22 citations · 110 across the 17 of their papers we have counts for
5 papers · 1 filter
Drag-reduction strategies in wall-bounded turbulent flows using deep reinforcement learning
L. Guastoni, J. Rabault, H. Azizpour +1
In this work we compare different drag-reduction strategies that compute their actuation based on the fluctuations at a given wall-normal location in turbulent open channel flow. I…
Easy attention: A simple attention mechanism for temporal predictions with transformers
Marcial Sanchis-Agudo, Yuning Wang, Roger Arnau +4
To improve the robustness of transformer neural networks used for temporal-dynamics prediction of chaotic systems, we propose a novel attention mechanism called easy attention whic…
Predicting the wall-shear stress and wall pressure through convolutional neural networks
Arivazhagan G. Balasubramanian, Luca Guastoni, Philipp Schlatter +2
The objective of this study is to assess the capability of convolution-based neural networks to predict wall quantities in a turbulent open channel flow. The first tests are perfor…
Deep reinforcement learning for turbulent drag reduction in channel flows
L. Guastoni, J. Rabault, P. Schlatter +2
We introduce a reinforcement learning (RL) environment to design and benchmark control strategies aimed at reducing drag in turbulent fluid flows enclosed in a channel. The environ…
Direct numerical simulation of a zero-pressure-gradient thermal turbulent boundary layer up to
Arivazhagan G. Balasubramanian, Luca Guastoni, Philipp Schlatter +1
The objective of the present study is to provide a numerical database of thermal boundary layers and to contribute to the understanding of the dynamics of passive scalars at differ…