Dispersion of components in transport processes: Velocity dispersion model

Pivovarov, S.

doi:10.1016/j.jcis.2005.04.060

Cited by 4 publications

(4 citation statements)

References 7 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…This behaviour has also been observed experimentally by Semra et al (2008). The authors defined a reactive dispersivity which value was increasing with heterogeneity for the same column size, and seemed to reach a limit value in the same way that hydrodynamic dispersivity increases to achieve the elementary representative volume for a specified sample size (Pivovarov, 2005). Hence, the reactive dominant dispersivity into heterogeneous media, function only of hydrodynamics and activity distribution, is as scale dependant as the hydrodynamic dispersivity.…”

Section: Derivation Of Breakthrough Curve Moments Using the Van Der Lsupporting

confidence: 68%

See 1 more Smart Citation

A New Mixing-Cell-in-Series Model to Predict Breakthrough Curve in Chemically Heterogeneous Media at Column Scale

Semra¹,

Simonnot²

2009

Chemical Product and Process Modeling

View full text Add to dashboard Cite

International audienceThe paper aims at modelling linearly adsorbed solute breakthrough curves into chemically heterogeneous media at column scale. The model was developed according to the mixing-cell-in-series approach and provided a general expression of the reduced variance for either water tracer or linearly adsorbed solute into either chemically homogeneous or heterogeneous medium. According to the experimental investigation of Semra et al. (2008), medium activity was assumed discrete with a known mean capacity. The chemical heterogeneity scale was assessed by the inverse of the ratio of active grains number to the total grains one. Discussion of the heterogeneous model results was accomplished considering breakthrough curve moments. Moment analysis showed that respective effects of interaction and transport are no longer independent from each other even when adsorption is linear. For a constant mean capacity and a constant hydrodynamic dispersion, the effective dispersion, accounted for by the temporal reduced variance, increases linearly with the chemical heterogeneity scale and the breakthrough spreading increase is favoured by high capacities. Moreover, mathematical form of the reduced variance predicts asymmetric breakthrough curves even in the case of equilibrium assumption. Considering kinetics, the model shows additive but independent effects of kinetics and hydrodynamics as in the case of chemically homogeneous media; it shows also independent kinetic effects from heterogeneity. Finally, modelling results were coherent with experimental observations made by Semra et al

show abstract

Section: Derivation Of Breakthrough Curve Moments Using the Van Der Lsupporting

confidence: 68%

“…It corresponds to the hydrodynamic dispersivity, α L , defined as the size above which, for a certain medium dimension, hydrodynamic parameters become constant. α L is related to the hydrodynamic dispersion by equation (23) (Zheng and Bennet, 1995;Banton and Bangoy, 1997;Pivovarov, 2005):…”

Section: Dominanting Heterogeneity Scalementioning

confidence: 99%

A New Mixing-Cell-in-Series Model to Predict Breakthrough Curve in Chemically Heterogeneous Media at Column Scale

Semra¹,

Simonnot²

2009

Chemical Product and Process Modeling

View full text Add to dashboard Cite

show abstract

“…This behavior means that the activity dispersivity is greater than the hydrodynamic one and is not only related to grain size distribution but depends also on the chemical heterogeneity scale. Chemical activity dispersivity seems to be the dominant heterogeneity scale and behaves as the hydrodynamic one that numerical values correlate with the scale of the experiment 1, 15, 16, 21, 22. So, chemical activity dispersivity seems also to be scale‐dependent as it has quickly achieved a limit value.…”

Section: Resultsmentioning

confidence: 89%

Effect of chemical heterogeneity on adsorbed solute dispersion at column scale

Semra

Simonnot

2008

AIChE Journal

View full text Add to dashboard Cite

in Wiley InterScience (www.interscience.wiley.com).Chemical heterogeneity seems to be responsible for spreading increase of adsorbed solute breakthrough curves. Adsorption in fixed beds assumes chemically homogeneous media. However, this is not always true, in particular when natural sands or mixed adsorbent filters are used in drinking water purification. Neglecting eventual effect of chemical heterogeneity may engender false modeling bases. So, considering homogeneous grain size distribution, the effect of chemical heterogeneity on global dispersion in porous media has been investigated experimentally in this article at column scale. Breakthroughs of adsorbed solute showed a visible effect of chemical heterogeneity on solute global dispersion increasing. The more heterogeneous the medium, the more spread the adsorbed solute breakthrough. Reduced variance showed a linear variation with the chemical heterogeneity scale at closely constant media global capacity. A pseudo-homogeneous model has been developed to simulate experimental data by increasing dispersion parameter.

show abstract

“…Furthermore, the dispersion coefficient is proportional to velocity. According to Pivovarov (2005), the increase of velocity led to increase dispersion, and consequently cause the higher dispersion coefficient. These results indicate that the dispersion coefficient can be predicted using the velocity and the optimal tank number N, which are obtained from NTIS model.…”

Section: Resultsmentioning

confidence: 99%

A new methodology for determining dispersion coefficient using ordinary and partial differential transport equations

Lee

Ham

Hwang

et al. 2009

Water Science and Technology

View full text Add to dashboard Cite

The present study proposes a methodology for determining the effective dispersion coefficient based on the field measurements performed in Gwangju (GJ) Creek in South Korea which is environmentally degraded by the artificial interferences such as weirs and culverts. Many previous works determining the dispersion coefficient were limited in application due to the complexity and artificial interferences in natural stream. Therefore, the sequential combination of N-Tank-In-Series (NTIS) model and Advection-Dispersion-Reaction (ADR) model was proposed for evaluating dispersion process in complex stream channel in this study. The series of water quality data were intensively monitored in the field to determine the effective dispersion coefficient of E. coli in rainy day. As a result, the suggested methodology reasonably estimates the dispersion coefficient for GJ Creek with 1.25 m(2)/s. Also, the sequential combined method provided Number of tank-Velocity-Dispersion coefficient (NVD) curves for convenient evaluation of dispersion coefficient of other rivers or streams. Comparing the previous studies, the present methodology is quite general and simple for determining the effective dispersion coefficients which are applicable for other rivers and streams.

show abstract

Dispersion of components in transport processes: Velocity dispersion model

Cited by 4 publications

References 7 publications

A New Mixing-Cell-in-Series Model to Predict Breakthrough Curve in Chemically Heterogeneous Media at Column Scale

A New Mixing-Cell-in-Series Model to Predict Breakthrough Curve in Chemically Heterogeneous Media at Column Scale

Effect of chemical heterogeneity on adsorbed solute dispersion at column scale

A new methodology for determining dispersion coefficient using ordinary and partial differential transport equations

Contact Info

Product

Resources

About