124 多目的遺伝的アルゴリズムと実験計画法による水車形状の最適化

抄録

An optimization system coupling CFD and design tool of Francis turbine runner shape with Multi-Objective Genetic Algorithm (MOGA) and Design of Experiences (DOE) is presented. The system is consists two processes. One is based on MOGA, and the other is based on DOE. At the first process, runner design parameters are automatically optimized according to objective function. At the second process, optimized runner which optimized first process is selected as base runner, and the runner design parameters are optimized by DOE. The system was applied to low specific speed Francis turbine runner. Hydraulic loss of runner and draft tube were selected for objective function. As the result of the optimization, high performance runner which has high turbine efficiency and low pressure fluctuation was obtained.