Published:
May 2002
Proceedings:
Proceedings of the Fifteenth International Florida Artificial Intelligence Research Society Conference (FLAIRS 2002)
Volume
Issue:
Proceedings of the Fifteenth International Florida Artificial Intelligence Research Society Conference (FLAIRS 2002)
Track:
All Papers
Downloads:
Abstract:
A reliable and fast method of predicting complex aerodynamic coefficients for flight simulation is presented using neural networks. The training data for the neural network is derived from numerical simulations and wind tunnel experiments. The aerodynamic coefficients are modeled as functions of the flow characteistics and the control surfaces of the vehicle. The basic coefficients of lift, drag and pitching moment are expressed as function of angles of attack and Mach number. The modeled and training aerodynamic coefficients show good agreement. This method shows excellent potential for rapid development of aerodynamic models for flight simulation.
FLAIRS
Proceedings of the Fifteenth International Florida Artificial Intelligence Research Society Conference (FLAIRS 2002)
ISBN 978-1-57735-141-2
Published by The AAAI Press, Menlo Park, California