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A posteriori error estimates are an important tool to bound discretization errors in terms of computable quantities avoiding regularity conditions that are often difficult to establish. For non-linear and non-differentiable problems,…

Numerical Analysis · Mathematics 2024-06-12 Sören Bartels , Alex Kaltenbach

In this study we propose a-posteriori error estimation results to approximate the precision loss in quantities of interests computed using reduced order models. To generate the surrogate models we employ Proper Orthogonal Decomposition and…

Numerical Analysis · Mathematics 2024-12-20 R. Stefanescu , A. Sandu

The offline time of the reduced basis method can be very long given a large training set of parameter samples. This usually happens when the system has more than two independent parameters. On the other hand, if the training set includes…

Numerical Analysis · Mathematics 2023-04-04 Sridhar Chellappa , Lihong Feng , Peter Benner

Motivated by problems in contact mechanics, we propose a duality approach for computing approximations and associated a posteriori error bounds to solutions of variational inequalities of the first kind. The proposed approach improves upon…

Numerical Analysis · Mathematics 2014-10-09 Zhenying Zhang , Eduard Bader , Karen Veroy

We derive efficient and reliable goal-oriented error estimations, and devise adaptive mesh procedures for the finite element method that are based on the localization of a posteriori estimates. In our previous work [SIAM J. Sci. Comput.,…

Numerical Analysis · Mathematics 2020-03-23 Bernhard Endtmayer , Ulrich Langer , Thomas Wick

Efficient high order numerical methods for evolving the solution of an ordinary differential equation are widely used. The popular Runge--Kutta methods, linear multi-step methods, and more broadly general linear methods, all have a global…

Numerical Analysis · Mathematics 2020-03-16 Adi Ditkowski , Sigal Gottlieb , Zachary J. Grant

Deep learning has shown successful application in visual recognition and certain artificial intelligence tasks. Deep learning is also considered as a powerful tool with high flexibility to approximate functions. In the present work,…

Machine Learning · Computer Science 2021-12-23 Ayan Chakraborty , Thomas Wick , Xiaoying Zhuang , Timon Rabczuk

We derive a posteriori error estimators for an optimal control problem governed by a convection-reaction-diffusion equation; control constraints are also considered. We consider a family of low-order stabilized finite element methods to…

Numerical Analysis · Mathematics 2017-04-24 Alejandro Allendes , Enrique Otarola , Richard Rankin

Multilevel methods represent a powerful approach in numerical solution of partial differential equations. The multilevel structure can also be used to construct estimates for total and algebraic errors of computed approximations. This paper…

Numerical Analysis · Mathematics 2024-05-13 Petr Vacek , Jan Papež , Zdeněk Strakoš

A reliable model order reduction process for parametric analysis in electromagnetics is detailed. Special emphasis is placed on certifying the accuracy of the reduced-order model. For this purpose, a sharp state error estimator is proposed.…

Numerical Analysis · Mathematics 2023-04-04 Sridhar Chellappa , Lihong Feng , Valentin de la Rubia , Peter Benner

This paper develops and discusses a residual-based a posteriori error estimator for parabolic surface partial differential equations on closed stationary surfaces. The full discretization uses the surface finite element method in space and…

Numerical Analysis · Mathematics 2026-03-31 Balázs Kovács , Michael Lantelme

The accuracy of the reduced-order model (ROM) mainly depends on the selected basis. Therefore, it is essential to compute an appropriate basis with an efficient numerical procedure when applying ROM to nonlinear problems. In this paper, we…

Numerical Analysis · Mathematics 2021-05-05 Jun-Geol Ahn , Hyun-Ik Yang , Jin-Gyun Kim

In this paper, we propose an equation-based parametric Reduced Order Model (ROM), whose accuracy is improved with data-driven terms added into the reduced equations. These additions have the aim of reintroducing contributions that in…

Numerical Analysis · Mathematics 2025-05-26 Anna Ivagnes , Giovanni Stabile , Gianluigi Rozza

Error estimates for the numerical solution of the master equation are presented. Estimates are based on adjoint methods. We find that a good estimate can often be computed without spending computational effort on a dual problem. Estimates…

Numerical Analysis · Mathematics 2016-10-12 Katharina Kormann , Shev MacNamara

This work presents a technique for statistically modeling errors introduced by reduced-order models. The method employs Gaussian-process regression to construct a mapping from a small number of computationally inexpensive `error indicators'…

Numerical Analysis · Computer Science 2015-04-16 Martin Drohmann , Kevin Carlberg

The numerical approximation of convection-dominated problems continues to remain subject of strong interest. Families of stabilization techniques for finite element methods were developed in the past. Adaptive techniques based on a…

Numerical Analysis · Mathematics 2018-03-20 Kristina Schwegler , Marius P. Bruchhäuser , Markus Bause

A new technique of residual-type a posteriori error analysis is developed for the lowest-order Raviart-Thomas mixed finite element discretizations of convection-diffusion-reaction equations in two- or three-dimension. Both centered mixed…

Numerical Analysis · Mathematics 2015-03-26 Shaohong Du , Xiaoping Xie

This article is a review on basic concepts and tools devoted to a posteriori error estimation for problems solved with the Finite Element Method. For the sake of simplicity and clarity, we mostly focus on linear elliptic diffusion problems,…

Numerical Analysis · Mathematics 2021-10-06 Ludovic Chamoin , Frederic Legoll

In a general setting, we study a posteriori estimates used in finite element analysis to measure the error between a solution and its approximation. The latter is not necessarily generated by a finite element method. We show that the error…

Numerical Analysis · Mathematics 2025-07-09 Thomas Führer , Sergio Rojas

We present an abstract framework for a posteriori error estimation for approximations of scalar parabolic evolution equations, based on elliptic reconstruction techniques [10, 9, 3, 5]. In addition to its original application (to derive…

Numerical Analysis · Mathematics 2019-10-30 Mario Ohlberger , Stephan Rave , Felix Schindler