Modeling of longitudinal unsteady aerodynamics at high angle-of-attack based on support vector machines

Author(s):  
Yongliang Chen
2013 ◽  
Vol 392 ◽  
pp. 170-177 ◽  
Author(s):  
Hong Biao Wang ◽  
Bin Bin Lv ◽  
Xiao Juan Yang ◽  
Tai Yuan Luo

with the BP algorithm, this paper sets up the High angle of attack unsteady aerodynamic neural network model. By using the large-amplitude pitch oscillation dynamic test data of some slender model in high-speed wind tunnel, this paper trains and verifies the BP neural network model and discusses elements which may influence the arithmetic speed and prediction accuracy of the neural network model. Test results show that the established BP neural network model matches the wind tunnel test results nicely and has relatively good capacity to predict the High angle of attack unsteady aerodynamics.


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