24 citations · 43 across the 10 of their papers we have counts for
9 papers · 1 filter
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…
Entropy stable shock capturing for high-order DGSEM on moving meshes
Anna Schwarz, Jens Keim, Christian Rohde +1
In this paper, a shock capturing for high-order entropy stable discontinuous Galerkin spectral element methods on moving meshes is proposed using Gauss--Lobatto nodes. The shock ca…
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…
Efficient computation of particle-fluid and particle-particle interactions in compressible flow
Anna Schwarz, Patrick Kopper, Emilian De Staercke +1
Particle collisions are the primary mechanism of inter-particle momentum and energy exchange for dense particle-laden flow. Accurate approximation of this collision operator in fou…