A stochastic multiscale framework for modeling flow through random heterogeneous porous media

Flow through porous media is ubiquitous, occurring from large geological scales down to the microscopic scales. Several critical engineering phenomena like contaminant spread, nuclear waste disposal and oil recovery rely on accurate analysis and prediction of these multiscale phenomena. Such analysi...

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Veröffentlicht in:	Journal of computational physics 2009-02, Vol.228 (2), p.591-618
Hauptverfasser:	Ganapathysubramanian, B., Zabaras, N.
Format:	Artikel
Sprache:	eng
Schlagworte:	ALGORITHMS CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSICS Collocation methods Computational techniques Data-driven modeling Exact sciences and technology FINITE ELEMENT METHOD Manifold learning Mathematical methods in physics Mathematical models Mixed finite elements Non-linear model reduction NONLINEAR PROBLEMS PARTIAL DIFFERENTIAL EQUATIONS PERMEABILITY Physics POROUS MATERIALS RADIOACTIVE WASTE DISPOSAL RANDOMNESS Scalable algorithms SIMULATION Sparse grids Stochastic partial differential equations STOCHASTIC PROCESSES VARIATIONAL METHODS Variational multiscale methods
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