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This paper studies formulations of second-order elliptic partial differential equations in nondivergence form on convex domains as equivalent variational problems. The first formulation is that of Smears \& S\"uli [SIAM J.\ Numer.\ Anal.\…

Numerical Analysis · Mathematics 2017-01-17 Dietmar Gallistl

In this paper, we consider the integrating factor midpoint method for wave-type equations and derive optimal order a posteriori error estimates. We first introduce an integrating factor midpoint approximation defined by the piecewise linear…

Numerical Analysis · Mathematics 2026-03-03 Xianfa Hu , Fazhan Geng , Wansheng Wang

Given a function f defined on a bidimensional bounded domain and a positive integer N, we study the properties of the triangulation that minimizes the distance between f and its interpolation on the associated finite element space, over all…

Numerical Analysis · Mathematics 2012-06-06 Jean-Marie Mirebeau

This paper proposes some efficient and accurate adaptive two-grid (ATG) finite element algorithms for linear and nonlinear partial differential equations (PDEs). The main idea of these algorithms is to utilize the solutions on the $k$-th…

Numerical Analysis · Mathematics 2020-09-22 Yukun Li , Yi Zhang

We devise an a posteriori error estimator for an affine optimal control problem subject to a semilinear elliptic PDE and control constraints. To approximate the problem, we consider a semidiscrete scheme based on the variational…

Optimization and Control · Mathematics 2025-05-08 Francisco Fuica , Nicolai Jork

The conformal formulation of the Einstein constraint equations is first reviewed, and we then consider the design, analysis, and implementation of adaptive multilevel finite element-type numerical methods for the resulting coupled nonlinear…

General Relativity and Quantum Cosmology · Physics 2009-04-07 Burak Aksoylu , David Bernstein , Stephen Bond , Michael Holst

We propose a new adaptive algorithm for the approximation of the Landau-Lifshitz-Gilbert equation via a higher-order tangent plane scheme. We show that the adaptive approximation satisfies an energy inequality and demonstrate numerically,…

Numerical Analysis · Mathematics 2026-02-06 Jan Bohn , Willy Dörfler , Michael Feischl , Stefan Karch

Mesh adaption procedures for finite element approximation allows one to adapt the resolution, by local refinement in the regions of strong variation of the function of interest. This procedure plays a key role in numerous applications of…

Numerical Analysis · Mathematics 2015-03-17 Jean-Marie Mirebeau

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

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

This article deals with the adaptive and approximative computation of the Lam\'e equations. The equations of linear elasticity are considered as boundary integral equations and solved in the setting of the boundary element method (BEM).…

Numerical Analysis · Mathematics 2022-05-11 Maximilian Bauer , Mario Bebendorf

This paper is concerned with the numerical approximation of quantities of interest associated with solutions to parametric elliptic partial differential equations (PDEs). The key novelty of this work is in its focus on the quantities of…

Numerical Analysis · Mathematics 2025-10-09 Alex Bespalov , Dirk Praetorius , Michele Ruggeri

In this paper, we develop an adaptive finite element method for the nonlinear steady-state Poisson-Nernst-Planck equations, where the spatial adaptivity for geometrical singularities and boundary layer effects are mainly considered. As a…

Numerical Analysis · Mathematics 2020-08-21 Tingting Hao , Manman Ma , Xuejun Xu

A finite element method for elliptic problems with discontinuous coefficients is presented. The discontinuity is assumed to take place along a closed smooth curve. The proposed method allows to deal with meshes that are not adapted to the…

Numerical Analysis · Mathematics 2007-07-12 Gunther H. Peichl , Rachid Touzani

We are concerned with the homogenization of second-order linear elliptic equations with random coefficient fields. For symmetric coefficient fields with only short-range correlations, quantified through a logarithmic Sobolev inequality for…

Analysis of PDEs · Mathematics 2016-11-08 Peter Bella , Benjamin Fehrman , Julian Fischer , Felix Otto

We design and analyze a new adaptive stabilized finite element method. We construct a discrete approximation of the solution in a continuous trial space by minimizing the residual measured in a dual norm of a discontinuous test space that…

Numerical Analysis · Mathematics 2020-04-22 Victor M. Calo , Alexandre Ern , Ignacio Muga , Sergio Rojas

In this paper we analyze a space-time unfitted finite element method for the discretization of scalar surface partial differential equations on evolving surfaces. For higher order approximations of the evolving surface we use the technique…

Numerical Analysis · Mathematics 2024-11-26 Arnold Reusken , Hauke Sass

Automatic algorithms attempt to provide approximate solutions that differ from exact solutions by no more than a user-specified error tolerance. This paper describes an automatic, adaptive algorithm for approximating the solution to a…

Numerical Analysis · Mathematics 2018-09-28 Yuhan Ding , Fred J. Hickernell , Lluís Antoni Jiménez Rugama

We propose and analyse a fully adaptive strategy for solving elliptic PDEs with random data in this work. A hierarchical sequence of adaptive mesh refinements for the spatial approximation is combined with adaptive anisotropic sparse…

Numerical Analysis · Mathematics 2020-08-26 Jens Lang , Robert Scheichl , David Silvester

Hierarchical optimization refers to problems with interdependent decision variables and objectives, such as minimax and bilevel formulations. While various algorithms have been proposed, existing methods and analyses lack adaptivity in…

Machine Learning · Computer Science 2025-10-27 Xiaochuan Gong , Jie Hao , Mingrui Liu
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