scholarly journals A Study on the Measurement of Bubble Size Distribution in the Upward Bubbly Flow

1984 ◽  
Vol 27 (228) ◽  
pp. 1127-1135
Author(s):  
Shigeru HINATA
Keyword(s):  
Size Distribution ◽  
Bubble Size ◽  
Bubbly Flow ◽  
Bubble Size Distribution

An Optical Method for Determining Bubble Size Distributions—Part I:Theory

1988 ◽  
Vol 110 (3) ◽  
pp. 325-331 ◽  
Author(s):  
P. R. Meernik ◽  
M. C. Yuen
Keyword(s):  
Statistical Analysis ◽  
Size Distribution ◽  
Bubble Size ◽  
Bubbly Flow ◽  
Bubble Size Distribution ◽  
Phase Flow ◽  
Size Distributions ◽  
Optical Technique ◽  
Narrow Beam ◽  
Two Phase

A new optical technique is developed to determine the size distribution of bubbles in a two-phase flow. Implementation involves passing a narrow beam of light through the bubbly flow and monitoring the transmitted light intensity. The basic units of data are the rate at which each bubble blocks off the beam and the duration of blockage. Adding the hypothesis that the distance of closest approach between a bubble’s center and the beam axis is randomly distributed, a statistical analysis yields the bubble size distribution.

Numerical Simulation of Heterogeneous Bubbly Flow in a Bubble Column

2006 ◽  
Author(s):  
Munenori Maekawa ◽  
Naoki Shimada ◽  
Kouji Kinoshita ◽  
Akira Sou ◽  
Akio Tomiyama
Keyword(s):  
Size Distribution ◽  
Bubble Size ◽  
Bubble Column ◽  
Fluid Model ◽  
Bubbly Flow ◽  
Bubble Size Distribution ◽  
Bubbly Flows ◽  
Bubble Coalescence ◽  
Size Distributions ◽  
Bubble Sizes

Numerical methods for predicting heterogeneous bubbly flows are indispensable for the design of a Fisher-Tropsh reactor for GTL (Gas To Liquid). It is necessary to take into account bubble size distribution determined by bubble coalescence and breakup for the accurate prediction of heterogeneous bubbly flows. Hence we implemented several bubble coalescence and breakup models into the (N+2) field model, which is a hybrid combination of an interface tracking method and a multi-fluid model. Void and bubble size distributions in an open rectangular bubble column were measured and compared with predicted ones. As a result, the following conclusions were obtained: (1) Void and bubble size distributions were not affected by inlet bubble sizes because the bubble size distribution reaches an equilibrium state at which the birth rate is equal to the death rate, and (2) the combination of Luo’s bubble breakup model and a coalescence model consisting of Prince & Blanch’s model and Wang’s wake entrainment model gave good predictions.

Hybrid Eulerian Eulerian Discrete Phase Model of Turbulent Bubbly Flow

2017 ◽  
Author(s):  
Hyunjin Yang ◽  
Surya P. Vanka ◽  
Brian G. Thomas
Keyword(s):  
Size Distribution ◽  
Bubble Size ◽  
Bubbly Flow ◽  
Bubble Size Distribution ◽  
Turbulent Dispersion ◽  
Phase Model ◽  
Discrete Phase Model ◽  
Local Bubble ◽  
Discrete Phase ◽  
Bubble Sizes

The Eulerian-Eulerian two-fluid model [1] (EE) is the most general model in multiphase flow computations. One limitation of the EE model is that it has no ability to estimate the local bubble sizes by itself. Thus, it must be complemented either by measurements of bubble size distribution or by additional models such as population balance theory or interfacial area concentration to get the local bubble size information. In this work, we have combined the Discrete Phase model (DPM) [2,8] to estimate the evolution of bubble sizes with the Eulerian-Eulerian model. The bubbles are tracked individually as point masses, and the change of bubble size distribution is estimated by additional coalescence and breakup modeling of the bubbles. The time varying bubble distribution is used to compute the local interface area between gas and liquid phase, which is used to estimate the momentum interactions such as drag, lift, wall lubrication and turbulent dispersion forces. This model is applied to compute an upward flowing bubbly flow in a vertical pipe and the results are compared with previous experimental work of Hibiki et al. [3]. The newly developed hybrid model (EEDPM) is able to reasonably predict the locally different bubble sizes and the velocity and void fraction fields. On the other hand, the standard EE model without the DPM shows good comparison with measurements only when the prescribed constant initial bubble size is accurate and does not change much.

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.

Sign in / Sign up

Export Citation Format

Share Document