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In this paper we study the linear systems arising from discretized poroelasticity problems. We formulate one block preconditioner for the two-filed Biot model and several preconditioners for the classical three-filed Biot model under the…

Numerical Analysis · Mathematics 2020-07-15 Shuangshuang Chen , Qingguo Hong , Jinchao Xu , Kai Yang

We solve elliptic systems of equations posed on highly heterogeneous materials. Examples of this class of problems are composite structures and geological processes. We focus on a model problem which is a second-order elliptic equation with…

Numerical Analysis · Mathematics 2015-12-11 Leonardo A. Poveda , Sebastian Huepo , Victor M. Calo , Juan Galvis

Solving the normal equations corresponding to large sparse linear least-squares problems is an important and challenging problem. For very large problems, an iterative solver is needed and, in general, a preconditioner is required to…

Numerical Analysis · Mathematics 2022-01-04 Hussam Al Daas , Pierre Jolivet , Jennifer Scott

Due to discretization effects and truncation to finite domains, many electromagnetic simulations present non-physical modifications of Maxwell's equations in space that may generate spurious signals affecting the overall accuracy of the…

Computational Physics · Physics 2016-02-17 H. Vincenti , J-L. Vay

We present novel model reduction methods for rapid solution of parametrized nonlinear partial differential equations (PDEs) in real-time or many-query contexts. Our approach combines reduced basis (RB) space for rapidly convergent…

Numerical Analysis · Mathematics 2024-10-04 Ngoc Cuong Nguyen

We present a monolithic geometric multigrid preconditioner for solving fluid-solid interaction problems in Stokes limit. The problems are discretized by a spatially adaptive high-order meshless method, the generalized moving least squares…

Numerical Analysis · Mathematics 2022-09-07 Zisheng Ye , Xiaozhe Hu , Wenxiao Pan

We construct and analyze a preconditioner of the linear elastiity system discretized by conforming linear finite elements in the framework of the auxiliary space method. The auxiliary space preconditioner is based on discretization of a…

Numerical Analysis · Mathematics 2010-03-15 James Brannick , Durkbin Cho

Physics-based models often involve large systems of parametrized partial differential equations, where design parameters control various properties. However, high-fidelity simulations of such systems on large domains or with high grid…

Computational Physics · Physics 2025-05-15 Diba Behnoudfar

We investigate the application of the additive overlapping Schwarz domain decomposition method as a preconditioner for the large sparse linear systems arising in graph-based nonlinear least-squares problems, specifically the pose-graph…

Numerical Analysis · Mathematics 2026-03-11 Stephan Köhler , Oliver Rheinbach , Yue Xiang Tee , Sebastian Zug

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 work introduces nodal auxiliary space preconditioners for discretizations of mixed-dimensional partial differential equations. We first consider the continuous setting and generalize the regular decomposition to this setting. With the…

Numerical Analysis · Mathematics 2019-10-15 Ana Budisa , Wietse Boon , Xiaozhe Hu

A preconditioning framework for the coupled problem of frictional contact mechanics and fluid flow in the fracture network is presented. The porous medium is discretized using low-order continuous finite elements, with cell-centered…

Numerical Analysis · Mathematics 2022-05-25 Andrea Franceschini , Laura Gazzola , Massimiliano Ferronato

Accelerating iterative eigenvalue algorithms is often achieved by employing a spectral shifting strategy. Unfortunately, improved shifting typically leads to a smaller eigenvalue for the resulting shifted operator, which in turn results in…

Numerical Analysis · Mathematics 2024-10-10 Lambert Theisen , Benjamin Stamm

The paper addresses parametric inequality systems described by polynomial functions in finite dimensions, where state-dependent infinite parameter sets are given by finitely many polynomial inequalities and equalities. Such systems can be…

Optimization and Control · Mathematics 2015-09-15 G. Li , B. S. Mordukhovich , T. T. A. Nghia , T. S. Pham

Optimization in machine learning, both theoretical and applied, is presently dominated by first-order gradient methods such as stochastic gradient descent. Second-order optimization methods, that involve second derivatives and/or second…

Machine Learning · Computer Science 2021-03-08 Rohan Anil , Vineet Gupta , Tomer Koren , Kevin Regan , Yoram Singer

We study preconditioners for a model problem describing the coupling of two elliptic subproblems posed over domains with different topological dimension by a parameter dependent constraint. A pair of parameter robust and efficient…

Numerical Analysis · Mathematics 2018-04-11 Miroslav Kuchta , Magne Nordaas , Joris C. G. Verschaeve , Mikael Mortensen , Kent-Andre Mardal

We present preconditioning techniques to solve linear systems of equations with a block two-by-two and three-by-three structure arising from finite element discretizations of the fictitious domain method with Lagrange multipliers. In…

Numerical Analysis · Mathematics 2026-03-09 Michele Benzi , Marco Feder , Luca Heltai , Federica Mugnaioni

Monolithic preconditioners applied to the linear systems arising during the solution of the discretized incompressible Navier-Stokes equations are typically more robust than preconditioners based on incomplete block factorizations. Lower…

Numerical Analysis · Mathematics 2026-02-11 Alexander Heinlein , Axel Klawonn , Jascha Knepper , Lea Saßmannshausen

To achieve sparse parametrizations that allows intuitive analysis, we aim to represent deformation with a basis containing interpretable elements, and we wish to use elements that have the description capacity to represent the deformation…

Computer Vision and Pattern Recognition · Computer Science 2012-11-30 Stefan Sommer , Mads Nielsen , Sune Darkner , Xavier Pennec

This work presents a scalable computational framework for optimal design under uncertainty with application to multi-material insulation components of building envelopes. The forward model consists of a multi-phase thermo-mechanical model…

Optimization and Control · Mathematics 2023-04-20 Jingye Tan , Danial Faghihi