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WASHINGTON UNIVERSITY
SEVER INSTITUTE
DEPARTMENT OF ENERGY, ENVIRONMENTAL AND CHEMICAL
ENGINEERING___________________________________________________________________
Bubble and Slurry Bubble Column Reactors: Mixing, Flow Regime Transition and
Scaleup
by
Ashfaq Shaikh
Prepared under the direction of
Professor Muthanna H. Al-Dahhan
___________________________________________________________________
A dissertation presented to the Sever Institute of Washington University
in partial fulfillment of the requirements for the degree of
DOCTOR OF SCIENCE
August 2007
Saint Louis, Missouri, USA
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WASHINGTON UNIVERSITY
SEVER INSTITUTE
DEPARTMENT OF ENERGY, ENVIRONMENTAL AND CHEMICAL ENGINEERING
_________________________________________________________________________
ABSTRACT
_____________________________________________________________
Bubble and Slurry Bubble Column Reactors: Mixing, Flow Regime Transition and
Scaleup
by
Ashfaq Shaikh
ADVISOR: Professor Muthanna H. Al-Dahhan_____________________________________________________________
August 2007
Saint Louis, Missouri, USA_____________________________________________________________
Bubble and slurry bubble column reactors are used for a wide range of applications in the
chemical, petrochemical, and biochemical industries. A thorough understanding of their
complex flow structure is crucial for design and scale-up of these reactors.
This study used a multi-pronged approach to advance the state of knowledge of the
hydrodynamics of high pressure bubble and slurry bubble column reactors. First, the
effect of liquid phase physical properties and solids loading on the flow structure of
slurry bubble column reactors was studied, with particular emphasis on the churn-
turbulent flow regime. This study was performed in a system using a liquid phase which
at room temperature mimics Fischer-Tropsch (FT) wax at FT synthesis conditions and a
gas at a pressure that mimics syngas density. Computer Automated Radioactive Particle
Tracking (CARPT) and single source -ray Computed Tomography (CT) were utilized to
compute the time-averaged solids velocity fields, turbulent parameters profiles, and
time-averaged solids and gas holdup profiles.
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The second part of this study included the development of non-invasive techniques, such
as CT and Nuclear Gauge Densitometry (NGD), for delineation of flow regimes in
bubble column reactors. The capability of these techniques to identify flow regime
transition was evaluated and compared against conventional methods of flow regime
demarcations, such as the change in the slope of the gas holdup curve and the drift flux
plot. Special attention was given to NGD to develop a non-invasive and online flow
regime measurement and monitoring technique. Hence, the guidelines and rules were set
up for these techniques (CT and NGD) by developing its flow regime identifiers. Both
of these techniques are active, i.e., involve penetration of-rays through the column,
and therefore are expected to represent the prevailing hydrodynamics with fidelity, even
in industrial scale columns.
The last part tackled the challenging task of extrapolating small diameter behavior to
large diameters, a task that essentially needs criteria for hydrodynamic similarity. Based
on a comprehensive review of the reported scaleup procedures, this work proposed a new
hypothesis for hydrodynamic similarity and subsequently for scale-up of bubble column
reactors operating in the regime of industrial interest, i.e., the churn-turbulent regime.
This task was performed in two stages: first, the proposed hypothesis was experimentally
evaluated for hydrodynamic similarity using existing CT and CARPT; second, for a
priori prediction of hydrodynamic parameters to maintain such similarity, state-of-the-art
correlations were developed using an Artificial Neural Network (ANN). The current
study showed that the similarity of overall gas holdup and its radial profile is pertinent for
similar recirculation and mixing in two systems. The similarity based only on global
hydrodynamics should be exercised with prudence.
The work accomplished in this study, and in particular the concepts developed in last two
parts, are, in retrospect, generic for multiphase reactors with bubble columns as an
example. Hence it presents promising avenues to explore them in other configurations of
multiphase reactors.
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To
my Ammiji, Abbaji, and Didi
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Copyright by
Ashfaq Shaikh
2007
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Contents
Page No. Tables . ix
Figures ... x
Nomenclature xix
Acknowledgements ... xxiv
1. Introduction 1
1.1 Motivation . 8
1.2 Objectives . 10
1.3 Thesis Organization . 12
2. Literature Review 15
2.1 Mixing of liquid/slurry phase . 15
2.2 Flow Regime Transition . 18
2.2.1 Flow Regime Types and Characteristics 19
2.2.2 Methods for Flow Regime Identification .. 21
2.2.3 Prediction of Flow Regime Transition .. 26
2.2.4 Remarks . 26
2.3 Scaleup of Bubble Column Reactors 28
2.3.1 Reported status of scaleup in literature .. 28
2.3.2 Reported status of scaleup in industry 37
3. Experimental Investigation of the Hydrodynamics of Slurry
Bubble Column: Phase Holdups Distribution via Computed
Tomography . 39
3.1 Choice of Phases .. 40
3.2 Experimental Details 42
3.3 Single Source Computed Tomography (CT) 45
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3.4 Results and Discussion. 47
3.4.1 Overall gas holdup ... 47
3.4.2 Drift Flux Model .. 49
3.4.3 Cross-sectional Distribution of Gas Holdup 51
3.4.4 Time averaged gas and solids holdup radial profile 53
3.4.5 Effect of liquid phase physical properties on gas and solids
holdup radial profile.
55
3.4.6 Effect of solids loading on gas and solids holdup radial
profile . 63
3.4.8 Normalized gas holdup radial profile . 67
3.4.9 Normalized solids holdup radial profile . 67
3.4.7 Comparison with predictions of Sedimentation-DispersionModel (SDM)
..
68
3.5 Remarks 70
4. Experimental Investigation of the Hydrodynamics of Slurry
Bubble Column: Solids Flow Pattern via CARPT 73
4.1 Experimental . 73
4.2 Computer Automated Radioactive Particle Tracking (CARPT) .. 74
4.3 Results and Discussion . 75
4.3.1 Time averaged solids velocities .. 75
4.3.2 Turbulent stresses and kinetic energy .. 81
4.3.3 Effect of liquid phase physical properties on solids axial
velocity and turbulent parameters parameters. 84
4.3.4 Effect of solids loading on solids axial velocity and turbulentparameters .. 89
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4.3.5 Cross-sectional averaged turbulent stresses . 93
4.3.6 Turbulent eddy viscosity 93
4.3.7 Eddy diffusivities . 93
4.4 Remarks 94
5. Flow Regime Transition ... 95
5.1 Flow Regime Transition using CT ... 95
5.1.1 Experimental setup and conditions 96
5.1.2 Results and Discussion ... 96
5.1.3 Evaluation of the empirical correlations . 103
5.2 Flow Regime Transition using NGD 105
5.2.1 Nuclear Gauge Densitometry (NGD) 106
5.2.2 Results and Discussion ... 109
5.2.3 Evaluation of the flow regime identifiers developed forNGD ... 130
5.2.4 Evaluation of literature correlations 142
5.3 Remarks 144
6. Scaleup of Bubble Column Reactors ... 147
6.1 Hypothesis for hydrodynamic similarity .. 147
6.2 Experimental conditions ... 149
6.3 Results ... 151
6.3a Discussion 162
6.4 Development of correlations for a priori prediction of
hydrodynamic parameters 166
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6.5 Remarks 167
7. Summary and Recommendations ... 168
7.1 Summary and Conclusions ... 168
7.2 Recommendations . 172
Appendix-A. Phase Distribution in Three Dynamic Phase Systems via
Combination of Computed Tomography (CT) and Electrical
Capacitance Tomography (ECT) . 175
Appendix -B. Experimental Investigation of Hydrodynamics of Slurry
Bubble Column Reactors via CT 186
Appendix -C. Experimental Investigation of Hydrodynamics of Slurry
Bubble Column Reactors via CARPT. 203
Appendix -D. Sedimentation-Dispersion Model 231
Appendix -E. Material Safety Data Sheet for Therminol LT . 236
Appendix F. Development of Artificial Neural Network (ANN)
Correlations for Hydrodynamic Parameters . 244
References 269
Vita 279
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Tables
3-1 Physical properties of Sasol wax and Therminol LT 40
3-2 Experimental conditions employed in this study 45
3-3 The values of drift flux parameters at the studied experimental
conditions
50
4-1 CARPT experimental conditions 73
5-1 Comparison of experimental and predicted transition velocities
from the available correlations in an air-Therminol LT system
at various operating pressures
105
5-2 Characteristics frequencies in bubble column (Drahos et al.,
1991)
109
5-3 Slope of power spectra at studied operating conditions 128
5-4 Experimental conditions for evaluation of flow regimeidentifiers
131
5-5 Statistical comparisons of prediction of correlations with
experimental data
144
6-1 List of similarity conditions in a 6 diameter stainless steelcolumn
151
6-2 List of experimental conditions of mismatch gas holdup radial
profile in a 6 diameter stainless steel column
152
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Figures
1-1 Schematic diagram of bubble/slurry bubble column 2
1-2 Projected US energy and oil production and consumption [Source:National Energy Policy, White House Report, 2001]
3
1-3 US vulnerability to oil disruption (Williams and AlHajji, 2003) 4
1-4 a) M. King Hubbert at 1956 API Spring Meeting proposing peaktheory b) Popular Hubbert-peak curve.
5
1-5 Relationship between fuel economy and urban air benefits (Koelmel,
2005)
6
1-6 CAPEX cost for GTL (Rahmim, 2003) 6
1-7 Projected economies of scale for GTL-FT process (Brown, 2003) 7
2-1 Various flow regimes in bubble column reactors 20
2-2 Flow regime map for air-water system at ambient pressure a) Shah et
al., 1982 and b) Zhang et al., 1997
21
2-3 Photographs of bubbly and churn-turbulent flow in 2-D column 22
2-4 Typical overall gas holdup curve a) Shaikh and Al-Dahhan, 2005; andb) Rados, 2003
23
2-5 Typical drift flux plot using Wallis (1969) approach (Deckwer et al.,
1981)
24
2-6 Average bubble-swarm velocity in air-ethanol-Co (van Baten et al.,
2003)
35
3-1 Bubble column reactor of 6 diameter used for CARPT/CT
measurements. CT1, CT2, and CT3 represent the scan levels used in
this investigation.
44
3-2 Configuration of the CT experimental setup (Kumar, 1994) 46
3-3 Effect of solids loading on a) overall gas holdup curve and b) drift
flux plot in air-Therminol LT-glass beads system at ambientconditions in 6 steel column
48
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3-4 Effect of operating pressure on overall gas holdup at various solidsloading in air-Therminol LT glass beads system in 6 steel column
49
3-5 Cross-sectional distribution of gas holdup in 6 diameter stainless
steel column using air-Therminol LT-glass beads system at differentsuperficial gas velocities, solids loading of 9.1 % vol. and P = a) 0.1,
and b) 1 MPa.
51
3-6 Cross-sectional distribution of gas holdup in 6 diameter stainless
steel column using air-Therminol LT-glass beads system at superficial
gas velocity of 30 cm/s, operating pressure of 1 MPa, and solidsloading of a) 9.1 and b) 25 % volume.
52
3-7 a)Gas holdup and b) solids holdup radial profile in air-Therminol LT-
glass beads system using 9.1 % vol. solids loading at superficial gas
velocity of 8 cm/s and ambient pressure
54
3-8 a) Gas holdup and b) solids holdup radial profile in air-Therminol LT-glass beads system using 25 % vol. solids loading at superficial gas
velocity of 30 cm/s and operating pressure of 1 MPa
54
3-9 Overall gas holdup curve using air-water-glass beads (Rados, 2003)
and air-Therminol LT-glass beads system at ambient conditions,
solids loading of 9.1 % vol. in a 6 diameter column.
55
3-10 Effect of physical properties on a) gas holdup, and b) solids holdupradial profile at P = 0.1 MPa, z/D = 5.5, solids loading of 9.1 % vol.
and Ug = a) 8, b) 14, and c) 30 cm/s in 6 diameter steel column
58
3-11 Overall gas holdup curve using air-water-glass beads (Rados, 2003)and air-Therminol LT-glass beads system at operating pressure of 1
MPa, solids loading of 9.1 % vol. in a 6 diameter column..
60
3-12 Effect of physical properties on a) gas holdup, and b) solids holdup
radial profile at P = 1 MPa, z/D = 5.5 and solids loading of 9.1 % vol.
at Ug = a) 8, b) 14, and c) 30 cm/s in 6 diameter steel column
61
3-13 Effect of solids loading on gas and solids holdup radial profile in air-
Therminol LT-glass beads system at ambient pressure at Ug = a) 20and b) 30 cm/s 6 diameter steel column
64
3-14 Effect of solids loading on gas and solids holdup radial profile in air-
Therminol LT-glass beads system at Ug = a) 20 and b) 30 cm/s and P= 1 MPa in 6 steel column
66
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3-15 Predictions of the SDM in air-Therminol LT-glass beads system at
ambient pressure and solids loading of a) 9.1 and b) 25 % vol. in 6diameter column
68
3-16 Comparison of the SDM predictions with experimental data in air-
Therminol LT-glass beads system at ambient pressure, solids loadingof 9.1 % vol., and Ug = a) 8 and b) 30 cm/s in 6 diameter column
69
3-17 Comparison of the SDM predictions with experimental data in air-Therminol LT-glass beads system at ambient pressure. a) effect of
superficial gas velocity at solids loading of 25 % vol. and b) effect of
solids loading at Ug = 30 cm/s in 6 diameter column
70
4-1 Configuration of the CARPT experimental setup (Degaleesan, 1997) 75
4-2 Time and azimuthally averaged solids velocity in air-Therminol LT-
glass beads system at Ug = 30 cm/s, P = 0.1 MPa, and solids loading =9.1 % volume a) uz-ur vector map, b) axial, and c) radial velocity
components
77
4-3 Radial profile of solids a) axial, b) radial, and c) tangential velocity in
air-Therminol LT-glass beads system at Ug = 30 cm/s, P = 0.1 MPa,and solids loading = 9.1 % volume
77
4-4 Probability distribution function of solids axial velocities at L/D = 2.5at various dimensional radius positions of r/R = 0.063, 0.44, and 0.96
at Ug = 30 cm/s, P = 0.1 MPa, and solids loading of 9.1 % volume
78
4-5 Probability distribution function of solids axial velocities at L/D = 2.5,
5.5, and 9 along the column radius at r/R = 0.063, 0.44, 0.69, and 0.96
at Ug = 30 cm/s, P = 0.1 MPa, and solids loading of 9.1 % volume
79
4-6 Probability distribution function of solids axial velocities in fully
developed flow in the column center and near the wall at a) 30 cm/s,9.1 % vol., and 0.1 MPa, b) 30 cm/s, 9.1 % vol., and 1.0 MPa, and c)
30 cm/s, 25 % vol., and 1.0 MP in 6 diameter stainless steel column.
80
4-7 Radial profile of solids a) turbulent kinetic energy, and b) axial, b)
radial, and c) tangential normal stresses in air-Therminol LT-glass
beads system at Ug = 30 cm/s, P = 0.1 MPa, and solids loading = 9.1% volume.
82
4-8 Radial profile of solids shear stress components in an air-Therminol
LT-glass beads system at Ug = 30 cm/s, P = 0.1 MPa, and solidsloading = 9.1 % volume
84
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4-9 Comparison of radial profile of a) gas holdup, b) solids axial velocity
c) solids TKE, and d) solids shear stress in air-water- glass beads andair-Therminol LT-glass beads system at Ug = 30 cm/s, P = 0.1 MPa,
and solids loading of 9.1 % vol.
86
4-10 Comparison of radial profile of a) gas holdup, b) solids axial velocityc) solids TKE, and d) solids shear stress in air-water-glass beads and
air-Therminol LT-glass beads system at Ug = 30 cm/s, P = 1 MPa, and
solids loading of 9.1 % vol.
87
4-11 Effect of solids loading on radial profile of solids a) axial velocity, b)
turbulent kinetic energy, c) axial normal stress, and d) shear stress inair-Therminol LT-glass beads system at Ug = 20 cm/s, and P = 0.1
MPa.
89
4-12 Effect of solids loading on radial profile of solids a) axial velocity, b)
turbulent kinetic energy, c) axial normal stress, and d) shear stress inair-Therminol LT-glass beads system at Ug = 30 cm/s, and P = 0.1
MPa
90
4-13 Effect of solids loading on radial profile of solids a) axial velocity, b)
turbulent kinetic energy, c) axial normal stress, and d) shear stress inair-Therminol LT-glass beads system at Ug = 20 cm/s, and P = 1 MPa
91
4-14 Effect of solids loading on radial profile of solids a) axial velocity, b)turbulent kinetic energy, c) axial normal stress, and d) shear stress in
air-Therminol LT-glass beads system at Ug = 30 cm/s, and P = 1 MPa.
92
5-1 Gas holdup radial profile at various superficial gas velocities in an air-
Therminol LT system at ambient condition in a 0.162 m steel column.
97
5-2 a) Cross-sectional averaged gas holdup versus superficial gas velocityand b) Drift flux plot based on cross-sectional averaged gas holdup in
an air-Therminol LT system at ambient conditions in a 0.162 m steel
column.
99
5-3 Evolution of steepness parameter with superficial gas velocity in an
air-Therminol LT system at ambient conditions in a 0.162 m steel
column.
100
5-4 Gas holdup radial profile at various superficial gas velocities in an air-
Therminol LT system at operating pressure of 0.4 MPa in a 0.162 msteel column.
100
5-5 a) Gas holdup curve based on cross-sectional averaged gas holdup andb) Flux plot based on cross-sectional averaged gas holdup in an air-
101
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Therminol LT system at operating pressure of 0.4 MPa in a 0.162 m
steel column.
5-6 a) Gas holdup curve based on cross-sectional averaged gas holdup and
b) Drift flux plot based on cross-sectional averaged gas holdup in an
air-Therminol LT system at operating pressure of 1.0 MPa in a 0.162m steel column.
102
5-7 Evolution of steepness parameter with superficial gas velocity in anair-Therminol LT system at operating pressures of 0.4 and 1 MPa in a
0.162 m steel column
103
5-8 Experimental setup of Nuclear Gauge Densitometry (NGD) 108
5-9 Overall gas holdup curve using an air-water system at ambient
conditions in 0.1012 m diameter column
110
5-10 Drift flux plot using an air-water system at ambient conditions in
0.1012 m diameter column
110
5-11 Time-series of photon count fluctuations in 0.1012 m diameter column
in a) empty column and b) water (no gas flow).
111
5-12 Time-series of photon count fluctuations in 0.1012 m diameter column
using air-water system at superficial gas velocity of in a) 1, b) 3, c) 7,and d) 11 cm/s at ambient conditions.
112
5-13 Variation of variance of photon counts fluctuations with superficial
gas velocity in 0.1012 m diameter column using air-water system at
ambient conditions.
114
5-14 Variation of variance of pressure drop fluctuations with superficial gas
velocity in 0.1012 m diameter column using air-water system at
ambient conditions (Reproduced from Lin et al., 1999).
115
5-15 The coefficient of departure from Poisson distribution versus
superficial gas velocity in 0.1012 m diameter column using an air-water system at ambient conditions.
117
5-16 Autocorrelation curve at superficial gas velocities of a) 1, b) 3, and c)4 cm/s using an air-water system in 0.1012 m diameter column at
ambient conditions.
118
5-17 Autocorrelation curve at superficial gas velocities of a) 7, b) 9, and c)11 cm/s using an air-water system in 0.1012 m diameter column at
ambient conditions.
119
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5-18 Typical log-log plot of normalized psdf at superficial gas velocities ofa) 1, b) 3, c) 4, d) 6, e) 9, and f) 11 cm/s using an air-water system in
0.1012 m diameter column at ambient conditions.
122
5-19 Power spectra of liquid velocity fluctuations in a bubble column byZarzewski et al. (1981). 124
5-20 LDA axial velocity signal power spectra a) D = 15 cm, Ug = 2.7 cm/s,z/D = 5.5, b) D = 23 cm, Ug = 1.2 cm/s, z/D = 6, and c) D = 40 cm,
Ug = 5.5 cm/s, z/D = 5 (Groen, 2004)
125
5-21 Log-log plot of normalized psdf of photon counts history obtained in
a) empty column and b) water (with no gas flow).
127
5-22 Log-log plot of normalized psdf with fitted slope line at superficial
gas velocities of a) 4, b) 6, c) 9, and d) 11 cm/s using an air-watersystem in 0.1012 m diameter column at ambient conditions
127
5-23 a) Overall gas holdup curve and b) drift flux plot in an air-water
system at ambient pressure in 6 diameter stainless steel column
132
5-24 Variation of coefficient of departure, Dp with superficial gas velocity
in an air-water system at ambient pressure in 6 diameter stainless
steel column
132
5-25 Autocorrelation curve in a) bubbly flow (Ug = 2 cm/s) and b) churn-turbulent flow (Ug = 20 cm/s) at ambient pressure using an air-water
system.
133
5-26 Psdf plot at superficial gas velocity of a) 2 cm/s, b) 7 cm/s, and c) 20cm/s and ambient pressure using an air-water system in 6 diameter
stainless steel column.
133
5-27 a) Overall gas holdup curve and b) drift flux plot in an air-water
system at operating pressure of 1 MPa in 6 diameter stainless steel
column
134
5-28 Variation of coefficient of departure, Dp, with superficial gas velocity
in an air-water system at operating pressure of 1 MPa in 6 diameterstainless steel column
135
5-29 Autocorrelation curve in a) bubbly flow (Ug = 2 cm/s) and b) churn-
turbulent flow (Ug = 20 cm/s) at operating pressure of 1 MPa using anair-water system.
135
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5-30 Psdf plot at superficial gas velocity of a) 2 cm/s, b) 10 cm/s, and c) 20
cm/s and operating pressure of 1 MPa using an air-water system in 6diameter stainless steel column.
135
5-31 a) Overall gas holdup curve and b) drift flux plot in an air-C9-C11
system at operating pressure of 0.1 MPa in 6 diameter stainless steelcolumn
136
5-32 Variation of coefficient of departure, Dp, with superficial gas velocityusing an air-C9-C11 system at operating pressure of 0.1 MPa in 6
diameter stainless steel column
137
5-33 Autocorrelation curve in a) bubbly flow (Ug = 2 cm/s) and b) churn-
turbulent flow (Ug = 20 cm/s) at ambient pressure using an air-C9-C11
system.
137
5-34 Psdf plot at superficial gas velocity of a) 2 cm/s, b) 12 cm/s, and c) 20cm/s and ambient pressure using an air- C9-C11 system in 6 diameter
stainless steel column.
138
5-35 a) Overall gas holdup curve and b) drift flux plot in an air-C9-C11
system at operating pressure of 1 MPa in 6 diameter stainless steelcolumn
138
5-36 Variation of coefficient of departure, Dp with superficial gas velocityusing an air-C9-C11 system at operating pressure of 1 MPa in 6
diameter stainless steel column
139
5-37 Autocorrelation curve in a) bubbly flow (Ug = 2 cm/s) and b) churn-
turbulent flow (Ug = 20 cm/s) at operating pressure of 1 MPa using an
air-C9-C11 system.
139
5-38 Psdf plot at superficial gas velocity of a) 2 cm/s, b) 14 cm/s, and c) 20
cm/s and operating pressure of 1 MPa using an air- C9-C11 system in6 diameter stainless steel column.
140
5-39 Comparison of reported correlations with transition velocitiesobtained based on variation in Dp of photon counts history in a) an
air-water system b) an air- C9-C11 system at ambient and high
pressure.
143
6-1 Comparison of gas holdup radial profile in 6 column using an air-
water system at two different operating conditions [D6U12P7Water: 7
bar, 12 cm/s, air-water (Kemoun et al., 2001); D6U60P1Water: 1 bar,60 cm/s, and air-water (Ong, 2003)] with similar overall gas holdup (~
0.41).
148
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6-2 a) Gas holdup and b) Axial liquid velocity radial profile in 6 diameterstainless steel column using an air-water system [D6P4U45: 6 inch
diameter, 4 bar, and 45 cm/s (Ong, 2003), D6P10U30: 6 inch
diameter, 10 bar and 30 cm/s] (Overall gas holdup ~ 0.41).
152
6-3 Variation of AARD in liquid axial velocities between similarity
conditions [D6P4U45Water (Ong, 2003) and D6P10U30Water] along
the column radius in 6 diameter stainless steel column using an air-water system.
153
6-4 TKE profile in 6 diameter stainless steel column using an air-watesystem [D6P4U45: 6 inch diameter column, 4 bar and 45 cm/s (Ong
2003), D6P10U30: 6 inch diameter column, 10 bar and 30 cm/s
(Overall gas holdup ~ 0.41).
153
6-5 a) Gas holdup and b) Axial liquid velocity radial profile in 6 diameterstainless steel column using an air-water system (D6P1U45Water: 6
inch diameter column, 1 bar and 45 cm/s, D6P4U30Water: 6 inch
diameter column, 4 bar and 30 cm/s) [Overall gas holdup ~ 0.35].
154
6-6 Variation of AARD in liquid axial velocities between similarity
conditions (D6P1U45water and D6P4U30water) along the columnradius in 6 diameter stainless steel column using an air-water system.
155
6-7 TKE radial profile in 6 diameter stainless steel column using an air-water system (D6P1U45Water: 6 inch diameter column, 1 bar and 45
cm/s, D6P4U30Water: 6 inch diameter column, 4 bar and 30 cm/s)[Overall gas holdup ~ 0.35].
155
6-8 a) Gas holdup and b) Axial liquid velocity radial profile in 6 diameterstainless steel column [D6P1U30 C9-C11: 6 inch diameter column, 1
bar, 30 cm/s (Han, 2006), and air- C9-C11 fluid system,
D6P4U30water: 6 inch diameter column, 4 bar, 30 cm/s, and an air-
water system] [Overall gas holdup ~ 0.35].
156
6-9 Variation of AARD in liquid axial velocities between similarity
conditions [D6P1U30C9-C11 (Han, 2006) and D6P4U30water] along
the column radius in 6 diameter stainless steel column.
157
6-10 TKE radial profile in 6 diameter stainless steel column (D6P1U30C9-C11: 6 inch diameter column, 1 bar, 30 cm/s, and air- C9-C11 fluid
system, D6P4U30water: 6 inch diameter column, 4 bar, 30 cm/s, and
an air-water system) [Overall gas holdup ~ 0.35].
157
6-11 a) Gas holdup and b) Axial liquid velocity radial profile in 6 diameter 159
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stainless steel column (D6P4U30water: 6 inch diameter column, 4 bar
and 30 cm/s, air-water; D6P4U16C9-C11: 6 inch diameter column, 4bar and 16 cm/s, air- C9-C11) [Overall gas holdup ~ 0.35].
6-12 Variation of AARD in liquid axial velocities between similarity
conditions (D6P4U30water and D6P4U16C9-C11) along the columnradius in 6 diameter stainless steel column.
159
6-13 TKE radial profile in 6 diameter stainless steel column(D6P4U30water: 6 inch diameter column, 4 bar and 30 cm/s, an air-
water; D6P4U16C9-C11: 6 inch diameter column, 4 bar and 16 cm/s,
air- C9-C11) [Overall gas holdup ~ 0.35].
160
6-14 a) Gas holdup and b) Axial liquid velocity radial profile in 6 diameter
stainless steel column (D6P4U30water: 6 inch diameter column, 4 bar
and 30 cm/s, an air-water; D6P10U8C9-C11: 6 inch diameter column,
10 bar and 8 cm/s, air- C9-C11) [Overall gas holdup ~ 0.35].
161
6-15 Variation of AARD in liquid axial velocities between similarityconditions (D6P4U30water and D6P10U8C9-C11) along the column
radius in 6 diameter stainless steel column.
161
6-16 TKE radial profile in 6 diameter stainless steel column
(D6P4U30water: 6 inch diameter column, 4 bar and 30 cm/s, an air-
water; D6P10U8C9-C11: 6 inch diameter column, 10 bar and 8 cm/s,air- C9-C11) [Overall gas holdup ~ 0.35].
162
6-17 Gas holdup radial profile in 6 diameter stainless steel column
(D6U2P1water: 1 bar and 2 cm/s, an air-water; D6U3P1TherminolLT:
1 bar and 3 cm/s, air- Therminol LT) [Overall gas holdup ~ 0.1].
165
6-18 Gas holdup radial profile in 6 diameter stainless steel column
(D6U5P4TherminolLT: 4 bar and 5 cm/s, air-Therminol LT;
D6U3.5P10Therminol: 10 bar and 3.5 cm/s, air- Therminol LT)[Overall gas holdup ~ 0.22].
165
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Nomenclature
BBO Bodenstein number, dimensionless
c Wall holdup parameter (equation 3-2), dimensionless
c Wall holdup parameter (equation 3-4), dimensionless
C0 Distribution parameter in drift flux model, dimensionless
C1 Weighted average drift velocity, m.s-1
CD Drag coefficient, dimensionless
CV Volumetric solids loading (equation 2-3), dimensionless
Cxx Autocorrelation function, dimensionless
D Column diameter, m
dB Bubble diameter, cm
dB Dimensionless bubble diameter, dimensionless
DG Gas dispersion coefficient, m2.s
-1
DL Liquid dispersion coefficient, m2.s-1
DP Coefficient of departure from Poisson distribution, dimensionless
Drr Radial eddy diffusivity, m2.s
-1
DR Ratio of gas and liquid phase densities, dimensionless
Dzz Axial eddy diffusivity, m2.s
-1
e Permittivity, F.m-1
Eo Etovos number, dimensionless
f Frequency, Hz
F(x) Fourier transform of x
Frg Gas Froude number, dimensionless
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g Gravity constant, m.s-2
Hd Dynamic height, m
HS Static height, m
I Number of input nodes
j drift flux, m.s-1
J Number of hidden layers
k0 Pseudo-first order rate constant, s-1
kLa Volumetric mass transfer coefficient, s-1
K Turbulent kinetic energy, cm2.s
-2
Number of output nodes
L Column length, m
Mo Morton number, dimensionless
n Slope of gas holdup curve (equation 2-1), dimensionlessSteepness parameter of gas holdup radial profile (equation 3-2), dimensionless
n Steepness parameter of solids holdup radial profile (equation 3-4), dimensionless
N Length of time series, dimensionless
r Radial location in the column, m
rk Relative permittivity, dimensionless
R Cross-correlation coefficient
Relative volumetric attenuation coefficient
Re Reynolds number, dimensionless
Sk Normalized output variable
T length of time series, min
ui Fluctuation velocity in ith
direction (i = r, , z)
ub0 Terminal velocity of an isolated bubble, m.s-1
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UB Terminal bubble rise velocity, m.s-1
UG Superficial gas velocity, m.s-1
UGtrans Superficial gas velocity at flow regime transition, m.s
-1
Ui Normalized input variable
UL Superficial liquid velocity, m.s-1
Ulb Large bubble rise velocity, m.s-1
umax Rise velocity of maximum stable bubble size, m.s-1
ur Solids radial velocity, m.s-1
recu Liquid recirculation velocity, m.s
-1
Usb Small bubble rise velocity, m.s-1
uslip Slip velocity, m.s-1
uz Solids/liquid axial velocity, m.s-1
u Solids azimuthal velocity, m.s-1
Vb0 Bubble rise velocity at vanishingly small velocity, m.s-1
wij,wjk ANN fitting parameters
Greek Letters
G Cross-sectionally averaged gas holdup, dimensionless
transG Overall gas hold up at transition point, dimensionless
G Overall gas hold up, dimensionless
s Cross-sectionally averaged solids holdup, dimensionless
s Overall solids hold up, dimensionless
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SL Solids loading, dimensionless
Constant (equation 2-17), dimensionless
eff Effective turbulent eddy viscosity, cm2.s-1
BIT Turbulent eddy viscosity due to bubble-induced turbulence, cm2.s
-1
SIT Turbulent eddy viscosity due to shear-induced turbulence, cm2.s
-1
m Molecular viscosity, cm2.s
-1
S Solids loading, (% vol/ %vol), dimensionless
SC Critical solids loading, (% vol/ %vol), dimensionless
Mean of a time-series, dimension of time-series
Phase angle of cross-spectral density function, rad
Standard deviation of a time series, dimension of time-series
Surface tension, dyne.cm-1
Time lag, sec
0 Drag interaction parameter, dimensionless
d Particle to liquid density ratio, dimensionless
u Drag interaction parameter, dimensionless
g Gas phase density, kg m-3
L Liquid phase density, kg m-3
S Solids phase density, kg m-3
SL Slurry phase density, kg m-3
L Liquid surface tension, N m-1
L Liquid viscosity, kg m-1
s-1
xx Power spectral density function
Correction factor, dimensionless
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Time lag, secAbbrevations
AARD Average Absolute Relative Difference
AARE Average Absolute Relative Error
ANN Artificial Neural Network
ARD Absolute Relative Difference
CARPT Computer Automated Radioactive Particle Tracking
CFD Computational Fluid Dynamics
CT Computed Tomography
DGD Dynamic Gas Disengagement
ECT Electrical Capacitance Tomography
FT Fischer-Tropsch
GTL Gas-to-Liquids
LDV Laser Doppler Velocimetry
PBM Population Balance Model
PDF Probability Density Function
PIV Particle Image Velocimetry
PSDF Power Spectral Density Function
SDM Sedimentation Dispersion Model
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Acknowledgements
First and foremost, thanks are due to the One God for His kindness and blessings, for
they sailed me through the ups and downs, and ecstasies and agonies during this time. It
is divinity we tend to believe in during such times, however, per JFKs famous quote
...here on earth, God's work must truly be our own, for better or worse we tend to rely
on people around us. As I am writing this acknowledgement, I see a fine ray of hope of
getting some name to the work and efforts of these peak years of my youth and also feel a
sense of gratitude to all those who have influenced it in some or other way during these
years.
I express a deep sense of gratitude to my advisor, Prof. M. H. Al-Dahhan, for giving me
an opportunity to work on this project. I wish to thank him for his encouragement and
support throughout my doctoral work which helped me overcome many obstacles. The
load of enthusiasm and intensity he brings to the work is simply amazing. The times
spent helping him on different reports, presentations, and short courses on bubble
columns were unforgettable.
I would like to thank Prof. M. P. Dudukovic for his comments on some parts of my work
and for being on my committee. It was indeed an experience to see him working so
closely which was and will be useful in future. I am thankful to my committee members,
Prof. P. A. Ramachandran, Prof. John Kardos, Prof. R. A. Gardner, and Dr. Jiangping
Zhang (Chevron) for investing their time and providing valuable comments. I also want
to thank my thesis committee members Prof. Ramesh Agarwal and Dr. Ralph Goodwin
(ConocoPhillips, USA) for agreeing to be on my committee and investing their valuable
time on relatively short notice. Thanks to Prof. Ramachandran for teaching me as well as
discussing facets of multiphase reactor modeling and to Prof. Kardos for being supportive
during different stages.
I would like to acknowledge the financial support of the High Pressure Slurry Bubble
Column Reactor Consortium (HPSBRC) [ConocoPhillips, USA; EniTech, Italy; Sasol,
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South Africa; Statoil, Norway] and the U.S. Department of Energy-University Coal
Research (DOE-UCR) grant (DE-FG26-99FT40594) that made this work possible. The
interactions with scientists and engineers from these industries during bi-annual review
meetings were a rewarding experience. The discussions with Drs. Alex Vogel and
Bremann Berthold of Sasol and Christina Marretto of EniTech provided me much needed
industrial perspective on parts of my research. During these years, I worked on various
bubble column related projects of Syntroleum Corporation and Snamprogetti that
certainly helped in looking at things from different angles. For the sake of my fancy of
undergraduate days, I had gone through Fischer-Tropsch (FT) synthesis and in general
Gas-to-Liquid (GTL) literature, most of it made sense after those long discussions with
Dr. Steve LeViness from Schlumberger. The discussions with him were invaluable and
further enhanced my interest in the field of energy. Thanks to Dr. Kym Arcuri from
Syntroleum for those valuable suggestions and advice, they were timely and will
certainly be useful.
I wish to acknowledge Professor K. Krishnaiah of the Indian Institute of Technology
(IIT), Madras for encouraging me to pursue doctoral studies. His reaction engineering
classes and surprise tests were certainly an enjoyable and memorable experience during
IIT-days. I am also thankful to my masters research advisors Drs. Abhijit Deshpande and
Susy Varughese of IIT, Madras.
Apart from CRELs abundant and high quality literature on bubble column reactors, I
immensely benefited from the works of Prof. J. B. Joshi of MUICT, Prof. R. Krishna of
University of Amsterdam, and Prof. L. S. Fan of OSU. Prof. Krishnas creative
descriptions of complex phenomena have been always a pleasure to read.
I am thankful to Mr. Pat Harkins, Mr. Jim Linders, and Mr. John Krietler for helping me
in various technical issues and fabrication of equipments. The experience of Mr. Steve
Picker was useful, particularly during crunch times. Mr. Edward Lau and Mrs. Susan
Tucker (MIT Nuclear Reactor) were extremely helpful during irradiation of tracer
radioactive particles.
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Numerous people at CREL were of immense help during these years. I thank Dr. Novica
Rados, with whom I started my research day-1 at CREL. He introduced me to CARPT,
CT, and experimental issues related to radioactive materials and bubble columns. I am
thankful to Dr. Muhammad Rafique for discussions on general research in multiphase
flows and also on different topics in my initial days. I am also thankful to Drs. Peter
Spicka and Stoyan Nedeltchev, who helped me understand various aspects of bubble
columns in the first year. The several useful discussions with Stoyan on regime transition
and chaos theory along with my own literature survey on regime transition convinced me
to work on flow regime transition in my thesis (although not using pressure fluctuations).
The long conversations with Dr. W. Warsito (OSU) on tomography were enlightening
and extremely useful. I wish to acknowledge Mr. Klass Koop for those daily insightful
discussions on hydrodynamics and mass transfer in bubble columns while we were
sharing an office. I am thankful to Mr. Lu Han and Mr. Chengtian Wu for helping me
during CARPT and other experimental work. Working together on the consortium project
with Novica, Lu, and Chengtian was an experience to remember. I am also thankful Dr.
Liu, a visiting scholar from China, and Mr. Saurabh Agarwala for being a timely help on
countless occasions when I was working late nights on CARPT/CT with Therminol LT. I
wish to acknowledge the help I received from Mr. Rajneesh Varma with a new CT setup
and experiments during joint work with OSU. I am thankful to Dr. Satish Bhusarapu for
his timely help at numerous occasions during my experimental work. The help I received
from Mr. Z. Kuzeljevic and Mr. S. Nayak during CT and CARPT experiments is highly
appreciated.
I wish to acknowledge the help of the secretaries of the Department of Chemical
Engineering in numerous administrative issues. I wish to thank Dr. Y. Yamashita for his
prompt help in computer and network related issues. The discussions on chaos theory,
symbolic dynamics, and S-statistics with Dr. Miryan Cassanello from University of
Buenous Aires were helpful in improving my knowledge regarding time-series analysis.
Thanks to Mr. Jim Ballard from the Engineering Technical Writing Center for going
through the manuscripts and helping to improve their language. Discussions with him on
nuances of technical English to various topics were amazing. I must also thank the
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personnel of InterLibraryLoan (ILL) services for providing the needed references on
time. Thanks to all those unknown faces behind Google and Wikipedia, for without them
my research life would not have been complete. However, I must mention that these were
not used as the scholarly references during this work.
During these years, I have made numerous friends who were of immense help time and
time and also made my stay enjoyable. Thanks to Dr. R. Ramaswamy for all those
agreements and disagreements over wide ranging issues during Sub-way lunches. I
assume they will continue. I wish to acknowledge all my roommates over these years
namely, Dennis Thomas, Keshav Ruthiya, Wisam Khudayar, and Ahmed Youssef. The
discussions with Keshav, ranging from the economy of chemical industries to economy
of India, to fancy business plans certainly diversified my interests. Thanks, Ahmed for
being a co-operative roommate during my last few months. Time spent with Ahmed and
Keshav was indeed a learning experience for me. I am thankful to many other people who
made a difference in one way or other: Shaibal, Pubs, Kartik, Subu, Karim, Mehul,,
Salim, Huping, Rajneesh, Radmila, Kaps, Saurabh, RC, DG, Ert, Nicola, Prashant.
Thanks to Abdul Rehman, Rehan, and Jaani for Eid dinners and to Chachi and Dr. Zakir
Sabry for making the environment during fasting far lighter and fun. I am thankful to
Jaani and Vikram for those weekend movie and biryani times in last years. Thanks to Mr.
Farhan Majid for discussing those lofty and fancy ideas related to economics.
I express a deep sense of gratitude to my parents and my younger sister for unconditional
support, patience, and belief in me. My father is my strength, and I forever appreciate the
courage of my mother in allowing her only son to go to the other side of the globe for
further education. In school days, out of guilt, I would pretend studying seeing my
younger sister studying so hard. I guess those times helped me when I actually started
studying. Words are just not enough to thank them. I owe everything that I have achieved
to them. I am thankful to my grandfathers and grandmothers, who, out of their affection
for my parents, wanted me to have some education. I wish to thank my Mumaani and
Mamu and also my other relatives for being a moral support to my family during these
years.
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Robert Frost ended his poem Stopping by Woods on Snowy Evening as,
The woods are lovely, dark and deep,
But I have promises to keep,
And miles to go before I sleep,And miles to go before I sleep.
As I end my walk through this portion of the woods and hope to enter a new one, I thank,
from the bottom of my heart, all those who directly and indirectly helped me over the
years during this journey.
Ashfaq Shaikh
Washington University, St. Louis
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1
Chapter 1.
Introduction
Bubble columns are two-phase gas-liquid systems in which a gas is dispersed through a
sparger and bubbles through a liquid in a vertical cylindrical column (Figure 1-1), with or
without internals. When suspended fine solids are present in liquid, they form a slurry
phase. Accordingly, they can be called either two-phase or three-phase (slurry) bubble
column. The liquid/slurry phase flow can be either co-current, counter-current, or in
batch mode with respect to the gas flow. The size of the solid particles ranges from 5 to
150 m, with solids loading up to 50 % volume (Krishna et al., 1997). The gas phase
contains one or more reactants, while the liquid phase usually contains product and/orreactants (or is sometimes inert). The solid particles are typically catalyst. In these
reactors, momentum is transferred from the faster, upward moving gas phase to the
slower liquid/slurry phase. Generally, the operating liquid superficial velocity (in the
range of 0 to 2 cm/s) is an order of magnitude smaller than the superficial gas velocity (1
to 50 cm/s). Hence, the hydrodynamics of such reactors are controlled mainly by the gas
flow.
Bubble columns offer numerous advantages such as good heat and mass transfer
characteristics, no moving parts and thus reduced wear and tear, higher catalyst
durability, ease of operation, and low operating and maintenance cost. One of the main
disadvantages of bubble column reactors is significant back-mixing, which can reduce
product conversion. The excessive back-mixing can be overcome by modifying the
design of bubble column reactors. Such modifications include the addition of internals,
baffles (Deckwer, 1991), or sieve plates (Maretto and Krishna, 2001). Bubble column
reactors have been used in chemical, petrochemical, biochemical, and pharmaceutical
industries for various processes (Carra and Morbidelli, 1987; Deckwer, 1992; Fan, 1989).
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2
Solids
Sparger
.. . .
.
.
.
. .
..
.
.
Liquid
Liquid
Gas Inlet
Gas Outlet
Figure 1-1: Schematic diagram of bubble/slurry bubble column
Examples of such chemical and petrochemical processes are the partial oxidation of
ethylene to acetaldehyde, wet-air oxidation (Deckwer, 1992), liquid phase methanol
synthesis (LPMeOH), Fischer-Tropsch (FT) synthesis (Wender, 1996), and
hydrogenation of maleic acid (MAC). In biochemical industries, bubble columns are used
for cultivation of bacteria, cultivation of mold fungi, production of single cell proteins,
animal cell culture (Lehmann et al., 1978), and treatment of sewage (Diesterweg, 1978).
In metallurgical industries, they can be used for leaching of ores. The most popular
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3
present day application of bubble columns is for energy conversion process where
stranded gas is converted to liquids. The popularity of such a conversion is a response
to thepostulatedfuture energy crisis.
Albert Einstein once wrote, I never think of the future, it comes soon enough. Einsteins
convenient approach to the future is a luxury that is denied to governments and energy
companies. These days of global economy and increased energy demands, coupled with
complex international relationships and interdependence, demand an understanding of the
probable trends and the drivers for future energy use. Figure 1-2 shows the projected gap
between oil production and consumption in USA. Currently, North America imports 65
% of their crude oil. With the economic growth of China, India, and other developing
countries, the demand for oil in these countries has risen significantly. Currently, Asia
imports approximately 65 % of their crude oil, while Western Europe imports 55 % of its
crude oil (Koelmel, 2005). These countries depend on the oil producing countries to meet
their energy demands. With current scenarios, it is clear that such dependence possibly
makes an existence of their own and subsequently ofother nations vulnerable.
Figure 1-2: Projected US energy and oil production and consumption [Source: National
Energy Policy, White House Report, 2001]
Figure 1-3 shows the vulnerability of the US to oil supply disruption. The percentage of
the vulnerability depends on the oil supply from secure and nonsecure sources.
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4
Presently, US vulnerability is at its peak, and is higher than during the first and second
energy shocks (Williams and Alhajji, 2003). Such scenarios are the motivation to come
up with a solution to meet the future energy challenges. The energy business is
characterized by large-scale, long-term investment and there is an urgent need to
understand potential future energy solutions. Because the latter half of Albert Einsteins
approach is not a luxury but a universal fact. It is said that the single biggest shift in
global demand for oil over the past decade has not been the rise of China but the rise of
SUVs (Zakaria, 2006). Hence, the solution to problems regarding energy demands a
multidimensional approach that involves politicians, policy makers, scientists,
technologists, and consumers of energy.
Figure 1-3: US vulnerability to oil disruption (Williams and AlHajji, 2003)
Shell geologist M. King Hubbert analyzed oil production utilizing the concept used by
population biologists to examine population growth. Hubbert (1956) predicted that US oil
production would peak in the early 1970s (Figure 1-4), which proved correct. He
predicted in 1969 that world oil production would peak around the year 2000, which is
supposedly also coming true (Deffeyes, 2004). In addition, the assessment of Simmons
(2005) of key oil fields in the world calls for heavy investment in alternative energy
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5
strategies. Such strategies should give priority to proven technologies rather than those
still in initial stages.
(a) (b)
Figure 1-4: a) M. King Hubbert at the 1956 API Spring Meeting where he proposed the
peak theory b) Popular Hubbert-peak curve.
The development of Gas-to-Liquid (GTL) conversion provides one piece of a more
complex solution. The development of GTL worldwide today suggests that it has the
potential to supply 10 % of the global diesel fuel market within the next 15 years. The use
of GTL fuel, in addition to utilizing flared and stranded gas, can aid energy conservation.
US economies are dominated by petrol fuels and thus, spark ignition engines, which are
less efficient than diesel engines. As shown in Figure 1-5, compared to the conventional
refinery fuels, GTL fuel can improve transportation fuel economy and carbon dioxide
efficiency while also augmenting urban air quality benefits. Hence, the combination of
efficient engines and clean fuels allows economies to reduce fuel consumption, reduce
greenhouse emissions, and improve air quality (Koelmel, 2005).
While GTL is a marginally commercial proposition today, it is a proven technology
compared to most other alternative energy technologies such as hydrogen and biomass.
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6
Figure 1-5: Relationship between fuel economy and urban air benefits (Koelmel, 2005)
Since Franz Fischer and Hans Tropsch developed the process to convert CO/H2 mixtureinto hydrocarbons and oxygenated compounds back in 1922, the obvious question is why
was its potential not un-locked before now? The answer lies in the Capital Expenditure
cost (CAPEX) of the GTL process, which has remained above $ 20,000/per specific
barrel of installed GTL capacity. The early pioneers of this process, specifically Sasol,
built plants at more like $ 120,000/bpd. As shown in Figure 1-6, the current CAPEX
remains close to $ 25,000/bpd (Brown, 2003). However below $ 20,000/bpd, one can
reach a watershed where GTL becomes attractive. At this cost, the resource holders have
enough margin to compete with refinery products.
Figure 1-6: CAPEX cost for GTL (Rahmim, 2003).
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8
2. Low temperature FT (LTFT): This process, with either an iron or cobalt basedcatalyst and temperature in a range of 200 240
0C, is used for the production of high
molecular weight linear waxes (> C20). The reactors are fixed beds and slurry bubble
columns.
The design of bubble columns has been considered for low temperature FT processes
since Kolbels pioneering work in 1950s. According to Krishna and Sie (2000), with the
present state of knowledge, it can be expected that a bubble column reactor may achieve
productivity a thousand times higher than that of the classical FT reactors (such as fixed
beds and multibed reactors) used in industry. However, there are considerable reactor
design and scale-up problems associated with such energy conversion processes
involving bubble columns. In order to achieve economically high space-time yields, a
high slurry concentration (typically 30 50 % vol) needs to be employed. To suspend
such a large amount of catalyst, a high energy input is needed, which can be provided by
high superficial gas velocities. The process operates under high-pressure conditions
(typically 10 80 bar). The high exothermic heat of reaction requires an efficient means
of heat removal that can operate in the churn-turbulent flow regime. Finally, the large gas
throughputs necessitate the use of large diameter reactors (typically 5 8 m), and to
obtain high conversion levels, large reactor heights, typically 20 30 m tall, are required.
Successful commercialization of bubble column reactors is crucially dependent on proper
understanding of their hydrodynamics and scale-up principles.
1-1Motivation
Although bubble column reactors are simple in construction, proper design and scale-up
of such reactors require a thorough understanding of the prevailing hydrodynamic and
mixing characteristics at conditions similar to the targeted process. The hydrodynamics of
such reactors affect the mixing intensity and gas-liquid interfacial area, which affect the
transport coefficients, and hence the conversion and selectivity of the reactor.
Hydrodynamic behavior in a bubble column reactor is complex, since the fluid phases
involved are characterized by very different masses, and one is more compressible than
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9
the other. Various design parameters (e.g., reactor geometry, internals, sparger design,
etc.) and operating variables (e.g., reactor pressure and temperature, gas and liquid/slurry
flow rates, catalyst size and loading, etc.) along with phase properties and kinetics, affect
the reactor hydrodynamic and transport rates in bubble/slurry bubble column reactors.
These, in turn, impact the reactor performance, operation, and its design and scale-up.
However, due to the complex interaction among the various phases, the flow field and
hydrodynamics of these reactors have not yet been well understood. In slurry bubble
column reactors, the ability to achieve complete catalyst suspension and the desired flow
pattern of the liquid/solid phase is critical to the targeted reactor performance.
Accordingly, in order to accomplish the desired flow pattern, an improved understanding
and quantification of the key hydrodynamic phenomena are required.
As mentioned earlier, industrial processes such as FT synthesis and liquid phase
methanol synthesis need to be carried out at high superficial gas velocity, high pressure,
high temperature, high catalyst loading, and in large diameter reactors. The literature
studies performed under such conditions are limited to global parameters such as overall
gas holdup and overall mass transfer coefficient (Wilkinson, 1991, Letzel, 1997).
Detailed studies of hydrodynamic parameters, such as phase holdup distribution and
velocity and turbulent parameter profiles, have been performed at high superficial gas
velocity and pressure only in air-water (Ong, 2003) and air-water-glass beads systems
(Rados, 2003) via advanced diagnostic techniques such as CT and CARPT. They found
that the effect of the sparger on hydrodynamics at high superficial gas velocities is
relatively insignificant. The pressure tends to increase the gas holdup and flatten gas
holdup radial profile. It was observed that an increase in pressure increases liquid
recirculation and reduces turbulent kinetic energy. In the literature, no work has been
reported regarding detailed hydrodynamic studies of slurry bubble columns at the
conditions of industrial interest. Such studies can be performed either by using a real
system or by mimicking the system of interest at laboratory operating conditions.
Therefore, the lack of hydrodynamic studies at the conditions of industrial interest
motivates the present work, which seeks to fill this gap by investigating the
hydrodynamics of a slurry bubble column using a liquid phase that at room temperature
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10
mimics the FT synthetic wax at low temperature FT reaction conditions. In addition, such
work will be useful in gaining insight into the effect of physical properties on the flow
dynamics by comparing the findings with those obtained using air-water-glass beads
(Rados, 2003). The work will further extend the benchmark data for evaluation and
validation of Computational Fluid Dynamics (CFD) models and closures predictions.
The demarcation of the flow regime in bubble columns is an important task because
different hydrodynamic characteristics exist in different flow regimes, and result in
different mixing and heat and mass transfer. It is very possible that the laboratory column
may operate in a heterogeneous regime, while industrial columns, due to their high
operating pressure and temperature and large diameters, may operate in a homogeneous
regime under similar conditions. The current state of empirical correlations, semi-
analytical models, and analytical models to predict transition in bubble columns is not yet
complete (Shaikh and Al-Dahhan, 2007a). The experimental techniques used to measure
flow regime transition are either visual or probe based. Apart from being intrusive,
probing techniques provide only point information or hydrodynamic information at the
wall. In large diameter industrial scale columns, such hydrodynamic information
transmitted from large distances can be questionable. Also, the implementation of a
probing technique for flow regime transition requires modification of existing reactors
and/or shut-down of the operation. Therefore, this work attempts to develop and
demonstrate non-invasive techniques for flow regime transition identification and its
objective flow regime identifiers that can be implemented on industrial scale bubble
columns without disturbing the operation to pinpoint the flow regime at the reactor
operating conditions. Noninvasive techniques such as -ray CT and Nuclear Gauge
Densitometry (NGD) will be considered for this purpose. NGD is commercially available
and used widely in industries for liquid/slurry level monitoring and control. Hence, the
successful development and demonstration of these techniques can be utilized for online
flow regime monitoring in commercial as well as laboratory applications.
Extrapolating the behavior of laboratory scale columns to industrial scale columns is
always a difficult and challenging task. Because the dispersion and interfacial heat and
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11
mass transfer fluxes, which often limit the chemical reaction rates (and in turn
conversion, selectivity, and yield), are closely related to hydrodynamics of the system
through the gas-liquid contact area and the turbulence properties of the flow, the scaleup
criteria need a reliable hydrodynamic similarity rule. The available scale up
methodologies for bubble columns depend on the similarity of overall gas holdup in the
two systems. It will be shown later that such an approach could be exclusively applicable
in bubbly flow, where gas holdup radial profiles are flat, but it cannot be extended to the
churn-turbulent regime, where parabolic profiles are present. Hence, the development of
a hydrodynamic similarity hypothesis in the regime of industrial interest motivates this
work to propose and evaluate a new methodology for scale up of bubble columns
operated in the churn-turbulent flow regime, with the aid of existing CT, CARPT, and
state-of-the-art modeling tool. An ideal choice of modeling tool for scaleup would be
CFD. However, due to the lack of universal closures, CFD has not yet been developed for
scaleup purposes. Hence, in this work, we have resorted to Artificial Neural Network
(ANN) correlations.
In summary, this work aims at advancing the state of knowledge of key hydrodynamic
parameters of bubble and slurry bubble column reactors at mimic industrial conditions. It
develops an experimental technique and flow regime identifiers for flow pattern
delineation that can be useful for online monitoring. Also, it proposes and demonstrates a
new scaleup methodology with the aid of state-of-the-art experimental and modeling
tools.
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1-2Objectives
The primary objective of the work is to improve the fundamental understanding of the
hydrodynamics of bubble/slurry bubble column reactors at industrially relevant
conditions. The specific goals of the work are as follows:
1-2.1 Hydrodynamic Parameters
Study the hydrodynamic characteristics of a slurry bubble column reactor using aliquid, which, at room temperature, mimics FT wax at FT reaction conditions.
Investigate the effects of liquid phase physical properties and solids loading on the
phase distribution via a single source -ray CT.
Investigate the effects of liquid phase physical properties and solids loading on solidsaxial velocity and turbulent parameters radial profile via CARPT.
1-2.2 Flow Regime Transition
This part of work includes the evaluation of single source -ray CT and NGD for
identification of regime transition. It comprises the following:
Evaluate CT for flow regime delineation and propose its flow regime identifiers.
Develop NGD for flow regime identification by analyzing obtained photon countshistory via various signal processing methods such as statistical analysis,
autocorrelation function analysis, and spectral analysis. The emphasis will be to study
the deviation of system behavior from a Poisson distribution and to develop flow
regime identifiers. This exercise will be useful for generalization of the proposed
flow regime identifiers. A successful development and demonstration should lead to
the implementation of Nuclear Gauge Densitometry (NGD) as a tool for online flow
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regime identification in industrial scale bubble/slurry bubble column reactors in
particular and multiphase flow systems in general.
1-2.3 Scale-up and hydrodynamic similarity
Develop a scale-up methodology for bubble columns by proposing a hypothesis thatto be hydrodynamically similar, the two reactors should have the same overall gas
holdup and its radial profile or cross-sectional distribution. The development of the
scaleup methodology consists of two steps:
I. Experimental evaluation of the proposed hypothesis, using CT and CARPT.
II. Development of state-of-the-art correlations based on ANN for prediction of
the overall gas holdup, the radial profiles of the gas holdup and liquid axial
velocity, and the center-line liquid velocity using available database and
including the findings of this work. Development of such correlations will
facilitate implementation of the developed scaleup methodology by a priori
prediction of the needed hydrodynamic parameters.
1-3Thesis Organization
A general review of mixing of liquid/solids phase, flow regime transition studies, and
available scaleup methodologies is provided in Chapter 2. The experimental studies
regarding flow behavior of slurry bubble column reactors are divided into two chapters
(Chapters 3 and 4). Chapter 3 provides the discussion on choice of fluid, experimental
setup, techniques used, and results related to the effect of operating parameters on phase
distribution. Chapter 4 discusses the effect of operating parameters on the solids axial
velocity and turbulent parameters at operating conditions similar to the studies in Chapter
3. The development of flow regime monitoring techniques and its flow regime identifiers
will be discussed in Chapter 5, while Chapter 6 presents the development of the new
scaleup methodology for hydrodynamic similarity and its experimental evaluation using
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CT and CARPT. ANN correlations of the needed hydrodynamic parameters that can be
useful in implementing the developed scaleup methodology are presented in Appendix-F.
Chapter 7 provides the conclusions and recommendations, and outlines possible future
efforts.
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Chapter 2.
Literature Review
In this chapter, a literature review pertinent to this thesis is presented. It is divided into
three parts as per the structure of thesis mentioned in Chapter 1. In the first part, mixing
of liquid/slurry phase is briefly reviewed. The second part reviews flow regime transition
studies in bubble column. The detailed review on this subject has been submitted for
publication [Shaikh and Al-Dahhan (2007a). A Review on Flow Regime Transition in
Bubble Columns. Accepted in International Journal of Chemical Reactor Engineering].
The third part deals with scaleup studies in bubble column reactors. The detailed reviewon this part [Shaikh and Al-Dahhan. (2007b) Scaleup of Bubble Column Reactors: A
Review of Current State of the Art] is being prepared and will be submitted for
publication.
2.1 Mixing and velocity profiles of liquid/slurry phase
Mixing and velocity profiles in two- and three-phase bubble columns have been reviewed
in detail by Ong (2003) and Rados (2003). In addition, Joshi et al. (1998) and Wild et al.
(2004) discussed mixing and velocity profiles in bubble columns in great detail, and
hence, these will not be repeated here.
Several studies have examined the hydrodynamics of bubble column reactors (Franz,
1984; Devanathan 1991; Yao, 1991; Degaleesan, 1997). These studies have been
performed at atmospheric pressure and/or at superficial gas velocities up to 15 cm/s.
Though high pressure operations are preferred operating conditions, very little is known
about the flow structure of bubble and slurry bubble columns at high pressure.Information available at high pressure is limited mainly to global parameters such as
overall gas holdup, and overall mass transfer coefficient. There have been few efforts to
study mixing in bubble columns at high pressure.
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high superficial gas velocity and high pressure, his studies are limited only to water as the
liquid phase. Hence, it is necessary to study the effect of physical properties on the
detailed flow behavior in such systems as the industrial systems consists of liquid phases
that has properties vastly different than water. It is important to know whether using the
liquid other than water will affect the trend and/or the magnitude of flow behavior.
In addition, Rados (2003) studies were conducted at relatively low solids loading (9.1 %
vol.) and have not investigated the effect of solids loading on hydrodynamic
characteristics of slurry bubble columns. The effect of solids loading is of particular
interest because the flow behavior of solids that are used as catalyst in industrial
processes will have significant effect on the performance of slurry bubble column
reactors. Such investigations will be extremely useful in determining the optimum
amount of catalyst for maximum reactor performance. Hence the brief review shows that,
there is a need to study the effect of physical properties and solids loading on
hydrodynamic characteristics of bubble/slurry bubble column reactors.
Also, as shown by Pohorecki et al. (2001) hydrodynamics at conditions of industrial
interest may show different behavior than at laboratory conditions. Therefore, one needs
to know in detail the fluid dynamics and mixing characteristics at the conditions of
industrial interest. This can be achieved either by performing experiments at the
industrial conditions using the real system or by mimicking the industrial system at
laboratory operating conditions. With the limitations encountered in laboratory studies,
the later option is more attractive. Such an option needs to be utilized to study the
hydrodynamic behavior of bubble column reactors.
2.2 Flow Regime Transition
Due to varied flow behavior, the demarcation of hydrodynamic flow regimes is an
important task in the design and scaleup of bubble column reactors. This section reviews
the studies performed for flow regime identification in bubble columns. The detailed
review article dealing with flow regime transition studies in bubble column has been
accepted for publication [Shaikh and Al-Dahhan (2007a). A Review on Flow Regime
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Transition in Bubble Columns. accepted International Journal of Chemical Reactor
Engineering]. Hence, it is briefly reviewed in the following sections.
2.2.1 Flow Regime Types and Characteristics
In bubble columns, four types of flow patterns have been observed, viz., homogeneous
(bubbly), heterogeneous (churn-turbulent), slug, and annular flow. Researchers have
reported the occurrence of a slug flow regime only in small diameter columns. In these
different flow regimes, the interaction of the dispersed gas phase with the continuous
liquid phase varies considerably. Figure 2-1 shows the various flow regimes in bubble
columns. However, bubbly and churn-turbulent flow regimes are most frequently
encountered. Depending upon the operating conditions, these two regimes can be
separated by a transition regime.
The homogeneous flow regime generally occurs at low to moderate superficial gas
velocities. It is characterized by uniformly sized small bubbles traveling vertically with
minor transverse and axial oscillations. There is practically no coalescence and break-up,
hence there is a narrow bubble size distribution. The gas holdup distribution is radially
uniform; therefore bulk liquid circulation is insignificant. The size of the bubbles depends
mainly on the nature of the gas distribution and the physical properties of the liquid.
Heterogeneous flow occurs at high gas superficial velocities. Due to intense coalescence
and break-up, small as well large bubbles appear in this regime, leading to wide bubble
size distribution. The large bubbles churn through the liquid, and thus, it is called as
churn-turbulent flow. The non-uniform gas holdup distribution across the radial direction
causes bulk liquid circulation in this flow regime.
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(a)
(b)
Figure 2-2: Flow regime map for air-water system at ambient pressure a) Shah et al.,
1982 and b) Zhang et al., 1997.
2.2.2 Methods for Flow Regime Identification
The experimental methods used for regime transition identification can be broadly
classified in the following groups:
Visual observation Evolution of global hydrodynamic parameter Temporal signatures of quantity related to hydrodynamics Advanced measurement techniques
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Visual Observation
Visual observation is the simplest method to study the flow pattern in bubble columns.
The slow, vertically rising bubbles can be observed in the homogeneous regime.
However, in the heterogeneous regime there is an intense interaction of bubbles, leading
to gross circulation (Figure 2-3). It is difficult to pinpoint the exact transition velocity by
visual observation. Moreover, this method can be useful only when the column is
transparent.
Figure 2-3: Photographs of bubbly and churn-turbulent flow in 2-D column
Evolution of global hydrodynamic parameter
Because the global hydrodynamic parameters are manifestations of the prevailing flow
patterns, they vary with the regimes. This fact has generally been utilized to identify flow
regime transition point. Typically, the global hydrodynamics have been quantified based
on overall gas holdup. The relationship between overall gas holdup and superficial gas
velocity can be expressed as
G . (2-1)n
GU
The overall gas holdup increases with an increase in superficial gas velocity. As can be
seen in Figure 2-4a (Shaikh and Al-Dahhan, 2005), the relationship between overall gas
holdup and superficial gas velocity varies over a range of velocities. The relationship is
almost linear (n ~ 0.8-1) at low gas velocities, but with an intense non-linear interaction
of bubbles at high gas velocities, the relationship between overall gas holdup and
superficial gas velocity deviates from linearity. The value of n is less than 1 (n ~ 0.4
0.6). Hence, the change in slope of the gas holdup curve can be identified as a regime
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transition point. Sometimes, gas holdup shows an S-shaped curve, depending upon
operating and design conditions (Figure2-4b) [Rados, 2003]. In such cases, the superficial
gas velocity at which maximum gas holdup has been attained is identified as the
transition velocity.
0 10 20 300
0.1
0.2
0.3
0.4
0.5
Superficial gas velocity (cm/s)
Cross-sectionalgasholdup
(a) (b)
Figure 2-4: Typical overall gas holdup curve a) Shaikh and Al-Dahhan, 2005; and b)
Rados, 2003.
However, when the change in slope is gradual or the gas holdup curve does not show a
maximum in gas holdup, it is difficult to identify the transition point. In such cases, the
drift flux method proposed by Wallis (1969) has been used extensively.
In this method, the drift flux,jGL (the volumetric flux of either phase relative to a surface
moving at the volumetric average velocity) is plotted against the superficial gas velocity,
UG. The drift flux velocity is given by:
(1 )GL G G L G
j U U = , (2-2)
where G is gas holdup and UL is superficial liquid velocity. The positive or negative sign
indicates counter-current or co-current flow of liquid relative to the gas phase,
respectively. Figure 2-5 shows a typical plot of the drift flux versus gas holdup. The
change in the slope of the curve represents the transition from homogeneous to
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heterogeneous flow. The change in slope of the drift flux plot is generally sharper than
the change in slope of gas holdup curve.
Figure 2-5: Typical drift flux plot using Wallis (1969) apporach (Deckwer et al., 1981)
Temporal signatures of quantity related to hydrodynamics
The global parameters represent macroscopic phenomena that are result of prevailing
microscopic phenomena. Several attempts have been made to capture the instantaneous
flow behavior through an energetic parameter.
The following temporal signatures have been utilized for flow regime transition:
- Pressure fluctuations [Nishikawa, 1969; Matsui, 1984; Drahos et al., 1991; Letzelet al., 1997; Vial et al., 2001, Park and Kim, 2003]
- Local holdup fluctuations using resistive or optical probes [Bakshi et al., 1995;Briens et al., 1997]
- Temperature fluctuations using a heat transfer probe [Thimmapuram et al., 1991]- Local bubble frequency measured using an optical transmittance probe [Kikuchi
et al., 1997]
- Conductivity probe [Zhang et al., 1997]- Sound fluctuations using an acoustic probe [Holler et al., 2003; Al-Masry, 2004]
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The prediction of transition using stability theory and CFD still needs substantial
improvement.
Energy conversion processes such as Fischer-Tropsch synthesis and methanol synthesis
operate in large diameter columns at high temperature, pressure, and solids loading.
Increased diameter, pressure, temperature (and thereby reduced viscosity) increases the
transition velocity, while solids loading reduces the transition velocity. Therefore,
experiments performed in lab scale columns and operating conditions (i.e., using air-
water system or conditions of no interest to industry) may be very much in the
heterogeneous regime, but quite possibly that in the homogeneous regime in industrial
columns. The state-of-the-art of empirical correlation, stability theory and CFD is not yet
sophisticated enough to a priori predict transition velocities in real systems. Hence, the
only option remains is to measure the transition velocity using a reliable experimental
technique. As discussed above, the available experimental techniques are based on either
visual observation or are probe based. Visual observation is often not possible due to the
opaque nature of the flows in bubble columns while probe based techniques are intrusive
and can provide unreliable hydrodynamic information in large diameter industrial scale
columns. By using probes flush to the wall, some researchers claim the probing
techniques to be non-invasive. However, in large diameter columns, one can not be sure
that fluctuations transmitted over great distances up to the wall can represent the
underlying hydrodynamics with fidelity. In addition, the probe-based techniques provide
point information that may not necessarily describe hydrodynamic information across
that cross-section. Also, Ellis et al. (2004) have shown that the probe dimensions can
influence the obtained hydrodynamic information and subsequently its interpretation. To
diagnose the flow in an industrial reactor which is in operation, probing techniques
require modification in the reactor and also shut-down of the operation to implement it,
which is not economical. Therefore, there is a need to develop a technique that is
noninvasive, can be easily implemented on an industrial scale without disturbing the
operation, and can provide hydrodynamic information that is reliable in lab scale and
industrial scale reactors.
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2.3 Scaleup of Bubble Column Reactors
The following is a brief review of the current state of the scale up of bubble column
reactors reported in literature. The detailed review regarding this topic [Shaikh and Al-
Dahhan. (2007b) Scaleup of Bubble Column Reactors: A Review of Current State of the
Art] will be submitted for publication and hence is briefly reviewed here.
2.3.1 Reported status of scaleup in literature
Wilkinson et al. (1992)
Wilkinson et al. (1992) performed experiments for scaleup purposes in two different
column diameters (15 and 23 cm) at operating pressures varying between 0.1 to 2 MPa
using three different liquids. Based on these experimental observations, they proposed
criteria for scaleup of high pressure bubble column reactors. It was argued that, the gas
holdup is virtually independent of the column dimensions and the sparger layout (for low
as well as high pressures) provided following criteria are fulfilled:
1) The column diameter has to be larger than 15 cm.2) The column height to diameter ratio has to be in excess of 5.3) The hole diameter of the sparger has to be larger than 1-2 mm.A correlation was
proposed based on their own and literature data that accounts the effect of gas density
and incorporates the flow regime transition.
A correlation was proposed for overall gas holdup based on their own and literature data
that accounts the effect of gas density and incorporates the flow regime transition.
Wilkinson et al. (1991) recommended using this correlation for scaleup purposes.
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Degaleesan (1997)
Degaleesan (1997) proposed a scaleup method that was based on the assumption that any
gas-liquid/slurry would exhibit the similar hydrodynamic behavior as air-water system if
both the systems have the same overall gas holdup. The procedure involves measuring (or
evaluating based on the suitable correlation) the overall gas holdup in scaled up unit at its
operating conditions and then calculating the equivalent superficial gas velocity, uGethat
results in the same overall gas holdup in an atmospheric air-water system as in the scaled
up unit. Hence, it was suggested that hydrodynamics and mixing at the equivalent
superficial gas velocity, uGe in an atmospheric air-water system would represent the
hydrodynamics and mixing in scaled up unit. The value ofuGe can then be used to predict
recirculation velocity and other turbulent parameters using correlations proposed based
on CARPT data in an air-water system. The liquid velocity profile has been estimated
using a 1-D model (Kumar, 1994), with a known mean recirculation velocity and gas
holdup radial profile.
Degaleesan (1997) developed a two-dimensional convection-diffusion model for liquid
mixing to interpret the tracer response in 18-inch diameter slurry bubble column reactor
for liquid phase methanol synthesis at La Porte, Texas. The convection-diffusion model
needs knowledge of liquid axial velocity profile, eddy diffusivities profile, and gas
holdup profile to predict the tracer responses. The available fluid dynamic measurements
in industrial unit were gas holdup radial profile measured using Nuclear Gauge
Densitometry (NGD). The liquid axial velocity profile and eddy diffusivities profile were
not available in industrial scale unit at reaction conditions. The experimental
measurements of these fluid dynamic parameters were available only in laboratory scale
bubble column (diameter = 14, 19, 44 cm) at ambient conditions in air-water system.
Degaleesan (1997) developed scaling rules to extrapolate available laboratory scale data
to industrial unit, to predict the needed fluid dynamic parameters,
It provides a systematic approach to characterize recirculation and mixing in an industrial
scale bubble column using an atmospheric air-water data. However, similarity based on
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only overall gas holdup may not be sufficient. This method needs a priori knowledge of
gas holdup and its distribution.
Inga and Morsi (1998)
Inga and Morsi (1998) have demonstrated their scaleup/scaledown methodology for FT
synthesis where it was shown that how the experimental results obtained in laboratory
scale stirred tank reactor could be extrapolated to design industrial scale slurry bubble
column. It is based on similarity of the relative importance of mass transfer resistance in
the overall reaction resistances, defined in terms of a dimensionless parameter, i which
represents the balance between kLa (mass transfer coefficient) and k0 (rate of
consumption, pseudo kinetic constant for first order). Accordingly, maintaining the same
in two reactors will result in the same reactant concentration and catalyst activity and
thereby the conversion and selectivity in two reactors.
Inga and Morsi (1998) demonstrated their proposed method for FT synthesis using a
laboratory scale 4-litre stirred tank reactor operating at 20 Hz and 5 % wt which was
simulated to a conceptual industrial scale slurry bubble column reactor. The conceptual
slurry bubble column reactor with 7 m diameter and 30 m height operating at 30 bars,523 K and 20 cm/s was modeled using Axial Dispersion Model (ADM). The simulations
were performed to maintain similar i as in stirred tank reactor. The authors found the
same productivity in both the reactors when the values ofi were the same.
The method proposed by these authors shows that, maintaining relative contribution of
tr