Aerodynamic Optimization and Mechanism Investigation on Performance Improvements in a Transonic Compressor Cascade

Abstract

In this paper, a transonic compressor cascade was optimized to improve its aerodynamic performance. A new blade parameterization method with 16 control variables was first proposed to fit the shapes of the suction and the pressure side, as well as the leading edge. Then, the Kriging surrogate-model-based genetic algorithm (GA) was used to optimize the performance of the transonic cascade. The optimization algorithm is effective in reducing the total pressure loss while extending the working range of the cascade. The results show that the total pressure loss coefficient could be reduced by 11% at the best airflow angle and the working range could be extended by 6.9% for the optimized cascade in two-dimensional simulations. Similar improvement results could also be obtained in the simulations of their linear cascade cases. Detailed analyses show that the relative maximum thickness positions of the optimized blades move forward by about 10% to the leading edge, and the radii of curvature of the front half of the suction and pressure surfaces increase, compared with the initial blade. This makes the front half of the optimized blades look more closely like a wedge. Consequently, the passage shock strength is reduced and the shock changes from the passage normal shock to oblique shock. The weakened shock strength leads to the disappearance of the flow separation caused by the shock boundary layer interaction on the suction surfaces of the optimized blades, and results in a narrowed wake width at the outlet section.