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20182023
most citedDeep Neural Networks for Data-Driven Turbulence Models

347 citations · 744 across the 18 of their papers we have counts for

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Showing physics.flu-dynShow all

6 papers · 1 filter

physics.flu-dyn2023★ 1 cited

A Viscous and Heat Conducting Ghost Fluid Method for Multi-Fluid Simulations

Steven Jöns, Christoph Müller, Johanna Hintz +2

The ghost fluid method allows a propagating interface to remain sharp during a numerical simulation. The solution of the Riemann problem at the interface provides proper informatio…

physics.flu-dyn2023★ 1 cited

Numerical and Experimental Investigation of a NACA 64A-110 Airfoil in Transonic Flow Regime

Marcel Blind, Christopher Schauerte, Anne-Marie Schreyer +1

In this paper we present experimental and numerical reference data for a NACA 64A-110 airfoil at two angles of attack for and a Reynolds number of with res…

physics.flu-dyn2023

Data-integrated uncertainty quantification for the performance prediction of iced airfoils

Jakob Dürrwächter, Andrea Beck, Claus-Dieter Munz

Airfoil icing is a severe safety hazard in aviation and causes power losses on wind turbines. The precise shape of the ice formation is subject to large uncertainties, so uncertain…

physics.flu-dyn2023★ 4 cited

Grid-Adaptation for Wall-Modeled Large Eddy Simulation Using Unstructured High-Order Methods

Marcel Blind, Ali Berk Kahraman, Johan Larsson +1

The accuracy and computational cost of a large eddy simulation are highly dependent on the computational grid. Building optimal grids manually from a priori knowledge is not feasib…

physics.flu-dyn2023★ 3 cited

A Time-Accurate Inflow Coupling for Zonal LES

Marcel Blind, Johannes Kleinert, Andrea Beck +1

Generating turbulent inflow data is a challenging task in zonal Large Eddy Simulation (zLES) and often relies on predefined DNS data to generate synthetic turbulence with the corre…

physics.flu-dyn2022★ 87 cited

Deep Reinforcement Learning for Turbulence Modeling in Large Eddy Simulations

Marius Kurz, Philipp Offenhäuser, Andrea Beck

Over the last years, supervised learning (SL) has established itself as the state-of-the-art for data-driven turbulence modeling. In the SL paradigm, models are trained based on a…