The effect of variable yield strength and variable fractal dimension on flocculation of cohesive sediment

Son, Minwoo; Hsu, Tian‐Jian

doi:10.1016/j.watres.2009.05.016

Cited by 79 publications

(108 citation statements)

References 47 publications

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“…Therefore, the flocculation process has been intensively studied. The flocculation process is mainly due to eletro-or biological-chemical attraction of fine sediment (e.g., [1]). When suspended particles collide with each other, there is a chance of aggregation by attraction.…”

Section: Introductionmentioning

confidence: 99%

“…It has been concluded in many studies that turbulent shear is the dominant mechanism of suspended sediment collisions (e.g., [5,6]). Moreover, turbulent shear is considered as the main mechanism of floc breakup (e.g., [1,7,8]). Many laboratory studies on the effects of turbulent shear have been conducted utilizing a mixing tank and Couette viscometer in order to control the intensity of turbulent shear (e.g., [9][10][11][12]).…”

Section: Introductionmentioning

confidence: 99%

“…However, neither Son and Hsu [7] nor Winterwerp [8] appropriately address the temporal evolution of floc size, although both calculate the equilibrium floc size under constant turbulence intensity conditions. Son and Hsu [1] further theoretically and mathematically derive an equation for the yield strength of flocs, which depends on the floc size and fractal dimension. The equation is similar to an empirical equation from Sonntag and Russel [22] when one empirical parameter, r, is set to be about 0.7 (see [1] for more details).…”

Section: Introductionmentioning

confidence: 99%

“…Son and Hsu [1] further theoretically and mathematically derive an equation for the yield strength of flocs, which depends on the floc size and fractal dimension. The equation is similar to an empirical equation from Sonntag and Russel [22] when one empirical parameter, r, is set to be about 0.7 (see [1] for more details). By incorporating this equation with a FGM from Son and Hsu [7], Son and Hsu [1] propose a new FGM using a variable fractal dimension and yield strength.…”

Section: Introductionmentioning

confidence: 99%

“…The equation is similar to an empirical equation from Sonntag and Russel [22] when one empirical parameter, r, is set to be about 0.7 (see [1] for more details). By incorporating this equation with a FGM from Son and Hsu [7], Son and Hsu [1] propose a new FGM using a variable fractal dimension and yield strength. The model from Son and Hsu [1] has been validated with laboratory experiments by Spice et al [23] and Burban et al [24].…”

Section: Introductionmentioning

confidence: 99%

See 4 more Smart Citations

Stochastic Flocculation Model for Cohesive Sediment Suspended in Water

Shin

Son

Lee

2015

Water

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Existing flocculation models for cohesive sediments are classified into two groups: population balance equation models (PBE) and floc growth models. An FGM ensures mass conservation in a closed system. However, an FGM determines only the average size of flocs, whereas a PBE has the capability to calculate a size distribution of flocs. A new stochastic approach to model the flocculation process is theoretically developed and incorporated into a deterministic FGM in this study in order to calculate a size distribution of flocs as well as the average size. A log-normal distribution is used to generate random numbers based on previous laboratory experiments. The new stochastic flocculation model is tested with three laboratory experiment results. It was found and validated with measured data that the new stochastic flocculation model has the capability to replicate a size distribution of flocs reasonably well under different sediment and carrier flow conditions. Three more distributions (normal; Pearson type 3; and generalized extreme value distributions) were also tested. From the comparison with results of different distribution functions, it is shown that a stochastic FGM using a log-normal distribution has a comparative advantage in terms of simplicity and accuracy.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Stochastic Flocculation Model for Cohesive Sediment Suspended in Water

Shin

Son

Lee

2015

Water

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On effects of skewed and asymmetric oscillatory flows on cohesive sediment flux: Numerical study

Son

Lee

2013

Water Resources Research

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[1] To investigate the effects of wave shape on cohesive sediment flux in shallow water environments, a one-dimensional vertical (1DV) model for cohesive sediment transport previously validated with field measurement is applied to conditions of skewed and asymmetric oscillatory flows. Cohesive sediments usually portray behaviors different from those of noncohesive sediments. This is mainly due to the flocculation process through which the density and the size of cohesive sediment change continuously. Therefore, a robust flocculation model is incorporated with a 1DV model in this study. Under the condition of skewed oscillatory flow (second-order Stokes wave-type oscillatory flow), the flux of cohesive sediment is significantly affected by the change of flow skewness, whereas the flux of noncohesive sediment of which size is 100 mm does not show a clear relationship with skewness. Under the condition of forward-leaning asymmetric oscillatory flow (sawtooth wave-type oscillatory flow), the direction of cohesive sediment flux is negative, whereas the flux of noncohesive sediment shows the positive direction. The phase-lag effect is considered as the main mechanism of these behaviors. The interactional relationship between the settling velocity, the variation of concentration profile, and hydrodynamics of carrier fluid enhances the phase-lag effect and causes different behaviors in cohesive sediment compared to the flux of fine noncohesive sediment.

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On the variability of near-bed floc size due to complex interactions between turbulence, SSC, settling velocity, effective density and the fractal dimension of flocs

Yang

Wang

et al. 2016

Geo-Mar Lett

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Interactions between turbulence, suspended sediment concentration (SSC), settling velocity, effective density, fractal dimension, and floc size were studied on the tide-dominated, muddy coastal shelf of the southwestern Yellow Sea, China. The measurements were carried out in July 2013 at two sites located in water depths of 21.2 and 22.1 m. Negative correlations were observed between shear rate, SSC, effective density, and mean floc size, which supports the results of previous numerical, experimental, and field studies. A significant positive correlation was observed between near-bed SSC and shear rate, an indication that SSC variations are controlled by turbulence and re-suspension. In addition, significant linear relationships were found between settling velocity and other parameters (floc size, turbulence, SSC, effective density, and fractal dimension) at the two sites, indicating that the controlling factors on settling velocity are spatially variable. Principal component analysis was applied to determine the relative importance of turbulence, flocculation ability, and SSC as controls on floc size in situ. The relative contributions of turbulence, flocculation ability, and SSC to floc size (at both sites) were~33.0%, 30.3%, and 29.7%, respectively, this being a new field-based quantitative analysis of the controls on floc size. The findings demonstrate that, in nature, flocculation ability affects floc size to the same degree as turbulence and SSC. Therefore, predictions of floc size in coastal marine environments require constraints not only on turbulence and SSC, but also on flocculation ability.

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The effect of variable yield strength and variable fractal dimension on flocculation of cohesive sediment

Cited by 79 publications

References 47 publications

Stochastic Flocculation Model for Cohesive Sediment Suspended in Water

Stochastic Flocculation Model for Cohesive Sediment Suspended in Water

On effects of skewed and asymmetric oscillatory flows on cohesive sediment flux: Numerical study

On the variability of near-bed floc size due to complex interactions between turbulence, SSC, settling velocity, effective density and the fractal dimension of flocs

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