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Higher-order numerical methods are used to find accurate numerical solutions to hyperbolic partial differential equations and equations of transport type. Limiting is required to either converge to the correct type of solution or to adhere…

Numerical Analysis · Mathematics 2024-07-10 James Woodfield

This work presents a novel stabilization strategy for the Galerkin formulation of the incompressible Navier-Stokes equations, developed to achieve high accuracy while ensuring convergence and compatibility with high-order elements on…

Numerical Analysis · Mathematics 2025-09-05 Antonio Blanco-Casares , Vishal Kumar , Daniel Mira , Oriol Lehmkuhl

This paper proposes a novel higher-order multi-scale (HOMS) computational method, which is highly targeted for efficient, high-accuracy and low-computational-cost simulation of hygro-thermo-mechanical (H-T-M) coupling problems in…

Numerical Analysis · Mathematics 2025-12-11 Hao Dong , Yifei Ding , Jiale Linghu , Yufeng Nie , Yaochuang Han

At present, deep learning based methods are being employed to resolve the computational challenges of high-dimensional partial differential equations (PDEs). But the computation of the high order derivatives of neural networks is costly,…

Numerical Analysis · Mathematics 2021-03-17 Quanhui Zhu , Jiang Yang

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 an extension to high-order of a first-order Lagrange-projection like method for the approximation of the Euler equations introduced in Coquel {\it et al.} (Math. Comput., 79 (2010), pp.~1493--1533). The method is based on a…

Numerical Analysis · Mathematics 2016-02-05 Florent Renac

The solution approximation for partial differential equations (PDEs) can be substantially improved using smooth basis functions. The recently introduced mollified basis functions are constructed through mollification, or convolution, of…

Numerical Analysis · Mathematics 2024-07-01 Dewangga Alfarisy , Lavi Zuhal , Michael Ortiz , Fehmi Cirak , Eky Febrianto

In this paper, we propose new geometrically unfitted space-time Finite Element methods for partial differential equations posed on moving domains of higher order accuracy in space and time. As a model problem, the convection-diffusion…

Numerical Analysis · Mathematics 2023-05-09 Fabian Heimann , Christoph Lehrenfeld , Janosch Preuß

We present and compare third- as well as fifth-order accurate finite difference schemes for the numerical solution of the compressible ideal MHD equations in multiple spatial dimensions. The selected methods lean on four different…

High Energy Astrophysical Phenomena · Physics 2015-05-18 A. Mignone , P. Tzeferacos , G. Bodo

We introduce an $hp$-version discontinuous Galerkin finite element method (DGFEM) for the linear Boltzmann transport problem. A key feature of this new method is that, while offering arbitrary order convergence rates, it may be implemented…

Numerical Analysis · Mathematics 2024-07-18 Paul Houston , Matthew E. Hubbard , Thomas J. Radley , Oliver J. Sutton , Richard S. J. Widdowson

This work introduces a novel discontinuity-tracking framework for resolving discontinuous solutions of conservation laws with high-order numerical discretizations that support inter-element solution discontinuities, such as discontinuous…

Numerical Analysis · Mathematics 2018-05-09 Matthew J. Zahr , Per-Olof Persson

We propose a graph-based sweep algorithm for solving the steady state, mono-energetic discrete ordinates on meshes of high-order curved mesh elements. Our spatial discretization consists of arbitrarily high-order discontinuous Galerkin…

Numerical Analysis · Mathematics 2019-01-11 T. S. Haut , P. G. Maginot , V. Z. Tomov , B. S. Southworth , T. A. Brunner , T. S. Bailey

High-dimensional PDEs have been a longstanding computational challenge. We propose to solve high-dimensional PDEs by approximating the solution with a deep neural network which is trained to satisfy the differential operator, initial…

Mathematical Finance · Quantitative Finance 2018-10-17 Justin Sirignano , Konstantinos Spiliopoulos

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

In this paper we propose the first better than second order accurate method in space and time for the numerical solution of the resistive relativistic magnetohydrodynamics (RRMHD) equations on unstructured meshes in multiple space…

General Relativity and Quantum Cosmology · Physics 2015-05-13 Michael Dumbser , Olindo Zanotti

In this work, we propose and investigate stable high-order collocation-type discretisations of the discontinuous Galerkin method on equidistant and scattered collocation points. We do so by incorporating the concept of discrete least…

Numerical Analysis · Mathematics 2021-02-24 Jan Glaubitz , Philipp Oeffner

An adaptive direct collocation method is developed for solving optimal control problems constrained by parabolic partial differential equations. The partial differential equation is first reformulated in a variational setting, where the…

Optimization and Control · Mathematics 2026-03-18 Alexander M. Davies , Sara Pollock , Miriam E. Dennis , Anil V. Rao

This paper presents a high-accuracy higher-order multiscale method for solving multi-continuum problems in in highly heterogeneous media. First, microscopic unit cell functions are defined, leading to the derivation of macroscopic…

Numerical Analysis · Mathematics 2026-04-08 Hao Dong , Jiayuan Peng , Jian Huang

We develop a convergence theory for non-monotone approximation schemes for fully nonlinear parabolic partial differential equations. Modern computational methods such as kernel-based collocation, spectral methods, physics-informed neural…

Numerical Analysis · Mathematics 2026-05-08 Yumiharu Nakano

We present novel model reduction methods for rapid solution of parametrized nonlinear partial differential equations (PDEs) in real-time or many-query contexts. Our approach combines reduced basis (RB) space for rapidly convergent…

Numerical Analysis · Mathematics 2024-10-04 Ngoc Cuong Nguyen
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