Deep reinforcement learning for flow control exploits different physics for increasing Reynolds number regimes P Varela, P Suárez, F Alcántara-Ávila, A Miró, J Rabault, B Font, ...
Actuators 11 (12), 359, 2022
47 2022 Deep learning of the spanwise-averaged Navier–Stokes equations B Font, GD Weymouth, VT Nguyen, OR Tutty
Journal of Computational Physics 434, 110199, 2021
37 2021 Span effect on the turbulence nature of flow past a circular cylinder B Font, GD Weymouth, VT Nguyen, OR Tutty
Journal of Fluid Mechanics 878, 306-323, 2019
23 * 2019 Active flow control of a turbulent separation bubble through deep reinforcement learning B Font, F Alcántara-Ávila, J Rabault, R Vinuesa, O Lehmkuhl
Journal of Physics: Conference Series 2753 (1), 012022, 2024
14 2024 A data-driven wall-shear stress model for LES using gradient boosted decision trees S Radhakrishnan, LA Gyamfi, A Miró, B Font, J Calafell, O Lehmkuhl
International Conference on High Performance Computing, 105-121, 2021
13 2021 Active flow control for three-dimensional cylinders through deep reinforcement learning P Suárez, F Alcántara-Ávila, A Miró, J Rabault, B Font, O Lehmkuhl, ...
arXiv preprint arXiv:2309.02462, 2023
12 2023 Active flow control for drag reduction through multi-agent reinforcement learning on a turbulent cylinder at P Suárez, F Alcantara-Avila, A Miró, J Rabault, B Font, O Lehmkuhl, ...
arXiv preprint arXiv:2405.17655, 2024
8 2024 Flow control of three-dimensional cylinders transitioning to turbulence via multi-agent reinforcement learning P Suárez, F Álcantara-Ávila, J Rabault, A Miró, B Font, O Lehmkuhl, ...
arXiv preprint arXiv:2405.17210, 2024
4 2024 WaterLily. jl: A differentiable fluid simulator in Julia with fast heterogeneous execution GD Weymouth, B Font
arXiv preprint arXiv:2304.08159, 2023
2 2023 WaterLily. jl: A differentiable and backend-agnostic Julia solver to simulate incompressible viscous flow and dynamic bodies GD Weymouth, B Font
arXiv preprint arXiv:2407.16032, 2024
1 2024 Turbulent wake prediction using deep convolutional neural networks B Font, G Weymouth, VT Nguyen, O Tutty
1 2020 Analysis of two-dimensional and three-dimensional wakes of long circular cylinders B Font, GD Weymouth, OR Tutty
OCEANS 2017-Aberdeen, 1-8, 2017
1 2017 Deep reinforcement learning for active flow control in a turbulent separation bubble B Font, F Alcántara-Ávila, J Rabault, R Vinuesa, O Lehmkuhl
Nature Communications 16 (1), 1422, 2025
2025 Towards Active Flow Control Strategies Through Deep Reinforcement Learning R Montalà, B Font, P Suárez, J Rabault, O Lehmkuhl, I Rodriguez
arXiv preprint arXiv:2411.05536, 2024
2024 Data-driven wall modeling for LES involving non-equilibrium boundary layer effects S Radhakrishnan, J Calafell, A Miró, B Font, O Lehmkuhl
International Journal of Numerical Methods for Heat & Fluid Flow 34 (8 …, 2024
2024 Towards active flow control strategies through deep reinforcement learning R Montalà Sales, B Font García, P Suárez Morales, J Rabault, ...
ECCOMAS: 9th European Congress on Computational Methods in Applied Sciences …, 2024
2024 WaterLily: A fast differentiable CPU/GPU flow simulator in Julia G Weymouth, B Font
Bulletin of the American Physical Society, 2023
2023 The effect of physical constraints on the loss function landscapes of deep learning models M Cabral, B Font, G Weymouth
Bulletin of the American Physical Society, 2023
2023 Deep reinforcement learning for active separation control in a turbulent boundary layer F Alcántara-Ávila, B Font, J Rabault, R Vinuesa, O Lehmkuhl
Bulletin of the American Physical Society, 2023
2023 On the entropy-viscosity method for flux reconstruction B Font, A Miró, O Lehmkuhl
2nd Spanish Fluid Mechanics Conference, 2023
2023 
Oriol LehmkuhlLarge-scale Computational Fluid Dynamics Team Leader at Barcelona Supercomputer Center (BSC)Geverifieerd e-mailadres voor bsc.es