Improvement of forward swept wing optimization in the compressible flow by using a hybrid method

Author

Vatandas, O. Erguven ; Altuntas, Yilmaz ; Celebi, Mansur

Author_Institution

Dept. of Aerosp. Eng., Turkish Air Force Acad., Istanbul, Turkey

fYear

2015

Firstpage

21

Lastpage

25

Abstract

The purpose of this study is to develop an effective hybrid aerodynamic optimization technique in the compressible flow for a forward swept wing (FSW) by using artificial neural network (ANN). ANN is hybridized with a genetic optimization method. This new optimization technique is observed much faster than Genetic Algorithm (GA). By using the method presented in this study, the drag coefficient can be reduced 30 percent faster than the conventional GA.

Keywords

aerodynamics; aerospace components; compressible flow; drag reduction; genetic algorithms; mechanical engineering computing; neural nets; ANN; artificial neural network; compressible flow; drag reduction; forward swept wing optimization; genetic optimization; hybrid aerodynamic optimization technique; Artificial neural networks; Drag; Genetic algorithms; Mathematical model; Optimization; Sociology; Statistics; Aerodynamic wing optimization; Artificial Neural Network; Forward swept wing;

fLanguage

English

Publisher

ieee

Conference_Titel

Recent Advances in Space Technologies (RAST), 2015 7th International Conference on

Conference_Location

Istanbul

Print_ISBN

978-1-4673-7760-7

Type

conf

DOI

10.1109/RAST.2015.7208309

Filename

7208309