一级半透平级叶片型线的气动优化设计研究

Aerodynamic Optimization Design of the Blade Profile in One and Half Turbine Stage

针对一级半透平级的直叶片,采用遗传算法和人工神经网络耦合气动性能分析方法,进行三维优化设计。优化设计目标是在流量和进出口气流角的约束条件下,等熵效率最大。优化设计结果表明:在流量和进出口气流角的约束条件下,相比于初始设计的一级半透平级,优化设计得到的等熵效率提高了1.67%。优化设计得到的动静叶之间的出口气流角匹配合理,减少了攻角损失;各列叶栅扩压区和扩压梯度均有减少,降低了二次流损失,提高了等熵效率。

Optimization design of the blade profile using aerodynamic performance analysis and genetic algorithms and artificial neural methods in one and half turbine stage was presented in this paper. The maximum isentropic efficiency of one and half turbine stage was selected as the optimization objective at the constraints of the mass flow rate and inlet/outlet flow angle flow conditions. The isentropic efficieny of the optimal design increases 1.67% compared with the initial design. The stator blade is well matched with the downstream rotor blade. This design leads to decreased incidence losses. In addition, The diffusion area and diffusion gradient in the blade flow passage are reduced and corresponding secondary flow losses is decreased and the isentropic efficiency is improved.