Reynolds averaged turbulence modelling using deep neural networks with embedded invariance

There exists significant demand for improved Reynolds-averaged Navier–Stokes (RANS) turbulence models that are informed by and can represent a richer set of turbulence physics. This paper presents a method of using deep neural networks to learn a model for the Reynolds stress anisotropy tensor from...

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Bibliographic Details
Published in:	Journal of fluid mechanics Vol. 807; pp. 155 - 166
Main Authors:	Ling, Julia, Kurzawski, Andrew, Templeton, Jeremy
Format:	Journal Article
Language:	English
Published:	Cambridge, UK Cambridge University Press 25.11.2016
Subjects:	Anisotropy CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSICS Fluid mechanics Navier-Stokes equations Reynolds number Turbulence Viscosity turbulent flows turbulence modelling turbulence theory
ISSN:	0022-1120, 1469-7645
Online Access:	Get full text
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