Simulation of 3D freely bubbling gas–solid fluidized beds using various drag models: TFM approach

Askaripour, Hossein; Dehkordi, Asghar Molaei

doi:10.1016/j.cherd.2015.05.041

Cited by 36 publications

(7 citation statements)

References 40 publications

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“…The drag model of Syamlal and O'Brien was chosen in this study since the flow pattern and bubble formation could be predicted by it more precisely than the other drag models [25]. It is also considered as the most reliable drag model for the large particles size of 500 mm [26]. Moreover, the model of Syamlal and O'Brien and Lun et al were chosen for granular viscosity and solid granular bulk viscosity, respectively [27,28].…”

Section: Numerical Simulation 21 Setup and Boundary Conditionmentioning

confidence: 99%

CFD simulation of bubbling fluidized bed: Effects of bed column geometry on hydrodynamics of gas–solid mixing

Afrooz

Sinnathambi

Chuang

et al. 2017

Materialwissenschaft Werkst

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In this study, multiphase computational fluid dynamics (CFD) is employed to simulate and study the hydrodynamics behavior of gas‐solid mixing in a new bed column design of bubbling fluidized bed called swirl bed. The new fluidized bed is a swirl tube reactor design based on swirl tube technology. The results are compared with the conventional straight tube rector which is the scaled down version of the existing pilot plant gasifier. It is found that the usage of the swirl tube reactor design results in better lateral solid mixing inside the bed. Furthermore an increase in residence time of the particles is also observed due to the swirl motion of the particles.

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Section: Numerical Simulation 21 Setup and Boundary Conditionmentioning

confidence: 99%

CFD simulation of bubbling fluidized bed: Effects of bed column geometry on hydrodynamics of gas–solid mixing

Afrooz

Sinnathambi

Chuang

et al. 2017

Materialwissenschaft Werkst

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“…Askaripour and Dehkordi [10] modeled a 3D gas-solid fluidized bed with various drag models to compare the bed's expansion ratio and solids' velocity. A wide range of particle size, the bed's static height, and fluidization velocity were investigated in their study.…”

Section: Introductionmentioning

confidence: 99%

Using an encoder-decoder convolutional neural network to predict the solid holdup patterns in a pseudo-2d fluidized bed

Bazai

Kargar²,

Mehrabi

2021

Chemical Engineering Science

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“…A number of numerical studies were performed to study the effect of the drag model on flow predictions in various types of fluidized beds [7,12,[23][24][25][26][27][28]. Taghipour et al [7] conducted an experimental and computational study on a 2D gas-solid fluidized bed and observed that the Syamlal and O'Brien (SO) drag model shows a reasonable agreement for mean pressure drop, bed expansion, and gas-solid flow pattern.…”

Section: Introductionmentioning

confidence: 99%

Effect of Drag Models on the Numerical Simulations of Bubbling and Turbulent Fluidized Beds

et al. 2021

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Granular option enabled two-fluid model coupled with different homogeneous and heterogeneous drag correlations, i.e., Gidaspow, Syamlal and O'Brien, Beetstra, Brucato, Gibilaro, energy minimization multiscale method (EMMS), and Tenneti, are employed for the prediction of bubbling and turbulent fluidized-bed characteristics. Numerically predicted results are validated against the literature data in terms of bubble shape and diameter, axial and radial variation of timeaveraged void fraction, pressure drop, and bed expansion. The Gidaspow, Syamlal and O'Brien drag model-predicted mean void fraction and bubble shapes are close to the experiments in bubbling and turbulent fluidized beds with both the 2D and 3D geometries. All drag models overpredicted the pressure drop at low superficial gas velocities in a turbulent fluidized bed.

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Simulation of 3D freely bubbling gas–solid fluidized beds using various drag models: TFM approach

Cited by 36 publications

References 40 publications

CFD simulation of bubbling fluidized bed: Effects of bed column geometry on hydrodynamics of gas–solid mixing

CFD simulation of bubbling fluidized bed: Effects of bed column geometry on hydrodynamics of gas–solid mixing

Using an encoder-decoder convolutional neural network to predict the solid holdup patterns in a pseudo-2d fluidized bed

Effect of Drag Models on the Numerical Simulations of Bubbling and Turbulent Fluidized Beds

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