Multi-Objective Design Optimization for a Steam Turbine Stator Blade Using LES and GA

Abstract

Multi-objective design optimization for a steam turbine stator blade was implemented using three-dimensional large eddy simulation (LES) and a genetic algorithm (GA). The GA used here was assisted by the Kriging response surface model for global and efficient optimization. The aim of the optimization described here was to reduce overall pressure loss and local pressure loss due to end walls simultaneously. The optimization results revealed the blade design candidates that overcame the baseline design in terms of overall loss and local loss, and the trade-off relation between them. In addition, these results provided a specific design concept and corresponding flow mechanism to realize a highly efficient stator blade.