22 citations · 48 across the 13 of their papers we have counts for
7 papers · 1 filter
Diff-SPORT: Diffusion-based Sensor Placement Optimization and Reconstruction of Turbulent flows in urban environments
Abhijeet Vishwasrao, Sai Bharath Chandra Gutha, Andres Cremades +8
Rapid urbanization demands efficient monitoring of turbulent wind and pollutant dispersion, yet existing reconstruction and sensor placement strategies fail under realistic sparsit…
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…
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…
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…
Predicting the near-wall region of turbulence through convolutional neural networks
A. G. Balasubramanian, L. Guastoni, A. Güemes +5
Modelling the near-wall region of wall-bounded turbulent flows is a widespread practice to reduce the computational cost of large-eddy simulations (LESs) at high Reynolds number. A…
Prediction of wall-bounded turbulence from wall quantities using convolutional neural networks
L. Guastoni, M. P. Encinar, P. Schlatter +2
A fully-convolutional neural-network model is used to predict the streamwise velocity fields at several wall-normal locations by taking as input the streamwise and spanwise wall-sh…