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Cascade airfoil design by multiobjective genetic algorithms

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3 Author(s)
Obayashi, S. ; Dept. of Aeronaut. & Space Eng., Tohoku Univ., Sendai, Japan ; Tsukahara, T. ; Nakamura, T.

Multiobjective genetic algorithm based on Fonseca-Fleming's Pareto-based ranking and fitness sharing techniques has been applied to aerodynamic shape optimization of cascade airfoil design. Airfoil performance is evaluated by a Navier-Stokes code. Evaluation of GA population is parallelized on numerical wind tunnel - a parallel vector machine. The present multiobjective design seeks high pressure rise, high flow turning angle, and low total pressure loss at a low Mach number. Pareto solutions that perform better than existing control diffusion airfoil were obtained

Published in:

Genetic Algorithms in Engineering Systems: Innovations and Applications, 1997. GALESIA 97. Second International Conference On (Conf. Publ. No. 446)

Date of Conference:

2-4 Sep 1997

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