A Rapid and Automatic Optimal Design Method for Six-Stage Axial-Flow Industry Compressor

Existing aerodynamic design systems for multi-stage axial-flow compressor suffer from several limitations, such as experience dependent models and time costly simulations. Few attempts, however, have been devoted to the rapid and automatic optimization of aerodynamic performance at the preliminary design phase, which plays a crucial role in the final aerodynamic performance. In this work, a rapid and automatic aerodynamic optimal design method is developed for the multi-stage axial-flow compressor based on one-dimensional meanline design method, radial-equilibrium equation and genetic algorithm. The one-dimensional performance prediction model includes some popular empirical correlations to calculate the flow loss, incidence angle, deviation angle and flow blockage. The radial-equilibrium equation is solved to obtain the spanwise distribution of aerodynamic and thermodynamic parameters at the inlet and outlet of each blade row. The genetic algorithm is used for an automatic search of the global optimal compressor configuration aiming at maximizing the design efficiency. The developed method is illustrated with the aerodynamic optimal design of a 6-stage axial-flow industry compressor and verified by computational fluid dynamics simulations. The results show that the developed method is capable of improving effectively the design efficiency and predicting accurately the aerodynamic performance of the 6-stage axial-flow industry compressor in a few minutes. This work is of scientific significance to improve the axial-flow compressor design system and of engineering importance to release the designers from the heavy experience dependence especially at the preliminary design phase.