Abstract:The bubble rising (BR) dynamic is a common phenomenon in numerous processes of industries. Here, a single air BR behavior is studied using computational fluid dynamics (CFD) modelling in a Newtonian fluid (NF) and non-Newtonian fluid (nNF). The volume of fluid formulation with the continuum surface force equation is used to track the air bubble in a NF, while the viscosity of the nNF fluid is estimated by using the power-law equation. The bubble terminal velocity and its shape deformation, as well as the influ… Show more
“…The grid size of the meshes that were optimum for resolving velocity and turbulence fields was not fine enough to accurately resolve the gas-liquid interphase. Similar conclusions were reported by Islam et al for their study on single bubble rising behaviors [38]. As the concentration of bubbles increases, the interfacial area increases, and the mesh requirement increases exponentially [39].…”
Section: Liquid-phase Dispersion In Air-water Two-phase Systemsupporting
confidence: 88%
“…by Islam et al for their study on single bubble rising behaviors [38]. As the concentration of bubbles increases, the interfacial area increases, and the mesh requirement increases exponentially [39].…”
Section: Liquid-phase Dispersion In Air-water Two-phase Systemmentioning
Liquid-phase dispersion in a continuous flow bubble column was studied using computational fluid dynamics (CFD) and different combinations of turbulence and biphasic models. The results were compared with the experimental data obtained by the stimulus-response method in an air-water pilot-scale bubble column (2 m tall, 0.234 m internal diameter). Two flow combinations were examined: high flow rates of 3.2 m3 h−1 and 4.5 m3 h−1 and low flow rates of 1.98 m3 h−1 and 0.954 m3 h−1 for water and air, respectively. The objective was to evaluate commercial CFD 16.1 software to predict flow behavior beyond macroscale parameters such as hold-up or mixing time. The turbulence models that best replicated the experimental tracer dispersion were large eddy simulation-type models: scale-adaptive simulation (SAS) and shear stress transport-SAS. The simulations qualitatively predicted the tracer concentration with time but were unable to reveal the small-scale perturbations in the biphasic system. The predicted tracer residence time was double or triple the measured times for low and high flow, respectively.
“…The grid size of the meshes that were optimum for resolving velocity and turbulence fields was not fine enough to accurately resolve the gas-liquid interphase. Similar conclusions were reported by Islam et al for their study on single bubble rising behaviors [38]. As the concentration of bubbles increases, the interfacial area increases, and the mesh requirement increases exponentially [39].…”
Section: Liquid-phase Dispersion In Air-water Two-phase Systemsupporting
confidence: 88%
“…by Islam et al for their study on single bubble rising behaviors [38]. As the concentration of bubbles increases, the interfacial area increases, and the mesh requirement increases exponentially [39].…”
Section: Liquid-phase Dispersion In Air-water Two-phase Systemmentioning
Liquid-phase dispersion in a continuous flow bubble column was studied using computational fluid dynamics (CFD) and different combinations of turbulence and biphasic models. The results were compared with the experimental data obtained by the stimulus-response method in an air-water pilot-scale bubble column (2 m tall, 0.234 m internal diameter). Two flow combinations were examined: high flow rates of 3.2 m3 h−1 and 4.5 m3 h−1 and low flow rates of 1.98 m3 h−1 and 0.954 m3 h−1 for water and air, respectively. The objective was to evaluate commercial CFD 16.1 software to predict flow behavior beyond macroscale parameters such as hold-up or mixing time. The turbulence models that best replicated the experimental tracer dispersion were large eddy simulation-type models: scale-adaptive simulation (SAS) and shear stress transport-SAS. The simulations qualitatively predicted the tracer concentration with time but were unable to reveal the small-scale perturbations in the biphasic system. The predicted tracer residence time was double or triple the measured times for low and high flow, respectively.
“…Also, they plotted a map of shape regimes for bubbles in a non-Newtonian fluid using Reynolds, Eötvös, and Morton numbers. Islam et al [12] used volumeof-fluid (VOF) approach to investigate rising bubble behavior in a Newtonian and non-Newtonian liquid. Behavior of a non-Newtonian liquid was described by power-law equation.…”
This study aims to investigate the behavior of multicomponent fluid flows consisting of Newtonian and non-Newtonian components, especially terminal velocity of a rising bubble in a power-law fluid. A recent lattice Boltzmann (LB) model is extended using power-law scheme to be able to simulate both Newtonian and non-Newtonian fluid flows at high density and viscosity ratios. Also, a variable mobility is introduced in this study to minimize the unphysical error around small bubbles in the domain. A three-component fluid flow system is examined using a constant and variable mobility. It is shown that each component has more stability using variable mobility while constant mobility causes interface dissipation, leading to mass loss gradually. In addition, two test cases including power-law fluid flows driven between two parallel plates are conducted to show the accuracy and capability of the model. To find a grid-independent computational domain, a grid independency test is carried out to show that a 200 × 400 domain size is suitable 1
Aerated stirred vessels are commonly employed to enhance gas dispersion. However, the associated high energy consumption is a challenging feature, particularly when dealing with complex non‐Newtonian fluids. Coaxial mixers comprising a central impeller and a close‐clearance impeller have emerged as an energy‐efficient alternative that effectively intensifies gas dispersion. Hence, the objective of this study is to investigate the effect of aeration and agitation on the gas dispersion effectiveness of a coaxial mixer containing a yield‐pseudoplastic fluid. An anchor‐pitched blade turbine was employed to disperse air into a 1 wt.% xanthan gum solution, and the analysis primarily focused on characterizing the gas holdup and fluid flow behaviour. Gas holdup data were obtained experimentally using electrical resistance tomography (ERT), while computational fluid dynamics (CFD) simulations provided a detailed analysis of fluid flow patterns within the coaxial mixer. The rotational speed of the impeller exhibited a non‐monotonic effect on the gas holdup, and a significant influence of the interaction between variables was identified. For instance, the experimental data showed that the aeration effect varied with the anchor speed. Nevertheless, the variables' interaction effect was explained by the change in flow pattern observed numerically. Furthermore, the CFD results demonstrated that high gas holdup does not necessarily indicate intensified mixing. Therefore, combining experimental data and numerical simulations enables a more accurate characterization of mixing performance. These findings contribute to the understanding and improvement of mixing performance in such a complex system, which is crucial for designing efficient operations.
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