化设计,改善了各列的性能,并对各列间参数进行了优化匹配,两种工况的总效率均提高1%,总流量基本不变,总体性能提高,达到设计要求.
- 航空、航天推进系统 /
- 涡轮 /
- 多工况优化设计 /
- 遗传算法 /
- 人工神经网络
Abstract: A three-stage axial turbine was redesigned by using an aerodynamic optimization design process of multistage axial turbine in multiple working conditions,which combines quasi-3Ddesign methods and multistage local optimization methods.Genetic algorithm and artificial neural network were employed to 3Dlocal optimization of various cascades.The flow field was computed through a three-dimensional viscosity Navier-Stokes equation.With optimization design,the performance of every cascade was optimized,and the overall efficiency increased by 1% under the reliable total flow mass,indicating that the total performance was improved to satisfy the design requirements.
- aerospace propulsion system /
- turbine /
- optimization design under multiple working conditions /
- genetic algorithm /
- artificial neural network

[1]	Kammerer S,Mayer J F,Paffrath M,et al.Three-dimensional optimization of turbomachinery bladings using sensitivity analysis[R].ASME GT2003-38037.
[2]	Arnone A,Bonaiuti D,Focacci A,et al.Parametric optimization of a high lift turbine vane[R].ASME GT2004-54308.
[3]	Hasenjager M,Sendhoff B,Sonoda T,et al.Three dimensional aerodynamic optimization for an ultra-low aspect ratio transonic turbine stator blade[R].ASME GT2005-68680,2005.
[4]	SU Jiexian,FENG Guotai,HU Kung.A direct problem method on S2 stream surface for transonic compressor in aeroengine[R].Corpus of the Second Sino-Soviet Space Navigation Proseminar,1992.
[5]	Vanderplaats G N.Numerical optimization techniques for engineering design[M].New York:McGraw-Hill,1984.
[6]	Goldberg D E.Genetic algorithms in search,optimization,and machine learning[M].Boston:Addison Wesley Professional,1989.
[7]	Demeulenaere A,Ligout A,Hirsch C.Application of multipoint optimization to the design of turbomachinery blades[R].ASME GT2004-53110,2004.
[8]	Fottner L.Test cases for computation of internal flows in aero engine components[R].AGARD-AR-275,1990.