Multiobjective genetic algorithm applied to aerodynamic design of cascade airfoils

被引：29
|
作者：
Obayashi, S [1 ]
Tsukahara, T
Nakamura, T
机构：
[1] Tohoku Univ, Dept Aeronaut & Space Engn, Sendai, Miyagi 9808579, Japan
[2] Fuji Heavy Ind Co Ltd, Aerosp Div, Utsunomiya Plant, Utsunomiya, Tochigi 3208564, Japan
[3] Natl Aerosp Lab, Chofu, Tokyo 1828522, Japan
来源：
IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS | 2000年 / 47卷 / 01期
关键词：
aerodynamics; compressors; design automation; gas turbines; genetic algorithms; optimization methods; Pareto distributions;
D O I：
10.1109/41.824144
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
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.
引用
收藏
页码：211 / 216
页数：6
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