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Deep learning in fluid dynamics
2017
Journal of Fluid Mechanics
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. Although neural networks have been applied previously to complex fluid flows, the article featured here (Ling et al., J. Fluid Mech., vol. 807, 2016, pp. 155–166) is the first to apply a true DNN
doi:10.1017/jfm.2016.803
fatcat:w6vqfv7j2jhjpalnp5nhjqrw6a