Deep learning in fluid dynamics

It was only a matter of time before deep neural networks (DNNs) – deep learning – made their mark in turbulence modelling, or more broadly, in the general area of high-dimensional, complex dynamical systems. In the last decade, DNNs have become a dominant data mining tool for big data applications....

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Bibliographic Details
Published in:	Journal of fluid mechanics Vol. 814; pp. 1 - 4
Main Author:	Kutz, J. Nathan
Format:	Journal Article
Language:	English
Published:	Cambridge, UK Cambridge University Press 10.03.2017
Subjects:	Algorithms Anisotropy Applied mathematics Artificial intelligence Artificial neural networks Computational fluid dynamics Data management Data mining Data processing Datasets Decomposition Deep learning Dynamical systems Dynamics Fluid dynamics Fluid flow Focus on Fluids Hydrodynamics Modelling Navier-Stokes equations Neural networks Physics Reynolds averaged Navier-Stokes method Studies Success Turbulence Turbulence models computational methods turbulence modelling low-dimensional models
ISSN:	0022-1120, 1469-7645
Online Access:	Get full text
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