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Multiphase flows are an important class of fluid flow and their study facilitates the development of diverse applications in industrial, natural, and biomedical systems. We consider a model that uses a continuum description of both phases…

Fluid Dynamics · Physics 2025-08-04 Bindi M. Nagda , Aaron Barrett , Boyce E. Griffith , Aaron L. Fogelson , Jian Du

We introduce a new cell-centered finite volume discretization for elasticity with weakly enforced symmetry of the stress tensor. The method is motivated by the need for robust discretization methods for deformation and flow in porous media,…

Numerical Analysis · Mathematics 2015-12-04 Eirik Keilegavlen , Jan Martin Nordbotten

Ill-conditioning of the system matrix is a well-known complication in immersed finite element methods and trimmed isogeometric analysis. Elements with small intersections with the physical domain yield problematic eigenvalues in the system…

Numerical Analysis · Mathematics 2019-12-17 F. de Prenter , C. V. Verhoosel , E. H. van Brummelen , J. A. Evans , C. Messe , J. Benzaken , K. Maute

Robust discretization methods for (nearly-incompressible) linear elasticity are free of volume-locking and gradient-robust. While volume-locking is a well-known problem that can be dealt with in many different discretization approaches, the…

Numerical Analysis · Mathematics 2020-01-24 Guosheng Fu , Christoph Lehrenfeld , Alexander Linke , Timo Streckenbach

We develop a general framework for MAP estimation in discrete and Gaussian graphical models using Lagrangian relaxation techniques. The key idea is to reformulate an intractable estimation problem as one defined on a more tractable graph,…

Artificial Intelligence · Computer Science 2007-10-02 Jason K. Johnson , Dmitry M. Malioutov , Alan S. Willsky

In this manuscript, we present a collective multigrid algorithm to solve efficiently the large saddle-point systems of equations that typically arise in PDE-constrained optimization under uncertainty, and develop a novel convergence…

Optimization and Control · Mathematics 2024-05-20 Gabriele Ciaramella , Fabio Nobile , Tommaso Vanzan

Overlapping block smoothers efficiently damp the error contributions from highly oscillatory components within multigrid methods for the Stokes equations but they are computationally expensive. This paper is concentrated on the development…

Numerical Analysis · Mathematics 2020-08-21 Lisa Claus , Matthias Bolten

A block diagonal preconditioner with the minimal residual method and a block triangular preconditioner with the generalized minimal residual method are developed for Hu-Zhang mixed finite element methods of linear elasticity. They are based…

Numerical Analysis · Mathematics 2016-05-24 Long Chen , Jun Hu , Xuehai Huang

In this paper, we extend the work of Brenner and Sung [Math. Comp. 59, 321--338 (1992)] and present a regularity estimate for the elastic equations in concave domains. Based on the regularity estimate we prove that the constants in the…

Numerical Analysis · Mathematics 2021-12-21 Hai Bi , Xuqing Zhang , Yidu Yang

We propose a robust, adaptive coarse-grid correction scheme for matrix-free geometric multigrid targeting PDEs with strongly varying coefficients. The method combines uniform geometric coarsening of the underlying grid with heterogeneous…

Performance · Computer Science 2025-11-18 Fabian Böhm , Nils Kohl , Harald Köstler , Ulrich Rüde

We present optimal preconditioners for a recently introduced hybridized discontinuous Galerkin finite element discretization of the Stokes equations. Typical of hybridized discontinuous Galerkin methods, the method has degrees-of-freedom…

Numerical Analysis · Mathematics 2023-07-06 Sander Rhebergen , Garth N. Wells

We develop a robust and efficient iterative method for hyper-elastodynamics based on a novel continuum formulation recently developed. The numerical scheme is constructed based on the variational multiscale formulation and the…

Numerical Analysis · Mathematics 2019-02-20 Ju Liu , Alison L. Marsden

In this work, we study a primal hybrid finite element method for the approximation of linear elasticity problems, posed in terms of displacement, an auxiliary pressure field, and a Lagrange multiplier related to the traction. We develop a…

Numerical Analysis · Mathematics 2026-01-30 Giovanni Taraschi , Maicon Ribeiro Correa

The Scheduled Relaxation Jacobi (SRJ) method is a linear solver algorithm which greatly improves the convergence of the Jacobi iteration through the use of judiciously chosen relaxation factors (an SRJ scheme) which attenuate the solution…

Numerical Analysis · Mathematics 2021-12-14 Mohammad Shafaet Islam , Qiqi Wang

This work studies three multigrid variants for matrix-free finite-element computations on locally refined meshes: geometric local smoothing, geometric global coarsening, and polynomial global coarsening. We have integrated the algorithms…

Numerical Analysis · Mathematics 2022-04-12 Peter Munch , Timo Heister , Laura Prieto Saavedra , Martin Kronbichler

In this paper, we introduce and analyze a lowest-order locking-free weak Galerkin (WG) finite element scheme for the grad-div formulation of linear elasticity problems. The scheme uses linear functions in the interior of mesh elements and…

Numerical Analysis · Mathematics 2023-09-12 Fuchang Huo , Ruishu Wang , Yanqiu Wang , Ran Zhang

Standard quadratic optimization problems (StQPs) provide a versatile modelling tool in various applications. In this paper, we consider StQPs with a hard sparsity constraint, referred to as sparse StQPs. We focus on various tractable convex…

Optimization and Control · Mathematics 2023-10-09 Immanuel Bomze , Bo Peng , Yuzhou Qiu , E. Alper Yıldırım

We consider discontinuous Galerkin methods for an elliptic distributed optimal control problem and we propose multigrid methods to solve the discretized system. We prove that the $W$-cycle algorithm is uniformly convergent in the energy…

Numerical Analysis · Mathematics 2023-05-11 Sijing Liu

The rapid growth of large language models (LLMs) presents significant deployment challenges due to their massive computational and memory demands. While model compression, such as network pruning, offers potential solutions, most existing…

Machine Learning · Computer Science 2026-04-07 Ziwei Li , Yuang Ma , Yi Kang

In the present paper we concentrate on an important issue in constructing a good multigrid solver: the choice of an efficient smoother. We will introduce all-at-once multigrid solvers for optimal control problems which show robust…

Numerical Analysis · Mathematics 2016-01-08 Stefan Takacs
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