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.

Two-Phase Flow and Bubble Size Distribution in Air-Sparged and Surface-Aerated Vessels Stirred by a Dual Impeller

2010 ◽  
Vol 49 (6) ◽  
pp. 2613-2623 ◽  
Author(s):  
Giuseppina Montante ◽  
Fabio Laurenzi ◽  
Alessandro Paglianti ◽  
Franco Magelli
Keyword(s):  
Size Distribution ◽  
Bubble Size ◽  
Two Phase Flow ◽  
Bubble Size Distribution ◽  
Phase Flow ◽  
Two Phase

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.

Study of Bubbly Flow Through a Packed Bed

2011 ◽  
Author(s):  
Daeseong Jo ◽  
Shripad T. Revankar
Keyword(s):  
Experimental Data ◽  
Comparative Study ◽  
Bubble Size ◽  
Bubbly Flow ◽  
Packed Bed ◽  
Bubble Coalescence ◽  
Size Distributions ◽  
Two Phase ◽  
Bubble Breakup ◽  
Flow Through

A two phase bubbly flow through a packed bed was studied for dominant bubble breakup and coalescence mechanisms through experiments and CFD modeling. Data on various two-phase parameters, such as local void fraction, bubble velocity, size, number, and shape were obtained from the high speed video images. Results indicated that when a flow regime changed from bubbly to either trickling or pulsing flow, the number of average size bubbles significantly decreased and the shape of majority of bubbles was no longer spherical. The bubble coalescence and breakup mechanisms depend on local conditions such as local velocity of the bubble and pore geometry. The CFD analysis using CFX software package was carried out to study bubble size distributions. In the analysis the models for interactions were examined for each case of bubble breakup flow and bubble coalescence. A comparative study was performed on the resulting bubble size distributions, breakup and coalescence rates estimated by individual models. For change of bubble size distributions along the axial direction medians was used as an comparative parameter and the CFD results on bubble medians were compared against the experimental data. This comparative study showed that the predictions estimated by CFD analyses with the bubble breakup and coalescence models currently available in the literature do not agree with the experimental data.

Predictive control of the bubble size distribution in a two-phase pilot flotation column

2016 ◽  
Vol 89 ◽  
pp. 71-76 ◽  
Author(s):  
A. Riquelme ◽  
A. Desbiens ◽  
R. del Villar ◽  
M. Maldonado
Keyword(s):  
Size Distribution ◽  
Predictive Control ◽  
Bubble Size ◽  
Bubble Size Distribution ◽  
Two Phase ◽  
Flotation Column

Modelling of the Bubble Size Distribution in an Aerated Stirred Tank: Theoretical and Numerical Comparison of Different Breakup Models

2014 ◽  
Vol 35 (3) ◽  
pp. 331-348 ◽  
Author(s):  
Zbyněk Kálal ◽  
Milan Jahoda ◽  
Ivan Fořt
Keyword(s):  
Size Distribution ◽  
Bubble Size ◽  
Water System ◽  
Secondary Phase ◽  
Bubble Size Distribution ◽  
Stirred Tank ◽  
Numerical Comparison ◽  
Size Distributions ◽  
Rushton Turbine ◽  
Breakup Model

Abstract The main topic of this study is the mathematical modelling of bubble size distributions in an aerated stirred tank using the population balance method. The air-water system consisted of a fully baffled vessel with a diameter of 0.29 m, which was equipped with a six-bladed Rushton turbine. The secondary phase was introduced through a ring sparger situated under the impeller. Calculations were performed with the CFD software CFX 14.5. The turbulent quantities were predicted using the standard k-ε turbulence model. Coalescence and breakup of bubbles were modelled using the MUSIG method with 24 bubble size groups. For the bubble size distribution modelling, the breakup model by Luo and Svendsen (1996) typically has been used in the past. However, this breakup model was thoroughly reviewed and its practical applicability was questioned. Therefore, three different breakup models by Martínez-Bazán et al. (1999a, b), Lehr et al. (2002) and Alopaeus et al. (2002) were implemented in the CFD solver and applied to the system. The resulting Sauter mean diameters and local bubble size distributions were compared with experimental data.

Bubble Tracking Simulations of Turbulent Two-Phase Flows

2016 ◽  
Author(s):  
Jun Fang ◽  
Igor A. Bolotnov
Keyword(s):  
Statistical Analysis ◽  
Level Set Method ◽  
Level Set ◽  
Extraction Efficiency ◽  
Flow Behavior ◽  
Data Extraction ◽  
Bubbly Flow ◽  
High Fidelity ◽  
Phase Flow ◽  
Two Phase

Bubbly flow is quite common in various natural and engineering phenomena. In particular, nuclear engineers are interested in fundamental understanding of the bubbly flow behavior due to its importance in cooling light water reactor cores. Given the extreme conditions and complex support structures in nuclear reactor cores, it is very challenging to study the flow behavior using high-fidelity experiments. Typically validated computational codes are chosen as practical tools for the thermal-hydraulic and safety analyses. As the new generations of nuclear reactors are being developed, more advanced modeling techniques are required to design safe and efficient systems. Different from most simulation approaches, direct numerical simulation (DNS) employs no turbulence closure assumptions, which makes it a promising tool for model development. The major bottleneck of DNS was and remains to be the high computational cost, increasing exponentially with the Reynolds number. However, thanks to the on-going improvements in computer power, these computationally expensive simulations are becoming more and more affordable. Coupled with level-set interface tracking method (ITM), DNS can be used for the high-fidelity studies of two-phase bubbly flows with unprecedented details. Meanwhile, another concern that arises is how one can best take advantage of the ‘big data’ generated from large-scale DNS and translate it into new knowledge. The traditional level-set method utilizes a signed distance field to distinguish different phases while the interface is modeled by the zero level-set. Although level-set method can distinguish gas bubbles from the liquid phase, it cannot recognize and track individual bubbles which hinders the collection of useful bubble information. As a result, the bubble tracking capability has to be developed to improve the data extraction efficiency. In the present work, a marker field is created and advected for bubble distinction and extraction of detailed bubble parameters from the simulations. Each bubble in the flow gets assigned a unique ID, based on which the code will collect the corresponding bubble information. It has been demonstrated that bubble tracking capability can significantly improve the data extraction efficiency for level-set based two-phase flow simulations. Statistical analysis tools are also developed to post-process the recorded information about the bubbles to study the dependencies/correlations of bubble behavior with bubble local conditions. For example, in the pressurized water reactor (PWR) subchannel geometry investigated in this paper, bubbles are observed to experience different relative velocity when presenting at different distance from fuel rod surfaces. With proper grouping criterion, statistical analysis would allow introducing variable drag coefficient for bubbles based on their positions. These new insights are contributing to more accurate modeling of the multiphase computational fluid dynamic (M-CFD) simulations, and better prediction of two-phase flow behavior in engineering systems. Together with the analysis tools, bubble tracking capability will open a new door to study and understand two-phase flows.

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