activity
20162023
most citedA neural network multigrid solver for the Navier-Stokes equations

49 citations · 324 across the 34 of their papers we have counts for

collaborators
Showing 2021Show all

5 papers · 1 filter

math.NA2021★ 2 cited

Error analysis for a parabolic PDE model problem on a coupled moving domain in a fully Eulerian framework

Henry von Wahl, Thomas Richter

We introduce an unfitted finite element method with Lagrange-multipliers to study an Eulerian time stepping scheme for moving domain problems applied to a model problem where the d…

physics.flu-dyn2021★ 12 cited

Steady azimuthal flow field induced by a rotating sphere near a rigid disk or inside a gap between two coaxially positioned rigid disks

Abdallah Daddi-Moussa-Ider, Alexander R. Sprenger, Thomas Richter +2

Geometric confinements play an important role in many physical and biological processes and significantly affect the rheology and behavior of colloidal suspensions at low Reynolds…

math.NA2021★ 3 cited

On temporal homogenization in the numerical simulation of atherosclerotic plaque growth

Stefan Frei, Alexander Heinlein, Thomas Richter

A temporal homogenization approach for the numerical simulation of atherosclerotic plaque growth is extended to fully coupled fluid-structure interaction (FSI) simulations. The num…

math.NA2021★ 3 cited

Deep neural networks for geometric multigrid methods

Nils Margenberg, Robert Jendersie, Thomas Richter +1

We investigate scaling and efficiency of the deep neural network multigrid method (DNN-MG). DNN-MG is a novel neural network-based technique for the simulation of the Navier-Stokes…

physics.flu-dyn2021★ 7 cited

Using a deep neural network to predict the motion of under-resolved triangular rigid bodies in an incompressible flow

Henry von Wahl, Thomas Richter

We consider non-spherical rigid body particles in an incompressible fluid in the regime where the particles are too large to assume that they are simply transported with the fluid…