Design Optimization of a Multistage Axial Flow Compressor Based on Full-Blade Surface Parameterization and Phased Strategy

Abstract

A new design optimization method is proposed for the problem of high-precision aerodynamic design of multistage axial compressors. The method mainly contains three aspects: full-blade surface parametrization can significantly reduce the number of control variables per blade row and increase the degrees of freedom of the leading edge blade angle compared with the traditional semiblade parametric method; secondly, the artificial bee colony algorithm improved initialization and food source exploration and exploitation mechanism to enhance the global optimization ability and convergence speed, and a distributed optimization system is built on the supercomputing platform based on this method; finally, a phased optimization strategy based on the “synchronous change in multirow blades” is proposed, and expert experience is introduced to achieve a better balance between exploration and exploitation. The optimization method is applied to the AL-31F four-stage low-pressure compressor. As a result, the adiabatic efficiency is improved by 0.67% and the surge margin is improved by 3.1% under the premise that the total pressure ratio and mass flow rate satisfy the constraints, which verifies the effectiveness and engineering practicality of the proposed optimization method in the field of multistage axial flow compressor aerodynamic optimization.