2009
DOI: 10.1016/j.ijheatmasstransfer.2009.07.017
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Characterization of a porous medium employing numerical tools: Permeability and pressure-drop from Darcy to turbulence

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Cited by 34 publications
(18 citation statements)
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“…The solver has been fully tested and validated for geometries including those presented in this study as well as for a broad range of Re (from Stokes flows to turbulent flows). Additional details regarding the numerical scheme and its implementation and validation are available in References [20,25].…”
Section: Methodsmentioning
confidence: 99%
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“…The solver has been fully tested and validated for geometries including those presented in this study as well as for a broad range of Re (from Stokes flows to turbulent flows). Additional details regarding the numerical scheme and its implementation and validation are available in References [20,25].…”
Section: Methodsmentioning
confidence: 99%
“…Specific details related to numerical simulations such as initial conditions, grids, convergence tests, etc. are given in detail in [20,25].…”
Section: Methodsmentioning
confidence: 99%
“…For example, Teruel and Rizwan-Uddin [7] numerically calculated the interfacial heat transfer coefficient in porous media. Xin et al [8] numerically investigated the heat and mass transfer behaviors in porous media for multiphase flow.…”
Section: Introductionmentioning
confidence: 99%
“…They are often carried out in periodic and simple porous structures that allow extracting a rich variety of results (e.g. laminar and turbulent flows and large range of porosities) with an acceptable computational cost [3,4]. The h sf coefficient has not been an exception; for instance, Martin et al [5], numerically determined this coefficient (or, more precisely, the Nusselt number) considering a porous structure represented by a periodic and triangular array of cylinders, and Kuwahara et al [6] carried out numerical simulations in periodic arrays of staggered square rods for a large range of flow conditions (1 < Re D < 10 4 ), porosities (0.36 < / < 0.91) and a variety of Prandtl numbers.…”
Section: Introductionmentioning
confidence: 99%