Filtration in a Porous Granular Medium: 1. Simulation of Pore-Scale Particle Deposition and Clogging

Kim, Yun Sung; Whittle, Andrew J.

doi:10.1007/s11242-005-6087-2

Cited by 36 publications

(22 citation statements)

References 48 publications

(51 reference statements)

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…Removal of particles and flocs in the filter media depends on transport mechanisms that carry the solids through the water to the surface of the filter grains, and on retention of the solids by the medium once contact has occurred. Transport mechanisms include gravity settling, inertial impaction, diffusion of colloid, Brownian movement and van der Waals forces (Kim and Whittle, 2006). Retention of solids once contact has occurred can be attributed primarily to electrochemical forces, van der Waals force, and physical adsorption (Yaroshevskaya, 2007).…”

Section: Filtrationmentioning

confidence: 99%

Removal Capability of Carbon-Soil-Aquifer Filtering System in Water Microbiological Pollutants

Nik¹,

Rahman²,

Ahmad³

et al. 2012

Ecological Water Quality - Water Treatment and Reuse

View full text Add to dashboard Cite

Section: Filtrationmentioning

confidence: 99%

Removal Capability of Carbon-Soil-Aquifer Filtering System in Water Microbiological Pollutants

Nik¹,

Rahman²,

Ahmad³

et al. 2012

Ecological Water Quality - Water Treatment and Reuse

View full text Add to dashboard Cite

“…(1) particles that are larger than the bond become sieved and remain at site i (causing clogging of the bond); (2) infiltrated particles that are collected within the bonds (computed from pore flow models; Kim and Whittle, 2005); (3) particles that are transported to site (i + 1); and (4) particles that remain in suspension within the bonds (due to differences in velocity within bonds, Equation (3). Following Hwang and Redner (2001), this last group of particles is partitioned between particles that advance to site (i + 1) and those that remain at site i.…”

Section: Particle Transportmentioning

confidence: 99%

“…where P [Infiltration] denotes the probability of particle collection within the bond (this includes particles that are rejected due to mounding of deposits at the inlet; Kim and Whittle, 2005). More details on the modeling of infiltration are given in Section 3.2.…”

Section: Particle Transportmentioning

confidence: 99%

“…where p j is the differential pressure across the bond based on correlations from pore scale numerical simulations (Equation 27; Kim and Whittle, 2005). For the first bubble, i = 1, a fixed inflow probability density function is used.…”

Section: Particle Transportmentioning

confidence: 99%

“…In the current model, the bonds are cylindrical flow channels with radial dimensions selected to match the dimensions of the pores and pore throats within the glass bead filter bed. The model simulates processes of sieving and infiltration, making extensive use of the numerical simulations of particle collection and mounding presented in a companion paper (Kim and Whittle, 2005). Observations of particle attachment and detachment processes (reported by Yoon et al, 2005) are incorporated directly in the bubble model enabling more realistic modeling of the spatial distribution of particles within the filter than can be achieved using continuum formulations.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

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

Kim¹,

Whittle

2006

Transp Porous Med

Self Cite

View full text Add to dashboard Cite

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.

show abstract

Pore‐network modeling of particle retention in porous media

Yang

Balhoff

2017

AIChE Journal

View full text Add to dashboard Cite

Transport and filtration of micron and submicron particles in porous media is important in applications such as water purification, contaminants dispersion, and drilling mud invasion. Existing macroscopic models often fail to be predictive without empirical adjustments and a more fundamental approach may be required. We develop a physically‐representative, 3D pore network model based on a particle tracking method to simulate particle retention and permeability impairment in polydisperse particle systems. The model includes the effect of hydraulic drag, gravity, electrostatic and van der Waals forces, as well as Brownian motion. A converging‐diverging pore throat geometry is used to capture the mechanism of interception. With the analytical solution of fluid velocity within a pore throat, the trajectory of each particle is calculated explicitly. We also incorporate surface roughness and particle–surface interaction to determine particle attachment and detachment. Pore throat structure and conductivity are updated dynamically to account for the effect of deposited particles. Predictions of effluent concentration and macroscopic filtration coefficient are in good agreement with published experimental data. We find that the filtration coefficient is dependent on the relative angle between fluid flow and gravity. Particle deposition by interception is significant for large particle/grain size ratios. Brownian diffusion is the primary cause of retention at low Peclet numbers, especially for small gravity numbers. Particle size distribution is found to be a cause of hyperexponential deposition often observed in experiments. Permeability reduction was small for strong repulsive forces because particles only deposited in paths of slow velocity. © 2017 American Institute of Chemical Engineers AIChE J, 63: 3118–3131, 2017

show abstract

Filtration in a Porous Granular Medium: 1. Simulation of Pore-Scale Particle Deposition and Clogging

Cited by 36 publications

References 48 publications

Removal Capability of Carbon-Soil-Aquifer Filtering System in Water Microbiological Pollutants

Removal Capability of Carbon-Soil-Aquifer Filtering System in Water Microbiological Pollutants

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

Pore‐network modeling of particle retention in porous media

Contact Info

Product

Resources

About