Simulation of the dynamics of depth filtration of non‐Brownian particles

Burganos, Vasilis N.; Skouras, E. D.; Paraskeva, Christakis Α.; Payatakes, A. C.

doi:10.1002/aic.690470411

Cited by 29 publications

(27 citation statements)

References 59 publications

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“…The degree of enhancement is expected to depend on the magnitude of the local fluid velocity at the interface, which in turn depends on the superficial fluid velocity, the detailed pore structure (accounting for the formed biofilms), and the hydraulic permeability of the biofilms (which in turn depends on geometric parameters at smaller length scales -see Step 5). It should be noted that Burganos et al [11] have shown that the deposition rate in granular porous media increases significantly when fluid flow through the already formed deposits is taken into account (and the increase is more pronounced for more porous depositssee their discussion in p. 889). For these two reasons, fluid flow through and convective mass transfer in the biofilm should be taken into account in the formulation of theoretical models and simulators (these two factors have been neglected in all the previous theoretical works).…”

Section: Critical Parametersmentioning

confidence: 95%

“…Simulations of the depth filtration of non-Brownian particles (size larger than 2 lm) by Burganos et al [9][10][11] have shown that the fraction of convected-out particles is highly dependent on the detailed pore geometry and the superficial fluid velocity. In particular, the fraction of convected-out particles increases as the superficial velocity and/or the size of the constriction between neighboring grains increase.…”

Section: Critical Parametersmentioning

confidence: 99%

“…Eqs. (11) and (12) are solved numerically by following the general formulation of the MAC method. This is a well-known scheme, thus only an outline of the method will be given here.…”

Section: Step 6: Determination Of the Flow Fieldmentioning

confidence: 99%

See 2 more Smart Citations

Hierarchical simulator of biofilm growth and dynamics in granular porous materials

Kapellos

Alexiou

Payatakes

2007

Advances in Water Resources

101

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Section: Critical Parametersmentioning

confidence: 95%

Section: Critical Parametersmentioning

confidence: 99%

See 1 more Smart Citation

Hierarchical simulator of biofilm growth and dynamics in granular porous materials

Kapellos

Alexiou

Payatakes

2007

Advances in Water Resources

101

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“…Numerous authors have recognized the potential of network models for understanding filtration processes by directly modeling the pore scale flow of particle suspensions (Rege and Fogler, 1988;Imdakm and Sahimi, 1991;Datta and Redner, 1998a, b;Lee and Koplik, 2001). For example, Burganos et al (1992Burganos et al ( , 2001 have developed 2-D and 3-D regular lattice models where each link has a constricted tube geometry and particle infiltration is computed using trajectory analyses (after Tien and Payatakes, 1979). In practice, it is often difficult to apply network models due to the limited information usually available for characterizing the pore morphology.…”

Section: Introductionmentioning

confidence: 99%

Filtration in a Porous Granular Medium: 2. Application of Bubble Model to 1-D Column Experiments

Kim¹,

Whittle

2006

Transp Porous Med

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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 paper. The modeling of infiltration is further refined based on detailed experimental observations and measurements of the filtration of a dilute suspension of acrylic particles through a column of glass beads reported by Yoon et al. (2005 Water Resour. Res., to appear). Their data distinguish (a) between the collection of particles on grain surfaces and at grain-tograin contact points, and (b) between particles that are fully entrapped and those that are hindered (temporarily collected) and can later become detached. These effects are represented by two parameters that characterize the probability of attachment and are linked to the surface roughness of the grains; one that describes the minimum particle size that can be fully entrapped, and one that describes the detachment rate. These parameters can be readily calibrated from conventional measurements of effluent concentration and effluent particle size distribution. Detailed comparisons with the data reported by Yoon et al.show that the proposed bubble model is able to achieve reliable predictions of the spatial distribution of particles within the filter bed following phases of particle injection and washing.

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“…As this work described limiting cases, the authors considered the transient behavior of the filtration process to be a combination of both cases and derived a semi-empirical correlation depending on operating variables which, in some cases, successfully predicted results from independent sources. More recently, Burganos et al [19] and Skouras et al [20] Furthermore, only a few of these models are truly predictive and they often require time-and memoryconsuming computations of streamlines and particle trajectories. In this article, based on theoretical considerations, we propose a new modeling principle for changes to the pressure drop and filtration efficiency throughout the granular bed during clogging with Brownian aerosols.…”

Section: Introductionmentioning

confidence: 99%

Modeling of the deep granular bed clogging by nanoparticles

Wingert

Bardin‐Monnier

Charvet

et al. 2017

Separation and Purification Technology

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Nanoparticles aerosols are a potential health hazard and are increasingly used in industry today.Effective means for their filtration to avoid occupational exposure are necessary. Granular bed filtration exhibits interesting properties in terms of ultrafine particle collection efficiency or retention capacity, which could make them a good alternative to the fiber filters commonly used in industry today. Being able to predict changes to their collection efficiency and pressure drop during clogging appears essential for the design, optimization and control of the filtration process. To meet these needs, this study presents a predictive model for the different phases of deep-bed clogging. The model developed successfully describes changes to collection efficiency and pressure drop using equivalent collector diameters. Microscopic observations showed these equivalent diameters to be compatible with considering the deposit as a uniform spherical layer all over the collector's surface. The predictions of the model agreed well with data from several clogging experiments for which various operating conditions were used, i.e., different collector's diameters, particulate materials or superficial velocities.

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Simulation of the dynamics of depth filtration of non‐Brownian particles

Abstract: A new simulator for flow of aqueous suspensions and deposition of non-Brownian particles in granular media

Cited by 29 publications

References 59 publications

Hierarchical simulator of biofilm growth and dynamics in granular porous materials

Hierarchical simulator of biofilm growth and dynamics in granular porous materials

Filtration in a Porous Granular Medium: 2. Application of Bubble Model to 1-D Column Experiments

Modeling of the deep granular bed clogging by nanoparticles

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