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Multiobjective genetic algorithm applied to aerodynamic design of cascade airfoils

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

A multiobjective genetic algorithm (GA) 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 the 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 airfoils were obtained

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Industrial Electronics, IEEE Transactions on  (Volume:47 ,  Issue: 1 )