Electrical capacitance volume tomography for imaging of pulsating flows in a trickle bed

Wang, Aining; Marashdeh, Qussai M.; Motil, Brian J.; Fan, Liang‐Shih

doi:10.1016/j.ces.2014.08.011

Cited by 58 publications

(19 citation statements)

References 31 publications

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“…Indeed, the scaling in Dankworth et al results in a characteristic time that is unrealistically small (or, equivalently, in characteristic pulse frequencies that are too large compared with the average observed frequencies). Although no detailed experimental observations are available on how the pulse frequency changes as the pulse “grows” when it travels down the column (and how these frequencies change, if at all, with column height), there is some indication that the frequency decreases as the pulse travels down the column. With the available experimental information, it is not clear how one can choose an a priori characteristic length for such effective viscosity models.…”

Section: Closure Relationsmentioning

confidence: 99%

Experimentally‐based constitutive relations for co‐current gas‐liquid flow in randomly packed beds

Salgi

Balakotaiah

2016

AIChE Journal

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Experimental Observations on average pulse velocity and frequency in concurrent gas‐liquid (down) flow through randomly packed beds are used to extract constitutive relations for the gas‐liquid interaction and mean curvature terms that appear in a recently proposed volume‐averaged two‐fluid model for bubbly flow. The proposed closures lead to a reasonably quantitative prediction of the average pressure drop and liquid saturation under bubbly flow conditions and in the near pulse regime. In addition, the proposed closures provide realistic estimates for the location of the bubble‐to‐pulse transition in microgravity and in 1g down‐flow and predict the disappearance of the bubbly flow pattern at low liquid fluxes in 1g down‐flow. © 2016 American Institute of Chemical Engineers AIChE J, 63: 812–822, 2017

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Section: Closure Relationsmentioning

confidence: 99%

Experimentally‐based constitutive relations for co‐current gas‐liquid flow in randomly packed beds

Salgi

Balakotaiah

2016

AIChE Journal

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“…Lastly, we predict that pulses formed just beyond the transition from bubbly ow may not be stable. Future work will focus on a more detailed comparison with available experimental data from both 0 g and 1 g down-ow data [8][9][10]. We will also continue exploring the feasibility of time-dependent simulations in the nearpulsing regime.…”

Section: Discussionmentioning

confidence: 97%

“…Temporal growth rate (s −1 ) v l, g : Average mesoscale velocity in liquid or gas phase (m/s) p l, g : Average mesoscale pressure in liquid or gas phase (Pa) Data Availability e data on average pulse properties used for comparison with the predictions made in this article may be found in the studies cited within the text as references [8][9][10].…”

Section: Symbols ε Lmentioning

confidence: 99%

Modeling Pulse Properties near the Bubble-to-Pulse Transition in Randomly Packed Beds

Salgi

Krayem

2019

International Journal of Chemical Engineering

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Traveling wave analysis of a recently developed two-fluid model for bubbly flow in lab-size packed beds is used to propose a constitutive closure for the effective viscosity, a nonzero parameter that is needed in the liquid momentum balance to avoid the prediction of disturbances with an infinite growth rate. Near-solitary wave profiles are predicted over a range of velocity parameters consistent with linear stability analysis. Centimeter-scale periodic disturbances are predicted in the near-pulsing regime. Preliminary estimates of average pulse properties compare well with typically reported experimental values. Initial comparison with time integration subject to periodic boundary conditions shows agreement of the liquid saturation profiles but differences in the liquid velocity profiles.

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“…When the liquid flux increases to 16.68 kg m −2 s −1 , the gas–liquid interaction is further intensified, thus the gas–liquid interface is broken up by the intense interactions and no longer clear and smooth, just as shown in Figure c. Under these conditions, as addressed by Wang et al, when most of the local void is occupied by liquids, the gas phase breaks local liquid blockages and pushed them down to form the small local liquid pulses, which can merge together to form large liquid pulses blocking the whole cross section. Therefore, the gas‐rich zone and the liquid‐rich zone appear alternately at a certain frequency, which is named as the pulse flow.…”

Section: Flow Regime Transition In Trickle Bedmentioning

confidence: 87%

On flow regime transition in trickle bed: Development of a novel deep‐learning‐assisted image analysis method

Wang

Yang

et al. 2019

AIChE Journal

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An image analysis method was developed based on deep-learning algorithms to extract phase fractions quantitatively in a rectangular trickle bed, and the average identification error was lower than 5%. Furthermore, the flow regime transition in the trickle bed was studied. In trickle-to-pulse flow transition, the trickle flow could be further classified into the stable trickle flow and accelerated one. The SD of liquid fractions and the peak width at half-height of the probability density curve of liquid fractions were close to zero in stable trickle flow, increased rapidly in accelerated trickle flow, and remained approximately constant in pulse flow. In bubble-to-pulse flow transition, dispersed bubbles in bubble flow induced the outliers outside the upper boundary of the boxplot of gas fraction, while alternative appearance of gasrich zone and liquid-rich zone in pulse flow induced outliers outside both the upper and lower boundaries of the boxplot of gas fraction.

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Electrical capacitance volume tomography for imaging of pulsating flows in a trickle bed

Cited by 58 publications

References 31 publications

Experimentally‐based constitutive relations for co‐current gas‐liquid flow in randomly packed beds

Experimentally‐based constitutive relations for co‐current gas‐liquid flow in randomly packed beds

Modeling Pulse Properties near the Bubble-to-Pulse Transition in Randomly Packed Beds

On flow regime transition in trickle bed: Development of a novel deep‐learning‐assisted image analysis method

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