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20162022
most citedLearning the structure of wind: A data-driven nonlocal turbulence model for the atmospheric boundary layer

9 citations · 13 across the 7 of their papers we have counts for

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Showing cs.CEShow all

6 papers · 1 filter

cs.CE2021

Semi matrix-free twogrid shifted Laplacian preconditioner for the Helmholtz equation with near optimal shifts

Daniel Drzisga, Tobias Köppl, Barbara Wohlmuth

Due to its significance in terms of wave phenomena a considerable effort has been put into the design of preconditioners for the Helmholtz equation. One option to derive a precondi…

cs.CE2021

Multidimensional coupling: A variationally consistent approach to fiber-reinforced materials

Ustim Khristenko, Stefan Schuß, Melanie Krüger +3

A novel mathematical model for fiber-reinforced materials is proposed. It is based on a 1-dimensional beam model for the thin fiber structures, a flexible and general 3-dimensional…

cs.CE2020

Frontiers in Mortar Methods for Isogeometric Analysis

Christian Hesch, Ustim Khristenko, Rolf Krause +4

Complex geometries as common in industrial applications consist of multiple patches, if spline based parametrizations are used. The requirements for the generation of analysis-suit…

cs.CE2020

A 3D-1D coupled blood flow and oxygen transport model to generate microvascular networks

Tobias Köppl, Ettore Vidotto, Barbara Wohlmuth

In this work, we introduce an algorithmic approach to generate microvascular networks starting from larger vessels that can be reconstructed without noticeable segmentation errors.…

cs.CE2019

Stencil scaling for vector-valued PDEs on hybrid grids with applications to generalized Newtonian fluids

Daniel Drzisga, Ulrich Rüde, Barbara Wohlmuth

Matrix-free finite element implementations for large applications provide an attractive alternative to standard sparse matrix data formats due to the significantly reduced memory c…

cs.CE20161 cited

Scheduling massively parallel multigrid for multilevel Monte Carlo methods

Björn Gmeiner, Daniel Drzisga, Ulrich Ruede +2

The computational complexity of naive, sampling-based uncertainty quantification for 3D partial differential equations is extremely high. Multilevel approaches, such as multilevel…