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We present the design and implementation details of a geometric multigrid method on adaptively refined meshes for massively parallel computations. The method uses local smoothing on the refined part of the mesh. Partitioning is achieved by…

Numerical Analysis · Computer Science 2021-08-04 Thomas C. Clevenger , Timo Heister , Guido Kanschat , Martin Kronbichler

In this work, we derive a reliable and efficient residual-typed error estimator for the finite element approximation of a 2d cathodic protection problem governed by a steady-state diffusion equation with a nonlinear boundary condition. We…

Numerical Analysis · Mathematics 2019-08-21 Guanglian Li , Yifeng Xu

It is significant and challenging to solve eigenvalue problems of partial differential operators when many highly accurate eigenpair approximations are required. The adaptive finite element discretization based parallel orbital-updating…

Numerical Analysis · Mathematics 2025-09-24 Xiaoying Dai , Yan Li , Bin Yang , Aihui Zhou

We develop a cut finite element method for a second order elliptic coupled bulk-surface model problem. We prove a priori estimates for the energy and $L^2$ norms of the error. Using stabilization terms we show that the resulting algebraic…

Numerical Analysis · Mathematics 2014-03-27 Erik Burman , Peter Hansbo , Mats G. Larson , Sara Zahedi

In this work, we develop a posteriori error control for a generalized Boussinesq model in which thermal conductivity and viscosity are temperature-dependent. Therein, the stationary Navier-Stokes equations are coupled with a stationary heat…

Numerical Analysis · Mathematics 2022-12-16 S. Beuchler , B. Endtmayer , J. Lankeit , T. Wick

In this paper we present an adaptive discretization technique for solving elliptic partial differential equations via a collocation radial basis function partition of unity method. In particular, we propose a new adaptive scheme based on…

Numerical Analysis · Mathematics 2018-11-13 R. Cavoretto , A. De Rossi

We design an adaptive finite element method to approximate the solutions of quasi-linear elliptic problems. The algorithm is based on a Ka\v{c}anov iteration and a mesh adaptation step is performed after each linear solve. The method is…

Numerical Analysis · Mathematics 2010-06-18 Eduardo M. Garau , Pedro Morin , Carlos Zuppa

We introduce a goal-oriented strategy for multiscale computations performed using the Multiscale Finite Element Method (MsFEM). In a previous work, we have shown how to use, in the MsFEM framework, the concept of Constitutive Relation Error…

Numerical Analysis · Mathematics 2019-08-02 Ludovic Chamoin , Frederic Legoll

We give a goal-oriented a posteriori error estimator for the atomistic-continuum modeling error in the quasicontinuum method, and we use this estimator to design an adaptive algorithm to compute a quantity of interest to a given tolerance…

Numerical Analysis · Mathematics 2007-08-02 Marcel Arndt , Mitchell Luskin

We present a robust and efficient target-based mesh adaptation methodology, building on hybridized discontinuous Galerkin schemes for (nonlinear) convection-diffusion problems, including the compressible Euler and Navier-Stokes equations.…

Numerical Analysis · Mathematics 2014-11-12 Michael Woopen , Georg May , Jochen Schütz

In this work, we propose and analyze a pointwise a posteriori error estimator for simple eigenvalues of elliptic eigenvalue problems with adaptive finite element methods (AFEMs). We prove the reliability and efficiency of the residual-type…

Numerical Analysis · Mathematics 2025-11-11 Zhenglei Li , Qigang Liang , Xuejun Xu

In this study we propose a-posteriori error estimation results to approximate the precision loss in quantities of interests computed using reduced order models. To generate the surrogate models we employ Proper Orthogonal Decomposition and…

Numerical Analysis · Mathematics 2024-12-20 R. Stefanescu , A. Sandu

We consider an interface problem often arising in transport problems: a coupled system of partial differential equations with one (elliptic) transport equation on a bounded domain and one equation (in this case the Laplace problem) on the…

Numerical Analysis · Mathematics 2016-05-24 Christoph Erath , Robert Schorr

Adaptive Finite Element Method (adaptivity) is known to be an effective numerical tool for some ill-posed problems. The key advantage of the adaptivity is the image improvement with local mesh refinements. A rigorous proof of this property…

Mathematical Physics · Physics 2012-10-30 Larisa Beilina , Michael V. Klibanov

In this work we present an adaptive Newton-type method to solve nonlinear constrained optimization problems in which the constraint is a system of partial differential equations discretized by the finite element method. The adaptive…

Optimization and Control · Mathematics 2017-06-05 Thomas Carraro , Simon Dörsam , Stefan Frei , Daniel Schwarz

A posteriori error estimators for the symmetric mixed finite element methods for linear elasticity problems of Dirichlet and mixed boundary conditions are proposed. Stability and efficiency of the estimators are proved. Finally, we provide…

Numerical Analysis · Mathematics 2017-05-12 Long Chen , Jun Hu , Xuehai Huang , Hongying Man

The proposed two-dimensional geometrically exact beam element extends our previous work by including the effects of shear distortion, and also of distributed forces and moments acting along the beam. The general flexibility-based…

Numerical Analysis · Mathematics 2025-08-06 Milan Jirasek , Martin Horak , Emma La Malfa Ribolla , Chiara Bonvissuto

We propose a time-adaptive predictor/multi-corrector method to solve hyperbolic partial differential equations, based on the generalized-$\alpha$ scheme that provides user-control on the numerical dissipation and second-order accuracy in…

Numerical Analysis · Mathematics 2022-10-11 Nicolas A. Labanda , Pouria Behnoudfar , Victor M. Calo

Starting from a recent a posteriori error estimator for the finite element solution of the wave equation with explicit time-stepping [Grote, Lakkis, Santos, 2024], we devise a space-time adaptive strategy which includes both time evolving…

Numerical Analysis · Mathematics 2026-01-07 Marcus J. Grote , Omar Lakkis , Carina S. Santos

Distribution shifts are ubiquitous in real-world machine learning applications, posing a challenge to the generalization of models trained on one data distribution to another. We focus on scenarios where data distributions vary across…

Machine Learning · Statistics 2024-06-05 Steven Wilkins-Reeves , Xu Chen , Qi Ma , Christine Agarwal , Aude Hofleitner