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Related papers: On the best accuracy using the $h$-adaptive finite…

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Adaptive mesh refinement (AMR) is indispensable for efficient finite element analyses. However, its performance depends not only on the refinement itself but also on strategy to mark elements for refinement and the way it is tuned. This…

Computational Engineering, Finance, and Science · Computer Science 2026-05-08 Oliver Wege , Kaan Atak , Marek Behr , Norbert Hosters

We present an improved method for topology optimization with both adaptive mesh refinement and derefinement. Since the total volume fraction in topology optimization is usually modest, after a few initial iterations the domain of…

Numerical Analysis · Mathematics 2010-09-28 Shun Wang , Eric de Sturler , Glaucio H. Paulino

In this paper we present an adaptive discretization technique for solving elliptic partial differential equations via a collocation radial basis function partition of unity method. In particular, we propose a new adaptive scheme based on…

Numerical Analysis · Mathematics 2018-11-13 R. Cavoretto , A. De Rossi

We propose a general algorithm for non-conforming adaptive mesh refinement (AMR) of unstructured meshes in high-order finite element codes. Our focus is on h-refinement with a fixed polynomial order. The algorithm handles triangular,…

Numerical Analysis · Computer Science 2019-05-13 Jakub Červený , Veselin Dobrev , Tzanio Kolev

This paper proves error estimates for $H^2$ conforming finite elements for equations which model the flow of surfaces by different powers of the mean curvature (this includes mean curvature flow). for an adapted scheme originally proposed…

Numerical Analysis · Mathematics 2021-03-26 Axel Kröner , Heiko Kröner

We consider a numerical scheme for the approximation of a system that couples the evolution of a two--dimensional hypersurface to a reaction--diffusion equation on the surface. The surfaces are assumed to be graphs and evolve according to…

Numerical Analysis · Mathematics 2021-04-13 Klaus Deckelnick , Vanessa Styles

In dynamical system theory, the process of obtaining a reduced-order approximation of the high-order model is called model order reduction. The closeness of the reduced-order model to the original model is generally gauged by using system…

Systems and Control · Electrical Eng. & Systems 2023-03-07 Umair Zulfiqar , Xin Dua , Qiuyan Song , Muwahida Liaquat , Victor Sreeram

Approximate dynamic programming has been used successfully in a large variety of domains, but it relies on a small set of provided approximation features to calculate solutions reliably. Large and rich sets of features can cause existing…

Artificial Intelligence · Computer Science 2015-03-17 Marek Petrik , Gavin Taylor , Ron Parr , Shlomo Zilberstein

This article investigates residual a posteriori error estimates and adaptive mesh refinements for time-dependent boundary element methods for the wave equation. We obtain reliable estimates for Dirichlet and acoustic boundary conditions…

Numerical Analysis · Mathematics 2020-10-01 Heiko Gimperlein , Ceyhun Oezdemir , David Stark , Ernst P. Stephan

In this paper we study adaptive discretization of the iteratively regularized Gauss-Newton method IRGNM with an a posteriori (discrepancy principle) choice of the regularization parameter in each Newton step and of the stopping index. We…

Numerical Analysis · Mathematics 2015-06-17 Barbara Kaltenbacher , Alana Kirchner , Slobodan Veljovi\' c

In this work, we investigate the regularized solutions and their finite element solutions to the inverse source problems governed by partial differential equations, and establish the stochastic convergence and optimal finite element…

Numerical Analysis · Mathematics 2021-10-25 Zhiming Chen , Wenlong Zhang , Jun Zou

We show how to construct the deep neural network (DNN) expert to predict quasi-optimal $hp$-refinements for a given computational problem. The main idea is to train the DNN expert during executing the self-adaptive $hp$-finite element…

Numerical Analysis · Mathematics 2022-09-14 Tomasz Sluzalec , Rafal Grzeszczuk , Sergio Rojas , Witold Dzwinel , Maciej Paszynski

Reinforcement Learning algorithms that learn from human feedback (RLHF) need to be efficient in terms of statistical complexity, computational complexity, and query complexity. In this work, we consider the RLHF setting where the feedback…

Machine Learning · Computer Science 2024-03-14 Runzhe Wu , Wen Sun

This work introduces an Adaptive Mesh Refinement (AMR) strategy for the topology optimization of structures made of discrete geometric components using the geometry projection method. Practical structures made of geometric shapes such as…

Optimization and Control · Mathematics 2020-04-22 Shanglong Zhang , Arun L. Gain , Julian A. Norato

In the present work we introduce a complete set of algorithms to efficiently perform adaptive refinement and coarsening by exploiting truncated hierarchical B-splines (THB-splines) defined on suitably graded isogeometric meshes, that are…

Numerical Analysis · Mathematics 2019-03-27 Massimo Carraturo , Carlotta Giannelli , Alessandro Reali , Rafael Vázquez

Adaptive Mesh Refinement (AMR) enhances the Finite Element Method, an important technique for simulating complex problems in engineering, by dynamically refining mesh regions, enabling a favorable trade-off between computational speed and…

Multiagent Systems · Computer Science 2023-10-11 Niklas Freymuth , Philipp Dahlinger , Tobias Würth , Simon Reisch , Luise Kärger , Gerhard Neumann

Meshing of geometric domains having curved boundaries by affine simplices produces a polytopial approximation of those domains. The resulting error in the representation of the domain limits the accuracy of finite element methods based on…

Numerical Analysis · Mathematics 2018-02-09 James Cheung , Mauro Perego , Pavel Bochev , Max Gunzburger

Mesh adaptivity is a useful tool for efficient solution to partial differential equations in very complex geometries. In the present paper we discuss the use of polygonal mesh refinement in order to tackle two common issues: first,…

Numerical Analysis · Mathematics 2021-12-21 Stefano Berrone , Alessandro D'Auria

The state-of-the art proof of a global inf-sup condition on mixed finite element schemes does not allow for an analysis of truly indefinite, second-order linear elliptic PDEs. This paper, therefore, first analyses a nonconforming finite…

Numerical Analysis · Mathematics 2014-01-21 Carsten Carstensen , Asha K. Dond , Neela Nataraj , Amiya K. Pani

We present tools for the analysis of Follow-The-Regularized-Leader (FTRL), Dual Averaging, and Mirror Descent algorithms when the regularizer (equivalently, prox-function or learning rate schedule) is chosen adaptively based on the data.…

Machine Learning · Computer Science 2015-11-10 H. Brendan McMahan
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