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Research Papers: Multiphase Flows

CFD Modeling and X-Ray Imaging of Biomass in a Fluidized Bed

[+] Author and Article Information
Mirka Deza

Department of Mechanical Engineering, Virginia Polytechnic Institute and State University, Blacksburg, VA 24061

Nathan P. Franka, Theodore J. Heindel

Department of Mechanical Engineering, Iowa State University, Ames, IA 50011

Francine Battaglia1

Department of Mechanical Engineering, Virginia Polytechnic Institute and State University, Blacksburg, VA 24061fbattaglia@vt.edu

1

Corresponding author.

J. Fluids Eng 131(11), 111303 (Oct 29, 2009) (11 pages) doi:10.1115/1.4000257 History: Received January 29, 2009; Revised August 25, 2009; Published October 29, 2009

Computational modeling of fluidized beds can be used to predict the operation of biomass gasifiers after extensive validation with experimental data. The present work focused on validating computational simulations of a fluidized bed using a multifluid Eulerian–Eulerian model to represent the gas and solid phases as interpenetrating continua. Simulations of a cold-flow glass bead fluidized bed, using two different drag models, were compared with experimental results for model validation. The validated numerical model was then used to complete a parametric study for the coefficient of restitution and particle sphericity, which are unknown properties of biomass. Biomass is not well characterized, and so this study attempts to demonstrate how particle properties affect the hydrodynamics of a fluidized bed. Hydrodynamic results from the simulations were compared with X-ray flow visualization computed tomography studies of a similar bed. It was found that the Gidaspow (blending) model can accurately predict the hydrodynamics of a biomass fluidized bed. The coefficient of restitution of biomass did not affect the hydrodynamics of the bed for the conditions of this study; however, the bed hydrodynamics were more sensitive to particle sphericity variation.

Copyright © 2009 by American Society of Mechanical Engineers
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Figures

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Figure 1

Schematic of the (a) experimental setup for a 9.5 cm ID fluidized bed and (b) the 2D plane representing the simulated bed chamber of the cylindrical reactor

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Figure 15

Time-averaged void fraction profiles of the ground walnut shell fluidized bed comparing the simulations using different particle sphericity with the experiments for data spatially averaged across the bed width versus axial direction

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Figure 14

Time-averaged void fraction contours of the ground walnut shell fluidized bed comparing the simulations using (a) ψ=0.5, (b) ψ=0.6, and (c) ψ=0.7 with the CT images for an (d) X-slice and (e) Y-slice

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Figure 13

Time-averaged void fraction contours of the ground walnut shell fluidized bed comparing the simulations using (a) e=0.75, (b) e=0.85, and (c) e=0.95

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Figure 12

Pressure drop versus superficial gas velocity through the ground walnut shell bed comparing the experiments with the simulations using the Gidaspow drag model at Ug=1.3Umf=24.3 cm/s

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Figure 11

Instantaneous gas-solid distributions of the ground walnut shell fluidized bed. For each pair of images, the left side is the X-ray radiograph and the right side is the void fraction contour from the simulation using the Gidaspow drag model at (a) 10 s, (b) 20 s, (c) 30 s, and (d) 40 s. Note: the gray scale legends are only applicable to the simulations.

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Figure 10

Time-averaged void fraction profiles of the glass bead fluidized bed comparing the simulations using different drag models with the experiments for data spatially averaged across the bed width versus axial direction

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Figure 9

Time-averaged void fraction profiles of the glass bead fluidized bed comparing the simulations using different drag models with the experiments at (a) z=4 cm and (b) z=8 cm

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Figure 8

Time-averaged void fraction contours of the glass bead fluidized bed comparing the simulations using the (a) Syamlal–O’Brien drag model and (b) the Gidaspow drag model with the CT images for an (c) X-slice and (d) Y-slice

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Figure 7

Pressure drop versus superficial gas velocity through the glass bead bed comparing the simulations using different drag models with the experiments

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Figure 6

Time-averaged void fraction profiles of the glass bead fluidized bed comparing the simulations using different grid resolutions with the experiments for data spatially averaged across the bed width versus axial direction

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Figure 5

Time-averaged void fraction profiles of the glass bead fluidized bed comparing the simulations using different grid resolutions with the experiments at (a) z=4 cm and (b) z=8 cm

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Figure 4

Time-averaged void fraction contours of the glass bead fluidized bed comparing the simulations using grid resolutions of (a) 19×40, (b) 38×80, and (c) 76×160 with the CT images for an (d) X-slice and (e) Y-slice

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Figure 3

Instantaneous gas-solid distributions of the glass bead fluidized bed. For each pair of images, the left side is the X-ray radiograph, and the right side is the void fraction contour from the simulation using the medium grid size at (a) 10 s, (b) 20 s, (c) 30 s, and (d) 40 s. Note: the gray scale legends are only applicable to the simulations.

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Figure 2

Time-averaged void fraction profiles of the glass bead bed simulations comparing six grid resolutions at (a) z=4 cm and (b) z=8 cm

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