Shaikh, Ashfaq

7/28/2019 Shaikh, Ashfaq

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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


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


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


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


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


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


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].


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

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