Multi-objective aerodynamic optimization design process of multistage axial turbine

Based on the result of quasi-3D design, applying multi-objective aerodynamic optimization design method, an aerodynamic optimization design process of multistage axial turbine is presented. Genetic algorithm and artificial neural network are jointly adopted during optimization. Three-dimensional viscosity Navier-Stokes equation solver was applied. The optimization process has three features: Local optimization based on aerodynamic performance of every cascade; several optimizations being performed to every cascade; and alternative use of coarse grid and fine grid. Such process is applied to optimize a three-stage axial turbine. The results show that the total efficiency increases 1%. This indicates that such method may be efficiently applied to the aerodynamic design optimization of multistage axial turbine.