Adaptive sparse linear solvers for implicit CFD using Newton-Krylov algorithms

L. McInnes; B. Norris; S. Bhowmick; P. Raghavan

doi:10.1016/B978-008044046-0.50250-5

Adaptive sparse linear solvers for implicit CFD using Newton-Krylov algorithms

L. McInnes, B. Norris, S. Bhowmick, P. Raghavan

Computer Science

Research output: Chapter in Book/Report/Conference proceeding › Chapter

14 Scopus citations

Abstract

We consider the simulation of three-dimensional transonic Euler flow using pseudo-transient Newton-Krylov methods [8,9]. The main computation involves solving a large, sparse linear system at each Newton (nonlinear) iteration. We develop a technique for adaptively selecting the linear solver method to match better the numeric properties of the linear systems as they evolve during the course of the nonlinear iterations. We show how such adaptive methods can be implemented using advanced software environments, leading to significant improvements in simulation time.

Original language	English (US)
Title of host publication	Computational Fluid and Solid Mechanics 2003
Publisher	Elsevier Inc.
Pages	1024-1028
Number of pages	5
ISBN (Electronic)	9780080529479
ISBN (Print)	9780080440460
DOIs	https://doi.org/10.1016/B978-008044046-0.50250-5
State	Published - Jun 2 2003

Keywords

Large-scale CFD simulations
Multi-method linear solvers
Newton-Krylov methods
Pseudo-transient continuation
Sparse linear solution
Transonic Euler flow

ASJC Scopus subject areas

General Engineering

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10.1016/B978-008044046-0.50250-5

Cite this

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abstract = "We consider the simulation of three-dimensional transonic Euler flow using pseudo-transient Newton-Krylov methods [8,9]. The main computation involves solving a large, sparse linear system at each Newton (nonlinear) iteration. We develop a technique for adaptively selecting the linear solver method to match better the numeric properties of the linear systems as they evolve during the course of the nonlinear iterations. We show how such adaptive methods can be implemented using advanced software environments, leading to significant improvements in simulation time.",

keywords = "Large-scale CFD simulations, Multi-method linear solvers, Newton-Krylov methods, Pseudo-transient continuation, Sparse linear solution, Transonic Euler flow",

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AU - McInnes, L.

AU - Norris, B.

AU - Bhowmick, S.

AU - Raghavan, P.

PY - 2003/6/2

Y1 - 2003/6/2

N2 - We consider the simulation of three-dimensional transonic Euler flow using pseudo-transient Newton-Krylov methods [8,9]. The main computation involves solving a large, sparse linear system at each Newton (nonlinear) iteration. We develop a technique for adaptively selecting the linear solver method to match better the numeric properties of the linear systems as they evolve during the course of the nonlinear iterations. We show how such adaptive methods can be implemented using advanced software environments, leading to significant improvements in simulation time.

AB - We consider the simulation of three-dimensional transonic Euler flow using pseudo-transient Newton-Krylov methods [8,9]. The main computation involves solving a large, sparse linear system at each Newton (nonlinear) iteration. We develop a technique for adaptively selecting the linear solver method to match better the numeric properties of the linear systems as they evolve during the course of the nonlinear iterations. We show how such adaptive methods can be implemented using advanced software environments, leading to significant improvements in simulation time.

KW - Large-scale CFD simulations

KW - Multi-method linear solvers

KW - Newton-Krylov methods

KW - Pseudo-transient continuation

KW - Sparse linear solution

KW - Transonic Euler flow

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BT - Computational Fluid and Solid Mechanics 2003

PB - Elsevier Inc.

ER -

Adaptive sparse linear solvers for implicit CFD using Newton-Krylov algorithms

Abstract

Keywords

ASJC Scopus subject areas

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