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We present an equilibration-based a posteriori error estimator for N\'ed\'elec element discretizations of the magnetostatic problem. The estimator is obtained by adding a gradient correction to the estimator for N\'ed\'elec elements of…

Numerical Analysis · Mathematics 2021-05-26 Joscha Gedicke , Sjoerd Geevers , Ilaria Perugia , Joachim Schöberl

Second-order partial differential equations in non-divergence form are considered. Equations of this kind typically arise as subproblems for the solution of Hamilton-Jacobi-Bellman equations in the context of stochastic optimal control, or…

Numerical Analysis · Mathematics 2020-08-13 Jan Blechschmidt , Roland Herzog , Max Winkler

This paper proposes a novel technique for the approximation of strong solutions $u \in C(\overline{\Omega}) \cap W^{2,n}_\mathrm{loc}(\Omega)$ to uniformly elliptic linear PDE of second order in nondivergence form with continuous leading…

Numerical Analysis · Mathematics 2026-04-10 Ngoc Tien Tran

We introduce a novel residual-based a posteriori error estimator for the conforming $C^1$ Virtual Element Method (VEM) applied to the buckling eigenvalue problem, incorporating nonlinear plane stress effects in both two and three…

Numerical Analysis · Mathematics 2026-03-24 Franco Dassi , Andres E Rubiano , Iván Velásquez

This paper is concerned with the derivation of computable and guaranteed upper and lower bounds of the difference between the exact and the approximate solution of a boundary value problem for static Maxwell equations. Our analysis is based…

Analysis of PDEs · Mathematics 2011-05-23 Dirk Pauly , Sergey Repin

We consider isogeometric discretizations of the Poisson model problem, focusing on high polynomial degrees and strong hierarchical refinements. We derive a posteriori error estimates by equilibrated fluxes, i.e., vector-valued mapped…

Numerical Analysis · Mathematics 2024-03-01 Gregor Gantner , Martin Vohralík

In this paper, we design the first residual type a posteriori error estimator for mixed interior penalty discontinuous Galerkin method for the H(curl)-elliptic problems. Then we prove that our residual based a posteriori error indicator is…

Numerical Analysis · Mathematics 2023-01-05 Ming Tang , Xiaoqing Xing , Liuqiang Zhong

We verify functional a posteriori error estimate for obstacle problem proposed by Repin. Simplification into 1D allows for the construction of a nonlinear benchmark for which an exact solution of the obstacle problem can be derived. Quality…

Numerical Analysis · Mathematics 2016-11-04 Petr Harasim , Jan Valdman

We present a posteriori error estimates for finite element approximations in a minimization approach to a coefficient inverse problem. The problem is that of reconstructing the dielectric permittivity $\varepsilon =…

Numerical Analysis · Mathematics 2015-02-27 John Bondestam Malmberg

A posteriori error estimates are an important tool to bound discretization errors in terms of computable quantities avoiding regularity conditions that are often difficult to establish. For non-linear and non-differentiable problems,…

Numerical Analysis · Mathematics 2024-06-12 Sören Bartels , Alex Kaltenbach

In this paper, we derive a novel recovery type a posteriori error estimation of the Crank-Nicolson finite element method for the Cahn--Hilliard equation. To achieve this, we employ both the elliptic reconstruction technique and a time…

Numerical Analysis · Mathematics 2023-05-03 Yaoyao Chen , Yunqing Huang , Nianyu Yi , Peimeng Yin

This paper introduces an explicit residual-based a posteriori error analysis for the symmetric mixed finite element method in linear elasticity after Arnold-Winther with pointwise symmetric and H(div)-conforming stress approximation.…

Numerical Analysis · Mathematics 2017-05-25 C. Carstensen , D. Gallistl , J. Gedicke

We derive and discuss a posteriori error estimators for Galerkin and collocation IGA boundary element methods for weakly-singular integral equations of the first-kind in 2D. While recent own work considered the Faermann residual error…

Numerical Analysis · Mathematics 2016-11-24 Michael Feischl , Gregor Gantner , Alexander Haberl , Dirk Praetorius

We derive a posteriori error estimate for a fully discrete adaptive finite element approximation of the stochastic Cahn-Hilliard equation with rough noise. The considered model is derived from the stochastic Cahn-Hilliard equation with…

Numerical Analysis · Mathematics 2025-12-18 Lubomir Banas , Jean Daniel Mukam

In this paper, we study an adaptive finite element method for a class of a nonlinear eigenvalue problems that may be of nonconvex energy functional and consider its applications to quantum chemistry. We prove the convergence of adaptive…

Numerical Analysis · Mathematics 2010-01-15 H. Chen , X. Gong , L. He , A. Zhou

For elliptic interface problems in two- and three-dimensions with a possible very low regularity, this paper establishes a priori error estimates for the Raviart-Thomas and Brezzi-Douglas-Marini mixed finite element approximations. These…

Numerical Analysis · Mathematics 2019-03-01 Shun Zhang

We propose new a posteriori error estimators for non-conforming finite element discretizations of second-order elliptic PDE problems. These estimators are based on novel reformulations of the standard Prager-Synge identity, and enable to…

Numerical Analysis · Mathematics 2026-01-22 T. Chaumont-Frelet

The main goal of this paper is to analyze a family of "simplest possible" initial data for which, as shown by numerical simulations, the incompressible Euler equations have multiple solutions. We take here a first step toward a rigorous…

Analysis of PDEs · Mathematics 2020-02-07 Alberto Bressan , Wen Shen

This article describes the extension of recent methods for a posteriori error estimation such as dual-weighted residual methods to node-centered finite volume discretizations of second order elliptic boundary value problems including upwind…

Numerical Analysis · Mathematics 2026-02-04 Lutz Angermann

Solutions to inverse problems that are ill-conditioned or ill-posed may have significant intrinsic uncertainty. Unfortunately, analysing and quantifying this uncertainty is very challenging, particularly in high-dimensional problems. As a…

Methodology · Statistics 2016-07-12 Marcelo Pereyra