Research on grid‐dependence of neural network turbulence model-Reference-Cited by-同舟云学术

Research on grid‐dependence of neural network turbulence model

Published:2022-06-30 Issue:11 Volume:94 Page:1909-1922
ISSN:0271-2091
Container-title:International Journal for Numerical Methods in Fluids
language:en
Short-container-title:Numerical Methods in Fluids

Author:

Song Shangxiao¹²³^ORCID,Zhang Weiwei¹²³,Sun Xuxiang¹²³,Zhu Linyang⁴,Liu Yilang¹²³

Affiliation:

1. School of Aeronautics Northwestern Polytechnical University Xi'an Shaanxi China

2. International Joint Institute of Artificial Intelligence on Fluid Mechanics Northwestern Polytechnical University Xi'an Shaanxi China

3. National Key Laboratory of Science and Technology on Aerodynamic Design and Research|School of Aeronautics Northwestern Polytechnical University Xi'an Shaanxi China

4. State Key Laboratory of Aerodynamics China Aerodynamics Research and Development Center Mianyang Sichuan China

Funder

National Natural Science Foundation of China

Fundamental Research Funds for the Central Universities

Publisher

Wiley

Subject

Applied Mathematics,Computer Science Applications,Mechanical Engineering,Mechanics of Materials,Computational Mechanics

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1002/fld.5125

Reference41 articles.

1. SpalartP AllmarasS.A one‐equation turbulence model for aerodynamic flows. Proceedings of the 30th Aerospace Sciences Meeting and Exhibit. Aerospace Sciences Meetings. American Institute of Aeronautics and Astronautics; 1992. doi:10.2514/6.1992‐439

2. Radial basis function neural network model for mean velocity and vorticity of capillary flow

3. Reduced order framework for convection dominant and pure diffusive problems based on combination of deep long short‐term memory and proper orthogonal decomposition/dynamic mode decomposition methods

4. Modeling transient fluid simulations with proper orthogonal decomposition and machine learning

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