143 citations · 348 across the 12 of their papers we have counts for
3 papers · 1 filter
SmartFlow: A CFD-solver-agnostic deep reinforcement learning framework for computational fluid dynamics on HPC platforms
Maochao Xiao, Yuning Wang, Felix Rodach +15
Deep reinforcement learning (DRL) is emerging as a powerful tool for fluid-dynamics research, encompassing active flow control, autonomous navigation, turbulence modeling and disco…
Harnessing Equivariance: Modeling Turbulence with Graph Neural Networks
Marius Kurz, Andrea Beck, Benjamin Sanderse
This work proposes a novel methodology for turbulence modeling in Large Eddy Simulation (LES) based on Graph Neural Networks (GNNs), which embeds the discrete rotational, reflectio…
Invariant Control Strategies for Active Flow Control using Graph Neural Networks
Marius Kurz, Rohan Kaushik, Marcel Blind +4
Reinforcement learning has gained traction for active flow control tasks, with initial applications exploring drag mitigation via flow field augmentation around a two-dimensional c…