Connecting implicit and explicit large eddy simulations of two-dimensional turbulence through machine learning.

@inproceedings{Maulik2019ConnectingIA,
  title={Connecting implicit and explicit large eddy simulations of two-dimensional turbulence through machine learning.},
  author={Romit Maulik and Omer San and Jamey D. Jacob},
  year={2019}
}
In this article, we utilize machine learning to dynamically determine if a point on the computational grid requires implicit numerical dissipation for large eddy simulation (LES). The decision making process is learnt through a priori training on quantities derived from direct numerical simulation (DNS) data. In particular, we compute eddy-viscosities obtained through the coarse graining of DNS quantities and utilize their distribution to categorize areas that require dissipation. If our… CONTINUE READING
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