Multiobjective optimization design of ultrahigh-head pump turbine runners with splitter blades

Abstract

The traditional design method, design-experiment-design, is time consuming and difficult. In the present paper, an efficiency design system for pump-turbine runners, the multiobjective optimization design system, which includes 3D inverse design, Computational Fluid Dynamics (CFD), Design Of Experiment (DOE), Radial Basis Function (RBF) and Multi Objective Genetic Algorithm (MOGA), is presented and then applied to design a scaled ultrahigh-head pump turbine runner. First, the control parameters, blade loading and the splitter work ratio, and the runner efficiencies under pump and turbine mode were selected as input variables and optimization objectives respectively. Then the DOE was applied to select the sample runners, and the CFD was used to predict the efficiencies of the sample runners under different modes. The relationship between input variables and objectives was built by RBF based on CFD results. Finally, the MOGA was applied to generate and search the good overall performance runners according to the relationship built by RBF. The results indicate that: the pump mode efficiency of preferred runner is increases by 0.34% and the turbine mode efficiency by 2.07% compared to the initial runner. With the improvement of efficiency, the pressure and streamline distribution are improved obviously.