Aerodynamic prediction of airfoil based on convolution neural network

Chunlong Fan; Wang Shengshun

doi:10.1117/12.2638654

23 May 2022 Aerodynamic prediction of airfoil based on convolution neural network

Chunlong Fan, Wang Shengshun

Proceedings Volume 12254, International Conference on Electronic Information Technology (EIT 2022); 1225426 (2022) https://doi.org/10.1117/12.2638654
Event: International Conference on Electronic Information Technology (EIT 2022), 2022, Chengdu, China

Abstract

In this paper, an airfoil aerodynamic prediction model based on neural network is proposed. In the traditional prediction method based on surrogate model, there are some shortcomings, such as over dependence on airfoil parameters, limited dimension of design variables, and complexity of strong nonlinear engineering design. As an alternative method, convolutional neural network (CNN) has been proved to have good ability of complex image classification, and is widely used in aerodynamic element modeling task. So in this paper, based on enough data sets, a convolutional neural network framework is constructed to replace the traditional CFD solver to predict large-scale nonlinear aerodynamic parameters. Using CNN, the aerodynamic parameters of airfoil at different angles of attack can be predicted（α)，The results of CFD solver are compared. The results show that the proposed method can maintain a high level of accuracy, and its efficiency is far better than CFD method.

Citation Download Citation

Chunlong Fan and Wang Shengshun "Aerodynamic prediction of airfoil based on convolution neural network", Proc. SPIE 12254, International Conference on Electronic Information Technology (EIT 2022), 1225426 (23 May 2022); https://doi.org/10.1117/12.2638654

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