CFD Modeling with Experimental Validation of the Internal Hydrodynamics in a Pilot-Scale Slurry Bubble Column Reactor

Omar M. Basha; Li Weng; Zhuowu Men; Badie I. Morsi

doi:10.1515/ijcre-2015-0165

Article

CFD Modeling with Experimental Validation of the Internal Hydrodynamics in a Pilot-Scale Slurry Bubble Column Reactor

Omar M. Basha , Li Weng , Zhuowu Men and Badie I. Morsi

Published/Copyright: February 9, 2016

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From the journal International Journal of Chemical Reactor Engineering Volume 14 Issue 2

Abstract

A multiphase-Eulerian, three-dimensional (3-D), computational fluid dynamics (CFD) model was built to investigate the local hydrodynamics of a pilot-scale (0.29 m ID, 3 m height) Slurry Bubble Column Reactor (SBCR). The model was first validated against the gas holdup radial profiles in an air-water-glass beads system obtained in a 0.254 m ID and 2.5 m height column under ambient conditions at various superficial gas velocities by Yu and Kim (Bubble characteristics in the radial direction of three-phase fluidized beds. AIChE Journal 34, 2069–2072, 1988). The model was next validated against the gas holdup radial profile data for N₂-Drakeol-glass beads system obtained in a 0.44 m ID and 2.44 m height reactor, including internals, operating under ambient conditions at various superficial gas velocities by Chen et al. (Fluid dynamic parameters in bubble columns with internals. Chemical Engineering Science 54, 2187–2197, 1999). The model was also validated against experimental data obtained in our lab for N₂-Fischer Tropsch (F-T) reactor wax-Fe catalyst system obtained in a pilot-scale, Slurry Bubble column Reactor, SBCR (0.29 m ID, 3 m height) under pressures and temperatures up to 25.9 bar and 490 K, respectively. These three validations led to the selection of the turbulence and interphase drag coefficient models, and the optimization of the solution method, mesh size and structure and the step size. Moreover, the inclusion of RNG k-ε turbulence model coupled with the Wen-Yu (Mechanics of Fluidization. Chemical Engineering Progress Symposium Series 62, 100–111, 1966) / Schiller-Naumann (A drag coefficient correlation. Zeitung Ver. Deutsch. Ing 77, 318–320, 1935) drag correlations, and the mass transfer coefficients were found to provide the most accurate predictions of the experimental data. The CFD model was then used to investigate local gas holdup, liquid recirculation, local turbulence intensities, bubble diameters, and solids distribution throughout our pilot-scale SBCR, operating under typical F-T process conditions. The model predictions showed strong liquid recirculation and backmixing near the walls of the reactor, and the solid-phase velocity vectors closely followed those of the liquid-phase. A relatively high liquid turbulence intensities were observed in the vicinity of the sparger upon startup, however, after reaching a steady state, the liquid turbulence intensities became more evenly distributed throughout the reactor. The liquid turbulence intensities were slightly higher near the center of the reactor, and closely resembled the velocity vectors. Also, the Sauter mean bubble diameters increased, whereas the solids distribution decreased with reactor height above the gas distributor.

Keywords: reactors; SBCR; computational fluid dynamics; modeling; Fischer-Tropsch

Nomenclature

a: Gas-liquid interfacial area per unit liquid volume (m^–1)
AARE: Absolute average relative error: 1n∑1nPred.−Exp.Exp.×100%
BB: Birth rate of bubbles due to the turbulence induced breakup
BC: Birth rate of bubbles due to the turbulence induced coalescence
CD: Drag Coefficient
C_S: Concentration of solid particles in the slurry phase (wt. %)
C_P: Concentration of solid particles in the slurry phase (kg/m³)
C_V: Volumetric concentration of solid particles in the slurry phase (vol. %)
dC: Column diameter (m)
dp: Particle diameter (m)
d₃₂: Sauter mean gas bubble diameter (m)
DB: Death rate of bubbles due to the turbulence induced breakup
DC: Death rate of bubbles due to the turbulence induced coalescence
ep: Coefficient of restitution
g: Acceleration due to gravity, m/s²
G: Mass flow rate (kg/m²∙s)
J‾‾k: Flux
k: Turbulent kinetic energy (J/mol)
kLa: Volumetric liquid-side mass transfer coefficient (1/s)
le: Characteristic length scale of the eddies
M_W: Molecular weight (kg∙kmol^–1)
n: Bubble number density (m⁻³)
P: Pressure (bar)
P_s: Solids pressure (Pa)
P_v: Liquid-phase saturation pressure (bar)
r: Bubble radius (m)
Re: Reynolds number
Reb: Bubble Reynolds number
Rep: Particle Reynolds number
ReS−L: Solid-Liquid Reynolds number for the Wen and Yu (1966) Drag model
t: Time (s)
t_ij: Coalescence time (s)
T: Temperature (K)
u_b: Gas bubble rise velocity (m·s^–1)
u_g: Superficial gas velocity (m·s^–1)
u′: Root-mean-square of the turbulent velocity fluctuations (m·s^–1)
U: Mean velocity (m·s^–1)
v: Linear flow velocity (m/s)
veff,rad: Radial momentum transfer coefficient (m²/s)
X_W: Foaming Coefficient of the liquid-phase (See Behkish et al. 2007)

Greek symbols

Greek Letters
α: Phase void fraction (-)
Γ: Gas sparger coefficient (See Behkish et al. 2006)
εg: Experimental gas holdup
η: Kinematic viscosity (m²/s)
Θ: (m²/s²)
κ: Coefficient of bulk viscosity
λS: Solids bulk viscosity (kg/m∙s)
μ: Viscosity (kg/m∙s)
μb: Relative apparent bed viscosity
μT: Turbulent or eddy viscosity
υ: Local velocity of the dispersed phase
ξ: Dimensionless radial position
ρ: Density (kg/m³)
σ: Surface tension (N/m)
τ: Viscous stress tensor (Pa)
τrz: Reynolds shear stress
ϕ⃗: Body source per unit mass
χ: Coalescence rate of bubbles (m⁻³ s⁻¹)
Ω: Break-up rate of bubbles (m⁻³ s⁻¹)

Subscripts

g: Gas
k: Phase
l: Liquid
s: Solid
w: Wall

Acronyms
CFD: Computational Fluid Dynamics
F-T: Fischer Tropsch
GTL: Gas to Liquid

Acknowledgement

The Authors would like to thank the National Institute of Clean-and-low-carbon Energy (NICE), China for supporting this research.

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Published Online: 2016-2-9

Published in Print: 2016-4-1

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Articles in the same Issue

https://doi.org/10.1515/ijcre-2015-0165

Keywords for this article

reactors; SBCR; computational fluid dynamics; modeling; Fischer-Tropsch