高压涡轮导叶非轴对称端壁优化设计

为使高压涡轮导叶非轴对称端壁造型在减少二次流损失、提高气动性能方面更好的发挥作用，以某一级高压涡轮为研究对象，采用端壁参数化造型、三维Navier-Stokes（N-S）方程流场求解和基于人工神经网络的遗传算法相结合的优化方法对涡轮导叶进行非轴对称端壁的优化设计。优化目标为在控制涡轮导叶进口质量流量、出口马赫数及出口气流角的情况下，导叶出口总压损失系数和出口二次流动能最小化。对比分析优化前后端壁对涡轮导叶出口参数和涡轮级性能的影响。结果表明：优化后得到的非轴对称端壁有效地改善了涡轮导叶通道内的流场，抑制了通道内二次流涡系的发展，降低了导叶出口处的流动损失，涡轮导叶出口总压损失系数降低了14．85％，高压涡轮级等熵效率提高了0．456％。

Optimization Design of Non-axisymmetric End Wall in a High Pressure Turbine Stator Row

With the optimization design, the non-axisymmetric end wall in a high pressure(HP) turbine stator row was optimized based on the methods which combined end wall parameterization, three-dimensional Navier-Stokes(N-S) flow computation, and genetic algorithm(GA) ground on artificial neural network(ANN). The objective of optimization design is to minimize the total pressure loss coefficient and secondary kinetic energy(SKE) at the stator exit while the inlet mass flow, the exit Mach number and the exit flow angle are controlled. This paper compared and analyzed the influences on the parameters at the stator exit and the stage performance of the HP turbine between the axisymmetric end wall before optimization and the non-axisymmetric end wall after optimization. The analysis results indicate that the optimized non-axisymmetric end wall can effectively improve the flow field through suppressing the development of secondary flow vortex system in the HP turbine stator so as to reduce the flow loss at the stator exit. And the total pressure loss coefficient at the stator exit reduces by 14.85%, while the stage isentropic efficiency increases by 0.456%.