Access the full text.
Sign up today, get DeepDyve free for 14 days.
Y. Erlangga, R. Nabben (2008)
Deflation and Balancing Preconditioners for Krylov Subspace Methods Applied to Nonsymmetric MatricesSIAM J. Matrix Anal. Appl., 30
R. Kraft, A. Coutinho, P. Sampaio (2007)
Edge‐based data structures for a symmetric stabilized finite element method for the incompressible Navier–Stokes equations with heat transferInternational Journal for Numerical Methods in Fluids, 53
R. Aubry, F. Mut, R. Löhner, J. Cebral (2008)
Deflated preconditioned conjugate gradient solvers for the Pressure-Poisson equationJ. Comput. Phys., 227
H. Elman, M. Mihajlovic, D. Silvester (2011)
Fast iterative solvers for buoyancy driven flow problemsJ. Comput. Phys., 230
J. MacQueen (1967)
Some methods for classification and analysis of multivariate observations, 1
R. Aubry, F. Mut, S. Dey, Rainald Löhner (2011)
Deflated preconditioned conjugate gradient solvers for linear elasticityInternational Journal for Numerical Methods in Engineering, 88
P. Sampaio (2006)
A stabilized finite element method for incompressible flow and heat transfer: A natural derivation based on the use of local time-stepsComputer Methods in Applied Mechanics and Engineering, 195
Y. Erlangga, R. Nabben (2008)
Multilevel Projection-Based Nested Krylov Iteration for Boundary Value ProblemsSIAM J. Sci. Comput., 30
Y. Saad, M. Yeung, J. Erhel, F. Guyomarc'h (1999)
A Deflated Version of the Conjugate Gradient AlgorithmSIAM J. Sci. Comput., 21
F. Vermolen, K. Vuik, G. Segal (2002)
Deflation in Preconditioned Conjugate Gradient Methods for Finite Element ProblemsReports of the Department of Applied Mathematical Analysis
Yanhu Guo, K. Bathe (2002)
A numerical study of a natural convection flow in a cavityInternational Journal for Numerical Methods in Fluids, 40
A. Brooks, T. Hughes (1990)
Streamline upwind/Petrov-Galerkin formulations for convection dominated flows with particular emphasis on the incompressible Navier-Stokes equationsComputer Methods in Applied Mechanics and Engineering, 32
J. Frank, C. Vuik (2001)
On the Construction of Deflation-Based PreconditionersSIAM J. Sci. Comput., 23
R. Löhner, F. Mut, J. Cebral, R. Aubry, G. Houzeaux (2011)
Deflated preconditioned conjugate gradient solvers for the pressure‐Poisson equation: Extensions and improvementsInternational Journal for Numerical Methods in Engineering, 87
M. Christon, P. Gresho, S. Sutton (2002)
Computational predictability of time‐dependent natural convection flows in enclosures (including a benchmark solution)International Journal for Numerical Methods in Fluids, 40
J. Cebral, F. Mut (2008)
Extensions to the computational hemodynamics modeling of cerebral aneurysms
P. Sampaio, A. Coutinho (1999)
Simulation of free and forced convection incompressible flows using an adaptive parallel/vector finite element procedureInternational Journal for Numerical Methods in Fluids, 29
Y. Saad (2003)
Iterative methods for sparse linear systems
A. Baker, T. Kolev, U. Yang (2010)
Improving algebraic multigrid interpolation operators for linear elasticity problemsNumerical Linear Algebra with Applications, 17
R. Nicolaides (1987)
Deflation of conjugate gradients with applications to boundary value problemsSIAM Journal on Numerical Analysis, 24
R. Codina, J. Principe, M. Avila (2010)
Finite element approximation of turbulent thermally coupled incompressible flows with numerical sub-grid scale modelingInternational Journal of Numerical Methods for Heat & Fluid Flow, 20
Purpose – The purpose of this paper is to show benefits of deflated preconditioned conjugate gradients (CG) in the solution of transient, incompressible, viscous flows coupled with heat transfer. Design/methodology/approach – This paper presents the implementation of deflated preconditioned CG as the iterative driver for the system of linearized equations for viscous, incompressible flows and heat transfer simulations. The De Sampaio-Coutinho particular form of the Petrov-Galerkin Generalized Least Squares finite element formulation is used in the discretization of the governing equations, leading to symmetric positive definite matrices, allowing the use of the CG solver. Findings – The use of deflation techniques improves the spectral condition number. The authors show in a number of problems of coupled viscous flow and heat transfer that convergence is achieved with a lower number of iterations and smaller time. Originality/value – This work addressed for the first time the use of deflated CG for the solution of transient analysis of free/forced convection in viscous flows coupled with heat transfer.
International Journal of Numerical Methods for Heat & Fluid Flow – Emerald Publishing
Published: Mar 2, 2015
Read and print from thousands of top scholarly journals.
Already have an account? Log in
Bookmark this article. You can see your Bookmarks on your DeepDyve Library.
To save an article, log in first, or sign up for a DeepDyve account if you don’t already have one.
Copy and paste the desired citation format or use the link below to download a file formatted for EndNote
Access the full text.
Sign up today, get DeepDyve free for 14 days.
All DeepDyve websites use cookies to improve your online experience. They were placed on your computer when you launched this website. You can change your cookie settings through your browser.