| Citation: | LYU Z Y，NIE X Y，ZHAO A B. Prediction of wing aerodynamic coefficient based on CNN[J]. Journal of Beijing University of Aeronautics and Astronautics，2023，49（3）：674-680 （in Chinese） doi: 10.13700/j.bh.1001-5965.2021.0276
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With the rapid development of machine learning and its outstanding nonlinear mapping ability, more and more scholars apply machine learning methods to the field of fluid mechanics. To overcome the obstacle that the traditional mathematical fitting cannot well present the system nonlinearity and the inconvenience of some neural network-based aerodynamic parameter prediction methods due to the need of parametric processing, and to achieve the multi-variable and multi-output aerodynamic parameters, this paper establishes a multi-variable and multi-output model based on convolutional neural network considering the variable angle of attack and the heave of the wing to realize the rapid prediction of the aerodynamic coefficient of the wing. The results show that this model has high prediction accuracy and its computational efficiency is 40 times higher than computational fluid dynamics (CFD). Moreover, the designed stability experiment results show that the proposed model has good stability.
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