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In this paper we develop two goal-oriented adaptive strategies for a posteriori error estimation within the generalized multiscale finite element framework. In this methodology, one seeks to determine the number of multiscale basis…

Numerical Analysis · Mathematics 2015-09-21 Eric T. Chung , Wing Tat Leung , Sara Pollock

Given a partial differential equation (PDE), goal-oriented error estimation allows us to understand how errors in a diagnostic quantity of interest (QoI), or goal, occur and accumulate in a numerical approximation, for example using the…

Machine Learning · Computer Science 2022-07-25 Joseph G. Wallwork , Jingyi Lu , Mingrui Zhang , Matthew D. Piggott

We consider an adaptive finite element method with arbitrary but fixed polynomial degree $p \ge 1$, where adaptivity is driven by an edge-based residual error estimator. Based on the modified maximum criterion from [Diening et al, Found.…

Numerical Analysis · Mathematics 2021-01-29 Michael Innerberger , Dirk Praetorius

The efficient and reliable approximation of convection-dominated problems continues to remain a challenging task. To overcome the difficulties associated with the discretization of convection-dominated equations, stabilization techniques…

Numerical Analysis · Mathematics 2022-12-15 Marius Paul Bruchhäuser , Kristina Schwegler , Markus Bause

In this work, we further develop multigoal-oriented a posteriori error estimation with two objectives in mind. First, we formulate goal-oriented mesh adaptivity for multiple functionals of interest for nonlinear problems in which both the…

Numerical Analysis · Mathematics 2018-04-05 B. Endtmayer , U. Langer , T. Wick

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

This paper is concerned with goal-oriented a posteriori error estimation for nonlinear functionals in the context of nonlinear variational problems solved with continuous Galerkin finite element discretizations. A two-level, or discrete,…

Computational Engineering, Finance, and Science · Computer Science 2025-01-10 Brian N. Granzow , D. Thomas Seidl , Stephen D. Bond

In this work, we present an anisotropic multi-goal error control based on the Dual Weighted Residual (DWR) method for time-dependent convection-diffusion-reaction (CDR) equations. This multi-goal oriented approach allows for an accurate and…

This article presents a general and novel approach to the automation of goal-oriented error control in the solution of nonlinear stationary finite element variational problems. The approach is based on automated linearization to obtain the…

Numerical Analysis · Mathematics 2012-05-01 Marie E. Rognes , Anders Logg

We consider goal-oriented adaptive space-time finite-element discretizations of the regularized parabolic p-Laplace problem on completely unstructured simplicial space-time meshes. The adaptivity is driven by the dual-weighted residual…

Numerical Analysis · Mathematics 2023-06-13 B. Endtmayer , U. Langer , A. Schafelner

We present an anisotropic goal-oriented error estimator based on the Dual Weighted Residual (DWR) method for time-dependent convection-dominated problems. Using elementwise p-anisotropic finite element spaces, the estimator is elementwise…

Numerical Analysis · Mathematics 2026-02-17 Nils Margenberg , Marius Paul Bruchhäuser , Bernhard Endtmayer

We present an anisotropic goal-oriented error estimator based on the Dual Weighted Residual (DWR) method for time-dependent convection-diffusion-reaction (CDR) equations. Using anisotropic interpolation operators the estimator is…

Numerical Analysis · Mathematics 2025-04-22 M. Bause , M. Bruchhäuser , B. Endtmayer , N. Margenberg , I. Toulopoulos , T. Wick

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 consider the general problem of learning a predictor that satisfies multiple objectives of interest simultaneously, a broad framework that captures a range of specific learning goals including calibration, regret, and multiaccuracy. We…

Machine Learning · Computer Science 2026-02-17 Jivat Neet Kaur , Isaac Gibbs , Michael I. Jordan

In this work, we develop adaptive schemes using goal-oriented error control for a highly nonlinear flow temperature model with temperature dependent density. The dual-weighted residual method for computing error indicators to steer mesh…

Numerical Analysis · Mathematics 2024-04-03 Sven Beuchler , Ayhan Demircan , Bernhard Endtmayer , Uwe Morgner , Thomas Wick

We propose optimal dimensionality reduction techniques for the solution of goal-oriented linear-Gaussian inverse problems, where the quantity of interest (QoI) is a function of the inversion parameters. These approximations are suitable for…

Methodology · Statistics 2017-03-16 Alessio Spantini , Tiangang Cui , Karen Willcox , Luis Tenorio , Youssef Marzouk

During the last decade there has been an increase on the use of goal-oriented error estimates which help to quantify and control the local error on a quantity of interest (QoI) that might result relevant for design purposes (e.g. the mean…

We discuss goal-oriented adaptivity in the frame of conforming finite element methods and plain convergence of the related a posteriori error estimator for different general marking strategies. We present an abstract analysis for two…

Numerical Analysis · Mathematics 2024-07-30 Valentin Helml , Michael Innerberger , Dirk Praetorius

We present a hybrid a-priori/a-posteriori goal oriented error estimator for a combination of dynamic iteration-based solution of ordinary differential equations discretized by finite elements. Our novel error estimator combines estimates…

Numerical Analysis · Mathematics 2026-02-13 Erik Weyl , Andreas Bartel , Manuel Schaller

In this work, we apply multi-goal oriented error estimation to the finite element method. In particular, we use the dual weighted residual method and apply it to a model problem. This model problem consist of locally different coercive…

Numerical Analysis · Mathematics 2024-05-30 Bernhard Endtmayer
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