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We introduce a family of proximal discontinuous Galerkin methods for variational inequalities, focusing on the obstacle problem as a didactic example. Each member of this family is born from applying a different well-known nonconforming…

Numerical Analysis · Mathematics 2026-04-23 Alexandre Ern , Brendan Keith , Dohyun Kim , Rami Masri , Beatrice Riviere

In this paper, we present a unified analysis of the superconvergence property for a large class of mixed discontinuous Galerkin methods. This analysis applies to both the Poisson equation and linear elasticity problems with symmetric stress…

Numerical Analysis · Mathematics 2021-07-28 Limin Ma

We propose an efficient variant of a primal Discontinuous Galerkin method with interior penalty for the second order elliptic equations on very general meshes (polytopes with eventually curved boundaries). Efficiency, especially when higher…

Numerical Analysis · Mathematics 2019-03-18 Alexei Lozinski

We propose and rigorously analyse semi- and fully discrete discontinuous Galerkin methods for an initial and boundary value problem describing inertial viscoelasticity in terms of elastic and viscoelastic stress components, and with mixed…

Numerical Analysis · Mathematics 2023-06-27 Salim Meddahi , Ricardo Ruiz-Baier

We derive energy-norm a posteriori error bounds for an Euler time-stepping method combined with various spatial discontinuous Galerkin schemes for linear parabolic problems. For accessibility, we address first the spatially semidiscrete…

Numerical Analysis · Mathematics 2011-04-06 Emmanuil H. Georgoulis , Omar Lakkis , Juha M. Virtanen

This paper is concerned with developing accurate and efficient numerical methods for fully nonlinear second order elliptic and parabolic partial differential equations (PDEs) in multiple spatial dimensions. It presents a general framework…

Numerical Analysis · Mathematics 2018-01-19 Xiaobing Feng , Thomas Lewis

Discontinuous Galerkin (DG) methods offer an enormous flexibility regarding local grid refinement and variation of polynomial degrees for a variety of different problem classes. With a focus on diffusion problems, we consider DG…

Numerical Analysis · Mathematics 2013-01-01 Kolja Brix , Claudio Canuto , Wolfgang Dahmen

In this paper, we study the convergence of adaptive mixed interior penalty discontinuous Galerkin method for H(curl)-elliptic problems. We first get the mixed model of H(curl)-elliptic problem by introducing a new intermediate variable.…

Numerical Analysis · Mathematics 2023-01-05 K. Liu , M. Tang , X. Q. Xing , L. Q. Zhong

An interior penalty discontinuous Galerkin method is devised to approximate minimizers of a linear folding model by discontinuous isoparametric finite element functions that account for an approximation of a folding arc. The numerical…

Numerical Analysis · Mathematics 2022-05-13 Sören Bartels , Andrea Bonito , Philipp Tscherner

This paper constitutes our initial effort in developing sparse grid discontinuous Galerkin (DG) methods for high-dimensional partial differential equations (PDEs). Over the past few decades, DG methods have gained popularity in many…

Numerical Analysis · Mathematics 2016-04-20 Zixuan Wang , Qi Tang , Wei Guo , Yingda Cheng

We present and analyze a discontinuous Galerkin method for the numerical modeling of a Kelvin-Voigt thermo/poro-viscoelastic problem. We present the derivation of the model and we develop a stability analysis in the continuous setting that…

Numerical Analysis · Mathematics 2025-08-01 Stefano Bonetti , Mattia Corti

In this paper we propose a variant of enriched Galerkin methods for second order elliptic equations with over-penalization of interior jump terms. The bilinear form with interior over-penalization gives a non-standard norm which is…

Numerical Analysis · Mathematics 2023-10-24 Jeonghun J. Lee , Omar Ghattas

We present a discontinuous Galerkin internal-penalty scheme that is applicable to a large class of linear and nonlinear elliptic partial differential equations. The unified scheme can accommodate all second-order elliptic equations that can…

Numerical Analysis · Mathematics 2022-01-13 Nils L. Fischer , Harald P. Pfeiffer

In this paper, we derive a priori error estimates for a class of interior penalty discontinuous Galerkin (DG) methods using immersed finite element (IFE) functions for a classic second-order elliptic interface problem. The error estimation…

Numerical Analysis · Mathematics 2016-11-02 Tao Lin , Qing Yang , Xu Zhang

In this paper, we present an immersed weak Galerkin method for solving second-order elliptic interface problems. The proposed method does not require the meshes to be aligned with the interface. Consequently, uniform Cartesian meshes can be…

Numerical Analysis · Mathematics 2019-10-18 Lin Mu , Xu Zhang

We develop a general convergence theory for adaptive discontinuous Galerkin methods for elliptic PDEs covering the popular SIPG, NIPG and LDG schemes as well as all practically relevant marking strategies. Another key feature of the…

Numerical Analysis · Mathematics 2020-09-07 Christian Kreuzer , Emmanuil H. Georgoulis

Motivated by applications to numerical simulation of flows in highly heterogeneous porous media, we develop multiscale finite element methods for second order elliptic equations. We discuss a multiscale model reduction technique in the…

Numerical Analysis · Mathematics 2015-06-15 Y. Efendiev , J. Galvis , R. Lazarov , M. Moon , M. Sarkis

We introduce a discontinuous Galerkin method for the mixed formulation of the elasticity eigenproblem with reduced symmetry. The analysis of the resulting discrete eigenproblem does not fit in the standard spectral approximation framework…

Numerical Analysis · Mathematics 2018-01-29 Felipe Lepe , Salim Meddahi , David Mora , Rodolfo Rodríguez

In this work a solver for instationary two-phase flows on the basis of the extended Discontinuous Galerkin (extended DG/XDG) method is presented. The XDG method adapts the approximation space conformal to the position of the interface. This…

Numerical Analysis · Mathematics 2020-10-19 Martin Smuda , Florian Kummer

In recent years, there has been an increasing interest in using deep learning and neural networks to tackle scientific problems, particularly in solving partial differential equations (PDEs). However, many neural network-based methods, such…

Machine Learning · Computer Science 2025-02-14 Adrian Celaya , Yimo Wang , David Fuentes , Beatrice Riviere