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Based on the method of FGD, we apply the method of adaptive gradient descent which uses different step length at different epoch. Adaptive gradient descent performs much better than FGD in the tests and keeps the guarantee of convergence…

Optimization and Control · Mathematics 2020-10-21 Dan Qiao

We provide an adaptive finite element approximation for a model of quasi-static crack growth in dimension two. The discrete setting consists of integral functionals that are defined on continuous, piecewise affine functions, where the…

Analysis of PDEs · Mathematics 2025-03-25 Vito Crismale , Manuel Friedrich , Joscha Seutter

An implementation of adaptive mesh refinement algorithms is presented for use with multilayer shallow water equations. Currently, adaptive mesh refinement is implemented with a single layer shallow water model in the GeoClaw framework. This…

Numerical Analysis · Mathematics 2018-03-06 Avi Schwarzschild , Kyle T. Mandli

A new concept is introduced for the adaptive finite element discretization of partial differential equations that have a sparsely representable solution. Motivated by recent work on compressed sensing, a recursive mesh refinement procedure…

Numerical Analysis · Mathematics 2009-02-26 Sadegh Jokar , Volker Mehrmann , Marc Pfetsch , Harry Yserentant

A space-time adaptive scheme is presented for solving advection equations in two space dimensions. The gradient-augmented level set method using a semi-Lagrangian formulation with backward time integration is coupled with a point value…

Computational Physics · Physics 2015-04-20 Dmitry Kolomenskiy , Jean-Christophe Nave , Kai Schneider

The subject of this work is an adaptive stochastic Galerkin finite element method for parametric or random elliptic partial differential equations, which generates sparse product polynomial expansions with respect to the parametric…

Numerical Analysis · Mathematics 2025-03-28 Markus Bachmayr , Martin Eigel , Henrik Eisenmann , Igor Voulis

We consider the vertex-centered finite volume method with first-order conforming ansatz functions. The adaptive mesh-refinement is driven by the local contributions of the weighted-residual error estimator. We prove that the adaptive…

Numerical Analysis · Mathematics 2016-11-24 Christoph Erath , Dirk Praetorius

The magnetohydrodynamics (MHD) equations are continuum models used in the study of a wide range of plasma physics systems, including the evolution of complex plasma dynamics in tokamak disruptions. However, efficient numerical solution…

Computational Physics · Physics 2022-02-09 Qi Tang , Luis Chacon , Tzanio V. Kolev , John N. Shadid , Xian-Zhu Tang

Adaptive mesh refinement (AMR) is widely used to efficiently resolve localized features in time-dependent partial differential equations (PDEs) by selectively refining and coarsening the mesh. However, in long-horizon simulations, repeated…

Numerical Analysis · Mathematics 2026-02-10 Kumar Saurabh , Makrand A. Khanwale , Masado Ishii , Hari Sundar , Baskar Ganapathysubramanian

This paper investigates an adaptive wavelet collocation time domain method for the numerical solution of Maxwell's equations. In this method a computational grid is dynamically adapted at each time step by using the wavelet decomposition of…

Numerical Analysis · Mathematics 2012-04-06 Haojun Li , Kirankumar R. Hiremath , Andreas Rieder , Wolfgang Freude

We solve the general relativistic magnetohydrodynamics equations using distributed parallel adaptive mesh refinement. We discuss strong scaling tests of the code, and present evolutions of Michel accretion and a TOV star.

General Relativity and Quantum Cosmology · Physics 2016-11-15 David Neilsen , Eric W. Hirschmann , Matthew Anderson , Steven L. Liebling

We present an adaptive space-time mesh refinement approach based a domain decomposition approach (Singh and Wheeler, 2018) that allows different time-step sizes and mesh refinements in different subdomains. Our numerical experiments…

Numerical Analysis · Mathematics 2018-09-10 Gurpreet Singh , Mary F. Wheeler

We demonstrate an approach to the numerical solution of nonlinear stochastic differential equations with Markovian switching. Such equations describe the stochastic dynamics of processes where the drift and diffusion coefficients are…

Numerical Analysis · Mathematics 2024-08-28 Cónall Kelly , Kate O'Donovan

A classic approach for solving differential equations with neural networks builds upon neural forms, which employ the differential equation with a discretisation of the solution domain. Making use of neural forms for time-dependent…

Neural and Evolutionary Computing · Computer Science 2022-09-02 Toni Schneidereit , Michael Breuß

We analyze optimal complexity of adaptive finite element methods (AFEMs) for general second-order linear elliptic partial differential equations (PDEs) in the Lax-Milgram setting. To this end, we formulate an adaptive algorithm which steers…

Numerical Analysis · Mathematics 2026-04-21 Thomas Führer , Paula Hilbert , Ani Miraçi , Dirk Praetorius

Near-optimal computational complexity of an adaptive stochastic Galerkin method with independently refined spatial meshes for elliptic partial differential equations is shown. The method takes advantage of multilevel structure in expansions…

Numerical Analysis · Mathematics 2025-03-25 Markus Bachmayr , Henrik Eisenmann , Igor Voulis

This article initiates the study of space-time adaptive mesh refinements for time-dependent boundary element formulations of wave equations. Based on error indicators of residual type, we formulate an adaptive boundary element procedure for…

Numerical Analysis · Mathematics 2025-11-07 Alessandra Aimi , Giulia Di Credico , Heiko Gimperlein , Chiara Guardasoni

We present a convergence result for the finite volume method applied to a particular phase field problem suitable for simulation of pure substance solidification. The model consists of the heat equation and the phase field equation with a…

Numerical Analysis · Mathematics 2020-10-14 Aleš Wodecki , Pavel Strachota , Michal Beneš

This paper interprets the stabilized finite element method via residual minimization as a variational multiscale method. We approximate the solution to the partial differential equations using two discrete spaces that we build on a…

Computational Engineering, Finance, and Science · Computer Science 2023-05-23 Juan F. Giraldo , Victor M. Calo

Mesh numbering is a critical issue in Finite Element Methods, as the computational cost of one analysis is highly dependent on the order of the nodes of the mesh. This paper presents some preliminary investigations on the problem of mesh…

Numerical Analysis · Computer Science 2007-06-12 Francis Sourd , Marc Schoenauer