压气机叶片多目标优化设计及稳定裕度分析

将数值最优化方法与压气机叶片流场计算相结合,以总压损失、压比、流量作为目标,应用人工神经网络来近似拟合其与设计变量的函数关系,基于罚函数利用遗传算法对其进行优化直至收敛。从压气机堵塞点开始,逐步提高背压,进行稳定性分析,得出优化前后叶片的稳定裕度。与原风扇转子相比,在设计工作点总压损失系数降低,压比和流量均增大,并且在整个工作流量范围内除在喘振点附近外总压比和效率都有一定的提高,经过验证优化后转子的峰值效率和稳定裕度都得到了显著提高。

Multi-objective Optimization Design of Axial Compressor Blade and Stability Margin Analysis

In this paper, an automatic aerodynamic optimization system for axial compressor was construc- ted which was composed of flow field simulations, Direct toward the target of total pressure loss, pressure ratio, mass flow, neural networks are used to approximately fit the relation between them and the design variables. Based on penalty function We use genetic algorithms to repeated optimizing until convergence. Starting from the plugging point of the compressor, gradually increase the back pressure, carrying on the stability analysis and get the stability margin before and after optimization of the blade. Compared with the original rotor in the design point, it has lower total pressure loss coefficient, and pressure ratio and flow were increased. On the entire operating flow range the total pressure ratio and efficiency has improved out- side the vicinity of the surge point, after verification, the stability margin and the peak efficiency of the op- timized rotor have been significantly imoroved.