Prediction model of velocity field around circular cylinder over various Reynolds numbers by fusion convolutional neural networks based on pressure on the cylinder-Reference-Cited by-同舟云学术

Prediction model of velocity field around circular cylinder over various Reynolds numbers by fusion convolutional neural networks based on pressure on the cylinder

Published:2018-04 Issue:4 Volume:30 Page:047105
ISSN:1070-6631
Container-title:Physics of Fluids
language:en
Short-container-title:Physics of Fluids

Author:

Jin Xiaowei¹²³,Cheng Peng⁴,Chen Wen-Li¹²³,Li Hui¹²³^ORCID

Affiliation:

1. Key Lab of Smart Prevention and Mitigation of Civil Engineering Disasters of Ministry of Industry and Information Technology, Harbin Institute of Technology, Harbin 150090, China

2. Key Lab of Structures Dynamic Behavior and Control of Ministry of Education, Harbin Institute of Technology, Harbin 150090, China

3. School of Civil Engineering, Harbin Institute of Technology, Harbin 150090, China

4. Institute for Turbulence-Noise-Vibration Interactions and Control, Shenzhen Division, Harbin Institute of Technology, Shenzhen 518055, China

Funder

National Natural Science Foundation of China

Publisher

AIP Publishing

Subject

Condensed Matter Physics,Fluid Flow and Transfer Processes,Mechanics of Materials,Computational Mechanics,Mechanical Engineering

Link

http://aip.scitation.org/doi/pdf/10.1063/1.5024595

Reference30 articles.

1. Twenty years of particle image velocimetry

2. Deep learning

3. Deep learning in fluid dynamics

4. Evaluation of machine learning algorithms for prediction of regions of high Reynolds averaged Navier Stokes uncertainty

5. Bayesian estimates of parameter variability in the k–ε turbulence model

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