Models for effective density and settling velocity of flocs

Khelifa, Ali; Hill, Paul S.

doi:10.1080/00221686.2006.9521690

Cited by 223 publications

(245 citation statements)

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“…In order to show the usefulness of eqn (9), a summary of fl oc settling velocities from the scientifi c literature summarized by Khelifa and Hill [16] were plotted in log-log paper. It is shown that eqn (9) is able to reproduce the general trend (Fig.…”

Section: Resultsmentioning

confidence: 99%

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A model for the settling velocity of flocs; application to an aquaculture recirculation tank

García-Aragón¹,

Salinas-Tapia²,

Moreno-Guevara³

et al. 2014

Int. J. CMEM

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A general model for fl ocs settling velocity is still an open fi eld of research in the scientifi c literature. In this work, a reduced model of an aquaculture recirculation tank was used to validate a model for fl oc settling velocity. Cohesive sediments from non-used food and fi sh excreta are a main concern in those tanks design. Excess concentrations of sediments can cause fi sh death or additional costs of energy for aeration. This research is aimed to understand the settling behavior of fl ocs when subjected to a liquid shear rate. A reduced scale model of an aquaculture recirculation tank was build in Plexiglas in order to use particle image velocimetry and particle tracking velocimetry techniques to measure fl uid velocities, solid settling velocities, fl ocs shape and size.Different fl ow rates and solid concentrations were used to develop varied confi gurations in the system; models for fl oc settling velocity based on fractal theory were calibrated. Cohesive sediments from fi sh food were observed in long-term experiments at constant fl uid shear rate in the recirculation tank. A group of 50 images were obtained for every 5 min. Image analysis provided us with fl oc settling velocity data and fl oc size. Using fl oc settling velocity data, fl oc density was obtained for different diameters at equilibrium conditions, after 1 h or larger experiments. Statistical analysis of fl oc velocities for different fl oc sizes allowed us to obtain an expression for the drag coeffi cient as a function of fl oc particle Reynolds number (R ep ). The results were compared with fl oc settling velocity results from different researchers. The model is able to defi ne the general behavior of fl oc settling velocity, which shows a reduction for larger fl ocs that is not taken into account in classical models. Only two parameters of the drag coeffi cient model for a permeable spherical particle are needed to be calibrated, for different types of sediments, in order to have more general applicability.

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Section: Resultsmentioning

confidence: 99%

“…Experimental data of cohesive sediments available in the scientifi c literature [13][14][15][16] were compared with the model developed in this research. The proposed model is shown to be able to reproduce these results if a calibration of the parameters defi ning the drag coeffi cient for permeable particles is properly done.…”

Section: Introductionmentioning

confidence: 99%

A model for the settling velocity of flocs; application to an aquaculture recirculation tank

García-Aragón¹,

Salinas-Tapia²,

Moreno-Guevara³

et al. 2014

Int. J. CMEM

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“…Most of these experiments have been performed on agglomerates with single-sized primary particles. There is also work indicating that in some cases, the fractal dimension decreases as the agglomerate size increases (Khelifa and Hill 2006), and there is a maximum agglomerate size that can be attained under shear (Selomnlya et al 2003). Models relating the effect of shearing on the maximum agglomerate size are presented in .…”

Section: Fractal Dimension Basismentioning

confidence: 99%

Hanford Waste Physical and Rheological Properties: Data and Gaps

Wells¹,

Kurath²,

Mahoney³

et al. 2011

103

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Executive SummaryThe Hanford Site in Washington State manages 177 underground storage tanks containing approximately 250,000 m 3 of waste generated during past defense reprocessing and waste management operations. These tanks contain a mixture of sludge, saltcake and supernatant liquids. The insoluble sludge fraction of the waste consists of metal oxides and hydroxides and contains the bulk of many radionuclides such as the transuranic components and 90 Sr. The saltcake, generated by extensive evaporation of aqueous solutions, consists primarily of dried sodium salts. The supernates consist of concentrated (5-15 M) aqueous solutions of sodium and potassium salts. The 177 storage tanks include 149 single-shell tanks (SSTs) and 28 double-shell tanks (DSTs).Ultimately the wastes need to be retrieved from the tanks for treatment and disposal. The SSTs contain minimal amounts of liquid wastes, and the Tank Operations Contractor is continuing a program of moving solid wastes from SSTs to interim storage in the DSTs. The Hanford DST system provides the staging location for waste feed delivery to the Department of Energy (DOE) Office of River Protection's (ORP) Hanford Tank Waste Treatment and Immobilization Plant (WTP). The WTP is being designed and constructed to pretreat and then vitrify a large portion of the wastes in Hanford's 177 underground waste storage tanks.The retrieval, transport, treatment and disposal operations involve the handling of a wide range of slurries. Solids in the slurry have a wide range of particle size, density and chemical characteristics. Depending on the solids concentration the slurries may exhibit a Newtonian or a non-Newtonian rheology.The extent of knowledge of the physical and rheological properties is a key component to the success of the design and implementation of the waste processing facilities. These properties are used in engineering calculations in facility designs. Knowledge of the waste properties is also necessary for the development and fabrication of simulants that are used in testing at various scales. The expense and hazards associated with obtaining and using actual wastes dictates that simulants be used at many stages in the testing and scale-up of process equipment. The results presented in this report should be useful for estimating process and equipment performance and provide a technical basis for development of simulants for testing.The purpose of this document is to provide an updated summary of the Hanford waste characterization data pertinent to safe storage, retrieval, transport and processing operations for both the tank farms and the WTP and thereby identify gaps in understanding and data. Important waste parameters for these operations are identified by examining examples of relevant mathematical models of selected phenomena including: The data sets in (UDS composition and particle density, UDS primary particle size and shape, UDS particle size distributions [PSDs], and estimated particle size and density distributions [PSDDs]) and Poloski et al. (2007) ...

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“…Modelling of the particle settling processes relies on the understanding of the dynamics of the flocculation system, variability of sediment concentration and composition, floc size, microbiological activity, salinity and temperature (Khelifa and Hill, 2006). Most current models assume a one-dimensional flow of particles in space and are therefore modelled by a set of linear differential equations.…”

Section: Theoretical Backgroundmentioning

confidence: 99%

A finite velocity simulation of sedimentation behaviour of flocculating particles – A real-time model evaluation

Sithebe¹,

Methula²,

Chirwa³

2014

WSA

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A mechanistic velocity model is developed to simulate the behaviour of flocculating colloidal particles in turbid water. The current model is based on one-dimensional mass transport in the vertical direction as an integrated form of the model derived by Ramatsoma and Chirwa. The percentile removal model achieved more accurate simulation of physical experimental data than known models such as the Ozer's model and San's model. In this study, an integrated velocity form was used to estimate flocculent settling velocity of fine suspended particles under near quiescent conditions. Model closeness to experimental measurements was determined as a function of the sum of squares error (SSE) between model data and experimental data. The proposed velocity model offers a distinctive advantage over the interpolated-isopercentile based models which are prone to numerical errors during interpolation. The results contribute towards the ultimate goal of achieving full automation of the design of gravitational particle separation devices for water and wastewater treatment.

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Models for effective density and settling velocity of flocs

Cited by 223 publications

References 50 publications

A model for the settling velocity of flocs; application to an aquaculture recirculation tank

A model for the settling velocity of flocs; application to an aquaculture recirculation tank

Hanford Waste Physical and Rheological Properties: Data and Gaps

A finite velocity simulation of sedimentation behaviour of flocculating particles – A real-time model evaluation

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