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A nonlinear multigrid solver for two-phase flow and transport in a mixed fractional-flow velocity-pressure-saturation formulation is proposed. The solver, which is under the framework of the full approximation scheme (FAS), extends our…

Numerical Analysis · Mathematics 2021-09-17 Chak Shing Lee , François P. Hamon , Nicola Castelletto , Panayot S. Vassilevski , Joshua A. White

Algebraic multigrid (AMG) methods derive their optimal efficiency from the interplay between a relaxation process and a corresponding coarse grid correction. In many standard formulations, relaxation and coarse-graining are analyzed and…

Numerical Analysis · Mathematics 2026-03-30 Rayan Moussa , Karsten Kahl

We investigate a novel monolithic algebraic multigrid (AMG) preconditioner for the Taylor-Hood ($\pmb{\mathbb{P}}_2/\mathbb{P}_1$) and Scott-Vogelius ($\pmb{\mathbb{P}}_2/\mathbb{P}_1^{disc}$) discretizations of the Stokes equations. The…

Numerical Analysis · Mathematics 2024-09-04 Alexey Voronin , Scott MacLachlan , Luke N. Olson , Raymond Tuminaro

We show how a scalable preconditioner for the primal discontinuous Petrov-Galerkin (DPG) method can be developed using existing algebraic multigrid (AMG) preconditioning techniques. The stability of the DPG method gives a norm equivalence…

Numerical Analysis · Mathematics 2018-07-10 Andrew T. Barker , Veselin Dobrev , Jay Gopalakrishnan , Tzanio Kolev

In this paper, we propose and evaluate the performance of a unified computational framework for preconditioning systems of linear equations resulting from the solution of coupled problems with monolithic schemes. The framework is composed…

Numerical Analysis · Mathematics 2016-08-24 Francesc Verdugo , Wolfgang A. Wall

We study the solution of block-structured linear algebra systems arising in optimization by using iterative solution techniques. These systems are the core computational bottleneck of many problems of interest such as parameter estimation,…

Optimization and Control · Mathematics 2019-09-10 Jose S. Rodriguez , Carl D. Laird , Victor M. Zavala

In this paper, we are interested in an efficient numerical method for the mixed-dimensional approach to modeling single-phase flow in fractured porous media. The model introduces fractures and their intersections as lower-dimensional…

Numerical Analysis · Mathematics 2019-06-03 Ana Budiša , Xiaozhe Hu

In this paper, we consider flow simulation in highly heterogeneous media that has many practical applications in industry. To enhance mass conservation, we write the elliptic problem in a mixed formulation and introduce a robust two-grid…

Numerical Analysis · Mathematics 2019-05-22 Yanfang Yang , Shubin Fu , Eric T. Chung

In this note we present a multigrid preconditioning method for solving quadratic optimization problems constrained by a fractional diffusion equation. Multigrid methods within the all-at-once approach to solve the first order-order…

Optimization and Control · Mathematics 2020-10-29 Harbir Antil , Andrei Dr{ă}g{ă}nescu , Kiefer Green

Algebraic multigrid (AMG) is one of the most widely used solution techniques for linear systems of equations arising from discretized partial differential equations. The popularity of AMG stems from its potential to solve linear systems in…

Numerical Analysis · Mathematics 2026-04-03 Carlo Janna , Andrea Franceschini , Jacob B. Schroder , Luke Olson

This paper describes a massively parallel algebraic multigrid method based on non-smoothed aggregation. It is especially suited for solving heterogeneous elliptic problems as it uses a greedy heuristic algorithm for the aggregation that…

Numerical Analysis · Mathematics 2013-10-01 Markus Blatt , Olaf Ippisch , Peter Bastian

We propose a path cover adaptive algebraic multigrid (PC-$\alpha$AMG) method for solving linear systems of weighted graph Laplacians and can also be applied to discretized second order elliptic partial differential equations. The…

Numerical Analysis · Mathematics 2018-06-20 Xiaozhe Hu , Junyuan Lin , Ludmil T. Zikatanov

This paper is to give an overview of AMG methods for solving large scale systems of equations such as those from the discretization of partial differential equations. AMG is often understood as the acronym of "Algebraic Multi-Grid", but it…

Numerical Analysis · Mathematics 2016-11-11 Jinchao Xu , Ludmil T Zikatanov

We propose an augmented Lagrangian-based preconditioner to accelerate the convergence of Krylov subspace methods applied to linear systems of equations with a block three-by-three structure such as those arising from mixed finite element…

Numerical Analysis · Mathematics 2023-10-26 Fatemeh P. A. Beik , Michele Benzi

We develop a simple algorithmic framework to solve large-scale symmetric positive definite linear systems. At its core, the framework relies on two components: (1) a norm-convergent iterative method (i.e. smoother) and (2) a preconditioner.…

Numerical Analysis · Mathematics 2013-02-18 Xiaozhe Hu , Shuhong Wu , Xiao-Hui Wu , Jinchao Xu , Chen-Song Zhang , Shiquan Zhang , Ludmil Zikatanov

Algebraic multigrid (AMG) methods are powerful solvers with linear or near-linear computational complexity for certain classes of linear systems, Ax=b. Broadening the scope of problems that AMG can effectively solve requires the development…

Numerical Analysis · Mathematics 2019-02-15 James Brannick , Scott P. MacLachlan , Jacob B. Schroder , Ben S. Southworth

The compositional model is often used to describe multicomponent multiphase porous media flows in the petroleum industry. The fully implicit method with strong stability and weak constraints on time-step sizes is commonly used in the…

Numerical Analysis · Mathematics 2024-09-18 Li Zhao , Chen-Song Zhang , Chun-Sheng Feng , Shi Shu

Many applications involving porous media--notably reservoir engineering and geologic applications--involve tight coupling between multiphase fluid flow, transport, and poromechanical deformation. While numerical models for these processes…

Topology optimization problems generally support multiple local minima, and real-world applications are typically three-dimensional. In previous work [I. P. A. Papadopoulos, P. E. Farrell, and T. M. Surowiec, Computing multiple solutions of…

Numerical Analysis · Mathematics 2022-11-23 Ioannis P. A. Papadopoulos , Patrick E. Farrell

We consider the use of multipreconditioning to solve linear systems when more than one preconditioner is available but the optimal choice is not known. In particular, we consider a selective multipreconditioned GMRES algorithm where we…

Numerical Analysis · Mathematics 2021-07-08 Niall Bootland , Andrew Wathen