J Shanghai Jiaotong Univ Sci

Journal of Shanghai Jiao Tong University (Science) ›› 2020, Vol. 25 ›› Issue (2): 186-192.doi: 10.1007/s12204-019-2140-0

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

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

ZHAO Yong (赵勇), MENG Yang (孟杨), YU Pengyao (于鹏垚), WANG Tianlin (王天霖), SU Shaojuan (苏绍娟)   

  1. (College of Naval and Ocean Engineering, Dalian Maritime University, Dalian 116000, Liaoning, China)
  2. (College of Naval and Ocean Engineering, Dalian Maritime University, Dalian 116000, Liaoning, China)
  • Online:2020-04-01 Published:2020-04-01
  • Contact: MENG Yang (孟杨) E-mail:my19951203@live.com

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Abstract: 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.

Key words: convolutional neural network (CNN) model| back propagation (BP) model| computational fluid dynamics (CFD)| bluff body flow| fluid force

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.

关键词: convolutional neural network (CNN) model| back propagation (BP) model| computational fluid dynamics (CFD)| bluff body flow| fluid force

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