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This work focuses on the conservation of quantities such as Hamiltonians, mass, and momentum when solution fields of partial differential equations are approximated with nonlinear parametrizations such as deep networks. The proposed…

Numerical Analysis · Mathematics 2023-10-12 Paul Schwerdtner , Philipp Schulze , Jules Berman , Benjamin Peherstorfer

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

A conforming discontinuous Galerkin finite element method is introduced for solving the biharmonic equation. This method, by its name, uses discontinuous approximations and keeps simple formulation of the conforming finite element method at…

Numerical Analysis · Mathematics 2019-07-26 Xiu Ye , Shangyou Zhang

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

We use a concept of weak asymptotic solution for homogeneous as well as non-homogeneous fractional advection dispersion type equations. Using Legendre scaling functions as basis, a numerical method based on Galerkin approximation is…

Numerical Analysis · Mathematics 2015-05-01 Harendra Singh , Manas Ranjan Sahoo , Om Prakash Singh

The conforming finite element Galerkin method is applied to discretise in the spatial direction for a class of strongly nonlinear parabolic problems. Using elliptic projection of the associated linearised stationary problem with Gronwall…

Numerical Analysis · Mathematics 2021-08-04 Ambit Kumar Pany , Morrakot Khebchareon , Amiya K. Pani

We present a method for linear stability analysis of systems with parametric uncertainty formulated in the stochastic Galerkin framework. Specifically, we assume that for a model partial differential equation, the parameter is given in the…

Numerical Analysis · Mathematics 2026-01-14 Bedřich Sousedík , Kookjin Lee

A numerical method is proposed to compute a low-rank Galerkin approximation to the solution of a parametric or stochastic equation in a non-intrusive fashion. The considered nonlinear problems are associated with the minimization of a…

Numerical Analysis · Mathematics 2017-05-11 Loïc Giraldi , Dishi Liu , Hermann G. Matthies , Anthony Nouy

We present a model reduction approach for the real-time solution of time-dependent nonlinear partial differential equations (PDEs) with parametric dependencies. The approach integrates several ingredients to develop efficient and accurate…

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

In many applications of practical interest, solutions of partial differential equation models arise as critical points of an underlying (energy) functional. If such solutions are saddle points, rather than being maxima or minima, then the…

Numerical Analysis · Mathematics 2020-09-07 Pascal Heid , Thomas P. Wihler

We propose a limiting procedure to preserve invariant domains with time explicit discrete high-order spectral discontinuous approximate solutions to hyperbolic systems of conservation laws. Provided the scheme is discretely conservative and…

Numerical Analysis · Mathematics 2022-03-15 Florent Renac , Valentin Carlier

We consider a linear elliptic partial differential equation (PDE) with a generic uniformly bounded parametric coefficient. The solution to this PDE problem is approximated in the framework of stochastic Galerkin finite element methods. We…

Numerical Analysis · Mathematics 2020-06-05 Alex Bespalov , Feng Xu

Numerical methods for random parametric PDEs can greatly benefit from adaptive refinement schemes, in particular when functional approximations are computed as in stochastic Galerkin and stochastic collocations methods. This work is…

Numerical Analysis · Mathematics 2023-05-03 Martin Eigel , Nando Farchmin , Sebastian Heidenreich , Philipp Trunschke

We study the numerical approximation by space-time finite element methods of a multi-physics system coupling hyperbolic elastodynamics with parabolic transport and modeling poro- and thermoelasticity. The equations are rewritten as a…

Numerical Analysis · Mathematics 2023-02-14 Markus Bause , Mathias Anselmann , Uwe Köcher , Florin A. Radu

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

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

In this paper, a practicable simulation-free model order reduction method by nonlinear moment matching is developed. Based on the steady-state interpretation of linear moment matching, we comprehensively explain the extension of this…

Systems and Control · Electrical Eng. & Systems 2024-12-20 Maria Cruz Varona , Raphael Gebhart , Julian Suk , Boris Lohmann

This paper concerns with numerical approximations of solutions of second order fully nonlinear partial differential equations (PDEs). A new notion of weak solutions, called moment solutions, is introduced for second order fully nonlinear…

Numerical Analysis · Mathematics 2007-08-14 Xiaobing Feng , Michael Neilan

We implement a high-order numerical scheme for the entropy-based moment closure, the so-called M$_N$ model, for linear kinetic equations in slab geometry. A discontinuous Galerkin (DG) scheme in space along with a strong-stability…

Numerical Analysis · Mathematics 2015-06-23 Graham Alldredge , Florian Schneider

Numerically solving high-dimensional random parametric PDEs poses a challenging computational problem. It is well-known that numerical methods can greatly benefit from adaptive refinement algorithms, in particular when functional…

Numerical Analysis · Mathematics 2024-07-29 Martin Eigel , Nando Hegemann