General correlation equations for predicting filtration efficiency under unfavorable surface interactions

Chang, Yu‐Wei; Cheng, Wenli; Liao, Keng-Yi

doi:10.1016/j.jtice.2017.04.031

Cited by 2 publications

(1 citation statement)

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“…Colloid filtration theory (CFT) is usually used to describe colloid attachment at the pore‐scale using the collection efficiency ( η , [‐]) and the sticking efficiency ( α , [‐]) (Chang et al., 2017; Tufenkji & Elimelech, 2004). The value of η is related to the mass transfer rate of colloids from the bulk solution to the SWI.…”

Section: Introductionmentioning

confidence: 99%

Simulation of Colloid Transport and Retention Using a Pore‐Network Model With Roughness and Chemical Heterogeneity on Pore Surfaces

Lin

Bradford

et al. 2021

Water Resources Research

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Colloid transport and retention in porous media is a common phenomenon in both nature and industry. However, many questions remain on how to obtain colloid transport and retention parameters. Previous work usually assumed constant transport parameters in a medium under a given physicochemical condition. In this study, pore‐network modeling is employed to upscale colloid transport and retention from the pore‐scale to the macro‐scale. The pore‐scale transport parameters including the collection efficiency (η), the sticking efficiency (α), and the fraction of the solid‐water interface that contributes to the colloid attachment (Sf) are obtained using numerical simulation and probability analysis for each pore throat. The influence of roughness and charge heterogeneity on the distribution of pore‐scale parameters is discussed. Breakthrough curves and the retention profiles under different roughness and charge heterogeneity conditions are also analyzed. Results show that pore‐scale parameters η, α, and Sf have various distributions in porous media that may not be accurately described using single‐valued effective parameters. The value of η decreases with velocity and exhibits a wide distribution under low‐velocity conditions. The parameter α tends to decrease with the colloid size and the pore water velocity and increased with the charge heterogeneity fraction. Nanoscale roughness alters α in a non‐monotonic fashion but tends to increase for lower roughness fractions and zeta potential. Microscopic roughness increases values of α for colloids that would otherwise be susceptible to hydrodynamic removal. Breakthrough curves and retention profiles show that more retention occurs for smaller particles, which reflects the influence of blocking.

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Section: Introductionmentioning

confidence: 99%