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Offline computation is an essential component in most multiscale model reduction techniques. However, there are multiscale problems in which offline procedure is insufficient to give accurate representations of solutions, due to the fact…

Numerical Analysis · Mathematics 2015-04-20 Eric T. Chung , Yalchin Efendiev , Wing Tat Leung

We propose a goal-oriented mesh-adaptive algorithm for a finite element method stabilized via residual minimization on dual discontinuous-Galerkin norms. By solving a saddle-point problem, this residual minimization delivers a stable…

Numerical Analysis · Mathematics 2021-02-24 Sergio Rojas , David Pardo , Pouria Behnoudfar , Victor M. Calo

In this work, a novel method with an adaptive functional basis for reduced order models (ROM) based on proper orthogonal decomposition (POD) is introduced. The method is intended to be applied in particular to hydrocarbon reservoir…

Numerical Analysis · Mathematics 2021-06-23 Dmitry Voloskov , Dimitri Pissarenko

The generalized polynomial chaos method is applied to the Buckley-Leverett equation. We consider a spatially homogeneous domain modeled as a random field. The problem is projected onto stochastic basis functions which yields an extended…

Numerical Analysis · Mathematics 2016-08-24 Per Pettersson , Hamdi A. Tchelepi

We propose a projection-based model order reduction method for the solution of parameter-dependent dynamical systems. The proposed method relies on the construction of time-dependent reduced spaces generated from evaluations of the solution…

Numerical Analysis · Mathematics 2019-09-11 Marie Billaud-Friess , Anthony Nouy

In this research, we propose an online basis enrichment strategy within the framework of a recently developed constraint energy minimizing generalized multiscale discontinuous Galerkin method (CEM-GMsDGM). Combining the technique of…

Numerical Analysis · Mathematics 2021-03-05 Sai-Mang Pun , Siu Wun Cheung

We design and analyze a new adaptive stabilized finite element method. We construct a discrete approximation of the solution in a continuous trial space by minimizing the residual measured in a dual norm of a discontinuous test space that…

Numerical Analysis · Mathematics 2020-04-22 Victor M. Calo , Alexandre Ern , Ignacio Muga , Sergio Rojas

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

Multiscale mathematical models have shown great promise in computational brain electrophysiology but are still hindered by high computational costs due to fast dynamics and complex brain geometries, requiring very fine spatio-temporal…

Numerical Analysis · Mathematics 2025-05-01 Caterina Beatrice Leimer Saglio , Stefano Pagani , Paola F. Antonietti

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

Model order reduction through the POD-Galerkin method can lead to dramatic gains in terms of computational efficiency in solving physical problems. However, the applicability of the method to non linear high-dimensional dynamical systems…

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 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

The weak Galerkin (WG) finite element method is an effective and flexible general numerical technique for solving partial differential equations. It is a natural extension of the classic conforming finite element method for discontinuous…

Numerical Analysis · Mathematics 2020-04-29 Xiu Ye , Shangyou Zhang

The Discontinuous Galerkin time-domain method is well suited for adaptive algorithms to solve the time-domain Maxwell's equations and depends on robust and economically computable drivers. Adaptive algorithms utilize local indicators to…

Computational Physics · Physics 2025-05-02 Apurva Tiwari , Avijit Chatterjee

The recently developed generalized Fourier-Galerkin method is complemented by a numerical continuation with respect to the kinetic energy, which extends the framework to the investigation of modal interactions resulting in folds of the…

Numerical Analysis · Mathematics 2021-01-07 Malte Krack , Lars Panning-von Scheidt , Jörg Wallaschek

In this paper the author reviews a version of the global Galerkin that was developed and applied in a series of earlier publications. The method is based on divergence-free basis functions satisfying all the linear and homogeneous boundary…

Fluid Dynamics · Physics 2018-04-13 Alexander Gelfgat

The numerical solution of strain gradient-dependent continuum problems has been dogged by continuity demands on the basis functions. For most commonly accepted models, solutions using the finite element method demand $C^{1}$ continuity of…

Numerical Analysis · Mathematics 2025-10-20 G. N. Wells , K. Garikipati , L. Molari

In this paper, we consider the constrained energy minimizing generalized multiscale finite element method (CEM-GMsFEM) with discontinuous Galerkin (DG) coupling for the linear elasticity equations in highly heterogeneous and high contrast…

Numerical Analysis · Mathematics 2022-11-09 Zhongqian Wang , Shubin Fu , Eric Chung

We use the ideas of goal-oriented error estimation and adaptivity to design and implement an efficient adaptive algorithm for approximating linear quantities of interest derived from solutions to elliptic partial differential equations…

Numerical Analysis · Mathematics 2019-03-21 Alex Bespalov , Dirk Praetorius , Leonardo Rocchi , Michele Ruggeri
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