activity
20122025
most citedAdaptive FEM with optimal convergence rates for a certain class of non-symmetric and possibly non-linear problems

76 citations · 1.5k across the 82 of their papers we have counts for

collaborators
Showing 2018Show all

8 papers · 1 filter

physics.comp-ph2018★ 13 cited

Computational micromagnetics with Commics

Carl-Martin Pfeiler, Michele Ruggeri, Bernhard Stiftner +6

We present our open-source Python module Commics for the study of the magnetization dynamics in ferromagnetic materials via micromagnetic simulations. It implements state-of-the-ar…

math.NA2018★ 22 cited

Convergence of adaptive stochastic Galerkin FEM

Alex Bespalov, Dirk Praetorius, Leonardo Rocchi +1

We propose and analyze novel adaptive algorithms for the numerical solution of elliptic partial differential equations with parametric uncertainty. Four different marking strategie…

math.NA2018★ 12 cited

Iterative solution and preconditioning for the tangent plane scheme in computational micromagnetics

Johannes Kraus, Carl-Martin Pfeiler, Dirk Praetorius +2

The tangent plane scheme is a time-marching scheme for the numerical solution of the nonlinear parabolic Landau-Lifshitz-Gilbert equation (LLG), which describes the time evolution…

math.NA2018★ 5 cited

Optimal additive Schwarz preconditioning for adaptive 2D IGA boundary element methods

Thomas Führer, Gregor Gantner, Dirk Praetorius +1

We define and analyze (local) multilevel diagonal preconditioners for isogeometric boundary elements on locally refined meshes in two dimensions. Hypersingular and weakly-singular…

math.NA2018★ 19 cited

Adaptive BEM with optimal convergence rates for the Helmholtz equation

Alex Bespalov, Timo Betcke, Alexander Haberl +1

We analyze an adaptive boundary element method for the weakly-singular and hypersingular integral equations for the 2D and 3D Helmholtz problem. The proposed adaptive algorithm is…

math.NA2018★ 20 cited

Goal-oriented error estimation and adaptivity for elliptic PDEs with parametric or uncertain inputs

Alex Bespalov, Dirk Praetorius, Leonardo Rocchi +1

We use the ideas of goal-oriented error estimation and adaptivity to design and implement an efficient adaptive algorithm for approximating linear quantities of interest derived fr…