利用周向涡量对压气机进行气动数值优化

Aerodynamic optimization of a low speed compressor based on circumferential vorticity

采用人工神经网络结合遗传算法,利用周向涡量,对一单级低速压气机转子空间弯掠积叠曲线进行了气动数值优化.优化目标为小流量工况下绝热效率最大.结果表明,优化后转子出口的周向涡量分布改善,压气机级在小流量区域的效率得到很大提高,稳定工作裕度得以拓宽.该方法不仅在数学和物理上使得优化进程高效的收敛于最优解,而且能给后续的压气机级提供一个组织有序的流场.

Based on artificial neural network and genetic algorithms, the aerodynamic optimization of stacking curve for a low-speed compressor rotor was implemented by controlling circumferential vorticity. The adiabatic efficiency under small flow rate condition was optimized. The numerical results show that the distribution of circumferential vorticity at the exit of rotor is improved, the adiabatic efficiency under small flow rate zone is enhanced, and the stall margin is greatly increased. The optimization approach have high efficiency, and can provide a ordered flow field for compressor.