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In this paper, we develop an adaptive Generalized Multiscale Discontinuous Galerkin Method (GMs-DGM) for a class of high-contrast flow problems, and derive a-priori and a-posteriori error estimates for the method. Based on the a-posteriori…

Numerical Analysis · Mathematics 2014-09-12 Eric T. Chung , Yalchin Efendiev , Wing Tat Leung

This work proposes a scheme for significantly reducing the computational complexity of discretized problems involving the non-smooth forward propagation of uncertainty by combining the adaptive hierarchical sparse grid stochastic…

Computational Physics · Physics 2015-09-07 Robert L. Gates , Maximilian R. Bittens

We introduce a generalized finite difference method for solving a large range of fully nonlinear elliptic partial differential equations in three dimensions. Methods are based on Cartesian grids, augmented by additional points carefully…

Numerical Analysis · Mathematics 2021-03-19 Brittany Froese Hamfeldt , Jacob Lesniewski

The purpose of the research is to find the numerical solutions to the system of time dependent nonlinear parabolic partial differential equations (PDEs) utilizing the Modified Galerkin Weighted Residual Method (MGWRM) with the help of…

Numerical Analysis · Mathematics 2023-07-11 Hazrat Ali , Nilormy Gupta Trisha , Md. Shafiqul Islam

In this paper we investigate an adaptive discretization strategy for ill-posed linear prob- lems combined with a regularization from a class of semiiterative methods. We show that such a discretization approach in combination with a…

Numerical Analysis · Mathematics 2014-07-22 Wolfgang Erb , Evgeniya V. Semenova

The numerical solution of time-dependent radiative transfer problems is challenging, both, due to the high dimension as well as the anisotropic structure of the underlying integro-partial differential equation. In this paper we propose a…

Numerical Analysis · Mathematics 2015-12-04 Herbert Egger , Matthias Schlottbom

In this work, approximate solutions to the nonlinear Klein-Gordon equation are constructed by means of the Galerkin method. Specifically, it is shown how the dynamics of a real scalar field in $1+1$ dimensions subjected to Dirichlet…

Mathematical Physics · Physics 2025-09-04 Annibal D. de Figueiredo Neto , Caio C. Holanda Ribeiro , Luana L. Silva Ribeiro

Consider the minimization of a nonconvex differentiable function over a polyhedron. A popular primal-dual first-order method for this problem is to perform a gradient projection iteration for the augmented Lagrangian function and then…

Optimization and Control · Mathematics 2020-08-05 Jiawei Zhang , Zhi-Quan Luo

In this paper, a fully discrete local discontinuous Galerkin (LDG) finite element method is considered for solving the time-fractional KdV-Burgers-Kuramoto (KBK) equation. The scheme is based on a finite difference method in time and local…

Numerical Analysis · Mathematics 2015-03-19 Leilei Wei , Yinnian He

A framework for performing dynamic mesh adaptation with the discontinuous Galerkin method (DGM) is presented. Adaptations include modifications of the local mesh step size (h-adaptation) and the local degree of the approximating polynomials…

Computational Physics · Physics 2013-01-29 Sascha M. Schnepp , Thomas Weiland

We extend the semi-Lagrangian discontinuous Galerkin (SLDG) method of Einkemmer to velocity grids with adaptive mesh refinement (AMR) and to three-dimensional velocity space. The original SLDG formulation assumes uniform cell widths, which…

Numerical Analysis · Mathematics 2026-03-23 Mark F. Adams

We propose a neural-enhanced weak Galerkin (WG) finite element method for second-order elliptic problems with low-regularity solutions. The method augments the classical WG approximation space with neural network functions constructed via a…

Numerical Analysis · Mathematics 2026-04-08 Chunmei Wang

The radiative transfer equation models the interaction of radiation with scattering and absorbing media and has important applications in various fields in science and engineering. It is an integro-differential equation involving time,…

Numerical Analysis · Mathematics 2020-04-20 Min Zhang , Juan Cheng , Weizhang Huang , Jianxian Qiu

This paper presents a framework for the analysis of discretization methods based on the decomposition into local and global problems. We apply the framework to provide a comprehensive error analysis for the embedded Trefftz discontinuous…

Numerical Analysis · Mathematics 2025-12-02 Philip L. Lederer , Christoph Lehrenfeld , Paul Stocker , Igor Voulis

A method is presented for the numerical solution of optimal boundary control problems governed by parabolic partial differential equations. The continuous space-time optimal control problem is transcribed into a sparse nonlinear programming…

Optimization and Control · Mathematics 2026-03-17 Alexander M. Davies , Sara Pollock , Miriam E. Dennis , Anil V. Rao

Discontinuous Galerkin (DG) discretizations with exact representation of the geometry and local polynomial degree adaptivity are revisited. Hybridization techniques are employed to reduce the computational cost of DG approximations and…

Numerical Analysis · Mathematics 2019-08-20 Matteo Giacomini , Ruben Sevilla

The elucidation of many physical problems in science and engineering is subject to the accurate numerical modelling of complex wave propagation phenomena. Over the last decades, high-order numerical approximation for partial differential…

Numerical Analysis · Mathematics 2025-10-20 Mathias Anselmann , Markus Bause

An efficient $hp$-multigrid scheme is presented for local discontinuous Galerkin (LDG) discretizations of elliptic problems, formulated around the idea of separately coarsening the underlying discrete gradient and divergence operators. We…

Numerical Analysis · Mathematics 2019-03-14 Daniel Fortunato , Chris H. Rycroft , Robert Saye

We study the numerical approximation of advection-diffusion equations with highly oscillatory coefficients and possibly dominant advection terms by means of the Multiscale Finite Element Method. The latter method is a now classical, finite…

Numerical Analysis · Mathematics 2024-11-12 Rutger A. Biezemans , Claude Le Bris , Frédéric Legoll , Alexei Lozinski

Deep neural networks are powerful tools for approximating functions, and they are applied to successfully solve various problems in many fields. In this paper, we propose a neural network-based numerical method to solve partial differential…

Numerical Analysis · Mathematics 2022-02-01 Yong Shang , Fei Wang , Jingbo Sun
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