Study on the prediction of aerodynamic loss coefficient of the airfoil by GA-BP neural network

Zhiwen Liu; Liangliang Liu; Ruixue Yu; Tao Bian

doi:10.1117/12.2671166

28 April 2023 Study on the prediction of aerodynamic loss coefficient of the airfoil by GA-BP neural network

Zhiwen Liu, Liangliang Liu, Ruixue Yu, Tao Bian

Proceedings Volume 12610, Third International Conference on Artificial Intelligence and Computer Engineering (ICAICE 2022); 126105X (2023) https://doi.org/10.1117/12.2671166
Event: Third International Conference on Artificial Intelligence and Computer Engineering (ICAICE 2022), 2022, Wuhan, China

Abstract

In this paper, the aerodynamic loss coefficient of the airfoil is obtained through GA-BP Neural Network. The maximum thickness, the position of the maximum thickness, the blade camber angle and the incident angle are set as input parameters, and the loss coefficient is output parameter. The neural network optimized by genetic algorithm is used for training and testing. The GA genetic algorithm is used to optimize the operating conditions, and the data is imported into the prediction model established by the BP neural network for training, and an effective loss coefficient prediction scheme is obtained. The research results show that the GA-BP neural network has high prediction accuracy, and the mean square error of prediction is 6.4228e -05, which can effectively solve the loss coefficient prediction problem of airfoil.

Citation Download Citation

Zhiwen Liu, Liangliang Liu, Ruixue Yu, and Tao Bian "Study on the prediction of aerodynamic loss coefficient of the airfoil by GA-BP neural network", Proc. SPIE 12610, Third International Conference on Artificial Intelligence and Computer Engineering (ICAICE 2022), 126105X (28 April 2023); https://doi.org/10.1117/12.2671166

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