Title :
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
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;
Conference_Titel :
Recent Advances in Space Technologies (RAST), 2015 7th International Conference on
Conference_Location :
Istanbul
Print_ISBN :
978-1-4673-7760-7
DOI :
10.1109/RAST.2015.7208309