Segregation and dispersion of binary solids in liquid fluidised beds: A CFD-DEM study

Peng, Zhengbiao; Joshi, Jyeshtharaj B.; Moghtaderi, Behdad; Khan, Md. Shakhaoath; Evans, Geoffrey M.; Doroodchi, Elham

doi:10.1016/j.ces.2016.05.032

Cited by 61 publications

(35 citation statements)

References 54 publications

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“…Nevertheless, the experimental data and the numerical modeling results reported in the literature consistently reveal the same trend of solid concentration variation in the transition zone, as shown in Figure . For data in the region close to the top surface of the bed where the solid concentration is decreasing due to hydrodynamic instabilities have been excluded.…”

Section: Model Developmentsupporting

confidence: 76%

“…The phenomenon of bed contraction has been reported to cause deviation in the application of the serial model to predict the total bed expansion, thus the deviation in the application of the present model in such systems. Therefore, the 25% deviation is considered acceptable in view of the substantial difference in both size and density of the binary mixture with a terminal settling velocity ratio of 3.23. As such, the logistic functions of Eqs.…”

Section: Resultsmentioning

confidence: 99%

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A simple model for predicting solid concentration distribution in binary‐solid liquid fluidized beds

2016

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A simple mathematical model for predicting the solid concentration profile in binary‐solid liquid fluidized beds is presented. The main assumption is that the solid concentration distribution follows the logistic function, which is supported by the literature. Various equations have been derived to solve key system quantities (e.g., bed expansion height, length and position of the transition zone). In contrast to previous models that often involve adjustable parameters and strongly rely on the availability of experimental data, the present model only requires inputs of fluid and particle properties, operating conditions, and correlations for dispersion and slip velocity. The results showed that the model is applicable to different binary‐solid systems that have size and/or density differences. The model's capability of predicting the layer inversion phenomenon has also been demonstrated. The model is simple but proves capable of accurately predicting key information for the design, operation and scale up of liquid fluidized beds. © 2016 American Institute of Chemical Engineers AIChE J, 63: 469–484, 2017

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Section: Model Developmentsupporting

confidence: 76%

Section: Resultsmentioning

confidence: 99%

A simple model for predicting solid concentration distribution in binary‐solid liquid fluidized beds

2016

Self Cite

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“…A layer inversion was mimicked in the simulations by placing the high density particles above the low density ones. Peng et al [26] presented the concentration profiles for each species for the steady state regime, i.e., after layer inversion took place, and comparisons with the experimental results of Galvin et al [27] showed good agreement. The authors also presented the trajectories of one single particle of each species during the layer inversion as well as the steady state.…”

Section: Introductionmentioning

confidence: 87%

“…The authors compared their results with experiments on relatively large beds (far from the narrow case) and the agreement between them was good. Peng et al [26] studied numerically the segregation of particles in binary SLFB by using a CFD-DEM approach.…”

Section: Introductionmentioning

confidence: 99%

Mimicking layer inversion in solid-liquid fluidized beds in narrow tubes

Cúñez

Franklin

2020

Powder Technology

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This paper investigates experimentally and numerically the dynamics of solid particles during the layer inversion of binary solid-liquid fluidized beds in narrow tubes. Layer inversion can happen in solid classifiers and biological reactors, where different solid particles coexist and segregation by diameter and density occurs. The fluidized beds were formed in a 25.4 mm-ID pipe and consisted of alumina and aluminum beads with diameters of 6 and 4.8 mm,respectively. We placed initially the lighter particles on the bottom in order to force an inversion of layers, mimicking the layer inversion mechanism. In the experiments, we filmed the bed with a high-speed camera and tracked individual beads along images, while in numerical simulations we computed the bed evolution with a CFD-DEM (computational fluid dynamics -dis-crete element method) code. We found the distances traveled by individual particles during the inversion and the characteristic time for layer inversion.

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“…An extensive review of the CFD‐DEM can be found in Zhou et al . The CFD‐DEM method has been used by Peng et al . to investigate the effect of segregation and solid dispersion in a bi‐disperse LSFB.…”

Section: Review Of Mathematical Models For Liquid–solid Fluidized Bedsmentioning

confidence: 99%

Mathematical modelling of expanded bed adsorption – a perspective on in silico process design

Koppejan

Ferreira

Lin

et al. 2018

J of Chemical Tech & Biotech

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Expanded bed adsorption (EBA) emerged in the early 1990s in an attempt to integrate the clarification, capture and initial product concentration/purification process. Several mathematical models have been put forward to describe its operation. However, none of the models developed specifically for EBA allows simultaneous prediction of bed hydrodynamics, mass transfer/adsorption and (unwanted) interactions and fouling. This currently limits the development and early optimization of EBA‐based separation processes. In multiphase reactor engineering, the use of multiphase computational fluid dynamics has been shown to improve fundamental understanding of fluidized beds. To advance EBA technology, a combination of particle, equipment and process scale models should be used. By employing a cascade of multiscale simulations, the various challenges EBA currently faces can be addressed. This allows for optimal design and selection of equipment, materials and process conditions, and reduces risks and development times of downstream processes involving EBA. © 2018 The Authors. Journal of Chemical Technology & Biotechnology published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry.

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Segregation and dispersion of binary solids in liquid fluidised beds: A CFD-DEM study

Cited by 61 publications

References 54 publications

A simple model for predicting solid concentration distribution in binary‐solid liquid fluidized beds

A simple model for predicting solid concentration distribution in binary‐solid liquid fluidized beds

Mimicking layer inversion in solid-liquid fluidized beds in narrow tubes

Mathematical modelling of expanded bed adsorption – a perspective on in silico process design

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