Multiobjective genetic algorithm applied to aerodynamic design of cascade airfoils

Author

Obayashi, Shigeru ; Tsukahara, Takanori ; Nakamura, Takashi

Author_Institution

Dept. of Aeronomy & Space Eng., Tohoku Univ., Sendai, Japan

Volume

47

Issue

1

fYear

2000

fDate

2/1/2000 12:00:00 AM

Firstpage

211

Lastpage

216

Abstract

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

Keywords

Navier-Stokes equations; Pareto distribution; aerodynamics; compressors; gas turbines; genetic algorithms; parallel machines; power engineering computing; Fonseca-Fleming´s Pareto-based ranking; Navier-Stokes code; Numerical Wind Tunnel; aerodynamic shape design; cascade airfoils design; compressors; control diffusion airfoils; design automation; fitness-sharing techniques; gas turbines; high flow turning angle; high pressure rise; low Mach number; low total pressure loss; multiobjective design; multiobjective genetic algorithm; parallel vector machine; Aerodynamics; Algorithm design and analysis; Automotive components; Compressors; Design methodology; Genetic algorithms; Geometry; Optimization methods; Shape; Turbomachinery;

fLanguage

English

Journal_Title

Industrial Electronics, IEEE Transactions on

Publisher

ieee

ISSN

0278-0046

Type

jour

DOI

10.1109/41.824144

Filename

824144