Application of Artificial Neural Networks in Nonlinear Aerodynamics and Aircraft Design 932533
The architecture and training of artificial neural networks are briefly described. Five applications of these networks to design and analysis problems are presented; three in aerodynamics and two in flight dynamics. The aerodynamics cases are those of a harmonically oscillating airfoil, a pitching delta wing, and airfoil design. The flight dynamic examples involve control of a super maneuver and a decoupled control case. It is demonstrated that highly nonlinear aerodynamic cases can be generalized with sufficient accuracy for design purposes. It is shown that although neural networks generalize well on the aerodynamic problems, they appear lacking comparable robustness in modeling dynamic systems. It is also shown that generalization appears to become weak outside of the training domain.
Citation: Rokhsaz, K. and Steck, J., "Application of Artificial Neural Networks in Nonlinear Aerodynamics and Aircraft Design," SAE Technical Paper 932533, 1993, https://doi.org/10.4271/932533. Download Citation
Author(s):
Kamran Rokhsaz, James E. Steck
Affiliated:
Wichita State Univ.
Pages: 11
Event:
Aerospace Technology Conference and Exposition
ISSN:
0148-7191
e-ISSN:
2688-3627
Also in:
SAE 1993 Transactions: Journal of Aerospace-V102-1
Related Topics:
Neural networks
Vehicle dynamics /flight dynamics
Aircraft
Aerodynamics
Education and training
Wings
Simulation and modeling
Architecture
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