2006
DOI: 10.1007/s11242-005-6060-0
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Filtration in a Porous Granular Medium: 2. Application of Bubble Model to 1-D Column Experiments

Abstract: This paper describes the formulation of a quasi-1-D network model, referred to as the 'bubble model', and its application for simulating particle transport and filtration through a granular filter bed. The model comprises a series of homogeneous sites linked through bundles of cylindrical bonds that represent flow pathways through distributions of pores and pore throats. This model incorporates pore scale processes of particle sieving and infiltration are based on numerical simulations described in a companion… Show more

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Cited by 21 publications
(17 citation statements)
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“…The paper also proposes simple empirical functions for the rejection efficiency based on the numerical simulations. These are used in accounting for the conservation of mass within a network model of filtration which is presented in a companion paper (Kim and Whittle, 2005a).…”
Section: Discussionmentioning
confidence: 99%
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“…The paper also proposes simple empirical functions for the rejection efficiency based on the numerical simulations. These are used in accounting for the conservation of mass within a network model of filtration which is presented in a companion paper (Kim and Whittle, 2005a).…”
Section: Discussionmentioning
confidence: 99%
“…The Authors propose semi-empirical functions for interpreting the numerical simulations of infiltration with mono-disperse particles including the particle collection rate and effects of mounding on the pore transmissivity. A companion paper (Kim and Whittle, 2005a) applies these results in network model simulations and compares these numerical predictions with detailed experimental observations of particle transport in a granular filter bed.…”
Section: Introductionmentioning
confidence: 95%
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“…Donaldson, Baker, and Carrol in 1977 [8] were the first to use networks to study particle transport within porous media. The clogging of particles has been studied in networks with different geometries including bundles of parallel tubes [8], square networks [14,16,21], triangular networks [3,25], cubic networks [2,17,29], bubble models [6,20], and the so-called three-dimensional physically representative networks [1,30].…”
Section: Introductionmentioning
confidence: 99%
“…in networks with different geometries including bundle of parallel tubes [8], square networks [14,16,23], triangular networks [3,27], cubic networks [2,17,33], bubble models [6,22], and the so-called three-dimensional physically representative networks [1,34].…”
mentioning
confidence: 99%