22 citations · 110 across the 17 of their papers we have counts for
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physics.flu-dyn2022★ 1 cited
Fully convolutional networks for velocity-field predictions based on the wall heat flux in turbulent boundary layers
L. Guastoni, A. G. Balasubramanian, F. Foroozan +6
Fully-convolutional neural networks (FCN) were proven to be effective for predicting the instantaneous state of a fully-developed turbulent flow at different wall-normal locations…
physics.flu-dyn2022★ 2 cited
Predicting the temporal dynamics of turbulent channels through deep learning
Giuseppe Borrelli, Luca Guastoni, Hamidreza Eivazi +2
The success of recurrent neural networks (RNNs) has been demonstrated in many applications related to turbulence, including flow control, optimization, turbulent features reproduct…