scholarly journals Numerical Model and Validation for Cryogenic High-Speed Cavitating Flow Based on Bubble Size Distribution Model in Consideration of Rigorous Heat Transfer around Bubble and Bubble Oscillation

2008 ◽  
Vol 56 (657) ◽  
pp. 456-463
Author(s):  
Yutaka ITO
Keyword(s):  
Heat Transfer ◽  
Numerical Model ◽  
Size Distribution ◽  
Bubble Size ◽  
High Speed ◽  
Bubble Size Distribution ◽  
Cavitating Flow ◽  
Distribution Model ◽  
Bubble Oscillation

scholarly journals A Numerical Model for Bubble Size Distribution in Turbulent Gas-Liquid Dispersion

2010 ◽  
pp. 25-34 ◽  
Author(s):  
MAK Azad ◽  
Sultana R Syeda
Keyword(s):  
Numerical Model ◽  
Size Distribution ◽  
Bubble Size ◽  
Chemical Engineering ◽  
Narrow Range ◽  
Collision Frequency ◽  
Bubble Size Distribution ◽  
Operating Conditions ◽  
Liquid Dispersion ◽  
Bubble Collision

In present study a numerical model for bubble size distribution is developed that considers bothbreakage and coalescence in turbulent gas liquid dispersion. Two-step mechanisms are considered forboth breakage and coalescence of bubbles. The bubble breakage is structured as the product of thebubble-eddy collision frequency and breakage efficiency in gas-liquid dispersions. The coalescencefunction considers the product of bubble-bubble collision frequency and coalescence efficiency. Themodel overcomes several limitations observed in previous efforts such as empirical parameters,narrow range of operating conditions, and narrow range of geometries. Favorable agreement is foundbetween the predicted bubble size distribution and the experimental data reported in the literature. Thepercentage of error obtained for the average bubble size was found within ± 17%.Journal of Chemical Engineering Vol.ChE 24 2006 25-34

scholarly journals Experimental study on breakup of a single bubble in a stirred tank: Effect of gas density and liquid properties

2021 ◽  
Author(s):  
Huahai Zhang ◽  
Yuelin Wang ◽  
Ali Sayyar ◽  
Tiefeng Wang
Keyword(s):  
Size Distribution ◽  
Bubble Size ◽  
High Speed ◽  
Agitation Speed ◽  
Bubble Size Distribution ◽  
Stirred Tank ◽  
Single Bubble ◽  
Operating Pressure ◽  
Gas Density ◽  
Bubble Breakup

Bubble breakup plays an important role in gas-liquid flows, but detailed studies are still scarce. In this work, the breakup behavior of a single bubble in a stirred tank was experimentally studied with a high-speed camera, focusing on the effect of gas density, liquid properties, agitation speed and mother bubble size. The bubble breakup time, breakup probability, breakup rate and daughter bubble size distribution were determined. The internal flow phenomenon inside a deformed bubble was studied in detail, which accounted for the effect of gas density or operating pressure. The results showed that with increasing gas density, agitation speed, mother bubble size and decreasing surface tension, the bubble breakup rate and probability of equal-size distribution significantly increased. With increasing liquid viscosity, the bubble breakup rate decreased especially in the high viscosity range. An M-shaped daughter bubble size distribution was observed, which was consistent with our previous bubble breakup model.

scholarly journals Bubble Size Distribution Characteristics of a Jet-Stirring Coupling Flotation Device

Minerals ◽  
2019 ◽  
Vol 9 (6) ◽  
pp. 369 ◽  
Author(s):  
Youli Han ◽  
Jinbo Zhu ◽  
Liang Shen ◽  
Wei Zhou ◽  
Yunjia Ling ◽  
...  
Keyword(s):  
Size Distribution ◽  
Bubble Size ◽  
High Speed ◽  
Bubble Size Distribution ◽  
Sampling Location ◽  
Flotation Column ◽  
Flotation Cell ◽  
Positive Linear Correlation ◽  
Feeding Pressure ◽  
Pressure Suction

In this study, a new jet-stirring coupling flotation device that incorporates the advantages of three conventional flotation machines (specifically, Jameson cell, mechanical flotation cell, flotation column) was designed based on jet suction. The suction capacity of a double cosine self-aspirated nozzle utilized by the device was analyzed under different feeding pressures, and the effects of frother concentration, feeding pressure, suction capacity, and height of sampling location on the bubble size distribution (BSD) were investigated using a high-speed video system. It was found that a large amount of air was sucked into the flotation cell by the self-aspirated nozzle arranged in a non-submerged manner, which met the requirements of flotation in terms of the suction amount of air. The suction capacity showed a positive linear correlation with negative pressure inside the nozzle. When the Methyl isobutyl carbinol (MIBC) concentration reached the critical coalescence concentration (CCC), the bubble size stabilized at approximately 0.31 mm, which was smaller than the bubble size produced by the conventional flotation machine. This indicated that bubbles suitable for flotation were generated. D32 linearly decreased with increasing of feeding pressures and conversely increased with increasing suction capacities and sampling location heights, independent of the frother concentration.

Physiochemical properties and reproducibility of air-based sodium tetradecyl sulphate foam using the Tessari method

2016 ◽  
Vol 32 (6) ◽  
pp. 390-396 ◽  
Author(s):  
Mike R Watkins ◽  
Richard J Oliver
Keyword(s):  
Size Distribution ◽  
Bubble Size ◽  
Bubble Size Distribution ◽  
Foam Density ◽  
Physiochemical Properties ◽  
Significant Difference ◽  
Experienced Operator ◽  
Sodium Tetradecyl Sulphate ◽  
Foam Production ◽  
Made In

Objectives The objectives were to examine the density, bubble size distribution and durability of sodium tetradecyl sulphate foam and the consistency of production of foam by a number of different operators using the Tessari method. Methods 1% and 3% sodium tetradecyl sulphate sclerosant foam was produced by an experienced operator and a group of inexperienced operators using either a 1:3 or 1:4 liquid:air ratio and the Tessari method. The foam density, bubble size distribution and foam durability were measured on freshly prepared foam from each operator. Results The foam density measurements were similar for each of the 1:3 preparations and for each of the 1:4 preparations but not affected by the sclerosant concentration. The bubble size for all preparations were very small immediately after preparation but progressively coalesced to become a micro-foam (<250 µm) after the first 30 s up until 2 min. Both the 1% and 3% solution foams developed liquid more rapidly when made in a 1:3 ratio (37 s) than in a 1:4 ratio (45 s) but all combinations took similar times to reach 0.4 ml liquid formation. For all the experiments, there was no statistical significant difference between operators. Conclusions The Tessari method of foam production for sodium tetradecyl sulphate sclerosant is consistent and reproducible even when made by inexperienced operators. The best quality foam with micro bubbles should be used within the first minute after production.

scholarly journals Development of Bubble Characteristics on Chute Spillway Bottom

Water ◽  
2018 ◽  
Vol 10 (9) ◽  
pp. 1129
Author(s):  
Ruidi Bai ◽  
Chang Liu ◽  
Bingyang Feng ◽  
Shanjun Liu ◽  
Faxing Zhang
Keyword(s):  
Size Distribution ◽  
Bubble Size ◽  
Dissipation Rate ◽  
Bubble Diameter ◽  
Bubble Size Distribution ◽  
Impact Zone ◽  
Air Bubble ◽  
Air Supply ◽  
Bubble Characteristics ◽  
The Impact

Chute aerators introduce a large air discharge through air supply ducts to prevent cavitation erosion on spillways. There is not much information on the microcosmic air bubble characteristics near the chute bottom. This study was focused on examining the bottom air-water flow properties by performing a series of model tests that eliminated the upper aeration and illustrated the potential for bubble variation processes on the chute bottom. In comparison with the strong air detrainment in the impact zone, the bottom air bubble frequency decreased slightly. Observations showed that range of probability of the bubble chord length tended to decrease sharply in the impact zone and by a lesser extent in the equilibrium zone. A distinct mechanism to control the bubble size distribution, depending on bubble diameter, was proposed. For bubbles larger than about 1–2 mm, the bubble size distribution followed a—5/3 power-law scaling with diameter. Using the relationship between the local dissipation rate and bubble size, the bottom dissipation rate was found to increase along the chute bottom, and the corresponding Hinze scale showed a good agreement with the observations.

CFD Simulation of Gas Dispersion in a Stirred Tank of Dual Rushton Turbines

2017 ◽  
Vol 15 (4) ◽  
Author(s):  
Xinju Li ◽  
Xiaoping Guan ◽  
Rongtao Zhou ◽  
Ning Yang ◽  
Mingyan Liu
Keyword(s):  
Flow Field ◽  
Size Distribution ◽  
Liquid Flow ◽  
Bubble Size ◽  
Great Influence ◽  
Gas Holdup ◽  
Bubble Size Distribution ◽  
Stirred Tank ◽  
Treatment Methods ◽  
Gas Dispersion

Abstract3D Eulerian-Eulerian model was applied to simulate the gas-liquid two-phase flow in a stirred tank of dual Rushton turbines using computational fluid dynamics (CFD). The effects of two different bubble treatment methods (constant bubble sizevs. population balance model, PBM) and two different coalescence models (Luo modelvs. Zaichik model) on the prediction of liquid flow field, local gas holdup or bubble size distribution were studied. The results indicate that there is less difference between the predictions of liquid flow field and gas holdup using the above models, and the use of PBM did not show any advantage over the constant bubble size model under lower gas holdup. However, bubble treatment methods have great influence on the local gas holdup under larger gas flow rate. All the models could reasonably predict the gas holdup distribution in the tank operated at a low aeration rate except the region far from the shaft. Different coalescence models have great influence on the prediction of bubble size distribution (BSD). Both the Luo model and Zaichik model could qualitatively estimate the BSD, showing the turning points near the impellers along the height, but the quantitative agreement with experiments is not achieved. The former over-predicts the BSD and the latter under-predicts, showing that the existing PBM models need to be further developed to incorporate more physics.

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