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Development and application of a parallel multigrid solver for the simulation of spreading droplets
Author(s) -
Gaskell P. H.,
Jimack P. K.,
Koh Y.Y.,
Thompson H. M.
Publication year - 2008
Publication title -
international journal for numerical methods in fluids
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.938
H-Index - 112
eISSN - 1097-0363
pISSN - 0271-2091
DOI - 10.1002/fld.1737
Subject(s) - multigrid method , discretization , solver , nonlinear system , grid , algebraic equation , mathematics , range (aeronautics) , computer science , finite difference , computational science , mathematical optimization , mathematical analysis , geometry , partial differential equation , physics , materials science , quantum mechanics , composite material
We consider the parallel application of an efficient solver developed for the accurate solution of a range of droplet spreading flows modelled as a coupled set of nonlinear lubrication equations. The underlying numerical scheme is based upon a second‐order finite difference discretization in space and a second‐order, fully implicit, adaptive scheme in time. At each time step, this leads to the need to solve a large system of nonlinear algebraic equations, for which the full approximation storage multigrid algorithm is employed. The motion of the contact line between the three phases (liquid, air and the solid substrate) is based upon the assumption of a thin precursor film, with a corresponding disjoining pressure term in the governing equations. It is the inclusion of this precursor film in the model that motivates the need for a parallel solution method. This is because the thickness of such a film must be very small in order to yield realistic predictions, while the finite difference grid must be correspondingly fine in order to obtain accurate numerical solutions. Results are presented which demonstrate that the parallel implementation is sufficiently efficient and robust to allow reliable numerical solutions to be obtained for a level of mesh resolution that is an order of magnitude finer than is possible using a single processor. Copyright © 2008 John Wiley & Sons, Ltd.