Maldistribution and dynamic liquid holdup quantification of quadrilobe catalyst in a trickle bed reactor using gamma-ray computed tomography: Pseudo-3D modelling and empirical modelling using deep neural network

Qi, Binbin; Farid, Omar; Uribe, Sebastián; Al‐Dahhan, Muthanna H.

doi:10.1016/j.cherd.2020.09.024

Cited by 14 publications

(12 citation statements)

References 32 publications

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“…This calibration process, facilitated by a bin, was essential for adjusting the detector's signal and accurately estimating the total wall thickness. Similarly, a comparable phantom was employed in validating and calibrating gamma-ray computed tomography, as Qi et al [25] detailed.…”

Section: The Measurement Techniquementioning

confidence: 99%

“…The attenuation of the gamma-ray beam depends on the radiation energy of the source, the density and the thickness of the absorbing material that the radiation beam passes through, and the mass attenuation coefficient (Al-Dahhan 2009) [19,24]. This dependency of the reduction in the radiation intensity from I₀ (at the source) to I can be described by Beer-Lambert's law according to the following equation [25].…”

Section: The Principle Of the Holdups' Measurements And The New Metho...mentioning

confidence: 99%

“…Thus, information on the two-phase (liquid-gas) distribution can be obtained for flow over a fixed bed of catalyst, as the attenuation due to the catalyst will be fixed and the variation in attenuation is due to the flowing liquid. Qi et al (2020) [25] studied dynamic liquid holdup in a trickle bed reactor (characterized by downward two-phase flow in a packed bed) filled with quadrilobe porous catalysts, using gamma-ray computed tomography (CT). They developed a method to measure the cross-sectional distribution of both dynamic liquid holdup and the combined liquid holdup inside the catalyst pores and the static liquid holdup between the catalyst joints.…”

Section: Introductionmentioning

confidence: 99%

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Experimental Investigation of Liquid Holdup in a Co-Current Gas–Liquid Upflow Moving Packed Bed Reactor with Porous Catalyst Using Gamma-Ray Densitometry

Toukan,

Jasim,

Alexander

et al. 2024

ChemEngineering

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This study explores the dynamics of liquid holdup in a lab-scale co-current two-phase upflow moving packed bed reactor, specifically examining how superficial gas velocity influences the line average external liquid holdup at a fixed superficial liquid velocity. Utilizing gamma-ray densitometry (GRD) for precise measurements, this research extends to determining line average internal porosity within catalyst particles. Conducted with an air–water system within a bed packed with 3 mm porous particles, the study presents a novel methodology using Beer–Lambert’s law to calculate liquid, gas, and solid holdups and catalyst porosity that is equivalent to the internal liquid holdup that fills the catalyst pores. Findings reveal a decrease in liquid holdup corresponding with increased superficial gas velocity across axial and radial locations, with a notable transition from bubbly to pulse flow regime at a critical velocity of 3.8 cm/sec. Additionally, the lower sections of the packed bed exhibited higher external liquid holdup compared to the middle sections at varied gas velocities. The liquid holdup distribution appeared uniform at lower flow rates, whereas higher flow rates favored the middle sections.

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Section: The Measurement Techniquementioning

confidence: 99%

Section: The Principle Of the Holdups' Measurements And The New Metho...mentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Experimental Investigation of Liquid Holdup in a Co-Current Gas–Liquid Upflow Moving Packed Bed Reactor with Porous Catalyst Using Gamma-Ray Densitometry

Toukan,

Jasim,

Alexander

et al. 2024

ChemEngineering

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“…The second developed technique for the measurement of local scale phenomena in fluidized beds and spouted beds are optical fiber sensors. Optical fiber sensors have been extensively used in experimental studies of gas-solid fluidized systems over the last decades [7,106,108,109]. Nevertheless, commonly, these sensors cannot simultaneously measure the solids holdup and velocities, show blind regions (their overall size is large and becomes highly invasive D probe ∼ 2 cm ) or fail to provide accurate time resolved measurements [110][111][112].…”

Section: Two-tip Optical Fiber Probe (Ttof)mentioning

confidence: 99%

Pairing Experimental and Mathematical Modeling Studies on Fluidized Beds for Enhancement of Models Predictive Quality: A Current Status Overview

Uribe

Al‐Dahhan

2021

Processes

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Modeling of gas-solid fluidized systems has been a prevailing challenge over the last few decades. With different approaches and implementing different sub-models to capture the essential multiphase and multiscale phenomena in these systems, major advances have been achieved, even though most models are only subject to a practical validation of macroscopic parameters. The current description of fluidized beds through mathematical models relies on the inclusion of vast sub-models, leading to an unquantifiable degree of uncertainty on the models’ applicability for extrapolation studies. Furthermore, each closure and fitting parameter in the model represents a possible source of deviation, and their optimization, hence, becomes another major challenge. The recent advances in measurement techniques can enable us to troubleshoot and optimize the implemented models and sub-models based on local scale measurements. Local multiphase hydrodynamic information obtained by advanced measurement techniques can enable the validation of local predictions and optimization of the coupled sub-models, leading to the development of simplified and highly predictive models. Thus, pairing advanced experimental studies on these systems with insightful modeling approaches is required to advance the shortcoming and enhance the predictive quality of the models. In this work, an overview of the status of modeling and experimental measurement techniques for gas-solid fluidized beds is presented; then, an overview on pairing both experimental and modeling studies to improve the models’ local predictions for fluidized beds is presented.

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“…Various experimental approaches 15,16 such as tracer injection methods, 17 liquid collection at the bottom of the reactor, [18][19][20][21][22][23] dye adsorption, 24,25 heater probe, 26 conductance probe, 27 optical fiber probe, 5 conductivity probe techniques, 28 and advanced imaging techniques such as computer-assisted tomography, 29 γ-ray tomography, 30,31 and capacitance tomography 32,33 have been employed to investigate the two-phase flow structure inside a trickle bed. Most of the mentioned experimental approaches are practical only for measuring the macroscopic hydrodynamic characteristics of a trickle bed, such as the overall liquid hold-up and pressure drop, due to particular technical limitations of the experimental method.…”

Section: Introductionmentioning

confidence: 99%

Magnetic resonance imaging of trickle flow

Fathiganjehlou,

Buist,

Peters

et al. 2024

AIChE Journal

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Trickle bed reactors (TBR) are widely used in the chemical industries. These reactors involve gas and liquid flow through a catalyst‐packed bed. For optimal TBR performance, it is crucial to achieve a uniform distribution of gas and liquid among the catalyst particles. However, in multitubular reactors with slender tubes, flow maldistribution near the tube walls is a common issue. Therefore, a comprehensive understanding of local phase and flow distribution is essential for designing and operating reactors with slender tubes. This article employs Magnetic Resonance Imaging (MRI) to characterize the three‐dimensional distribution of the two‐phase trickle flow within a slender tube. Three quantities are characterized: gas‐liquid‐solid distribution, particle wetting efficiency, and the flow field. Structure and flow MRI images are processed to calculate these quantities. Additionally, a novel postprocessing technique is introduced to determine the liquid distribution over individual particle surfaces. This distribution is determined at several axial and radial positions.

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Maldistribution and dynamic liquid holdup quantification of quadrilobe catalyst in a trickle bed reactor using gamma-ray computed tomography: Pseudo-3D modelling and empirical modelling using deep neural network

Cited by 14 publications

References 32 publications

Experimental Investigation of Liquid Holdup in a Co-Current Gas–Liquid Upflow Moving Packed Bed Reactor with Porous Catalyst Using Gamma-Ray Densitometry

Experimental Investigation of Liquid Holdup in a Co-Current Gas–Liquid Upflow Moving Packed Bed Reactor with Porous Catalyst Using Gamma-Ray Densitometry

Pairing Experimental and Mathematical Modeling Studies on Fluidized Beds for Enhancement of Models Predictive Quality: A Current Status Overview

Magnetic resonance imaging of trickle flow

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