scholarly journals CFD–PBM Simulation on Bubble Size Distribution in a Gas–Liquid–Solid Flow Three-Phase Flow Stirred Tank

ACS Omega ◽  
2022 ◽  
Author(s):  
Shuai Li ◽  
Runquan Yang ◽  
Caili Wang ◽  
Hua Han ◽  
Shiyu Shen ◽  
...  
Keyword(s):  
Size Distribution ◽  
Bubble Size ◽  
Bubble Size Distribution ◽  
Stirred Tank ◽  
Phase Flow ◽  
Solid Flow ◽  
Three Phase ◽  
Three Phase Flow

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.

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.

Effect of adding glycerol and Tween 80 on gas holdup and bubble size distribution in an aerated stirred tank

2014 ◽  
Vol 441 ◽  
pp. 815-824 ◽  
Author(s):  
Konstantinos Samaras ◽  
Margaritis Kostoglou ◽  
Thodoris D. Karapantsios ◽  
Paul Mavros
Keyword(s):  
Size Distribution ◽  
Bubble Size ◽  
Tween 80 ◽  
Gas Holdup ◽  
Bubble Size Distribution ◽  
Stirred Tank

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

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.

Parametric numerical study and optimization of mass transfer and bubble size distribution in a gas-liquid stirred tank bioreactor equipped with Rushton turbine using computational fluid dynamics

2021 ◽  
Vol 0 (0) ◽  
Author(s):  
Sanaz Salehi ◽  
Amir Heydarinasab ◽  
Farshid Pajoum Shariati ◽  
Ali Taghvaie Nakhjiri ◽  
Kourosh Abdollahi
Keyword(s):  
Fluid Dynamics ◽  
Mass Transfer ◽  
Computational Fluid Dynamics ◽  
Transfer Coefficient ◽  
Size Distribution ◽  
Bubble Size ◽  
Bubble Size Distribution ◽  
Stirred Tank ◽  
Operating Parameters ◽  
Stirred Tank Bioreactor

Abstract Designing and optimizing a bioreactor can be an especially challenging process. Computational modelling is an effective tool to investigate the effects of various operating parameters on bioreactor performance and identify the optimum ones. In this work, a computational fluid dynamics-population balance model (CFD-PBM) was developed to elucidate the effect of different geometrical and operating parameters on the hydrodynamics and mass transfer coefficient of a batch stirred tank bioreactor. The validated model was projected to predict the effect of different parameters including the gas flow rate, the impeller off-bottom clearance, the number of agitator blades, and rotational speed of the impeller on the velocity profiles, air volume fraction, bubble size distribution, and the local gas mass transfer coefficient (K l a) in the bioreactor. Air bubble breakup and coalescence phenomena were considered in all simulations. Factorial experimental design approach was employed to statistically investigate the impacts of the aforementioned operating and geometrical parameters on K l a and bubble size distribution in the bioreactor in order to determine the most significant parameters. This can give an essential insight into the most impactful factors when it comes to designing and scaling up a bioreactor.

Experimental Study on Bubble Size Distribution in Gas-Liquid Reversed Jet Loop Reactor

2019 ◽  
Vol 0 (0) ◽  
Author(s):  
Rongshan Bi ◽  
Jiao Tang ◽  
Linxi Wang ◽  
Qingqing Yang ◽  
Meilan Zuo ◽  
...  
Keyword(s):  
Liquid Phase ◽  
Size Distribution ◽  
Gas Phase ◽  
Flow Rate ◽  
Bubble Size ◽  
Draft Tube ◽  
Bubble Size Distribution ◽  
Image Processing Technique ◽  
Phase Flow ◽  
Loop Reactor

Abstract Bubble size distribution (BSD) is important for gas-liquid jet loop reactor (JLR)’s mass transfer performance of inter-phases. A self-designed reversed JLR was investigated with air-water system on the BSD. The CCD camera of particle imaging velocimetry (PIV) system and image processing technique were used to obtain the reliable photo. The influences of four parameters, gas phase flow rate, liquid phase flow rate, draft tube diameter and ejector mounting position, on the BSD were studied in detail. The results showed that the local BSD is accordance with log-normal distribution under the experimental conditions and the average diameter and BSD range increase with the increase of the gas phase flow rate, and decrease with the increase of the liquid phase flow rate, the downward movement of the nozzle installation position and the increase of the diameter of the draft tube.

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