Transonic Axial-flow Blade Shape Optimization Using Evolutionary Algorithm and Three-dimensional Navier-stokes Solver

* NRC Research Associate, Turbomachinery and Propulsion System Division, Member AIAA. Located at Ohio Aerospace Institute ICOMP, 22800 Cedar Point Rd., Cleveland, OH 44142, USA = Senior Scientist, Turbomachinery and Propulsion System Division, Associate Fellow AIAA # Associate Professor, Institute of Fluid Science, Associate Fellow AIAA Copyright © 2002 by the American Institute of Aeronautics and Astronautics, Inc. No copyright is asserted in the United States under Title 17, U.S. Code. The U.S. Government has a royalty-free license to exercise all rights under the copyright claimed herein for governmental purposes. All other rights are reserved by the copyright owner. ABSTRACT A reliable and efficient aerodynamic design optimization tool using evolutionary algorithm has been developed for transonic compressor blades. A real-coded adaptive-range genetic algorithm is used to improve efficiency and robustness in design optimization. To represent flow fields accurately and produce reliable designs, three-dimensional NavierStokes computation is used for aerodynamic analysis. To ensure feasibility of the present method, aerodynamic redesign of NASA rotor67 is demonstrated. Entropy production is considered as the objective function to be minimized. The computation is parallelized on the SGI ORIGIN2000 cluster at Institute of Fluid Science, Tohoku University, by distributing flow analyses of design candidates to 64 processing elements. The present method successfully obtained a design that reduced entropy production by more than 19% compared with the rotor67 while satisfying constraints on the mass flow rate and the pressure ratio. The use of the present tool for turbomachinery blade design is demonstrated to allow designers to achieve higher aerodynamic efficiency, while shortening design cycle and reducing design costs significantly.