DocumentCode
1686604
Title
Reducing the cost of computational fluid dynamics optimization using multi layer perceptrons
Author
Schmitz, Adeline ; Besnard, Eric ; Vives, Eric
Author_Institution
Mech. & Aerosp. Eng. Dept., California State Univ., Long Beach, CA, USA
Volume
2
fYear
2002
fDate
6/24/1905 12:00:00 AM
Firstpage
1877
Lastpage
1882
Abstract
The paper presents a method for reducing the cost of computational fluid dynamics optimization by using a neural network to fill-in the design space. The method trains a network to approximate the aero- or hydrodynamic performance of vehicles with the cascade correlation algorithm. This network is coupled with a genetic algorithm to optimize the hydrodynamic performance of the configuration
Keywords
computational fluid dynamics; genetic algorithms; multilayer perceptrons; cascade correlation algorithm; computational fluid dynamics optimization; genetic algorithm; hydrodynamic performance; multilayer perceptrons; Aerospace engineering; Computational efficiency; Computational fluid dynamics; Cost function; Design optimization; Hydrodynamics; Neural networks; Optimization methods; Space technology; Vehicles;
fLanguage
English
Publisher
ieee
Conference_Titel
Neural Networks, 2002. IJCNN '02. Proceedings of the 2002 International Joint Conference on
Conference_Location
Honolulu, HI
ISSN
1098-7576
Print_ISBN
0-7803-7278-6
Type
conf
DOI
10.1109/IJCNN.2002.1007805
Filename
1007805
Link To Document