Prediction of Fluid Force Exerted on Bluff Body by Neural Network Method

被引:4
|
作者
Zhao Y. [1 ]
Meng Y. [1 ]
Yu P. [1 ]
Wang T. [1 ]
Su S. [1 ]
机构
[1] College of Naval and Ocean Engineering, Dalian Maritime University, Dalian, Liaoning
关键词
A; back propagation (BP) model; bluff body flow; computational fluid dynamics (CFD); convolutional neural network (CNN) model; fluid force; O; 351.2;
D O I
10.1007/s12204-019-2140-0
中图分类号
学科分类号
摘要
With the development of artificial intelligence, artificial neural network (ANN) has been widely used in recent years. In this paper, the method is applied to the prediction of the fluid force exerted on the bluff body when flow passes around. Firstly, back propagation (BP) model and convolutional neural network (CNN) model are introduced; then the mapping relation between the shape of bluff body and the fluid force, which is calculated by computational fluid dynamics (CFD), is established by sample training. Finally, it is used to predict the fluid force of the new shape bluff body. By taking the CFD results as benchmark, CNN model is capable of predicting both the resistance and lift force, while BP model is incompetent to predict lift force. Furthermore, both CNN and BP models have a significant advantage in prediction efficiency, compared by CFD calculation method. © 2019, Shanghai Jiao Tong University and Springer-Verlag GmbH Germany, part of Springer Nature.
引用
收藏
页码:186 / 192
页数:6
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