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The proximal Galerkin (PG) method is a finite element method for solving variational problems with inequality constraints. It has several advantages, including constraint-preserving approximations and mesh independence. This paper presents…

Numerical Analysis · Mathematics 2026-02-09 Brendan Keith , Rami Masri , Marius Zeinhofer

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

The proximal Galerkin finite element method is a high-order, low-iteration complexity, nonlinear numerical method that preserves the geometric and algebraic structure of point-wise bound constraints in infinite-dimensional function spaces.…

Numerical Analysis · Mathematics 2024-12-18 Brendan Keith , Thomas M. Surowiec

We introduce the first-order system proximal Galerkin (FOSPG) method, a locally mass-conserving, hybridizable finite element method for solving heterogeneous anisotropic diffusion and obstacle problems. Like other proximal Galerkin methods,…

Numerical Analysis · Mathematics 2025-09-17 Guosheng Fu , Brendan Keith , Rami Masri

We resolve a longstanding open problem in the computational modeling of nonlinear plates by introducing a numerical method that exactly enforces the isometry constraint, namely, that the first fundamental form of the mid-surface coincides…

Numerical Analysis · Mathematics 2026-05-11 Brendan Keith , Frédéric Marazzato

The phase-field method has emerged as a powerful tool for simulating fracture mechanics, yet it presents significant numerical challenges, particularly regarding the enforcement of physical constraints such as irreversibility and…

Numerical Analysis · Mathematics 2026-04-30 Miguel Castillón , Biswajit Khara , Jørgen S. Dokken , Thomas M. Surowiec , Brendan Keith , Yuri Bazilevs

Complementarity problems and variational inequalities arise in a wide variety of areas, including machine learning, planning, game theory, and physical simulation. In all of these areas, to handle large-scale problem instances, we need fast…

Machine Learning · Computer Science 2013-06-21 Geoffrey J. Gordon

We leverage the proximal Galerkin algorithm (Keith and Surowiec, Foundations of Computational Mathematics, 2024, DOI: 10.1007/s10208-024-09681-8), a recently introduced mesh-independent algorithm, to obtain a high-order finite element…

Numerical Analysis · Mathematics 2025-03-11 Ioannis P. A. Papadopoulos

We present a new approach to using neural networks to approximate the solutions of variational equations, based on the adaptive construction of a sequence of finite-dimensional subspaces whose basis functions are realizations of a sequence…

Machine Learning · Computer Science 2021-06-01 Mark Ainsworth , Justin Dong

This paper presents a numerical approach to the stochastic obstacle problem using the stochastic Galerkin (SG) method. Due to the low regularity of the solution, linear finite elements are employed in both the physical and random variable…

Numerical Analysis · Mathematics 2026-04-29 Chenhui Zhu , Fei Wang , Weimin Han

The discontinuous Petrov-Galerkin method is a minimal residual method with broken test spaces and is introduced for a nonlinear model problem in this paper. Its lowest-order version applies to a nonlinear uniformly convex model example and…

Numerical Analysis · Mathematics 2017-10-03 Carsten Carstensen , Philipp Bringmann , Friederike Hellwig , Peter Wriggers

In this study, we examine numerical approximations for 2nd-order linear-nonlinear differential equations with diverse boundary conditions, followed by the residual corrections of the first approximations. We first obtain numerical results…

Numerical Analysis · Mathematics 2023-06-19 Shovan Sourav Datta Pranta , Md. Shafiqul Islam

In this paper, we develop a Discontinuous Galerkin (DG) method for solving H(curl)-elliptic hemivariational inequalities. By selecting an appropriate numerical flux, we construct an Interior Penalty Discontinuous Galerkin (IPDG) scheme. A…

Numerical Analysis · Mathematics 2026-04-21 Xiajie Huang , Fei Wang , Weimin Han , Min Ling

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

The purpose of this research work is to employ the Optimal Auxiliary Function Method (OAFM) for obtaining numerical approximations of time-dependent nonlinear partial differential equations (PDEs) that arise in many disciplines of science…

Numerical Analysis · Mathematics 2023-06-13 Nilormy Gupta Trisha , Md. Shafiqul Islam

This paper introduces a novel staggered discontinuous Galerkin (SDG) method tailored for solving elliptic equations on polytopal meshes. Our approach utilizes a primal-dual grid framework to ensure local conservation of fluxes,…

Numerical Analysis · Mathematics 2024-11-01 L. Chen , X. Huang , E. Park , R. Wang

We introduce a family of discontinuous Galerkin methods to approximate the eigenvalues and eigenfunctions of a Stokes-Brinkman type of problem based in the interior penalty strategy. Under the standard assumptions on the meshes and a…

Numerical Analysis · Mathematics 2025-07-17 Felipe Lepe , Gonzalo Rivera , Jesus Vellojin

A new primal-dual weak Galerkin (PD-WG) finite element method was developed and analyzed in this article for first-order linear convection equations in non-divergence form. The PD-WG method results in a symmetric discrete system involving…

Numerical Analysis · Mathematics 2019-11-20 Dan Li , Chunmei Wang , Junping Wang

In this work, we propose and develop an arbitrary-order adaptive discontinuous Petrov-Galerkin (DPG) method for the nonlinear Grad-Shafranov equation. An ultraweak formulation of the DPG scheme for the equation is given based on a minimal…

Numerical Analysis · Mathematics 2020-07-14 Zhichao Peng , Qi Tang , Xian-Zhu Tang

In this paper, we present the proximal-proximal-gradient method (PPG), a novel optimization method that is simple to implement and simple to parallelize. PPG generalizes the proximal-gradient method and ADMM and is applicable to…

Optimization and Control · Mathematics 2017-10-19 Ernest K. Ryu , Wotao Yin
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