Abstract
A new approach for multi-objective design optimization which combines CFD analysis and optimization techniques has been proposed and applied to the airfoil design for a steam turbine stator blade. In the present approach, genetic algorithm is used to search compromised solutions in the multi-objective problem. In addition, response surface approximation using the Kriging model is used together in order to reduce the computational time for objective function evaluation. As a result, the computational time required for the entire optimization process was kept within a realistic range. Moreover, the trade-off relations between multiple objective functions have been discovered, even though the accuracy of the response surface approximation was not yet in a satisfactory level. Finally, many design candidates that outperform the original baseline design have also been discovered.
