1 citations · 1 across the 6 of their papers we have counts for
9 papers
In-Memory Load Balancing for Discontinuous Galerkin Methods on Polytopal Meshes
Patrick Kopper, Anna Schwarz, Jens Keim +1
High-order accurate discontinuous Galerkin (DG) methods have emerged as powerful tools for solving partial differential equations such as the compressible Navier-Stokes equations d…
Evaluating simulation techniques for lubricant distribution in gearboxes
Pawan S. Murthy, Anja Lippert, Andrea Beck
Efficient lubrication is crucial for the performance and durability of high-speed gearboxes, particularly under varying load conditions. Excess lubrication leads to increased churn…
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…
Entropy stable high-order discontinuous Galerkin spectral-element methods on curvilinear, hybrid meshes
Jens Keim, Anna Schwarz, Patrick Kopper +3
Hyperbolic-parabolic partial differential equations are widely used for the modeling of complex, multiscale problems. High-order methods such as the discontinuous Galerkin (DG) sch…
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…
Comparison of Entropy Stable Collocation High-Order DG Methods for Compressible Turbulent Flows
Anna Schwarz, Daniel Kempf, Jens Keim +3
High-order methods are well-suited for the numerical simulation of complex compressible turbulent flows, but require additional stabilization techniques to capture instabilities ar…