Improving the efficiency of ‘Clean-In-Place’ procedures using a four-lobed swirl pipe: A numerical investigation

Li, Guozhen; Hall, Philip; Miles, N.J.; Wu, Tao

doi:10.1016/j.compfluid.2014.11.032

Cited by 23 publications

(9 citation statements)

References 24 publications

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“…shear stress and fluctuation intensity, affect cleaning results (Jensen et al, 2006;Jensen and Friis, 2005;Schöler et al, 2012) and to improve the hygienic design of valves, pipes and connections (Friis and Jensen, 2002;Jensen and Friis, 2004). Li et al (2015aLi et al ( , 2015b) simulated a four-lobed swirl pipe by using CFD and identified the potential to improve the efficiency of CIP by…”

Section: A N U S C R I P Tmentioning

confidence: 99%

CFD modelling of axial mixing in the intermediate and final rinses of cleaning-in-place procedures of straight pipes

Yang

Jensen²,

Nordkvist³

et al. 2018

Journal of Food Engineering

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Section: A N U S C R I P Tmentioning

confidence: 99%

CFD modelling of axial mixing in the intermediate and final rinses of cleaning-in-place procedures of straight pipes

Yang

Jensen²,

Nordkvist³

et al. 2018

Journal of Food Engineering

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“…They found that the decay rate is not only a function of Reynolds number but also is related to the type of swirl generation. The relationship between the decay rate and friction factor coefficient obtained by Li et al (2015) was slightly higher than that of Steenbergen; they pointed out that the difference between the results may be due to the different types of swirl generators they used. The swirl flow induction method used in Steenbergen's experiment produced more tangential shear force on the wall compared to Li's experimental rotating wall and four-lobed tube.…”

Section: Effects Of Different Lobed Numbers Pitch Length Ratios On Dmentioning

confidence: 79%

“…We found that the decay rate varies linearly with the friction factor coefficient based on our analysis of exiting numerical data. The decay rate correlation formula obtained by fitting is β = 1.76 f, β = 1.72 f, β = 1.71 f, and β = 1.70 f for the Reynolds numbers Re = 50,000, 75,000, 100,000, and 125,000, (Cavazzuti & Corticelli, 2017;Li et al, 2015;Reader-Harris, 1994;Steenbergen & Voskamp, 1998).…”

Section: Effects Of Different Lobed Numbers Pitch Length Ratios On Dmentioning

confidence: 97%

“…Additional CFD analyses can significantly enrich this understanding while reducing the time and cost of experimental research (Akbarian et al, 2018;Gabl & Righetti, 2018;Ghalandari et al, 2019;Salih et al, 2019). Li et al (2015) constructed a numerical model of a four-lobed swirl tube and found that it can generate tangential wall shear stress downstream to improve the CIP efficiency. Swirl intensity also showed a significant impact on the tangential wall shear stress.…”

Section: Introductionmentioning

confidence: 99%

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Numerical evaluation on the decaying swirling flow in a multi-lobed swirl generator

Yan

Sun

et al. 2020

Engineering Applications of Computational Fluid Mechanics

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Accurate predictions of decaying swirling flow behavior in the multi-lobed swirl generator (MLSG) are essential for certain engineering applications. In this study, decaying swirling flow characteristics in an MLSG are examined using the Computational Fluid Dynamics (CFD) technique with a Reynolds stress turbulence model (RSM). The effects of different lobe numbers (n) and pitch length ratios (P/D) on swirl intensity, pressure drop, friction factor coefficient, and decay rate are observed with Reynolds number from 50,000 to 125,000. Combined with the pressure loss, the efficiency of swirl induction is evaluated by introducing a swirl effectiveness (SE) evaluation criterion. The initial swirl intensity is shown to first increases and then decreases as lobe number increases. The maximum value is obtained at lobe number n = 4. The pitch length ratios P/D corresponding to the optimal SE value obtained from different lobe also differ. The optimal SE value is achieved at n = 4 and P/D = 8. The friction factor ratio f s /f p decreases as pitch length ratio increases, but the decreasing trend decelerates over time. Correlations based on the numerical predictions of friction factor ratio f s /f p and decay rate β are presented accordingly.

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“…Thus, some authors have discarded standard wall functions for modeling swirl flows of small-scale experiments. Najafi et al used scalable wall functions, because of the robustness in turbulent components, and Li used nonequilibrium wall functions, because of the pressure gradients generated by the swirl pattern near the wall. Attending to these considerations, the following set of recommendations are defined: Scalable and standard wall functions are not recommended under strong pressure gradients. − The pressure gradients may be significant at large swirl intensities, providing inconsistent results.…”

Section: Computational Fluid Dynamics (Cfd) Modelingmentioning

confidence: 99%

Computational Fluid Dynamics (CFD) Modeling of Swirling Flows in Industrial Counter-Current Spray-Drying Towers under Fouling Conditions

Hernández

Fraser

Juan

et al. 2018

Ind. Eng. Chem. Res.

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This work presents a novel procedure to predict the airflow pattern under different levels of deposition and Reynolds numbers for swirling-flow industrial-scale spray-drying towers. It improves the accuracy in the prediction of both the hydrodynamics and the effect of the deposition. Initially, steady-state and transient simulations are compared, showing that the model can be reduced to steady state for a certain mesh size. The computational fluid dynamics (CFD) model is later calibrated using the experimental swirl intensity values under different levels of deposits that have reached a dynamic equilibrium. The model then is validated for different Reynolds numbers of operation. Finally, the validated model is applied to examine the vortex behavior and evaluate the effect of the tower radius reduction. A limit of operation is found for low Reynolds numbers, in terms of stability, and it is observed that the momentum cannot be only modeled with the radius reduction.

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Improving the efficiency of ‘Clean-In-Place’ procedures using a four-lobed swirl pipe: A numerical investigation

Cited by 23 publications

References 24 publications

CFD modelling of axial mixing in the intermediate and final rinses of cleaning-in-place procedures of straight pipes

CFD modelling of axial mixing in the intermediate and final rinses of cleaning-in-place procedures of straight pipes

Numerical evaluation on the decaying swirling flow in a multi-lobed swirl generator

Computational Fluid Dynamics (CFD) Modeling of Swirling Flows in Industrial Counter-Current Spray-Drying Towers under Fouling Conditions

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