One‐Dimensional Modeling and Simulation of Bubble Column Reactors

Jung, Sebastian; Becker, Marc; Agar, David W.; Franke, Robert

doi:10.1002/ceat.201000313

Cited by 9 publications

(7 citation statements)

References 25 publications

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“…numerically demonstrated that the prediction of a nonideal reactor behavior by the ADM is similar to the MCM 35, 36. The one‐dimensional ADM was widely applied 36–40 due to its simplicity and ease of use and is the most common approach for modeling of SBCRs.…”

Section: Introductionmentioning

confidence: 88%

Modeling of Slurry Bubble‐Column Reactors with Emphasis on the Importance of Bubble Size Estimation

2021

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A mathematical model entitled varying‐bubble model (V‐BM) was adapted to simulate a slurry bubble‐column reactor, operating in a churn‐turbulent regime, based on an axial‐dispersion model. This model was theoretically able to estimate the size of forming bubbles at the sparger, variations of each chemical species and catalyst concentration, pressure drop in both gas and liquid phases, change in size and rising velocity of bubbles, as well as gas holdup and specific gas‐liquid interfacial area along the reactor axis. A comparison between the V‐BM and single‐bubble model (S‐BM) indicates that the V‐BM is better compatible with the experimental data. The results demonstrate that the contribution of mass transfer is much more than the pressure drop in increasing the size of the bubble along the reactor.

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Section: Introductionmentioning

confidence: 88%

Modeling of Slurry Bubble‐Column Reactors with Emphasis on the Importance of Bubble Size Estimation

2021

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“…This correlation has shown good agreement with experimental data while the operating conditions of both are similar. In hydrocracking systems as well as for hydrogenation systems where the homogeneous bubble flow prevails, a common approximation for the liquid axial dispersion coefficient is considered with the correlation proposed by Deckwer et al ,, Recently Khadem-Hamedani et al have shown, for a HDS system under sever conditions of temperature and pressure, that the correlation proposed by Deckwer et al formulated for a F – T system, can be satisfactorily included in the modeling regardless of the type of flow regime (homogeneous or heterogeneous). Other correlations are presented extensively in different works starting with Shah et al, Fan, Degaleesan and Dudokivic, and recently with Sivaiah and Majumder, who present a summary of the typical correlations for three-phase systems and their respective range of parameters.…”

Section: Estimation Of Model Parametersmentioning

confidence: 99%

Modeling of Slurry-Phase Reactors for Hydrocracking of Heavy Oils

Calderón

Ancheyta

2016

Energy Fuels

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The modeling of slurry-phase reactors for petroleum hydrocracking has been reviewed and analyzed. A general description of the flow regime was proposed, and it is anticipated that due to the operating conditions usually implemented in hydrocracking of heavy oils, the homogeneous bubble flow is usually considered. It was also found in the literature that most of the models are only able to describe the liquid-phase behavior, omitting the dynamic behavior of the gas phase, the dispersion, and deactivation of catalysts, as well as coke formation. Computational fluid dynamics formulations are preferred despite the computational effort involved in the calculations. Also in the majority of those models, simple pseudocomponent kinetic rate expressions have been applied, without enough experimental information referring to kinetic parameters. Finally a generalized reactor model, which considers all mass and heat transfer phenomena, is proposed based on the literature, and details are provided to estimate all of the model parameters. For slurry-phase hydrocracking systems it becomes evident the lack of experimental information needed for validation and the necessity of exploring different types of models, as axial dispersion models under different bubble flow regimes as well as deep study of the transitory state.

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“…The value of the dispersion coefficient can be obtained via residence time measurements. The coefficient itself can then be used within mathematical models, e.g., dispersed plug flow models (Jung et al [21]), to simulate bubble column reactors.…”

Section: Liquid Backmixing Studiesmentioning

confidence: 99%

Hydrodynamics of High‐Pressure Bubble Columns

et al. 2013

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Bubble column hydrodynamics influence important performance parameters like conversion, selectivity, and yield of a chemical reaction. Backmixing of the liquid phase and gas holdup are thereby of particular importance. In order to determine these parameters, a number of correlations exist in the literature. These correlations are mainly derived from small-scale equipment operated under atmospheric conditions using the physical system air/water. Published experimental results regarding gas holdups and dispersion in bubble columns operated under high pressure are discussed and a recommendation for further research is given.

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One‐Dimensional Modeling and Simulation of Bubble Column Reactors

Cited by 9 publications

References 25 publications

Modeling of Slurry Bubble‐Column Reactors with Emphasis on the Importance of Bubble Size Estimation

Modeling of Slurry Bubble‐Column Reactors with Emphasis on the Importance of Bubble Size Estimation

Modeling of Slurry-Phase Reactors for Hydrocracking of Heavy Oils

Hydrodynamics of High‐Pressure Bubble Columns

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