Two-fluids RANS predictions of gas cavities, power consumption, mixing time and oxygen transfer rate in an aerated fermenter scale-down stirred with multiple impellers

Maluta, Francesco; Paglianti, Alessandro; Montante, Giuseppina Maria Rosa

doi:10.1016/j.bej.2020.107867

Cited by 25 publications

(23 citation statements)

References 57 publications

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“…The Reynolds stress tensor was modelled with the standard k À ε turbulence model in which phase-averaged properties were adopted to extend its validity to multiphase flows. Based on previous results, [9] the adoption of other available multiphase extensions of the k À ε is not expected to provide any improvement.…”

Section: The Two-fluid Model (Tfm) For Rans Equationsmentioning

confidence: 88%

“…The last two terms in Equation ( 3) are the interphase forces coupling the momentum balance equations for the two phases, which are the drag force, F D , and the turbulent dispersion force, F TD . As reported in the literature for similar systems, [9,45] additional interphase momentum exchange terms can be neglected. The Reynolds stress tensor was modelled with the standard k À ε turbulence model in which phase-averaged properties were adopted to extend its validity to multiphase flows.…”

Section: The Two-fluid Model (Tfm) For Rans Equationsmentioning

confidence: 96%

“…For instance, the Rushton turbine is one of the most studied impellers, [6] but in gas-liquid applications, it could suffer from a reduction in the power transferred to the mixture due to the formation of aerated cavities behind the impeller blades, [7,8] causing suboptimal gas distribution and lower mass transfer rates. [9] To overcome these issues, asymmetric concave blade turbines, such as the Chemineer BT-6, demonstrated flattened gassed power curves and better gas handling, resulting in higher gas dispersion before flooding. [10] Despite being one of the most efficient impellers in gas-liquid applications, [11] BT-6s are comparatively less characterized than Rushton impellers.…”

Section: Introductionmentioning

confidence: 99%

“…The major limitation arises from the choice of the bubble diameter, which strongly affects the generated gas-liquid flow field. [9] In general, in the simulation of gas-liquid stirred tanks, two approaches exist in determining the bubble diameter: either it derives from experimental observations [20,21] and correlations [22] or it is calculated through the solution of a population balance equation (PBE). [23][24][25][26] The computational fluid dynamics (CFD) coupled with a population balance model would allow fully predictive simulations to be performed, but the increased computational cost and some limitations in the description of aerated stirred tanks in non-homogeneous flow regimes still limit its use in most industrial applications.…”

Section: Introductionmentioning

confidence: 99%

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Validation of a procedure for the numerical simulations of gas–liquid stirred tanks by means of a computational fluid dynamics approach

et al. 2022

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Impellers with concave and vertically asymmetric blades proved superior gas dispersion capabilities and power consumption characteristics under gassed turbulent conditions with respect to traditional flat‐blade turbines in aerated fermenters. In this study, a pilot‐size gas–liquid tank stirred with an asymmetric blade disk impeller is numerically investigated by means of a Reynolds averaged two‐fluid model combined with a simplified population balance model without adjustable parameters. This work aims at increasing the predictive capabilities of computational fluid dynamics multiphase modelling by validating a computational approach for the realistic simulation of industrial aerated fermenters and thus allowing for a more reliable scale‐up. A methodology for achieving fully predictive results on fundamental variables for gas–liquid stirred tanks such as gassed power consumption, overall gas hold‐up, and volumetric mass transfer coefficient, with affordable computational requirements at pilot and industrial scale is presented. Two‐phase results are compared with the experimental data collected in a geometry matching the computational domain equipped with 3 planes of 16 sensors to enable electro‐resistance tomography measurements and with suitable correlations from the literature. The limits and strength of the numerical procedure are discussed, starting from the comparison between computational predictions and experimental measurements.

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Section: The Two-fluid Model (Tfm) For Rans Equationsmentioning

confidence: 88%

Section: The Two-fluid Model (Tfm) For Rans Equationsmentioning

confidence: 96%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Validation of a procedure for the numerical simulations of gas–liquid stirred tanks by means of a computational fluid dynamics approach

et al. 2022

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“…In fact, the comprehensive analysis of the hydrodynamic behavior throughout the vessel in different scales is highly desired to have a better understanding of the fluid flow upon scaling-up. However, there are some numerical limitations in simulating commercialscale equipment because it requires a high number of mesh elements that lead to a high computational effort [146]. Normally, model simplifications are needed in these cases but still a good prediction of the fluid behavior can be obtained from CFD analyses.…”

Section: Scale-upmentioning

confidence: 99%

Gas Dispersion in Non-Newtonian Fluids with Mechanically Agitated Systems: A Review

2022

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Gas dispersion in non-Newtonian fluids is encountered in a broad range of chemical, biochemical, and food industries. Mechanically agitated vessels are commonly employed in these processes because they promote high degree of contact between the phases. However, mixing non-Newtonian fluids is a challenging task that requires comprehensive knowledge of the mixing flow to accurately design stirred vessels. Therefore, this review presents the developments accomplished by researchers in this field. The present work describes mixing and mass transfer variables, namely volumetric mass transfer coefficient, power consumption, gas holdup, bubble diameter, and cavern size. It presents empirical correlations for the mixing variables and discusses the effects of operating and design parameters on the mixing and mass transfer process. Furthermore, this paper demonstrates the advantages of employing computational fluid dynamics tools to shed light on the hydrodynamics of this complex flow. The literature review shows that knowledge gaps remain for gas dispersion in yield stress fluids and non-Newtonian fluids with viscoelastic effects. In addition, comprehensive studies accounting for the scale-up of these mixing processes still need to be accomplished. Hence, further investigation of the flow patterns under different process and design conditions are valuable to have an appropriate insight into this complex system.

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Hydrodynamics of gas-liquid and biophase-gas-liquid systems in stirred tanks of different scales

Cudak

Rakoczy

2022

Korean J. Chem. Eng.

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Two-fluids RANS predictions of gas cavities, power consumption, mixing time and oxygen transfer rate in an aerated fermenter scale-down stirred with multiple impellers

Cited by 25 publications

References 57 publications

Validation of a procedure for the numerical simulations of gas–liquid stirred tanks by means of a computational fluid dynamics approach

Validation of a procedure for the numerical simulations of gas–liquid stirred tanks by means of a computational fluid dynamics approach

Gas Dispersion in Non-Newtonian Fluids with Mechanically Agitated Systems: A Review

Hydrodynamics of gas-liquid and biophase-gas-liquid systems in stirred tanks of different scales

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