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Research Papers: Multiphase Flows

A CFD Study of Pressure Fluctuations to Determine Fluidization Regimes in Gas–Solid Beds

[+] Author and Article Information
Mirka Deza

e-mail: mdeza@iastate.edu

Francine Battaglia

Department of Mechanical Engineering,
Virginia Tech,
Blacksburg, VA 24061

For the remainder of the discussion, the word “cotton” will refer to “cotton stalks.”

1Corresponding author.

Contributed by the Fluids Engineering Division of ASME for publication in the Journal of Fluids Engineering. Manuscript received August 27, 2012; final manuscript received May 20, 2013; published online August 6, 2013. Assoc. Editor: Michael G. Olsen.

J. Fluids Eng 135(10), 101301 (Aug 06, 2013) (11 pages) Paper No: FE-12-1408; doi: 10.1115/1.4024750 History: Received August 27, 2012; Revised May 20, 2013

Reliable computational methods can provide valuable insight into gas–solid flow processes and can be used as a design tool. Of particular interest in this study is the hydrodynamics of a binary mixture of sand–biomass in a fluidized bed. Biomass particulates vary in size, shape, and density, which inevitably alter how well the particles fluidize. Our study will use computational fluid dynamics (CFD) to interpret the hydrodynamic states of a fluidized bed by analyzing the local pressure fluctuations of beds of sand and a binary mixture of cotton stalks and sand over long time periods. Standard deviation of pressure fluctuations will be compared with experimental data to determine different fluidization regimes at inlet gas velocities ranging from two to nine times the minimum fluidization velocity. We will use Bode plots to present the pressure spectra and reveal characteristic frequencies that describe the bed hydrodynamics for different fluidization regimes. This work will present CFD as a useful tool to perform that analysis. Other important contributions include the study of pressure fluctuations of a fluidized bed in bubbling, slugging, and turbulent regimes, and the analysis of a binary mixture using CFD.

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Figures

Grahic Jump Location
Fig. 1

Schematic of the 3D rectangular cylinder representing the experiments by Zhang et al. [20,21]

Grahic Jump Location
Fig. 2

Pressure drop versus inlet gas velocity comparing experiments [20] and simulations of a sand fluidized bed for three different grid sizes

Grahic Jump Location
Fig. 3

Pressure drop versus inlet gas velocity comparing experiments [20] and 2D simulations of a sand fluidized bed

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Fig. 4

Pressure drop versus inlet gas velocity comparing experiments [20] and 2D and 3D simulations of sand and cotton–sand fluidized beds

Grahic Jump Location
Fig. 5

Standard deviation of pressure drop comparing experiments [21] and 2D simulations of sand and cotton–sand fluidized bed versus inlet gas velocity

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Fig. 6

Best fit of standard deviation of pressure drop for sand and cotton–sand fluidized beds compared with experiments [21]

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Fig. 7

Time-averaged void fraction of sand (top row) and cotton–sand (bottom row) fluidized beds using a 3D domain with inlet velocities of (a) Ug = 0.8 m/s, (b) Ug = 1.2 m/s, (c) Ug = 1.6 m/s, and (d) x–y average void fraction for the three cases

Grahic Jump Location
Fig. 8

Instantaneous void fraction of a sand fluidized bed at an inlet velocity Ug = 0.8 m/s (top row), Ug = 1.2 m/s (middle row), and Ug = 1.6 m/s (bottom row) at three different times

Grahic Jump Location
Fig. 9

Pressure drop fluctuation (a) with time, (b) as a PSD analysis, and (c) as a Bode plot for a sand fluidized bed with inlet velocity of 0.8 m/s using a 3D domain

Grahic Jump Location
Fig. 10

Pressure drop fluctuation (a) with time, (b) as a PSD analysis, and (c) as a Bode plot for a sand fluidized bed with inlet velocity of 1.2 m/s using a 3D domain

Grahic Jump Location
Fig. 11

Pressure drop fluctuation (a) with time, (b) as a PSD analysis, and (c) as a Bode plot for a sand fluidized bed with inlet velocity of 1.6 m/s using a 3D domain

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