A three-stage axial turbine was redesigned by jointly applying S2 flow surface direct problem calculation methods and multistage local optimization methods. A genetic algorithm and artificial neural network were jointly adopted during optimization. A three-dimensional viscosity Navier–Stokes equation solver was applied for flow computation. H-O-H-topology grid was adopted as computation grid, that is, an H-topology grid was adopted for inlet and outlet segment, whereas an O-topology grid was adopted for stator zone and rotor zone. Through the optimization design, the total efficiency increases 1.1%, thus indicating that the total performance is improved and the design objective is achieved.
ZHAO Honglei, WANG Songtao, HAN Wanjin, FENG Guotai
. Aerodynamic design by jointly applying S2 flow
surface calculation and modern optimization methods on multistage
axial turbine[J]. Frontiers in Energy, 2008
, 2(1)
: 93
-98
.
DOI: 10.1007/s11708-008-0007-4
1. Shahpar S A comparativestudy of optimization on methods for aerodynamic design of turbomachinerybladesProceedings of ASME Turbo Expo 2000,2000-GT-523 2000
2. Vanderplaats G N NumericalOptimization Techniques for Engineering DesignNew YorkMcGraw-Hill 1984
3. Goldberg D E GeneticAlgorithms in Search, Optimization, and Machine LearningBostonAddisonWesley Professional 1989
4. Demeulenaere A Ligout A Hirsch C Application of multipoint optimization to the design ofturbomachinery bladesProceedings of ASMETurbo Expo 2004, GT2004-53110 2004
