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

Author(s):  
Konstantinos Samaras ◽  
Margaritis Kostoglou ◽  
Thodoris D. Karapantsios ◽  
Paul Mavros
Author(s):  
Xinju Li ◽  
Xiaoping Guan ◽  
Rongtao Zhou ◽  
Ning Yang ◽  
Mingyan Liu

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.


2014 ◽  
Vol 35 (3) ◽  
pp. 331-348 ◽  
Author(s):  
Zbyněk Kálal ◽  
Milan Jahoda ◽  
Ivan Fořt

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.


Author(s):  
Sanaz Salehi ◽  
Amir Heydarinasab ◽  
Farshid Pajoum Shariati ◽  
Ali Taghvaie Nakhjiri ◽  
Kourosh Abdollahi

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.


Bubble sizes in bubble column affect transfer processes. Therefore, it’s important to calculate bubble size and interfacial area. Bubble size distribution (BSD) in a bubble column of rectangular cross section with dimensions 0.2m x 0.02m was measured using photographic method (400 fps) for air-water system. Gas holdup, Sauter-mean bubble diameter, aspect ratio and specific interfacial area were estimated from BSD. Effect of superficial gas velocity and static bed height on these parameters was investigated. The bubble size distribution exhibited mono-modal distribution showing the presence of non-uniform homogeneous bubbling regime. The frames of video were analysed using image processing steps to obtain major and minor axis of elliptical bubbles. Values of d32, , and ai were estimated from the data. The value of d32 increased with increasing Ug but is independent of Hs. The values of d32 were somewhat higher than the values reported by other investigators. The value of ai increases with increasing Ug and with decreasing Hs. Present values of compared well with the data reported in literature.


Author(s):  
Huahai Zhang ◽  
Yuelin Wang ◽  
Ali Sayyar ◽  
Tiefeng Wang

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.


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