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Related papers: Extending h adaptivity with refinement patterns

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We present an administration technique for the bookkeeping of adaptive mesh refinement on (hyper-)rectangular meshes. Our technique is a unified approach for h-refinement on 1-, 2- and 3D domains, which is easy to use and avoids traversing…

Numerical Analysis · Mathematics 2022-02-08 Niklas Kolbe , Nikolaos Sfakianakis

The convergence analysis for least-squares finite element methods led to various adaptive mesh-refinement strategies: Collective marking algorithms driven by the built-in a posteriori error estimator or an alternative explicit…

Numerical Analysis · Mathematics 2023-09-18 Philipp Bringmann

Fitted finite element methods are constructed for a singularly perturbed convection-diffusion problem in two space dimensions. Exponential splines as basis functions are combined with Shishkin meshes to obtain a stable parameter-uniform…

Numerical Analysis · Mathematics 2023-10-03 Alan F. Hegarty , Eugene O'Riordan

This article is concerned with the numerical solution of convex variational problems. More precisely, we develop an iterative minimisation technique which allows for the successive enrichment of an underlying discrete approximation space in…

Numerical Analysis · Mathematics 2015-07-07 Paul Houston , Thomas P. Wihler

This paper presents an enhanced direct-method-based approach for the real-time solution of optimal control problems to handle path constraints, such as obstacles. The principal contributions of this work are twofold: first, the existing…

Systems and Control · Electrical Eng. & Systems 2024-03-05 Juho Bae , Ji Hoon Bai , Byung-Yoon Lee , Jun-Yong Lee

The use of adaptive mesh refinement (AMR) techniques is crucial for accurate and efficient simulation of higher dimensional spacetimes. In this work we develop an adaptive algorithm tailored to the integration of finite difference…

General Relativity and Quantum Cosmology · Physics 2009-11-10 Frans Pretorius , Luis Lehner

In this paper we develop a simple finite element method for simulation of embedded layers of high permeability in a matrix of lower permeability using a basic model of Darcy flow in embedded cracks. The cracks are allowed to cut through the…

Numerical Analysis · Mathematics 2017-09-05 Erik Burman , Peter Hansbo , Mats G. Larson

Refinement is a powerful mechanism for mastering the complexities that arise when formally modelling systems. Refinement also brings with it additional proof obligations -- requiring a developer to discover properties relating to their…

Logic in Computer Science · Computer Science 2011-06-22 Maria Teresa Llano , Andrew Ireland , Alison Pease

As modeling and visualization applications proliferate, there arises a need to simplify large polygonal models at interactive rates. Unfortunately existing polygon mesh simplification algorithms are not well suited for this task because…

Graphics · Computer Science 2025-07-22 Dmitry Brodsky , Benjamin Watson

We introduce refinement in the function-behaviour-structure framework for design, as described by John Gero, in order to deal with complexity. We do this by connecting the frameworks for the design of two models, one the refinement of the…

Software Engineering · Computer Science 2015-04-03 Bob Diertens

This paper addresses the problem of evaluating the quality of finite element meshes for the purpose of structural mechanic simulations. It proposes the application of a machine learning model trained on data collected from expert…

Machine Learning · Computer Science 2021-07-23 Joachim Sprave , Christian Drescher

The aim of this paper is to provide new perspectives on the relative finite elements accuracy. Starting from a geometrical interpretation of the error estimate which can be deduced from Bramble-Hilbert lemma, we derive a probability law…

Numerical Analysis · Mathematics 2019-01-14 Joel Chaskalovic , Franck Assous

This paper studies chance-constrained stochastic optimization problems with finite support. It presents an iterative method that solves reduced-size chance-constrained models obtained by partitioning the scenario set. Each reduced problem…

Optimization and Control · Mathematics 2024-11-26 Marius Roland , Alexandre Forel , Thibaut Vidal

Refinement types are a well-studied manner of performing in-depth analysis on functional programs. The dependency pair method is a very powerful method used to prove termination of rewrite systems; however its extension to higher order…

Logic in Computer Science · Computer Science 2011-01-25 Cody Roux

When a numerical simulation has to handle a physics problem with a wide range of time-dependent length scales, dynamically adaptive discretizations can be the method of choice. We present a major upgrade to the numerical relativity code…

General Relativity and Quantum Cosmology · Physics 2023-05-31 Sarah Renkhoff , Daniela Cors , David Hilditch , Bernd Brügmann

We investigate the value of extending the completeness of a decision model along different dimensions of refinement. Specifically, we analyze the expected value of quantitative, conceptual, and structural refinement of decision models. We…

Artificial Intelligence · Computer Science 2013-03-08 Kim-Leng Poh , Eric J. Horvitz

In recent work we have presented a novel algorithm for mesh refinement which utilizes a reduced model. In particular, the reduced model is used to monitor the transfer of activity (e.g. mass, energy) from larger to smaller scales. When the…

Numerical Analysis · Mathematics 2014-02-27 Panagiotis Stinis

Event-B is a formal approach oriented to system modeling and analysis. It supports refinement mechanism that enables stepwise modeling and verification of a system. By using refinement, the complexity of verification can be spread and…

Software Engineering · Computer Science 2012-10-29 Tsutomu Kobayashi , Shinichi Honiden

The conformal formulation of the Einstein constraint equations is first reviewed, and we then consider the design, analysis, and implementation of adaptive multilevel finite element-type numerical methods for the resulting coupled nonlinear…

General Relativity and Quantum Cosmology · Physics 2009-04-07 Burak Aksoylu , David Bernstein , Stephen Bond , Michael Holst

The use of neural networks to approximate partial differential equations (PDEs) has gained significant attention in recent years. However, the approximation of PDEs with localised phenomena, e.g., sharp gradients and singularities, remains…

Numerical Analysis · Mathematics 2025-01-30 Santiago Badia , Wei Li , Alberto F. Martín
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