11 citations · 16 across the 2 of their papers we have counts for
Showing physics.flu-dynShow all
2 papers · 1 filter
physics.flu-dyn2019★ 11 cited
Deep learning for subgrid-scale turbulence modeling in large-eddy simulations of the atmospheric boundary layer
Yu Cheng, Marco Giometto, Pit Kauffmann +7
In large-eddy simulations, subgrid-scale (SGS) processes are parameterized as a function of filtered grid-scale variables. First-order, algebraic SGS models are based on the eddy-v…
physics.flu-dyn2019
Non-equilibrium three-dimensional boundary layers at moderate Reynolds numbers
Adrián Lozano-Durán, Marco Giometto, George I. Park +1
Non-equilibrium wall turbulence with mean-flow three-dimensionality is ubiquitous in geophysical and engineering flows. Under these conditions, turbulence may experience a counter-…