216 citations · 219 across the 3 of their papers we have counts for
4 papers
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…
Towards extraction of orthogonal and parsimonious non-linear modes from turbulent flows
Hamidreza Eivazi, Soledad Le Clainche, Sergio Hoyas +1
We propose a deep probabilistic-neural-network architecture for learning a minimal and near-orthogonal set of non-linear modes from high-fidelity turbulent-flow-field data useful f…
Deep Neural Networks for Nonlinear Model Order Reduction of Unsteady Flows
Hamidreza Eivazi, Hadi Veisi, Mohammad Hossein Naderi +1
Unsteady fluid systems are nonlinear high-dimensional dynamical systems that may exhibit multiple complex phenomena both in time and space. Reduced Order Modeling (ROM) of fluid fl…
Recurrent neural networks and Koopman-based frameworks for temporal predictions in a low-order model of turbulence
Hamidreza Eivazi, Luca Guastoni, Philipp Schlatter +2
The capabilities of recurrent neural networks and Koopman-based frameworks are assessed in the prediction of temporal dynamics of the low-order model of near-wall turbulence by Moe…