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A heterogeneous modeling method for porous media flows
Author(s) -
Hlepas Georgette,
Truster Timothy,
Masud Arif
Publication year - 2014
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.3904
Subject(s) - domain decomposition methods , porous medium , embedding , domain (mathematical analysis) , mathematical optimization , benchmark (surveying) , darcy's law , mathematics , computer science , decomposition method (queueing theory) , residual , coupling (piping) , algorithm , finite element method , mathematical analysis , physics , geology , porosity , engineering , geotechnical engineering , mechanical engineering , geodesy , discrete mathematics , artificial intelligence , thermodynamics
Summary This paper presents a new heterogeneous multiscale modeling method for porous media flows. Physics at the global level is governed by one set of PDEs, while features in the solution that are beyond the resolution capacity of the global model are accounted for by the next refined set of governing equations. In this method, the global or coarse model is given by the Darcy equation, while the local or refined model is given by the Darcy–Stokes equation. Concurrent domain decomposition where global and local models are applied to adjacent subdomains, as well as overlapping domain decomposition where global and local models coexist on overlapping domains, is considered. An interface operator is developed for the case where global and local models commute along the common interface. For the overlapping decomposition, a residual‐based coupling technique is developed that consistently facilitates bottom‐up embedding of scale effects from the local Darcy–Stokes model into the global Darcy model. Numerical results are presented for nonoverlapping and overlapping domain decompositions for various benchmark problems. Computed results show that the hierarchically coupled models accurately account for the heterogeneity of the medium and efficiently incorporate local features into the global response. Copyright © 2014 John Wiley & Sons, Ltd.