基元叶栅攻角特性多目标优化

采用多段Bezier曲线对轴流压气机叶型予以参数化表达，通过Isight优化平台，结合S1流面数值模拟分析，以改良的非支配排序遗传算法(NSGA Ⅱ)对美国NASA单级轴流跨声压气机Stage 35的动叶和静叶叶中截面基元叶栅进行攻角特性的多目标优化，优化目标是降低全攻角范围内的总压损失系数以及拓宽攻角适应性范围。以总压损失系数最小点以及总压损失系数相对最高点和最低点的差值作为优化目标函数，叶栅流量不变为约束条件。结果表明:优化显著降低了动、静叶叶中截面基元叶栅的总压损失系数，并使其攻角适应性范围分别拓宽了5°和3°。 

Multi objective optimization of incidence features for cascade

Multi Bezier curve was adopted to describe the cascade of the axial flow compressor in parameterized form. By taking the Isight software as optimization platform, the calculation program of the S1 surface was adopted to calculate the flow field, and the improved non dominated sorting genetic algorithm (NSGA Ⅱ) was employed to conduct the multi objective optimization of the features of incidence for the cascade of the middle section of rotor and stator of Stage35, which was one stage axial flow transonic compressor from NASA. The optimization goal was to reduce the total pressure loss coefficient in the whole range of the incidence and widen the adaptive range of the incidence. The lowest total pressure loss coefficient and the difference between the relatively highest and the lowest point of total pressure loss coefficient were set as the optimization objective functions. The flow rate of the cascade constant was set as constraint. Results indicated that the optimization greatly reduced the total pressure loss coefficient of the cascade of the middle section of rotor and stator, and widened the range of the incidence of the middle section of rotor and stator by 5° and 3° respectively.