3 papers
physics.flu-dyn2026
An Architecture-Agnostic High-Order Discontinuous Galerkin Framework for Compressible Flows
Spencer Starr, Yannik Feldner, Patrick Kopper +6
With the recent proliferation of heterogeneous, GPU-accelerated supercomputers, high-order computational fluid dynamics (CFD) simulations of complex, turbulent flows are more acces…
physics.flu-dyn2025
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…
cs.LG2025
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…