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Deflated preconditioned conjugate gradient solvers for the pressure‐Poisson equation: Extensions and improvements
Author(s) -
Löhner Rainald,
Mut Fernando,
Cebral Juan Raul,
Aubry Romain,
Houzeaux Guillaume
Publication year - 2011
Publication title -
international journal for numerical methods in engineering
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.421
H-Index - 168
eISSN - 1097-0207
pISSN - 0029-5981
DOI - 10.1002/nme.2932
Subject(s) - conjugate gradient method , poisson's equation , solver , compressibility , mathematics , poisson distribution , conjugate , reduction (mathematics) , set (abstract data type) , derivation of the conjugate gradient method , pressure gradient , conjugate residual method , computer science , mathematical optimization , mathematical analysis , geometry , mechanics , physics , gradient descent , statistics , machine learning , artificial neural network , programming language
Extensions and improvements to a deflated preconditioned conjugate gradient technique for the solution of the pressure‐Poisson equation within an incompressible flow solver are described. In particular, the use of the technique for embedded grids, for cases where volume of fluid or level set schemes are required and its implementation on parallel machines are considered. Several examples are included that demonstrate a considerable reduction in the number of iterations and a remarkable insensitivity to the number of groups/ regions chosen and/or to the way the groups are formed. Copyright © 2010 John Wiley & Sons, Ltd.