Multi-objective automatic optimization design of centrifugal impeller based on genetic algorithm

A parameterization method is developed to perform the multi-objective optimization design of centrifugal impellers. The relationship of the impeller parameters and the dimensionless length in the cylindrical coordinate system is established by the transformation of impeller profile data. Non-uniform rational B-spline is used to reconstruct the impeller to obtain the profile of the blade and the meridional surface. An automatic optimization design platform for the centrifugal impellers is constructed by the multi-objective genetic algorithm combined with parameterization method and the commercial computational fluid dynamics software NUMECA. The Krain high-speed centrifugal impeller is optimized by using the present method at the design condition, and the aerodynamic performance and the flow characteristics are analyzed. The numerical results show that the aerodynamic performance of the optimal impellers is improved to some extent. The flow field distribution at the outlet of the optimal impellers is more uniform. The total pressure ratio and the isentropic efficiency increases by about 2.5% and 1.0% respectively. These findings confirm that the present multi-objective optimization design method for the centrifugal impellers is effective.