Numerical study of gas–solid drag models in a bubbling fluidized bed

Zinani, Flávia Schwarz Franceschini; Philippsen, Caterina Gonçalves; Indrusiak, Maria Luiza Sperb

doi:10.1080/02726351.2016.1192570

Cited by 9 publications

(4 citation statements)

References 29 publications

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“…Luna et al 34 noted that the lattice Boltzmann method (LBM)‐based drag models provided better predictions compared to empirical drag models by accounting heterogeneous structures in the bubbling fluidization regime. Further, Zinani et al 23 found a significant difference in the instantaneous and time‐averaged results with different drag laws. In the above studies, simulations are conducted with 2D geometries to minimize the computation time with reasonable accuracy in predictions.…”

Section: Introductionmentioning

confidence: 98%

“…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%

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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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Section: Introductionmentioning

confidence: 98%

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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“…However, the use of CFD in simulating gas–solid particle systems is still constrained by the complexity of mathematical models, which often involve a series of theoretical or empirical correlations. [ 6 ] In many cases, CFD may require the incorporation of additional mathematical models to achieve realistic system hydrodynamics. Upadhyay et al [ 7 ] applied artificial neural network (ANN) for predicting solid volume fraction along the riser height.…”

Section: Introductionmentioning

confidence: 99%

CFD‐ANN coupling model simulation of gas–solid feeding design for ternary biomass mixtures in bubbling fluidized bed gasifier

Soanuch,

Pareek,

Piumsomboon

et al. 2024

Can J Chem Eng

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The performance of continuous feeding fluidized bed reactors is significantly influenced by their design. These reactors can effectively operate with a wide range of biomass mixtures. Therefore, it is imperative to carefully design the gas distributor plate and solid tube inlet to ensure stable fluidization and uniform distribution of fluidizing gas and solid particles within the reactor. This study investigated the impact of gas–solid feeder design in bubbling fluidized bed gasifier for biomass mixtures on system hydrodynamics, employing a computational fluid dynamics–artificial neural network (CFD‐ANN) coupling model to achieve more realistic simulations. A 2k factorial experimental design was adopted to inquire the impact of gas and solid feeding systems. The responses under investigation included the gas–solid mixing index and the solid residence time, both of which hold pivotal roles in specific chemical processes related to biomass utilization in fluidized bed technology. All cases were successfully simulated, and the results uncovered that the position and length of the solid inlet tube wielded a significant influence on reactor performance, particularly concerning solid residence time. Furthermore, the designs of the gas distributor were identified as critical factors capable of enhancing system turbulence and mixing. In summary, the results showed the potential for enhancing reactor performance through the optimization of gas–solid feeding systems and underscored the efficacy of the ANN drag model in simulating continuous biomass gasification systems.

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“…MFiX (which is an acronym for "Multiphase Flow with Interphase eXchanges") is developed by the National Energy Technology Laboratory of the United States. Presently, it is employed by researchers all around the world for various purposes [23][24][25][26][27][28][29][30][31][32]. We chose it because of its unique advantages: it is an open-source program that is entirely transparent to the user and editable, but it is also provided with a user-friendly graphical user interface (GUI).…”

Section: Introductionmentioning

confidence: 99%

A Discrete Element Method Study of Solids Stress in Cylindrical Columns Using MFiX

Marchelli

Felice

2020

Processes

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Friction phenomena play a key role in discrete element method (DEM) modeling. To analyze this aspect, we employed the open-source program MFiX to perform DEM simulations of cylindrical vertical columns filled with solid particles. These are still associated with and described by the pioneering model by the German engineer H.A. Janssen. By adapting the program’s code, we were able to gather numerous insights on the stress distribution within the solids. The column was filled with different amounts of solids and, after the system had stabilized, we assessed the pressure in the vertical and radial directions and the distribution of the friction force for all particles. An analysis of the bottom pressure for varying particle loads allowed us to infer that the program can correctly predict the expected asymptotical behavior. After a detailed assessment of the behavior of a single system, we performed a sensitivity analysis taking into account several of the variables employed in the simulations. The friction coefficient and filling rate seem to affect the final behavior the most. The program appears suitable to describe friction phenomena in such a static system.

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Numerical study of gas–solid drag models in a bubbling fluidized bed

Cited by 9 publications

References 29 publications

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

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

CFD‐ANN coupling model simulation of gas–solid feeding design for ternary biomass mixtures in bubbling fluidized bed gasifier

A Discrete Element Method Study of Solids Stress in Cylindrical Columns Using MFiX

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