Neural network models for the anisotropic Reynolds stress tensor in turbulent channel flow-Reference-Cited by-同舟云学术

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Neural network models for the anisotropic Reynolds stress tensor in turbulent channel flow

Published:2019-12-24 Issue:9-10 Volume:21 Page:525-543
ISSN:1468-5248
Container-title:Journal of Turbulence
language:en
Short-container-title:Journal of Turbulence

Author:

Fang Rui¹²^ORCID,Sondak David¹,Protopapas Pavlos¹,Succi Sauro¹³⁴

Affiliation:

1. Institute for Applied Computational Science, Harvard University, Cambridge, MA, USA

2. The University of Texas at Austin, Austin, TX, USA

3. Center for Life Nanoscience at la Sapienza, Istituto Italiano di Tecnologia, Rome, Italy

4. Istituto Applicazioni del Calcolo, National Research Council of Itaty, Rome, Italy

Funder

H2020 European Research Council

Publisher

Informa UK Limited

Subject

General Physics and Astronomy,Mechanics of Materials,Condensed Matter Physics,Computational Mechanics

Link

https://www.tandfonline.com/doi/pdf/10.1080/14685248.2019.1706742

Reference39 articles.

1. Hybrid LES/RANS methods for the simulation of turbulent flows

2. Turbulence Modeling in the Age of Data

3. Extended Boltzmann Kinetic Equation for Turbulent Flows

4. Constitutive equations for turbulent flows

5. Johansson A. Engineering turbulence models and their development, with emphasis on explicit algebraic Reynolds stress models. In: Oberlack M, Busse FH, editors. Theories of turbulence. Vienna: Springer; 2002. p. 253–300.

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