Mass transfer across the turbulent gas–water interface

Xu, Zhijie; Khoo, Boo Cheong; Carpenter, Keith

doi:10.1002/aic.10972

Cited by 30 publications

(20 citation statements)

References 23 publications

(36 reference statements)

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“…The results of b (Table 2) and K ref (column 1, Table 3) permit comparison of the present data with the surface divergence models. Figure 10 follows the graphs of Xu et al, 18 where K(Db) À1/2 is plotted against b. The shadowed areas correspond to the data of McKenna and McGillis 22 and those used by Xu et al 18 The data of Tamburrino and Gulliver, 17 Tamburrino et al, 19 Tamburrino and Aravena, 47 Herlina and Jirka, 34 and Xu et al 48 are plotted together with the present results.…”

Section: Evolution Of Integral Length Scales Along the Depthmentioning

confidence: 78%

“…Figure 10 follows the graphs of Xu et al, 18 where K(Db) À1/2 is plotted against b. The shadowed areas correspond to the data of McKenna and McGillis 22 and those used by Xu et al 18 The data of Tamburrino and Gulliver, 17 Tamburrino et al, 19 Tamburrino and Aravena, 47 Herlina and Jirka, 34 and Xu et al 48 are plotted together with the present results. It can be observed that the data from Herlina and Jirka 34 are comparable to the present data, although the transfer velocity was determined through long-time oxygen concentration measurements in the bulk liquid.…”

Section: Evolution Of Integral Length Scales Along the Depthmentioning

confidence: 78%

“…Various investigators have used a measured surface divergence to determine b 0 and predict K (Kumar et al, 15 Law et al, 16 Tamburrino and Gulliver, 17 Xu et al, 18 and Tamburrino et al 19 ). Law and Khoo, 20 using CO 2 and water with different concentrations of glycerol (to obtain different Schmidt, Sc ¼ m/D, numbers), proposed…”

mentioning

confidence: 98%

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Estimation of mass transfer velocity based on measured turbulence parameters

et al. 2009

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in Wiley InterScience (www.interscience.wiley.com).The aim of this study is to quantify the mass transfer velocity using turbulence parameters from simultaneous measurements of oxygen concentration fields and velocity fields. The surface divergence model was considered in more detail, using data obtained for the lower range of b (surface divergence). It is shown that the existing models that use the divergence concept furnish good predictions for the transfer velocity also for low values of b, in the range of this study. Additionally, traditional conceptual models, such as the film model, the penetration-renewal model, and the large eddy model, were tested using the simultaneous information of concentration and velocity fields. It is shown that the film and the surface divergence models predicted the mass transfer velocity for all the range of the equipment Reynolds number used here. The velocity measurements showed viscosity effects close to the surface, which indicates that the surface was contaminated with some surfactant. Considering the results, this contamination can be considered slight for the mass transfer predictions. V

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Section: Evolution Of Integral Length Scales Along the Depthmentioning

confidence: 78%

Section: Evolution Of Integral Length Scales Along the Depthmentioning

confidence: 78%

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Estimation of mass transfer velocity based on measured turbulence parameters

et al. 2009

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“…Classical mass transfer models include the two-film model (Lewis and Whitman, 1924), penetration theory (Higbie, 1935), surface renewal model (Danckwerts, 1951), film penetration model (Toor and Marchello, 1958) and eddy cell model (Lamont and Scott, 1970). Some more complex models were also proposed in recent years, e.g., the surfacerenewal-stretch model (Jajuee et al, 2006), and model based on the vertical velocity gradient at the interface (Xu et al, 2006). More comprehensive summary of the mass transfer models is referred to the publications by Jajuee et al (2006) and by Kulkarni (2007).…”

Section: Introductionmentioning

confidence: 98%

Numerical simulations of gas–liquid mass transfer in bubble columns with a CFD–PBM coupled model

Wang¹,

Wang²

2007

Chemical Engineering Science

165

109

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“…The latter is the predominant driving force of gas exchange in a water column. Comprehensive review and investigation of this phenomenon can be found in Brumley and Jirka, 2 Gulliver and Halverson, 12 Isaacs and Gaudy, 16 Jirka and Ho, 21 Moog and Jirka, 28 Chu and Jirka, 3 Tamburrino and Gulliver, 31 Xu et al, 35 and Herlina and Jirka.…”

Section: Introductionmentioning

confidence: 98%

Effect of waves on reaeration

Nguyen

Tan²

2013

AIChE Journal

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Mechanically generated surface waves and their influence on oxygen transfer were investigated. The experiments were conducted in a reaeration column (Reynolds number from 125-937). The water surface was set in oscillatory motion to simulate periodic surface level fluctuation. The wave frequency used ranged from 0.125 Hz to 0.425 Hz for various wave heights ranging from 0.15 cm to 1.5 cm. After bleeding the water column with nitrogen, dissolved oxygen concentration was measured over time below the water surface. A modified surface renewal model was proposed and found to describe the oxygen transfer phenomenon well. In addition, it was found that the mean film thickness d D , may be used as the characteristic length to describe the reaeration process under the influence of small perturbation and surface water waves. The proposed model was also extended to include the reaeration process under larger waves reported by other researchers.

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Mass transfer across the turbulent gas–water interface

Cited by 30 publications

References 23 publications

Estimation of mass transfer velocity based on measured turbulence parameters

Estimation of mass transfer velocity based on measured turbulence parameters

Numerical simulations of gas–liquid mass transfer in bubble columns with a CFD–PBM coupled model

Effect of waves on reaeration

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