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

页码：211 / 216

页数：6

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