Deep bed filtration: Mathematical models and observations

Jegatheesan, V; Vigneswaran, S

Deep bed filtration: Mathematical models and observations

Jegatheesan, V Vigneswaran, S

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Publication Type:: Journal Article
Citation:: Critical Reviews in Environmental Science and Technology, 2005, 35 (6), pp. 515 - 569
Issue Date:: 2005-11-01

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Field	Value	Language
dc.contributor.author	Jegatheesan, V	en_US
dc.contributor.author	Vigneswaran, S https://orcid.org/0000-0002-8117-4322	en_US
dc.date.issued	2005-11-01	en_US
dc.identifier.citation	Critical Reviews in Environmental Science and Technology, 2005, 35 (6), pp. 515 - 569	en_US
dc.identifier.issn	1064-3389	en_US
dc.identifier.uri	http://hdl.handle.net/10453/3676
dc.description.abstract	Numerous mathematical models have been developed to evaluate both initial and transient stage removal efficiency of deep bed filters. Microscopic models either using trajectory analysis or convective-diffusion equations were used to compute the initial removal efficiency. These models predicted the removal efficiency under favorable filtration conditions quantitatively, but failed to predict the removal efficiency under unfavorable conditions. They underestimated the removal efficiency under unfavorable conditions. Thus, semi-empirical formulations were developed to compute initial removal efficiencies under unfavorable conditions. Also, correction for the adhesion of particles onto filter grains improved the results obtained for removal efficiency from the trajectory analysis. Macroscopic models were used to predict the transient stage removal efficiency of deep bed filters. The O'Melia and Ali1 model assumed that the particle removal is due to filter grains as well as the particles that are already deposited onto the filter grain. Thus, semi-empirical models were used to predict the ripening of filtration. Several modifications were made to the model developed by O'Melia and Ali to predict the deterioration of particle removal during the transient stages of filtration. Models considering the removal of particles under favorable conditions and the accumulation of charges on the filter grains during the transient stages were also developed. This article evaluates those models and their applicability under different operating conditions of filtration. Copyright © Taylor & Francis Inc.	en_US
dc.relation.ispartof	Critical Reviews in Environmental Science and Technology	en_US
dc.relation.isbasedon	10.1080/10643380500326432	en_US
dc.subject.classification	Environmental Sciences	en_US
dc.title	Deep bed filtration: Mathematical models and observations	en_US
dc.type	Journal Article
utslib.citation.volume	6	en_US
utslib.citation.volume	35	en_US
utslib.for	090407 Process Control and Simulation	en_US
utslib.for	090404 Membrane and Separation Technologies	en_US
utslib.for	090409 Wastewater Treatment Processes	en_US
pubs.embargo.period	Not known	en_US
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology/School of Civil and Environmental Engineering
pubs.organisational-group	/University of Technology Sydney/Strength - CTWW - Centre for Technology in Water and Wastewater Treatment
utslib.copyright.status	closed_access
pubs.issue	6	en_US
pubs.publication-status	Published	en_US
pubs.volume	35	en_US

Abstract:

Numerous mathematical models have been developed to evaluate both initial and transient stage removal efficiency of deep bed filters. Microscopic models either using trajectory analysis or convective-diffusion equations were used to compute the initial removal efficiency. These models predicted the removal efficiency under favorable filtration conditions quantitatively, but failed to predict the removal efficiency under unfavorable conditions. They underestimated the removal efficiency under unfavorable conditions. Thus, semi-empirical formulations were developed to compute initial removal efficiencies under unfavorable conditions. Also, correction for the adhesion of particles onto filter grains improved the results obtained for removal efficiency from the trajectory analysis. Macroscopic models were used to predict the transient stage removal efficiency of deep bed filters. The O'Melia and Ali1 model assumed that the particle removal is due to filter grains as well as the particles that are already deposited onto the filter grain. Thus, semi-empirical models were used to predict the ripening of filtration. Several modifications were made to the model developed by O'Melia and Ali to predict the deterioration of particle removal during the transient stages of filtration. Models considering the removal of particles under favorable conditions and the accumulation of charges on the filter grains during the transient stages were also developed. This article evaluates those models and their applicability under different operating conditions of filtration. Copyright © Taylor & Francis Inc.

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http://hdl.handle.net/10453/3676