Optimization method for the design of axial hydraulic turbines

Abstract

Computational fluid dynamics (CFD) is becoming an increasingly reliable tool for the design of water turbines. Using different CFD codes, it is possible to find out and compare criteria for classifying runner blade geometry regarding the strengths of their characteristics. The final decision of runner geometry, with demanding energetic and cavitation characteristics, always remains for the design engineer. To reach the final result, the engineer has to compare the flow analysis results of a great number of different geometries. To replace a part of this work, an optimization algorithm has been developed. This optimization procedure helps to check many more geometries with less human work. In this paper, a multiobjective genetic algorithm for the design of axial runners is presented. For the flow analysis, the CFX-TASC flow code, with a standard k-ɛ turbulence model, has been used, because the code enables calculation within a rotating frame of reference. For design of the initial geometry, within the optimization procedure, a special program has been developed, which makes it possible to start the optimization procedure with a relatively high level of efficiency and transforms prescribed genetic parameters to the runner geometry.