NR88587.pdf - University of Regina

FOAMING IN CO2 ABSORPTION PROCESS USING AQUEOUS SOLUTIONS

OF ALKANOLAMINES

A Thesis

Submitted to the Faculty of Graduate Studies and Research

In Partial Fulfillment of the Requirements

for the Degree of

Doctor of Philosophy

in Environmental Systems Engineering

University of Regina

By

Bhurisa Thitakamol

Regina, Saskatchewan

July, 2010

Copyright 2010: B. Thitakamol

FOAMING IN COz ABSORPTION PROCESS USING AQUEOUS SOLUTIONS

OF ALKANOLAMINES

A Thesis

Submitted to the Faculty of Graduate Studies and Research

In Partial Fulfillment of the Requirements

for the Degree of

Doctor of Philosophy

in Environmental Systems Engineering

University of Regina

By

Bhurisa Thitakamol

Regina, Saskatchewan

July, 2010

Copyright 2010: B. Thitakamol

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Library and Archives Canada

Published Heritage Branch

Bibliotheque et Archives Canada

Direction du Patrimoine de I'edition

395 Wellington Street Ottawa ON K1A0N4 Canada

395, rue Wellington Ottawa ON K1A 0N4 Canada

Your file Votre reference

ISBN: 978-0-494-88587-1

Our file Notre reference

ISBN: 978-0-494-88587-1

NOTICE:

The author has granted a nonexclusive license allowing Library and Archives Canada to reproduce, publish, archive, preserve, conserve, communicate to the public by telecommunication or on the Internet, loan, distrbute and sell theses worldwide, for commercial or noncommercial purposes, in microform, paper, electronic and/or any other formats.

AVIS:

L'auteur a accorde une licence non exclusive permettant a la Bibliotheque et Archives Canada de reproduire, publier, archiver, sauvegarder, conserver, transmettre au public par telecommunication ou par I'lnternet, preter, distribuer et vendre des theses partout dans le monde, a des fins commerciales ou autres, sur support microforme, papier, electronique et/ou autres formats.

The author retains copyright ownership and moral rights in this thesis. Neither the thesis nor substantial extracts from it may be printed or otherwise reproduced without the author's permission.

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In compliance with the Canadian Privacy Act some supporting forms may have been removed from this thesis.

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Canada

UNIVERSITY OF REGINA

FACULTY OF GRADUATE STUDIES AND RESEARCH

SUPERVISORY AND EXAMINING COMMITTEE

Bhurisa Thitakamol, candidate for the degree of Doctor of Philosophy in Environmental Systems Engineering, has presented a thesis titled, Foaming in CO2 Absorption Process Using Aqueous Solutions of Alkanolamines, in an oral examination held on May 17, 2010. The following committee members have found the thesis acceptable in form and content, and that the candidate demonstrated satisfactory knowledge of the subject material.

External Examiner:

Supervisor:

Committee Member:

Committee Member:

Committee Member:

Committee Member:

Chair of Defense:

*Dr. Gary T. Rochell, University of Texas at Austin

Dr. Amornvadee Veawab, Environmental Systems Engineering

Dr. Yongan (Peter) Gu, Petroleum Systems Engineering

Dr. Amr Henni, Industrial Systems Engineering

Dr. Adisorn Aroonwilas, Industrial Systems Engineering

Dr. Andrew Wee, Department of Chemistry and Biochemistry

Dr. George W. Maslany, Dr. John Archer Library

*Attended via video conference

UNIVERSITY OF REGINA

FACULTY OF GRADUATE STUDIES AND RESEARCH

SUPERVISORY AND EXAMINING COMMITTEE

Bhurisa Thitakamol, candidate for the degree of Doctor of Philosophy in Environmental Systems Engineering, has presented a thesis titled, Foaming in C02 Absorption Process Using Aqueous Solutions of Alkanolamines, in an oral examination held on May 17, 2010. The following committee members have found the thesis acceptable in form and content, and that the candidate demonstrated satisfactory knowledge of the subject material.

External Examiner: *Dr. Gary T. Rochell, University of Texas at Austin

Supervisor: Dr. Amornvadee Veawab, Environmental Systems Engineering

Committee Member: Dr. Yongan (Peter) Gu, Petroleum Systems Engineering

Committee Member: Dr. Amr Henni, Industrial Systems Engineering

Committee Member: Dr. Adisorn Aroonwilas, Industrial Systems Engineering

Committee Member: Dr. Andrew Wee, Department of Chemistry and Biochemistry

Chair of Defense: Dr. George W. Maslany, Dr. John Archer Library

•Attended via video conference

Abstract

Coal-fired power plants produce electricity by coal combustion and emit carbon

dioxide (CO2), a major greenhouse gas contributing to global climate change, to the

atmosphere. One of many solutions to reduce such CO2 emissions is to integrate an

alkanolamine-based CO2 absorption process into the downstream end of the power plant

as a flue gas post-combustion treatment unit. However, foaming is one of the most severe

operational problems in this absorption process causing adverse impacts on process

integrity and process cost. Unfortunately, knowledge of foaming is very scarce since no

information of foaming is presently available for this relatively new application of a CO2

absorption process in coal-fired power plants.

In this study, the foaming tendency of this process was experimentally evaluated

using the pneumatic method modified from the ASTM standard and then reported in

terms of foaminess coefficient (E). The results show considerable effects of the tested

parameters on E. Following these experimental studies, a foam height correlation was

developed to predict pneumatic steady-state foam heights for the MEA-based CO2

absorption process and was built on the correlation of Pilon et al. (2001). The simulation

results show that the model fits well with our experimental foam data with R2 of 0.88 and

can be used to describe foaming behaviour with respect to changes in process conditions.

A foam model was developed for an alkanolamine-based CO2 absorption process

fitted with sheet-metal structured packing. The model was built upon the principles of

fluid flow pattern, column hydrodynamics, and foam formation mechanism and was

verified with the experimental foam data with an average absolute deviation (AAD) of

i

Abstract

Coal-fired power plants produce electricity by coal combustion and emit carbon

dioxide (CO2), a major greenhouse gas contributing to global climate change, to the

atmosphere. One of many solutions to reduce such CO2 emissions is to integrate an

alkanolamine-based CO2 absorption process into the downstream end of the power plant

as a flue gas post-combustion treatment unit. However, foaming is one of the most severe

operational problems in this absorption process causing adverse impacts on process

integrity and process cost. Unfortunately, knowledge of foaming is very scarce since no

information of foaming is presently available for this relatively new application of a CO2

absorption process in coal-fired power plants.

In this study, the foaming tendency of this process was experimentally evaluated

using the pneumatic method modified from the ASTM standard and then reported in

terms of foaminess coefficient (£). The results show considerable effects of the tested

parameters on E. Following these experimental studies, a foam height correlation was

developed to predict pneumatic steady-state foam heights for the MEA-based CO2

absorption process and was built on the correlation of Pilon et al. (2001). The simulation

results show that the model fits well with our experimental foam data with R2 of 0.88 and

can be used to describe foaming behaviour with respect to changes in process conditions.

A foam model was developed for an alkanolamine-based CO2 absorption process

fitted with sheet-metal structured packing. The model was built upon the principles of

fluid flow pattern, column hydrodynamics, and foam formation mechanism and was

verified with the experimental foam data with an average absolute deviation (AAD) of

i

16.3%. Simulation results show that the model has the capacity for determining possible

foam sites and process conditions where foaming is likely to occur and for evaluating

foaming impacts on process throughput. The presence of degradation products and

corrosion inhibitors induces more foam volumes in the absorber.

ii

16.3%. Simulation results show that the model has the capacity for determining possible

foam sites and process conditions where foaming is likely to occur and for evaluating

foaming impacts on process throughput. The presence of degradation products and

corrosion inhibitors induces more foam volumes in the absorber.

ii

Acknowledgements

I would like to express my grateful thanks to Assoc. Prof. Dr. Amornvadee

Veawab, my supervisor, who has always given me not only countless opportunities to

master my skills and knowledge and to broaden my horizons in the field of Carbon

Capture and Storage, but also her invaluable guidance and support since I joined the

University of Regina in 2004. Throughout the program, she has been an impeccable

supervisor and mentor, and all of the experience working with her for these past few

years will be gratefully remembered and appreciated. I also would like to express my

deep appreciation to Assoc. Prof. Dr. Adisorn Aroonwilas for his valuable advice.

My gratitude is gladly offered to Assoc. Prof. Dr. Amr Henni and Prof. Dr. Peter

Gu for their exceptional instruction in Advanced Thermodynamics and Surface

Thermodynamics, respectively. The knowledge that I gained from their courses helped

guide me into an in-depth understanding of my research in foaming.

I also wish to express my gratitude to Prof. Dr. Mingzhe Dong and again Prof. Dr.

Amr Henni who allowed me to access to their research equipment for completion of this

research. I also wish to thank Mr. David Wirth and Mr. Harald Berwald for their great

help and effort put into developing my experimental apparatus. In addition, I am grateful

to my advisory committee for their constructive questions and suggestions that helped

perfect this work. Finally, I would like to gratefully acknowledge the Natural Sciences

and Engineering Research Council of Canada (NSERC), the Faculty of Graduate Studies

and Research (FGSR), and the Faculty of Engineering and Applied Science for their

generous financial support.

iii

Acknowledgements

I would like to express my grateful thanks to Assoc. Prof. Dr. Amornvadee

Veawab, my supervisor, who has always given me not only countless opportunities to

master my skills and knowledge and to broaden my horizons in the field of Carbon

Capture and Storage, but also her invaluable guidance and support since I joined the

University of Regina in 2004. Throughout the program, she has been an impeccable

supervisor and mentor, and all of the experience working with her for these past few

years will be gratefully remembered and appreciated. I also would like to express my

deep appreciation to Assoc. Prof. Dr. Adisorn Aroonwilas for his valuable advice.

My gratitude is gladly offered to Assoc. Prof. Dr. Amr Henni and Prof. Dr. Peter

Gu for their exceptional instruction in Advanced Thermodynamics and Surface

Thermodynamics, respectively. The knowledge that I gained from their courses helped

guide me into an in-depth understanding of my research in foaming.

I also wish to express my gratitude to Prof. Dr. Mingzhe Dong and again Prof. Dr.

Amr Henni who allowed me to access to their research equipment for completion of this

research. I also wish to thank Mr. David Wirth and Mr. Harald Berwald for their great

help and effort put into developing my experimental apparatus. In addition, I am grateful

to my advisory committee for their constructive questions and suggestions that helped

perfect this work. Finally, I would like to gratefully acknowledge the Natural Sciences

and Engineering Research Council of Canada (NSERC), the Faculty of Graduate Studies

and Research (FGSR), and the Faculty of Engineering and Applied Science for their

generous financial support.

iii

Dedication

This work is dedicated to my grandparents, Mr. Somjit Thitakamol and Mrs.

Nuntana Chumpolvong, who are no longer with me, and my supportive family, especially

my parents, who are my greatest inspiration and encouragement; my grandparents, Mr.

Kriengsak Chumpolvong and Mrs. Seay Thitakamol, for their love and their contribution

to my upbringing; and my lovely sister for taking care of our parents in Thailand.

I would like to express my gratitude to all of my professors at the King Mongkut's

Institute of Technology Ladkrabang and the Petroleum and Petrochemical College,

Chulalongkorn University, as well as teachers who taught me throughout my life for their

support and understanding. Without their helpful guidance and wisdom, I would not have

made the achievements I have today.

Moreover, my thanks are also extended to all of my friends at the International

Test Center for CO2 Capture and the Student Association of Thais at the University of

Regina for their friendship and generosity, as well as all the administrative staff of the

Faculty of Engineering and Applied Science, University of Regina, for their assistance.

Finally, I would like to thank my beloved husband, Mr. Teerawat

Sanpasertpamich, from the bottom of my heart, who not only always looks after me and

shares all the moments of my happiness and sorrow, but also provided very useful

technical advice regarding the mathematical modeling employed in this work.

iv

Dedication

This work is dedicated to my grandparents, Mr. Somjit Thitakamol and Mrs.

Nuntana Chumpolvong, who are no longer with me, and my supportive family, especially

my parents, who are my greatest inspiration and encouragement; my grandparents, Mr.

Kriengsak Chumpolvong and Mrs. Seay Thitakamol, for their love and their contribution

to my upbringing; and my lovely sister for taking care of our parents in Thailand.

I would like to express my gratitude to all of my professors at the King Mongkut's

Institute of Technology Ladkrabang and the Petroleum and Petrochemical College,

Chulalongkom University, as well as teachers who taught me throughout my life for their

support and understanding. Without their helpful guidance and wisdom, I would not have

made the achievements I have today.

Moreover, my thanks are also extended to all of my friends at the International

Test Center for CO2 Capture and the Student Association of Thais at the University of

Regina for their friendship and generosity, as well as all the administrative staff of the

Faculty of Engineering and Applied Science, University of Regina, for their assistance.

Finally, I would like to thank my beloved husband, Mr. Teerawat

Sanpasertparnich, from the bottom of my heart, who not only always looks after me and

shares all the moments of my happiness and sorrow, but also provided very useful

technical advice regarding the mathematical modeling employed in this work.

iv

Table of Contents

Page

Abstract i

Acknowledgements iii

Dedication iv

Table of Contents v

List of Tables ix

List of Figures xii

Nomenclature xviii

1. INTRODUCTION 1

1.1 Process description of regenerable CO2 absorption 5

1.2 Process solution 8

1.2.1 Absorption solvent 8

1.2.2 Other chemicals 10

1.3 Foaming problems in CO2 absorption plants 14

1.3.1 Causes and effects 14

1.3.2 Existing foaming control methods 16

1.3.3 Industrial experience with foaming problem 18

1.4 Limitations of current knowledge 21

1.5 Research objective 28

1.6 Thesis overview 29

2. THEORY AND LITERATURE REVIEW 31

2.1 Basic principles of foam 31

2.1.1 Foam mechanism 34

v

Table of Contents

Page

Abstract i

Acknowledgements iii

Dedication iv

Table of Contents v

List of Tables ix

List of Figures xii

Nomenclature xviii

1. INTRODUCTION 1

1.1 Process description of regenerable CO2 absorption 5

1.2 Process solution 8

1.2.1 Absorption solvent 8

1.2.2 Other chemicals 10

1.3 Foaming problems in CO2 absorption plants 14

1.3.1 Causes and effects 14

1.3.2 Existing foaming control methods 16

1.3.3 Industrial experience with foaming problem 18

1.4 Limitations of current knowledge 21

1.5 Research objective 28

1.6 Thesis overview 29

2. THEORY AND LITERATURE REVIEW 31

2.1 Basic principles of foam 31

2.1.1 Foam mechanism 34

v

2.1.2 Foam stability 36

2.1.3 Marangoni effect 37

2.2 Buckingham Pi-theorem 40

2.3 Literature review on the correlation of the pneumatic foam height 41

2.3.1 Application of Buckingham Pi-theorem 41

2.3.2 Other approaches 46

3. EXPERIMENTS 51

3.1 Static foaming experiment 51

3.1.1 Experimental setup 51

3.1.2 Preparation of test solutions 54

3.1.3 Experimental procedures 56

3.1.4 Data analysis 58

3.1.5 Tested parameters and experimental conditions 58

3.2 Column foaming experiment 62



3.2.3 Experimental conditions 68

4. PARAMETRIC STUDY ON FOAMING BEHAVIOUR 70

4.1 Superficial gas velocity 70

4.2 Solution volume 72

4.3 Alkanolamine concentration 75

4.4 CO2 loading 79

4.5 Solution temperature 82

4.6 Degradation products of MEA 85

4.7 Corrosion inhibitor 87

4.8 Alkanolamine type 90

vi

2.1.2 Foam stability 36

2.1.3 Marangoni effect 3 7

2.2 Buckingham Pi-theorem 40

2.3 Literature review on the correlation of the pneumatic foam height 41

2.3.1 Application of Buckingham Pi-theorem 41

2.3.2 Other approaches 46

3. EXPERIMENTS 51

3.1 Static foaming experiment 51


3.1.2 Preparation of test solutions 54


3.1.4 Data analysis 5 8

3.1.5 Tested parameters and experimental conditions 5 8

3.2 Column foaming experiment 62



3.2.3 Experimental conditions 68

4. PARAMETRIC STUDY ON FOAMING BEHAVIOUR 70

4.1 Superficial gas velocity 70

4.2 Solution volume 72

4.3 Alkanolamine concentration 75

4.4 CO2 loading 79

4.5 Solution temperature 82

4.6 Degradation products of MEA 85

4.7 Corrosion inhibitor 87

4.8 Alkanolamine type 90

vi

5. CORRELATION OF A PNEUMATIC FOAM HEIGHT 95

5.1 Correlation framework 95

5.2 Subroutine calculations 100

5.2.1 Average bubble radius 100

5.2.2 Density 107

5.2.3 Viscosity 108

5.2.4 Surface tension 108

5.3 Foam height prediction results 112

5.3.1 Parametric effects 121

5.3.2 Sensitivity analysis 122

6. DEVELOPMENT OF A FOAM MODEL 129

6.1 Model development 129

6.1.1 Input of parameters 133

6.1.2 Slab foam model 135

6.1.3 Prediction of total foam volume per packing section 140

6.2 Results and discussions 141

6.2.1 Experimental foam data 141

6.2.2 Model verification 145

6.3 Model simulation 147

6.3.1 Foaming tendency within an absorber 147

6.3.2 Foaming impact on process throughput 151

7. CONCLUSIONS AND RECOMMENDATIONS 154

7.1 Conclusions 154

7.1.1 Parametric study 154

7.1.2 Pneumatic foam height correlation 155

7.1.3 Foam model 156

vii

5. CORRELATION OF A PNEUMATIC FOAM HEIGHT 95

5.1 Correlation framework 95

5.2 Subroutine calculations 100

5.2.1 Average bubble radius 100

5.2.2 Density 107

5.2.3 Viscosity 108

5.2.4 Surface tension 108

5.3 Foam height prediction results 112

5.3.1 Parametric effects 121

5.3.2 Sensitivity analysis 122

6. DEVELOPMENT OF A FOAM MODEL 129

6.1 Model development 129

6.1.1 Input of parameters 133

6.1.2 Slab foam model 135

6.1.3 Prediction of total foam volume per packing section 140

6.2 Results and discussions 141

6.2.1 Experimental foam data 141

6.2.2 Model verification 145

6.3 Model simulation 147

6.3.1 Foaming tendency within an absorber 147

6.3.2 Foaming impact on process throughput 151

7. CONCLUSIONS AND RECOMMENDATIONS 154

7.1 Conclusions 154

7.1.1 Parametric study 154

7.1.2 Pneumatic foam height correlation 155

7.1.3 Foam model 156

vii

7.2 Recommendations for future work 157

8. REFERENCES 159

Appendix A : Experimental data of parametric study 168

Appendix B : Input parameters and simulation outputs of a foam height 183

correlation

Appendix C : Experimental data of a column foaming experiment 189

viii

7.2 Recommendations for future work 157

8. REFERENCES 159

Appendix A : Experimental data of parametric study 168

Appendix B : Input parameters and simulation outputs of a foam height 183

correlation

Appendix C : Experimental data of a column foaming experiment 189

viii

List of Tables

Page

Table 1.1 List of examples of coal-fired power plants with an 4

alkanolamine-based CO2 absorption process as a CO2 capture

unit

Table 1.2 Typical concentrations of heat stable salt anions found in gas 13

treating units

Table 1.3 List of examples of CO2 capture plants (both commercial and 20

demonstration scale) experiencing foaming problems

Table 1.4 Literature review on foaming in gas absorption processes 24

using aqueous solutions of alkanolamines

Table 3.1 Source and purity of chemicals and gases 55

Table 3.2 Summary of tested parameters and operating conditions 61

Table 3.3 Geometric characteristics of Mellapak 500.Y 64

Table 3.4 Experimental conditions for the column foaming experiment 69

Table 4.1 Effect of degradation products on foaminess coefficient 86

(degradation product concentration = 10000 ppm, MEA

concentration = 5.0 kmol/m3, N2 velocity = 2.06 m3/m2-hr,

solution volume = 4.0x104 m3, CO2 loading = 0.40 mol/mol

and solution temperature = 60°C)

Table 4.2 Surface tension of 5.0 kmol/m3 MEA solutions containing no 89

CO2 loading at 25°C with/without 1000 ppm corrosion

inhibitor (measured by Kress Tensiometer K100 using the

Wihelmy plate's principle)

Table 4.3 Effect of alkanolamine type on foaminess coefficient (total 92

alkanolamine concentration = 4.0 kmol/m3, N2 velocity = 2.06

m3/m2-hr, solution volume = 400 cm3, CO2 loading = 0.40

mol/mol, solution temperature = 60°C and mixing mole ratio

of blended solution = 1:2, 1:1 and 2:1)

ix

List of Tables

Table 1.1 List of examples of coal-fired power plants with an

alkanolamine-based CO2 absorption process as a CO2 capture

unit

Typical concentrations of heat stable salt anions found in gas

treating units

List of examples of CO2 capture plants (both commercial and

demonstration scale) experiencing foaming problems

Literature review on foaming in gas absorption processes

using aqueous solutions of alkanolamines

Source and purity of chemicals and gases

Summary of tested parameters and operating conditions

Geometric characteristics of Mellapak 500.Y

Experimental conditions for the column foaming experiment

Effect of degradation products on foaminess coefficient

(degradation product concentration = 10000 ppm, ME A


solution volume = 4.0x10"4 m3, CO2 loading = 0.40 mol/mol

and solution temperature = 60°C)

Surface tension of 5.0 kmol/m3 ME A solutions containing no

CO2 loading at 25°C with/without 1000 ppm corrosion

inhibitor (measured by KrOss Tensiometer K100 using the

Wihelmy plate's principle)

Table 4.3 Effect of alkanolamine type on foaminess coefficient (total

alkanolamine concentration = 4.0 kmol/m3, N2 velocity = 2.06

m3/m2-hr, solution volume = 400 cm3, CO2 loading = 0.40

mol/mol, solution temperature = 60°C and mixing mole ratio

of blended solution = 1:2, 1:1 and 2:1)

Page

4

Table 1.2

Table 1.3

Table 1.4

Table 3.1

Table 3.2

Table 3.3

Table 3.4

Table 4.1

Table 4.2

13

20

24

55

61

64

69

86

89

92

ix

Table 5.1

Table 5.2

Table 5.3

Table 5.4

Table 6.1

Table A.1

Table A.2

Table A.3

Table A.4

Table A.5

Table A.6

Table A.7

Table A.8

Table A.9

Table A.10

Table A.11

Table A.12

Table A.13

Sensitivity analysis of coefficients used in the prediction of P*

Adjustable parameters for the MEA-0O2-water system

Ranges of process parameters

Ranges of physical properties

Process conditions for the evaluation of foaming impacts on

process performance

Experimental data for the effect of superficial gas velocity at

MEA concentration of 2.0 kmol/m3

Experimental data for the effect of superficial gas velocity at


Experimental data for the effect of solution volume

Experimental data for the effect of MEA concentration at the

absorber top condition

Experimental data for the effect of MEA concentration at the

absorber bottom condition

Experimental data for the effect of CO2 loading at the solution

temperature of 40°C





Experimental data for the effect of solution temperature at the

CO2 loading of 0.20 mol CO2/mol MEA

Experimental data for the effect of solution temperature at the

CO2 loading of 0.40 mol CO2/mol MEA

Experimental data for the effect of degradation products of

MEA

Experimental data for the effect of corrosion inhibitor

Experimental data for the effect of alkanolamine type (single

alkanolamine)

x

104

111

125

126

152

168

169

170

171

172

173

174

175

176

177

178

180

181

Table 5.1 Sensitivity analysis of coefficients used in the prediction of P* 104

Table 5.2 Adjustable parameters for the MEA-C02-water system 111

Table 5.3 Ranges of process parameters 125

Table 5.4 Ranges of physical properties 126

Table 6.1 Process conditions for the evaluation of foaming impacts on 152

process performance

Table A.l Experimental data for the effect of superficial gas velocity at 168


Table A.2 Experimental data for the effect of superficial gas velocity at 169


Table A.3 Experimental data for the effect of solution volume 170

Table A.4 Experimental data for the effect of MEA concentration at the 171

absorber top condition

Table A.5 Experimental data for the effect of MEA concentration at the 172

absorber bottom condition

Table A.6 Experimental data for the effect of CO2 loading at the solution 173






Table A.9 Experimental data for the effect of solution temperature at the 176

CO2 loading of 0.20 mol CCVmol MEA

Table A.10 Experimental data for the effect of solution temperature at the 177

CO2 loading of 0.40 mol CCVmol MEA

Table A.11 Experimental data for the effect of degradation products of 178

MEA

Table A.12 Experimental data for the effect of corrosion inhibitor 180

Table A.13 Experimental data for the effect of alkanolamine type (single 181

alkanolamine)

x

Table A.14

Table B.1

Table C.1

Experimental data for the effect of alkanolamine type (blended

alkanolamine)

Input parameters and simulation outputs of a foam height

correlation

Experimental percent foam volume per packing volume

plotted at different superficial gas velocities and superficial

liquid velocities

xi

182

184

189

Table A.14 Experimental data for the effect of alkanolamine type (blended 182

alkanolamine)

Table B.l Input parameters and simulation outputs of a foam height 184

correlation

Table C.l Experimental percent foam volume per packing volume 189

plotted at different superficial gas velocities and superficial

liquid velocities

xi

List of Figures

Page

Figure 1.1 Schematic diagram of a coal-fired power plant with post- 3

combustion treatment processes

Figure 1.2 Schematic diagram of a typical absorption-based CO2 capture unit

Figure 2.1 Characterization of foam morphology based on the gas fraction 33

criteria (redrawn from Schramm (1994) and Thiele et al. (2003))

Figure 2.2 Marangoni effect in the surfactant-stabilized film (Schramm, 39

1994)

Figure 3.1 Schematic diagram of the static foaming experimental setup 53

Figure 3.2 Average foam volume profile during blowing time (MEA solution 57

volume = 400 cm3, CO2 loading = 0.40 mol/mol, N2 velocity =

2.06 m3/m2-hr, MEA concentration = 5.0 kmol/m3 and solution

temperature = 40°C)

Figure 3.3 (a) Schematic diagram of the column foaming experimental 63

apparatus and (b) photograph of the absorber fitted with two

elements of Mellapak 500.Y

Figure 3.4 Example of (a) a solution level above the liquid outlet tube at the 67

bottom of the column and (b) a foam height measurement (liquid

velocity = 4.6 m3/m2-hr, air velocity = 120 mm/s and elapse time

at = 15 minutes)

Figure 4.1 Effect of superficial gas velocity on foaminess coefficients (MEA 71

concentration = 2.0 and 5.0 kmol/m3, solution volume = 400 cm3,

CO2 loading = 0.40 mol/mol and solution temperature = 40°C)

Figure 4.2 Effect of solution volume on foaminess coefficients (MEA 73

concentration = 2.0 kmol/m3, N2 velocity = 2.06 m3/m2-hr, CO2

loading = 0.40 mol/mol and solution temperature = 40°C)

Figure 4.3 Three principal forces influencing bubble formation 74

x i i

List of Figures

Figure 1.1 Schematic diagram of a coal-fired power plant with post-

combustion treatment processes


Figure 2.1 Characterization of foam morphology based on the gas fraction

criteria (redrawn from Schramm (1994) and Thiele et al. (2003))

Figure 2.2 Marangoni effect in the surfactant-stabilized film (Schramm,

1994)

Figure 3.1 Schematic diagram of the static foaming experimental setup

Figure 3.2 Average foam volume profile during blowing time (MEA solution

volume = 400 cm3, CO2 loading = 0.40 mol/mol, N2 velocity =

2.06 m3/m2-hr, MEA concentration = 5.0 kmol/m3 and solution

temperature = 40°C)

Figure 3.3 ( a ) Schematic diagram of the column foaming experimental

apparatus and (b) photograph of the absorber fitted with two

elements of Mellapak 500.Y

Figure 3.4 Example of (a) a solution level above the liquid outlet tube at the

bottom of the column and (b) a foam height measurement (liquid

velocity = 4.6 m3/m2-hr, air velocity = 120 mm/s and elapse time

at = 15 minutes)

Figure 4.1 Effect of superficial gas velocity on foaminess coefficients (MEA

concentration = 2.0 and 5.0 kmol/m3, solution volume = 400 cm3,


Figure 4.2 Effect of solution volume on foaminess coefficients (MEA

concentration = 2.0 kmol/m3, N2 velocity = 2.06 m3/m2-hr, C02


Figure 4.3 Three principal forces influencing bubble formation

Page

3

7

33

39

53

57

63

67

71

73

74

xn

Figure 4.4 Effect of alkanolamine concentration on foaminess coefficient (N2 77

velocity = 2.06 m3/m2-hr, solution volume = 400 cm3, absorber top

condition: CO2 loading = 0.20 mol/mol and solution temperature =

40°C, absorber bottom condition: CO2 loading = 0.40 mol/mol and

solution temperature = 60°C)

Figure 4.5 (a) Surface tension of the CO2-unloaded aqueous MEA solution 78

replotted from the experimental data (Vazquez et al., 1997), (b)

predicted density of the CO2-loaded MEA solution from

correlation (Weiland et al., 1998) and (c) predicted viscosity of the

CO2-loaded aqueous MEA solutions from correlation (Weiland et

al., 1998)

Figure 4.6 Effect of CO2 loading on foaminess coefficient (MEA 80


solution volume = 400 cm3 and solution temperature = 40, 60 and

90°C)

Figure 4.7 (a) Surface tension of the CO2-loaded aqueous MEA solution as a 81

function of CO2 loading and solution temperature (measured by

Spinning Drop Interfacial Tensiometer Model 510), (b) predicted

density of 5.0 kmol/m3 MEA solution from correlation (Weiland et

al., 1998), and (c) predicted viscosity of 5.0 kmol/m3 MEA

solution from correlation (Weiland et al., 1998)

Figure 4.8 Effect of solution temperature on foaminess coefficient (MEA 83


solution volume = 400 cm3 and CO2 loading = 0.20 and 0.40

mol/mol)

Figure 4.9 (a) Predicted viscosity of 5.0 kmol/m3 MEA solution from 84

correlation (Weiland et al., 1998), (b) surface tension of 5.0

kmol/m3 unloaded-CO2 MEA solution replotted from experimental

data (Vazquez et al., 1997), and (c) predicted density of 5.0

kmol/m3 MEA solution from correlation (Weiland et al., 1998)

Figure 4.4 Effect of alkanolamine concentration on foaminess coefficient (N2 77

velocity = 2.06 m3/m2-hr, solution volume = 400 cm3, absorber top

condition: CO2 loading = 0.20 mol/mol and solution temperature =

40°C, absorber bottom condition: CO2 loading = 0.40 mol/mol and


Figure 4.5 (a) Surface tension of the C02-unloaded aqueous ME A solution 78

replotted from the experimental data (Vazquez et al., 1997), (b)

predicted density of the CC>2-loaded MEA solution from

correlation (Weiland et al., 1998) and (c) predicted viscosity of the

CC>2-loaded aqueous MEA solutions from correlation (Weiland et

al., 1998)

Figure 4.6 Effect of CO2 loading on foaminess coefficient (MEA 80

concentration =5.0 kmol/m3, N2 velocity = 2.06 m3/m2-hr,

solution volume = 400 cm3 and solution temperature = 40, 60 and

90°C)

Figure 4.7 ( a ) Surface tension of the CC^-loaded aqueous MEA solution as a 81

function of CO2 loading and solution temperature (measured by

Spinning Drop Interfacial Tensiometer Model 510), (b) predicted

density of 5.0 kmol/m3 MEA solution from correlation (Weiland et

al., 1998), and (c) predicted viscosity of 5.0 kmol/m3 MEA

solution from correlation (Weiland et al., 1998)

Figure 4.8 Effect of solution temperature on foaminess coefficient (MEA 83


solution volume = 400 cm3 and CO2 loading = 0.20 and 0.40

mol/mol)

Figure 4.9 (a) Predicted viscosity of 5.0 kmol/m3 MEA solution from 84

correlation (Weiland et al., 1998), (b) surface tension of 5.0

kmol/m3 unloaded-C02 MEA solution replotted from experimental

data (Vazquez et al., 1997), and (c) predicted density of 5.0

kmol/m3 MEA solution from correlation (Weiland et al., 1998)

xiii

Figure 4.10 Effect of corrosion inhibitors on foaminess coefficient (corrosion 88

inhibitor = NaVO3, CuCO3 and Na2SO3, corrosion inhibitor

concentration = 1000 ppm, MEA concentration = 5.0 kmol/m3, N2

velocity = 2.06 m3/m2-hr, solution volume = 400 cm3, CO2 loading

= 0.40 mol/mol and solution temperature = 60°C)

Figure 4.11 (a) Surface tension of the CO2-unloaded aqueous alkanolamine 93

solution as a function of alkanolamine concentration (40°C)

replotted from experimental data (Vazquez et al., 1996 and 1997

and Alvarez et al., 1998), (b) density of the CO2-unloaded aqueous

alkanolamine solution as a function of alkanolamine concentration

(60°C) replotted from experimental data (Maham et al., 1994;

Maham et al., 1995 and Henni et al., 2003), and (c) viscosity of the

CO2-unloaded aqueous alkanolamine solution as a function of

alkanolamine concentration (60°C) replotted from experimental

data (Teng et al., 1994; Maham et al., 2002 and Henni et al., 2003)

Figure 4.12 (a) Surface tension of CO2-unloaded aqueous blended 94

alkanolamine solutions at 60°C replotted from experimental data:

MEA+MDEA (Alvarez et al., 1998), DEA+MDEA (Alvarez et al.,

1998) and MEA+AMP (Vazquez et al., 1997), (b) predicted

viscosity of CO2-unloaded aqueous blended alkanolamine solution

with 4.0 kmol/m3 total concentration at 60°C (Mandal et al., 2003)

Figure 5.1 Framework of the foam height correlation 98

Figure 5.2 Schematic diagram of the pressures exerted on the gas bubble in 105

the liquid solution

Figure 5.3 Example of the foam observed in the static foaming experiment 106

Figure 5.4 Parity chart between H„p and H for the foam height correlation 113

(dashed•lines represent 95% confidence interval)

Figure 5.5 Simulation results of predicted foam height with respect to 116

superficial gas velocity (solution volume = 400 cm3, CO2 loading

= 0.40 mol/mol and solution temperature = 40°C) with MEA

concentration (a) 2.0 kmol/m3 and (b) 5.0 kmol/m3

xiv

Figure 4.10 Effect of corrosion inhibitors on foaminess coefficient (corrosion 88

inhibitor = NaVC>3, CUCO3 and Na2S03, corrosion inhibitor

concentration = 1000 ppm, MEA concentration = 5.0 kmol/m3, N2

velocity = 2.06 m3/m2-hr, solution volume = 400 cm3, CO2 loading

= 0.40 mol/mol and solution temperature = 60°C)

Figure 4.11 (a ) Surface tension of the C02-unloaded aqueous alkanolamine 93

solution as a function of alkanolamine concentration (40°C)

replotted from experimental data (Vazquez et al., 1996 and 1997

and Alvarez et al., 1998), (b) density of the C02-unloaded aqueous

alkanolamine solution as a function of alkanolamine concentration

(60°C) replotted from experimental data (Maham et al., 1994;

Maham et al., 1995 and Henni et al., 2003), and (c) viscosity of the

C02-unloaded aqueous alkanolamine solution as a function of

alkanolamine concentration (60°C) replotted from experimental

data (Teng et al., 1994; Maham et al., 2002 and Henni et al., 2003)

Figure 4.12 (a) Surface tension of CCh-unloaded aqueous blended 94

alkanolamine solutions at 60°C replotted from experimental data:

MEA+MDEA (Alvarez et al., 1998), DEA+MDEA (Alvarez et al.,

1998) and MEA+AMP (Vazquez et al., 1997), (b) predicted

viscosity of CCVunloaded aqueous blended alkanolamine solution

with 4.0 kmol/m3 total concentration at 60°C (Mandal et al., 2003)

Figure 5.1 Framework of the foam height correlation 98

Figure 5.2 Schematic diagram of the pressures exerted on the gas bubble in 105

the liquid solution

Figure 5.3 Example of the foam observed in the static foaming experiment 106

Figure 5.4 Parity chart between Hexp and H for the foam height correlation 113

(dashed'lines represent 95% confidence interval)


superficial gas velocity (solution volume = 400 cm3, CO2 loading

= 0.40 mol/mol and solution temperature = 40°C) with MEA

concentration (a) 2.0 kmol/m3 and (b) 5.0 kmol/m3

xiv


solution volume (MEA concentration = 2.0 kmol/m3, superficial

gas velocity = 0.57 mm/s, CO2 loading = 0.40 mol/mol and


Figure 5.7 Simulation results of predicted foam height with respect to MEA 118

concentration (superficial gas velocity = 0.57 mm/s and solution

volume = 400 cm3); (a) absorber top condition: CO2 loading =

0.20 mol/mol and solution temperature = 40°C and (b) absorber

bottom condition: CO2 loading = 0.40 mol/mol and solution

temperature = 60°C

Figure 5.8 Simulation results of predicted foam height with respect to CO2 119

loading (MEA concentration = 5.0 kmol/m3, superficial gas

velocity = 0.57 mm/s and solution volume = 400 cm3) with

solution temperature (a) 40°C, (b) 60°C, and (c) 90°C


solution temperature (MEA concentration = 5.0 kmol/m3,

superficial gas velocity = 0.57 mm/s and solution volume = 400

cm3) with CO2 loading (a) 0.20 mol/mol and (b) 0.40 mol/mol

Figure 5.10 Sensitivity analysis of process parameters on foam height; (a) 127

minimum value of the remaining process parameters and (b)

maximum value of the remaining process parameters

Figure 5.11 Sensitivity analysis of physical properties on foam height; (a) 128



Figure 6.1 Concept of a foam model development 131

Figure 6.2 Model framework to predict total foam volume in a structured 132

packed absorber

X V


solution volume (MEA concentration = 2.0 kmol/m3, superficial

gas velocity = 0.57 mm/s, CO2 loading = 0.40 mol/mol and


Figure 5.7 Simulation results of predicted foam height with respect to MEA 118

concentration (superficial gas velocity = 0.57 mm/s and solution

volume = 400 cm3); (a) absorber top condition: CO2 loading =

0.20 mol/mol and solution temperature = 40°C and (b) absorber

bottom condition: CO2 loading = 0.40 mol/mol and solution

temperature = 60°C

Figure 5.8 Simulation results of predicted foam height with respect to CO2 119

loading (MEA concentration = 5.0 kmol/m3, superficial gas

velocity = 0.57 mm/s and solution volume = 400 cm3) with

solution temperature (a) 40°C, (b) 60°C, and (c) 90°C


solution temperature (MEA concentration = 5.0 kmol/m3,

superficial gas velocity = 0.57 mm/s and solution volume = 400

cm3) with CO2 loading (a) 0.20 mol/mol and (b) 0.40 mol/mol

Figure 5.10 Sensitivity analysis of process parameters on foam height; (a) 127



Figure 5.11 Sensitivity analysis of physical properties on foam height; (a) 128



Figure 6.1 Concept of a foam model development 131

Figure 6.2 Model framework to predict total foam volume in a structured 132

packed absorber

xv

Figure 6.3 (a) An arrangement of corrugated sheets with flow directions of 134

gas and liquid, (b) a location of foam layer on a surface of a

corrugated sheet with a certain crimp dimension and (c) a

mechanism of foam formation on a surface area of a packing

element

Figure 6.4 Illustration of four main forces affecting average bubble radius 139

Figure 6.5 (a) Experimental percent foam volume per packing volume plotted 143

versus the superficial gas velocity at different superficial liquid

velocities (MEA concentration = 5.0 kmol/m3, CO2 loading = 0.40

mol/mol, and solution temperature = 18.5°C) and (b) experimental

foam volume per packing volume plotted versus the L/G ratio

(MEA concentration = 5.0 kmol/m3, CO2 loading = 0.40 mol/mol,

and solution temperature = 18.5°C)

Figure 6.6 Example of turbulence developed at the bottom of the column 144

(superficial liquid velocity = 2.3 m3/m2-hr and superficial gas

velocity = 360 mm/s)

Figure 6.7 Simulation results compared between the experimental and 146

predicted percent foam volume per packing volume

Figure 6.8 Simulated profiles of local foam volumes along the absorber 148

height under various CO2 absorption conditions: (a) effect of CO2

loading of feed solution at three different superficial liquid

velocities (feed solution temperature = 33.2 ± 1.1°C, air flow rate

= 38.5 kmol/m2-hr and MEA concentration = 3.0 kmol/m3) and (b)

effect of the temperature of feed solution at three different

superficial liquid velocities (CO2 loading of feed solution = 0.33

mol/mol, air flow rate = 38.5 kmol/m2-hr, and MEA concentration

= 3.0 kmol/m3)

xvi

Figure 6.3 (a) An arrangement of corrugated sheets with flow directions of 134

gas and liquid, (b) a location of foam layer on a surface of a

corrugated sheet with a certain crimp dimension and (c) a

mechanism of foam formation on a surface area of a packing

element

Figure 6.4 Illustration of four main forces affecting average bubble radius 139

Figure 6.5 (a) Experimental percent foam volume per packing volume plotted 143

versus the superficial gas velocity at different superficial liquid

velocities (MEA concentration = 5.0 kmol/m3, CO2 loading = 0.40

mol/mol, and solution temperature = 18.5°C) and (b) experimental

foam volume per packing volume plotted versus the LIG ratio

(MEA concentration = 5.0 kmol/m3, CO2 loading = 0.40 mol/mol,

and solution temperature = 18.5°C)

Figure 6.6 Example of turbulence developed at the bottom of the column 144

(superficial liquid velocity = 2.3 m3/m2-hr and superficial gas

velocity = 360 mm/s)

Figure 6.7 Simulation results compared between the experimental and 146

predicted percent foam volume per packing volume

Figure 6.8 Simulated profiles of local foam volumes along the absorber 148

height under various CO2 absorption conditions: (a) effect of CO2

loading of feed solution at three different superficial liquid

velocities (feed solution temperature = 33.2 ± 1.1°C, air flow rate

= 3 8 . 5 k m o l / m 2 - h r a n d M E A c o n c e n t r a t i o n = 3 . 0 k m o l / m 3 ) a n d ( b )

effect of the temperature of feed solution at three different

superficial liquid velocities (CO2 loading of feed solution = 0.33

mol/mol, air flow rate = 38.5 kmol/m2-hr, and MEA concentration

= 3.0 kmol/m3)

xvi

Figure 6.9 Effect of the degradation product (ammonium thiosulfate) and 150

corrosion inhibitor (sodium metavanadate) on the simulated

foaming profile along the absorber (air flow rate = 38.5 kmol/m2-

hr, MEA concentration = 3.0 kmol/m3, CO2 loading of feed

solution = 0.33 mol/mol, superficial liquid velocity = 12.2 m3/m2-

hr, and feed solution temperature = 21.1°C (Aroonwilas, 2001)

Figure 6.10 Effect of the foaming on the gas volumetric flow rate for non- 153

degraded and degraded MEA solutions containing degradation

product (ammonium thiosulfate) and corrosion inhibitor (sodium

metavanadate) (MEA concentration = 3.0 kmol/m3, lean and rich

CO2 loading of the solution = 0.20 and 0.55 mol/mol, respectively,

feed solution temperature = 40°C, and CO2 concentration in the

gas phase = 15%)

xvii

Figure 6.9 Effect of the degradation product (ammonium thiosulfate) and 150

corrosion inhibitor (sodium metavanadate) on the simulated

foaming profile along the absorber (air flow rate = 38.5 kmol/m2-

hr, MEA concentration = 3.0 kmol/m3, CO2 loading of feed

solution = 0.33 mol/mol, superficial liquid velocity = 12.2 m3/m2-

hr, and feed solution temperature = 21.1°C (Aroonwilas, 2001)

Figure 6.10 Effect of the foaming on the gas volumetric flow rate for non- 153

degraded and degraded MEA solutions containing degradation

product (ammonium thiosulfate) and corrosion inhibitor (sodium

metavanadate) (MEA concentration = 3.0 kmol/m3, lean and rich

CO2 loading of the solution = 0.20 and 0.55 mol/mol, respectively,

feed solution temperature = 40°C, and CO2 concentration in the

gas phase = 15%)

xvii

Nomenclature

a1,...,a6 coefficients used in Subroutine 3

constant between interaction energy of molecular pair ij

an exponent of physical variable of n

ap specific surface area of packing material (m2/m3 packing)

A cross-sectional area

As surface area (m2)

b slab width (m)

b1,...,b6 coefficients used in Subroutine 3

bh constant for Equation (2.19)

B half of corrugation base width (m)

c constant for Equation (6.12)

ci,..•,c6 coefficients used in Subroutine 3

Ca capillary number

d bubble diameter (mm)

dave average bubble diameter (m)

d, diameter of bubble entering the foam layer (m)

dx, dy, dz increment of distance in the x-, y- and z-axis, respectively

Dc column diameter (m)

Dh diameter of perforation hole (mm)

E surface elasticity (mN/m)

E eff effective elasticity (mN/m)

EM Marangoni dilational modulus (mN/rn)

xviii

Nomenclature

ai,...,a6 coefficients used in Subroutine 3

ay constant between interaction energy of molecular pair ij

a„ exponent of physical variable of n

ap specific surface area of packing material (m2/m3 packing)

^ cross-sectional area

As surface area (m2)

b slab width (m)

bj,...,b(5 coefficients used in Subroutine 3

bh constant for Equation (2.19)

B half of corrugation base width (m)

c constant for Equation (6.12)

ci,...,c6 coefficients used in Subroutine 3

Ca capillary number

d bubble diameter (mm)

dê average bubble diameter (m)

d„ diameter of bubble entering the foam layer (m)

dx, dy, dz increment of distance in the x-, y- and z-axis, respectively

Dc column diameter (m)

Dh diameter of perforation hole (mm)

E surface elasticity (mN/m)

Eeff effective elasticity (mN/m)

EM Marangoni dilational modulus (mN/m)

xviii

fpe,foration perforation factor of the packing element

fweited fraction of the wetted surface area

F8 buoyancy force

Fy hydrostatic force

FK kinetic force

Fs surface tension force

Fr Froude number

g gravitational acceleration (m/s2)

G Gibbs free energy (J)

Gexcess molar excess Gibbs free energy (J)

Gidea! molar Gibbs free energy of the ideal solution (J)

G gas flow rate (m3/s)

G gas flow rate per unit area or superficial gas velocity

6, critical superficial gas velocity

Gm minimum superficial gas velocity (mm/s)

hcrimp crimp height

hd height of gas dispersion layer (m)

hiiq liquid height above the perforation hole (m)

hp height of packing element (m)

h' liquid holdup (m3 liquid solution/m3 packing)

H pneumatic steady-state foam height

Hexp experimental steady-state foam height

the number of dimensional parameters

xix

/perforation

fwetted

Fb

FH

FK

Fs

Fr

8

G

Gexcess

G ideal

G

G

GL

hcrimp

hd

hliq

hp

h'

H

exp

perforation factor of the packing element

fraction of the wetted surface area

buoyancy force

hydrostatic force

kinetic force

surface tension force

Froude number

gravitational acceleration (m/s )

Gibbs free energy (J)

molar excess Gibbs free energy (J)

molar Gibbs free energy of the ideal solution (J)

gas flow rate (m3/s)

gas flow rate per unit area or superficial gas velocity

critical superficial gas velocity

minimum superficial gas velocity (mm/s)

crimp height

height of gas dispersion layer (m)

liquid height above the perforation hole (m)

height of packing element (m)

liquid holdup (m3 liquid solution/m3 packing)

pneumatic steady-state foam height

experimental steady-state foam height

the number of dimensional parameters

xix

k

K

Kf

Ki,

1

L/G

L

m,

M

MW,

n

N

N bub

NT

P

PC

P H,d

P Hi

P inside

P outside

P.

gdown

the total number of fundamental units needed to express the

system

adjustable parameter for Equation (2.16)

constant for Equation (2.21)


capillary perimeter (mm)

liquid-to-gas ratio (kg solution/kg air)

liquid flow rate per unit area or superficial liquid velocity

mass percent of i

MEA concentration (kmol/m3)

molecular weight of i

the number of physical variables

adjustable parameter for Equation (2.16)

the number of bubbles formed at diffuser per unit of time

the total number of slabs per a packing section of interest

operating pressure (N/m2)

capillary pressure (N/m2)

hydrostatic pressure due to gas dispersion layer (N/m2)

hydrostatic pressure due to foam layer (N/m2)

pressure inside of the gas bubble (N/m2)

pressure outside of the gas bubble (N/m2)

additional pressure term (N/m2)

rate of liquid in lamella flowing back to the bulk solution (m/s)

XX

k the total number of fundamental units needed to express

system

K adjustable parameter for Equation (2.16)

KJ constant for Equation (2.21)

KP constant for Equation (2.20)

I capillary perimeter (mm)

L/G liquid-to-gas ratio (kg solution/kg air)

L liquid flow rate per unit area or superficial liquid velocity

NTI mass percent of i

M MEA concentration (kmol/m3)

MW, molecular weight of i

n the number of physical variables

N adjustable parameter for Equation (2.16)

Nbub the number of bubbles formed at diffuser per unit of time

Nt the total number of slabs per a packing section of interest

P operating pressure (N/m2)

Pc capillary pressure (N/m2)

PHJ hydrostatic pressure due to gas dispersion layer (N/m2)

PHJ hydrostatic pressure due to foam layer (N/m2)

P inside pressure inside of the gas bubble (N/m2)

P outside pressure outside of the gas bubble (N/m2)

P* additional pressure term (N/m2)

(Jdown rate of liquid in lamella flowing back to the bulk solution (m/s)

XX

• film rate of liquid from the bulk solution moving upward to the foam

layer through the foam films (m/s)

q,, PB rate of liquid from the bulk solution moving upward to the foam

layer through the Plateau borders (m/s)

Qn physical variable of n

r average bubble radius (mm)

reg effective average radius of bubble

r 1,,prechcted average bubble radius predicted using the Laplace equation

R universal gas constant

RI, R2 principal radii of curvature (mm)

Re Reynolds number

s the number of immobile surfaces

S, additional physical variable of i

Sr sum of squares of residuals

T temperature

u velocity of liquid in the vertical lamella (rnm/s)

U„ interaction energy of molecular pair ii

interaction energy of molecular pair ij

U,, interaction energy of molecular pair jj

v, molar volume of pure component i at constant temperature

molar volume of pure component j at constant temperature

molar volume of i (ml/mol)

Vbub bubble volume (m3)

Vso1 solution volume (cm3) xxi

gup, film rate of liquid from the bulk solution moving upward to the foam

layer through the foam films (m/s)

qup PB rate of liquid from the bulk solution moving upward to the foam

layer through the Plateau borders (m/s)

Q„ physical variable of n

r average bubble radius (mm)

reff effective average radius of bubble

j/,predicted average bubble radius predicted using the Laplace equation

R universal gas constant

Ri, R2 principal radii of curvature (mm)

Re Reynolds number

5 the number of immobile surfaces

Si additional physical variable of i

Sr sum of squares of residuals

T temperature

u velocity of liquid in the vertical lamella (mm/s)

Uu interaction energy of molecular pair ii

U,j interaction energy of molecular pair ij

Ujj interaction energy of molecular pair jj

Vi molar volume of pure component i at constant temperature

Vj molar volume of pure component j at constant temperature

V, molar volume of i (ml/mol)

Vbub bubble volume (m3)

Vsoi solution volume (cm3) xxi

Vy constant for Equation (5.15)

V** molar volume due to the interaction between MEA and CO2

Vr" liquid volume after supplying gas to the test cell (cm3)

Ve entire gas volume dispersed through the diffuser (m3)

w constant for Equation (6.12)

x, mole fraction of i

Greek letter

a corrugation angle (°)

aco2 CO2 loading (mol CO2/mol MEA)

y surface tension

Yslag slag surface tension (N/m)

Ay surface tension gradient (mN/m)

g film thickness

acr critical thickness of the lamella film (m)

Save average gas fraction in the foam layer

sd gas fraction in the gas dispersion layer

sf gas fraction in the foam layer

acute angle of a slab with respect to the next corrugation sheet

A parameter defined by Equation (5.21)

viscosity

slag viscosity (Pa.$)

V'

V"

•ycell

ygff

w

Xi

Greek letter

a

aco2

r

Yslag

Ay

S

dCr

Save

ed

*

9

A

H

Mslag


molar volume due to the interaction between MEA and CO2

liquid volume after supplying gas to the test cell (cm3)

entire gas volume dispersed through the diffuser (m )


mole fraction of i

corrugation angle (°)

CO2 loading (mol CCVmol MEA)

surface tension

slag surface tension (N/m)

surface tension gradient (mN/m)

film thickness

critical thickness of the lamella film (m)

average gas fraction in the foam layer

gas fraction in the gas dispersion layer

gas fraction in the foam layer

acute angle of a slab with respect to the next corrugation sheet

parameter defined by Equation (5.21)

viscosity

slag viscosity (Pa.s)

xxii

17i

p

Pstag

Op

Tbo

V

Vexp

Vslab

dimensionless parameter of i

density (kg/m3)

slag density (kg/m3)

difference between liquid and gas density (kg/m3)

foaminess coefficient

binary coalescence time (s)

average steady-state foam volume (m3)

experimental steady-state foam volume (cm3)

slap foam volume (m3)

total foam volume (m3)

Subscript

CO2 carbon dioxide

G gas

1120 water

L liquid

MEA monoethanolamine

N2 nitrogen

Abbreviation

AAD average absolute deviation

AMP 2-amino-2-methyl-l-propanol

DEA diethanolamine

nt

p

pslag

Ap

E

T-bo

V

Vexp

Vslab

or

Subscript

co2

G

H20

L

MEA

N2

Abbreviation

AAD

AMP

DEA

dimensionless parameter of i

density (kg/m3)

slag density (kg/m3)

difference between liquid and gas density (kg/m )

foaminess coefficient

binary coalescence time (s)

average steady-state foam volume (m3)

experimental steady-state foam volume (cm3)

•5

slap foam volume (m )

total foam volume (m3)

carbon dioxide

gas

water

liquid

monoethanolamine

nitrogen

average absolute deviation

2-amino-2-methyl-1 -propanol

diethanolamine

xxiii

DEP 1-(2-hydroxyethyl) piperazine

DGA diglycolamine

DIPA diisopropanolamine

HEP 1,4-Bis (2-hydroxyethyl)piperazine

MDEA N-methyldiethanolamine


MMSCFD million standard cubic feet per day

PB Plateau border

PM particulate matter

PZ piperazine

R&D research and development

scfm standard cubic foot per minute

SDBS sodium dodecylbenzene sulphonate

xxiv

DEP l-(2-hydroxyethyl) piperazine

DGA diglycolamine

DIPA diisopropanolamine

HEP 1,4-Bis (2-hydroxyethyl)piperazine

MDEA N -methy Idiethanolamine


MMSCFD million standard cubic feet per day

PB Plateau border

PM particulate matter

PZ piperazine

R&D research and development

scfm standard cubic foot per minute

SDBS sodium dodecylbenzene sulphonate

xxiv

1. INTRODUCTION

Coal-fired power plants generate electricity by combusting coal to produce high

pressure steam, which drives a series of turbines and generators. The coal combustion

produces flue gas containing a number of air pollutants currently being regulated or to be

regulated in the near future under various environmental laws. These pollutants include

hazardous pollutants such as mercury (Hg) and also criteria pollutants such as particulate

matter (PM), sulfur oxides (SOX), and nitrogen oxides (N0x). The coal-fired power plants

also produce and release carbon dioxide (CO2), a major greenhouse gas contributing to

global climate change, to the atmosphere. The CO2 emission is of great concern due to its

large quantity and implications to the environment. It is predicted that coal combustion

will contribute approximately 45 percent of the total world CO2 emissions (40385 million

metric tonnes) in 2030. The coal combustion from the United States and Canada is

predicted to contribute about 15.9 and 1.8 percent, respectively, of the world CO2

emissions in 2030 (EIA, 2009).

To enforce the reduction of global greenhouse gas emissions, delegates from

many countries attending the United Nations climate change conference held in

December 2009 in Copenhagen have agreed on the Copenhagen Accord (UNFCCC,

2009a). Under this accord, Canada recently submitted an emissions target of 17 percent

reduction from 2005's level by 2020 to the United Nations Framework Convention on

Climate Change (UNFCCC, 2009b). One of the reduction strategies to help Canada and

other nations achieve their target is to capture CO2 from combustion flue gas streams

generated by coal-fired power plants since CO2 emission from these power stations is

expected to contribute about 60 percent of the total world CO2 emissions that are released

1. INTRODUCTION

Coal-fired power plants generate electricity by combusting coal to produce high

pressure steam, which drives a series of turbines and generators. The coal combustion

produces flue gas containing a number of air pollutants currently being regulated or to be

regulated in the near future under various environmental laws. These pollutants include

hazardous pollutants such as mercury (Hg) and also criteria pollutants such as particulate

matter (PM), sulfur oxides (SOx), and nitrogen oxides (NOx). The coal-fired power plants

also produce and release carbon dioxide (CO2), a major greenhouse gas contributing to

global climate change, to the atmosphere. The CO2 emission is of great concern due to its

large quantity and implications to the environment. It is predicted that coal combustion

will contribute approximately 45 percent of the total world CO2 emissions (40385 million

metric tonnes) in 2030. The coal combustion from the United States and Canada is

predicted to contribute about 15.9 and 1.8 percent, respectively, of the world CO2

emissions in 2030 (EIA, 2009).

To enforce the reduction of global greenhouse gas emissions, delegates from

many countries attending the United Nations climate change conference held in

December 2009 in Copenhagen have agreed on the Copenhagen Accord (UNFCCC,

2009a). Under this accord, Canada recently submitted an emissions target of 17 percent

reduction from 2005's level by 2020 to the United Nations Framework Convention on

Climate Change (UNFCCC, 2009b). One of the reduction strategies to help Canada and

other nations achieve their target is to capture CO2 from combustion flue gas streams

generated by coal-fired power plants since CO2 emission from these power stations is

expected to contribute about 60 percent of the total world CO2 emissions that are released

by large stationary point sources using combustion of fossil fuels (Metz et al., 2005).

This strategy also enables the continuation of fossil fuel utilization to meet energy

demand as alternative energy sources are developed. The CO2 capture unit can be

integrated into the power plant as a flue gas post-treatment unit with the arrangement

shown in Figure 1.1. This is to treat the flue gas after the removal of PM and SO2 in order

to prevent plugging and fouling and to minimize degradation of CO2 capture solvents.

Although CO2 capture can be technically implemented by a number of gas

separation methods, gas absorption into a liquid solvent is the most attractive because of

its maturity in gas treating services. For many decades, the alkanolamine-based gas

absorption process has played a significant role in gas sweetening plants in removing

acid gases from gas streams. This process is currently gaining a great deal of interest as

an environmental abatement unit for capturing CO2 from industrial flue gas streams

generated by coal-fired power plants. The existing power plants that are integrated with

the alkanolamine absorption-based CO2 capture unit are listed in Table 1.1. Most of these

CO2 capture units are R&D scale pilot plants in which the feed gas is a slipstream of flue

gas produced by a power plant.

2

by large stationary point sources using combustion of fossil fuels (Metz et al., 2005).

This strategy also enables the continuation of fossil fuel utilization to meet energy

demand as alternative energy sources are developed. The CO2 capture unit can be

integrated into the power plant as a flue gas post-treatment unit with the arrangement

shown in Figure 1.1. This is to treat the flue gas after the removal of PM and SO2 in order

to prevent plugging and fouling and to minimize degradation of CO2 capture solvents.

Although CO2 capture can be technically implemented by a number of gas

separation methods, gas absorption into a liquid solvent is the most attractive because of

its maturity in gas treating services. For many decades, the alkanolamine-based gas

absorption process has played a significant role in gas sweetening plants in removing

acid gases from gas streams. This process is currently gaining a great deal of interest as

an environmental abatement unit for capturing CO2 from industrial flue gas streams

generated by coal-fired power plants. The existing power plants that are integrated with

the alkanolamine absorption-based CO2 capture unit are listed in Table 1.1. Most of these

C02 capture units are R&D scale pilot plants in which the feed gas is a slipstream of flue

gas produced by a power plant.

2

Electricity supply to community

COAL-FIRED POWER PLANT

CO2 for utilization and storage

FLUE GAS TREATMENT

Flue gas M

Emit to atmosphere

Figure 1.1 Schematic diagram of a coal-fired power plant with post-combustion

treatment processes

3

Electricity supply to community

C02 for utilization and storage

Emit to atmosphere

FLUE GAS TREATMENT

COAL-FIRED POWER PLANT

Flue gas PM S02

Figure 1.1 Schematic diagram of a coal-fired power plant with post-combustion

treatment processes

3

Table 1.1 List of examples of coal-fired power plants with an alkanolamine-based CO2

absorption process as a CO2 capture unit

Power plant Type of Plant CO2 capacity Use of Reference coal capacity (Tonne CO2 CO2

(MW) /day)

Warrior Run power station (Cumberland,

Bituminous coal

229 150 Food industry

Davison et al., 2001

USA)

Boundary Dam power station (Saskatchewan,

Lignite coal 813 up to 4 CO2product

Idem et al., 2006

Canada)

Esbjerg power station (Esbjerg, Denmark)

400 24 CO2product

Knudsen et al., 2009

Niederaussem power station (Niederaussem,

Lignite coal 3864 Up to 7.2 CO2product

Moser et al., 2009

Germany)

4

Table 1.1 List of examples of coal-fired power plants with an alkanolamine-based CO2

absorption process as a CO2 capture unit

Power plant Type of coal

Plant capacity (MW)

C02 capacity (Tonne C02

/day)

Use of co2

Reference

Warrior Run power station (Cumberland, USA)

Bituminous coal

229 150 Food industry

Davison et al., 2001

Boundary Dam power station (Saskatchewan, Canada)

Lignite coal 813 up to 4 C02

product Idem et al., 2006


- 400 24 C02

product Knudsen et al., 2009

Niederaussem power station (Niederaussem, Germany)

Lignite coal 3864 Up to 7.2 C02

product Moser et al., 2009

4

1.1 Process description of regenerable CO2 absorption

Figure 1.2 illustrates a typical configuration of the CO2 absorption process using a

regenerable liquid solvent. The process consists of two major sections, an absorption

section where CO2 in the flue gas is absorbed into the liquid solvent and a regeneration

section where the absorbed CO2 is stripped out by means of heat. In the absorption

section, the gas stream containing CO2 is passed upward through the absorber,

countercurrent to the solvent entering the absorber at the top. Under proper conditions,

CO2 is transferred from the gas stream to the liquid solvent, resulting in a treated gas with

low CO2 content passing out of the absorber top and a CO2-rich solvent leaving the

absorber at the bottom. The rich solvent is then heated in a lean/rich heat exchanger and

enters the regenerator at some point near the top. The CO2-rich solvent is heated to

boiling in the regeneration section by a hot steam reboiler located at the bottom of the

regenerator. The captured CO2 is thereby released from the solvent. Finally, the CO2-lean

solvent is pumped from the regenerator through the lean/rich heat exchanger and a cooler

before being re-introduced to the absorber.

It is recognized that the chemical solvents for CO2 capture are subject to

degradation problems characterized an accumulation of non-regenerable and inactive

products during the process. A reclaimer attached to the hot steam reboiler is used

periodically to remove such degradation products, particularly when the level of these

products exceeds certain amounts (e.g., 1.2 wt% heat stable salt anion of solution (CCR

technologies, 2006) or 10 wt% heat stable salt of total alkanolamine concentration

(DuPart et al., 1993)). An inline filtration is also used in parallel to remove some

degradation products. Makeup tanks for water and alkanolamine solutions are in use for

5

1.1 Process description of regenerable CO2 absorption

Figure 1.2 illustrates a typical configuration of the CO2 absorption process using a

regenerable liquid solvent. The process consists of two major sections, an absorption

section where CO2 in the flue gas is absorbed into the liquid solvent and a regeneration

section where the absorbed CO2 is stripped out by means of heat. In the absorption

section, the gas stream containing CO2 is passed upward through the absorber,

countercurrent to the solvent entering the absorber at the top. Under proper conditions,

CO2 is transferred from the gas stream to the liquid solvent, resulting in a treated gas with

low CO2 content passing out of the absorber top and a C02-rich solvent leaving the

absorber at the bottom. The rich solvent is then heated in a lean/rich heat exchanger and

enters the regenerator at some point near the top. The CC>2-rich solvent is heated to

boiling in the regeneration section by a hot steam reboiler located at the bottom of the

regenerator. The captured CO2 is thereby released from the solvent. Finally, the C02-lean

solvent is pumped from the regenerator through the lean/rich heat exchanger and a cooler

before being re-introduced to the absorber.

It is recognized that the chemical solvents for CO2 capture are subject to

degradation problems characterized an accumulation of non-regenerable and inactive

products during the process. A reclaimer attached to the hot steam reboiler is used

periodically to remove such degradation products, particularly when the level of these

products exceeds certain amounts (e.g., 1.2 wt% heat stable salt anion of solution (CCR

technologies, 2006) or 10 wt% heat stable salt of total alkanolamine concentration

(DuPart et al., 1993)). An inline filtration is also used in parallel to remove some

degradation products. Makeup tanks for water and alkanolamine solutions are in use for

5

making up the solvent concentration due to degradation and solvent loss, thereby

maintaining the desired CO2 capture efficiency of the process.

6

making up the solvent concentration due to degradation and solvent loss, thereby

maintaining the desired CO2 capture efficiency of the process.

6

CO2 and steam

SOLVENT/WATER MAKEUP TANK

Treated gas 4 Lean

solution

ABSORBER

Flue gas

REGENERATOR

Rich Bplux solution

COOLER I Lean solution

LEAN LEAN/RICH SOLUTION

HEAT PUMP EXCHANGER

Rich solution

BOOSTER PUMP RECLAIMER Drain

OVERHEAD CONDENSER

CO2

1-- " )

REFLUX PUMP PUMP

REFLUX DRUM

Steaml v REBOILER

I Steam(


7

C02 and steam OVERHEAD

CONDENSER

if _co2

REGENERATOR SOLVENT/WATER

MAKEUP TANK Rich solution

fteflux Treated gas

Lean solution

REFLUX DRUM

COOLEI Lean solution

REFLUX PUMP ABSORBER

LEAN SOLUTION

PUMP

LEAN/RICH ~ HEAT

EXCHANGER REBOILER

Flue gas.

Rich solution Steam

BOOSTER PUMP RECLAIMER Drain


7

1.2 Process solution

1.2.1 Absorption solvent

At present, there are a number of absorption solvents commercially available for

CO2 capture. They are classified into two categories, chemical and physical solvents. The

chemical solvents are commonly used for treating gas streams with low- and moderate-

CO2 partial pressure while the physical solvents are suitable for high-pressure gas

streams. The typical chemical solvents are alkanolamines commonly used in forms of

aqueous solutions. These chemical solvents include monoethanolamine (MEA),

diethanolamine (DEA), N-methyldiethanolamine (MDEA), diglycolamine (DGA),

diisopropanolamine (DIPA), and 2-amino-2-methyl- 1 -propanol (AMP). Mixtures of

these single alkanolamines known as blended alkanolamines are also gaining a great deal

of interest from practitioners due to their process advantages over the single

alkanolamines. Common formulations of the blended alkanolamines are tertiary

alkanolamines, which are designed for specific CO2 capture targets and purposes. MDEA

is gaining recognition as the key component of the blended alkanolamines because of its

low energy requirements and high CO2 absorption capacity. Addition of a primary amine

MEA or secondary amine DEA into the MDEA solution helps enhance the rate of CO2

capture while maintaining the advantages of MDEA.

The physical solvents are commonly used for high-pressure gas streams. They

require less energy for solvent regeneration than the chemical solvents. Examples of the

physical solvents are propylene carbonate, Selexol, methanol, and N-methyl-2-

pyrrolidone. It is commonly known that the physical solvents alone are ineffective for

low-pressure gas streams. However, mixing between chemical and physical solvents

could provide some benefits for CO2 capture under low-pressure conditions. For instance,

8

1.2 Process solution

1.2.1 Absorption solvent

At present, there are a number of absorption solvents commercially available for

CO2 capture. They are classified into two categories, chemical and physical solvents. The

chemical solvents are commonly used for treating gas streams with low- and moderate-

CO2 partial pressure while the physical solvents are suitable for high-pressure gas

streams. The typical chemical solvents are alkanolamines commonly used in forms of

aqueous solutions. These chemical solvents include monoethanolamine (MEA),

diethanolamine (DEA), N-methyldiethanolamine (MDEA), diglycolamine (DGA),

diisopropanolamine (DIPA), and 2-amino-2-methyl-l-propanol (AMP). Mixtures of

these single alkanolamines known as blended alkanolamines are also gaining a great deal

of interest from practitioners due to their process advantages over the single

alkanolamines. Common formulations of the blended alkanolamines are tertiary

alkanolamines, which are designed for specific CO2 capture targets and purposes. MDEA

is gaining recognition as the key component of the blended alkanolamines because of its

low energy requirements and high CO2 absorption capacity. Addition of a primary amine

MEA or secondary amine DEA into the MDEA solution helps enhance the rate of CO2

capture while maintaining the advantages of MDEA.

The physical solvents are commonly used for high-pressure gas streams. They

require less energy for solvent regeneration than the chemical solvents. Examples of the

physical solvents are propylene carbonate, Selexol, methanol, and N-methyl-2-

pyrrolidone. It is commonly known that the physical solvents alone are ineffective for

low-pressure gas streams. However, mixing between chemical and physical solvents

could provide some benefits for CO2 capture under low-pressure conditions. For instance,

8

blends of physical and chemical solvents such as Sulfinol-D (Sulfolane and DIPA) and

Sulfinol-M (Sulfolane and MDEA) have been found to be effective for the removal of

CO2 and sulfur compounds from gas streams (Gupta et al., 2003). Sulfolane physically

absorbs the bulk of CO2 while both DIPA and MDEA (chemical solvents) work as the

reactive species for capture activities to completely purify gas streams. These mixed

solvents also help reduce corrosion problems.

Apart from the typical alkanolamines mentioned above, there are also a large

number of solvents currently proposed and being investigated. Some of them are

proprietary. The Kansai Electric Company and Mitsubishi Heavy Industries developed a

family of energy-efficient proprietary solvents namely KS-1 (Mimura et al., 1995). This

solvent has been commercialized to recover CO2 from i) the flue gases generated by

natural gas-fired and oil-fired boilers for general use of CO2 such as beverage and dry ice

in Japan and ii) the steam reformer flue gas for urea production in Malaysia and India

(Iijima, 2008). The CO2 capture plant in Japan has a capacity of 330 tonnes of CO2

captured/day and those in Malaysia and India have a capacity of 200 and 450 (x 2 units)

tonnes of CO2 captured/day, respectively (Iijima, 2008). In 2006, an attempt to use the

KS-1 solvent to capture CO2 from coal-fired flue gases was tested in the 2x500 MW

bituminous coal-fired power plant in Matsushima, Japan with a capacity of 10 tonnes of

CO2 captured/day (Kishimoto et al., 2009).

Many researchers have investigated the performance of hot potassium carbonate

(K2CO3) plus DEA as an absorption rate enhancer (Savage et al., 1980; Tseng et al.,

1988; Pohorecki and Kucharski, 1991). Recently, a group of researchers from the

University of Texas at Austin has been testing the performance of blends between K2CO3

and piperazine (PZ) (Cullinane and Rochelle, 2004). Although comparison results

9

blends of physical and chemical solvents such as Sulfinol-D (Sulfolane and DIPA) and

Sulfinol-M (Sulfolane and MDEA) have been found to be effective for the removal of

CO2 and sulfur compounds from gas streams (Gupta et al., 2003). Sulfolane physically

absorbs the bulk of CO2 while both DIPA and MDEA (chemical solvents) work as the

reactive species for capture activities to completely purify gas streams. These mixed

solvents also help reduce corrosion problems.

Apart from the typical alkanolamines mentioned above, there are also a large

number of solvents currently proposed and being investigated. Some of them are

proprietary. The Kansai Electric Company and Mitsubishi Heavy Industries developed a

family of energy-efficient proprietary solvents namely K.S-1 (Mimura et al., 1995). This

solvent has been commercialized to recover CO2 from /) the flue gases generated by

natural gas-fired and oil-fired boilers for general use of CO2 such as beverage and dry ice

in Japan and if) the steam reformer flue gas for urea production in Malaysia and India

(Iijima, 2008). The CO2 capture plant in Japan has a capacity of 330 tonnes of CO2

captured/day and those in Malaysia and India have a capacity of 200 and 450 (x 2 units)

tonnes of CO2 captured/day, respectively (Iijima, 2008). In 2006, an attempt to use the

KS-1 solvent to capture CO2 from coal-fired flue gases was tested in the 2x500 MW

bituminous coal-fired power plant in Matsushima, Japan with a capacity of 10 tonnes of

CO2 captured/day (Kishimoto et al., 2009).

Many researchers have investigated the performance of hot potassium carbonate

(K2CO3) plus DEA as an absorption rate enhancer (Savage et al., 1980; Tseng et al.,

1988; Pohorecki and Kucharski, 1991). Recently, a group of researchers from the

University of Texas at Austin has been testing the performance of blends between K2CO3

and piperazine (PZ) (Cullinane and Rochelle, 2004). Although comparison results

9

between an aqueous solution of PZ with K2CO3 and an aqueous MEA solution as an

absorption solvent for a post-combustion CO2 absorption process obtained from rigorous

thermodynamic models showed that the aqueous MEA solution thermodynamically and

economically outperforms the aqueous PZ/K2CO3 solution, a further investigation by a

model with greater accuracy in prediction of heat of reaction and heat of capacity was

recommended to be used in further testing of the solvent (Oexmann and Kather, 2009).

Ammonia has also been investigated for quite a while (Huang et al., 2002) and has

recently been used in the demonstration CO2 capture units to capture flue gases produced

by i) the 50-MW R.E. Burger power plant in Ohio, USA (McLarnon and Duncan, 2009)

and ii) the 1226-MW Pleasant Prairie Power Plant in Wisconsin, USA (Kozak et al.,

2009). The former has a capacity of 20 tonnes of CO2 captured/day and the latter has a

capacity of more than 35 tonnes of CO2 captured/day.

1.2.2 Other chemicals

In addition to the absorption solvents, the process solution also contains

degradation products and chemical additives such as corrosion inhibitors, antifoam

agents, oxygen scavengers, and salt neutralizers. The degradation products are essentially

formed by degradation reactions of the absorption solvents with other chemical

constituents in the process solution. They can be either regenerable or nonregenerable

under normal operating conditions of CO2 stripping (or solvent regeneration) depending

on the types of chemical constituents taking part in the reactions. The degradation

products caused by CO2 are mostly regenerable and, hence, are not of great concern

compared to the nonregenerable products. The nonregenerable degradation products,

mainly heat stable salts, are formed through the reactions of the absorption solvents with

10

between an aqueous solution of PZ with K2CO3 and an aqueous MEA solution as an

absorption solvent for a post-combustion CO2 absorption process obtained from rigorous

thermodynamic models showed that the aqueous MEA solution thermodynamically and

economically outperforms the aqueous PZ/K2CO3 solution, a further investigation by a

model with greater accuracy in prediction of heat of reaction and heat of capacity was

recommended to be used in further testing of the solvent (Oexmann and Kather, 2009).

Ammonia has also been investigated for quite a while (Huang et al., 2002) and has

recently been used in the demonstration CO2 capture units to capture flue gases produced

by t) the 50-MW R.E. Burger power plant in Ohio, USA (McLarnon and Duncan, 2009)

and ii) the 1226-MW Pleasant Prairie Power Plant in Wisconsin, USA (Kozak et al.,

2009). The former has a capacity of 20 tonnes of CO2 captured/day and the latter has a

capacity of more than 35 tonnes of CO2 captured/day.

1.2.2 Other chemicals

In addition to the absorption solvents, the process solution also contains

degradation products and chemical additives such as corrosion inhibitors, antifoam

agents, oxygen scavengers, and salt neutralizers. The degradation products are essentially

formed by degradation reactions of the absorption solvents with other chemical

constituents in the process solution. They can be either regenerable or nonregenerable

under normal operating conditions of CO2 stripping (or solvent regeneration) depending

on the types of chemical constituents taking part in the reactions. The degradation

products caused by CO2 are mostly regenerable and, hence, are not of great concern

compared to the nonregenerable products. The nonregenerable degradation products,

mainly heat stable salts, are formed through the reactions of the absorption solvents with

10

acids stronger than CO2, such as carboxylic acids. The carboxylic acids are usually

introduced to the capture process along with makeup water and feed gas streams or

generated within the process by undergoing chemical reactions with gaseous components

such as 0 2, CO, and SO2. For example, formic and oxalic acids can be generated by the

reactions of MEA with CO and 0 2 as shown below:

Degradation by CO (modified from Rooney et al., 1997):

H2NCH2CH2OH + H2O --> Ii3NCH2CH2OH + Off (1.1)

CO + OH" —> HCOO" (1.2)

H3NCH2CH2OH + HCOO" —> H2NCH2CH2OH2+-HCOO" (1.3)

where H2NCH2CH2OH, HC00", and H2NCH2CH2OH2+-HCOO" denote MEA,

anion, heat-stable formate salt of MEA, respectively.

Degradation by 0 2 (modified from McCullough and Nielsen, 1996):

formate

H2NCH2CH2OH +'A 0 2 H2NCH2CHO (cc-amino acetaldehyde) (1.4)

H2NCH2CHO +''A 0 2 --> H2NCH2COOH (glycine) (1.5)

H2NCH2COOH + 0 2 --> HOCH2COOH (glycolic acid) (1.6)

HOCH2COOH + 0 2 -4 HCOCOOH (glyoxylic acid) (1.7)

HCOCOOH + 0 2 —> HOCOCOOH (oxalic acid) (1.8)

where H2NCH2CHO, H2NCH2COOH, HOCH2COOH, HCOCOOH, and HOCOCOOH

are cc-amino acetaldehyde, glycine, glycolic acid, glyoxylic acid, and glyoxylic acid,

respectively. Concentrations of common heat stable salts found in gas treating plants are

listed in Table 1.2. The presence of heat stable salts in the process solution causes a

number of adverse effects, including a reduction in acid gas absorption capacity of

alkanolamine, an increase in solution viscosity, an increase in foaming tendency of the

11

acids stronger than CO2, such as carboxylic acids. The carboxylic acids are usually

introduced to the capture process along with makeup water and feed gas streams or

generated within the process by undergoing chemical reactions with gaseous components

such as O2, CO, and SO2. For example, formic and oxalic acids can be generated by the

reactions of MEA with CO and O2 as shown below:

Degradation bv CO (modified from Rooney et al., 1997):

H2NCH2CH2OH + H20 -> H3NCH2CH2OH + OH' (1.1)

CO + OH" -> HCOO" (1.2)

H3NCH2CH2OH + HCOO" -> H2NCH2CH2OH2+-HCOO' (1.3)

where H2NCH2CH2OH, HCOO", and H2NCH2CH2OH2+-HCOO- denote MEA, formate

anion, heat-stable formate salt of MEA, respectively.

Degradation bv O? (modified from McCullough and Nielsen, 1996):

H2NCH2CH2OH + '/2 02 -> H2NCH2CHO (oc-amino acetaldehyde) (1.4)

H2NCH2CHO + '/2 02 -> H2NCH2COOH (glycine) (1.5)

H2NCH2COOH + 02 -> HOCH2COOH (glycolic acid) (1.6)

HOCH2COOH + 02 HCOCOOH (glyoxylic acid) (1.7)

HCOCOOH + 02 -> HOCOCOOH (oxalic acid) (1.8)

where H2NCH2CHO, H2NCH2COOH, HOCH2COOH, HCOCOOH, and HOCOCOOH

are oc-amino acetaldehyde, glycine, glycolic acid, glyoxylic acid, and glyoxylic acid,

respectively. Concentrations of common heat stable salts found in gas treating plants are

listed in Table 1.2. The presence of heat stable salts in the process solution causes a

number of adverse effects, including a reduction in acid gas absorption capacity of

alkanolamine, an increase in solution viscosity, an increase in foaming tendency of the

11

solution, a reduced filter runtime due to the solid precipitation in the solution, and an

increase in corrosion (Rooney and DuPart, 2000; Tanthapanichakoon et al., 2006). An

addition of oxygen scavenger to the solution is claimed to reduce the formation of heat-

stable salts. Examples of oxygen scavenger are oxime, quinine, and hydroxylamine and

their mixtures (Veldman and Trahan, 1997; 2001).

A number of corrosion inhibitors (Mago and West, 1976; Veawab, 2000) have

been developed, patented, and/or commercialized by many major chemical companies for

use in CO2 absorption plants. The patented organic inhibitors include thiourea and

salicyclic acid, while the inorganic inhibitors are vanadium, antimony, copper, cobalt, tin

and sulfur compounds. The inorganic inhibitors are, in practice, more favoured than the

organic ones because of their superior inhibition performance. Vanadium compounds,

particularly sodium metavanadate (NaVO3), are the most extensively and successfully

used in gas treating plants. In addition, antifoam agents are often used for reducing foam

formation, which may occur due to the presence of fine solid particles and heat stable

salts. Common antifoam agents are high-boiling alcohols (Kohl and Nielsen, 1997), such

as octylphenoxyethanol, or silicone-based compounds (Ohta, 1982) such as dimethyl

silicone oil.

12

solution, a reduced filter runtime due to the solid precipitation in the solution, and an

increase in corrosion (Rooney and DuPart, 2000; Tanthapanichakoon et al., 2006). An

addition of oxygen scavenger to the solution is claimed to reduce the formation of heat-

stable salts. Examples of oxygen scavenger are oxime, quinine, and hydroxylamine and

their mixtures (Veldman and Trahan, 1997; 2001).

A number of corrosion inhibitors (Mago and West, 1976; Veawab, 2000) have

been developed, patented, and/or commercialized by many major chemical companies for

use in CO2 absorption plants. The patented organic inhibitors include thiourea and

salicyclic acid, while the inorganic inhibitors are vanadium, antimony, copper, cobalt, tin

and sulfur compounds. The inorganic inhibitors are, in practice, more favoured than the

organic ones because of their superior inhibition performance. Vanadium compounds,

particularly sodium metavanadate (NaVOj), are the most extensively and successfully

used in gas treating plants. In addition, antifoam agents are often used for reducing foam

formation, which may occur due to the presence of fine solid particles and heat stable

salts. Common antifoam agents are high-boiling alcohols (Kohl and Nielsen, 1997), such

as octylphenoxyethanol, or silicone-based compounds (Ohta, 1982) such as dimethyl

silicone oil.

12

Table 1.2 Typical concentrations of heat stable salt anions found in gas treating units

Heat-stable salt

Range (ppm) References Note

Acetate 0-1500 Fan et al., 2000 DEA solution in refinery (vendor data)

5000 Liu et al., 1995 MDEA solution in refinery (plant sample)

2406-3789 Liu et al., 1995 MDEA solution in refinery (plant sample)

750-1250 Craig Jr. and DEA solution in refinery (plant sample) McLaughlin, 1996

Formate 0-35000 Fan et al., 2000 DEA solution in refinery (vendor data)

15000-17000 Fan et al., 2000 DEA solution in refinery (vendor data)




500-11900 Litschewski, 1996 MDEA solution in refinery (plant sample)



Glycolate 0-150 Fan et al., 2000 DEA solution in refinery (vendor data)

6000-21000 Craig Jr. and DEA solution in refinery (plant sample) McLaughlin, 1996

Oxalate 0-150 Fan et al., 2000 DEA solution in refinery (vendor data)


Sulfate 0-350 Fan et al., 2000 DEA solution in refinery (vendor data)


Thiosulfate 0-700 Fan et al., 2000 DEA solution in refinery (vendor data)


Thiocyanate 0-3000 Fan et al., 2000 DEA solution in refinery (vendor data)







13

Table 1.2 Typical concentrations of heat stable salt anions found in gas treating units

Heat-stable salt Range (ppm) References Note

Acetate 0-1500 Fan et al., 2000 DEA solution in refinery (vendor data)



750-1250 Craig Jr. and McLaughlin, 1996

DEA solution in refinery (plant sample)

Formate 0-35000 Fan et al., 2000 DEA solution in refineiy (vendor data)





500-11900 Litschewski, 1996 MDEA solution in refinery (plant sample)


10474-57747 Liuetal., 1995 MDEA solution in refinery (plant sample)

Glycolate 0-150 Fan et al., 2000 DEA solution in refinery (vendor data)

6000-21000 Craig Jr. and McLaughlin, 1996

DEA solution in refinery (plant sample)

Oxalate 0-150 Fan et al., 2000 DEA solution in refinery (vendor data)


Sulfate 0-350 Fan et al., 2000 DEA solution in refinery (vendor data)

100 Liuetal., 1995 MDEA solution in refinery (plant sample)

Thiosulfate 0-700 Fan et al., 2000 DEA solution in refinery (vendor data)


Thiocyanate 0-3000 Fan et al., 2000 DEA solution in refinery (vendor data)






883-21462 Liuetal., 1995 MDEA solution in refinery (plant sample)

13

13 Foaming problems in CO2 absorption plants

1.3.1 Causes and effects

Foaming is one of the most severe operational problems in CO2 absorption

processes using aqueous solutions of alkanolamines, as it causes a great deal of extra

expenditures in capital investment and operation. It typically occurs during plant start-up

and operation in both the absorber and regenerator. Foaming is primarily caused by

process contaminants. As reported by Kohl and Nielsen (1997), clean alkanolamine

solutions do not lead to stable foam, but the dirty ones do. Examples of such

contaminants are condensed or dissolved hydrocarbons, suspended solids, organic acids,

water-soluble surfactants, degradation products of alkanolamine, additives (e.g.,

corrosion inhibitors and antifoam agents), grease, and inorganic chemicals in makeup

water. These contaminants enter the process with feed gas and additives or are generated

within the process through reactions of alkanolamine degradation. Such contaminants can

increase foaming tendency by lowering the surface tension and enhance foam stability by

either increasing surface viscosity or forming gelatinous surface layers, thereby retarding

the liquid drainage. Extensive reviews of the contaminants based on plant experiences

can be found from many technical papers (Ballard, 1966 and 1986; Smith, 1979;

Lieberman, 1980; Keaton and Bourke, 1983; Thomason, 1985; Pauley, 1991; Stewart and

Lanning, 1994; Abdi et al., 2001). In addition, extreme turbulence, high gas velocities,

sludge deposits plugging gas contactors, either trays or packing-type can also bring about

foaming. Oxygen contamination can enhance foam stability through the formation of

carboxylic acids and heat stable salts.

14

1.3 Foaming problems in CO2 absorption plants

1.3.1 Causes and effects

Foaming is one of the most severe operational problems in CO2 absorption

processes using aqueous solutions of alkanolamines, as it causes a great deal of extra

expenditures in capital investment and operation. It typically occurs during plant start-up

and operation in both the absorber and regenerator. Foaming is primarily caused by

process contaminants. As reported by Kohl and Nielsen (1997), clean alkanolamine

solutions do not lead to stable foam, but the dirty ones do. Examples of such

contaminants are condensed or dissolved hydrocarbons, suspended solids, organic acids,

water-soluble surfactants, degradation products of alkanolamine, additives (e.g.,

corrosion inhibitors and antifoam agents), grease, and inorganic chemicals in makeup

water. These contaminants enter the process with feed gas and additives or are generated

within the process through reactions of alkanolamine degradation. Such contaminants can

increase foaming tendency by lowering the surface tension and enhance foam stability by

either increasing surface viscosity or forming gelatinous surface layers, thereby retarding

the liquid drainage. Extensive reviews of the contaminants based on plant experiences

can be found from many technical papers (Ballard, 1966 and 1986; Smith, 1979;

Lieberman, 1980; Keaton and Bourke, 1983; Thomason, 1985; Pauley, 1991; Stewart and

Lanning, 1994; Abdi et al., 2001). In addition, extreme turbulence, high gas velocities,

sludge deposits plugging gas contactors, either trays or packing-type can also bring about

foaming. Oxygen contamination can enhance foam stability through the formation of

carboxylic acids and heat stable salts.

14

Based on plant experiences in gas treating industry, excessive foaming is reported

to cause a number of adverse impacts on the integrity of plant operation as listed below:

1. Excessive loss of absorption solvents. Pressure differential gauge cells across the

absorber and the regenerator are commonly used to detect the occurrence of foaming

(Smith, 1979). A significant change in such pressure indicates excessive foaming and

great entrainment of alkanolamine solutions.

2. Premature flooding. The onset of foam can block the liquid to reach the bottom of the

column, causing an increase in the liquid holdup in upper trays and, consequently, a

liquid entrainment. If this increase is intensified, the flooding can be prematurely

triggered (Smith, 1979).

3. Reduction in plant throughput. With the presence of foams in the absorber, poor

contact of gas stream and alkanolamine solution results in a lower acid gas (CO2)

removal rate (Ballard, 1966). If foaming occurs in the regenerator, the alkanolamine

concentration in the reflux water will increase.

4. Off-specification of products due to poor gas-liquid contact (Smith, 1979).

5. High alkanolamine carryover to downstream plants. The Claus sulfur plant is an

example of a downstream plant that is greatly affected by this problem. The high

carryover results in catalyst damage, which causes dark sulfur. However, other

factors, such as high temperature operation, fouled reflux condensers, and an out of

order liquid-level control system can also cause the carryover problems (Smith,

1979).

15

Based on plant experiences in gas treating industry, excessive foaming is reported

to cause a number of adverse impacts on the integrity of plant operation as listed below:

1. Excessive loss of absorption solvents. Pressure differential gauge cells across the

absorber and the regenerator are commonly used to detect the occurrence of foaming

(Smith, 1979). A significant change in such pressure indicates excessive foaming and

great entrainment of alkanolamine solutions.

2. Premature flooding. The onset of foam can block the liquid to reach the bottom of the

column, causing an increase in the liquid holdup in upper trays and, consequently, a

liquid entrainment. If this increase is intensified, the flooding can be prematurely

triggered (Smith, 1979).

3. Reduction in plant throughput. With the presence of foams in the absorber, poor

contact of gas stream and alkanolamine solution results in a lower acid gas (CO2)

removal rate (Ballard, 1966). If foaming occurs in the regenerator, the alkanolamine

concentration in the reflux water will increase.

4. Off-specification of products due to poor gas-liquid contact (Smith, 1979).

5. High alkanolamine carryover to downstream plants. The Claus sulfur plant is an

example of a downstream plant that is greatly affected by this problem. The high

carryover results in catalyst damage, which causes dark sulfur. However, other

factors, such as high temperature operation, fouled reflux condensers, and an out of

order liquid-level control system can also cause the carryover problems (Smith,

1979).

15

1.3.2 Existing foaming control methods

A number of preventive and control methods of foaming have been applied in gas

treating plants. Of these, the preferred ones are mechanical filtration, carbon adsorption,

solution reclamation (distillation), and addition of antifoam agent.

i) Mechanical filtration

An appropriate mechanical filter can be selected for a particular system by

considering filter characteristics (e.g., performance and efficiency) and fluid properties

(e.g., viscosity). Types of mechanical filters are categorized according to the removal

mechanisms. The filter removing contaminants at the filter surface is called a surface-

type filter while that removing contaminants inside the filter structure is called a depth-

type filter (Ballard and von Phul, 1991). The filter performance is arbitrarily defined by

manufacturers and can be indicated by nominal and absolute rating. The nominal rating is

usually used to determine the particle size removed by the filter while the absolute rating

is assigned to the largest particle size that can pass through the filter. However, both

ratings are meaningless unless the removal efficiency is given. It should be noted that

filters with the same rating can remove particulates at different capacities if their removal

efficiencies are different. A higher efficiency indicates a higher amount of particles that

can be filtered out of the system. Therefore, it is vital to select a filter with the proper

rating and removal efficiency, together with considering its thermal stability and

chemical compatibility with the solution. Pauley et al. (1989) recommended that filters

with 0.5 micron absolute ratings are effective for removing most particles in the system,

while filters with 10 micron absolute ratings can significantly alleviate foaming. Their

recommendation was verified in a gas treating plant using MEA in Texas. In addition to a

16

1.3.2 Existing foaming control methods

A number of preventive and control methods of foaming have been applied in gas

treating plants. Of these, the preferred ones are mechanical filtration, carbon adsorption,

solution reclamation (distillation), and addition of antifoam agent.

/) Mechanical filtration

An appropriate mechanical filter can be selected for a particular system by

considering filter characteristics (e.g., performance and efficiency) and fluid properties

(e.g., viscosity). Types of mechanical filters are categorized according to the removal

mechanisms. The filter removing contaminants at the filter surface is called a surface-

type filter while that removing contaminants inside the filter structure is called a depth-

type filter (Ballard and von Phul, 1991). The filter performance is arbitrarily defined by

manufacturers and can be indicated by nominal and absolute rating. The nominal rating is

usually used to determine the particle size removed by the filter while the absolute rating

is assigned to the largest particle size that can pass through the filter. However, both

ratings are meaningless unless the removal efficiency is given. It should be noted that

filters with the same rating can remove particulates at different capacities if their removal

efficiencies are different. A higher efficiency indicates a higher amount of particles that

can be filtered out of the system. Therefore, it is vital to select a filter with the proper

rating and removal efficiency, together with considering its thermal stability and

chemical compatibility with the solution. Pauley et al. (1989) recommended that filters

with 0.5 micron absolute ratings are effective for removing most particles in the system,

while filters with 10 micron absolute ratings can significantly alleviate foaming. Their

recommendation was verified in a gas treating plant using MEA in Texas. In addition to a

16

good filtration system, monitoring of solution quality should also be constantly

performed (Bacon, 1987).

ii) Carbon adsorption

Adsorption using activated carbon as a sorbent is commonly used for removing

contaminants, especially liquid hydrocarbons. Activated carbon with a higher iodine

number is recommended. Note that activated carbon-based filters are sensitive to

surfactants, which results in a higher amount of carbon required and also the inability to

remove low molecular weight organic acids (Pauley et al., 1989).

iii) Solution reclamation

Most high-boiling point and non-volatile contaminants (e.g., heat stable salts,

suspended solids, and volatile acids) can be removed from the solution by solution

reclamation in a reclaimer under a semi-continuous batch operation. In the reclaimer, the

solution is filled and heated to the operating temperature. As the result, alkanolamine

vapour is released from the overhead while the sludge or residue is thickened at the

bottom of the reclaimer and eventually disposed from the reclaimer by water flush. It is

recommended that the reclamation temperature should be maintained in the range of 143-

149°C. A higher operating temperature above the recommended value can lead to

contaminated distilled vapour, which can be prevented by adding steam or water into the

system periodically (Ballard, 1966; Lieberman, 1980). Soda ash or caustic soda is also

added to the reclaimer as a neutralizer for the heat stable salts and volatile acids. An

integration of the on-site reclaimer to the gas treating plant increases both capital and

operating costs due to the needed supply of steam, water, and chemicals.

17

good filtration system, monitoring of solution quality should also be constantly

performed (Bacon, 1987).

/'/') Carbon adsorption

Adsorption using activated carbon as a sorbent is commonly used for removing

contaminants, especially liquid hydrocarbons. Activated carbon with a higher iodine

number is recommended. Note that activated carbon-based filters are sensitive to

surfactants, which results in a higher amount of carbon required and also the inability to

remove low molecular weight organic acids (Pauley et al., 1989).

iii) Solution reclamation

Most high-boiling point and non-volatile contaminants (e.g., heat stable salts,

suspended solids, and volatile acids) can be removed from the solution by solution

reclamation in a reclaimer under a semi-continuous batch operation. In the reclaimer, the

solution is filled and heated to the operating temperature. As the result, alkanolamine

vapour is released from the overhead while the sludge or residue is thickened at the

bottom of the reclaimer and eventually disposed from the reclaimer by water flush. It is

recommended that the reclamation temperature should be maintained in the range of 143-

149°C. A higher operating temperature above the recommended value can lead to

contaminated distilled vapour, which can be prevented by adding steam or water into the

system periodically (Ballard, 1966; Lieberman, 1980). Soda ash or caustic soda is also

added to the reclaimer as a neutralizer for the heat stable salts and volatile acids. An

integration of the on-site reclaimer to the gas treating plant increases both capital and

operating costs due to the needed supply of steam, water, and chemicals.

17

iv) Addition of antifoam agent

Foaming in gas treating plants can be reduced by the addition of antifoam agents.

To select an appropriate antifoam agent, foaming tests are required with an appropriate

dosage for a particular system and operating conditions (Ballard, 1966). Addition of

antifoam agent is less preferable than filtration and solution reclamation because it does

not physically remove the contaminants from the system and, thus, does not permanently

remedy the foaming (Keaton and Bourke, 1983; Thomason, 1985; Ballard, 1986; Pauley

et al., 1989).

1.3.3 Industrial experience with foaming problem

As listed in Table 1.3, the foaming problem in the CO2 absorption process can be

found in both gas treating services and post-combustion CO2 capture applications. Many

gas treating plants employing an alkanolamine-based absorption process have

encountered the foaming problem. In 1959, the gas treating plant in Aderklaa (Vienna,

Austria), which originally used a 20 wt% aqueous MEA solution and later converted to a

25 wt% aqueous DEA solution to capture acid gases from a 84 MMSCFD natural gas

stream, had battled with a foaming problem caused by liquid hydrocarbons (Heisler and

Weiss, 1975). In 1988, excessive loss of the aqueous MEA solution (over 75% of the

expected value) together with a high MEA carryover due to an onset of foaming in an

absorption column caused the Longview gas plant in Texas to reduce its plant capacity

for processing of natural gas from 27 to 16 MMSCFD. This resulted in an increase in

expenditure of approximately $10000 per year due to MEA loss and a reduction of

$4000000 per year in income (Pauley and Perlmutter, 1988). In 1998, the Master Gas

System processing plants owned by Saudi Aramco using a 35-50 wt% aqueous DGA

18

iv) Addition of antifoam agent

Foaming in gas treating plants can be reduced by the addition of antifoam agents.

To select an appropriate antifoam agent, foaming tests are required with an appropriate

dosage for a particular system and operating conditions (Ballard, 1966). Addition of

antifoam agent is less preferable than filtration and solution reclamation because it does

not physically remove the contaminants from the system and, thus, does not permanently

remedy the foaming (Keaton and Bourke, 1983; Thomason, 1985; Ballard, 1986; Pauley

et al., 1989).

1.3.3 Industrial experience with foaming problem

As listed in Table 1.3, the foaming problem in the CO2 absorption process can be

found in both gas treating services and post-combustion CO2 capture applications. Many

gas treating plants employing an alkanolamine-based absorption process have

encountered the foaming problem. In 1959, the gas treating plant in Aderklaa (Vienna,

Austria), which originally used a 20 wt% aqueous MEA solution and later converted to a

25 wt% aqueous DEA solution to capture acid gases from a 84 MMSCFD natural gas

stream, had battled with a foaming problem caused by liquid hydrocarbons (Heisler and

Weiss, 1975). In 1988, excessive loss of the aqueous MEA solution (over 75% of the

expected value) together with a high MEA carryover due to an onset of foaming in an

absorption column caused the Longview gas plant in Texas to reduce its plant capacity

for processing of natural gas from 27 to 16 MMSCFD. This resulted in an increase in

expenditure of approximately $10000 per year due to MEA loss and a reduction of

$4000000 per year in income (Pauley and Perlmutter, 1988). In 1998, the Master Gas

System processing plants owned by Saudi Aramco using a 35-50 wt% aqueous DGA

18

solution to sweeten sour gases also encountered foaming problems in both the absorption

and regeneration columns, which led to tray damage, reduction in plant capacity (< 50%

of the design value), and plant shutdown (Harruff, 1998). The foaming problem reported

at the Air Products LaPorte Texas HYCO-3 plant employing a 28 wt% aqueous MEA

solution for CO2 capture from syngas caused a substantial CO2 breakthrough and

eventually plant shutdown (Barnes, 1999). For the McMahon plant using a 18 w t %

aqueous MEA solution to absorb sour gases from natural gas with a flow rate of 800

MMSCFD in British Columbia (Canada), foaming caused plant capacity curtailment,

which was equivalent to $2000000 in losses per year, plant shutdown for acid washing,

and the need for an antifoam agent, which resulted in extra spending of up to $100000

per year (Greg et al., 1999). Recently, the foaming problem has been experienced in a

CASTOR CO2 capture pilot plant in Esbjergvwrket (Denmark), which employs a gas

absorption process using a 30 wt% aqueous MEA solution to capture 1 tonne/hr of CO2

from the flue gas generated from a coal-fired power plant (Knudsen et al., 2009).

19

solution to sweeten sour gases also encountered foaming problems in both the absorption

and regeneration columns, which led to tray damage, reduction in plant capacity (< 50%

of the design value), and plant shutdown (Harruff, 1998). The foaming problem reported

at the Air Products LaPorte Texas HYCO-3 plant employing a 28 wt% aqueous ME A

solution for CO2 capture from syngas caused a substantial CO2 breakthrough and

eventually plant shutdown (Barnes, 1999). For the McMahon plant using a 18 wt%

aqueous MEA solution to absorb sour gases from natural gas with a flow rate of 800

MMSCFD in British Columbia (Canada), foaming caused plant capacity curtailment,

which was equivalent to $2000000 in losses per year, plant shutdown for acid washing,

and the need for an antifoam agent, which resulted in extra spending of up to $100000

per year (Greg et al., 1999). Recently, the foaming problem has been experienced in a

CASTOR CO2 capture pilot plant in Esbjergvaerket (Denmark), which employs a gas

absorption process using a 30 wt% aqueous MEA solution to capture 1 tonne/hr of CO2

from the flue gas generated from a coal-fired power plant (Knudsen et al., 2009).

19

Table 1.3 List of examples of CO2 capture plants (both commercial and demonstration

scale) experiencing foaming problems

Plant Solution Reported foaming impacts

Gas treating services

Aderklaa sour gas treating plant (Vienna, Austria)

Aqueous DEA solution Not reported

Longview gas plant (Texas, USA)

Aqueous MEA solution •

•

Excessive solvent loss ($10000/year)

Reduction in plant capacity ($4000000 loss/year)

Master Gas System processing plants (Saudi Arabia)

Aqueous DGA solution •

•

•

Tray damage

Reduction in plant capacity

Plant shutdown

Air Products LaPorte (Texas, USA)


•

CO2 breakthrough

Plant shutdown

McMahon plant (British Columbia, Canada)


•

•


Plant shutdown

Increase in operating cost due to an antifoam agent (up to $100000/year)

Post-combustion CO2 capture application

Esbjerg power Aqueous MEA solution • Use of an antifoam agent station (Esbjerg, and proprietary blended

• Unstable operation Denmark) alkanolamine solutions

20

Table 1.3 List of examples of CO2 capture plants (both commercial and demonstration

scale) experiencing foaming problems

Plant Solution Reported foaming impacts

Gas treating services

Aderklaa sour gas treating plant (Vienna, Austria)

Aqueous DEA solution Not reported


Aqueous MEA solution • Excessive solvent loss ($10000/year)


• Reduction in plant capacity ($4000000 loss/year)

Master Gas System processing plants (Saudi Arabia)

Aqueous DGA solution •

•

•

Tray damage

Reduction in plant capacity

Plant shutdown

Air Products LaPorte (Texas, USA)


•

CO2 breakthrough

Plant shutdown

McMahon plant (British Columbia, Canada)


•

•


Plant shutdown

Increase in operating cost due to an antifoam agent (up to $100000/year)

Post-combustion CO2 capture application


Aqueous MEA solution and proprietary blended alkanolamine solutions

•

•

Use of an antifoam agent

Unstable operation

20

1.4 Limitations of current knowledge

Since gas absorption using alkanolamine-based solvents has been widely used in

gas treating plants to remove acid gases from sour-gas streams in many industries (e.g.,

oil refineries, natural gas processing, and the petrochemical industry) for decades, a

number of technical papers on foaming problems in gas treating plants obtained from

plant operator experience were made public through conference proceedings and

scientific journals, while a few publications were obtained from experimental-based

research as summarized in Table 1.4. In terms of research, there are a few studies being

conducted in this area. The following are summaries of research studies systematically

carried out to reveal the behaviour and mechanisms of foams. In 1989, Pauley and his

colleague studied the effect of alkanolamine types, liquid hydrocarbon, and degradation

products on foaming tendency and foam stability by using air as a dispersing gas under

atmospheric pressure through a sparger (Pauley et al., 1989). The tested aqueous

alkanolamine solutions included a 20 wt% aqueous MEA solution, a 30 wt% aqueous

DEA solution, a 50 wt% aqueous MDEA solution and two aqueous formulated MDEA

solutions (with non-specified additives and alkanolamine concentrations). They found

that the foams generated by the aqueous solutions of MEA, DEA, and MDEA were small

and unstable. As a result, these alkanolamines had a lower foaming tendency and foam

stability than the two formulated MDEAs. Also, 5000 ppm of liquid hydrocarbon were

added in the aqueous MEA, MDEA, and two formulated MDEA solutions to test the

effect of liquid hydrocarbon. The results showed that the addition of liquid hydrocarbon

significantly affected the foam stabilities of MDEA and formulated MDEA due to the

formation of a gelatinous layer. However, both foaming tendency and foam stability of

pure MEA were not greatly changed. The organic acids added to test the effect of

21

1.4 Limitations of current knowledge

Since gas absorption using alkanolamine-based solvents has been widely used in

gas treating plants to remove acid gases from sour-gas streams in many industries (e.g.,

oil refineries, natural gas processing, and the petrochemical industry) for decades, a

number of technical papers on foaming problems in gas treating plants obtained from

plant operator experience were made public through conference proceedings and

scientific journals, while a few publications were obtained from experimental-based

research as summarized in Table 1.4. In terms of research, there are a few studies being

conducted in this area. The following are summaries of research studies systematically

carried out to reveal the behaviour and mechanisms of foams. In 1989, Pauley and his

colleague studied the effect of alkanolamine types, liquid hydrocarbon, and degradation

products on foaming tendency and foam stability by using air as a dispersing gas under

atmospheric pressure through a sparger (Pauley et al., 1989). The tested aqueous

alkanolamine solutions included a 20 wt% aqueous ME A solution, a 30 wt% aqueous

DEA solution, a 50 wt% aqueous MDEA solution and two aqueous formulated MDEA

solutions (with non-specified additives and alkanolamine concentrations). They found

that the foams generated by the aqueous solutions of MEA, DEA, and MDEA were small

and unstable. As a result, these alkanolamines had a lower foaming tendency and foam

stability than the two formulated MDEAs. Also, 5000 ppm of liquid hydrocarbon were

added in the aqueous MEA, MDEA, and two formulated MDEA solutions to test the

effect of liquid hydrocarbon. The results showed that the addition of liquid hydrocarbon

significantly affected the foam stabilities of MDEA and formulated MDEA due to the

formation of a gelatinous layer. However, both foaming tendency and foam stability of

pure MEA were not greatly changed. The organic acids added to test the effect of

degradation product included formic acid, acetic acid, propionic acid, butyric acid,

pentanoic acid, n-hexanoic acid, octanoic acid, decanoic acid, and dodecanoic acid. The

first five organic acids were tested only in aqueous MEA solution, and the rest were

tested in aqueous solutions of MEA, DEA, MDEA, and one formulated MDEA. It was

demonstrated that the degradation products caused an increase in both foaming tendency

and foam stability in pure alkanolamine solutions.

In 1996, McCarthy and Trebble carried out a parametric study of a 30 wt%

aqueous DEA solution to investigate the effect of contaminants including methanol,

hexane, corrosion inhibitor, antifoam agent, lubrication oil, organic acids, degradation

products, and suspended solids at temperatures ranging from 20 to 85°C and under

pressures of 0.1-3 MPa (McCarthy and Trebble, 1996). The solutions contained in a

Jerguson high pressure sight glass were purged by air, nitrogen (N2), CO2, and calibrated

ethane (C2H6) gas through a sparger. Results indicated that most contaminants did not

initiate foams in the clean aqueous DEA solution, but rather acted as foam promoters

once the foams already existed in the system. As the temperature and pressure were

increased, foams were enhanced as a result of the reduced surface tension. However, a

further increase in pressure could decrease the amount of foam due to a reduced gas

velocity at a given mass flow rate. This Jerguson apparatus was later used to test the

effects of methanol, hexane, organic acids, and degradation products on the foaming

tendency of a 50 wt% aqueous MDEA solutions at temperatures varying from 24 to 85°C

and pressures varying from atmospheric pressure to 500 kPa (Yanicki and Trebble,

2006). Similar results as previously found by McCarthy and Trebble (1996) were

expected. The foaming tendency of the solutions tended to be intensified by heavy

organic acids and worsened by the addition of methanol and degradation products.

22

degradation product included formic acid, acetic acid, propionic acid, butyric acid,

pentanoic acid, n-hexanoic acid, octanoic acid, decanoic acid, and dodecanoic acid. The

first five organic acids were tested only in aqueous MEA solution, and the rest were

tested in aqueous solutions of MEA, DEA, MDEA, and one formulated MDEA. It was

demonstrated that the degradation products caused an increase in both foaming tendency

and foam stability in pure alkanolamine solutions.

In 1996, McCarthy and Trebble carried out a parametric study of a 30 wt%

aqueous DEA solution to investigate the effect of contaminants including methanol,

hexane, corrosion inhibitor, antifoam agent, lubrication oil, organic acids, degradation

products, and suspended solids at temperatures ranging from 20 to 85°C and under

pressures of 0.1-3 MPa (McCarthy and Trebble, 1996). The solutions contained in a

Jerguson high pressure sight glass were purged by air, nitrogen (N2), CO2, and calibrated

ethane (C2H6) gas through a sparger. Results indicated that most contaminants did not

initiate foams in the clean aqueous DEA solution, but rather acted as foam promoters

once the foams already existed in the system. As the temperature and pressure were

increased, foams were enhanced as a result of the reduced surface tension. However, a

further increase in pressure could decrease the amount of foam due to a reduced gas

velocity at a given mass flow rate. This Jerguson apparatus was later used to test the

effects of methanol, hexane, organic acids, and degradation products on the foaming

tendency of a 50 wt% aqueous MDEA solutions at temperatures varying from 24 to 85°C

and pressures vaiying from atmospheric pressure to 500 kPa (Yanicki and Trebble,

2006). Similar results as previously found by McCarthy and Trebble (1996) were

expected. The foaming tendency of the solutions tended to be intensified by heavy

organic acids and worsened by the addition of methanol and degradation products.

22

Increasing temperature and reducing pressure led to an increase in foaming. On the basis

of the DEA and MDEA concentrations typically used in industry, the MDEA solutions

could cause more serious foaming than the DEA solutions (Yanicki and Trebble, 2006).

Later, in 1998, Harruff invented a foam testing apparatus to assess foaming

tendency of an aqueous DGA solution (concentration varied within 35-50 wt%) under

operating conditions of gas treating plants (approximately 93°C and up to 6.9 MPa) by

using N2 gas as a dispersed phase (Harruff, 1998). Foaming tendency of the DGA

solution was lower at a high temperature but slightly affected by pressure variation. To

understand the effect of alkanolamine type, Aguila-Hernandez et al. (2007) employed

their in-house dynamic foam-meter device to measure the foaming behaviour of i)

aqueous solutions of single alkanolamines (i.e., 10-50 wt% DEA and 10-50 wt%

MDEA), ii) aqueous solution of two blended alkanolamines (i.e., 12.5 wt% DEA + 32.5

wt% MDEA), and iii) aqueous solutions of three blended alkanolamines (i.e., 12.5 wt%

DEA + 32.5 wt% MDEA + 2-10 wt% AMP) at different temperatures ranging from 30 to

70°C. These solutions were bubbled by natural gas through a fitted glass disc for ninety

minutes. In general, results showed that increasing the alkanolamine concentration as

well as the temperature would decrease the foaming tendency of the solutions; the

aqueous DEA solutions tended to create more foam than the aqueous MDEA solutions,

and the addition of AMP in the range of 4-10 wt% to the aqueous DEA/MDEA solutions

at temperatures between 30 and 50°C helped decrease foaming.

23

Increasing temperature and reducing pressure led to an increase in foaming. On the basis

of the DEA and MDEA concentrations typically used in industry, the MDEA solutions

could cause more serious foaming than the DEA solutions (Yanicki and Trebble, 2006).

Later, in 1998, Harruff invented a foam testing apparatus to assess foaming

tendency of an aqueous DGA solution (concentration varied within 35-50 wt%) under

operating conditions of gas treating plants (approximately 93°C and up to 6.9 MPa) by

using N2 gas as a dispersed phase (Harruff, 1998). Foaming tendency of the DGA

solution was lower at a high temperature but slightly affected by pressure variation. To

understand the effect of alkanolamine type, Aguila-Hernandez et al. (2007) employed

their in-house dynamic foam-meter device to measure the foaming behaviour of /)

aqueous solutions of single alkanolamines (i.e., 10-50 wt% DEA and 10-50 wt%

MDEA), ii) aqueous solution of two blended alkanolamines (i.e., 12.5 wt% DEA + 32.5

wt% MDEA), and iii) aqueous solutions of three blended alkanolamines (i.e., 12.5 wt%

DEA + 32.5 wt% MDEA + 2-10 wt% AMP) at different temperatures ranging from 30 to

70°C. These solutions were bubbled by natural gas through a fitted glass disc for ninety

minutes. In general, results showed that increasing the alkanolamine concentration as

well as the temperature would decrease the foaming tendency of the solutions; the

aqueous DEA solutions tended to create more foam than the aqueous MDEA solutions,

and the addition of AMP in the range of 4-10 wt% to the aqueous DEA/MDEA solutions

at temperatures between 30 and 50°C helped decrease foaming.

23

Table 1.4 Literature review on foaming in gas absorption processes using aqueous

solutions of alkanolamines

Reference Nature of

work Detail

Ballard, 1966 Technical review

Gas sweetening system (Acid gases/Natural gas stream) • Causes and effects of foaming • Process symptoms • Foaming control methods (antifoam agent) • General procedures to test the antifoam agent and its

quantity

Heisler and Weiss, 1975

Technical Gas sweetening system (Acid gases/Natural gas stream) review • Causes of foaming

• Foaming control methods (antifoam agent: Ocenol dissolved in methylalcohol)

• General procedures to test the antifoam agent and its quantity

Smith, 1979 Technical review

Gas sweetening system (Acid gases/Natural gas stream) • Causes and effects of foaming • Process symptoms • Foaming control methods (antifoam agent and filtration) • Laboratory and field foaming test

Lieberman, 1980

Technical review

Gas sweetening system (Acid gases/Refinery stream) • Causes and effects of foaming • Process symptoms • Foaming control methods

Keaton and Technical Bourke, 1983 review

Gas sweetening system (Acid gases/Refinery stream) • Causes and effects of foaming • Process symptoms • Foaming control methods (carbon filtration)

Thomason, 1985

Technical review

Gas sweetening system (Acid gases/Natural gas stream) • Causes of foaming • Foaming control methods (filtration and solution

reclamation)

Ballard, 1986 Technical Gas sweetening system (Acid gases/Natural gas stream) review • Causes and effects of foaming

• Process symptoms • Foaming control methods • Foaming test

24


solutions of alkanolamines

Reference Nature of

work Detail

Ballard, 1966 Technical review

Gas sweetening system (Acid gases/Natural gas stream) • Causes and effects of foaming • Process symptoms • Foaming control methods (antifoam agent) • General procedures to test the antifoam agent and its

quantity

Heisler and Technical Gas sweetening system (Acid gases/Natural gas stream) Weiss, 1975 review • Causes of foaming

• Foaming control methods (antifoam agent: Ocenol dissolved in methylalcohol)

• General procedures to test the antifoam agent and its quantity

Smith, 1979 Technical Gas sweetening system (Acid gases/Natural gas stream) review • Causes and effects of foaming

• Process symptoms • Foaming control methods (antifoam agent and filtration) • Laboratory and field foaming test

Lieberman, Technical Gas sweetening system (Acid gases/Refinery stream) 1980 review • Causes and effects of foaming

• Process symptoms • Foaming control methods

Keaton and Technical Gas sweetening system (Acid gases/Refinery stream) Bourke, 1983 review • Causes and effects of foaming

• Process symptoms • Foaming control methods (carbon filtration)

Thomason, Technical Gas sweetening system (Acid gases/Natural gas stream) 1985 review • Causes of foaming

• Foaming control methods (filtration and solution reclamation)

Ballard, 1986 Technical Gas sweetening system (Acid gases/Natural gas stream) review • Causes and effects of foaming

• Process symptoms • Foaming control methods • Foaming test

24


solutions of alkanolamines (continued)

Reference Nature of

work Detail

Pauley and Technical Perlmutter, review 1988

Gas sweetening system (Acid gases/Natural gas stream) • Causes and effects of foaming • Foaming control methods (filtration)

Pauley et al., 1989

Experiment Gas sweetening system Condition: atmospheric pressure • Alkanolamine type: MEA, DEA, MDEA and two

formulated MDEA (with non specified additives) • Gas phase: Air • Degradation product: formic acid, acetic acid, propionic

acid, butyric acid, pentanoic acid, n-hexanoic acid, octanoic acid, decanoic acid and dodecanoic acid

• Contaminant: liquid hydrocarbon

Pauley, 1991 Technical review

Gas sweetening system (Acid gases/Gas stream) • Causes and effects of foaming • Foaming control methods (solution monitoring, filtration)

Stewart and Technical Lanning, 1994 review

Gas sweetening system (Acid gases/Gas stream) • Causes of foaming • Process symptoms • Foaming control methods

McCarthy and Experiment Gas sweetening system Trebble, 1996 Condition: 20-85°C, 0.1-3 MPa

• Alkanolamine type: DEA • Gas phase: air, N2, CO2, and calibration gas mixture • Degradation product: Organic acids, 1,4-Bis (2-

hydroxyethyl)piperazine (HEP) and l-(2-hydroxyethyl) piperazine (DEP)

• Additive: antifoam agent and corrosion inhibitor • Contaminant: suspended solids (i.e., iron sulfide, rich amine

filter scrapings, iron oxide) • Other: methanol, hexane, lubrication oil

Harruff, 1998 Experiment Gas sweetening system (Acid gases/Gas stream) Condition: 93°C, up to 6.9 MPa • Alkanolamine type: DGA (plant sample) • Gas phase: N2

25



Reference Nature of work Detail

Pauley and Perlmutter, 1988

Technical review


Pauley et al., 1989

Experiment Gas sweetening system Condition: atmospheric pressure • Alkanolamine type: MEA, DEA, MDEA and two

formulated MDEA (with non specified additives) • Gas phase: Air • Degradation product: formic acid, acetic acid, propionic

acid, butyric acid, pentanoic acid, n-hexanoic acid, octanoic acid, decanoic acid and dodecanoic acid

• Contaminant: liquid hydrocarbon

Pauley, 1991 Technical review

Gas sweetening system (Acid gases/Gas stream) • Causes and effects of foaming • Foaming control methods (solution monitoring, filtration)

Stewart and Lanning, 1994

Technical review

Gas sweetening system (Acid gases/Gas stream) • Causes of foaming • Process symptoms • Foaming control methods

McCarthy and Trebble, 1996

Experiment Gas sweetening system Condition: 20-85°C, 0.1-3 MPa • Alkanolamine type: DEA • Gas phase: air, N2, C02, and calibration gas mixture • Degradation product: Organic acids, 1,4-Bis (2-

hydroxyethyl)piperazine (HEP) and l-(2-hydroxyethyl) piperazine (DEP)

• Additive: antifoam agent and corrosion inhibitor • Contaminant: suspended solids (i.e., iron sulfide, rich amine

filter scrapings, iron oxide) • Other: methanol, hexane, lubrication oil

Harruff, 1998 Experiment Gas sweetening system (Acid gases/Gas stream) Condition: 93°C, up to 6.9 MPa • Alkanolamine type: DGA (plant sample) • Gas phase: N2

25



Reference Nature of

work Detail

Barnes, 1999 Technical review

Syngas production system (CO2/Synthesis gas) • Causes and effects of foaming • Foaming control methods (filtration)

Greg et al., Technical Gas sweetening system (Acid gases/Natural gas stream) 1999 review • Causes and effects of foaming

• Process symptoms • Foaming control methods (the establishment of the

investigation team using a approach of Root Cause Failure Analysis, filtration and antifoam agent)

Abdi et al., Technical Gas sweetening system (Acid gases/Natural gas stream) 2001 review • Causes and effects of foaming

• Foaming control methods (filtration)

Yanicki and Trebble, 2006

Experiment Gas sweetening system Condition: 24-85°C, atmospheric pressure-500 kPa • Alkanolamine type: MDEA • Gas phase: N2, methane and ethane gas • Degradation product: Organic acids, HEP and DEP • Other: methanol and hexane

Aguila- Experiment Gas sweetening system (Acid gases/Natural gas stream) Hernandez et Condition: 30-70°C, atmospheric pressure al., 2007 • Alkanolamine type: DEA, MDEA, DEA+MDEA, DEA

+MDEA+AMP • Gas phase: Natural gas

26



Reference Nature of work Detail

Barnes, 1999 Technical review

Syngas production system (C02/Synthesis gas) • Causes and effects of foaming • Foaming control methods (filtration)

Greg et al., 1999

Technical review

Gas sweetening system (Acid gases/Natural gas stream) • Causes and effects of foaming • Process symptoms • Foaming control methods (the establishment of the

investigation team using a approach of Root Cause Failure Analysis, filtration and antifoam agent)

Abdi et al., 2001

Technical review


Yanicki and Trebble, 2006

Experiment Gas sweetening system Condition: 24-85°C, atmospheric pressure-500 kPa • Alkanolamine type: MDEA • Gas phase: N2, methane and ethane gas • Degradation product: Organic acids, HEP and DEP • Other: methanol and hexane

Aguila-Hernandez et al., 2007

Experiment Gas sweetening system (Acid gases/Natural gas stream) Condition: 30-70°C, atmospheric pressure • Alkanolamine type: DEA, MDEA, DEA+MDEA, DEA

+MDEA+AMP • Gas phase: Natural gas

26

It is apparent from the above reviews that the knowledge of foaming in gas

treating plants is mostly derived from plant experience and is presently limited to

qualitative information. Only a few research studies have been carried out and published

in the literature. The current knowledge is not adequate for the development of cost-

effective preventive and control technologies for foaming in gas treating applications.

Moreover, it is also not advisable to apply this existing knowledge directly to the

foaming problem in alkanolamine-based CO2 absorption processes used for capturing

CO2 from industrial flue gas for the purpose of greenhouse gas emission reduction, or so-

called CO2 capture units. This is mainly due to the difference in the process operating

conditions that can act on the onset of foam differently. For instance, the operating

pressure of the alkanolamine-based acid gas absorption process in a gas treating plant is

relatively high compared to that in a CO2 capture unit. The higher the operating pressure,

the more difficult the foam formation is.

In addition to the above-mentioned concern of using the existing foaming

knowledge obtained from gas treating plants, no reports of plant experiences and no

research studies on foaming are presently available for CO2 capture units since the

application of CO2 capture from flue gas is relatively new and has not been widely

implemented, although, it is anticipated to have widespread use in coming years. These

two limitations, in turn, cause even more scarcity of current foaming knowledge for CO2

capture units used for post-combustion treatment of flue gas in coal-fired power plants.

27

It is apparent from the above reviews that the knowledge of foaming in gas

treating plants is mostly derived from plant experience and is presently limited to

qualitative information. Only a few research studies have been carried out and published

in the literature. The current knowledge is not adequate for the development of cost-

effective preventive and control technologies for foaming in gas treating applications.

Moreover, it is also not advisable to apply this existing knowledge directly to the

foaming problem in alkanolamine-based CO2 absorption processes used for capturing

CO2 from industrial flue gas for the purpose of greenhouse gas emission reduction, or so-

called CO2 capture units. This is mainly due to the difference in the process operating

conditions that can act on the onset of foam differently. For instance, the operating

pressure of the alkanolamine-based acid gas absorption process in a gas treating plant is

relatively high compared to that in a CO2 capture unit. The higher the operating pressure,

the more difficult the foam formation is.

In addition to the above-mentioned concern of using the existing foaming

knowledge obtained from gas treating plants, no reports of plant experiences and no

research studies on foaming are presently available for CO2 capture units since the

application of CO2 capture from flue gas is relatively new and has not been widely

implemented, although, it is anticipated to have widespread use in coming years. These

two limitations, in turn, cause even more scarcity of current foaming knowledge for CO2

capture units used for post-combustion treatment of flue gas in coal-fired power plants.

27

1.5 Research objective

Due to such lack of knowledge, this work aimed at obtaining comprehensive

foaming information from static experiments under well-simulated environments and

understanding foaming behaviour in the absorber where the system's hydrodynamics

play a role in foam formation. The comprehensive objectives of the present work are

listed as below:

• To reveal the parametric effects that have never been studied in previous

research (e.g., CO2 loading, gas flow rate, volume of solution, alkanolamine

concentration, heat stable salts, type of blended alkanolamine, corrosion

inhibitor), reinvestigate the parametric effects that show conflicting results in

previous works (e.g., temperature) for post-combustion flue gas treatment

applications.

• To develop a correlation that predicts pneumatic foam height in terms of

process parameters and physical properties.

• To develop a foam model that has the capacity to predict foam volume and

determine possible foam sites and process conditions that can potentially lead

to foaming in a CO2 absorption process using structured packing.

The obtained knowledge from this work is expected to provide essential

information for the development of cost-effective remedial means of foaming prevention

and control through a determination of possible plant locations and process conditions

potentially facilitating the foaming problem. This allows practitioners to prioritize their

actions effectively to cope with the problem and to estimate the impact of the foaming on

the plant performance. An improvement of plant integrity through prevention of

28

1.5 Research objective

Due to such lack of knowledge, this work aimed at obtaining comprehensive

foaming information from static experiments under well-simulated environments and

understanding foaming behaviour in the absorber where the system's hydrodynamics

play a role in foam formation. The comprehensive objectives of the present work are

listed as below:

• To reveal the parametric effects that have never been studied in previous

research (e.g., CO2 loading, gas flow rate, volume of solution, alkanolamine

concentration, heat stable salts, type of blended alkanolamine, corrosion

inhibitor), reinvestigate the parametric effects that show conflicting results in

previous works (e.g., temperature) for post-combustion flue gas treatment

applications.

• To develop a correlation that predicts pneumatic foam height in terms of

process parameters and physical properties.

• To develop a foam model that has the capacity to predict foam volume and

determine possible foam sites and process conditions that can potentially lead

to foaming in a CO2 absorption process using structured packing.

The obtained knowledge from this work is expected to provide essential

information for the development of cost-effective remedial means of foaming prevention

and control through a determination of possible plant locations and process conditions

potentially facilitating the foaming problem. This allows practitioners to prioritize their

actions effectively to cope with the problem and to estimate the impact of the foaming on

the plant performance. An improvement of plant integrity through prevention of

28

premature flooding due to foaming as well as a reduction of operating costs (e.g., reduced

expenditures on antifoam agent) can be anticipated.

The research involved three parts in order to accomplish the above objectives,

given as follows

Part I: Generation of foaming data for a parametric study

The foaming tendency of aqueous CO2-loaded alkanolamine solutions was tested

by a static foaming experiment modified from a standard ASTM D892 pneumatic method

and was represented by the parameter called a foaminess coefficient (E).

Part II: A development of a pneumatic foam height correlation

The correlation was developed based on the Pilon et al. (2001) correlation with

the integration of several subroutine calculations to estimate the average bubble radius

and physical properties and experimental foaming data obtained from Part I.

Part III: A foam model — development, validation, and simulation

The model was developed based on knowledge of fluid flow pattern,

hydrodynamic parameters, and the mechanism of foam formation, together with the

correlation obtained from Part II. This model was verified by the experimental foam

heights that were observed in a laboratory-scale absorption column fitted with structured

packing. After validation, the model was used to simulate the potential foaming profile

along a pilot-scale absorber.

1.6 Thesis overview

This thesis is divided into seven chapters. Chapter 2 provides the basic principles

of foam theory, Buckingham Pi-Theorem, and a literature review of a correlation used to

predict pneumatic foam height. Chapter 3 contains details of the experimental

29

premature flooding due to foaming as well as a reduction of operating costs (e.g., reduced

expenditures on antifoam agent) can be anticipated.

The research involved three parts in order to accomplish the above objectives,

given as follows

Part I: Generation of foaming data for a parametric study

The foaming tendency of aqueous C02-loaded alkanolamine solutions was tested

by a static foaming experiment modified from a standard ASTM D892 pneumatic method

and was represented by the parameter called a foaminess coefficient (E).

Part II: A development of a pneumatic foam height correlation

The correlation was developed based on the Pilon et al. (2001) correlation with

the integration of several subroutine calculations to estimate the average bubble radius

and physical properties and experimental foaming data obtained from Part I.

Part III: A foam model - development, validation, and simulation

The model was developed based on knowledge of fluid flow pattern,

hydrodynamic parameters, and the mechanism of foam formation, together with the

correlation obtained from Part II. This model was verified by the experimental foam

heights that were observed in a laboratory-scale absorption column fitted with structured

packing. After validation, the model was used to simulate the potential foaming profile

along a pilot-scale absorber.

1.6 Thesis overview

This thesis is divided into seven chapters. Chapter 2 provides the basic principles

of foam theory, Buckingham Pi-Theorem, and a literature review of a correlation used to

predict pneumatic foam height. Chapter 3 contains details of the experimental

29

apparatuses and procedures of both the static and column foaming experiments. In

Chapter 4, the experimental results and discussion of the parametric study on foaming

behaviour are given, while Chapter 5 is devoted to the development of the correlation

from these foaming results for prediction of pneumatic foam height. Chapter 6 solely

involves the development, validation, and simulation of a foam model, as well as an

analysis of foaming impacts on column performance. Finally, Chapter 7 summarizes

conclusions drawn from this work and provides recommendations for future work.

30

apparatuses and procedures of both the static and column foaming experiments. In

Chapter 4, the experimental results and discussion of the parametric study on foaming

behaviour are given, while Chapter 5 is devoted to the development of the correlation

from these foaming results for prediction of pneumatic foam height. Chapter 6 solely

involves the development, validation, and simulation of a foam model, as well as an

analysis of foaming impacts on column performance. Finally, Chapter 7 summarizes

conclusions drawn from this work and provides recommendations for future work.

30

2. THEORY AND LITERATURE REVIEW

This chapter reviews the basic principles of foam including the characteristics of

foam, the typical mechanism of foaming and key factors on foam stability, especially the

Marangoni effect. Details of the Buckingham Pi-theorem are given since this theorem is a

key approach of the dimensional analysis that has been extensively used to develop the

correlations for predicting pneumatic foam height. A literature review on the foam height

correlations developed for both aqueous and non-aqueous systems is also summarized.

2.1 Basic principles of foam

Foam is a colloidal system, which is the agglomeration of closed gas bubbles

(dispersed or discontinuous phase) being dispersed in a liquid (continuous phase). Each

bubble is separated by a thin liquid film called a lamella. Foam is considered a

compressible fluid since a major portion of foam (greater than 75 percent) is gas, and its

physical properties, particularly density, demonstrate compressible characteristics

(Walstra, 1989). Foams can be classified into two types of foams (i.e., Kugelschaum

(sphere foam) and Polyederschaum (polyhedral foam)). The Kugelschaum is usually

composed of large amounts of liquid or high liquid fraction. As a result, the thickness of

the lamella between the gas bubbles is approximately equal to the diameter of the gas

bubbles. Kugelschaum is typically located next to the liquid surface. As the liquid

fraction becomes smaller, the Kugelschaum turns to Polyederschaum, which is typically

located between the Kugelschaum and the gas phase. This is because the amount of

liquid in the lamella is decreased due to drainage. Therefore, the Polyederschaum is more

vulnerable than the Kugelschaum and subject to foam coalescence and rupture.

31

2. THEORY AND LITERATURE REVIEW

This chapter reviews the basic principles of foam including the characteristics of

foam, the typical mechanism of foaming and key factors on foam stability, especially the

Marangoni effect. Details of the Buckingham Pi-theorem are given since this theorem is a

key approach of the dimensional analysis that has been extensively used to develop the

correlations for predicting pneumatic foam height. A literature review on the foam height

correlations developed for both aqueous and non-aqueous systems is also summarized.

2.1 Basic principles of foam

Foam is a colloidal system, which is the agglomeration of closed gas bubbles

(dispersed or discontinuous phase) being dispersed in a liquid (continuous phase). Each

bubble is separated by a thin liquid film called a lamella. Foam is considered a

compressible fluid since a major portion of foam (greater than 75 percent) is gas, and its

physical properties, particularly density, demonstrate compressible characteristics

(Walstra, 1989). Foams can be classified into two types of foams (i.e., Kugelschaum

(sphere foam) and Polyederschaum (polyhedral foam)). The Kugelschaum is usually

composed of large amounts of liquid or high liquid fraction. As a result, the thickness of

the lamella between the gas bubbles is approximately equal to the diameter of the gas

bubbles. Kugelschaum is typically located next to the liquid surface. As the liquid

fraction becomes smaller, the Kugelschaum turns to Polyederschaum, which is typically

located between the Kugelschaum and the gas phase. This is because the amount of

liquid in the lamella is decreased due to drainage. Therefore, the Polyederschaum is more

vulnerable than the Kugelschaum and subject to foam coalescence and rupture.

31

As illustrated in Figure 2.1, these two different morphologies of foam can be

distinguished by a gas fraction (6)-) or a liquid fraction (1-q). In general, Walstra (1989)

and Thiele et al. (2003) both proposed that the Kugelschaum occurs when the gas

fraction is about 0.5 and then it will deviate to Polyederschaum when the gas fraction is

about 0.75. Hartland (2004) used the liquid fraction to determine the foam morphology

and stated that foam with at least 25 percent liquid, or at most 75 percent gas (ef < 0.75),

is categorized as Kugelschaum. This implies that the deviation of Kugelschaum to

Polyederschaum starts when the foam is composed of a gas ratio greater than 75 percent

(ef > 0.75), and a complete transformation will occur when the percent of liquid in foam

is reduced to less than 2 percent or more than 98 percent gas (6y> 0.98).

32

As illustrated in Figure 2.1, these two different morphologies of foam can be

distinguished by a gas fraction (sj) or a liquid fraction In general, Walstra (1989)

and Thiele et al. (2003) both proposed that the Kugelschaum occurs when the gas

fraction is about 0.5 and then it will deviate to Polyederschaum when the gas fraction is

about 0.75. Hartland (2004) used the liquid fraction to determine the foam morphology

and stated that foam with at least 25 percent liquid, or at most 75 percent gas (£/< 0.75),

is categorized as Kugelschaum. This implies that the deviation of Kugelschaum to

Polyederschaum starts when the foam is composed of a gas ratio greater than 75 percent

(£/> 0.75), and a complete transformation will occur when the percent of liquid in foam

is reduced to less than 2 percent or more than 98 percent gas (s/> 0.98).

32

Dispersing gas

Polyederschaum

Kugelschaum

Gas dispersion

Plateau border

Lamella (Thin liquid film)

Researcher

Colloidal system

Foam

Polyederschaum Kugelschaum gas dispersion

Walstra, 1989 e1 >0.75 0.75 ? ef? 0.5

Thiele et al., 2003 ef> 0.74 0.74 ? ef> 0.52 ei- < 0.52

Hartland, 2004 q> 0.75 0.75 ? of

Figure 2.1 Characterization of foam morphology based on the gas fraction criteria

(redrawn from Schramm (1994) and Thiele et al. (2003))

33

Dispersing gas

Air

Plateau border

Polyederschaum <

Gas Lamella

(Thin liquid film) Kugelschaum {

Gas dispersion

Colloidal system

Researcher Foam gas dispersion

Polyederschaum Kugelschaum gas dispersion

Walstra, 1989 %> 0.75 0.75 > Sf> 0.5 -

Thiele et al., 2003 £f> 0.74 0.74 > £f> 0.52 ^r<0.52

Hartland, 2004 %> 0.75 0.75 > ef -

Figure 2.1 Characterization of foam morphology based on the gas fraction criteria

(redrawn from Schramm (1994) and Thiele et al. (2003))

33

2.1.1 Foam mechanism

Foam formation, drainage, coalescence, and collapse are primary mechanisms

applied to all types of foam. In order to form a foam, gas (dispersed phase) is purged and

mixed into liquid (continuous phase) through a diffuser or an orifice. Buoyancy force and

surface force are two important forces for foam formation. Bubbles from the diffuser are

lifted up through bulk liquid by the buoyancy force calculated by the equation shown

below:

FB = Apribubg (2.1)

where FB is the buoyancy force (N), iXp is a difference between liquid and gas density

(kg/m3), g is gravitational acceleration (m/s2), and Vbub is bubble volume (m3). The

buoyancy force must overcome the force due to the surface tension of liquid solution

expressed by the following equation in order for the bubble to detach from the diffuser.

F 71s

— — 106

(2.2)

where Fs is the surface tension force (N), y is surface tension (mN/m), and 1 is capillary

perimeter (mm).

From Equation (2.2), the surface tension is mainly responsible for the foaming

tendency of a solution. Nonpolar solutions (e.g., hydrocarbon solutions) or solutions with

weak intermolecular bonding (a small amount of hydrogen bonding) tend to have a lower

surface tension than polar solutions or solutions with strong intermolecular bonding (a

large amount of hydrogen bonding). Therefore, the foaming tendency of the former

solutions is higher than the latter since the buoyancy force can easily overcome the

surface tension force. In the case of turbulence, shearing force becomes a key force, in

addition to the buoyancy force, to disengage bubbles.

34

2.1.1 Foam mechanism

Foam formation, drainage, coalescence, and collapse are primary mechanisms

applied to all types of foam. In order to form a foam, gas (dispersed phase) is purged and

mixed into liquid (continuous phase) through a diffuser or an orifice. Buoyancy force and

surface force are two important forces for foam formation. Bubbles from the diffuser are

lifted up through bulk liquid by the buoyancy force calculated by the equation shown

below:

FB=Apvt>ubg (2-1)

where FB is the buoyancy force (N), Ap is a difference between liquid and gas density

(kg/m3), g is gravitational acceleration (m/s2), and Vbuh is bubble volume (m3). The

buoyancy force must overcome the force due to the surface tension of liquid solution

expressed by the following equation in order for the bubble to detach from the diffuser.

Fs=A- (2-2) s 10

where Fs is the surface tension force (N), y is surface tension (mN/m), and / is capillary

perimeter (mm).

From Equation (2.2), the surface tension is mainly responsible for the foaming

tendency of a solution. Nonpolar solutions (e.g., hydrocarbon solutions) or solutions with

weak intermolecular bonding (a small amount of hydrogen bonding) tend to have a lower

surface tension than polar solutions or solutions with strong intermolecular bonding (a

large amount of hydrogen bonding). Therefore, the foaming tendency of the former

solutions is higher than the latter since the buoyancy force can easily overcome the

surface tension force. In the case of turbulence, shearing force becomes a key force, in

addition to the buoyancy force, to disengage bubbles.

34

When three or more bubbles adjoin, a Plateau border (PB) is formed by concaving

three lamellae to bubbles with an angle of 120°, as illustrated in Figure 2.1 (page 33). It is

also possible that an angle decreases to 109° when four bubbles meet at the PB (Hartland,

2004). As a result, a polyhedral or honeycomb network of bubbles is formed and allows

liquid to flow around this complicatedly interconnected PB structure. At this stage,

disproportionation or Ostwald ripening can be observed from the dissolution of smaller

bubbles into bigger ones, which results in an increase in size. After the lamella

rearrangement, surface tension naturally creates a pressure gradient of the pressure inside

(concaved side) and outside (convex side) the bubble. Such a pressure gradient is

commonly called capillary pressure (Pa, N/m2) and can be predicted by the Laplace

equation given below:

( 1 1_____+—\ R1 R2

(2.3)

where Riand R2 are the principal radii of curvature (mm).

An increase in the capillary force causes a liquid to flow from the lamella to the

PBs (so-called a capillary flow or Laplace flow) and, thus, leads to thin lamella thickness

and foam rupture. The change in the principal radii of curvature due to bubble

deformation accelerates the foam drainage since it increases the capillary force. This

force also indicates an external stress, a product of velocity gradient and viscosity, that

must be applied to a bigger bubble for breakage into smaller ones (Walstra, 1989).

Besides capillary force, drainage can be caused by gravitational force.

In summary, once gas is bubbled through liquid, foam is formed in the system and

simultaneously undergoes the thinning process caused by drainage, foam coalescence,

and foam rupture.

35

When three or more bubbles adjoin, a Plateau border (PB) is formed by concaving

three lamellae to bubbles with an angle of 120°, as illustrated in Figure 2.1 (page 33). It is

also possible that an angle decreases to 109° when four bubbles meet at the PB (Hartland,

2004). As a result, a polyhedral or honeycomb network of bubbles is formed and allows

liquid to flow around this complicatedly interconnected PB structure. At this stage,

disproportionation or Ostwald ripening can be observed from the dissolution of smaller

bubbles into bigger ones, which results in an increase in size. After the lamella

rearrangement, surface tension naturally creates a pressure gradient of the pressure inside

(concaved side) and outside (convex side) the bubble. Such a pressure gradient is

commonly called capillary pressure (Pc, N/m2) and can be predicted by the Laplace

equation given below:

f \ i N (2.3)

Rx R2

where i?/and iJâre the principal radii of curvature (mm).

An increase in the capillary force causes a liquid to flow from the lamella to the

PBs (so-called a capillary flow or Laplace flow) and, thus, leads to thin lamella thickness

and foam rupture. The change in the principal radii of curvature due to bubble

deformation accelerates the foam drainage since it increases the capillary force. This

force also indicates an external stress, a product of velocity gradient and viscosity, that

must be applied to a bigger bubble for breakage into smaller ones (Walstra, 1989).

Besides capillary force, drainage can be caused by gravitational force.

In summary, once gas is bubbled through liquid, foam is formed in the system and

simultaneously undergoes the thinning process caused by drainage, foam coalescence,

and foam rupture.

35

2.1.2 Foam stability

By nature, foams are subject to three main instabilities (i.e., thinning, coalescence

and rupture processes). Such instabilities lead to a decrease in their surface area and

consequently surface free energy (Thiele et al., 2003). It is an opposite characteristic to

foam stability affected by surface elasticity, Marangoni effect (see section 2.1.3), surface

viscosity, and bulk viscosity, repulsive coulombic forces, and gravitational force. Surface

elasticity (E) is the ability of a surface to resist a thinning process due to a surface tension

gradient. It is defined as a change in surface tension with respect to a change in surface

area (A5) as given below:

E = 2As(dy/ dAs) (2.4)

During dispersion, a surface tension gradient between a stretched and a non-

stretched area of surfactant-adsorbed surfaces is created as the surface is exposed to rapid

expansion and shrinkage. At this point, the surface elasticity is responsible for balancing

this gradient by using viscous forces to induce the underlying liquid to flow from the

non-stretched area to the stretched area as a result of self-contraction of surfaces.

Consequently, the stretched area is thickened and foam stability is enhanced (Rosen,

1989; Schramm, 1994; Morrison and Ross, 2002). The phenomenon that the surface

tension gradient causes a liquid flow in the lamella is the so-called Marangoni effect.

Bulk viscosity and surface viscosity also play a role in foam stability. Bulk

viscosity is the liquid viscosity in a bulk liquid phase while surface viscosity is the liquid

viscosity at the interface between the gas bubble and liquid in the lamella. The surface

viscosity is usually higher than bulk viscosity and is also increased according to an

increase in bulk viscosity. In general, high bulk viscosity is favourable since it will slow

down the drainage due to gravitational force. However, the increase in bulk viscosity can

36

2.1.2 Foam stability

By nature, foams are subject to three main instabilities (i.e., thinning, coalescence

and rupture processes). Such instabilities lead to a decrease in their surface area and

consequently surface free energy (Thiele et al., 2003). It is an opposite characteristic to

foam stability affected by surface elasticity, Marangoni effect (see section 2.1.3), surface

viscosity, and bulk viscosity, repulsive coulombic forces, and gravitational force. Surface

elasticity (E) is the ability of a surface to resist a thinning process due to a surface tension

gradient. It is defined as a change in surface tension with respect to a change in surface

area (As) as given below:

E=2A\dy/dAs) (2.4)

During dispersion, a surface tension gradient between a stretched and a non-

stretched area of surfactant-adsorbed surfaces is created as the surface is exposed to rapid

expansion and shrinkage. At this point, the surface elasticity is responsible for balancing

this gradient by using viscous forces to induce the underlying liquid to flow from the

non-stretched area to the stretched area as a result of self-contraction of surfaces.

Consequently, the stretched area is thickened and foam stability is enhanced (Rosen,

1989; Schramm, 1994; Morrison and Ross, 2002). The phenomenon that the surface

tension gradient causes a liquid flow in the lamella is the so-called Marangoni effect.

Bulk viscosity and surface viscosity also play a role in foam stability. Bulk

viscosity is the liquid viscosity in a bulk liquid phase while surface viscosity is the liquid

viscosity at the interface between the gas bubble and liquid in the lamella. The surface

viscosity is usually higher than bulk viscosity and is also increased according to an

increase in bulk viscosity. In general, high bulk viscosity is favourable since it will slow

down the drainage due to gravitational force. However, the increase in bulk viscosity can

36

lead to a very high surface viscosity and eventually destroy surface elasticity. This is

because surface films cannot be easily moved with only a small amount of external stress

and become like a solid at a high surface viscosity, which in turn, causes foam stability to

decrease. In addition, other external forces also have an impact on the foam stability. The

repulsive Coulombic forces typically slow down the gravity drainage, while the

gravitational force does the opposite (Pauley et al., 1989).

2.1.3 Marangoni effect

The Marangoni effect was discovered by Carlo Marangoni in 1865. It explains the

phenomenon in which the surface tension gradients (Ay) cause a mass transfer or liquid

flow in a liquid layer. It is simply illustrated in Figure 2.2. A quick expansion of a

surfactant-stabilized film creates two regions, an expanded region and an unexpanded

region. The expanded region has a higher surface tension than the unexpanded region

since the amount of surfactant being adsorbed in the expanded region is less than that in

the unexpanded region. In order to balance this surface tension gradient, the surface layer

naturally contracts itself, which consequently induces the liquid to flow from a lower

surface tension region to a higher surface tension region due to viscous forces. The

Marangoni effect also requires a certain period of time in order to properly function

(Bikerman, 1973). Thus, it is necessary to maintain the surface tension gradient so that

the bulk liquid can flow into the lamella. A velocity gradient of a liquid flow also causes

a surface tension gradient since the flow will move some surfactants away from an

upstream region to a downstream region. Therefore, the surface tension of the

downstream region is lower than that of the upstream region (Walstra, 1989).

37

lead to a very high surface viscosity and eventually destroy surface elasticity. This is

because surface films cannot be easily moved with only a small amount of external stress

and become like a solid at a high surface viscosity, which in turn, causes foam stability to

decrease. In addition, other external forces also have an impact on the foam stability. The

repulsive Coulombic forces typically slow down the gravity drainage, while the

gravitational force does the opposite (Pauley et al., 1989).

2.1.3 Marangoni effect

The Marangoni effect was discovered by Carlo Marangoni in 1865. It explains the

phenomenon in which the surface tension gradients (Ay) cause a mass transfer or liquid

flow in a liquid layer. It is simply illustrated in Figure 2.2. A quick expansion of a

surfactant-stabilized film creates two regions, an expanded region and an unexpanded

region. The expanded region has a higher surface tension than the unexpanded region

since the amount of surfactant being adsorbed in the expanded region is less than that in

the unexpanded region. In order to balance this surface tension gradient, the surface layer

naturally contracts itself, which consequently induces the liquid to flow from a lower

surface tension region to a higher surface tension region due to viscous forces. The

Marangoni effect also requires a certain period of time in order to properly function

(Bikerman, 1973). Thus, it is necessary to maintain the surface tension gradient so that

the bulk liquid can flow into the lamella. A velocity gradient of a liquid flow also causes

a surface tension gradient since the flow will move some surfactants away from an

upstream region to a downstream region. Therefore, the surface tension of the

downstream region is lower than that of the upstream region (Walstra, 1989).

37

The classic example of the Marangoni effect is tears of wine in a glass. Wine is

mainly composed of water and alcohol. The surface tension of the region with a higher

water content (or a lower alcohol content) is higher than that with a lower water content

(or a higher alcohol content) since the surface tension of water is higher than that of

alcohol. As wine starts to form a film on the glass, alcohol tends to be evapourated faster

than water due to the lower vapour pressure, which causes the surface tension of the film

to increase locally and consequently induces the liquid flow from the region that has a

higher alcohol content to form a drop on the glass (Adamson, 1967). The Marangoni

effect plays an important role in film/foam stability as the restoring force against the

thinning process (Schramm, 1994; Rosen, 1989; Morrison and Ross, 2002).

38

The classic example of the Marangoni effect is tears of wine in a glass. Wine is

mainly composed of water and alcohol. The surface tension of the region with a higher

water content (or a lower alcohol content) is higher than that with a lower water content

(or a higher alcohol content) since the surface tension of water is higher than that of

alcohol. As wine starts to form a film on the glass, alcohol tends to be evapourated faster

than water due to the lower vapour pressure, which causes the surface tension of the film

to increase locally and consequently induces the liquid flow from the region that has a

higher alcohol content to form a drop on the glass (Adamson, 1967). The Marangoni

effect plays an important role in film/foam stability as the restoring force against the

thinning process (Schramm, 1994; Rosen, 1989; Morrison and Ross, 2002).

38

Liquid Before expansion

4sMAY4.4:44:44.:444.44444:4:4

After expansion

Figure 2.2 Marangoni effect in the surfactant-stabilized film (Schramm, 1994)

39

Liquid

Gas bubble

Lame a

Before expansion

m * f r fs&~ 4 " •S> w> N> *QP 6 c*

ja£U3Yt««W2«xi£U2!£LQCfcQiCLDlX2£LQS[Xltt y y y y v y v v v y i y y y y y y y y y y y y y

After expansion

iife UWHt

H i ' ? I J \ftow

Liquid

Figure 2.2 Marangoni effect in the surfactant-stabilized film (Schramm, 1994)

39

2.2 Buckingham Pi-theorem

The Buckingham Pi-theorem established by Buckingham in 1914 has been well-

recognized as a fundamental theorem in dimensional analysis (Buckingham, 1914). It

involves establishment of a mathematical procedure to obtain a series of dimensionless

parameters from a certain number of physical variables describing a physical system or

phenomenon of interest. With the assumption of having all the ratios of the physical

variables constant, the physical phenomenon can be described as:

AQ/, Q2, • • •, Qn) = 0 (2.5)

where Q is the physical variable(s). The dimensionless parameter (1l) is defined as:

II nl val n2a2

— vn nan

v (2.6)

where al, a2, a„ are the exponents of each physical variable that must satisfy the

principle of dimensional homogeneity. As a result, the physical system is alternatively

expressed as a function of the dimensionless parameters as shown in the following

expression:

F(11, n2,..., fl ) = 0 (2.7)

The value of i must be determined since it represents the total number of dimensional

parameters that can be constructed from the original physical variables (Q1, Q2, • • •, Qn).

All the physical variables that are significant and influential to a specific system must

also be identified. The following are calculation steps to define each dimensionless

parameter:

(i) Breakdown the unit of all physical variables into fundamental units (e.g.,

mass, length, time, and temperature). The unit of each physical variable in

40

2.2 Buckingham Pi-theorem

The Buckingham Pi-theorem established by Buckingham in 1914 has been well-

recognized as a fundamental theorem in dimensional analysis (Buckingham, 1914). It

involves establishment of a mathematical procedure to obtain a series of dimensionless

parameters from a certain number of physical variables describing a physical system or

phenomenon of interest. With the assumption of having all the ratios of the physical

variables constant, the physical phenomenon can be described as:

AQi,Q2,...,Qn) = 0 (2.5)

where Q is the physical variable(s). The dimensionless parameter (IT) is defined as:

n = Q?Qp...QZ" (2.6)

where a/, 02, ..., a„ are the exponents of each physical variable that must satisfy the

principle of dimensional homogeneity. As a result, the physical system is alternatively

expressed as a function of the dimensionless parameters as shown in the following

expression:

F(n,,n2,...,110 = 0 (2.7)

The value of / must be determined since it represents the total number of dimensional

parameters that can be constructed from the original physical variables (Qi, Q2, ..., Qn).

All the physical variables that are significant and influential to a specific system must

also be identified. The following are calculation steps to define each dimensionless

parameter:

(i) Breakdown the unit of all physical variables into fundamental units (e.g.,

mass, length, time, and temperature). The unit of each physical variable in

40

Equation (2.6) could be either fundamental or derived (e.g., pascal, watt, cP,

etc.).

(ii) Determine the number of dimensional parameters (i) by

i = n k (2.8)

where n is the number of physical variables and k is the total number of

fundamental units needed to express the system.

(iii) Select k (out of n) physical variables (Qi, Q2,..., Qk) arbitrarily that have the

fundamental units as the basis for III, I12,...,

(iv) Incorporate one of the remaining physical variables (Qic+1, 0+2,- • •, Qn),

which mainly have derived units, into a set of k physical variables as

mentioned in Step (iii). This additional physical variable is defined as Si, S2,

S,. Then, the general form can be represented by:

[nii = [010..-QPsil [ll 2 = [Q1a2 Q: 2 S 2

• • • [nil= [Q,-Q2'...Qk'SrI

(2.9)

(v) Replace the unit of Q's and S by the fundamental units.

(vi) Find the values of all the exponents a, b, . . k for each dimensionless

parameter, which must eliminate all the fundamental units.

2.3 Literature review on the correlation of the pneumatic foam height

2.3.1 Application of Buckingham Pi-theorem

Several foaming semi-empirical equations have been extensively developed for

slag foaming systems using the Buckingham Pi-theorem. Ito and Fruehan (1989a and

41

Equation (2.6) could be either fundamental or derived (e.g., pascal, watt, cP,

etc.).

(ii) Determine the number of dimensional parameters (/') by

i = n-k (2.8)

where n is the number of physical variables and k is the total number of

fundamental units needed to express the system.

(iii) Select k (out of n) physical variables (Qi, 02,..., Qk) arbitrarily that have the

fundamental units as the basis for II|, it2,..., rij.

(iv) Incorporate one of the remaining physical variables (Qk+i, Qk+2Q»),

which mainly have derived units, into a set of k physical variables as

mentioned in Step (iii). This additional physical variable is defined as Si, S2,

Si. Then, the general form can be represented by:

[n,]=

[nj= jape? -a'-Sj] (2.9)

[n,]=[er &'...&*•s,]

(v) Replace the unit of Q's and S by the fundamental units.

(vi) Find the values of all the exponents a, b,..., k for each dimensionless

parameter, which must eliminate all the fundamental units.

23 Literature review on the correlation of the pneumatic foam height

2.3.1 Application of Buckingham Pi-theorem

Several foaming semi-empirical equations have been extensively developed for

slag foaming systems using the Buckingham Pi-theorem. Ito and Fruehan (1989a and

41

1989b) were the first to propose an empirical equation to predict a foaminess coefficient

for the CaO-SiO2-FeO with FeO content of 10-60 wt% at 1250-1400°C.

E=570 /4 Y slag P slag

(2.10)

where E is the foaminess coefficient (s) defined by Bikerman (1938 and 1973), ,u slag is

the slag viscosity (Pas), Ps/ag is the slag density (kg/m3), and ',wag is the slag surface

tension (N/m). From the equation, it was obvious that E was a strong function of

viscosity, which played a role in foam stability through deceleration of liquid drainage

from lamella in the foam, and E was inversely proportional to the square root of both

surface tension and density. This equation was expected to predict the slag foam

occurring in iron and steelmaking processes including oxygen steelmaking, electric

furnace steelmaking, and bath smelting. In 1991, Jiang and Fruehan extended Ito and

Fruehan's work to cover a lower range of FeO content of about 5 wt% at a higher

temperature of 1500°C, and they used more reliable methods to predict physical

properties (Jiang and Fruehan, 1991). They proposed an improved empirical equation,

shown below, which yielded higher accuracy in predicting E for the CaO-SiO2-FeO

system:

E = 115 slag Y slag P slag

(2.11)

This equation was later applied to predict foaming occurring in industrial bath smelting

processes without the presence of coke.

Zhang and Fruehan (1995) were the first to incorporate bubble diameter into foam

height correlation to account for the fact that foam morphology, one of the most

important parameters in foam stability, can be varied from sphere foam formed by small

42

1989b) were the first to propose an empirical equation to predict a foaminess coefficient

for the CaO-SiCh-FeO with FeO content of 10-60 wt% at 1250-1400°C.

£ = 570 . ^'ag (2.10) \ /slag r slag

where Z is the foaminess coefficient (s) defined by Bikerman (1938 and 1973), jusiag is

the slag viscosity (Pas), psiag is the slag density (kg/m3), and ystag is the slag surface

tension (N/m). From the equation, it was obvious that Z was a strong function of

viscosity, which played a role in foam stability through deceleration of liquid drainage

from lamella in the foam, and Z was inversely proportional to the square root of both

surface tension and density. This equation was expected to predict the slag foam

occurring in iron and steelmaking processes including oxygen steelmaking, electric

furnace steelmaking, and bath smelting. In 1991, Jiang and Fruehan extended Ito and

Fruehan's work to cover a lower range of FeO content of about 5 wt% at a higher

temperature of 1500°C, and they used more reliable methods to predict physical

properties (Jiang and Fruehan, 1991). They proposed an improved empirical equation,

shown below, which yielded higher accuracy in predicting Z for the Ca0-Si02-Fe0

system:

£ = 115 (2.11) y Yslag P stag

This equation was later applied to predict foaming occurring in industrial bath smelting

processes without the presence of coke.

Zhang and Fruehan (1995) were the first to incorporate bubble diameter into foam

height correlation to account for the fact that foam morphology, one of the most

important parameters in foam stability, can be varied from sphere foam formed by small

42

spherical bubbles to polyhedral foam composed of relatively large polyhedral bubbles

(Bikerman, 1938 and 1973). The bubble size was not accounted for in previous studies

(Equations 2.10-2.11) due to the small variation in bubble diameter of the foams

observed in their studies. Zhang and Fruehan developed the following correlation using

the bubble diameter as one of the independent parameters besides the physical properties

for a CaO-SiO2-FeO-A120 3 system with FeO content of 5-15 wt% at 1500°C:

.2 4" slag

E= 115 v 02 nsla g slag—

d av" e

(2.12)

where dare is the average bubble diameter (m). The model showed that E strongly

depended on viscosity; was inversely proportional to density and bubble diameter with

powers of -1.0 and -0.9, respectively; and was a weak function of surface tension. In

2000, Jung and Fruehan verified the above correlation (Equation (2.12)) by using it to

calculate E of the slag foaming for a CaO-SiO2-FeO-MgO system with a higher FeO

content of 10-32 wt% at 1400-1550°C. Although the predicted E was somewhat lower

than the experimental E due to the error from the prediction of liquid viscosity, this

correlation was still considered to adequately predict the foaming that occurred in this

particular system (Jung and Fruehan, 2000).

By performing dimensional analysis on their experimental results (Ghag et al.,

1998a), Ghag and his team recommended three different correlations for predicting E (s)

for an aqueous solution of glycerol containing a surfactant, sodium dodecylbenzene

sulphonate (SDBS), at 20°C (Ghag et al., 1998b):

A71.32E = 2.02 x106 /4/ 2.32 3.64 (2.13)

43

spherical bubbles to polyhedral foam composed of relatively large polyhedral bubbles

(Bikerman, 1938 and 1973). The bubble size was not accounted for in previous studies

(Equations 2.10-2.11) due to the small variation in bubble diameter of the foams

observed in their studies. Zhang and Fruehan developed the following correlation using

the bubble diameter as one of the independent parameters besides the physical properties

for a Ca0-SiC>2-Fe0-Al203 system with FeO content of 5-15 wt% at 1500°C:

(2-12) / stag r slag ave

where dme is the average bubble diameter (m). The model showed that X strongly

depended on viscosity; was inversely proportional to density and bubble diameter with

powers of -1.0 and -0.9, respectively; and was a weak function of surface tension. In

2000, Jung and Fruehan verified the above correlation (Equation (2.12)) by using it to

calculate X of the slag foaming for a Ca0-Si02-Fe0-Mg0 system with a higher FeO

content of 10-32 wt% at 1400-1550°C. Although the predicted X was somewhat lower

than the experimental X due to the error from the prediction of liquid viscosity, this

correlation was still considered to adequately predict the foaming that occurred in this

particular system (Jung and Fruehan, 2000).

By performing dimensional analysis on their experimental results (Ghag et al.,

1998a), Ghag and his team recommended three different correlations for predicting X (s)

for an aqueous solution of glycerol containing a surfactant, sodium dodecylbenzene

sulphonate (SDBS), at 20°C (Ghag et al., 1998b):

X = 2.02 x10V; ( Ayi 32 ^ , „ \ 2.32 >3.64 (PLS) d ,

(2.13)

43

E°89 E=5.43x105PL (pLes9d278

E=1.00x106 pi ( Eeff 3 (pLg)d

(2.14)

(2.15)

where d is the bubble diameter (mm), PL is liquid viscosity (Pa's), PL is liquid density

(kg/m3), Ay is the surface tension depression equal to the difference between surface

tension of aqueous solution of glycerol with and without the SDBS (mN/m), EM is the

Marangoni dilational modulus (mN/m), which is the maximum surface elasticity of the

surface film, and Eeff is the effective elasticity (mN/m), which represents the true surface

elasticity. They suggested that E would depend on the surface tension depression in

Equation (2.13), the Marangoni dilational modulus in Equation (2.14), and the effective

elasticity in Equation (2.15) rather than the equilibrium surface tension, as previously

considered by Ito and Fruehan (1989b), Jiang and Fruehan (1991), and Zhang and

Fruehan (1995), since these properties better reflected the effect of viscoelastic forces on

foam stablity, which was induced by a variation in surface tension of the solution due to

the addition of surfactant. From the above correlations, they concluded that bubble size

had the greatest impact on the foam height, and Equation (2.15) best fitted with the

experimental data since a use of effective elasticity could naturalistically estimate the

degree of stability affected by the dynamic adsorption of surfactant. In 1998, Ghag et al.

(1998c) employed the experimental E of the slag foaming in the CaO-SiO2-FeO system

from Zhang and Fruehan (1995) to test the application of Equation (2.15) for a wider

range of physical properties and industrial practices. The results showed that the

predicted values did not show good agreement with the experimental data (Ghag et al.,

44

S = 5.43xl0Vi /

(2.14) (j>LgyMd 1.89 *2.78

V

(2.15)

where d is the bubble diameter (mm), /4 is liquid viscosity (Pa s), pi is liquid density

(kg/m3), Ay is the surface tension depression equal to the difference between surface

tension of aqueous solution of glycerol with and without the SDBS (mN/m), EM is the

Marangoni dilational modulus (mN/m), which is the maximum surface elasticity of the

surface film, and Eeff is the effective elasticity (mN/m), which represents the true surface

elasticity. They suggested that X would depend on the surface tension depression in

Equation (2.13), the Marangoni dilational modulus in Equation (2.14), and the effective

elasticity in Equation (2.15) rather than the equilibrium surface tension, as previously

considered by Ito and Fruehan (1989b), Jiang and Fruehan (1991), and Zhang and

Fruehan (1995), since these properties better reflected the effect of viscoelastic forces on

foam stablity, which was induced by a variation in surface tension of the solution due to

the addition of surfactant. From the above correlations, they concluded that bubble size

had the greatest impact on the foam height, and Equation (2.15) best fitted with the

experimental data since a use of effective elasticity could naturalistically estimate the

degree of stability affected by the dynamic adsorption of surfactant. In 1998, Ghag et al.

(1998c) employed the experimental Z of the slag foaming in the CaO-SiCVFeO system

from Zhang and Fruehan (1995) to test the application of Equation (2.15) for a wider

range of physical properties and industrial practices. The results showed that the

predicted values did not show good agreement with the experimental data (Ghag et al.,

44

1998c). In addition, it was difficult to measure these substituted physical properties by

simple techniques in order to use or validate their correlations.

Unlike the previous works, which applied dimensional analysis with an

application of the Buckingham-Pi theorem to a set of significant physical properties upon

which E depended, Pilon and his colleagues performed the analysis using the governing

equation of the foam layer proposed by Bhakta and Ruckenstein (1997) and presented the

following semi-empirical equation to predict the pneumatic steady-state foam height (H,

mm) under isothermal conditions (Pilon et al., 2001):

Ca(-1= Kr Rer

r L Fr ) (2.16)

where Re is the Reynolds number defined as PAO - Gm Kik, Fr is the Froude number

defined as (G — Gm )2/gr, Ca is the capillary number defined as it/JO - 6„, )1y, G is the

superficial gas velocity (mm/s), Gm is the minimum superficial gas velocity for the onset

of foaming (mm/s), r is the average bubble radius in the foam (mm), and K and N are the

adjustable parameters for a power-law relationship between two dimensionless groups

(i.e., lii = Ca(H/r) and U2 = Re/Fr), which in this case were 2905 and -1.80, respectively.

Consequently, the final correlation was written as:

H 2905 r 2r 6 0( [,UL (G -61'1

(Pa)(2.17)

This correlation was validated by foaming data available in the literature for a

high viscosity system with different types of dispersing gases (i.e., argon, air, N2, helium

and hydrogen) and diffusers (i.e., single and multiple orifice and Pyrex disk). It was

proven to be applicable to various systems with a broad range of physical properties (46

45

1998c). In addition, it was difficult to measure these substituted physical properties by

simple techniques in order to use or validate their correlations.

Unlike the previous works, which applied dimensional analysis with an

application of the Buckingham-Pi theorem to a set of significant physical properties upon

which X depended, Pilon and his colleagues performed the analysis using the governing

equation of the foam layer proposed by Bhakta and Ruckenstein (1997) and presented the

following semi-empirical equation to predict the pneumatic steady-state foam height (H,

mm) under isothermal conditions (Pilon et al., 2001):

where Re is the Reynolds number defined as pi{ G - Gm )r/jUL, Fr is the Froude number

defined as (G - Gm )2/gr, Ca is the capillary number defined as ML(G - Gm )!y, G is the

superficial gas velocity (mm/s), Gm is the minimum superficial gas velocity for the onset

of foaming (mm/s), r is the average bubble radius in the foam (mm), and K and N are the

adjustable parameters for a power-law relationship between two dimensionless groups

(i.e., Ill = Ca(H/r) and rh = Re/Fr), which in this case were 2905 and -1.80, respectively.

Consequently, the final correlation was written as:

This correlation was validated by foaming data available in the literature for a

high viscosity system with different types of dispersing gases (i.e., argon, air, N2, helium

and hydrogen) and diffusers (i.e., single and multiple orifice and Pyrex disk). It was

proven to be applicable to various systems with a broad range of physical properties (46

(2.16)

V /

(2.17)

45

< < 12100 mPas, 69.5 < y< 478 mN/m and 1200 < pc, < 3000 kg/m3), average bubble

size (0.7 < r < 20 mm), and superficial gas velocity (0 < G < 40 mm/s) within ±35%

error. The results of the sensitivity analysis on the average bubble radius, which was the

most influential parameter in predicting foam height according to Equation (2.17),

indicated that the predicted foam height could vary significantly within ±10% deviation

of the average bubble radius. As a result, it was suggested that bubble size distribution

replace the average bubble radius in future correlations. In addition, they recommended a

further investigation of the effect of initial liquid height through the minimum superficial

gas velocity since they observed a very large deviation between the predicted and

experimental values, particularly when small foam heights were measured at G

approaching Gm (Pilon et al., 2001). Note that Lotun and Pilon found that the use of the

Buckingham-Pi theorem with independent variables influencing the steady-state foam

height of the slag foam could lead to the same dimensionless numbers as those found by

non-dimensionalizing the governing equation (Equation (2.16)) (Lotun and Pilon, 2005).

2.3.2 Other approaches

Bikerman introduced the first foaming correlation for aqueous systems as

expressed below. The correlation predicts the foam height for aqueous solutions of n-

butyl alcohol dispersed by air (Bikerman, 1938 and 1973).

v HA H

G G G (2.18)

where v is the average steady foam volume (m3), H is pneumatic steady-state foam height

(m), G is the gas flow rate (m3/s), A is the cross-sectional area of the test cell (m2), and

46

< JUL< 12100 mPas, 69.5 < y< 478 mN/m and 1200 < pi< 3000 kg/m3), average bubble

size (0.7 < r < 20 mm), and superficial gas velocity (0 < G <40 mm/s) within ±35%

error. The results of the sensitivity analysis on the average bubble radius, which was the

most influential parameter in predicting foam height according to Equation (2.17),

indicated that the predicted foam height could vary significantly within ±10% deviation

of the average bubble radius. As a result, it was suggested that bubble size distribution

replace the average bubble radius in future correlations. In addition, they recommended a

further investigation of the effect of initial liquid height through the minimum superficial

gas velocity since they observed a very large deviation between the predicted and

experimental values, particularly when small foam heights were measured at G

approaching Gm (Pilon et al., 2001). Note that Lotun and Pilon found that the use of the

Buckingham-Pi theorem with independent variables influencing the steady-state foam

height of the slag foam could lead to the same dimensionless numbers as those found by

non-dimensionalizing the governing equation (Equation (2.16)) (Lotun and Pilon, 2005).

2.3.2 Other approaches

Bikerman introduced the first foaming correlation for aqueous systems as

expressed below. The correlation predicts the foam height for aqueous solutions of n-

butyl alcohol dispersed by air (Bikerman, 1938 and 1973).

(2., 8) G G G

where v is the average steady foam volume (m3), H is pneumatic steady-state foam height

(m), G is the gas flow rate (m3/s), A is the cross-sectional area of the test cell (m2), and

46

G is the superficial gas velocity (m/s). He found that E did not depend on gas flow rate,

experimental apparatus (dimension of test cell and size and porosity of diffusers),

incoming gas pressure, and solution volume when: 1) the solution volume was

sufficiently high to provide a certain depth to balance its rise due to gas bubbles and its

decrease due to the carryover of liquid into foam lamella and 2) the gas flow rate was in

the proper range, not so slow so as to cause little or no foam and not so fast so as to cause

any difficulties in obtaining readings either from rapid rupture or unstable position of the

upper foam boundary. He also claimed that E can be used as a physical property of the

solution with the unit of time indicating a residence time of gas traveling upward through

the foam or an average lifetime of foam before rupture. However, the application of

Equation (2.18) was limited within a certain range of the gas flow rate as mentioned

above. Therefore, the use of Equation (2.18) to explain foaming behaviour of the

solutions outside this particular range, especially at very low and high gas flow rates, is

questionable.

In recent years, more sophisticated foaming correlations have been developed, not

only to cover wider ranges of gas flow rates and physical properties of the liquid phase,

but also to account for the actual phenomenon of foam so that the prediction of the

steady-state foam height is more accurate and realistic. For example, Hrma considered

the facts that i) the foam height was determined by the bubbles at the top, which would

burst as soon as the liquid between the bubbles was drained out and the film thickness

reached the critical value and ii) the bubbles at the top of the foam layer must be ruptured

to balance new bubbles created by the incoming gas at the bottom of the layer so as to

maintain the steady-state condition of foam. As a result, he proposed the steady-state

47

G is the superficial gas velocity (m/s). He found that £ did not depend on gas flow rate,

experimental apparatus (dimension of test cell and size and porosity of diffusers),

incoming gas pressure, and solution volume when: 1) the solution volume was

sufficiently high to provide a certain depth to balance its rise due to gas bubbles and its

decrease due to the carryover of liquid into foam lamella and 2) the gas flow rate was in

the proper range, not so slow so as to cause little or no foam and not so fast so as to cause

any difficulties in obtaining readings either from rapid rupture or unstable position of the

upper foam boundary. He also claimed that X can be used as a physical property of the

solution with the unit of time indicating a residence time of gas traveling upward through

the foam or an average lifetime of foam before rupture. However, the application of

Equation (2.18) was limited within a certain range of the gas flow rate as mentioned

above. Therefore, the use of Equation (2.18) to explain foaming behaviour of the

solutions outside this particular range, especially at very low and high gas flow rates, is

questionable.

In recent years, more sophisticated foaming correlations have been developed, not

only to cover wider ranges of gas flow rates and physical properties of the liquid phase,

but also to account for the actual phenomenon of foam so that the prediction of the

steady-state foam height is more accurate and realistic. For example, Hrma considered

the facts that /) the foam height was determined by the bubbles at the top, which would

burst as soon as the liquid between the bubbles was drained out and the film thickness

reached the critical value and /'/') the bubbles at the top of the foam layer must be ruptured

to balance new bubbles created by the incoming gas at the bottom of the layer so as to

maintain the steady-state condition of foam. As a result, he proposed the steady-state

47

foaming correlation in 1990 to predict the foam height in terms of the bubble radius and

superficial gas velocity as shown below (Hrma, 1990):

-( 1 1

H = 2re.0" 1+ bhGm Gcr 1 (2.19) 1 1

6 Gcr

where ref is the effective average radius of bubble, bh is the constant, Gm is the threshold

gas flux or minimum superficial gas velocity required for the onset of foam, and 6, is

the critical superficial gas velocity at which the steady-state foam no longer exists. His

correlation presented the opportunity to eliminate the constraint of Equation (2.18) since

it can predict the foam height as the superficial velocity of the incoming gas ( 6 ) was

changed, i.e., (i) when G < 6„„ the foam was not formed in system, (ii) when G = 6„„

the foam height was equal to the diameter of the monolayer bubbles, (iii) when Gm < G

< 6„, the foam height was predicted by Equation (2.19), (iv) when G 6,, the foam

height was approaching infinity, which meant that the foam continuously increased

without a limit and consequently the steady-state condition could not be obtained. Even

though Hrma's correlation revealed more details of foaming behaviours, unclear

explanation of the constant bh together with the lack of the relationships to link the

physical properties of the solution into his correlation, led to a need for further

development.

Subsequently, Jeelani and his research team incorporated the effect of the binary

coalescence between gas bubbles into their foam height correlation to predict the foam

height of aqueous solutions of glycerine containing surfactants (Jeelani et al., 1990).

According to the material balance of liquid phase in the foam layer, liquid in the lamella

48

foaming correlation in 1990 to predict the foam height in terms of the bubble radius and

superficial gas velocity as shown below (Hrma, 1990):

H = 2rJ \ + b.

1 1 ^

1 1

G Gcr )

(2.19)

where reg is the effective average radius of bubble, bh is the constant, Gm is the threshold

gas flux or minimum superficial gas velocity required for the onset of foam, and Gcr is

the critical superficial gas velocity at which the steady-state foam no longer exists. His

correlation presented the opportunity to eliminate the constraint of Equation (2.18) since

it can predict the foam height as the superficial velocity of the incoming gas (G ) was

changed, i.e., (i) when G < Gm, the foam was not formed in system, (ii) when G = Gm,

the foam height was equal to the diameter of the monolayer bubbles, (iii) when Gm < G

< Gcr, the foam height was predicted by Equation (2.19), (iv) when G > Gcr, the foam

height was approaching infinity, which meant that the foam continuously increased

without a limit and consequently the steady-state condition could not be obtained. Even

though Hrma's correlation revealed more details of foaming behaviours, unclear

explanation of the constant bh together with the lack of the relationships to link the

physical properties of the solution into his correlation, led to a need for further

development.

Subsequently, Jeelani and his research team incorporated the effect of the binary

coalescence between gas bubbles into their foam height correlation to predict the foam

height of aqueous solutions of glycerine containing surfactants (Jeelani et al., 1990).

According to the material balance of liquid phase in the foam layer, liquid in the lamella

48

flowing back to the bulk solution (qd,,„„, m/s) was balanced by the liquid from the bulk

solution moving upward to the foam layer through the foam films (qupfibn, m/s) and the

Plateau borders (qup,pB, m/s) (Hartland and Barber, 1974). To avoid mathematical

complications, they divided the prediction into two cases. The first case was when qup,firm

was insignificant, which allowed qd w, to be equal to qup,pB, and the second case was

when qup,PB was insignificant, which allowed qdoi,„ to be equal to qupilan•

Case 1: qdown :4:- qup,pg since

K pc I 0 ) di.5

quizpg» qupium

2

H= eaveg„ 0.72s,u°L.75

K where p = '10.25 0.5 1 1 K2ci'"P O0.5 Wig) Y

65(5:reaverb„

Case 2: (Mown = qup, irm since qup,PB<< qupfilm

H = (6rb° +

cave (K fd,2.2560.25 (6Z" hod

ave

1 4.851.75e0•5r cr ave bo

where Kf = 0.138 s2 t425

gy .25 y

(2.20)

(2.21)

where H is pneumatic steady-state foam height (m); rbo and do are the binary coalescence

time (s) and the diameter of bubble entering the foam layer (m), respectively; G is the gas

flow rate per unit area (m3/m2-s); Kp and Kf are constants for Cases 1 and 2, respectively;

gar is the critical film thickness (m), which allows the coalescence to occur; say, is the

average gas fraction in the foam obtained by the y-ray attenuation technique; pc, is the

liquid viscosity (Pas); is the liquid density (kg/m3); y is the surface tension (N/m), and

s is the number of immobile surfaces, which number 2 for this system. By knowing a

change in the average bubble diameter along the foam height, the authors suggested that

49

flowing back to the bulk solution (qdown, m/s) was balanced by the liquid from the bulk

solution moving upward to the foam layer through the foam films (qupf,im, m/s) and the

Plateau borders (q^pB, m/s) (Hartland and Barber, 1974). To avoid mathematical

complications, they divided the prediction into two cases. The first case was when qup,jtim

was insignificant, which allowed qdown to be equal to qUP/>B, and the second case was

when qUPJPB was insignificant, which allowed qdown to be equal to qupjnm-

Case 1' qdown = quP,PB since qupjPB qupjiim

H =

Kpda

€ S K ave cr / G M.5

' f K2d2 ^ ^ 1

y6Scr£awTho j G05

^ o.i2sMr where Kp=- —

\PLS) y

Case 1". qdown = quP, iim since quP,PB qupjiin,

H = -c V ave /

+ -

r6

\ £<IV e

\~

Kfd™G0'25 ^ 0.8

. ^ 0.138^V125 where K , =

\0.25

(2.20)

(2.21)

where H is pneumatic steady-state foam height (m); Tb0 and d0 are the binary coalescence

time (s) and the diameter of bubble entering the foam layer (m), respectively; G is the gas

flow rate per unit area (m3/m2-s); Kp and K/ are constants for Cases 1 and 2, respectively;

Scr is the critical film thickness (m), which allows the coalescence to occur; w is the

average gas fraction in the foam obtained by the y-ray attenuation technique; fit is the

liquid viscosity (Pa s); pi is the liquid density (kg/m3); /is the surface tension (N/m), and

s is the number of immobile surfaces, which number 2 for this system. By knowing a

change in the average bubble diameter along the foam height, the authors suggested that

49

the steady-state foam height at a specified gas flow rate up to the critical value was a

function of gas flux, critical film thickness, binary coalescence time, bubble diameter and

liquid physical properties as expressed in Equations (2.20) — (2.21). The results clearly

showed that both equations could predict the experimental foam height reasonably well.

However, verifying the correlations was not possible since some experimental

parameters, such as the average gas-holdup fraction, could not be obtained from the

literature.

50

the steady-state foam height at a specified gas flow rate up to the critical value was a

function of gas flux, critical film thickness, binary coalescence time, bubble diameter and

liquid physical properties as expressed in Equations (2.20) - (2.21). The results clearly

showed that both equations could predict the experimental foam height reasonably well.

However, verifying the correlations was not possible since some experimental

parameters, such as the average gas-holdup fraction, could not be obtained from the

literature.

50

3. EXPERIMENTS

The foaming behaviours of the CO2-loaded aqueous solutions of alkanolamines

were investigated in both static and column foaming experiments, of which the details of

the experimental setups and procedures are given in Sections 3.1 and 3.2, respectively.

The key purpose of the former experiment was to carry out a parametric study to provide

the comprehensive information on the effects of process parameters on foaming

behaviours. The obtained experimental results were also used to develop the correlation

for prediction of pneumatic steady-state foam height (see details in Chapter 5). The latter

experiment was primarily aimed at generating experimental foam data used for foam

model verification (see details in Chapter 6).

3.1 Static foaming experiment

3.1.1 Experimental setup

The foaming experiments were carried out using the pneumatic method modified

from the standard ASTM D892 for foaming testing of lubricating oils (ASTM, 1999). As

shown in Figure 3.1, the setup was composed of a 1000 cm3 graduated cylinder cell, a

temperature bath with an immersion digital circulator with a stability of ±0.01°C in a

temperature ranging from 5°C above ambient temperature to 120°C, a metal diffuser

supplied from Petrolab Corp. (Latham, New York, U.S.), a polycarbonate drying column,

a flowmeter with an accuracy of ±2% full scale, and a gas mass flowmeter with an

accuracy ±1% full scale. The diffuser was made of sintered five micron porous stainless

steel with a maximum pore diameter not greater than 80 micron. Industrial grade N2

purchased from Praxair (Canada) was utilized as a dispersed gas to bubble the test

51

3. EXPERIMENTS

The foaming behaviours of the CC>2-loaded aqueous solutions of alkanolamines

were investigated in both static and column foaming experiments, of which the details of

the experimental setups and procedures are given in Sections 3.1 and 3.2, respectively.

The key purpose of the former experiment was to carry out a parametric study to provide

the comprehensive information on the effects of process parameters on foaming

behaviours. The obtained experimental results were also used to develop the correlation

for prediction of pneumatic steady-state foam height (see details in Chapter 5). The latter

experiment was primarily aimed at generating experimental foam data used for foam

model verification (see details in Chapter 6).

3.1 Static foaming experiment


The foaming experiments were carried out using the pneumatic method modified

from the standard ASTM D892 for foaming testing of lubricating oils (ASTM, 1999). As

shown in Figure 3.1, the setup was composed of a 1000 cm3 graduated cylinder cell, a

temperature bath with an immersion digital circulator with a stability of ±0.01°C in a

temperature ranging from 5°C above ambient temperature to 120°C, a metal diffuser

supplied from Petrolab Corp. (Latham, New York, U.S.), a polycarbonate drying column,

a flowmeter with an accuracy of ±2% full scale, and a gas mass flowmeter with an

accuracy ±1% full scale. The diffuser was made of sintered five micron porous stainless

steel with a maximum pore diameter not greater than 80 micron. Industrial grade N2

purchased from Praxair (Canada) was utilized as a dispersed gas to bubble the test

51

solution instead of air. This was to prevent the degradation of alkanolamine that may

affect the foaming data obtained and also to maintain the CO2 loading of the test solution

during the experiments.

52

solution instead of air. This was to prevent the degradation of alkanolamine that may

affect the foaming data obtained and also to maintain the CO2 loading of the test solution

during the experiments.

52

Gas mass flowmeter

N2 cylinder

Emitted to atmosphere

Temperature bath


Gas mass flowmeter Emitted to

atmosphere

Drying column

Test Cell

Immerse heater with thermometer

Flowmeter

Led

N2 cylinder Temperature bath


53

3.1.2 Preparation of test solutions

Four single alkanolamines, MEA, DEA, MDEA, and AMP and three blended

alkanolamines, MEA+MDEA, DEA+MDEA, and MEA+AMP with mixing mole ratios

of 1:2, 1:1, and 2:1, respectively, were investigated in this study. These reagent-grade

alkanolamines were purchased from Sigma-Aldrich (Ontario, Canada). Their aqueous

solutions were prepared by diluting the reagent-grade alkanolamines to a desired

concentration using deionized water. The solution concentration was determined by

titration using a standard solution of 1 N hydrochloric acid (HCl) and methyl orange as

an indicator. The prepared solutions were loaded with CO2 by bubbling the industrial-

grade CO2 purchased from Praxair (Canada) through the fresh solutions of alkanolamines

for a certain period of time, depending on the desired CO2 loading in solution. The CO2

loading was determined using the standard method established by the Association of

Official Analytical Chemists (AOAC) (Horowitz, 1975). The details of chemicals and

gases used in this research are listed in Table 3.1.

54

3.1.2 Preparation of test solutions

Four single aikanolamines, ME A, DEA, MDEA, and AMP and three blended

aikanolamines, MEA+MDEA, DEA+MDEA, and MEA+AMP with mixing mole ratios

of 1:2, 1:1, and 2:1, respectively, were investigated in this study. These reagent-grade

aikanolamines were purchased from Sigma-Aldrich (Ontario, Canada). Their aqueous

solutions were prepared by diluting the reagent-grade aikanolamines to a desired

concentration using deionized water. The solution concentration was determined by

titration using a standard solution of 1 N hydrochloric acid (HC1) and methyl orange as

an indicator. The prepared solutions were loaded with CO2 by bubbling the industrial-

grade CO2 purchased from Praxair (Canada) through the fresh solutions of aikanolamines

for a certain period of time, depending on the desired CO2 loading in solution. The CO2

loading was determined using the standard method established by the Association of

Official Analytical Chemists (AOAC) (Horowitz, 1975). The details of chemicals and

gases used in this research are listed in Table 3.1.

54

Table 3.1 Source and purity of chemicals and gases

Chemical/gas Source Purity

MEA Sigma-Aldrich 99+%

DEA Sigma-Aldrich 99%

MDEA Sigma-Aldrich 99+%

AMP Sigma-Aldrich 95%

Acetic acid Sigma-Aldrich 99.7+%

Ammonium thiosulfate Sigma-Aldrich 99%

Bicine Sigma-Aldrich 99%

Copper (II) carbonate Sigma-Aldrich 98%

Formic acid Sigma-Aldrich 95 — 97%

Glycolic acid Sigma-Aldrich 99%

Hydrochloric acid EMD chemicals 36.5 — 38.0%

Malonic acid Sigma-Aldrich 99%

Oxalic acid Sigma-Aldrich 98%

Sodium chloride EMD chemicals 99%

Sodium metavanadate Sigma-Aldrich 90%

Sodium sulfite Fisher 99.3%

Sodium thiocyanate Sigma-Aldrich 98%

Sodium thiosulfate Sigma-Aldrich 99%

Sulfuric acid VWR 95 — 98%

Hydrochloric acid standard solution Fisher 1.000 mol/dm3

Methyl orange solution VWR 0.01%

CO2 Praxair 99.5%

N2 Praxair 99.995%

55

Table 3.1 Source and purity of chemicals and gases

Chemical/gas Source Purity

MEA Sigma-Aldrich 99+%

DEA Sigma-Aldrich 99%

MDEA Sigma-Aldrich 99+%

AMP Sigma-Aldrich 95%

Acetic acid Sigma-Aldrich 99.7+%

Ammonium thiosulfate Sigma-Aldrich 99%

Bicine Sigma-Aldrich 99%

Copper (II) carbonate Sigma-Aldrich 98%

Formic acid Sigma-Aldrich 95 - 97%

Glycolic acid Sigma-Aldrich 99%

Hydrochloric acid EMD chemicals 36.5 - 38.0%

Malonic acid Sigma-Aldrich 99%

Oxalic acid Sigma-Aldrich 98%

Sodium chloride EMD chemicals 99%

Sodium metavanadate Sigma-Aldrich 90%

Sodium sulfite Fisher 99.3%

Sodium thiocyanate Sigma-Aldrich 98%

Sodium thiosulfate Sigma-Aldrich 99%

Sulfuric acid VWR 95 - 98%

Hydrochloric acid standard solution Fisher 1.000 mol/dm"

Methyl orange solution VWR 0.01%

C02 Praxair 99.5%

n2 Praxair 99.995%

55

3.1.3 Experimental procedures

Prior to the experiments, the test solution was placed at a given volume (400 cm3

in most experimental runs) into the test cell without mechanical shaking or stirring, and

heated in a temperature bath to a set temperature for approximately 20 minutes. A metal

diffuser was inserted into the heated test cell and left for approximately 5 minutes to be

saturated with the test solution. N2 gas was then introduced to a polycarbonate drying

column to remove moisture before entering a flow meter for approximate measurement

and, subsequently, a mass flow meter for steady reading. The test solution was vigorously

bubbled by N2 gas through the gas diffuser with a blowing time of 25 min ± 5 seconds

(starting when the first N2 bubble rose from the gas diffuser). The N2 gas was eventually

released to the atmosphere from the outlet of the test cell. The concentration of

alkanolamine solution as well as its CO2 loading, conductivity, and pH were determined

before and after each experiment to ensure no changes occurred in the solution

constituents due to alkanolamine degradation products or variation in operating

conditions. During the blowing time, the foam volume above the gas dispersion layer (see

Figure 2.1, page 33) was recorded every minute. Such foam volume was in some cases

difficult to measure due to the unclear interface between the gas dispersion and the

Kugelschaum, the uneven Polyederfoam surface, and unpredictable foam rupture. As

such, average foam volumes at the 25th minute were then used (as shown in Figure 3.2)

instead of the actual foam volume to reduce errors due to data readings. It was found that

the average foam volume, in most experiments, began to reach a steady state after 10

minutes of blowing time. This steady value was, therefore, used as the representative

foam volume for subsequent data analysis.

56


Prior to the experiments, the test solution was placed at a given volume (400 cm3

in most experimental runs) into the test cell without mechanical shaking or stirring, and

heated in a temperature bath to a set temperature for approximately 20 minutes. A metal

diffiiser was inserted into the heated test cell and left for approximately 5 minutes to be

saturated with the test solution. N2 gas was then introduced to a polycarbonate drying

column to remove moisture before entering a flow meter for approximate measurement

and, subsequently, a mass flow meter for steady reading. The test solution was vigorously

bubbled by N2 gas through the gas diffuser with a blowing time of 25 min ± 5 seconds

(starting when the first N2 bubble rose from the gas diffiiser). The N2 gas was eventually

released to the atmosphere from the outlet of the test cell. The concentration of

alkanolamine solution as well as its CO2 loading, conductivity, and pH were determined

before and after each experiment to ensure no changes occurred in the solution

constituents due to alkanolamine degradation products or variation in operating

conditions. During the blowing time, the foam volume above the gas dispersion layer (see

Figure 2.1, page 33) was recorded every minute. Such foam volume was in some cases

difficult to measure due to the unclear interface between the gas dispersion and the

Kugelschaum, the uneven Polyederfoam surface, and unpredictable foam rupture. As

such, average foam volumes at the 25th minute were then used (as shown in Figure 3.2)

instead of the actual foam volume to reduce errors due to data readings. It was found that

the average foam volume, in most experiments, began to reach a steady state after 10

minutes of blowing time. This steady value was, therefore, used as the representative

foam volume for subsequent data analysis.

56

2.0

• 1.8

2 1.6 0

E • 1

'4

ea O E

1.2

te 11"f 1.0 co

0.8

& 0.6

• 0.4

0.2

0.0

• -I - • -*.-x- • *• • -* -x- • *• --x- •Yi- • -IX - X-- • -It- -x

5 10 15 20 25 Time (min)

Figure 3.2 Average foam volume profile during blowing time (MEA solution volume =

400 cm3, CO2 loading = 0.40 mol/mol, N2 velocity = 2.06 m3/m2-hr, MEA

concentration = 5.0 kmol/m3 and solution temperature = 40°C)

57

E 3 O > E <0 ^ O n £ E

"Sfe (0 0) D) & tt I

2.0

1.8

1.6

1.4

1.2

1.0

0.8

0.6

0.4

0.2

0.0

•O—o—^—O— . . . A . . . . © . — < • - " * " ™ * — - © • — « - o — - 0 — H .

-X- -x-:

-i 1 1 i 1 1 1 r- 1 1 1 1- i i 1 i

10 15 Time (min)

20 25

Figure 3.2 Average foam volume profile during blowing time (MEA solution volume:

400 cm3, CO2 loading = 0.40 mol/mol, N2 velocity = 2.06 m3/m2-hr, MEA

concentration =5.0 kmol/m3 and solution temperature = 40°C)

57

3.1.4 Data analysis

A foaminess coefficient (E, min) was calculated using the following equation

(Bikerman, 1973). It is a ratio of foam volume and superficial gas velocity, representing a

residence time of gas traveling upward through the foam or an average lifetime of foam

before rupture.

E 60v

GA (3.1)

where 6 is gas (N2) flow rate per unit area or superficial gas velocity (m3/m2-hr).

According to Bikerman (1973), the foaminess coefficient does not depend on gas flow

rate, dimension of test cell, solution volume, and pore size of diffuser if the solution

volume is deep enough and the superficial gas velocity is in a proper range. In this

research, the ranges of solution volume and superficial gas velocity are from 400 to 700

cm3 and from 1.75 to 2.41 m3/m2-hr, respectively.

3.1.5 Tested parameters and experimental conditions

A parametric study was carried out under a wide spectrum of operating

conditions. The parameters of interest are superficial gas velocity, solution volume,

alkanolamine concentration, CO2 loading of solution, solution temperature, degradation

product of alkanolamine, corrosion inhibitor, and alkanolamine type. Note that pressure

of the system was not included in the test program here. This is because it was reported to

have an insignificant effect on foaming tendency (Harruff, 1998). A summary of

parameters and experimental conditions is given in Table 3.2.

58

3.1.4 Data analysis

A foaminess coefficient (I, min) was calculated using the following equation

(Bikerman, 1973). It is a ratio of foam volume and superficial gas velocity, representing a

residence time of gas traveling upward through the foam or an average lifetime of foam

before rupture.

where G is gas (N2) flow rate per unit area or superficial gas velocity (m3/m2-hr).

According to Bikerman (1973), the foaminess coefficient does not depend on gas flow

rate, dimension of test cell, solution volume, and pore size of diffuser if the solution

volume is deep enough and the superficial gas velocity is in a proper range. In this

research, the ranges of solution volume and superficial gas velocity are from 400 to 700

cm3 and from 1.75 to 2.41 m3/m2-hr, respectively.

3.1.5 Tested parameters and experimental conditions

A parametric study was carried out under a wide spectrum of operating

conditions. The parameters of interest are superficial gas velocity, solution volume,

alkanolamine concentration, CO2 loading of solution, solution temperature, degradation

product of alkanolamine, corrosion inhibitor, and alkanolamine type. Note that pressure

of the system was not included in the test program here. This is because it was reported to

have an insignificant effect on foaming tendency (Harruff, 1998). A summary of

parameters and experimental conditions is given in Table 3.2.

58

Solution volume and superficial gas velocity were chosen as test parameters to

identify ranges with a constant E. Such ranges were used in the foaming tests for this

CO2-aqueous alkanolamine system, enabling the generation of foam data that are not

dependent on pore size of gas disperser, and dimension of test cell and ensuring the

consistency of foam data if solution volume and gas flow rate are changed within these

particular ranges. Due to its popularity in gas treating services, MEA was used as a

representative solvent in all foaming tests. Its concentration and CO2 loading cover

operating ranges in gas treating plants (Kohl and Nielson, 1997). Note that although the

MEA concentration of 7.0 kmol/m3 is not commonly used due to severe corrosion of

process equipment and piping, it is worth testing it here because such high MEA

concentrations present an opportunity for improved efficiency of the process and are thus

expected to be employed together with a corrosion inhibitor in the near future.

Solution temperatures up to 90°C were tested to simulate the temperatures of

various process components, such as the absorber, lean/rich heat exchanger, and cooler.

With the features of the test cell, foaming tests at temperatures beyond 90°C are not

applicable, as the CO2 loading of solution cannot be maintained under atmospheric

pressure. Nevertheless, the obtained data are adequate to reveal the effect of temperature

on foam tendency.

Thirteen degradation products were selected from the products reported in

published literature, including both regenerable compounds (i.e. bicine) (Rooney and

Dupart, 2000) and non-regenerable ones (i.e., carboxylic acids, sulfite, sulfate,

thiosulfate, thiocyanate and chloride) (Liu et al., 1995; Craig Jr. and McLaughlin, 1996;

Litschewski, 1996; Rooney et al., 1997; Fan et al., 2000). Sodium metavanadate

represents a toxic heavy-metal corrosion inhibitor commonly used in gas treating

59

Solution volume and superficial gas velocity were chosen as test parameters to

identify ranges with a constant £. Such ranges were used in the foaming tests for this

C02-aqueous alkanolamine system, enabling the generation of foam data that are not

dependent on pore size of gas disperser, and dimension of test cell and ensuring the

consistency of foam data if solution volume and gas flow rate are changed within these

particular ranges. Due to its popularity in gas treating services, MEA was used as a

representative solvent in all foaming tests. Its concentration and CO2 loading cover

operating ranges in gas treating plants (Kohl and Nielson, 1997). Note that although the

MEA concentration of 7.0 kmol/m3 is not commonly used due to severe corrosion of

process equipment and piping, it is worth testing it here because such high MEA

concentrations present an opportunity for improved efficiency of the process and are thus

expected to be employed together with a corrosion inhibitor in the near future.

Solution temperatures up to 90°C were tested to simulate the temperatures of

various process components, such as the absorber, lean/rich heat exchanger, and cooler.

With the features of the test cell, foaming tests at temperatures beyond 90°C are not

applicable, as the CO2 loading of solution cannot be maintained under atmospheric

pressure. Nevertheless, the obtained data are adequate to reveal the effect of temperature

on foam tendency.

Thirteen degradation products were selected from the products reported in

published literature, including both regenerable compounds (i.e. bicine) (Rooney and

Dupart, 2000) and non-regenerable ones (i.e., carboxyiic acids, sulfite, sulfate,

thiosulfate, thiocyanate and chloride) (Liu et al., 1995; Craig Jr. and McLaughlin, 1996;

Litschewski, 1996; Rooney et al., 1997; Fan et al., 2000). Sodium metavanadate

represents a toxic heavy-metal corrosion inhibitor commonly used in gas treating

59

industry, while copper carbonate and sodium sulfite represent low toxic ones.

Alkanolamine types, both single and blended-types, were also included in the test

program. In addition to MEA representing primary alkanolamine, DEA, MDEA, and

AMP were selected to represent secondary, tertiary, and sterically hindered

alkanolamines, respectively. Blended MEA+MDEA, DEA+MDEA, and MEA+AMP

were chosen because they are gaining a great deal of attention for their energy saving

characteristics. They represent mixtures of primary-tertiary, secondary-tertiary, and

primary-sterically hindered alkanolamines.

60

industry, while copper carbonate and sodium sulfite represent low toxic ones.

Alkanolamine types, both single and blended-types, were also included in the test

program. In addition to MEA representing primary alkanolamine, DEA, MDEA, and

AMP were selected to represent secondary, tertiary, and sterically hindered

alkanolamines, respectively. Blended MEA+MDEA, DEA+MDEA, and MEA+AMP

were chosen because they are gaining a great deal of attention for their energy saving

characteristics. They represent mixtures of primary-tertiary, secondary-tertiary, and

primary-sterically hindered alkanolamines.

60

Table 3.2 Summary of tested parameters and operating conditions

Parameter Operating condition

Superficial gas (N2) velocity: 0.44 - 3.40 m3/m2-hr

2.0 and 5.0 kmol/m3 MEA, 400 cm3 solution volume, 0.40 mol/mol CO2 loading, and 40°C

Solution volume: 200 - 700 cm3

2.0 kmol/m3 MEA, 2.06 m3/m2-hr N2 velocity, 0.40 mol/mol CO2 loading, and 40°C

Alkanolamine concentration: 2.0 - 7.0 kmol/m3

CO2 loading: 0.10 - 0.55 mol/mol

MEA, 2.06 m3/m2-hr N2 velocity, 400 cm3 solution volume, 0.20 and 0.40 mol/mol CO2 loading, and 40°C 5.0 kmol/m3 MEA, 2.06 m3/m2-hr N2 velocity, 400 cm3solution volume, and 40, 60 and 90°C

Solution temperature: 40 - 90°C

5.0 kmol/m3 MEA, 2.06 m3/m2-hr N2 velocity, 400 cm3solution volume, and 0.20 and 0.40 mol/mol CO2 loading

Degradation product of MEA: acetic acid ammonium thiosulfate bicine formic acid glycolic acid hydrochloric acid malonic acid oxalic acid sodium chloride sodium sulfite (additive) sodium thiocyanate sodium thiosulfate sulfuric acid

10000 ppm of degradation product, 5.0 kmol/m3 MEA, 2.06 mi/m2-hr N2 velocity, 400 cm3 solution volume, 0.40 mol/mol CO2 loading, and 60°C

Corrosion inhibitor: copper carbonate sodium metavanadate sodium sulfite

1000 ppm of corrosion inhibitor, 5.0 kmol/m3 MEA, 2.06 m /m2-hr N2 velocity, 400 cm3 solution volume, 0.40 mol/mol CO2 loading, and 60°C

Alkanolamine type: MEA DEA MDEA AMP MEA+MDEA DEA+MDEA MEA+AMP

4.0 kmol/m3 alkanolamine, 2.06 m3/m2-hr N2 velocity, 400 cm3 solution volume, 0.40 mol/mol CO2 loading, 60°C, and mixing mole ratio of blended solution = 1:2, 1:1 and 2:1

61

Table 3.2 Summary of tested parameters and operating conditions

Parameter Operating condition

Superficial gas (N2) velocity: 0.44 - 3.40 m3/m2-hr

2.0 and 5.0 kmol/m3 MEA, 400 cm3 solution volume, 0.40 mol/mol CO2 loading, and 40°C

Solution volume: 200-700 cm3

2.0 kmol/m3 MEA, 2.06 m3/m2-hr N2 velocity, 0.40 mol/mol CO2 loading, and 40°C

Alkanolamine concentration: 2.0 - 7.0 kmol/m3

MEA, 2.06 m3/m2-hr N2 velocity, 400 cm3 solution volume, 0.20 and 0.40 mol/mol CO2 loading, and 40°C

CO2 loading: 0.10-0.55 mol/mol

5.0 kmol/m3 MEA, 2.06 m3/m2-hr N2 velocity, 400 cm3

solution volume, and 40, 60 and 90°C

Solution temperature: 40 - 90°C

5.0 kmol/m3 MEA, 2.06 m3/m2-hr N2 velocity, 400 cm3

solution volume, and 0.20 and 0.40 mol/mol CO2 loading

Degradation product of MEA: 10000 ppm of degradation product, 5.0 kmol/m3 MEA, acetic acid 2.06 m /m2-hr N2 velocity, 400 cm3 solution volume, ammonium thiosulfate 0.40 mol/mol CO2 loading, and 60°C bicine formic acid glycolic acid hydrochloric acid malonic acid oxalic acid sodium chloride sodium sulfite (additive) sodium thiocyanate sodium thiosulfate sulfuric acid

Corrosion inhibitor: 1000 ppm of corrosion inhibitor, 5.0 kmol/m3 MEA, copper carbonate 2.06 m /m2-hr N2 velocity, 400 cm3 solution volume, sodium metavanadate 0.40 mol/mol CO2 loading, and 60°C sodium sulfite

Alkanolamine type: 4.0 kmol/m3 alkanolamine, 2.06 m3/m2-hr N2 velocity, MEA 400 cm3 solution volume, 0.40 mol/mol CO2 loading, DEA 60°C, and mixing mole ratio of blended solution = 1:2, MDEA 1:1 and 2:1 AMP MEA+MDEA DEA+MDEA MEA+AMP

61

3.2 Column foaming experiment


A series of foaming experiments, shown in Figure 3.3a, was carried out in a gas

absorption system mainly consisting of an absorber fitted with Mellapak 500.Y structured

packing, a solution buffer tank, solution pump, and gas filter and regulator. The absorber

was 0.80 m high and 0.10 m in diameter and made of acrylic plastic so as to allow visual

observation of foam generated during the experiments as shown in Figure 3.3b. Two

elements of Mellapak 500.Y were packed and arranged with 90° rotation. Their

geometric characteristics are provided in Table 3.3. The solution buffer tank was 0.02 m3

in volume and made of high-density polyethylene. The stainless steel gear pump

controlled by a digital dispensing drive was used to circulate the absorption solution with

±0.3% accuracy in flow rate. The liquid flow rate was regulated by a calibrated liquid

flow meter with a high-resolution valve. Feed gas (air) was regulated by a pressure

regulator providing a flow capacity of 15.0 scfm at 620 kPa and filtered by a 5-p.m

sintered brass element. A direct reading variable-area gas flow meter with a maximum

capacity of 8.0 scfm was used to measure gas flow rate. The temperatures of gas and

solution were measured using a J-KEM Model 210 temperature controller and K-type

thermocouples with a maximum error of ±0.4% on readings above 0°C. The foam heights

were measured using a measuring tape starting from the liquid level accumulated in the

outlet tubing at the bottom of the absorber.

62

3.2 Column foaming experiment


A series of foaming experiments, shown in Figure 3.3a, was carried out in a gas

absorption system mainly consisting of an absorber fitted with Mellapak 500. Y structured

packing, a solution buffer tank, solution pump, and gas filter and regulator. The absorber

was 0.80 m high and 0.10 m in diameter and made of acrylic plastic so as to allow visual

observation of foam generated during the experiments as shown in Figure 3.3b. Two

elements of Mellapak 500.Y were packed and arranged with 90° rotation. Their

geometric characteristics are provided in Table 3.3. The solution buffer tank was 0.02 m3

in volume and made of high-density polyethylene. The stainless steel gear pump

controlled by a digital dispensing drive was used to circulate the absorption solution with

±0.3% accuracy in flow rate. The liquid flow rate was regulated by a calibrated liquid

flow meter with a high-resolution valve. Feed gas (air) was regulated by a pressure

regulator providing a flow capacity of 15.0 scfm at 620 kPa and filtered by a 5-jam

sintered brass element. A direct reading variable-area gas flow meter with a maximum

capacity of 8.0 scfm was used to measure gas flow rate. The temperatures of gas and

solution were measured using a J-KEM Model 210 temperature controller and K-type

thermocouples with a maximum error of ±0.4% on readings above 0°C. The foam heights

were measured using a measuring tape starting from the liquid level accumulated in the

outlet tubing at the bottom of the absorber.

62

Gas outlet

_l........

Absorber packed with structured packing

Gas inlet 4

\.., ./ Measuring

tape

Solution buffer tank

(a)

Air

[ -----°w1"---Filter

(b)

Figure 3.3 (a) Schematic diagram of the column foaming experimental apparatus and (b)

photograph of the absorber fitted with two elements of Mellapak 500.Y

(original in color)

63

m Gas outlet

Absorber packed with structured packing

Gas inlet

Measuring tape

Air Solution buffer tank Filter

(a) (b)

Figure 33 (a) Schematic diagram of the column foaming experimental apparatus and (b)

photograph of the absorber fitted with two elements of Mellapak 500. Y

(original in color)

63

Table 3.3 Geometric characteristics of Mellapak 500.Y

Geometric characteristics

Element height (hp, m) 0.205

Specific area (ap, m2/m3) 500

Void fraction 0.91

Corrugation angle (a, °) 45

Crimp height (hcrimp, 6.53x 10-3

Corrugation base (2B, m) 9.60x 10-3

Table 3.3 Geometric characteristics of Mellapak 500. Y

Geometric characteristics

Element height (hp, m) 0.205

Specific area (ap, m2/m3) 500

Void fraction 0.91

Corrugation angle (a, °) 45

Crimp height (h crimP, m) 6.53x10"3

Corrugation base (25, m) 9.60x10'3

64


Prior to the experiment, the aqueous MEA solution was prepared by diluting the

reagent-grade MEA (Sigma-Aldrich, Ontario, Canada) with deionized water to a desired

concentration and purging the solution with an industrial-grade CO2 (Praxair, Canada) to

a desired CO2 loading. After regulated to a given flow rate, a stream of air was

introduced to the bottom of the absorber through a filter to remove solid particles from

the stream, through a gas flow meter to measure gas flow rate, and through a

thermocouple to measure the temperature of feed air. The air then travelled upward and

countercurrently with the aqueous MEA solution, which was pumped from the storage

tank through the liquid flow meter and the thermocouple to the top of the absorber. The

solution was collected at the bottom of the column and recirculated. The reading of the

foam height was taken at the thirtieth minute after initiation of the experiment. Then, the

air and liquid temperature were respectively measured.

At the bottom of the column, a certain amount of foam, together with the liquid

solution, was gathered at the liquid outlet tube. In order to measure foam height in the

tube, the level of the accumulated solution above the outlet tube was, necessarily, kept to

the minimum so that all the foam was pushed down the tube as illustrated in Figure 3.4a.

The total foam height was the sum of the measured foam height, using the measuring tape

as shown in Figure 3.4b, and the distance from the top of the liquid outlet tube inside the

column to the measuring tape outside the column. This total foam height was used to

calculate the foam volume by multiplying the cross-sectional area of the tube with an

inside diameter of 9.5 mm. The experiment required repetition if the foam in the tube

coalesced into an air gap. During the experiment, if the solution level above the liquid

65


Prior to the experiment, the aqueous MEA solution was prepared by diluting the

reagent-grade MEA (Sigma-Aldrich, Ontario, Canada) with deionized water to a desired

concentration and purging the solution with an industrial-grade CO2 (Praxair, Canada) to

a desired CO2 loading. After regulated to a given flow rate, a stream of air was

introduced to the bottom of the absorber through a filter to remove solid particles from

the stream, through a gas flow meter to measure gas flow rate, and through a

thermocouple to measure the temperature of feed air. The air then travelled upward and

countercurrently with the aqueous MEA solution, which was pumped from the storage

tank through the liquid flow meter and the thermocouple to the top of the absorber. The

solution was collected at the bottom of the column and recirculated. The reading of the

foam height was taken at the thirtieth minute after initiation of the experiment. Then, the

air and liquid temperature were respectively measured.

At the bottom of the column, a certain amount of foam, together with the liquid

solution, was gathered at the liquid outlet tube. In order to measure foam height in the

tube, the level of the accumulated solution above the outlet tube was, necessarily, kept to

the minimum so that all the foam was pushed down the tube as illustrated in Figure 3.4a.

The total foam height was the sum of the measured foam height, using the measuring tape

as shown in Figure 3.4b, and the distance from the top of the liquid outlet tube inside the

column to the measuring tape outside the column. This total foam height was used to

calculate the foam volume by multiplying the cross-sectional area of the tube with an

inside diameter of 9.5 mm. The experiment required repetition if the foam in the tube

coalesced into an air gap. During the experiment, if the solution level above the liquid

65

outlet tube was noticeably changed, some adjustment to the height of the tube was

necessary.

66

outlet tube was noticeably changed, some adjustment to the height of the tube was

necessary.

66

(a) (b)

Figure 3.4 Example of (a) a solution level above the liquid outlet tube at the bottom of

the column and (b) a foam height measurement (liquid velocity = 4.6

m3/m2-hr, air velocity = 120 mm/s and elapse time at =15 minutes)

(original in color)

67

(a) (b)

Figure 3.4 Example of (a) a solution level above the liquid outlet tube at the bottom of

the column and (b) a foam height measurement (liquid velocity = 4.6

m3/m2-hr, air velocity = 120 mm/s and elapse time at = 15 minutes)

(original in color)

67

3.2.3 Experimental conditions

In the experiment, MEA was chosen as the absorption solvent due to its

popularity in the gas treating industry and its potential for post-combustion carbon

capture (Tzimas and Peteves, 2003; Metz et al., 2005). In addition, the aqueous MEA

solution with concentration and CO2 loading of 5.0 kmollm3 and 0.40 mol/mol,

respectively, was reported to induce higher foaming tendency than other alkanolamine

solutions (see Sections 4.3 and 4.4). To eliminate the effect of mass transfer on the

foaming results, air was used to disperse the preloaded aqueous MEA solution.

Experimental conditions are summarized in Table 3.4. Note that both tested gas and

liquid flow rates provide liquid-to-gas (LIG) ratios ranging from 0.6 to 18.9 (kg

solution/kg air), which cover the LIG ratio range used in the CO2 capture pilot plant at the

Esbjerg coal-fired power plant (Knudsen et al., 2009).

68

3.2.3 Experimental conditions

In the experiment, MEA was chosen as the absorption solvent due to its

popularity in the gas treating industry and its potential for post-combustion carbon

capture (Tzimas and Peteves, 2003; Metz et al., 2005). In addition, the aqueous MEA

solution with concentration and CO2 loading of 5.0 kmol/m3 and 0.40 mol/mol,

respectively, was reported to induce higher foaming tendency than other alkanolamine

solutions (see Sections 4.3 and 4.4). To eliminate the effect of mass transfer on the

foaming results, air was used to disperse the preloaded aqueous MEA solution.

Experimental conditions are summarized in Table 3.4. Note that both tested gas and

liquid flow rates provide liquid-to-gas (L/G) ratios ranging from 0.6 to 18.9 (kg

solution/kg air), which cover the L/G ratio range used in the CO2 capture pilot plant at the

Esbjerg coal-fired power plant (Knudsen et al., 2009).

68

Table 3.4 Experimental conditions for the column foaming experiment

Parameter Conditions

Liquid phase

Absorption solvent MEA

MEA concentration (lunol/m3) 5.0

CO2 loading (mol/mol) 0.40

Liquid velocity (m3/m2-hr) up to 4.6

Liquid temperature (°C) 15.3 — 21.6

Gas phase

Air velocity (mm/s) 48 — 360

Air temperature (°C) 20.0 — 22.8

Table 3.4 Experimental conditions for the column foaming experiment

Parameter Conditions

Liquid phase

Absorption solvent MEA

MEA concentration (kmol/m3) 5.0

CO2 loading (mol/mol) 0.40

Liquid velocity (m3/m2-hr) up to 4.6

Liquid temperature (°C) 15.3-21.6

Gas phase

Air velocity (mm/s) 48 - 360

Air temperature (°C) 20.0 - 22.8

69

4. PARAMETRIC STUDY ON FOAMING BEHAVIOUR

The parametric study provides a comprehensive set of foaming data under a wide

spectrum of operating conditions in the CO2 absorption process using aqueous solutions

of alkanolamines. The obtained data were reproducible with a standard deviation of 0.15

minutes and were, thus, sufficiently reliable to be used for revealing the effects of process

parameters on E and providing a better understanding of foaming behaviour. The

complete experimental results were given in Appendix A. Such data were also used to

develop an empirical correlation for the purpose of foaming prediction (see details in

Chapter 5).

4.1 Superficial gas velocity

N2 velocity was varied from 0.44 to 3.40 m3/m2-hr in both 2.0 and 5.0 kmol/m3

MEA solutions under 0.40 mol/mol CO2 loading at 40°C to investigate the effect of

velocity on E. The results in Figure 4.1 show that an increase in N2 velocity nonlinearly

decreases E. This is because the increasing turbulence created by the increasing gas

velocity disrupts foam formation and reduces foam stability.

As the N2 velocity is further increased to 1.75 m3/m2-hr or greater, E reaches

stabilization. This suggests that the volume of foam proportionally increases with N2

flow rate. Such gas velocity with a constant E presents an opportunity for the elimination

of the gas velocity effect on E in any foaming experiments. In this work, we, therefore,

chose to use a N2 velocity of 2.06 m3/m2-hr in all experimental runs.

70

4. PARAMETRIC STUDY ON FOAMING BEHAVIOUR

The parametric study provides a comprehensive set of foaming data under a wide

spectrum of operating conditions in the CO2 absorption process using aqueous solutions

of alkanolamines. The obtained data were reproducible with a standard deviation of 0.15

minutes and were, thus, sufficiently reliable to be used for revealing the effects of process

parameters on E and providing a better understanding of foaming behaviour. The

complete experimental results were given in Appendix A. Such data were also used to

develop an empirical correlation for the purpose of foaming prediction (see details in

Chapter 5).

4.1 Superficial gas velocity

N2 velocity was varied from 0.44 to 3.40 m3/m2-hr in both 2.0 and 5.0 kmol/m3

MEA solutions under 0.40 mol/mol CO2 loading at 40°C to investigate the effect of

velocity on 2. The results in Figure 4.1 show that an increase in N2 velocity nonlinearly

decreases S. This is because the increasing turbulence created by the increasing gas

velocity disrupts foam formation and reduces foam stability.

As the N2 velocity is further increased to 1.75 m3/m2-hr or greater, E reaches

stabilization. This suggests that the volume of foam proportionally increases with N2

flow rate. Such gas velocity with a constant I presents an opportunity for the elimination

of the gas velocity effect on 2 in any foaming experiments. In this work, we, therefore,

chose to use a N2 velocity of 2.06 m3/m2-hr in all experimental runs.

70

6.00

S WEN

5.00 -.

20 4.00 -IE m 00 3.000 m a) c 2.00 - .E m o u. 1.00 -

0.00 0.00

--0-- 2.0 kmoUm3

—43-- 5.0 kmoUm3

'a -ia.

-EL_ 0 - 13 - - - - la- ____ „.......

11............... ......:: :

1.00 2.00 3.00

Superficial gas velocity (m3/m2-hr)

4.00


concentration = 2.0 and 5.0 kmol/m3, solution volume = 400 cm3, CO2


71

6.00

| 5.00

•g 4.00 E o> g 3.00 CO CO

c 2.00 E (0 £ 1.00

0.00

—•— 2.0 kmol/m3

• — \ \ \ \ \ s *

5.0 kmol/m3

\ *

s \

* "El V O ""13' EJ---.

C ""'"--a

0.00 -i 1 1 r i 1 i 1 i 1 i

1.00 2.00 3.00

Superficial gas velocity (m3/m2-hr) 4.00


concentration = 2.0 and 5.0 kmol/m3, solution volume = 400 cm3, CO2


71

4.2 Solution volume

The effect of solution volume on E was investigated by varying the solution volume

of a 2.0 kmol/m3 MEA solution containing 0.40 mol/mol CO2 loading from 200 to 700

cm3 at 40°C and 2.06 m3/m2-hr N2 velocity. The results shown in Figure 4.2 indicate that

foam formation does not occur when solution volume is 200 cm3. This is due to the

insufficient contact time for gas and liquid contact or due to an inadequate hydrostatic

force to resist the buoyancy force of a N2 bubble (Figure 4.3). As a result, the bubble

detaches from the diffuser and induces a turbulent flow among bubbles in the test cell.

The shearing force caused by this turbulence may destroy the foams. Once the solution

volume increases to more than 200 cm3, foams are produced and E increases with

solution volume. This is because the increase in solution volume leads to an increase in

hydrostatic force, which in turn reduces the turbulence caused by the bubble detachment

from the diffuser. As the solution volume is further increased from 400 to 700 cm3, E

becomes invariant. This is because the increasing hydrostatic force overcomes the

turbulence caused by the bubble detachment or makes such turbulence insignificant.

Gravity drainage is also retarded because an increase in solution volume increases the

thickness of the lamella. This eventually helps reduce foam collapse in the system. The

above findings suggest that solution volume should not be chosen arbitrarily for foaming

experiments since different values of foam volume and E can be obtained under identical

operating conditions. To eliminate such effects of solution volume, the solution volume

resulting in a steady E (i.e., > 400 cm3) should be used. In this work, we, therefore,

selected a solution volume of 400 cm3 for all experimental runs.

72

4.2 Solution volume

The effect of solution volume on 2 was investigated by varying the solution volume

of a 2.0 kmol/m3 MEA solution containing 0.40 mol/mol CO2 loading from 200 to 700

cm3 at 40°C and 2.06 m3/m2-hr N2 velocity. The results shown in Figure 4.2 indicate that

foam formation does not occur when solution volume is 200 cm3. This is due to the

insufficient contact time for gas and liquid contact or due to an inadequate hydrostatic

force to resist the buoyancy force of a N2 bubble (Figure 4.3). As a result, the bubble

detaches from the diffuser and induces a turbulent flow among bubbles in the test cell.

The shearing force caused by this turbulence may destroy the foams. Once the solution

•j volume increases to more than 200 cm , foams are produced and S increases with

solution volume. This is because the increase in solution volume leads to an increase in

hydrostatic force, which in turn reduces the turbulence caused by the bubble detachment

from the diffuser. As the solution volume is further increased from 400 to 700 cm3, Z

becomes invariant. This is because the increasing hydrostatic force overcomes the

turbulence caused by the bubble detachment or makes such turbulence insignificant.

Gravity drainage is also retarded because an increase in solution volume increases the

thickness of the lamella. This eventually helps reduce foam collapse in the system. The

above findings suggest that solution volume should not be chosen arbitrarily for foaming

experiments since different values of foam volume and X can be obtained under identical

operating conditions. To eliminate such effects of solution volume, the solution volume

resulting in a steady £ (i.e., > 400 cm3) should be used. In this work, we, therefore,

selected a solution volume of 400 cm3 for all experimental runs.

72

1.00

S •.... E 0.80

61a) .0— 0.60 m o m m 0.40 m c .E al 0.20 o u-

0.00 0 200 400

Solution volume (cm3)

600 800

Figure 4.2 Effect of solution volume on foaminess coefficients (MEA concentration =

2.0 kmol/m3, N2 velocity = 2.06 m3/m2-hr, CO2 loading = 0.40 mol/mol and


73

1.00

E 0.80

0.60

0.40

0.20 u.

0.00 0 200 400 600 800

Solution volume (cm3)

Figure 4.2 Effect of solution volume on foaminess coefficients (MEA concentration =

2.0 kmol/m3, N2 velocity = 2.06 m3/m2-hr, CO2 loading = 0.40 mol/mol and


73

Liquid

Hydrostatic force

l irBuoyancy Surface

force force

t

Gas

Solid


74

Liquid

Hydrostatic force

\ Buoyancy Surface

force force

Solid


74

4.3 Alkanolamine concentration

The concentration of aqueous MEA solution was varied from 2.0 to 7.0 kmol/m3

under two operating conditions of the absorber (i.e., 0.20 mol/mol CO2 loading and 40°C

representing the conditions of the absorber top and 0.40 mol/mol CO2 loading and 60°C

representing the conditions of the absorber bottom). The results in Figure 4.4 show that E

initially increases with MEA concentration and then declines after the MEA

concentration reaches 3.0 and 6.0 kmol/m3 in the cases of the absorber top and bottom,

respectively.

The increase in E with MEA concentration is due to a decrease in surface tension

of solution (Figure 4.5a). When the surface tension is decreased, the surface force is

lowered and overcome by the buoyancy force of the foam bubble. This then results in

greater foam volume and E. In addition to the surface tension, the density and viscosity of

MEA solution are also attributable to the increase in E. The higher concentration of MEA

solution increases the density and the bulk viscosity of the solution (Figures 4.5b-4.5c).

The increased solution density increases the buoyancy force of the foam bubble, while

the increased bulk viscosity retards the foam collapse caused by gravity drainage. Both

effects lead to a greater E.

As mentioned previously, E not only increases but also decreases with MEA

concentration when the MEA concentration is greater than 3.0 and 6.0 kmol/m3 under the

conditions of the absorber top and bottom, respectively. This is a result of the creaming

process (Walstra, 1989), wherein bulk viscosity plays a significant role on the rising

bubbles through the liquid phase to form a foam layer. According to the Stokes' equation,

75

4.3 Alkanolamine concentration

The concentration of aqueous MEA solution was varied from 2.0 to 7.0 kmol/m3

under two operating conditions of the absorber (i.e., 0.20 mol/mol CO2 loading and 40°C

representing the conditions of the absorber top and 0.40 mol/mol CO2 loading and 60°C

representing the conditions of the absorber bottom). The results in Figure 4.4 show that E

initially increases with MEA concentration and then declines after the MEA

concentration reaches 3.0 and 6.0 kmol/m3 in the cases of the absorber top and bottom,

respectively.

The increase in £ with MEA concentration is due to a decrease in surface tension

of solution (Figure 4.5a). When the surface tension is decreased, the surface force is

lowered and overcome by the buoyancy force of the foam bubble. This then results in

greater foam volume and E. In addition to the surface tension, the density and viscosity of

MEA solution are also attributable to the increase in E. The higher concentration of MEA

solution increases the density and the bulk viscosity of the solution (Figures 4.5b-4.5c).

The increased solution density increases the buoyancy force of the foam bubble, while

the increased bulk viscosity retards the foam collapse caused by gravity drainage. Both

effects lead to a greater X.

As mentioned previously, I not only increases but also decreases with MEA

concentration when the MEA concentration is greater than 3.0 and 6.0 kmol/m3 under the

conditions of the absorber top and bottom, respectively. This is a result of the creaming

process (Walstra, 1989), wherein bulk viscosity plays a significant role on the rising

bubbles through the liquid phase to form a foam layer. According to the Stokes' equation,

75

an increase in bulk viscosity leads to an increase in drag force, which can retard or even

stop the rising bubbles. This thereby decreases foam formation in the solution.

Such decrease in E is also caused by a reduction of foam stability due to an

increase in surface viscosity of the solution. The increased viscosity can make the foam

surface more immobile and weakens the surface elasticity. As a result, the foam surface

has less ability to resist foam thinning and collapse.

76

an increase in bulk viscosity leads to an increase in drag force, which can retard or even

stop the rising bubbles. This thereby decreases foam formation in the solution.

Such decrease in £ is also caused by a reduction of foam stability due to an

increase in surface viscosity of the solution. The increased viscosity can make the foam

surface more immobile and weakens the surface elasticity. As a result, the foam surface

has less ability to resist foam thinning and collapse.

76

C

j 0.80 -

m 0.60 -C

0

1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 MEA concentration (kmoUm3)

Figure 4.4 Effect of alkanolamine concentration on foaminess coefficient (N2 velocity =

2.06 m3/m2-hr, solution volume = 400 cm3, absorber top condition: CO2

loading = 0.20 mol/mol and solution temperature = 40°C, absorber bottom

condition: CO2 loading = 0.40 mol/mol and solution temperature = 60°C)

77

1.00

-c I o 0.80 o £ a> o 0 0)

« 0.60 c 1 a o LL

0.40

0.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 MEA concentration (kmol/m3)

Figure 4.4 Effect of alkanolamine concentration on foaminess coefficient (N2 velocity =

2.06 m3/m2-hr, solution volume = 400 cm3, absorber top condition: CO2

loading = 0.20 mol/mol and solution temperature = 40°C, absorber bottom

condition: CO2 loading = 0.40 mol/mol and solution temperature = 60°C)

—•— Absorber top

—Q— Absorber bottom 1 1 1 1 1 » 1 1 i 1 1 1 1 1 1 1 1 1 1 1 1—1—n—»—1 1 1—1—1—r

77

80 . c • o TA 70 - . 5?. E 60 ' C, 't= 50 -w •

40 0.0 2.0 4.0 6.0 8.0


1.12

• 1.10 c O ̂ 1.08 la n E d.21.06

4 a) ".5 1.04

a. 1.02

1.00

(a)

0.0 2.0 4.0 6.0 8.0 MEA concentration (kmol/m3)

(b) 4.0

P 3.0 - o c..) ..._O 0

> oi 2.0 --a a. I; E •

.-- • 1 0 - V

a. 0.0


(c)

Figure 4.5 (a) Surface tension of the CO2-unloaded aqueous MEA solution replotted

from the experimental data (Vazquez et al., 1997), (b) predicted density of the

CO2-loaded MEA solution from correlation (Weiland et al., 1998) and (c)

predicted viscosity of the CO2-loaded aqueous MEA solutions from

correlation (Weiland et al., 1998)

78

2.0 4.0 6.0 8.0 MEA concentration (kmol/m3)

(a)

-B" Bottom

.0 2.0 4.0 6.0 8.0 MEA concentration (kmol/m3)

(b)

& I 3 o £ M > « 2. T3 a. 0 c 4-* c

1 1

e a.

0.

0

0

.0

.0

.0

— T o p --Q-- Bottom

//

O"


(c)

Figure 4.5 (a) Surface tension of the CCVunloaded aqueous MEA solution replotted

from the experimental data (Vazquez et al., 1997), (b) predicted density of the

CC>2-loaded MEA solution from correlation (Weiland et al., 1998) and (c)

predicted viscosity of the CC^-loaded aqueous MEA solutions from

correlation (Weiland et al., 1998)

78

4.4 CO2 loading

The effect of CO2 loading of solution on E was studied using a 5.0 kmol/m3

aqueous MEA solutions under three different temperatures of 40, 60 and 90°C and CO2

loading ranging from 0.10 to 0.55 mol/mol. The results in Figure 4.6 show that an

increase in CO2 loading increases E for all temperatures. This can be explained by the

surface tension and density of the solution. As the CO2 loading increases, the surface

tension decreases (Figure 4.7a) and the solution density increases (Figure 4.7b). This

results in a reduced surface force and an increased buoyancy force, which, thus, promotes

foam formation and causes a greater E. Such increase in E is also due to an enhancement

of foam stability caused by an increase in bulk viscosity (Figure 4.7c) preventing the

thinning process and by an existence of a surface tension gradient promoting the

Marangoni effect. As CO2 loading increases, this surface tension gradient becomes

larger, which in turn enhances the Marangori effect. In addition to the above increasing

trend of E, the results in Figure 4.6 also show a decreasing trend of E after the CO2

loading is increased to a certain value. This is primarily due to the influence of solution

viscosity, which becomes more significant than those of surface tension and density. At a

higher CO2 loading, solution viscosity is increased (Figure 4.7c), thereby discouraging

foam formation. The higher solution viscosity also reflects a greater surface viscosity,

which in turn results in a reduction in foam stability.

79

4.4 CO2 loading

The effect of CO2 loading of solution on E was studied using a 5.0 kmol/m3

aqueous MEA solutions under three different temperatures of 40, 60 and 90°C and CO2

loading ranging from 0.10 to 0.55 mol/mol. The results in Figure 4.6 show that an

increase in CO2 loading increases 2 for all temperatures. This can be explained by the

surface tension and density of the solution. As the CO2 loading increases, the surface

tension decreases (Figure 4.7a) and the solution density increases (Figure 4.7b). This

results in a reduced surface force and an increased buoyancy force, which, thus, promotes

foam formation and causes a greater 2. Such increase in 2 is also due to an enhancement

of foam stability caused by an increase in bulk viscosity (Figure 4.7c) preventing the

thinning process and by an existence of a surface tension gradient promoting the

Marangoni effect. As CO2 loading increases, this surface tension gradient becomes

larger, which in turn enhances the Marangori effect. In addition to the above increasing

trend of I, the results in Figure 4.6 also show a decreasing trend of £ after the CO2

loading is increased to a certain value. This is primarily due to the influence of solution

viscosity, which becomes more significant than those of surface tension and density. At a

higher CO2 loading, solution viscosity is increased (Figure 4.7c), thereby discouraging

foam formation. The higher solution viscosity also reflects a greater surface viscosity,

which in turn results in a reduction in foam stability.

79

1.50

S •_ E

CI2 1.00 -

E o o o a 6 2 0.50 -

•Eas 0 LL

0.00 0.00 0.10 0.20 0.30 0.40 0.50 0.60

CO2loading in solution (mol CO2/mol MEA)

Figure 4.6 Effect of CO2 loading on foaminess coefficient (MEA concentration = 5.0

kmoi/m3, N2 velocity = 2.06 m3/m2-hr, solution volume = 400 cm3 and

solution temperature = 40, 60 and 90°C)

80

1.50

I

J 1.00 o

SE ® o 0 (0 (0 ® 0.50

1 •s o UL

0.00 0.00 0.10 0.20 0.30 0.40 0.50 0.60

C02 loading in solution (mol C02/mol MEA)

40°C •--- 60°C *— 90°C

-or a •

Figure 4.6 Effect of CO2 loading on foaminess coefficient (MEA concentration = 5.0

kmol/m3, N2 velocity = 2.06 m3/m2-hr, solution volume = 400 cm3 and

solution temperature = 40,60 and 90°C)

80

65 0 2 —.60 -

E

3 E 66 - ea

u) • 60

45 0.00 0.20 0.40 0.60

CO2 loading (mol CO2/mol MEA)

- 2 kmoUm3, 40°C 2 kmoUm3, 60°C

— •X• • - 3 kmoUm3, 40°C - -d 3kmoUm3, 60°C

(a) 1.16 .

1.12 my •o

11.08 2 -a, •-1.04 Iv 0. 1.00

0.96 • • • . 0.00 0.20 0.40 0.60 CO2 loading (mol CO2/mol MEA)

(b) 4.0

713 3.0 -

co > ca 1, E 0- 2.0 - a ••• „

a. x_ _ _ _x__ 31;_ • * E •

0.0 0.00 0.20 0.40 0.60 CO2 loading (mol CO2/mol MEA)

(c)

Figure 4.7 (a) Surface tension of the CO2-loaded aqueous MEA solution as a function of CO2 loading and solution temperature (measured by Spinning Drop Interfacial Tensiometer Model 510), (b) predicted density of 5.0 kmol/m3 MEA solution from correlation (Weiland et al., 1998), and (c) predicted viscosity of 5.0 kmol/m3 MEA solution from correlation (Weiland et al., 1998)

81

o » «! •I o E. •c 3 to

65

.60

55

50

45

—* ft— — —a

—•— 2 kmol/m3, 40°C —G— 2 kmol/m3, 60°C - * - 3 kmol/mJ, 40°C --A-- 3 kmol/m3, 60°C

0.00 0.20 0.40 0.60 C02 loading (mol CO^mol MEA)

(a)

-Q— 60°C

0.00 0.20 0.40 0.60 C02 loading (mol COj/mol MEA)

(b)

0.0

- 40°C —•&— 60°C - * - 90°C

„Q-0E0

0.00 0.20 0.40 0.60 C02 loading (mol COj/mol MEA)

(c)

Figure 4.7 (a) Surface tension of the C02-loaded aqueous MEA solution as a function of CO2 loading and solution temperature (measured by Spinning Drop Interfacial Tensiometer Model 510), (b) predicted density of 5.0 kmol/m3 MEA solution from correlation (Weiland et al., 1998), and (c) predicted viscosity of 5.0 kmol/m3 MEA solution from correlation (Weiland et al., 1998)

81

4.5 Solution temperature

Solution temperature was found to have a significant effect on E. As seen from

Figure 4.8, as the temperature of 5.0 kmol/m3 MEA solutions increased from 40 to 90°C,

E decreased considerably. This is true for both systems containing 0.20 and 0.40 mol/mol

CO2 loading. Such an effect is a result of poor foam stability, which is caused by reduced

bulk viscosity (Figure 4.9a) and a turbulence flow created by the vigorous movement of

molecules at an elevated temperature. Note that surface tension and density of the

solution play a minor role in such decreasing trends of E. As seen from Figures 4.9b-4.9c,

surface tension and density decrease with increasing temperature. This implies a lower

surface force (reflecting an enhancement of foam formation) and a lower buoyancy force

(reflecting a retardation of foam formation). The resulting force may be small or

insignificant compared to the influence of solution viscosity described above.

82

4.5 Solution temperature

Solution temperature was found to have a significant effect on E. As seen from

Figure 4.8, as the temperature of 5.0 kmol/m3 MEA solutions increased from 40 to 90°C,

2 decreased considerably. This is true for both systems containing 0.20 and 0.40 mol/mol

CO2 loading. Such an effect is a result of poor foam stability, which is caused by reduced

bulk viscosity (Figure 4.9a) and a turbulence flow created by the vigorous movement of

molecules at an elevated temperature. Note that surface tension and density of the

solution play a minor role in such decreasing trends of 2. As seen from Figures 4.9b-4.9c,

surface tension and density decrease with increasing temperature. This implies a lower

surface force (reflecting an enhancement of foam formation) and a lower buoyancy force

(reflecting a retardation of foam formation). The resulting force may be small or

insignificant compared to the influence of solution viscosity described above.

82

1.60

-a- 1.40 •E .--. 1.20 c .02 1.00 E 8 0.80 0 vi i 0.60 a) c 'E 0.40 Uo u 0.20

0.00 1 1 1

40.0

--•-- 0.20 mol CO2/mol MEA - - a - - 0.40 mol CO2/mol MEA

v ------____12

a 1 I 1 1 I 1 1 I I 1- 1 1 1 1 1 r t 1 1 -1-

50.0 60.0 70.0 80.0

Solution temperature (°C)

Figure 4.8 Effect of solution temperature on foaminess coefficient (MEA concentration

= 5.0 kmol/m3, N2 velocity = 2.06 m3/m2-hr, solution volume = 400 cm3 and

CO2 loading = 0.20 and 0.40 mol/mol)

90.0

83

1.60

<£ 1.40

~ 1.20

| 1.00 £ § 0.80 0 m 0.60 ® )

1 0.40 CO £ 0.20

0.00 40.0 50.0 60.0 70.0 80.0 90.0


Figure 4.8 Effect of solution temperature on foaminess coefficient (MEA concentration

= 5.0 kmol/m3, N2 velocity = 2.06 m3/m2-hr, solution volume = 400 cm3 and

CO2 loading = 0.20 and 0.40 mol/mol)

2.5

2.0

-.4.4 1.5

3, lig 1.0

0.5 a.

0.0

70

0

a c

E 60 -

0 E CIS •••••••

50- a co

0.20 moUmol CO2 loading 0.40 moUmol CO2 loading

40.0 50.0 60.0 70.0 80.0 90.0


40

20.0 30.0 40.0 50.0 60.0 Solution temperature (°C)

(a)

1.00

40.0 50.0 60.0 70.0 80.0 90.0 Solution temperature (°C)

(c)

Figure 4.9 (a) Predicted viscosity of 5.0 kmol/m3 MEA solution from correlation

(Weiland et al., 1998), (b) surface tension of 5.0 kmol/m3 unloaded-CO2

MEA solution replotted from experimental data (Vazquez et al., 1997), and

(c) predicted density of 5.0 kmol/m3 MEA solution from correlation (Weiland

et al., 1998)

(b)

0.20 moUmol CO2 loading -e--- 0.40 moUmol CO2 loading

5 ----- 19-- ---- -

84

"O £ Q.

0.5

0.0

-•— 0.20mol/moi CO2 loading -•B— Q.40 mol/mo< C02 loading


(a)

20.0 30.0 40.0 50.0 60.0 Solution temperature (°C)

(b)

1.16 0.20 moi/mol CO2 loading

-B—- 0.40 moi/mol C02 loading

1.00 I I I


(c)

Figure 4.9 (a) Predicted viscosity of 5.0 kmol/m3 MEA solution from correlation

(Weiland et al., 1998), (b) surface tension of 5.0 kmol/m3 unloaded-CCh

MEA solution replotted from experimental data (Vazquez et al., 1997), and

(c) predicted density of 5.0 kmol/m3 MEA solution from correlation (Weiland

et al., 1998)

84

4.6 Degradation products of MEA

The effect of thirteen degradation products on E was investigated by using a 5.0

kmol/m3 aqueous MEA solution containing 0.40 mol/mol CO2 loading at 60°C. The

results in Table 4.1 indicate that the solutions containing degradation products (except

sulfuric acid) provide a greater E than those without degradation products. Ammonium

thiosulfate induces the highest foam volume and E, followed by glycolic acid, sodium

sulfite, malonic acid, oxalic acid, sodium thiocyanate, sodium chloride, sodium

thiosulfate, bicine, hydrochloric acid, formic acid, acetic acid, and sulfuric acid.

The increase in E is due to formation of anionic surfactants in the presence of

sulfate (SO4- ), sulfonate ( SO;), and carboxylate (C00) functioning as a hydrophilic

group. These anionic surfactants reduce surface tension of the solution, thereby

encouraging foam formation. Such surfactants also enhance foam stability by improving

surface elasticity due to the Marangoni effect. The results also show that the presence of

chloride ions increases E. This is probably because the chloride ions reduce surface

tension by neutralizing the ionic products resulting from the reaction between CO2 and

MEA, which in turn enhances foam formation (Danckwerts and Tavares da Silva, 1967).

85

4.6 Degradation products of MEA

The effect of thirteen degradation products on E was investigated by using a 5.0

kmol/m3 aqueous MEA solution containing 0.40 mol/mol CO2 loading at 60°C. The

results in Table 4.1 indicate that the solutions containing degradation products (except

sulfuric acid) provide a greater I than those without degradation products. Ammonium

thiosulfate induces the highest foam volume and 2, followed by glycolic acid, sodium

sulfite, malonic acid, oxalic acid, sodium thiocyanate, sodium chloride, sodium

thiosulfate, bicine, hydrochloric acid, formic acid, acetic acid, and sulfuric acid.

The increase in 2 is due to formation of anionic surfactants in the presence of

sulfate (SO4"), sulfonate (SOj), and carboxylate (COO") functioning as a hydrophilic

group. These anionic surfactants reduce surface tension of the solution, thereby

encouraging foam formation. Such surfactants also enhance foam stability by improving

surface elasticity due to the Marangoni effect. The results also show that the presence of

chloride ions increases I. This is probably because the chloride ions reduce surface

tension by neutralizing the ionic products resulting from the reaction between CO2 and

MEA, which in turn enhances foam formation (Danckwerts and Tavares da Silva, 1967).

85

Table 4.1 Effect of degradation products on foaminess coefficient (degradation product

concentration = 10000 ppm, MEA concentration = 5.0 kmol/m3, N2 velocity =

2.06 m3/m2-hr, solution volume = 400 cm3, CO2 loading = 0.40 mol/mol and


Degradation product Average foaminess coefficient (min)1

None 0.79

Ammonium thiosulfate 0.97

Glycolic acid 0.94

Sodium sulfite 0.92

Malonic acid 0.92

Oxalic acid 0.90

Sodium thiocyanate 0.90

Sodium chloride 0.90

Sodium thiosulfate 0.85

Bicine 0.85

Hydrochloric acid 0.83

Formic acid 0.83

Acetic acid 0.82

Sulfuric acid 0.77 1 The maximum standard deviation of the foaminess coefficients is ±0.05 min.

86

Table 4.1 Effect of degradation products on foaminess coefficient (degradation product

concentration = 10000 ppm, MEA concentration = 5.0 kmol/m3, N2 velocity =

2.06 m3/m2-hr, solution volume = 400 cm3, C02 loading = 0.40 mol/mol and


Degradation product Average foaminess coefficient (min)1

None 0.79


Glycolic acid 0.94

Sodium sulfite 0.92

Malonic acid 0.92

Oxalic acid 0.90




Bicine 0.85


Formic acid 0.83

Acetic acid 0.82

Sulfuric acid 1 • ... -

0.77

86

4.7 Corrosion inhibitor

The effect of corrosion inhibitors on E was studied by adding three corrosion

inhibitors (i.e., sodium metavanadate, copper carbonate, and sodium sulfite) with a

concentration of 1000 ppm into a 5.0 kmol/m3 aqueous MEA solution containing 0.40

mol/mol CO2 loading. The results in Figure 4.10 clearly show that sodium metavanadate

and copper carbonate increase foam volume or E and sodium metavanadate induces a

greater effect, whereas sodium sulfite has no apparent effect. This can be explained by

considering the surface tension of aqueous MEA solutions. As shown in Table 4.2, the

surface tension values of aqueous MEA solutions are reduced when sodium

metavanadate and copper carbonate are added. However, a similar trend is not found for

sodium sulfite. For sodium sulfite, the surface tensions of the aqueous MEA solution with

and without the addition of sodium sulfite are not significantly different. This explains

why the foaming tendency of the aqueous MEA solution with sodium sulfite is somewhat

similar to that without sodium sulfite.

87

4.7 Corrosion inhibitor

The effect of corrosion inhibitors on I was studied by adding three corrosion

inhibitors (i.e., sodium metavanadate, copper carbonate, and sodium sulfite) with a

concentration of 1000 ppm into a 5.0 kmol/m3 aqueous MEA solution containing 0.40

mol/mol CO2 loading. The results in Figure 4.10 clearly show that sodium metavanadate

and copper carbonate increase foam volume or £ and sodium metavanadate induces a

greater effect, whereas sodium sulfite has no apparent effect. This can be explained by

considering the surface tension of aqueous MEA solutions. As shown in Table 4.2, the

surface tension values of aqueous MEA solutions are reduced when sodium

metavanadate and copper carbonate are added. However, a similar trend is not found for

sodium sulfite. For sodium sulfite, the surface tensions of the aqueous MEA solution with

and without the addition of sodium sulfite are not significantly different. This explains

why the foaming tendency of the aqueous MEA solution with sodium sulfite is somewhat

similar to that without sodium sulfite.

87

•

MEA

1.20 C' -1 1.00

I 0.80

0.60

0.40 0

0.20

0.00 MEA+NaVO3 MEA+CuCO3 MEA+Na2SO3

Corrosion inhibitor

Figure 4.10 Effect of corrosion inhibitors on foaminess coefficient (corrosion inhibitor =

NaVO3, CuCO3 and Na2SO3, corrosion inhibitor concentration = 1000 ppm,

MEA concentration = 5.0 kmol/m3, N2 velocity = 2.06 m3/m2-hr, solution

volume = 400 cm3, CO2 loading = 0.40 mol/mol and solution temperature =

60°C)

88

1.20

-§1.00 c © O 0.80 0 0 0) 0.60 <0

c 1 0.40

CO o u_

0.20

0.00 MEA MEA+NaV03 MEA+CuC03 MEA+Na2S03

Corrosion inhibitor

Figure 4.10 Effect of corrosion inhibitors on foaminess coefficient (corrosion inhibitor =

NaVC>3, C11CO3 and Na2SC>3, corrosion inhibitor concentration = 1000 ppm,

MEA concentration = 5.0 kmol/m3, N2 velocity = 2.06 m3/m2-hr, solution

volume = 400 cm3, CO2 loading = 0.40 mol/mol and solution temperature =

60°C)

88

Table 4.2 Surface tension of 5.0 kmol/m3 MEA solutions containing no CO2 loading at

25°C with/without 1000 ppm corrosion inhibitor (measured by KrOss

Tensiometer K100 using the Wilhelmy plate's principle)

System Surface tension (mN/m)

MEA without corrosion inhibitors 61.10 ± 0.02

MEA + sodium metavanadate 56.46 ± 0.03

57.67 ± 0.06

MEA + copper carbonate 58.63 ± 0.02

60.25 ± 0.01

MEA + sodium sulfite 62.51 ± 0.01

62.51 ± 0.01

89

Table 4.2 Surface tension of 5.0 kmol/m3 MEA solutions containing no CO2 loading at

25°C with/without 1000 ppm corrosion inhibitor (measured by KrOss

Tensiometer K100 using the Wilhelmy plate's principle)

System Surface tension (mN/m)

MEA without corrosion inhibitors 61.10 ±0.02

MEA + sodium metavanadate 56.46 ± 0.03

57.67 ± 0.06

MEA + copper carbonate 58.63 ± 0.02

60.25 ± 0.01

MEA + sodium sulfite 62.51 ±0.01

62.51 ±0.01

89

4.8 Alkanolamine type

Both single and blended alkanolamine solutions were tested for foaming tendency

using a 4.0 kmol/m3 total alkanolamine concentration containing 0.40 mol/mol CO2

loading at 60°C. The results for single alkanolamine solutions show that foam formation

occurs in MEA and MDEA but not in DEA and AMP solutions (Table 4.3). This implies

that surface force (represented by surface tension in Figure 4.11a) is overcome by

buoyancy force (represented by density in Figure 4.11b), and, consequently, bubbles can

be produced at the diffuser in the MEA and MDEA systems. E of MEA solution is

approximately 2.5 times that of MDEA solution since the rising bubbles in MEA solution

are easier to cream and form a layer of foam than those in MDEA solutions owing to the

lower solution viscosity of MEA solution than that of MDEA solution (Figure 4.11c).

From the observation, DEA and AMP solutions do not foam. It can be possibly explained

by a high bulk viscosity that could stop the bubbles from rising. Note that despite its high

viscosity, the MDEA solution may have foamed due to CO2 stripping as observed from

the decrease in CO2 loading of MDEA solution from 0.40 to 0.27 mol/mol during the

experiment.

For the blended alkanolamine solutions, only the MEA+AMP solution at a mixing

mole ratio of 2:1 has the potential to create foam, whereas MEA+MDEA and

DEA+MDEA solutions produce virtually no foam or only a trace amount at any mixing

ratio. This is because the surface tension of MEA+AMP is lower than that of

MEA+MDEA and DEA+MDEA at any mixing ratio (Figure 4.12a) and also because

MEA+AMP (Figure 4.12b) has the lowest bulk viscosity compared to the other blended

solutions. For the MEA+MDEA solutions, no foam is observed due to the high surface

tension (promoting less foam formation) and high bulk viscosity (hindering the creaming

90

4.8 Alkanolamine type

Both single and blended alkanolamine solutions were tested for foaming tendency

using a 4.0 kmol/m total alkanolamine concentration containing 0.40 mol/mol CO2

loading at 60°C. The results for single alkanolamine solutions show that foam formation

occurs in MEA and MDEA but not in DEA and AMP solutions (Table 4.3). This implies

that surface force (represented by surface tension in Figure 4.11a) is overcome by

buoyancy force (represented by density in Figure 4.1 lb), and, consequently, bubbles can

be produced at the diffuser in the MEA and MDEA systems. E of MEA solution is

approximately 2.5 times that of MDEA solution since the rising bubbles in MEA solution

are easier to cream and form a layer of foam than those in MDEA solutions owing to the

lower solution viscosity of MEA solution than that of MDEA solution (Figure 4.11c).

From the observation, DEA and AMP solutions do not foam. It can be possibly explained

by a high bulk viscosity that could stop the bubbles from rising. Note that despite its high

viscosity, the MDEA solution may have foamed due to CO2 stripping as observed from

the decrease in CO2 loading of MDEA solution from 0.40 to 0.27 mol/mol during the

experiment.

For the blended alkanolamine solutions, only the MEA+AMP solution at a mixing

mole ratio of 2:1 has the potential to create foam, whereas MEA+MDEA and

DEA+MDEA solutions produce virtually no foam or only a trace amount at any mixing

ratio. This is because the surface tension of MEA+AMP is lower than that of

MEA+MDEA and DEA+MDEA at any mixing ratio (Figure 4.12a) and also because

MEA+AMP (Figure 4.12b) has the lowest bulk viscosity compared to the other blended

solutions. For the MEA+MDEA solutions, no foam is observed due to the high surface

tension (promoting less foam formation) and high bulk viscosity (hindering the creaming

90

process of the bubbles). In addition, the unchanged in CO2 loading of these solutions

suggests that the effect of CO2 stripping plays no role in the foam formation as it does in

the MDEA solution.

91

process of the bubbles). In addition, the unchanged in CO2 loading of these solutions

suggests that the effect of CO2 stripping plays no role in the foam formation as it does in

the MDEA solution.

91

Table 4.3 Effect of alkanolamine type on foaminess coefficient (total alkanolamine

concentration = 4.0 kmol/m3, N2 velocity = 2.06 m3/m2-hr, solution volume =

400 cm3, CO2 loading = 0.40 mol/mol, solution temperature = 60°C and mixing

mole ratio of blended solution = 1:2, 1:1 and 2:1)

Type of alkanolamine Average foaminess coefficient (min)1

MEA 0.85

DEA No foam

MDEA2 0.32

AMP No foam

MEA + MDEA (1:2) No foam



DEA + MDEA (1:2) No foam



MEA + AMP (1:2) No foam


MEA + AMP (2:1) 0.13

I Maximum standard deviation of the foaminess coefficients is ±0.02 min. 2 Foam created by the MDEA solution could be a combined effect of CO2 stripping and viscosity.

92

Table 4.3 Effect of alkanolamine type on foaminess coefficient (total alkanolamine

concentration = 4.0 kmol/m3, N2 velocity = 2.06 m3/m2-hr, solution volume =

400 cm3, CO2 loading = 0.40 mol/mol, solution temperature = 60°C and mixing

mole ratio of blended solution — 1:2,1:1 and 2:1)

Type of alkanolamine Average foaminess coefficient (min)1

MEA 0.85

DEA No foam

MDEA2 0.32

AMP No foam









MEA + AMP (2:1) 0.13 -J— Maximum standard deviation of the foaminess coefficients is ±0.02 min. 2 Foam created by the MDEA solution could be a combined effect of CO2 stripping and viscosity.

92

.6-- • _

MEA (Vazquez et al., 1997) DEA(Vazcpiez et al., 1996)

--X- MDEA (Alvarez et al., 1998) -•kg- • AMP pfizquez et al., 1997)

2.0 4.0 6.0 Alkanolamine concentration

(kmol/m3)

(a)

--0-- MEA (Maham et al., 1994) --8-- DEA (Maham et al., 1994)

E 1.10 - "X- MDEA (Maham et al., 1995) c.) —a- • AMP (Henni et al., 2003)

1.00 4.46r j 3;t r_ trf.. • • ---- -a

0.90

8.0

80 • 70 O▪ 60 -0 ̂ 60 - • 40 o E 30 - —

20 -U, 10

0 0.0

1.20

0.0 2.0 4.0 6.0 Alkanolamine concentration

(kmol/m3)

(b)

—4--- MEA (Maham et al., 2002) To' ---ia--- DEA (Teng et at., 1994)

a. oi 6.0 - -* - MDEA (Tang et al., 1994) I

E - -it- - AMP (Henni et al., 2003) / , ;,' 4.0 x / / Z 40

/ . e-- . - -- 8 2.0 : Ar.. --.

0.0 0.0 2.0 4.0 6.0

Alkanolamine concentration (kmol/m3) (c)

Figure 4.11 (a) Surface tension of the CO2-unloaded aqueous alkanolamine solution as a function of alkanolamine concentration (40°C) replotted from experimental data (Vazquez et al., 1996 and 1997 and Alvarez et al., 1998), (b) density of the CO2-unloaded aqueous alkanolamine solution as a function of alkanolamine concentration (60°C) replotted from experimental data (Maham et al., 1994; Maham et al., 1995 and Henni et al., 2003), and (c) viscosity of the CO2-unloaded aqueous alkanolamine solution as a function of alkanolamine concentration (60°C) replotted from experimental data (Teng et al., 1994; Maham et al., 2002 and Henni et al., 2003)

93

cp50

o £ 30

*_ * X- «-A-A-.^ * ̂̂ - A- - A-..

MEA (Vdzquez et al., 1997) DEA (Vazquez et al., 1996) MDEA (Alvarez et al., 1998) AMP fV6zquez etal., 1997)

2.0 4.0 6.0 Alkanolamine concentration

(kmol/m3)

(a) 1.20

E 1.10 o 3 £1.00 M C

£ ° 0.90

—•— MEA (Maham etal., 1994) -~B— DEA (Maham et al., 1994) - MDEA (Maham et al., 1995) - a- AMP (Henni et al., 2003)


(kmol/m3)

(b) 8.0

• MEA (Maham et al., 2002) -e— DEA (Teng et al., 1994)

MDEA(Teng etal., 1994) /* - -A— • AMP (Henni et al., 2003) /

X X


(kmol/m3)

(c)

Figure 4.11 (a) Surface tension of the CCVunloaded aqueous alkanolamine solution as a function of alkanolamine concentration (40°C) replotted from experimental data (Vazquez et al., 1996 and 1997 and Alvarez et al., 1998), (b) density of the C02-unloaded aqueous alkanolamine solution as a function of alkanolamine concentration (60°C) replotted from experimental data (Maham et al., 1994; Maham et al., 1995 and Henni et al., 2003), and (c) viscosity of the CC>2-unloaded aqueous alkanolamine solution as a function of alkanolamine concentration (60°C) replotted from experimental data (Teng et al., 1994; Maham et al., 2002 and Henni et al., 2003)

93

55

? E 50 -

C .2 0 f t 45 -

m 0 it= (0 40 -

35

3:1 2:1

2:1

MEA+MDEA DEA+MDEA MEA+AMP Type of blended alkanolamines

(a)

DEA+MDEA MEA+AMP Type of blended alkanolamine

(b)

Figure 4.12 (a) Surface tension of CO2-unloaded aqueous blended alkanolamine

solutions at 60°C replotted from experimental data: MEA+MDEA (Alvarez

et al., 1998), DEA+MDEA (Alvarez et al., 1998) and MEA+AMP (Vazquez

et al., 1997), (b) predicted viscosity of CO2-unloaded aqueous blended

alkanolamine solution with 4.0 kmol/m3 total concentration at 60°C

(Mandal et al., 2003)

94

55

50

c & «

45 « o € 3 CO 40

35

• 1

MEA+MDEA DEA+MDEA MEA+AMP

Type of blended alkanolamines

(a)

• 1:1

• 2:1

1 I I MEA+MDEA DEA+MDEA MEA+AMP

Type of blended alkanolamine

(b)

Figure 4.12 (a) Surface tension of C02-unloaded aqueous blended alkanolamine

solutions at 60°C replotted from experimental data: MEA+MDEA (Alvarez

et al., 1998), DEA+MDEA (Alvarez et al., 1998) and MEA+AMP (Vazquez

et al., 1997), (b) predicted viscosity of CCh-unloaded aqueous blended

alkanolamine solution with 4.0 kmol/m3 total concentration at 60°C

(Mandal et al., 2003)

94

5. CORRELATION OF A PNEUMATIC FOAM HEIGHT

In this chapter, the development of the correlation for predicting steady-state

foam heights, which were experimentally obtained from the static experiment, in terms of

the process parameters and physical properties, was divided into three sections: i) a

framework of the correlation explaining mathematical algorithms of the correlation, ii)

subroutine calculations of average bubble radius and physical properties used in the

framework, and iii) simulation results including discussions of each individual parametric

effect and sensitivity analysis of the correlation. Not only did the correlation shed some

light on which process parameters and physical properties played a significant role in

foaming behaviour, but it also helped predict the foam height in the foam model (see

details in Chapter 6).

5.1 Correlation framework

In this work, the correlation was built on the Pilon et al. (2001) correlation and

experimental foam data from the parametric study. The Pilon et al. (2001) correlation was

chosen since it offered the possibility to predict 1 for aqueous systems through the

flexibility of adjustable parameters K and N as expressed in Equation (2.16) (page 45).

Our experimental data were chosen because they were the most comprehensive compared

to the existing foaming data in the literature, covering all important process parameters in

alkanolamine plants.

From the general form of the Pilon et al. (2001) correlation (Equation (2.16), page

45), to determine the foam height (H, mm), the adjustable parameters (K and N) and the

dimensionless parameters (Ca, Re and Fr), which are a function of pL, 6, 6,„ r, ?IL, and

95

5. CORRELATION OF A PNEUMATIC FOAM HEIGHT

In this chapter, the development of the correlation for predicting steady-state

foam heights, which were experimentally obtained from the static experiment, in terms of

the process parameters and physical properties, was divided into three sections: /) a

framework of the correlation explaining mathematical algorithms of the correlation, ii)

subroutine calculations of average bubble radius and physical properties used in the

framework, and Hi) simulation results including discussions of each individual parametric

effect and sensitivity analysis of the correlation. Not only did the correlation shed some

light on which process parameters and physical properties played a significant role in

foaming behaviour, but it also helped predict the foam height in the foam model (see

details in Chapter 6).

5.1 Correlation framework

In this work, the correlation was built on the Pilon et al. (2001) correlation and

experimental foam data from the parametric study. The Pilon et al. (2001) correlation was

chosen since it offered the possibility to predict Z for aqueous systems through the

flexibility of adjustable parameters K and N as expressed in Equation (2.16) (page 45).

Our experimental data were chosen because they were the most comprehensive compared

to the existing foaming data in the literature, covering all important process parameters in

alkanolamine plants.

From the general form of the Pilon et al. (2001) correlation (Equation (2.16), page

45), to determine the foam height (H, mm), the adjustable parameters {K and N) and the

dimensionless parameters (Ca, Re and Fr), which are a function of PL, G, Gm, r, fiL, and

95

y must be calculated. The density difference between liquid and gas phase (6,p) is used

instead of the liquid density to account for the effect of gas density (pG) on the foam

height. As illustrated in the correlation framework (Figure 5.1), the calculations of these

parameters requires input information from our static foaming experiments (i.e.,

experimental steady-state foam height (Heap, mm), liquid volume after supplying gas to

the test cell ( Vrll , cm3), MEA concentration (M, kmol/m3), solution temperature (T, °C),

superficial gas velocity (G , nun/s), solution volume (Vsol, cm3), CO2 loading (a(.o, , mol

CO2/mol MEA), water viscosity ( µH20 , mPas), and cross-sectional area of the test cell

(A, cm2)). The minimum superficial gas velocity (Gm , mm/s) is assumed to be zero for

the purpose of correlation development even though the actual minimum velocity in our

experiment was 0.12 mm/s. The correlation using O. of 0.12 mm/s yielded an average

absolute deviation (AAD) of 22%, which was 3% greater than %AAD of the correlation

using Om of zero. The calculations involve numerical iteration, subroutine calculations

of Ap r, ,a1,, and y, and statistical analysis. At the beginning of the correlation, initial

guesses for K, N, and r are required to predict the foam height, while those of P* and

coefficients (a i,...,a6; b 1,—,b6; c 1,...,c6) are required for computing Subroutines 2 and 3,

respectively. It is noted that besides two adjustable parameters, constants K and N for

Equation (2.16) (page 45), there are additional eighteen adjustable parameters (a 1,...,a6;

bi,...,b6; ci,...,c6) for the prediction of P* required in the correlation framework. After the

physical properties (i.e., pc, PL, y) are calculated, an average bubble radius predicted

using the Laplace equation (rL•predwied) is estimated as a final result of Subroutines 1 to 3.

96

y must be calculated. The density difference between liquid and gas phase (Ap) is used

instead of the liquid density to account for the effect of gas density (pc) on the foam

height. As illustrated in the correlation framework (Figure 5.1), the calculations of these

parameters requires input information from our static foaming experiments (i.e.,

experimental steady-state foam height (Hexp, mm), liquid volume after supplying gas to

the test cell (V[e", cm3), ME A concentration (M, kmol/m3), solution temperature (T, °C),

superficial gas velocity {G, mm/s), solution volume (Vsoi, cm3), CO2 loading (aC(h , mol

CCVmol MEA), water viscosity (nHlQ, mPa s), and cross-sectional area of the test cell

0 * (A, cm )). The minimum superficial gas velocity (Gm, mm/s) is assumed to be zero for

the purpose of correlation development even though the actual minimum velocity in our

experiment was 0.12 mm/s. The correlation using Gm of 0.12 mm/s yielded an average

absolute deviation (AAD) of 22%, which was 3% greater than %AAD of the correlation

using Gm of zero. The calculations involve numerical iteration, subroutine calculations

of Ap, r, Hi, and y, and statistical analysis. At the beginning of the correlation, initial

guesses for K, N, and r are required to predict the foam height, while those of P* and

coefficients (a/,...,a<s; bi,...,b6\ c/,...,c6) are required for computing Subroutines 2 and 3,

respectively. It is noted that besides two adjustable parameters, constants K and N for

Equation (2.16) (page 45), there are additional eighteen adjustable parameters (a/,...,a<5;

a,...,Ctf) for the prediction of P* required in the correlation framework. After the

physical properties (i.e., pc, pi, ML, Y) are calculated, an average bubble radius predicted

using the Laplace equation (r/ -/,r"to"/) is estimated as a final result of Subroutines 1 to 3.

96

Details of the calculations of average bubble radius and physical properties are given in

Section 5.2.

The statistical analysis, namely multiple non-linear regression with a stochastic

technique, is applied to obtain new constants, K and N, for the next iteration. This

statistical technique assists in minimizing the sum of squares of residuals (Sr) between the

Hew and the foam height recalculated from the r i' Predicled (or H). Note that this technique is

used for predictions of both average bubble radius and surface tension. The calculation is

terminated when the constants, K and N and Sr of the current iteration, equal those of the

previous iteration. Finally, the H and the calculated constants are reported as final

outputs. A summary of input parameters and simulation results is given in Appendix B.

97

Details of the calculations of average bubble radius and physical properties are given in

Section 5.2.

The statistical analysis, namely multiple non-linear regression with a stochastic

technique, is applied to obtain new constants, K and N, for the next iteration. This

statistical technique assists in minimizing the sum of squares of residuals (Sr) between the

Hexp and the foam height recalculated from the rL pred,cled (or H). Note that this technique is

used for predictions of both average bubble radius and surface tension. The calculation is

terminated when the constants, K and N and Sr of the current iteration, equal those of the

previous iteration. Finally, the H and the calculated constants are reported as final

outputs. A summary of input parameters and simulation results is given in Appendix B.

97

(START)

/Imidal guess r■r }7,r1 ; b „..., 1,4 ;c„...,c,

rSubroutine 2

(To find Pr"t er)

I-

4. Tr 7. aco2i

5. di3. Mr 6. V

S. PH2oi 9.A

trosso../

Calculate

1. Subroutine - Gas density (PG,) 2. Subroutine - Liquid density (PL.)

3. Subroutine - Liquid viscosity (etizi )

4. Subroutine - Surface tension (7;)

O

count =1

Subroutine 1

r(To find r,7'gd)

L

27, {1.1 - L -{

P - inside — P H,d i — P 11,f i — P i* ba

(a ,,...,a,)={a„...,a,rw

{b„...,b,}- (b„ be) w

count

Figure 5.1 Framework of the foam height correlation

98

(START)

/i.iti.i gu«s-K^,, NaM.„{r,}rr-', {p>}r"-;{., «,.•*, Clr"'/ r 4. TL 5. C,

6. K >W,

Calculate

1. Subroutine - Gas density (/)Cj) 3. Subroutine - Liquid viscosity (/itj)

2. Subroutine - Liquid density (PI.) 4. Subroutine - Surface tension (J*,)

count =1

(*>

SubroutineJ l(r<J /inrf r;-"-)

N'Nce.., {"/- «,}—

{',L={',}r {*,- >*.}={», A.}""

kL={/r)r {°i-

*««L-

Subroutine 2

!(ro find p;-"*")

[p I L r(l

_ p- ( count

Figure 5.1 Framework of the foam height correlation

98

Subroutine 3 riTo ar ; br ,...,br ;cr

L

cri Guess new coefficients: al, 14; bb....b6;

al(v-i,)'(mirs(Tir'(014z60„) for % ( fli" /1" ) 53PLI

(aco,, )16 for 53 < 73

ci(Vm,)"(Mir(Ti)44 (6) " (aco4)`' for %(11" — P112°1ifr"" — P7') 21-. 0.0

( or

=1

a,

.

br

I, „ .

b,'

„

cr

ly . = .1

c„.

.

7

I

\ ar a6 bT b6 cr ,c6 \

count

27i {riL,prediried) =

I'd hd

P — PH ,d i — PH J i —

{dp. 6 —6 rL' 'dia`d} (Rerfw"),„ — ' ' '''')

'P

PL,

iFerediceedL i _1( — )2 g r L ,predicard

!xi

hti

{H,}={4e."1{Ref'll Ca, Fr/predtried

J.,

Cakulate R2

( END

Figure 5.1 Framework of the foam height correlation (continued)

99

Sabrontiiie3 {to find aT,...,ar ;bT ;CT cfT Guess new coefficients: a/,..., a,;

rt

-,(^,)C1 (*0" ft)" (6,)" for %(^"~^ ' ] > 7 3

*r

YES

1 count

L--2?/

L-Art k " /XJ

W^L -Jp , Gi-Cm,)rLp"acu'\ \ ' ml f I

W^L - L •fa--<U1 „ L,prtdkK<l [

.* 1 J /xi 3

I

I

Adjust AT, yv

count = count +1 S„Kc„m-K,N,

Report Hi, K and N T

Calculate R2

"7x— ( END )

Figure 5.1 Framework of the foam height correlation (continued)

99

5.2 Subroutine calculations

5.2.1 Average bubble radius

This work deals with the average radius of bubbles that wander between the gas

dispersion layer and gas-liquid interface because they are less deviated than those in the

foam layer, which are tremendously subject to disproportionation or Ostwald ripening.

The average bubble radius was determined under different experimental conditions using

the Laplace equation (Bikerman, 1973) shown in Equation (2.3) (page 35). The capillary

pressure is instantaneously created across any curved interface with two principal radii of

curvature (RI and R2) at a given point between gas and liquid phases or two immiscible

liquids due to surface tension. With an assumption of the spherical gas bubbles, both radii

are at the gas side and equal to the average bubble radius (RI = R2 = r) resulting in a

positive capillary pressure. Thus, Equation (2.3) (page 35) can be rewritten as follows:

r = 2y r

(5.1)

The positive capillary pressure in Equation (5.1) is the difference between the pressure

inside (or at the concaved side) of the gas bubble (P,„,,,,k) and the pressure outside (or at

the convex side) of the gas bubble (P„„,„de) as written below:

P c P inside P ouiside (5.2)

Since it is difficult to measure Pinside of the compressed gas at the diffuser, Pinstde

is assumed to be atmospheric even though in reality, Pinside is above atmospheric pressure

due to the compression of gas through the diffuser and P - outside is approximately

atmospheric. Regardless of the assumed Amide, Pc must remain positive. The average

bubble radius can be calculated by combining Equations (5.1) and (5.2) as shown below:

100

5.2 Subroutine calculations

5.2.1 Average bubble radius

This work deals with the average radius of bubbles that wander between the gas

dispersion layer and gas-liquid interface because they are less deviated than those in the

foam layer, which are tremendously subject to disproportionation or Ostwald ripening.

The average bubble radius was determined under different experimental conditions using

the Laplace equation (Bikerman, 1973) shown in Equation (2.3) (page 35). The capillary

pressure is instantaneously created across any curved interface with two principal radii of

curvature (Ri and R2) at a given point between gas and liquid phases or two immiscible

liquids due to surface tension. With an assumption of the spherical gas bubbles, both radii

are at the gas side and equal to the average bubble radius (R/ = R2 = r) resulting in a

positive capillary pressure. Thus, Equation (2.3) (page 35) can be rewritten as follows:

P.=— (5.1) r

The positive capillary pressure in Equation (5.1) is the difference between the pressure

inside (or at the concaved side) of the gas bubble (Pmide) and the pressure outside (or at

the convex side) of the gas bubble (Poutside) as written below:

Pe = f.Inside ~ ̂ outside (5.2)

Since it is difficult to measure Pinside of the compressed gas at the diffuser, PinSide

is assumed to be atmospheric even though in reality, PinSide is above atmospheric pressure

due to the compression of gas through the diffuser and Poutside is approximately

atmospheric. Regardless of the assumed Pinside, Pc must remain positive. The average

bubble radius can be calculated by combining Equations (5.1) and (5.2) as shown below:

100

2y r =

kP inside P outside)

(5.3)

When a gas bubble is detached from the diffuser, the bubble is immediately exposed to

the pressure in the test cell as demonstrated in Figure 5.2. The outside pressure of the

bubble is composed of the hydrostatic pressures caused by gas dispersion and foam layers

above the bubble. Although the Laplace equation was established to predict the bubble

radius for static rather than dynamic systems, this limitation can be corrected to reflect

the actual turbulent surroundings of the bubble by adding the additional pressure term

called P* to account for the stress caused by the flow of other bubbles, the pressure

caused by the incoming gas flow, and the normal pressure due to the collision between

bubbles. Therefore, the P outsde can be expressed as:

P outstde = PH ,d PH,f P

PH ,d = P LSO d)ild

,f. = P Lg(1 — f)H exp

(5.4)

(5.5)

(5.6)

where P fbd and PM! are the hydrostatic pressures due to the gas dispersion layer defined

via Equation (5.5) (N/m2) and the foam layer defined via Equation (5.6) (N/m2),

respectively. The calculation of other parameters is given below:

v. cell v L — , s0a,

Ed v. cell

L

Vr" hd =

100A

H exP 11)0

exP

O A

101

When a gas bubble is detached from the diffuser, the bubble is immediately exposed to

the pressure in the test cell as demonstrated in Figure 5.2. The outside pressure of the

bubble is composed of the hydrostatic pressures caused by gas dispersion and foam layers

above the bubble. Although the Laplace equation was established to predict the bubble

radius for static rather than dynamic systems, this limitation can be corrected to reflect

the actual turbulent surroundings of the bubble by adding the additional pressure term

called P* to account for the stress caused by the flow of other bubbles, the pressure

caused by the incoming gas flow, and the normal pressure due to the collision between

bubbles. Therefore, the Poutside can be expressed as:

where PN,D and PH,/ are the hydrostatic pressures due to the gas dispersion layer defined

via Equation (5.5) (N/m2) and the foam layer defined via Equation (5.6) (N/m2),

respectively. The calculation of other parameters is given below:

outside

(5.5)

(5.4)

(5.6)

yce l l _ y r L v sol (5.7)

cell

(5.8)

H — EXP exp 100 A

(5.9)

101

where ed is the gas fraction in the gas dispersion layer calculated using Equation (5.7), hd

is the height of the gas dispersion layer (m) calculated using Equation (5.8), Hew is the

experimental steady-state foam height (m), which is calculated from the experimental

steady-state foam volume (ve,p, cm3) shown in Equation (5.9), and ef is the gas fraction

in the foam layer, which is assumed to be equal to 0.75 (Watstra, 1989) from the

literature review summarized in the table in Figure 2.1 (page 33). This void fraction was

expected to represent a typical morphology of the foams observed during the static

experiments as shown in Figure 5.3, which was a combination of Kugelschaum and

Polyederschaum. Tiny gas bubbles were formed after N2 was dispersed through the

diffuser. These bubbles hit and sat at the interface to form Kugelschaum, which was

mainly composed of spherical bubbles. Then, Kugelschaum started to change to

Polyederschaum, wherein most of the spherical bubbles were deviated to the polyhedral

bubbles.

By substituting Equation (5.4) into Equation (5.3), the final relationship based on

the Laplace equation to predict r is expressed as

r= 2y

inside — PH ,d PH ,f — Ps(5.10)

where P* can be determined using the following empirical correlations, depending upon

surface viscosity. These P* correlations were obtained by regressing our experimental

data given in Chapter 4 with R2 of 0.96.

P* = 109925.52 T3.436x10-3 65.3840-7

v m

1.9240-2 1.50x10-3 3.004 0-4r sat "*CO2

104410 06 ML93X1°-3 T6.83x10-3O4.64104

where %(PL — PH20 j < 53

PL (5.11)

u lA040-2 , 3.62x10-3 so /

where 53 < %(PL — PH20

73 (5.12) 4.4co, PL

102

where £d is the gas fraction in the gas dispersion layer calculated using Equation (5.7), hd

is the height of the gas dispersion layer (m) calculated using Equation (5.8), HEXP is the

experimental steady-state foam height (m), which is calculated from the experimental

steady-state foam volume (oexp, cm3) shown in Equation (5.9), and £/ is the gas fraction

in the foam layer, which is assumed to be equal to 0.75 (Watstra, 1989) from the

literature review summarized in the table in Figure 2.1 (page 33). This void fraction was

expected to represent a typical morphology of the foams observed during the static

experiments as shown in Figure 5.3, which was a combination of Kugelschaum and

Polyederschaum. Tiny gas bubbles were formed after N2 was dispersed through the

diffuser. These bubbles hit and sat at the interface to form Kugelschaum, which was

mainly composed of spherical bubbles. Then, Kugelschaum started to change to

Polyederschaum, wherein most of the spherical bubbles were deviated to the polyhedral

bubbles.

By substituting Equation (5.4) into Equation (5.3), the final relationship based on

the Laplace equation to predict r is expressed as

r = - ^^ (5.10) Y inside ~ PhM ~ PftJ ~ P )

where P* can be determined using the following empirical correlations, depending upon

surface viscosity. These P* correlations were obtained by regressing our experimental

data given in Chapter 4 with R2 of 0.96.

109925.52 r3 06x,r5G5-38xI0"7 . ^ jyi.92xio~2 wi.50xi<r' 3.ooxio-4 where ^

V sol m aCO, Hi. <53 (5.11)

IfM/M AA£ iyl.93xl0"3 7-6.83x10"' ^4.64x10^ (., ,, \ P- = 104410.06M T G ^ tH40x10-2 3.62X10"' y sol aC02 ML

<73 (5.12)

102

P. = 104167.39 1 1524°-47,2.50.10-3

69.61x10-2 a l:01,10-3 where %(/4/.. PH20 > 73

PL (5.13)

where T is solution temperature (°C), M is MEA concentration (kmol/m3), V301 is solution

volume (cm3), a co2 is CO2 loading (mol CO2/mol MEA), G is in the unit of m/s for

Equations (5.11) — (5.13). The sensitivity of coefficients on 1)* are studied by varying

±10% from the reported values. Results in Table 5.1 indicate that the most sensitive

coefficients are the coefficients al, b1 and ci (see Figure 5.1, page 98). Note that the

average bubble radius calculated in this work ranged from 0.09 to 0.47 mm. This range is

in good agreement with the bubble radius (0.005-0.5 mm) indicated in ASTM D892,

which creates the gas dispersion layer beneath the foam layer (ASTM, 1999).

103

P' = 104167.39 M 39 A/3'52*10' 7,2-50xl°3

where %f^ ^2°1>73 (5.13) I VL J

9.61x10 /•l.31x10* sol

,1.01x10

CO,

where T is solution temperature (°C), M is MEA concentration (kmol/m3), Vso/ is solution

volume (cm3), aCOi is CO2 loading (mol C02/mol MEA), G is in the unit of m/s for

Equations (5.11) - (5.13). The sensitivity of coefficients on P* are studied by varying

±10% from the reported values. Results in Table 5.1 indicate that the most sensitive

coefficients are the coefficients ai, bj and c/ (see Figure 5.1, page 98). Note that the

average bubble radius calculated in this work ranged from 0.09 to 0.47 mm. This range is

in good agreement with the bubble radius (0.005-0.5 mm) indicated in ASTM D892,

which creates the gas dispersion layer beneath the foam layer (ASTM, 1999).

103

Table 5.1 Sensitivity analysis of coefficients used in the prediction of P'

Coefficien

t

% variation in P5

Prediction with coefficient +10% Prediction with coefficient - 10%

al - 10 10

a2 1 -1

a3 0.01 - 0.01

04 - 0.11 0.11

a5 4.06x10-5 - 4.06x10-5

a6 - 3.06x10-3 3.06x10-3

b 1 - 10.00 10.00

b2 0.83 - 0.84

b3 - 0.03 0.03

b4 - 0.28 0.27

b5 0.03 - 0.03

b6 - 0.04 0.04

CI - 10.00 10.00

C2 7.54 - 8.16

C3 - 0.06 0.06

C4 - 0.10 0.10

C5 - 7.43 6.92

C6 - 0.01 0.01

104

Table 5.1 Sensitivity analysis of coefficients used in the prediction of P*

Coefflcien % variation in P*

t Prediction with coefficient +10% Prediction with coefficient - 10%

O] -10 10

02 1 -1

a3 0.01 -0.01

a4 -0.11 0.11

a.j 4.06x10-5 - 4.06x 10"5

C16 - 3.06x103 3.06x10"3

b, - 10.00 10.00

b2 0.83 -0.84

b3 -0.03 0.03

b4 -0.28 0.27

b5 0.03 -0.03

b6 -0.04 0.04

Cl -10.00 10.00

C2 7.54 -8.16

C3 -0.06 0.06

c4 -0.10 0.10

Cs -7.43 6.92

C6 -0.01 0.01

104

Dispersing gas

Gas dispersion P*

Figure 5.2 Schematic diagram of the pressures exerted on the gas bubble in the liquid

solution

105

Dispersing gas }

Foam

Interface

Gas dispersion

Air

M

* 0 0

tr 0

b °

Uqufd"

1

o-

• • : 1 3 . 0 , > - : 1

PH,f

PH,C

Figure 5.2 Schematic diagram of the pressures exerted on the gas bubble in the liquid

solution

105

Polyederschaum

Kugelschaum

Figure 5.3 Example of the foam observed in the static foaming experiment

(original in color)

Polyederschaum

Kugelschaum

Figure 53 Example of the foam observed in the static foaming experiment

(original in color)

106

5.2.2 Density

Since the nitrogen (N2) gas was assumed to follow the ideal gas law, the gas

density was calculated using the following equation:

P insicle(M N 2 ) G =

RT (5.14)

where pp is the density of N2 (kg/m3), Pi„,,d, is the pressure inside the gas bubble

(assumed to be equal to 101325 N/m2), R is the universal gas constant, MWN2 is the

molecular weight of N2, and T is the solution temperature (K).

The liquid density of the CO2-loaded aqueous MEA solutions at different CO2

loadings, MEA concentrations, and temperatures was estimated using the correlation

developed by Weiland and his team (Weiland et al., 1998):

[ X MEAMW MEA X H2OMW H 20 + X CO2 MW CO2

PL = 1000

V MEA =

X MEA VMEA li 2 0 + x V +xCO2 VCO2 +xMEA xH20 V* +xMEAXCO2 V ** 110

MW MEA

—5.35162x10-7 T2 —4.51417x10-4 T+1.19451

(5.15)

(5.16)

where PL is the density of the liquid solution (kg/m3); xi, MK, and V, are the mole

fraction, molecular weight, and molar volume (ml/mol), respectively, of MEA, water, and

CO2; T is the solution temperature (K); if is the constant equal to -1.8218; and V** is the

molar volume due to the interaction between MEA and CO2, which is equal to zero. The

standard deviation of the predicted value by the correlation is 0.00221.

107

5.2.2 Density

Since the nitrogen (N2) gas was assumed to follow the ideal gas law, the gas

density was calculated using the following equation:

Pc (5.14)

where pa is the density of N2 (kg/m3), P,„side is the pressure inside the gas bubble

(assumed to be equal to 101325 N/m ), R is the universal gas constant, MWNi is the

molecular weight of N2, and T is the solution temperature (K).

The liquid density of the C02-loaded aqueous MEA solutions at different CO2

loadings, MEA concentrations, and temperatures was estimated using the correlation

developed by Weiland and his team (Weiland et al., 1998):

pL =1000 X MEA M^mea + xh2o^Wh2o + xco2 M^co2

XMEA^MEA +XH,()VH20 + XC()2 K'O, + XMEAXH,0^ + XMEAXCoJ^ (5.15)

MW VMEA = r—. ^ J (5.16)

-5.35162x10 r -4.51417x10 T + 1.19451

where pi is the density of the liquid solution (kg/m3); jc„ MWh and V, are the mole

fraction, molecular weight, and molar volume (ml/mol), respectively, of MEA, water, and

CO2; T is the solution temperature (K); V* is the constant equal to -1.8218; and V*" is the

molar volume due to the interaction between MEA and CO2, which is equal to zero. The

standard deviation of the predicted value by the correlation is 0.00221.

107

5.2.3 Viscosity

The liquid viscosity (PL) of the CO2-loaded aqueous MEA solutions was

estimated using the following correlation developed by Weiland and his team (Weiland et

al., 1998):

L = x

PH20

}(21.186m + 2373) [aco, (0.01015m+ 0.0093T —2.2589)+ dm

T2 (5.17)

where pi, and 1111,0 are the viscosities of the aqueous MEA solution and water,

respectively (mPa s); m is the mass percent of MEA; and T is the solution temperature

(K). The standard deviation of the predicted value by the correlation is 0.0732.

5.2.4 Surface tension

Since the CO2-loaded aqueous MEA solutions were considered to be a tertiary

system, the work of Chunxi and his colleagues (Chunxi et al., 2000) was extended to

predict surface tension of the solutions using Gibbs free energy (G, J) needed to expand

per surface area (As, m2) at constant temperature (7), pressure (P), and composition i (x,),

as shown below:

Y-la 1,p,„

(5.18)

For a multi-component non-ideal solution under isothermal and isobaric conditions, the

molar Gibbs free energy of the bulk solution, which was assumed to be uniform across

the surface, was equal to the sum of the molar Gibbs free energy of the ideal solution

(G,dead, J) and the molar excess Gibbs free energy (G.„, J), which in this work was

predicted by the Wilson equation, as shown below:

108

5.23 Viscosity

The liquid viscosity (JIL) of the C02-loaded aqueous MEA solutions was

estimated using the following correlation developed by Weiland and his team (Weiland et

al., 1998):

(21.186/W+2373) [aCOi (0.01015m + 0.009371 - 2.2589)+l]m = exp<

Mh2O (5.17)

where Hi and //Wj0 are the viscosities of the aqueous MEA solution and water,

respectively (mPa s); m is the mass percent of MEA; and T is the solution temperature

(K). The standard deviation of the predicted value by the correlation is 0.0732.

5.2.4 Surface tension

Since the CC>2-loaded aqueous MEA solutions were considered to be a tertiary

system, the work of Chunxi and his colleagues (Chunxi et al., 2000) was extended to

predict surface tension of the solutions using Gibbs free energy (G, J) needed to expand

per surface area (As, m2) at constant temperature (7), pressure (P), and composition i (x,),

as shown below:

For a multi-component non-ideal solution under isothermal and isobaric conditions, the

molar Gibbs free energy of the bulk solution, which was assumed to be uniform across

the surface, was equal to the sum of the molar Gibbs free energy of the ideal solution

(fiideal* J) and the molar excess Gibbs free energy (Gexcess, J), which in this work was

predicted by the Wilson equation, as shown below:

108

G = G„kai + Gexcess (5.19)

G =(Ex,G,

v.

+ RT

— a

xiln xi j— RTExEln(ExiA y ) (5.20)

A = —v

exp (i~j) (5.21) RT

where ay is the constant representing the difference between interaction energy of

molecular pair ij (U) and that of molecular pair ii (U„) and v, and vv are the molar volume

of pure component i and j at constant temperature T (K), of which its ratio between two

components is equal to one (Chunxi et al., 2000). Therefore, the surface tension for the

multi-component system can be predicted by incorporating Equation (5.20) into Equation

(5.18) and differentiating it with respect to the surface area (A3), resulting in:

ia(u„, -u„)) y.E x,y, — RTE xe Ex. Exin, RT aAs ) T ,P

(5.22)

From Equation (5.22), there were two types of adjustable parameters: Uy — U„

accounting for the local composition effect and (a(Uy -u ,,)/ aAt,p, representing the

excess surface tension. Therefore, twelve adjustable parameters must be obtained for the

surface tension model (i.e., U12 - U11, U21 - U22, U13 - Ul 1, U3, - U33, U23 - U22,

U32 - U22, (a(U12 -U 11 )/ aA r (a(u2i -u22 )/air)T,p,x, (a(u,, - U ,,)/

(a(u3,-U33)/ (aW23-(122)/air),,p.„,, (a(u32- U 33 )/a4s),,,p,x,). Subscripts 1,

2, and 3 are MEA, CO2, and water, respectively. The twelve adjustable parameters were

minimized by assuming that the interaction of molecular pair ij (U,J) is equal to the

arithmetic average between those of the same molecular pair ii (U„) and jj (Un) (Chunxi

et al., 2000). As a result, six adjustable parameters remained for the correlation of surface

tension as listed below:

109

excess (5.19)

G = fZX'G' + RTYtX.lnx,]- RT^x. ln Y,xjAV \ i i J i \ j j

(5.20)

v , - a„ -^-exp—^ ( i*j) (5.21)

where ay is the constant representing the difference between interaction energy of

molecular pair ij (U,j) and that of molecular pair ii (£/,,) and v, and y, are the molar volume

of pure component i and j at constant temperature T (K), of which its ratio between two

components is equal to one (Chunxi et al., 2000). Therefore, the surface tension for the

multi-component system can be predicted by incorporating Equation (5.20) into Equation

(5.18) and differentiating it with respect to the surface area (As), resulting in:

From Equation (5.22), there were two types of adjustable parameters: Uy - U t i

excess surface tension. Therefore, twelve adjustable parameters must be obtained for the

surface tension model (i.e., Un - Uu, U21 - U22, U13 - (///, Ua - U33, U23 - U22,

u,2 - u2!, (a(ul2-u„)/dA-l(d(un-uI2)/8A-lJ,Ji,

(etUv-Uj/dA'l^, {stU^-U^/dA-l^, Subscripts 1,

2, and 3 are MEA, CO2, and water, respectively. The twelve adjustable parameters were

minimized by assuming that the interaction of molecular pair ij (Uy) is equal to the

arithmetic average between those of the same molecular pair ii (Uu) and jj ([Uy) (Chunxi

et al., 2000). As a result, six adjustable parameters remained for the correlation of surface

tension as listed below:

(5.22)

accounting for the local composition effect and (d(t/(/ - Un)/ dA s ̂ ^ representing the

109

U12 - U11 (U21 - U22)

U13 - Ull - (U31 - U33)

U23 - U22 = - (U32 - U22)

(a(u,2 —u11) a(u2 ( ,—u22))aAs aAs

(a(u13 —u11) (a(u3,—u33))aAs 0A3

49(U23 - U 22 )j o(u32 - U 33 )J

aAs aAs T ,P „xi

The final correlation of the surface tension is presented below:

y=1000

x,y, + x2 y2 + x3y3

— RT

ix ran,o+x (an,3 x, rx ran,,)+x ran 3 )) x2 A,2 +x3A,3 aAs ) aAs)) x,A 2,+x3A 2, 1 ) ads2 ))

x3 Cx1

ran21 + x,A3, +x2A32 aAs ) ,

(5.23)

(5.24)

(5.25)

(5.26)

(5.27)

(5.28)

(5.29)

In order to find the values of these parameters, a measurement of surface tension

for aqueous solutions of MEA containing CO2 was carried out experimentally by

applying the spinning drop method using a Spinning Drop Interfacial Tensiometer Model

510 (Temco, Inc, OK, USA). The experimental conditions and results of the

measurement were reported in Section 4.4 (Figure 4.7a, page 81). Multiple non-linear

regression with a stochastic technique was used to minimize the sum of squares of

residuals between the predicted surface tensions and the experimental ones. All the

correlation parameters needed for Equation (5.29) were determined and are given in

Table 5.2 with R2of 0.89.

110

U I2-U I I = -(U2 , -U22)

U I 3-U„ = -{U3 I-U3 3)

U2 3-U22=-(U32-U22)

(d(u„-uj (a(u2 , -uj)

I av , I ar J

ra(t/13-(/Mr| = . (3P„-Vn)) av ) T.Psi ar )r

%U*-UnY) (d(U,2

ar J T f j C j a4' J,

T.PJ,

(5.23)

(5.24)

(5.25)

(5.26)

(5.27)

(5.28) r.Pjj

The final correlation of the surface tension is presented below:

y = 1000

xj, +x2y2 +x3y }

x,

-RT Jf2A|2 +X3A,j

( f ao

+ AT, ' 3A | 3 Y|

V ) , dA' )) X,A2) +X}A2

8Aj, H dAs

+ x, dAy 8AS

*1^31 x2^-n + x2

\

l SA' J kdA' J /

(5.29)

In order to find the values of these parameters, a measurement of surface tension

for aqueous solutions of MEA containing CO2 was carried out experimentally by

applying the spinning drop method using a Spinning Drop Interfacial Tensiometer Model

510 (Temco, Inc, OK, USA). The experimental conditions and results of the

measurement were reported in Section 4.4 (Figure 4.7a, page 81). Multiple non-linear

regression with a stochastic technique was used to minimize the sum of squares of

residuals between the predicted surface tensions and the experimental ones. All the

correlation parameters needed for Equation (5.29) were determined and are given in

Table 5.2 with/ôf 0.89.

110

Table 5.2 Adjustable parameters for the MEA-0O2-water system

System aii or (14 — UN) (a(u,,—uil ))

aAs

MEA (1) — Water (3) 8094.50205 0.005800471

MEA (1) — CO2 (2) -105.88605 -0.114570736

CO2 (2) — Water (3) -943.07398 -0.558414553

Table 5.2 Adjustable parameters for the MEA-CCh-water system

System ay or (Uij - Ua) 3[v t-u„y

dA5 ' T,P,x

MEA (1) - Water (3)

MEA (1) - C02(2)

CO2 (2) - Water (3)

8094.50205

-105.88605

-943.07398

0.005800471

-0.114570736

-0.558414553

111

53 Foam height prediction results

With 134 experimental foaming data sets, an empirical correlation as shown

below and a series of subroutine modules for physical property estimation for the CO2-

loaded aqueous MEA system were successfully developed. The foam height correlation

comprises parameters including bubble radius, surface tension of liquid, viscosity of

liquid, difference in density of gas and liquid, and superficial gas velocity; constants K of

4394 and N of -1.30; and dimensionless Ca, Re, and Fr in ranges of 2.0x10-3 — 6.3x 10-2,

5.0 — 276.4, and 0.01 — 0.89, respectively. The summary of these dimensionless numbers

are given in Appendix B. The correlation fits well with the experimental data as indicated

by a R2 of 0.88 as illustrated in Figure 5.4. The detailed explanation for foaming

behaviour with respect to process parameters was previously given in Chapter 4 while the

discussions of correlation prediction are given below.

H = 4394 r • ir60

( . .30" G

V.30

I

(5.30)

112

S3 Foam height prediction results

With 134 experimental foaming data sets, an empirical correlation as shown

below and a series of subroutine modules for physical property estimation for the CO2-

loaded aqueous MEA system were successfully developed. The foam height correlation

comprises parameters including bubble radius, surface tension of liquid, viscosity of

liquid, difference in density of gas and liquid, and superficial gas velocity; constants K of

4394 and Nof-1.30; and dimensionless Ca, Re, and Fr in ranges of 2.0xl0"3 - 6.3xl0"2,

5.0 - 276.4, and 0.01 - 0.89, respectively. The summary of these dimensionless numbers

are given in Appendix B. The correlation fits well with the experimental data as indicated

by a R2 of 0.88 as illustrated in Figure 5.4. The detailed explanation for foaming

behaviour with respect to process parameters was previously given in Chapter 4 while the

discussions of correlation prediction are given below.

v /

(5.30)

112

0.0 10.0 20.0 30.0 40.0 50.0 60.0 Hem, (mm)

Figure 5.4 Parity chart between Hew and H for the foam height correlation (dashed lines

represent 95% confidence interval)

113

60.0

50.0

40.0

| 30.0

X 20.0

XX

10.0

0.0 0.0 10.0 20.0 30.0 40.0 50.0 60.0

Hexp(mm)

Figure 5.4 Parity chart between HEXP and //for the foam height correlation (dashed lines

represent 95% confidence interval)

113

The correlation can also describe the behaviour of foaming with changes in

process conditions. From Figure 5.5, the correlation gives good predictions compared to

the experimental data at the superficial gas velocity ranging from 0.12 to 0.94 mm/s. The

errors between the predicted foam heights and the experimental results are very small,

although a proportional increase in the experimental foam height with the superficial gas

velocity is only achieved at a certain range of the superficial gas velocity. As illustrated

in Figure 5.6, the experimental results show that the effect of the initial solution volume

on foam height is significant when the initial solution volume increases from 200 to 400

cm3 and becomes insignificant when the initial solution volume is greater than 400 cm3.

The predicted results show good agreement with the experimental data except for some

deviations observed at the minimum and maximum initial solution volumes. For this

correlation, the effect of initial solution volume is embedded in the calculation of the

average bubble radius through the prediction of P ju and P* instead of 6,„ , which can

implicitly account for this effect as previously discussed by Pilon et al. (2001). Thus,

incorporating 6„, into the correlation could possibly reduce these deviations. A further

development is required to explicitly recognize the initial solution volume as one of the

independent parameters in the future foam height correlation.

Figures 5.7 — 5.9 demonstrated that the correlation generally yields good

prediction of the foam height as the MEA concentration, CO2 loading, and solution

temperature are changed. However, a variation in the predicted and experimental foam

heights is noticeable at higher solution temperatures. Not only does the higher solution

temperature weaken the stability of foam by lowering liquid viscosity, but it also creates

a more severely turbulent environment caused by violent bubble movements, which can

disturb an existing foam layer. The latter can be observed from the experiment. Although

114

The correlation can also describe the behaviour of foaming with changes in

process conditions. From Figure 5.5, the correlation gives good predictions compared to

the experimental data at the superficial gas velocity ranging from 0.12 to 0.94 mm/s. The

errors between the predicted foam heights and the experimental results are very small,

although a proportional increase in the experimental foam height with the superficial gas

velocity is only achieved at a certain range of the superficial gas velocity. As illustrated

in Figure 5.6, the experimental results show that the effect of the initial solution volume

on foam height is significant when the initial solution volume increases from 200 to 400

cm and becomes insignificant when the initial solution volume is greater than 400 cm .

The predicted results show good agreement with the experimental data except for some

deviations observed at the minimum and maximum initial solution volumes. For this

correlation, the effect of initial solution volume is embedded in the calculation of the

average bubble radius through the prediction of PHJ and P* instead of Gm, which can

implicitly account for this effect as previously discussed by Pilon et al. (2001). Thus,

incorporating Gm into the correlation could possibly reduce these deviations. A further

development is required to explicitly recognize the initial solution volume as one of the

independent parameters in the future foam height correlation.

Figures 5.7 - 5.9 demonstrated that the correlation generally yields good

prediction of the foam height as the MEA concentration, C02 loading, and solution

temperature are changed. However, a variation in the predicted and experimental foam

heights is noticeable at higher solution temperatures. Not only does the higher solution

temperature weaken the stability of foam by lowering liquid viscosity, but it also creates

a more severely turbulent environment caused by violent bubble movements, which can

disturb an existing foam layer. The latter can be observed from the experiment. Although

114

the correlation uses Re to characterize the flow regimes, no proper Re criteria for

different flow regimes, to the best of our knowledge, has been provided for this particular

system. Then, it is possible that this particular correlation only works well in the laminar

and possibly transition regime. An additional parameter or another correlation for a

turbulent regime should be considered in future work.

115

the correlation uses Re to characterize the flow regimes, no proper Re criteria for

different flow regimes, to the best of our knowledge, has been provided for this particular

system. Then, it is possible that this particular correlation only works well in the laminar

and possibly transition regime. An additional parameter or another correlation for a

turbulent regime should be considered in future work.

115

70.0

60.0

E

0 40.0

E 30.0 0 u. 20.0

10.0

0.0 0.00 0.20 0.40 0.60 0.80

Superficial gas velocity(mm/s)

(a) 2.0 kmol/m3

70.0

60.0 •

E 50.0

a 40.0 - 0

30.0 - o IL 20.0 -

10.0 -

0.0 0.00 0.20 0.40 0.60 0.80

Superficial gas velocity(mm/s)

(b) 5.0 kmol/m3

Figure 5.5 Simulation results of predicted foam height with respect to superficial gas

velocity (solution volume = 400 cm3, CO2 loading = 0.40 mol/mol and

solution temperature = 40°C) with MEA concentration (a) 2.0 kmol/m3 and

(b) 5.0 kmol/m3

1.00

1.00

116

70.0

60.0

| 50.0

% 40.0 o

E 30.0 CO o "• 20.0

10.0

0.0

_ •

—•— Experiment

— P r e d i c t e d

0.00 0.20 0.40 0.60 0.80 Superficial gas velocity(mm/s)

(a) 2.0 kmol/m3

1.00

70.0

60.0

| 50.0

» 40.0

E 30.0 (0 o

20.0

10.0 Experiment

Predicted 0.0

0.00 1.00 0.20 0.40 0.60 0.80 Superficial gas velocity(mm/s)

(b) 5.0 kmol/m3

Figure 5.5 Simulation results of predicted foam height with respect to superficial gas

velocity (solution volume = 400 cm3, CO2 loading = 0.40 mol/mol and

solution temperature = 40°C) with MEA concentration (a) 2.0 kmol/m3 and

(b) 5.0 kmol/m3

116

40.0

30.0

I E .*.. f o 20.0 - m.-.

E 10 .0- L ..

0.0

.,. - - - "" • . ..

, 4c

Experiment

---x-- Predicted

0 •

200 400 600 Solution volume (cm3)

800

Figure 5.6 Simulation results of predicted foam height with respect to solution volume

(MEA concentration = 2.0 kmol/m3, superficial gas velocity = 0.57 mm/s,


117

40.0

30.0 -E E

I 20.0 -© JZ E to £ 10.0 -


—x— Predicted 0.0

0 200 400 600 800 Solution volume (cm3)

Figure 5.6 Simulation results of predicted foam height with respect to solution volume

(MEA concentration = 2.0 kmol/m3, superficial gas velocity = 0.57 mm/s,


117

40.0

-i- 30.0 -E . .c .:2: 20.0 -

i o IL 10.0 -

0.0

0.0

■ ■

--0— Experiment --a--- Predicted

2.0 4.0 6.0 MEA concentration (kmolim3)

(a) Absorber top

0.0 2.0 4.0 6.0 MEA concentration (kmoUm3)

(b) Absorber bottom

Figure 5.7 Simulation results of predicted foam height with respect to MEA

concentration (superficial gas velocity = 0.57 mm/s and solution volume =

400 cm3); (a) absorber top condition: CO2 loading = 0.20 mol/mol and

solution temperature = 40°C and (b) absorber bottom condition: CO2 loading

= 0.40 mol/mol and solution temperature = 60°C

8.0

8.0

118


Predicted

I 1 1 I 1 I * 2.0 4.0 6.0 8.0


(a) Absorber top

? 30.0 E,

B) ® 20.0

E (0 o u.

10.0

0.0 0.0 2.0 4.0 6.0 8.0


(b) Absorber bottom

Figure 5.7 Simulation results of predicted foam height with respect to MEA

concentration (superficial gas velocity = 0.57 mm/s and solution volume =

400 cm3); (a) absorber top condition: CO2 loading = 0.20 mol/mol and

solution temperature = 40°C and (b) absorber bottom condition: CO2 loading

= 0.40 mol/mol and solution temperature = 60°C

10.0 -

0.0 --0.0

1

•


— P r e d i c t e d I 1 1 1 I 1 I

118

50.0 E 40.0 -. .1.a. 30.0 - co 1 20.0 - i 10.0 -0

13. 0.0 0.00 0.10 0.20 0.30 0.40 0.50 0.60 CO2 loading in solution

(mol CO2/mol MEA)(a) 40°C

50.0 E 40.0 - .c 4- 30.0 - a' 'd 20.0 - i 10.0 -0 w 0.0

0.00 0.10 0.20 0.30 0.40 0.50 0.60 CO2 loading in solution (mol CO2/mol MEA)

(b) 60°C 50.0 ....... - E 40.0 -EFE-. 30.0 -

en -'m 20.0 - .c . i 10.0 - o 'LI' 0.0

0.00 0.10 0.20 0.30 0.40 0.50 0.60 CO2 loading in solution (mol CO2/mol MEA)

(c) 90°C

Figure 5.8 Simulation results of predicted foam height with respect to CO2 loading

(MEA concentration = 5.0 kmol/m3, superficial gas velocity = 0.57 mm/s and

solution volume = 400 cm3) with solution temperature (a) 40°C, (b) 60°C, and

(c) 90°C

119

® 20.0

i 10.0 o "" 0.0

— E x p e r i m e n t Predicted T 1 1 1 1 I 1 1 1 1 1—

0.00 0.10 0.20 0.30 0.40 0.50 0.60 COz loading in solution

(mol COJmol MEA)

(a) 40°C

50.0

1 40.0

2 30.0 o> | 20.0

i 10.0 o u. 0.0

9 % ir-i"

•» * xr — E x p e r i m e n t •» * xr

Predicted

0.00 0.10 0.20 0.30 0.40 0.50 0.60 COz loading in solution

(mol COj/mol MEA)

(b) 60°C

Expenment Predicted E 40.0

«- 30.0

3 20.0

§ 10.0

0.00 0.10 0.20 0.30 0.40 0.50 0.60 C02 loading in solution

(mol C02/mol MEA)

(c) 90°C

Figure 5.8 Simulation results of predicted foam height with respect to CO2 loading

(MEA concentration = 5.0 kmol/m3, superficial gas velocity = 0.57 mm/s and

solution volume = 400 cm3) with solution temperature (a) 40°C, (b) 60°C, and

(c) 90°C

119

0.0 40.0 50.0 60.0 70.0 80.0


(a) 0.20 mol CO2/mol MEA

60.0

50.0 E

E-; 40.0 .c p) 2 30.0 -

Io u. 20.0 -

90.0

10.0 -

0.0 40.0

--s— Experiment

- - x- - - Predicted

--x

50.0 60.0 70.0 80.0 Solution temperature (°C)

90.0

(b) 0.40 mol CO2/mol MEA

Figure 5.9 Simulation results of predicted foam height with respect to solution

temperature (MEA concentration = 5.0 kmol/m3, superficial gas velocity =

0.57 mm/s and solution volume = 400 cm3) with CO2 loading (a) 0.20

mol/mol and (b) 0.40 mol/mol

120

60.0

_ 50.0 E E r 40.0 f JSP £ 30.0 E «o £ 20.0

10.0

0.0 40.0 50.0 60.0 70.0 80.0 90.0


(a) 0.20 mol CCVmol MEA

60.0 -| —•— Experiment

50.0 1( Predicted E

§ 40.0 £ O) 1 30.0 E n £ 2 0 . 0 .

10.0

0.0 40.0 50.0 60.0 70.0 80.0 90.0


(b) 0.40 mol CCVmol MEA

Figure 5.9 Simulation results of predicted foam height with respect to solution

temperature (MEA concentration = 5.0 kmol/m3, superficial gas velocity =

0.57 mm/s and solution volume = 400 cm3) with CO2 loading (a) 0.20

mol/mol and (b) 0.40 mol/mol


-Hi— Experiment

Predicted

120

5.3.1 Parametric effects

From Equation (5.30), the foam height is a function of bubble radius, difference

in density of gas and liquid, surface tension of liquid, viscosity of liquid, and superficial

gas velocity. The bubble radius has an inverse relationship with the foam height, which is

similar to the findings from Zhang and Fruehan (1995). That is, the foam height increases

with a decrease in the bubble radius due to an enhancement of foam stability. Very

minute bubbles with a spherical shape are much more stable than coarse bubbles with a

polyhedral shape. This is because the coarse bubbles are susceptible to bubble

coalescence, which causes bubble bursting. The density difference between gas and

liquid plays a role in foam height through foam drainage. The greater the density

difference, the lower the foam height. The increase in the density difference between gas

and liquid helps accelerate the velocity of liquid (u, mm/s) in the vertical lamella flowing

down from between the two parallel and immobile films with the thickness of 5 due to

the gravitational field to the bulk solution as expressed below (Bikerman, 1973):

„,s 2

= "I/ u12µ L

(5.31)

This deteriorates the stability of foam through drainage of liquid solution in the lamella to

the bulk solution. Note that since the gas density near atmospheric conditions is three

orders of magnitude smaller than the liquid density, the density difference between gas

and liquid is in this case mainly refers to the liquid density.

The surface tension affects the foam height in an inverse fashion as indicated by

the term 7/r16 of Equation (5.30) where r is proportional to y at a given capillary

pressure (Equation (5.3), page 101). A decrease in the surface tension causes the foam

height to rise because the minimum work required to expand the interface, or interfacial

121

5.3.1 Parametric effects

From Equation (5.30), the foam height is a function of bubble radius, difference

in density of gas and liquid, surface tension of liquid, viscosity of liquid, and superficial

gas velocity. The bubble radius has an inverse relationship with the foam height, which is

similar to the findings from Zhang and Fruehan (1995). That is, the foam height increases

with a decrease in the bubble radius due to an enhancement of foam stability. Very

minute bubbles with a spherical shape are much more stable than coarse bubbles with a

polyhedral shape. This is because the coarse bubbles are susceptible to bubble

coalescence, which causes bubble bursting. The density difference between gas and

liquid plays a role in foam height through foam drainage. The greater the density

difference, the lower the foam height. The increase in the density difference between gas

and liquid helps accelerate the velocity of liquid (u, mm/s) in the vertical lamella flowing

down from between the two parallel and immobile films with the thickness of 5 due to

the gravitational field to the bulk solution as expressed below (Bikerman, 1973):

u =Apgd_

12/i,

This deteriorates the stability of foam through drainage of liquid solution in the lamella to

the bulk solution. Note that since the gas density near atmospheric conditions is three

orders of magnitude smaller than the liquid density, the density difference between gas

and liquid is in this case mainly refers to the liquid density.

The surface tension affects the foam height in an inverse fashion as indicated by

the term /r16 of Equation (5.30) where r is proportional to y at a given capillary

pressure (Equation (5.3), page 101). A decrease in the surface tension causes the foam

height to rise because the minimum work required to expand the interface, or interfacial

121

free energy, is decreased, and consequently, foam formation is promoted. The surface

tension also plays a role in foam stability through the Marangoni effect occurring when

there is a difference between surface tension of the aqueous MEA solution and of the

CO2-loaded aqueous MEA solution. As the surface tension of the CO2-loaded aqueous

MEA solution decreases, the surface tension gradient is increased. The foam stability is,

thus, enhanced.

The solution viscosity affects the foam height in a proportional manner. An

increase in the solution viscosity increases the foam height due to an enhancement of

foam stability. As the solution viscosity increases, the liquid drainage from the lamella in

the foam layer to the bulk solution, owing to gravity drainage, is retarded, thereby

resulting in greater foam stability. This can be seen from the relationship between liquid

velocity and viscosity in Equation (5.31) (i.e. increasing the viscosity slows down the

liquid velocity). Note that the stability of foam could be destroyed if the surface viscosity

is so high that it causes immobile films between the lamella.

The superficial gas velocity influences the foam height (i.e. an increase in the

superficial gas velocity increases the foam height). This is a result of increasing volume

and number of bubbles generated in the system as shown in the following equation:

VGdiff = V= NbubVbubE (5.32)

where rt6d- ifir is the entire gas volume dispersed through the diffuser (m3) and Nfrub is the

number of the bubbles formed at the diffuser per a unit of time.

5.3.2 Sensitivity analysis

Sensitivity analysis was carried out to rank the parametric effects on the foam

height. Two types of parameters, dependent and independent, are involved in foaming in

122

free energy, is decreased, and consequently, foam formation is promoted. The surface

tension also plays a role in foam stability through the Marangoni effect occurring when

there is a difference between surface tension of the aqueous MEA solution and of the

CC>2-loaded aqueous MEA solution. As the surface tension of the CCh-loaded aqueous

MEA solution decreases, the surface tension gradient is increased. The foam stability is,

thus, enhanced.

The solution viscosity affects the foam height in a proportional manner. An

increase in the solution viscosity increases the foam height due to an enhancement of

foam stability. As the solution viscosity increases, the liquid drainage from the lamella in

the foam layer to the bulk solution, owing to gravity drainage, is retarded, thereby

resulting in greater foam stability. This can be seen from the relationship between liquid

velocity and viscosity in Equation (5.31) (i.e. increasing the viscosity slows down the

liquid velocity). Note that the stability of foam could be destroyed if the surface viscosity

is so high that it causes immobile films between the lamella.

The superficial gas velocity influences the foam height (i.e. an increase in the

superficial gas velocity increases the foam height). This is a result of increasing volume

and number of bubbles generated in the system as shown in the following equation:

V (f = v = Nb u bVb u hYJ (5.32)

where V (f f f is the entire gas volume dispersed through the diffuser (m3) and Nb u b is the

number of the bubbles formed at the diffuser per a unit of time.

5.3.2 Sensitivity analysis

Sensitivity analysis was carried out to rank the parametric effects on the foam

height. Two types of parameters, dependent and independent, are involved in foaming in

122

the CO2 absorption process. The independent parameters are process parameters (i.e.,

superficial gas velocity, solution volume, MEA concentration, CO2 loading, and solution

temperature). The dependent parameters are physical properties (i.e., gas density, liquid

density, liquid viscosity, and surface tension). To perform the sensitivity analysis, ranges

of these parameters were defined as listed in Tables 5.3 — 5.4. The minimum and

maximum values of the process parameters were adopted from the static experimental

conditions while those of the physical properties were determined from the subroutine

calculations (Sections 5.2.2 — 5.2.4) using the minimum and maximum values of the

process parameters. For each process parameter, a curve was plotted between percent

change in parameter and foam height index. The value of the parameter of interest was

increased in 10 percent increments from its minimum to its maximum while the rest of

the process parameters were fixed at either their minimum or maximum values. Note that

the values of the physical properties changed with respect to the increase in the given

process parameter. The foam height index is defined as a ratio of the predicted foam

height at a new value of a parameter to the predicted foam height at the minimum value

of a parameter. A similar procedure was applied to the sensitivity analysis of all of the

physical properties.

The results in Figures 5.10 — 5.11 show that the foam height increases with

superficial gas velocity, solution volume, CO2 loading, MEA concentration, gas density,

liquid density, and liquid viscosity but decreases with solution temperature and surface

tension. Among process parameters, solution volume is the most influential on the foam

height, followed by solution temperature. The remaining parameters, superficial gas

velocity, CO2 loading, and MEA concentration, have similar effects on the foam height.

The solution volume and superficial gas velocity mechanically affect foam height while

123

the CO2 absorption process. The independent parameters are process parameters (i.e.,

superficial gas velocity, solution volume, MEA concentration, CO2 loading, and solution

temperature). The dependent parameters are physical properties (i.e., gas density, liquid

density, liquid viscosity, and surface tension). To perform the sensitivity analysis, ranges

of these parameters were defined as listed in Tables 5.3 - 5.4. The minimum and

maximum values of the process parameters were adopted from the static experimental

conditions while those of the physical properties were determined from the subroutine

calculations (Sections 5.2.2 - 5.2.4) using the minimum and maximum values of the

process parameters. For each process parameter, a curve was plotted between percent

change in parameter and foam height index. The value of the parameter of interest was

increased in 10 percent increments from its minimum to its maximum while the rest of

the process parameters were fixed at either their minimum or maximum values. Note that

the values of the physical properties changed with respect to the increase in the given

process parameter. The foam height index is defined as a ratio of the predicted foam

height at a new value of a parameter to the predicted foam height at the minimum value

of a parameter. A similar procedure was applied to the sensitivity analysis of all of the

physical properties.

The results in Figures 5.10 - 5.11 show that the foam height increases with

superficial gas velocity, solution volume, CO2 loading, MEA concentration, gas density,

liquid density, and liquid viscosity but decreases with solution temperature and surface

tension. Among process parameters, solution volume is the most influential on the foam

height, followed by solution temperature. The remaining parameters, superficial gas

velocity, CO2 loading, and MEA concentration, have similar effects on the foam height.

The solution volume and superficial gas velocity mechanically affect foam height while

123

the rest of the process parameters impact the foam height through physical properties. A

change in solution temperature, CO2 loading, and MEA concentration primarily affects

liquid viscosity followed by liquid density, surface tension, and gas density as seen from

the relationships given in Sections 5.2.2 — 5.2.4. Among the physical properties (Figure

5.11), the foam height is the most sensitive to liquid viscosity, followed by liquid density

and surface tension, while it is not sensitive to gas density.

124

the rest of the process parameters impact the foam height through physical properties. A

change in solution temperature, CO2 loading, and MEA concentration primarily affects

liquid viscosity followed by liquid density, surface tension, and gas density as seen from

the relationships given in Sections 5.2.2 - 5.2.4. Among the physical properties (Figure

5.11), the foam height is the most sensitive to liquid viscosity, followed by liquid density

and surface tension, while it is not sensitive to gas density.

124

Table 5.3 Ranges of process parameters

Parameter Minimum Maximum

Superficial gas velocity (mm/s) 0.12 0.94

Solution volume (cm3) 200 700

MEA concentration (kmol/m3) 2.0 7.0

CO2 loading (mol/mol) 0.10 0.55

Solution temperature (°C) 40 90

125

Table 5.3 Ranges of process parameters


Superficial gas velocity (mm/s) 0.12 0.94

Solution volume (cm3) 200 700

MEA concentration (kmol/m3) 2.0 7.0

CO2 loading (mol/mol) 0.10 0.55

Solution temperature (°C) 40 90

125

Table 5.4 Ranges of physical properties


Gas density (kg/m3) 0.94 1.09

Liquid density (kg/m3) 976 1173

Liquid viscosity (mPas) 0.41 6.18

Surface tension (mN/m) 15.7 62.5

126

Table 5.4 Ranges of physical properties


Gas density (kg/m3) 0.94 1.09

Liquid density (kg/m3) 976 1173

Liquid viscosity (mPa s) 0.41 6.18

Surface tension (mN/m) 15.7 62.5

126

.9 .c E

u.

Foa

m h

eig

ht i

ndex

8.00

7.00 -

6.00 -

5.00

4.00 -

3.00

2.00 -

1.00

0.00 0

8.00

7.00 -

6.00 -

5.00 -

4.00 -

3.00

2.00 -

1.00

0.00

-B-Superficial gas velocity - -x- • Solution volume

MEA concentration - CO2 loading - Solution temperature

•

,,•

••• • • -X'

10 20 30 40 50 60 70 80 90 100 %increase in parameter

(a)

-9- Superficial gas velocity - Solution volume ---*- MEA concentration -AD-• CO2 loading -4- Solution temperature

.-.". .• •

0 10 20 30 40 50 60 70 80 90 100 %increase in parameter

(b)

Figure 5.10 Sensitivity analysis of process parameters on foam height; (a) minimum

value of the remaining process parameters and (b) maximum value of the

remaining process parameters

127

8.00

7.00

$ 6.00 X3

Z 5.00 £ SP © 4.00 £

i 3.00 o u.

2.00

-e— Superficial gas velocity •-*-•• Solution volume

MEA concentration CO2 loading Solution temperature

,.;c

10 20 30 40 50 60 70 80 90 100 %increase in parameter

(a)

8.00

7.00 -

3 6.00 -"D Z 5.00 £ « 4.00 £

i 3.00 o

-b— Superficial gas velocity *- Solution volume

MEA concentration - CO2 loading -•*- Solution temperature

j:

x-

..-a'


(b)

Figure 5.10 Sensitivity analysis of process parameters on foam height; (a) minimum



127

8.00

7.00

6.00

5.00 .2) • 4.00 E o 3.00 u.

2.00

1.00

0.00

8.00

7.00

6.00

:5 5.00 a) .c • 4.00 E 0 3.00 u.

2.00

1.00

0.00


(a)

-9- Gas density - -- - Liquid density

Liquid viscosity - •-• Surface tension

X.•

•

_ . _ . -g• •


(b)

Figure 5.11 Sensitivity analysis of physical properties on foam height; (a) minimum



128

Gas density - -x- • Liquid density

Liquid viscosity Surface tension •o 6.00

5.00 IP ©

4.00 E o 3.00

I I 10 20 30 40 50 60 70 80

%increase in parameter 90 100

(a) 8.00

7.00 -x «

T3 C 6.00 -

£ 5.00 -O) 0 JZ 4.00 -£ (0 o 3.00 -u.

2.00 •

1.00

0.00

—a— Gas density - -x- - Liquid density —*•— Liquid viscosity —Surface tension

80 90 100

1 , 1 i 1 i r—

0 10 20 30 40 50 60 70 %increase in parameter

(b)

Figure 5.11 Sensitivity analysis of physical properties on foam height; (a) minimum



128

6. DEVELOPMENT OF A FOAM MODEL

This chapter involves five main parts: i) development of a foam model for

columns fitted with the metal sheet structured packing as a column internal due to its

rising popularity in industrial use, high mass-transfer performance, and low pressure

drop; ii) generation of experimental foam data from a laboratory-scale absorber packed

with Mellapak 500.Y; iii) model verification with the experimental foam data; iv) model

simulation for foaming tendency; and v) evaluation of foaming impacts on process

performance.

6.1 Model development

A foam model for the alkanolamine-based CO2 absorption process using sheet-

metal structured packing as a column internal was developed with an aim to predict foam

volumes generated under a wide spectrum of CO2 absorption operation. The model was

built on the concept depicted in Figure 6.1. That is, a total foam volume generated within

a column is the sum of the foam volumes generated on all packing slabs when a packing

slab is defined as a half of the corrugation channel. Each slab has a number of

perforations and is partially covered by liquid rivulets. Only the perforations covered

with the liquid rivulets are considered to be foam sites accommodating foam formation as

they provide liquid pools for gas to disperse in. The foam volume at a given foam site is

quantified by using the pneumatic steady-state foam correlation (see Equation (5.30),

page 112). The total foam volume of a packing section is essentially a product of the

foam volume per one slab and the total number of slabs in the packing section. Based on

this concept, a model framework shown in Figure 6.2 was established to incorporate three

129

6. DEVELOPMENT OF A FOAM MODEL

This chapter involves five main parts: i ) development of a foam model for

columns fitted with the metal sheet structured packing as a column internal due to its

rising popularity in industrial use, high mass-transfer performance, and low pressure

drop; it) generation of experimental foam data from a laboratory-scale absorber packed

with Mellapak 500.Y; iii) model verification with the experimental foam data; iv) model

simulation for foaming tendency; and v) evaluation of foaming impacts on process

performance.

6.1 Model development

A foam model for the alkanolamine-based CO2 absorption process using sheet-

metal structured packing as a column internal was developed with an aim to predict foam

volumes generated under a wide spectrum of CO2 absorption operation. The model was

built on the concept depicted in Figure 6.1. That is, a total foam volume generated within

a column is the sum of the foam volumes generated on all packing slabs when a packing

slab is defined as a half of the corrugation channel. Each slab has a number of

perforations and is partially covered by liquid rivulets. Only the perforations covered

with the liquid rivulets are considered to be foam sites accommodating foam formation as

they provide liquid pools for gas to disperse in. The foam volume at a given foam site is

quantified by using the pneumatic steady-state foam correlation (see Equation (5.30),

page 112). The total foam volume of a packing section is essentially a product of the

foam volume per one slab and the total number of slabs in the packing section. Based on

this concept, a model framework shown in Figure 6.2 was established to incorporate three

129

components: 1) input of parameters, 2) a slab foam model, and 3) prediction of total foam

volume.

130

components: 1) input of parameters, 2) a slab foam model, and 3) prediction of total foam

volume.

130

Slab

Structured packing

r t 1 REPRESENTATION OF SLAB FOAM MODEL

‘ 1 i t

. .

Gas •' -' .,.. I _ , '

(Section A-A)

No of slab for a length of a given packing

section

I

FOAM

Liquid Rivulets (Wetted stir ace)

Pneumatic steady-state foaming experiment

Foam volume/Slab

Total foam volume

Figure 6.1 Concept of a foam model development

131

Slab Packing sheet

Structured packing

REPRESENTATION OF SLAB FOAM MODEL

Liquid Rivulets (Wetted surface)

Dry surface

Perforations

Dispersing g«

FOAM

Gas t (Section A-A)

Pneumatic steady-state foaming experiment

No. of slab for a length of a given packing

section Foam volume/Slab

Total foam volume

Figure 6.1 Concept of a foam model development

131

r

INPUT PARAMETER

r

Packing and column design parameter

• Corrugation base (2B) • Element height (hp) • Crimp height (h,881,) • Specific area (ap) • Diameter of Perforation hole (D8) • Perforation factor (fo p,) • Column diameter (Dc)

Process parameter

• Amine concentration (Al) • Superficial liquid velocity ( L) • CO2 loading (aco2) • Operating pressure (P) • Temperature of feed liquid (7) • Superficial gas velocity (G)

SLAB FOAM MODEL

Hydrodynamic feature

r • Liquid holdup (h') 4

• Fraction of wetted surface area (4ened)

Liquid height (h8q)

S

Physical property

• Gas density (pG) • Liquid density (PL) • Liquid viscosity (pL) • Surface tension (y) • Water viscosity (p,2„)

Force

• Buoyancy force (F8) • Kinetic force (FK) • Surface force (Fs) • Hydrostatic force (FR)

Average bubble radius (r)

4

Pneumatic foam height

Y Oy .30

H = 4.394 r 1 • 6°

130(40

Slab foam volume

t ) slab = h 7;erforation

(hp It„„„p

sin B)

4

r

No. of slab

The total number of the slab (Nr)

V Total foam volume

UT = l) slab. i

TOTAL FOAM VOLUME

Figure 6.2 Model framework to predict total foam volume in a structured packed

absorber

132

INPUT PARAMETER

SLAB FOAM MODEL

TOTAL FOAM VOLUME

The total number of the slab (AY)

No. of slab Total foam volume

slab, i

Packing and column design parameter

Corrugation base (2B) Element height (hp)

Crimp height (ha Specific area (ap) Diameter of Perforation hole (DH) Perforation factor {/perforation)

Column diameter (Dc)

Amine concentration ( M ) Superficial liquid velocity (L) C02 loading («r02) Operating pressure ( P ) Temperature of feed liquid (T) Superficial gas velocity (G)

Process parameter

Figure 6.2 Model framework to predict total foam volume in a structured packed

absorber

132

6.1.1 Input of parameters

Three types of parameters are involved in the model (i.e., process, packing, and

column design parameters). The process parameters refer to alkanolamine concentration,

superficial velocity of gas and liquid, CO2 loading of solution, operating pressure, and

feed liquid temperature. The packing parameters characterize configuration of structured

packings, as well as a fluid flow pattern within the column, while the column design

parameter involves the information on column diameter. By principle, the column is

packed with a series of structured packing elements, each of which can be rotated at a

specific angle ranging from zero to 90° with respect to the adjacent elements. As

illustrated in Figure 6.3, the structured packing element used for the model development

is of a sheet-metal type that is made of several thin corrugated metal sheets with

perforations with diameter (Dh), a crimp geometry of crimp height (h„,mp), and

corrugation base (2B) arranged alternately parallel to each other and at a fixed angle (a)

to the horizontal plane. The corrugation is composed of two inclined slabs with a slope of

0, which can be calculated from the crimp geometry of the packing to the adjacent sheet.

Specifically, our simulation used Mellapak 500.Y with 4.5 mm Dh, 6.53 mm hcrimp and

9.60 mm 2B as a case study. In gas absorption operations, gas travels upward from the

bottom to the top of the column, whereas liquid flows countercurrently downward in the

form of thin liquid films on the surface of the structured packing along corrugation

channels and packing intersections. When the packing elements are wetted by these

films, it is possible to observe a foam layer covering all the wetted packing surface and

flowing along with the liquid downward to the bottom of the column as shown in Figure

6.3b.

133

6.1.1 Input of parameters

Three types of parameters are involved in the model (i.e., process, packing, and

column design parameters). The process parameters refer to alkanolamine concentration,

superficial velocity of gas and liquid, CO2 loading of solution, operating pressure, and

feed liquid temperature. The packing parameters characterize configuration of structured

packings, as well as a fluid flow pattern within the column, while the column design

parameter involves the information on column diameter. By principle, the column is

packed with a series of structured packing elements, each of which can be rotated at a

specific angle ranging from zero to 90° with respect to the adjacent elements. As

illustrated in Figure 6.3, the structured packing element used for the model development

is of a sheet-metal type that is made of several thin corrugated metal sheets with

perforations with diameter (£)/,), a crimp geometry of crimp height {hcrimp), and

corrugation base (2B) arranged alternately parallel to each other and at a fixed angle (a)

to the horizontal plane. The corrugation is composed of two inclined slabs with a slope of

9, which can be calculated from the crimp geometry of the packing to the adjacent sheet.

Specifically, our simulation used Mellapak 500.Y with 4.5 mm A,, 6.53 mm hcrimp and

9.60 mm 2B as a case study. In gas absorption operations, gas travels upward from the

bottom to the top of the column, whereas liquid flows countercurrently downward in the

form of thin liquid films on the surface of the structured packing along corrugation

channels and packing intersections. When the packing elements are wetted by these

films, it is possible to observe a foam layer covering all the wetted packing surface and

flowing along with the liquid downward to the bottom of the column as shown in Figure

6.3b.

133

FRONT VIEW

Foam layer

Liquid layer

(a)

p4- 2B '"""" 11

•4(

(b)

TOP VIEW

SIDE VIEW

Wetted zone

Packing surface Dry zone

x iff-mg 111110111111111 IIII Ill III

>zGas1 T T rt

—

gas k

1

T dy

z

h' lig

Liquid

(c)

Figure 6.3 (a) An arrangement of corrugated sheets with flow directions of gas and

liquid, (b) a location of foam layer on a surface of a corrugated sheet with a

certain crimp dimension and (c) a mechanism of foam formation on a surface

area of a packing element

134

FRONT VIEW

(a) Foam layer TOP VIEW

Liquid layer 2B

V

(b)

T W

SIDE VIEW

Wetted zone

Packing surface Dry zone

z Gas

Liquid

(c) Figure 6.3 (a) An arrangement of corrugated sheets with flow directions of gas and

liquid, (b) a location of foam layer on a surface of a corrugated sheet with a

certain crimp dimension and (c) a mechanism of foam formation on a surface

area of a packing element

134

6.1.2 Slab foam model

A slab foam volume ( vsk,b) is the foam volume generated on one slab of the

corrugation channel. A liquid film with a thickness of hhq (Figure 6.3c) is divided into

small stationary volume elements, hi,q dxdz, through which both gas and liquid flow. Each

liquid volume element sufficiently accommodates an infinitesimal foam volume (dv) that

is generated when gas is dispersed underneath a given element and is expressed as:

dv = dxdydz (6.1)

where dx, dy, and dz are increments of distance in the x-axis, which is parallel to the

inclined packing surface; in the y-axis, which is perpendicular to the inclined packing

surface; and in the z-axis, which is parallel to the vertical, respectively. Since the foam

height only varies along the y-axis, the boundary conditions necessary for integrating

Equation (6.1) are listed below:

B.C. 1: at x = 0, = b hcrimp

(6.2) x =

sin 0

B.C. 2: at y = 0, y = H (6.3)

B.C. 3: at z = 0, z = hp (6.4)

where b is the slab width (m), H is the foam height formed on the surface of slab (m) and

hp is the height of a packing element (m), which in our simulation case, is equal to the

total height of the two Mellapak 500.Y packing elements. Therefore, the Vslab is a product

of the integration result of Equation (6.1) and the two factors, which are the liquid holdup

(h`) and the perforation factor (f v perforation) as given by:

(hp hcrimp slab

) v = h' f Peif°ramn H sin 0

(6.5)

135

6.1.2 Slab foam model

A slab foam volume (vsiab) is the foam volume generated on one slab of the

corrugation channel. A liquid film with a thickness of hi,g (Figure 6.3c) is divided into

small stationary volume elements, hnqdxdz, through which both gas and liquid flow. Each

liquid volume element sufficiently accommodates an infinitesimal foam volume (do) that

is generated when gas is dispersed underneath a given element and is expressed as:

dv = dxdydz (6.1)

where dx, dy, and dz are increments of distance in the x-axis, which is parallel to the

inclined packing surface; in the .y-axis, which is perpendicular to the inclined packing

surface; and in the z-axis, which is parallel to the vertical, respectively. Since the foam

height only varies along the j'-axis, the boundary conditions necessary for integrating

Equation (6.1) are listed below:

h, B.C.I: at x = 0, x = ft = -222. (6.2)

sin 9

B.C. 2: at ^ = 0, y = H (6.3)

B.C. 3: at z = 0, z = hp (6.4)

where b is the slab width (m), H is the foam height formed on the surface of slab (m) and

hp is the height of a packing element (m), which in our simulation case, is equal to the

total height of the two Mellapak 500.Y packing elements. Therefore, the vsiab is a product

of the integration result of Equation (6.1) and the two factors, which are the liquid holdup

(h') and the perforation factor if perforation) as given by:

®slab h fperforation ̂

f hP h

\

(6.5) sin 6 /

135

The liquid holdup represents the total amount of a liquid pool that accommodates

the onset of foaming, whereas the perforation factor indicates a fraction of an opening

hole on the surface area of the packing element where gas can flow upward through the

liquid pool. In the case of Mellapak 500.Y„fperforation is 0.102 with the distance between

the centers of two holes equal to 12.5 mm. H can be estimated from the foam height

correlation (see Equation (5.30), page 112) developed from the static foaming

experiments for the CO2 absorption process using aqueous alkanolamine solutions.

Details of the correlation and the prediction of physical properties were previously

discussed in Chapter 5.

From Equation (5.30) (page 112), the average radius of a gas bubble, a key

parameter in predicting the foam height, is calculated. As shown in Figure 6.4, the bubble

forms at a round perforation of the packing in which four forces (i.e., buoyancy force

(F8), kinetic force (FK), surface tension force (Fs), and hydrostatic force (FH)) play an

important role in the dimensions of the bubble. A balance equation of all forces is

expressed as:

FB FK = Fs + FH (6.6)

where the forces are in the unit of nN. r can be obtained by solving Equation (6.6).

Buoyancy and kinetic force are the upward forces that tend to disengage the bubble from

the perforation while surface tension and hydrostatic force act on the bubble in the

opposite direction. Buoyancy force is mainly caused by a density difference between gas

and liquid phases as shown below:

FB =-4 3 773 Apg (6.7)

136

The liquid holdup represents the total amount of a liquid pool that accommodates

the onset of foaming, whereas the perforation factor indicates a fraction of an opening

hole on the surface area of the packing element where gas can flow upward through the

liquid pool. In the case of Mellapak 500.Y, fperforation is 0.102 with the distance between

the centers of two holes equal to 12.5 mm. H can be estimated from the foam height

correlation (see Equation (5.30), page 112) developed from the static foaming

experiments for the CO2 absorption process using aqueous alkanolamine solutions.

Details of the correlation and the prediction of physical properties were previously

discussed in Chapter 5.

From Equation (5.30) (page 112), the average radius of a gas bubble, a key

parameter in predicting the foam height, is calculated. As shown in Figure 6.4, the bubble

forms at a round perforation of the packing in which four forces (i.e., buoyancy force

(FB), kinetic force (FK), surface tension force (Fs), and hydrostatic force (FH)) play an

important role in the dimensions of the bubble. A balance equation of all forces is

expressed as:

where the forces are in the unit of nN. r can be obtained by solving Equation (6.6).

Buoyancy and kinetic force are the upward forces that tend to disengage the bubble from

the perforation while surface tension and hydrostatic force act on the bubble in the

opposite direction. Buoyancy force is mainly caused by a density difference between gas

and liquid phases as shown below:

fb + = Fs + fH (6.6)

(6.7)

136

Kinetic force accounts for gas motion through a perforation with a diameter of Dh

(mm) as calculated by:

2 'FK = 500p,;62(1rD1 (6.8)

4

Surface tension force is the downward force produced by surface tension of liquid

phase exerting pressure on the perimeter of the hole as given below:

Fs = 70hy

1000 (6.9)

Hydrostatic force is the force pressing on the bubble when a certain amount of

liquid is present, which can be represented by:

pLghliy (47(7'2) FH (6.10)

1000

where hhq is the liquid height above the perforation hole (m) calculated by the following

equation:

h' hny =

fwelied a p

(6.11)

where ffemet is the fraction of the wetted surface area or, in this work, a ratio of the

effective mass-transfer area experimentally attained by Aroonwilas (2001) to the surface

area of the packing element; ap is the specific surface area (m2/m3 packing); and h' is the

liquid holdup at a given liquid velocity (m3 liquid solution/m3 packing) for Mellapak

estimated using the empirical equation with 10% accuracy (Suess and Spiegel, 1992), as

given below:

h' =capu3(0

\ 0.25 PL

PH20, 20*C (6.12)

137

Kinetic force accounts for gas motion through a perforation with a diameter of A,

(mm) as calculated by:

v 4 , (6.8) FK =500PGG2

Surface tension force is the downward force produced by surface tension of liquid

phase exerting pressure on the perimeter of the hole as given below:

F E£hV ( 69 ) s 1000

Hydrostatic force is the force pressing on the bubble when a certain amount of

liquid is present, which can be represented by:

p, ghlia 4w21 p 1 (6 1{))

" 1000

where hnq is the liquid height above the perforation hole (m) calculated by the following

equation:

K=-r— <61» J welted® P

where fwetted is the fraction of the wetted surface area or, in this work, a ratio of the

effective mass-transfer area experimentally attained by Aroonwilas (2001) to the surface

area of the packing element; ap is the specific surface area (m2/m3 packing); and ti is the

liquid holdup at a given liquid velocity (m3 liquid solution/m3 packing) for Mellapak

estimated using the empirical equation with 10% accuracy (Suess and Spiegel, 1992), as

given below:

/ \0.25

K = ca™(Lf CL

\^H20,20°C (6.12)

137

where L is the superficial liquid velocity (m3/m2-hr), jimio 20.c

is the water viscosity at

20°C (mPa's), c is 0.0169 for L < 40 m3/m2-hr or 0.0075 for L > 40 m3/m2-hr, and w is

0.37 for L < 40 m3/m2-hr or 0.59 for L > 40 m3/m2-hr.

138

where L is the superficial liquid velocity (m3/m2-hr), 20.c is the water viscosity at

20°C (mPa s), c is 0.0169 for L < 40 m3/m2-hr or 0.0075 for L> 40 m3/m2-hr, and w is

0.37 for L< 40 m3/m2-hr or 0.59 for L> 40 m3/m2-hr.

138

Hydrostatic force

IF Buoyancy Surface

force force

•

tKinetic force

Figure 6.4 Illustration of four main forces affecting average bubble radius

Hydrostatic force

1 Buoyancy Surface

force force

Gas

k Kinetic T force

Figure 6.4 Illustration of four main forces affecting average bubble radius

139

6.1.3 Prediction of total foam volume per packing section

In order to calculate the total foam volume after the vsiab is obtained, a number of

assumptions are applied to reduce mathematical complication. These are: 1) gas and

liquid countercurrently flows in the z-axis with a flow pattern of ideal plug flow

providing a uniform composition and flow rates, 2) perforations are distributed in a basic

regular pattern (Aroonwilas, 2001), 3) all foams after being generated on the packing

surface flow along the liquid stream to the bottom of the column without any collapse, 4)

only a variation of physical properties of both phases in the z-axis is considered, and 5)

the packing surface is wetted with the liquid to a thickness of hhq m, which is sufficient to

generate at least a monolayer of bubbles with an average bubble radius of r mm. With

these assumptions, the total foam volume ( v7-, m3) of the absorption column filled with a

series of structured packings is the sum of the slab foam volumes as expressed by:

41 4

UT = LUslab, i i=1

(6.13)

where NT is the total number of slabs per packing section of interest, which can be

determined by:

N = aA

b (6.14)

where A is the cross-sectional area of the column (m2). Note that the slab length is

assumed to be equal to the height of the given packing section.

140

6.1.3 Prediction of total foam volume per packing section

In order to calculate the total foam volume after the vsiab is obtained, a number of

assumptions are applied to reduce mathematical complication. These are: 1) gas and

liquid countercurrently flows in the z-axis with a flow pattern of ideal plug flow

providing a uniform composition and flow rates, 2) perforations are distributed in a basic

regular pattern (Aroonwilas, 2001), 3) all foams after being generated on the packing

surface flow along the liquid stream to the bottom of the column without any collapse, 4)

only a variation of physical properties of both phases in the z-axis is considered, and 5)

the packing surface is wetted with the liquid to a thickness of huq m, which is sufficient to

generate at least a monolayer of bubbles with an average bubble radius of r mm. With

these assumptions, the total foam volume (or, m3) of the absorption column filled with a

series of structured packings is the sum of the slab foam volumes as expressed by:

where Nr is the total number of slabs per packing section of interest, which can be

determined by:

where A is the cross-sectional area of the column (m2). Note that the slab length is

assumed to be equal to the height of the given packing section.

(6.13) 1=1

(6.14)

140

6.2 Results and discussions

6.2.1 Experimental foam data

The experimental foam data were analyzed and presented in Figure 6.5a (see

Appendix C) as a function of superficial liquid velocity and superficial gas velocity.

Results show that superficial liquid velocity has an apparent effect on foam volume,

whereas superficial gas velocity has a negligible effect at a low superficial liquid velocity

and a small effect at higher superficial liquid velocities. An increase in the superficial

liquid velocity generally increases foam volume generated at a given superficial gas

velocity. This can be explained by the fact that greater superficial liquid velocity lead to

greater degrees of wetted packing area and liquid holdup. As a result, the total number of

the perforations covered by the liquid solution is increased, which in turn increases

foaming tendency.

The negligible effect of superficial gas velocity is evident at the low superficial

liquid velocity of 0.8 m3/m2-hr (i.e., the foam volume does not change with superficial

gas velocity). This might be because the liquid holdup is too small to provide an adequate

liquid layer above the perforation hole or a sufficient contacting time between a gas

bubble and a liquid layer. However, at higher superficial liquid velocities, the foam

volume tends to increase with superficial gas velocity at a given superficial liquid

velocity. This is due to an increase in gas volume and in turn an increase in the number of

bubbles generated above the perforation holes.

It should be noted that at 360 nun/s superficial gas velocity for 2.3 m3/m2-hr

superficial liquid velocity and at 300 and 360 minis for a 3.1 m3/m2-hr, the turbulence

between gas and liquid phases at the bottom of absorber could create a slight drop in the

foam volumes. The turbulence, as shown in Figure 6.6, could even hinder the

141

6.2 Results and discussions

6.2.1 Experimental foam data

The experimental foam data were analyzed and presented in Figure 6.5a (see

Appendix C) as a function of superficial liquid velocity and superficial gas velocity.

Results show that superficial liquid velocity has an apparent effect on foam volume,

whereas superficial gas velocity has a negligible effect at a low superficial liquid velocity

and a small effect at higher superficial liquid velocities. An increase in the superficial

liquid velocity generally increases foam volume generated at a given superficial gas

velocity. This can be explained by the fact that greater superficial liquid velocity lead to

greater degrees of wetted packing area and liquid holdup. As a result, the total number of

the perforations covered by the liquid solution is increased, which in turn increases

foaming tendency.

The negligible effect of superficial gas velocity is evident at the low superficial

liquid velocity of 0.8 m3/m2-hr (i.e., the foam volume does not change with superficial

gas velocity). This might be because the liquid holdup is too small to provide an adequate

liquid layer above the perforation hole or a sufficient contacting time between a gas

bubble and a liquid layer. However, at higher superficial liquid velocities, the foam

volume tends to increase with superficial gas velocity at a given superficial liquid

velocity. This is due to an increase in gas volume and in turn an increase in the number of

bubbles generated above the perforation holes.

It should be noted that at 360 mm/s superficial gas velocity for 2.3 m3/m2-hr

superficial liquid velocity and at 300 and 360 mm/s for a 3.1 m3/m2-hr, the turbulence

between gas and liquid phases at the bottom of absorber could create a slight drop in the

foam volumes. The turbulence, as shown in Figure 6.6, could even hinder the

141

measurement of foam volume at the superficial gas velocity above 240 mm/s and the

superficial liquid velocity above 3.8 m3/m2-hr since it could obstruct and destroy

downcoming foam bubbles. At high gas and liquid velocities, difficulty in collecting the

foam at the liquid outlet tube was unavoidable as a result of intensified turbulence.

To combine the effects of both gas and liquid velocities on foam volume, the

experimental results are also presented as a function of the ratio of liquid to gas velocity

(LIG) as shown in Figure 6.5b. At the low LIG ratio of 0.8, the foam volume is very small

due to the insufficient liquid holdup and the excessive gas velocity, which could easily

breakdown the gas bubbles. As the LIG ratio is increased up to 4.8, the foam volume

increases. This suggests that the effect of liquid velocity on foam volume is predominant

over that of gas velocity. The effect of liquid velocity becomes much less when LIG

exceeds 4.8.

142

measurement of foam volume at the superficial gas velocity above 240 mm/s and the

superficial liquid velocity above 3.8 m /m -hr since it could obstruct and destroy

downcoming foam bubbles. At high gas and liquid velocities, difficulty in collecting the

foam at the liquid outlet tube was unavoidable as a result of intensified turbulence.

To combine the effects of both gas and liquid velocities on foam volume, the

experimental results are also presented as a function of the ratio of liquid to gas velocity

(L/G) as shown in Figure 6.5b. At the low LIG ratio of 0.8, the foam volume is very small

due to the insufficient liquid holdup and the excessive gas velocity, which could easily

breakdown the gas bubbles. As the LIG ratio is increased up to 4.8, the foam volume

increases. This suggests that the effect of liquid velocity on foam volume is predominant

over that of gas velocity. The effect of liquid velocity becomes much less when LIG

exceeds 4.8.

142

0.70

0.60 -

a. 0.60 - • 0EE oa 0.40 - > > E °' 0.30- a c o 32

c.) c a m 0.20 - P. a 0.10 -

0.00

• •

- = 0.8 m3/m2-hr -e-- L =1.5 m3/m2-hr -0- L = 2.3 m3/m2-hr - = 3.1 m3/m2-hr - 0- L = 3.8 m3/m2-hr

L = 4.6 m3/m2-hr

[ I I I

0 50 100 150 200 250 300 350 400 450 Superficial gas velocity (mm/s)

0.70

0.60 • a. O 0.50 - E E o 0 0.40 - > >

2 E

T • c 0.30 -

o c O a 0.20 -e 0 a. 0.10 -

0.00 0.00 5.00

(a)

10.00 UG

15.00 20.00

(b)

Figure 6.5 (a) Experimental percent foam volume per packing volume plotted versus the

superficial gas velocity at different superficial liquid velocities (MEA

concentration = 5.0 kmol/m3, CO2 loading = 0.40 mol/mol, and solution

temperature = 18.5°C) and (b) experimental foam volume per packing volume

plotted versus the LIG ratio (MEA concentration = 5.0 kmol/m3, CO2 loading

= 0.40 mol/mol, and solution temperature = 18.5°C)

143

o ex.

0.70

0.60

0.50

§1 If0-40

I c 0.30

Z o c CO « Q-o

0.20 -

CL 0.10 -

0.00

L = 0.8 m3/m2-hr L -1.5 m3/m2-hr L = 2.3 m3/m24ir L = 3.1 m3/m2-hr L = 3.8 m3/m2-hr L = 4.6 m3/m2-hr

50 100 150 200 250 300 350 400 450 Superficial gas velocity (mm/s)

(a)

ii s i E o> « c

~ 2 c S o Q. e O Q.

0.70

0.60

0.50

0.40

0.30

0.20

0.10

0.00 0.00 5.00 10.00

L/G 15.00 20.00

(b)

Figure 6.5 (a) Experimental percent foam volume per packing volume plotted versus the

superficial gas velocity at different superficial liquid velocities (MEA

concentration = 5.0 kmol/m3, CO2 loading = 0.40 mol/mol, and solution

temperature = 18.5°C) and (b) experimental foam volume per packing volume

plotted versus the LIG ratio (MEA concentration = 5.0 kmol/m3, CO2 loading

= 0.40 mol/mol, and solution temperature = 18.5°C)

143

Figure 6.6 Example of turbulence developed at the bottom of the column (superficial

liquid velocity = 2.3 m3/m2-hr and superficial gas velocity = 360 mm/s)

(original in color)

144

Figure 6.6 Example of turbulence developed at the bottom of the column (superficial

liquid velocity = 2.3 m3/m2-hr and superficial gas velocity = 360 mm/s)

(original in color)

144

6.2.2 Model verification

The developed foam model was verified with 67 experimental foam data sets in

Section 6.2.1. Results indicate that the model has a capacity to predict foam volume

within the absorber packed with sheet-metal structured packing with 16.3%AAD and

percent deviation of ±30%, as illustrated in the parity plot in Figure 6.7. The deviation of

the predicted foam volume could be caused by: 1) estimation of physical properties and

liquid holdup from available correlations that are intrinsic to certain degrees of deviation,

2) extrapolation of effective wetted area at the low superficial liquid velocity, 3)

approximation of total number of the corrugation channels, 4) estimation of average

bubble radius from theory and not from experimental measurements, and 5) violation of

model assumptions due to the nature of foam and column hydrodynamics (i.e., zero foam

collapse and zero liquid buildup between the packing elements). For the assumption of

zero foam collapse, a non-wetted surface area inside the packing element could create

blockage of foam bubbles from travelling down to the bottom. As a result, these bubbles

may build up, potentially coalesce into a large bubble, and eventually rupture.

Turbulence between gas and liquid phase above the liquid outlet, especially at high

velocities, could also be a factor in the destruction of downcoming bubbles. For the

assumption of zero liquid buildup between the packing elements, additional liquid

volume could be accumulated between the packings when packing elements are stacked

with a certain degree of rotation with respect to one another (Aroonwilas, 2001).

145

6.2.2 Model verification

The developed foam model was verified with 67 experimental foam data sets in

Section 6.2.1. Results indicate that the model has a capacity to predict foam volume

within the absorber packed with sheet-metal structured packing with 16.3%AAD and

percent deviation of ±30%, as illustrated in the parity plot in Figure 6.7. The deviation of

the predicted foam volume could be caused by: 1) estimation of physical properties and

liquid holdup from available correlations that are intrinsic to certain degrees of deviation,

2) extrapolation of effective wetted area at the low superficial liquid velocity, 3)

approximation of total number of the corrugation channels, 4) estimation of average

bubble radius from theory and not from experimental measurements, and 5) violation of

model assumptions due to the nature of foam and column hydrodynamics (i.e., zero foam

collapse and zero liquid buildup between the packing elements). For the assumption of

zero foam collapse, a non-wetted surface area inside the packing element could create

blockage of foam bubbles from travelling down to the bottom. As a result, these bubbles

may build up, potentially coalesce into a large bubble, and eventually rupture.

Turbulence between gas and liquid phase above the liquid outlet, especially at high

velocities, could also be a factor in the destruction of downcoming bubbles. For the

assumption of zero liquid buildup between the packing elements, additional liquid

volume could be accumulated between the packings when packing elements are stacked

with a certain degree of rotation with respect to one another (Aroonwilas, 2001).

145

0.70

E 0.60 - = o > (A 0.50 - E § 6 1:5 0.40 - .2 > ..... ce .c 0.30 - 2 11

" 0. 0.20 -am •Cj a 0.10 - -a E o. 0.00

0.00

- a --a P--.-

O L = 0.8 m3/m2-hr .--" a L =1.5 m3/m2-hr

o L = 2.3 m3/m2-hr x 1= 3.1 m3/m2-hr & L= 3.8 m3/m2-hr • L = 4.6 m3/m2-hr

0.10 0.20 0.30 0.40 0.50 0.60 0.70 Experimental percent foam volume

per packing volume

Figure 6.7 Simulation results compared between the experimental and predicted percent

foam volume per packing volume

146

t

o

i c W ® .£ O J* in •o *-{& s 0.

0.70

0.60

0.50

0.40

0.30

0.20

0.10

0.00

A +30% ,aD

-30%

X 4-'

a o • o

X

A •

L = 0.8 m3/m2-hr L= 1.5 m3/m2-hr /Is 2.3 m3/m2-hr L = 3.1 m3/m2-hr L = 3.8 m3/m2-hr L = 4.6 m3/m2-hr

0.00 0.10 0.20 0.30 0.40 0.50 0.60 Experimental percent foam volume

per packing volume

0.70

Figure 6.7 Simulation results compared between the experimental and predicted percent

foam volume per packing volume

146

6.3 Model simulation

6.3.1 Foaming tendency within an absorber

To demonstrate an application of the developed foam model, the model was used

to predict foaming tendency of the MEA solution within an absorber with an inside

diameter of 0.10 m and packed with Mellapak 500.Y as a case study. The information of

operating conditions along the column height was obtained from Aroonwilas (2001). The

simulation results in Figure 6.8 show that the model has the capacity to predict local

foam volumes at different heights of the absorber where solution temperature and CO2

loading in the solution (or gas-phase CO2 concentration) are varied. The local foam

volume tends to be higher at the absorber top than at the bottom. This is mainly because

the system temperature at the absorber top is lower than that at the absorber's bottom,

reflecting a higher liquid viscosity at the absorber top, which retards the gravity drainage

of the liquid in lamella and in turn enhances the stability of foam.

It should be noted here that while the temperature plays a role in the foaming

tendency within the absorber as described previously, the CO2 loading of solution also

influences the foaming tendency but to a relatively small extent and in the opposite

manner. That is, as the solution travels downward, the CO2 loading increases. This alone

would result in a higher foam volume at the absorber bottom. However, the influence of

temperature on the foaming tendency predominates over that of CO2 loading, as

evidenced in Figure 6.8; thus, the higher foam volume is found at the absorber top, not at

the bottom.

147

6.3 Model simulation

6.3.1 Foaming tendency within an absorber

To demonstrate an application of the developed foam model, the model was used

to predict foaming tendency of the MEA solution within an absorber with an inside

diameter of 0.10 m and packed with Mellapak 500.Y as a case study. The information of

operating conditions along the column height was obtained from Aroonwilas (2001). The

simulation results in Figure 6.8 show that the model has the capacity to predict local

foam volumes at different heights of the absorber where solution temperature and CO2

loading in the solution (or gas-phase CO2 concentration) are varied. The local foam

volume tends to be higher at the absorber top than at the bottom. This is mainly because

the system temperature at the absorber top is lower than that at the absorber's bottom,

reflecting a higher liquid viscosity at the absorber top, which retards the gravity drainage

of the liquid in lamella and in turn enhances the stability of foam.

It should be noted here that while the temperature plays a role in the foaming

tendency within the absorber as described previously, the CO2 loading of solution also

influences the foaming tendency but to a relatively small extent and in the opposite

manner. That is, as the solution travels downward, the CO2 loading increases. This alone

would result in a higher foam volume at the absorber bottom. However, the influence of

temperature on the foaming tendency predominates over that of CO2 loading, as

evidenced in Figure 6.8; thus, the higher foam volume is found at the absorber top, not at

the bottom.

147

0.70

0.60

r, o. 0.50 E• m0 .24.. 0.40

I 51- --#---- ----12> 0 i

go 0.30 - • 0.35 moUrnol @ L = 3.8 m3/m2-hr .2 3g.6. 0 0.45 moUmol @ L = 3.8 m3/m2-hr c 0 0.20 - O a • 0.35 mol/mol @ 1 = 7.6 m3/m2-hr

m 0 0 0.45 moUmol @ L = 7.6 m3/m2-hr

.10 a A 0.35 moUmol @ L = 12.2 m3/m2-hr

A 0.45 mollmol @ L = 12.2 m3/m2-hr 0.00

0.00

0.70

0.60 a. 0 a, 0.50 S• 1- .2 E = 0.40 - 0 - O o > Et E co 0.30 - 0 c .42 -Ng 4,4 0 c 0 0.20 - O a 2 a. O 0.10 -

0.00 0.00

0.50 1.00 1.50 Distance from the top (m)

(a)

-------o- __________ 0 -o-

2.00

A

• 20.7°C @ L = 3.8 m3/m2-hr o 50.2°C @ L = 3.8 m3/m2-hr • 21.5°C @ L = 7.6 m3/m2-hr o 44.7°C @ L = 7.6 m3/m2-hr • 21.1°C @ L = 12.2 m3/m2-hr A 33.7°C @ L = 12.2 m3/m2-hr


2.00

(b)

Figure 6.8 Simulated profiles of local foam volumes along the absorber height under various CO2 absorption conditions: (a) effect of CO2 loading of feed solution at three different superficial liquid velocities (feed solution temperature =

33.2 ± 1.1°C, air flow rate = 38.5 kmol/m2-hr and MEA concentration = 3.0

kmol/m3) and (b) effect of the temperature of feed solution at three different superficial liquid velocities (CO2 loading of feed solution = 0.33 mol/mol, air flow rate = 38.5 lcmoUm2-hr, and MEA concentration = 3.0 kmol/m3)

148

Q.

II 11 « C £3 +* o C (0 d> CL H a> Q.

0.70 -

0.60 1 4

0.50 i P*- 1 " t ,

— K . —t

-

0.40 j w

0.30 - • 0.35 mol/mol @ L = 3.8 m3/m2-hr

0.20 -• 0.45 mol/mol @ L = 3.8 m3/m2-hr

0.20 - • 0.35 mol/mol @ L = 7.6 m3/m2-hr

0.10 -0 0.45 mol/mol @ L - 7.6 m3/m2-hr

0.10 - A 0.35 mol/mol @ L =12.2 m3/m2-hr

0.00 A 0.45 mol/mol @ L =12.2 m3/m2-hr

1 1 » 1 » *

0.00 0.50 1.00 1.50 Distance from the top (m)

(a)

•

o A A

-B-20.7°C 50.2 °C 21.5°C 44.7 °C 21.1°C 33.7°C = 12.2

m3/m2-hr m3/m2-hr m3/m2-hr m3/m2-hr m3/m2-hr m3/m2-hr

2.00

0.00 0.50 1.00 1.50 2.00 Distance from the top (m)

(b)

Figure 6.8 Simulated profiles of local foam volumes along the absorber height under

various CO2 absorption conditions: (a) effect of CO2 loading of feed solution at three different superficial liquid velocities (feed solution temperature =

33.2 ± 1.1°C, air flow rate = 38.5 kmol/m2-hr and MEA concentration = 3.0

kmol/m3) and (b) effect of the temperature of feed solution at three different

superficial liquid velocities (CO2 loading of feed solution = 0.33 mol/mol, air

flow rate = 38.5 kmol/m2-hr, and MEA concentration = 3.0 kmol/m3)

148

The developed model was further used to evaluate the foaming tendency of the

degraded MEA solution containing a corrosion inhibitor under the experimental

conditions in Section 6.3.1 as a case study. Ammonium thiosulfate and sodium

metavadate were chosen as representatives for the degradation product and the corrosion

inhibitor, respectively, due to their ability for foam induction. According to our previous

study, ammonium thiosulfate enhances the foaming coefficient of the non-degraded and

uninhibited MEA solution by a factor of 1.23 while sodium metavadate enhances the

coefficient by 1.28. For the purpose of this evaluation, ammonium thiosulfate and sodium

metavadate were assumed to contribute no synergistic effect on the foaming tendency of

the MEA solution containing both of these chemicals. This means that the foaming

coefficient in the MEA containing ammonium thiosulfate and sodium metavadate was

estimated to be 1.51, which was the sum of the coefficient enhancement factors of these

chemicals. The simulated foam profiles along the absorber of this degraded and inhibited

MEA solution are given in Figure 6.9.

149

The developed model was further used to evaluate the foaming tendency of the

degraded MEA solution containing a corrosion inhibitor under the experimental

conditions in Section 6.3.1 as a case study. Ammonium thiosulfate and sodium

metavadate were chosen as representatives for the degradation product and the corrosion

inhibitor, respectively, due to their ability for foam induction. According to our previous

study, ammonium thiosulfate enhances the foaming coefficient of the non-degraded and

uninhibited MEA solution by a factor of 1.23 while sodium metavadate enhances the

coefficient by 1.28. For the purpose of this evaluation, ammonium thiosulfate and sodium

metavadate were assumed to contribute no synergistic effect on the foaming tendency of

the MEA solution containing both of these chemicals. This means that the foaming

coefficient in the MEA containing ammonium thiosulfate and sodium metavadate was

estimated to be 1.51, which was the sum of the coefficient enhancement factors of these

chemicals. The simulated foam profiles along the absorber of this degraded and inhibited

MEA solution are given in Figure 6.9.

149

1.80

1.60

le) 1.40 a . Em 1.20

i a E

too > o > E im 0.80 4 U C

I. E i 0 AO "C 4 V

8 a0.40 .. 0 0- 020

0.00 r ,

7 - - - , _ ., .. __ 4 k.... .... " . ... _ . ... . .._. . . . . _ • ....,_,_.,__,__.41• _.___.._.. ._......

'

. - . . . , ,_ , 1 i k r ,

--e— non-degraded soin --1,-- degraded soin (deg.prod.) —*-- degraded soin (deg.prod. + corr. inhibitor

0.00 0.50 1.00 1.50 2.00 Distance from the top (m)

Figure 6.9 Effect of the degradation product (ammonium thiosulfate) and corrosion

inhibitor (sodium metavanadate) on the simulated foaming profile along the

absorber (air flow rate = 38.5 kmol/m2-hr, MEA concentration = 3.0

kmol/m3, CO2 loading of feed solution = 0.33 mol/mol, superficial liquid

velocity = 12.2 m3/m2-hr, and feed solution temperature = 21.1°C

(Aroonwilas, 2001)

150

1.80

1.60

fc 1-40

| « 1.20

jf 1.00

E o> 0.80 ' (V C J

£ ? 0.60 -C «8 g 0.40 o Q- 0.20 ^

0.00 0.00

non-degraded soln degraded soln (deg.prod.) degraded soln (deg.prod. + corr. inhibitor)

I ' ' I ' I ' ' I ' 1 } I T '"T - f1" •""T""' "T - "T' - 'I


2.00

Figure 6.9 Effect of the degradation product (ammonium thiosulfate) and corrosion

inhibitor (sodium metavanadate) on the simulated foaming profile along the

absorber (air flow rate = 38.5 kmol/m -hr, MEA concentration = 3.0

kmol/m , CO2 loading of feed solution = 0.33 mol/mol, superficial liquid

velocity = 12.2 m3/m2-hr, and feed solution temperature = 21.1°C

(Aroonwilas, 2001)

150

6.3.2 Foaming impact on process throughput

In addition to foaming tendency within the absorber, the developed model can

also be used to evaluate the impact of foaming on process throughput. As illustrated in

Figure 6.3b (page 134), the opening space of the corrugation channel is reduced as a

result of foam formation on the packing surface. This could lead to a decrease in

available void space for gas to flow through. Consequently, a reduction in volumetric

flow rate of gas stream is required to maintain a designed gas velocity (i.e. 1 m/s). This is

especially true for the existing plants where column diameter cannot be altered. On the

contrary, in the case of the new plants, such foaming impact can be minimized by

increasing the column diameter to a certain extent to maintain the process throughput.

To evaluate this impact, foam volume and process throughput under the process

conditions listed in Table 6.1 for the MEA solutions were determined using the

developed model. Results in Figure 6.10 show that the gas flow rate of the foaming

system is not significantly reduced (less than 2.1%) from that of the non-foaming system

at any given liquid velocity. This is because the foam volume generated is very small and

decreases the available void space by less than 2.1% from that of the non-foaming

system. However, the gas flow rates of the degraded and inhibited MEA solutions are

slightly reduced from that of the MEA solution containing no degradation product and

corrosion inhibitor. This suggests that the presence of degradation product and corrosion

inhibitor could further reduce the process throughput during foaming.

151

6.3.2 Foaming impact on process throughput

In addition to foaming tendency within the absorber, the developed model can

also be used to evaluate the impact of foaming on process throughput. As illustrated in

Figure 6.3b (page 134), the opening space of the corrugation channel is reduced as a

result of foam formation on the packing surface. This could lead to a decrease in

available void space for gas to flow through. Consequently, a reduction in volumetric

flow rate of gas stream is required to maintain a designed gas velocity (i.e. 1 m/s). This is

especially true for the existing plants where column diameter cannot be altered. On the

contrary, in the case of the new plants, such foaming impact can be minimized by

increasing the column diameter to a certain extent to maintain the process throughput.

To evaluate this impact, foam volume and process throughput under the process

conditions listed in Table 6.1 for the MEA solutions were determined using the

developed model. Results in Figure 6.10 show that the gas flow rate of the foaming

system is not significantly reduced (less than 2.1%) from that of the non-foaming system

at any given liquid velocity. This is because the foam volume generated is very small and

decreases the available void space by less than 2.1% from that of the non-foaming

system. However, the gas flow rates of the degraded and inhibited MEA solutions are

slightly reduced from that of the MEA solution containing no degradation product and

corrosion inhibitor. This suggests that the presence of degradation product and corrosion

inhibitor could further reduce the process throughput during foaming.

151

Table 6.1 Process conditions for the evaluation of foaming impacts on process

performance

Parameter Condition

Liquid phase

MEA concentration (kmol/m3) 3.0

Lean CO2 loading (mol/mol) 0.20

Rich CO2 loading (mol/mol) 0.55

Superficial liquid velocity (m3/m2-hr) 15-26

feed temperature (°C) 40

Gas phase

Superficial gas velocity (m/s) 1.0

CO2 concentration in the gas phase (%) 15

152

Table 6.1 Process conditions for the evaluation of foaming impacts on process

performance

Parameter Condition

Liquid phase

ME A concentration (kmol/m3) 3.0

Lean CO2 loading (mol/mol) 0.20

Rich CO2 loading (mol/mol) 0.55

Superficial liquid velocity (m3/m2-hr) 15-26

feed temperature (°C) 40

Gas phase

Superficial gas velocity (m/s) 1.0

CO2 concentration in the gas phase (%) 15

152

7.0E-03

1€7 I E

6.5E-03

O cf) 6.0E-03

E

o 5.5E-03 U)ea 0

5.0E-03

10.0

—o— non-foaming system

--4c— • foaming system (non-degraded soln)

foaming system (degraded soln. - deg.prod.)

El— foaming system (degraded soln. - deg.prod. + corr. inhibitor)

20.0 Superficial liquid velocity (m3/m2-hr)

30.0

Figure 6.10 Effect of the foaming on the gas volumetric flow rate for non-degraded and

degraded MEA solutions containing degradation product (ammonium

thiosulfate) and corrosion inhibitor (sodium metavanadate) (MEA

concentration = 3.0 kmol/m3, lean and rich CO2 loading of the solution =

0.20 and 0.55 mol/mol, respectively, feed solution temperature = 40°C, and

CO2 concentration in the gas phase = 15%)

153

7.0E-03

to

E "T 6.5E-03 s & I ® 6.0E-03 B o> | o 5.5E-03 > CO a O

5.0E-03 10.0 20.0 30.0

Superficial liquid velocity (m3/m2-hr)

Figure 6.10 Effect of the foaming on the gas volumetric flow rate for non-degraded and

degraded MEA solutions containing degradation product (ammonium

thiosulfate) and corrosion inhibitor (sodium metavanadate) (MEA

concentration = 3.0 kmol/m3, lean and rich CO2 loading of the solution =

0.20 and 0.55 mol/mol, respectively, feed solution temperature = 40°C, and

CO2 concentration in the gas phase = 15%)

—o— non-foaming system

- *- - foaming system (non-degraded soln)

foaming system (degraded soln. - deg.prod.)

- cd- - foaming system (degraded soln. - deg.prod. + corr. inhibitor)

1 I 1

153

7. CONCLUSIONS AND RECOMMENDATIONS

7.1 Conclusions

7.1.1 Parametric study

Results from the parametric study conducted in the static foaming experiment

allow useful conclusions on the effects of process parameters influencing the foaming

behaviour in alkanolamine-based CO2 absorption processes, which are drawn as follows:

• Solution volume affects foaming tendency when it is small. Increasing the solution

volume results in a constant foam volume or foaminess coefficient. After a certain

degree of increase, a plateau in foam volume or foaminess coefficient is reached.

• An increase in superficial gas velocity decreases foaminess coefficient. The gas

superficial gas velocity can lead to a constant foaminess coefficient when increased.

In other words, as above, after a certain degree of increase, a plateau is reached in

foaminess coefficient.

• Ranges of solution volume and superficial gas velocity that lead to a constant

foaminess coefficient were found for the CO2-aqueous alkanolamines. These ranges,

when used for foaming tests, enable the generation of foam data that are not

dependent on solution volume, gas flow rate, pore size of gas disperser, and

dimensions and volume of the test cell.

• Variations in MEA concentration, CO2 loading, and solution temperature affect

foaming tendency. Solution temperature is the most influential. An increase in

temperature decreases foaminess coefficient. The foaminess coefficient increases and

then declines with increasing MEA concentration and CO2 loading.

154

7. CONCLUSIONS AND RECOMMENDATIONS

7.1 Conclusions

7.1.1 Parametric study

Results from the parametric study conducted in the static foaming experiment

allow useful conclusions on the effects of process parameters influencing the foaming

behaviour in alkanolamine-based CO2 absorption processes, which are drawn as follows:

• Solution volume affects foaming tendency when it is small. Increasing the solution

volume results in a constant foam volume or foaminess coefficient. After a certain

degree of increase, a plateau in foam volume or foaminess coefficient is reached.

• An increase in superficial gas velocity decreases foaminess coefficient. The gas

superficial gas velocity can lead to a constant foaminess coefficient when increased.

In other words, as above, after a certain degree of increase, a plateau is reached in

foaminess coefficient.

• Ranges of solution volume and superficial gas velocity that lead to a constant

foaminess coefficient were found for the CC>2-aqueous alkanolamines. These ranges,

when used for foaming tests, enable the generation of foam data that are not

dependent on solution volume, gas flow rate, pore size of gas disperser, and

dimensions and volume of the test cell.

• Variations in ME A concentration, CO2 loading, and solution temperature affect

foaming tendency. Solution temperature is the most influential. An increase in

temperature decreases foaminess coefficient. The foaminess coefficient increases and

then declines with increasing MEA concentration and CO2 loading.

154

• Most degradation products and corrosion inhibitors in aqueous MEA solutions

enhance foaminess coefficient, except for sulfuric acid.

• MEA, MDEA, and MEA+AMP (2:1 mixing mole ratio) generate apparent foams

while DEA, AMP, MEA+MDEA, DEA+MDEA, and MEA+AMP (1:1 and 1:2) do

not.

• Physical properties, particularly surface tension, density, and viscosity of solution,

play a significant role in foaming tendency through foam formation and foam

stability.

7.1.2 Pneumatic foam height correlation

The empirical correlation for predicting pneumatic steady-state foam heights

generated in the CO2 absorption process using aqueous MEA solutions and a series of

subroutine modules for physical property estimation was successfully developed. The

foam height correlation was built on the Pilon et al. (2001) model with constants K and N

equalling 4394 and -1.30, respectively, and dimensionless Ca, Re, and Fr in the ranges of

2.0x 10-3 - 6.3x 10-2, 5.0 — 276.4, and 0.01 — 0.89, respectively. The calculations involve

numerical iteration and statistical analysis, namely multiple non-linear regression with a

stochastic technique, as well as a series of subroutine modules for the estimation of

average bubble radius and physical properties. The findings are summarized as follows:

• The correlation fits well with the experimental foam data with R2 of 0.88. Most of the

predicted foam heights are in a good agreement with the experimental results within

the 95% confidence interval and can also predict the foaming tendency of the

solutions as the process conditions are varied.

155

• Most degradation products and corrosion inhibitors in aqueous MEA solutions

enhance foaminess coefficient, except for sulfuric acid.

• MEA, MDEA, and MEA+AMP (2:1 mixing mole ratio) generate apparent foams

while DEA, AMP, MEA+MDEA, DEA+MDEA, and MEA+AMP (1:1 and 1:2) do

not.

• Physical properties, particularly surface tension, density, and viscosity of solution,

play a significant role in foaming tendency through foam formation and foam

stability.

7.1.2 Pneumatic foam height correlation

The empirical correlation for predicting pneumatic steady-state foam heights

generated in the CO2 absorption process using aqueous MEA solutions and a series of

subroutine modules for physical property estimation was successfully developed. The

foam height correlation was built on the Pilon et al. (2001) model with constants K and N

equalling 4394 and -1.30, respectively, and dimensionless Ca, Re, and Fr in the ranges of

2.0xl0"3 - 6.3xl0"2, 5.0 - 276.4, and 0.01 - 0.89, respectively. The calculations involve

numerical iteration and statistical analysis, namely multiple non-linear regression with a

stochastic technique, as well as a series of subroutine modules for the estimation of

average bubble radius and physical properties. The findings are summarized as follows:

• The correlation fits well with the experimental foam data with R2 of 0.88. Most of the

predicted foam heights are in a good agreement with the experimental results within

the 95% confidence interval and can also predict the foaming tendency of the

solutions as the process conditions are varied.

155

• The correlation shows that the foam height inversely depends on the bubble radius, the

difference between the liquid and gas densities, and the surface tension but

proportionally depends on the viscosity and the superficial gas velocity.

• From the sensitivity analysis, the predicted foam height increases with superficial gas

velocity, solution volume, CO2 loading, MEA concentration, gas density, liquid

density, and liquid viscosity but decreases with solution temperature and surface

tension. Compared to other process parameters, solution volume is the most influential

on foam height, followed by solution temperature, and among physical properties,

foam height is the most sensitive to liquid viscosity, followed by liquid density and

surface tension, but it is not sensitive to gas density.

7.1.3 Foam model

A foam model for the alkanolamine-based CO2 absorption process was

successfully developed and verified with the experimental foaming data obtained from a

0.10 m (ID.) absorption column fitted with Mellapak 500.Y. Experimental results show

that superficial liquid velocity has an apparent effect on foam volume, whereas

superficial gas velocity has a negligible effect at a low liquid velocity and a small effect

at higher liquid velocities. The model has the capacity to predict foam volumes within the

absorber with an AAD of 16.3% and to determine local foam volumes at different

locations within a column packed with structured packing, which can be used to evaluate

foaming tendency and process throughput of the column and particularly the absorber.

The simulation results show that foaming is likely to occur more at the absorber top than

the bottom and causes no significant reduction in process throughput. However, during

actual plant operation, one can anticipate more foam volumes within the process due to

156

• The correlation shows that the foam height inversely depends on the bubble radius, the

difference between the liquid and gas densities, and the surface tension but

proportionally depends on the viscosity and the superficial gas velocity.

• From the sensitivity analysis, the predicted foam height increases with superficial gas

velocity, solution volume, CO2 loading, MEA concentration, gas density, liquid

density, and liquid viscosity but decreases with solution temperature and surface

tension. Compared to other process parameters, solution volume is the most influential

on foam height, followed by solution temperature, and among physical properties,

foam height is the most sensitive to liquid viscosity, followed by liquid density and

surface tension, but it is not sensitive to gas density.

7.1.3 Foam model

A foam model for the alkanolamine-based CO2 absorption process was

successfully developed and verified with the experimental foaming data obtained from a

0.10 m (ID.) absorption column fitted with Mellapak 500.Y. Experimental results show

that superficial liquid velocity has an apparent effect on foam volume, whereas

superficial gas velocity has a negligible effect at a low liquid velocity and a small effect

at higher liquid velocities. The model has the capacity to predict foam volumes within the

absorber with an AAD of 16.3% and to determine local foam volumes at different

locations within a column packed with structured packing, which can be used to evaluate

foaming tendency and process throughput of the column and particularly the absorber.

The simulation results show that foaming is likely to occur more at the absorber top than

the bottom and causes no significant reduction in process throughput. However, during

actual plant operation, one can anticipate more foam volumes within the process due to

156

the presence of suspended solids and surfactant-based additives in the solutions, which

were not accounted for in this work.

7.2 Recommendations for future work

• Effect of solution volume and type of dispersing gas

For a pneumatic foam height correlation, the solution volume should be explicitly

included in the correlation as the independent parameter, as discussed in Chapter 5, since

it affects the terminal velocity of bubbles reaching the interface to form a foam layer.

Another improvement in the prediction is to account for the effect of gas type by

incorporating other physical properties of gas, besides the gas density, such as diffusion

coefficient and Oswald coefficient or solubility of gas in the liquid phase in future

correlations. Since the proposed correlation in this work was built on a set of foam

heights that were generated by one gas (i.e. N2) and no research has been conducted to

investigate the effect of the gas type on the foam height for this particular aqueous

solution, this limits the opportunity to examine foaming phenomena that can be affected

by the type of gas, such as, disproportionation. Hartland et al. (1993) studied the effect of

gases (i.e., xenon, nitrous oxide, N2 and CO2) used to bubble an aqueous solution of

10%wt glycerinate with the addition of Marlophen 89 on the foam height. They

discovered that the foam layer dispersed by gas with a higher gas solubility tended to be

more susceptible to collapse than that by gas with a lower gas solubility since the

interbubble gas diffusion or so-called disproportionation was much more pronounced at a

higher degree of solubility. This consequently led to poorer foam stability as a result of

faster growth in large bubbles or, in the other words, a more rapid decrease in the

interfacial area per unit gas volume (Hartland et al., 1993).

157

the presence of suspended solids and surfactant-based additives in the solutions, which

were not accounted for in this work.

7.2 Recommendations for future work

• Effect of solution volume and type of dispersing gas

For a pneumatic foam height correlation, the solution volume should be explicitly

included in the correlation as the independent parameter, as discussed in Chapter 5, since

it affects the terminal velocity of bubbles reaching the interface to form a foam layer.

Another improvement in the prediction is to account for the effect of gas type by

incorporating other physical properties of gas, besides the gas density, such as diffusion

coefficient and Oswald coefficient or solubility of gas in the liquid phase in future

correlations. Since the proposed correlation in this work was built on a set of foam

heights that were generated by one gas (i.e. N2) and no research has been conducted to

investigate the effect of the gas type on the foam height for this particular aqueous

solution, this limits the opportunity to examine foaming phenomena that can be affected

by the type of gas, such as, disproportionation. Hartland et al. (1993) studied the effect of

gases (i.e., xenon, nitrous oxide, N2 and CO2) used to bubble an aqueous solution of

10%wt glycerinate with the addition of Marlophen 89 on the foam height. They

discovered that the foam layer dispersed by gas with a higher gas solubility tended to be

more susceptible to collapse than that by gas with a lower gas solubility since the

interbubble gas diffusion or so-called disproportionation was much more pronounced at a

higher degree of solubility. This consequently led to poorer foam stability as a result of

faster growth in large bubbles or, in the other words, a more rapid decrease in the

interfacial area per unit gas volume (Hartland et al., 1993).

• Measurements of physical properties and average bubble radius

The model accuracy can be augmented by measuring physical properties and

average bubble radius rather than predicting and reducing model assumptions to account

for the complexity of the system. Measurements of physical properties of the solutions

are expected to enhance the accuracy of prediction. In particular, it is necessary to

measure both the equilibrium and dynamic surface tension of the CO2-loaded aqueous

solutions of alkanolamine, which are among the crucial liquid properties for foam

mechanisms, since no open literature has been published containing the information

regarding these surface tension measurements to date. Not only would this information

help predict foam height more accurately, but it is also expected to give a more in-depth

explanation of the foaming behaviour in this CO2 absorption process.

• Effects of suspended solids and surfactant-based additives

Suspended solids are considered one of the important factors and, based on plant

experience, are commonly found in the alkanolamine-based gas absorption process, being

introduced through either external or internal sources (Ballard, 1966, Lieberman, 1980,

Keaton and Bourke, 1983, Pauley et al., 1989). Iron sulphide (FeS) is recommended as an

example of the suspended solids to test the effect of suspended solids since it can be

formed in the circulating alkanolamine system through corrosion. Results from this work

can help establish the relationship between corrosion and foaming problems, which

would help practitioners to predict the onset of foam in the system more effectively. In

addition, the effect of surfactant-based additives, including corrosion inhibitors and

antifoam agents, should be examined to expand the application of the model.

158

• Measurements of physical properties and average bubble radius

The model accuracy can be augmented by measuring physical properties and

average bubble radius rather than predicting and reducing model assumptions to account

for the complexity of the system. Measurements of physical properties of the solutions

are expected to enhance the accuracy of prediction. In particular, it is necessary to

measure both the equilibrium and dynamic surface tension of the C02-loaded aqueous

solutions of alkanolamine, which are among the crucial liquid properties for foam

mechanisms, since no open literature has been published containing the information

regarding these surface tension measurements to date. Not only would this information

help predict foam height more accurately, but it is also expected to give a more in-depth

explanation of the foaming behaviour in this CO2 absorption process.

• Effects of suspended solids and surfactant-based additives

Suspended solids are considered one of the important factors and, based on plant

experience, are commonly found in the alkanolamine-based gas absorption process, being

introduced through either external or internal sources (Ballard, 1966, Lieberman, 1980,

Keaton and Bourke, 1983, Pauley et al., 1989). Iron sulphide (FeS) is recommended as an

example of the suspended solids to test the effect of suspended solids since it can be

formed in the circulating alkanolamine system through corrosion. Results from this work

can help establish the relationship between corrosion and foaming problems, which

would help practitioners to predict the onset of foam in the system more effectively. In

addition, the effect of surfactant-based additives, including corrosion inhibitors and

antifoam agents, should be examined to expand the application of the model.

158

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167

Yanicki, G.; Trebble, M. A. Experimental Measurements of Foaming Tendencies in Aqueous Gas Sweetening Solutions Containing MDEA over a Temperature Range of 297 - 358K and a Pressure Range of 101 - 500 kPa. Chemical Engineering Communications. 2006, 193(10), 1151 - 1163.

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167

Appendix A

Experimental data of parametric study

A.1 Effect of superficial gas velocity

Table A.1 Experimental data for the effect of superficial gas velocity at MEA

concentration of 2.0 kmol/m3

Superficial gas velocity (m3/m2-hr) Foaminess coefficient (min)

0.44 2.02

0.44 2.05

0.88 1.49

0.88 1.42

1.75 0.81

1.75 0.80

2.06 0.80

2.06 0.80

2.41 0.80

2.41 0.79

2.79 0.90

2.79 0.73

3.40 0.49

3.40 0.50

168

Appendix A

Experimental data of parametric study

A.1 Effect of superficial gas velocity




0.44 2.02

0.44 2.05

0.88 1.49

0.88 1.42

1.75 0.81

1.75 0.80

2.06 0.80

2.06 0.80

2.41 0.80

2.41 0.79

2.79 0.90

2.79 0.73

3.40 0.49

3.40 0.50

168



Superficial gas velocity (m3/m2-br) Foaminess coefficient (min)

0.44 5.00

0.88 2.84

1.32 2.07

1.54 1.84

1.75 1.65

2.06 1.41

2.19 1.62

2.41 1.38

2.79 1.02

3.40 0.92

169

Table A.2 Experimental data for the effect of superficial gas velocity at ME A



0.44 5.00

0.88 2.84

1.32 2.07

1.54 1.84

1.75 1.65

2.06 1.41

2.19 1.62

2.41 1.38

2.79 1.02

3.40 0.92

169

A.2 Effect of solution volume

Table A.3 Experimental data for the effect of solution volume

Solution volume (cm3) Foaminess coefficient (min)

200 0.00

200 0.00

250 0.40

330 0.65

330 0.68

350 0.78

350 0.79

400 0.80

400 0.80

450 0.82

450 0.82

550 0.83

550 0.83

700 0.83

170

A.2 Effect of solution volume

Table A3 Experimental data for the effect of solution volume

Solution volume (cm3) Foaminess coefficient (min)

200 0.00

200 0.00

250 0.40

330 0.65

330 0.68

350 0.78

350 0.79

400 0.80

400 0.80

450 0.82

450 0.82

550 0.83

550 0.83

700 0.83

170

A.3 Effect of MEA concentration

Table A.4 Experimental data for the effect of MEA concentration at the absorber top

condition

MEA concentration (kmol/m3) Foaminess coefficient (min)

0.81

2.0 0.76

0.80

0.96

3.0 0.94

0.96

0.84

5.0 0.94

0.89

0.96

5.5

0.96

0.93

0.97

6.0

0.89

0.81

0.96

0.71

7.0 0.70

0.71

171

A3 Effect of MEA concentration

Table A.4 Experimental data for the effect of MEA concentration at the absorber top

condition


0.81

2.0 0.76

0.80

0.96

3.0 0.94

0.96

0.84

0.94

0.89

0.96

0.96

0.93

0.97

0.89

0.81

0.96

0.71

7.0 0.70

0.71

5.0

5.5

6.0

171

Table AS Experimental data for the effect of MEA concentration at the absorber bottom

condition


0.61

2.0 0.63

0.63

0.65

3.0 0.72

0.72

0.85

4.0 0.86

0.86

0.79

0.79

0.82 5.0

0.80

0.84

0.84

0.93

6.0 0.88

0.78

0.72

7.0 0.74

0.71

172

Table A.5 Experimental data for the effect of MEA concentration at the absorber bottom

condition


0.61

2.0 0.63

0.63

0.65

0.72

0.72

0.85

0.86

0.86

0.79

0.79

0.82

0.80

0.84

0.84

0.93

0.88

0.78

0.72

0.74

0.71

3.0

4.0

5.0

6.0

7.0

172

A.4 Effect of CO2 loading

Table A.6 Experimental data for the effect of CO2 loading at the solution temperature of

40°C

CO2 loading in solution (mol CO2/mol MEA) Foaminess coefficient (min)

0.10 0.74

0.94

0.89 0.20

0.96

0.84

0.30 1.15

1.17 0.33

1.35

0.40 1.41

0.44 1.17

0.48 1.07

0.99 0.53

1.20

0.55 0.90

173

A.4 Effect of CO2 loading


40°C

C02 loading in solution (mol C02/mol MEA) Foansiness coefficient (min)

0.10 0.74

0.94

0.89 0.20

0.96

0.84

0.30 1.15

1.17 0.33

1.35

0.40 1.41

0.44 1.17

0.48 1.07

0.99 0.53

1.20

0.55 0.90

173


60°C

CO2 loading in solution (mol CO2/mol MEA) Foaminess coefficient (min)

0.10 0.39

0.53

0.56

0.20 0.54

0.57

0.55

0.25 0.57

0.30 0.61

0.33 0.70

0.35 0.68

0.84

0.84

0.80 0.40

0.79

0.82

0.79

0.45 0.97

0.50 0.88

0.67 0.53

0.69

0.55 0.75

174


60°C

CO2 loading In solution (mol C02/mol MEA) Foaminess coefficient (min)

0.10 0.39

0.53

0.56

0.20 0.54

0.57

0.55

0.25 0.57

0.30 0.61

0.33 0.70

0.35 0.68

0.84

0.84

0.80 0.40

0.79

0.82

0.79

0.45 0.97

0.50 0.88

0.67 0.53

0.69

0.55 0.75

174


90°C

CO2 loading in solution (mot CO2/mol MEA) Foaminess coefficient (min)

0.00 0.20

0.10

0.27 0.33

0.34

0.54 0.40

0.50

0.65 0.53

0.77

175


90°C

CO2 loading in solution (mol CCVmol MEA) Foaminess coefficient (min)

0.00 0.20

0.10

0.27 0.33

0.34

0.54 0.40

0.50

0.65 0.53

0.77

175

A.5 Effect of solution temperature

Table A.9 Experimental data for the effect of solution temperature at the CO2 loading of

0.20 mol CO2/mol MEA

Solution temperature (°C) Foaminess coefficient (min)

0.84

40 0.94

0.89

0.73 50

0.72

0.56

0.54

60 0.53

0.57

0.55

0.27 70

0.30

0.02 80

0.22

0.00 90

0.10

176

A.5 Effect of solution temperature

Table A.9 Experimental data for the effect of solution temperature at the CO2 loading of

0.20 mol CCVmol MEA


40

0.84

0.94

0.89

0.73 50

0.72

0.56

0.54

60 0.53

0.57

0.55

0.27 70

0.30

80 0.02

0.22

90 0.00

0.10

176

Table A.10 Experimental data for the effect of solution temperature at the CO2 loading

of 0.40 mol CO2/mol MEA


40 1.41

1.02 50

0.94

0.79

0.82

0.79 60

0.80

0.84

0.84

0.68 70

0.65

0.54 80

0.58

0.54 90

0.50

177

Table A.10 Experimental data for the effect of solution temperature at the CO2 loading

of 0.40 mol CCVmol MEA


40 1.41

1.02 50

0.94

0.79

0.82

0.79 60

0.80

0.84

0.84

0.68 70

0.65

0.54 80

0.58

90 0.54

0.50

177

A.6 Effect of degradation products of MEA

Table A.11 Experimental data for the effect of degradation products of MEA

Degradation product Foaminess coefficient (min)

0.78

0.79

None 0.79

0.82

0.80

1.00


0.99

0.92

Glycolic acid 0.97

0.94

0.89

Sodium sulfite 0.97

0.91

0.91

Malonic acid 0.91

0.94

0.87

Oxalic acid 0.94

0.88

178

A.6 Effect of degradation products of MEA

Table A. 11 Experimental data for the effect of degradation products of MEA


0.78

0.79

None 0.79

0.82

0.80

1.00


0.99

0.92

Glycolic acid 0.97

0.94

0.89

Sodium sulfite 0.97

0.91

0.91

Malonic acid 0.91

0.94

0.87

Oxalic acid 0.94

0.88

178

Table A.11 Experimental data for the effect of degradation products of MEA (continued)


0.89


0.89

0.90


0.89

0.83


0.86

0.83

Bicine 0.86

0.85

0.80


0.82

0.85

Formic acid 0.79

0.84

0.86

Acetic acid 0.77

0.82

0.73

Sulfuric acid 0.78

0.80

179

Table A. 11 Experimental data for the effect of degradation products of ME A (continued)


0.89


0.89

0.90


0.89

0.83


0.86

0.83

Bicine 0.86

0.85

0.80


0.82

0.85

Formic acid 0.79

0.84

0.86

Acetic acid 0.77

0.82

0.73

Sulfuric acid 0.78

0.80

179

A.7 Effect of corrosion inhibitor

Table A.12 Experimental data for the effect of corrosion inhibitor

Corrosion inhibitor Foaminess coefficient (min)

0.78

0.79

None 0.79

0.82

0.80

0.99

Sodium metavanadate 1.00

1.05

0.88

Copper carbonate 0.96

0.97

0.83

Sodium sulfite 0.88

0.78

180

A. 7 Effect of corrosion inhibitor

Table A.12 Experimental data for the effect of corrosion inhibitor

Corrosion inhibitor Foaminess coefficient (min)

0.78

0.79

None 0.79

0.82

0.80

0.99

Sodium metavanadate 1.00

1.05

0.88

Copper carbonate 0.96

0.97

0.83

Sodium sulfite 0.88

0.78

180

A.8 Effect of alkanolamine type

Table A.13 Experimental data for the effect of alkanolamine type (single alkanolamine)

Type of alkanolamine Foaminess coefficient (min)

0.85

None 0.86

0.86

No foam

DEA No foam

No foam

0.34

MDEA 0.31

0.32

No foam

AMP No foam

No foam

181

A.8 Effect of alkanolamine type

Table A. 13 Experimental data for the effect of alkanolamine type (single alkanolamine)


0.85

None 0.86

0.86

No foam

DEA No foam

No foam

MDEA

0.34

0.31

0.32

No foam

AMP No foam

No foam

181

Table A.14 Experimental data for the effect of alkanolamine type (blended

alkanolamine)


No foam


No foam

No foam


No foam

No foam


No foam

No foam


No foam

No foam


No foam

No foam


No foam

No foam


No foam

No foam


No foam

0.13

MEA + AMP (2:1) 0.13

0.13

182

Table A.14 Experimental data for the effect of alkanolamine type (blended

alkanolamine)


No foam


No foam

No foam


No foam

No foam


No foam

No foam

DEA +MDEA (1:2) No foam

No foam

No foam


No foam

No foam


No foam

No foam


No foam

No foam


No foam

0.13

MEA + AMP (2:1) 0.13

0.13

182

Appendix B

Input parameters and simulation outputs of a foam height correlation

183

Appendix B

Input parameters and simulation outputs of a foam height correlation

183

Table B.1 Input parameters and simulation outputs of a foam height correlation

Input parameter Physical property Output Heq,

(mm) Veen

(cm3) M

(kmolim3) T

(°C) 6

(mm/s) 11,1

(cm ) aco2

(mol/mol) p6

(kg/m3) ft

(kg/m3) y

(mN/m) IA

(mPa s) Pi "°'e" (N/m2)

P (N/m2)

r (mm)

Ca (x10-3)

Fr Re H (mm)

0.0 215 2.0 40 0.57 200 0.4 1.09 1031.25 60.42 0.999 100343 100327 0.47 9.47 0.07 276 4.7 0.0 215 2.0 40 0.57 200 0.4 1.09 1031.25 60.42 0.999 100343 100327 0.47 9.47 0.07 276 4.7 13.8 265 2.0 40 0.57 250 0.40 1.09 1031.25 60.42 0.999 99860 99897 0.26 9.47 0.13 153 12.3 22.4 348 2.0 40 0.57 330 0.40 1.09 1031.25 60.42 0.999 99366 99366 0.18 9.47 0.19 105 22.4 23.3 348 2.0 40 0.57 330 0.40 1.09 1031.25 60.42 0.999 99345 99366 0.18 9.47 0.19 105 22.2 26.9 370 2.0 40 0.57 350 0.40 1.09 1031.25 60.42 0.999 99196 99253 0.17 9.47 0.20 101 23.8 27.0 370 2.0 40 0.57 350 0.40 1.09 1031.25 60.42 0.999 99195 99253 0.17 9.47 0.20 101 23.8 27.5 420 2.0 40 0.57 400 0.40 1.09 1031.25 60.42 0.999 99001 98999 0.16 9.47 0.22 92 27.6 27.5 420 2.0 40 0.57 400 0.40 1.09 1031.25 60.42

._ 0.999 99000 98999 0.16 9.47 0.22 92 27.6

28.2 470 2.0 40 0.57 450 0.40 1.09 1031.25 60.42 0.999 98802 98775 0.15 9.47 0.23 88 29.7 28.2 470 2.0 40 0.57 450 0.40 1.09 1031.25 60.42 0.999 98800 98775 0.15 9.47 0.23 88 29.7 28.5 580 2.0 40 0.57 550 0.40 1.09 1031.25 60.42 0.999 98424 98394 0.15 9.47 0.23 87 30.3 28.4 580 2.0 40 0.57 550 0.40 1.09 1031.25 60.42 0.999 98427 98394 0.15 9.47 0.23 87 30.3 28.6 735 2.0 40 0.57 700 0.40 1.09 1031.25 60.42 0.999 97868 97939 0.17 9.47 0.20 99 24.6 14.8 411 2.0 40 0.12 400 0.40 1.09 1031.25 60.42 0.999 99105 98999 0.15 2.01 0.01 19 18.5 15.0 413 2.0 40 0.12 400 0.40 1.09 1031.25 60.42 0.999 99099 98999 0.15 2.01 0.01 19 18.5 21.7 412 2.0 40 0.24 400 0.40 1.09 1031.25 60.42 0.999 99005 98999 0.15 4.03 0.04 38 22.0 20.7 418 2.0 40 0.24 400 0.40 1.09 1031.25 60.42 0.999 99030 98999 0.15 4.03 0.04 38 22.1 23.6 420 2.0 40 0.49 400 0.40 1.09 1031.25 60.42 0.999 99058 98999 0.15 8.06 0.16 77 26.8 23.5 420 2.0 40 0.49 400 0.40 1.09 1031.25 60.42 0.999 99062 98999 0.15 8.06 0.16 77 26.8 27.5 420 2.0 40 0.57 400 0.40 1.09 1031.25 60.42 0.999 99001 98999 0.16 9.47 0.22 92 27.6 27.5 420 2.0 40 0.57 400 0.40 1.09 1031.25 60.42 0.999 99000 98999 0.16 9.47 0.22 92 27.6 32.2 420 2.0 40 0.67 400 0.40 1.09 1031.25 60.42 0.999 98932 98999 0.16 11.08 0.29 109 28.2 31.6 425 2.0 40 0.67 400 0.40 1.09 1031.25 60.42 0.999 98943 98999 0.16 11.08 0.29 109 28.3 41.7 420 2.0 40 0.77 400 0.40 1.09 1031.25 60.42 0.999 98789 98999 0.16 12.79 0.37 130 28.0 33.7 421 2.0 40 0.77 400 0.40 1.09 1031.25 60.42 0.999 98928 98999 0.16 12.79 0.38 127 29.2 27.6 425 2.0 40 0.94 400 0.40 1.09 1031.25 60.42 0.999 99067 98999 0.16 15.61 0.58 152 32.0 28.1 425 2.0 40 0.94 400 0.40 1.09 1031.25 60.42 0.999 99058 98999 0.16 15.61 0.58 152 31.9 36.6 420 5.0 40 0.12 400 0.40 1.09 1089.44 42.66 2.357 98697 98696 0.09 6.73 0.02 5 36.5 41.6 420 5.0 40 0.24 400 0.40 1.09 1089.44 42.66 2.357 98729 98728 0.09 13.47 0.07 10 41.7 45.5 430 5.0 40 0.37 400 0.40 1.09 1089.44 42.66 2.357 98736 98747 0.10 20.20 0.14 16 44.7

Table B.1 Input parameters and simulation outputs of a foam height correlation

00

Input parameter Physical property Output

(mm) yL"*

(cm3) M

(kmol/m3) r

CC) G

(mm/s) K"! (cm3)

OC02 (mol/mol)

PC, (kg/m3) (kg/m3)

7 (mN/m)

At (mPas)

p*,Urttt

(N/m2) P*

(N/m2) r

(mm) Ca

(xl0°) Fr Re H

(mm)

0.0 215 2.0 40 0.57 200 0.4 1.09 1031.25 60.42 0.999 100343 100327 0.47 9.47 0.07 276 4.7 0.0 215 2.0 40 0.57 200 0.4 1.09 1031.25 60.42 0.999 100343 100327 0.47 9.47 0.07 276 4.7 13.8 265 2.0 40 0.57 250 0.40 1.09 1031.25 60.42 0.999 99860 99897 0.26 9.47 0.13 153 12.3 22.4 348 2.0 40 0.57 330 0.40 1.09 1031.25 60.42 0.999 99366 99366 0.18 9.47 0.19 105 22.4 23.3 348 2.0 40 0.57 330 0.40 1.09 1031.25 60.42 0.999 99345 99366 0.18 9.47 0.19 105 22.2 26.9 370 2.0 40 0.57 350 0.40 1.09 1031.25 60.42 0.999 991% 99253 0.17 9.47 0.20 101 23.8 27.0 370 2.0 40 0.57 350 0.40 1.09 1031.25 60.42 0.999 99195 99253 0.17 9.47 0.20 101 23.8 27.5 420 2.0 40 0.57 400 0.40 1.09 1031.25 60.42 0.999 99001 98999 0.16 9.47 0.22 92 27.6 27.5 420 2.0 40 0.57 400 0.40 1.09 1031.25 60.42 0.999 99000 98999 0.16 9.47 0.22 92 27.6 28.2 470 2.0 40 0.57 450 0.40 1.09 1031.25 60.42 0.999 98802 98775 0.15 9.47 0.23 88 29.7 28.2 470 2.0 40 0.57 450 0.40 1.09 1031.25 60.42 0.999 98800 98775 0.15 9.47 0.23 88 29.7 28.5 580 2.0 40 0.57 550 0.40 1.09 1031.25 60.42 0.999 98424 98394 0.15 9.47 0.23 87 30.3 28.4 580 2.0 40 0.57 550 0.40 1.09 1031.25 60.42 0.999 98427 98394 0.15 9.47 0.23 87 30.3 28.6 735 2.0 40 0.57 700 0.40 1.09 1031.25 60.42 0.999 97868 97939 0.17 9.47 0.20 99 24.6 14.8 411 2.0 40 0.12 400 0.40 1.09 1031.25 60.42 0.999 99105 98999 0.15 2.01 0.01 19 18.5 15.0 413 2.0 40 0.12 400 0.40 1.09 1031.25 60.42 0.999 99099 98999 0.15 2.01 0.01 19 18.5 21.7 412 2.0 40 0.24 400 0.40 1.09 1031.25 60.42 0.999 99005 98999 0.15 4.03 0.04 38 22.0 20.7 418 2.0 40 0.24 400 0.40 1.09 1031.25 60.42 0.999 99030 98999 0.15 4.03 0.04 38 22.1 23.6 420 2.0 40 0.49 400 0.40 1.09 1031.25 60.42 0.999 99058 98999 0.15 8.06 0.16 77 26.8 23.5 420 2.0 40 0.49 400 0.40 1.09 1031.25 60.42 0.999 99062 98999 0.15 8.06 0.16 77 26.8 27.5 420 2.0 40 0.57 400 0.40 1.09 1031.25 60.42 0.999 99001 98999 0.16 9.47 0.22 92 27.6 27.5 420 2.0 40 0.57 400 0.40 1.09 1031.25 60.42 0.999 99000 98999 0.16 9.47 0.22 92 27.6 32.2 420 2.0 40 0.67 400 0.40 1.09 1031.25 60.42 0.999 98932 98999 0.16 11.08 0.29 109 28.2 31.6 425 2.0 40 0.67 400 0.40 1.09 1031.25 60.42 0.999 98943 98999 0.16 11.08 0.29 109 28.3 41.7 420 2.0 40 0.77 400 0.40 1.09 1031.25 60.42 0.999 98789 98999 0.16 12.79 0.37 130 28.0 33.7 421 2.0 40 0.77 400 0.40 1.09 1031.25 60.42 0.999 98928 98999 0.16 12.79 0.38 127 29.2 27.6 425 2.0 40 0.94 400 0.40 1.09 1031.25 60.42 0.999 99067 98999 0.16 15.61 0.58 152 32.0 28.1 425 2.0 40 0.94 400 0.40 1.09 1031.25 60.42 0.999 99058 98999 0.16 15.61 0.58 152 31.9 36.6 420 5.0 40 0.12 400 0.40 1.09 1089.44 42.66 2.357 98697 98696 0.09 6.73 0.02 5 36.5 41.6 420 5.0 40 0.24 400 0.40 1.09 1089.44 42.66 2.357 98729 98728 0.09 13.47 0.07 10 41.7 45.5 430 5.0 40 0.37 400 0.40 1.09 1089.44 42.66 2.357 98736 98747 0.10 20.20 0.14 16 44.7

Table B.1 Input parameters and simulation outputs of a foam height correlation (continued)

Input parameter Physical property Output H.?

(mm) VL" R(cm3)

M (kmol/m3)

T (°C)

G (mm/s)

Vsof (cm )

aCO2 (mol/mol)

PG , (kg/m')

Pi (kg/m3)

r(mN/m)

pi,(mPa s)

?And

(N/m2)

10

(N/m2)

r

(mm)

Ca

(x10-3)

Fr Re H(mm)

47.0 425 5.0 40 0.43 400 0.40 1.09 1089.44 42.66 2.357 98740 98754 0.10 23.57 0.19 19 45.9 48.3 425 5.0 40 0.49 400 0.40 1.09 1089.44 42.66 2.357 98744 98760 0.10 26.94 0.25 22 46.9 48.4 425 5.0 40 0.57 400 0.40 1.09 1089.44 42.66 2.357 98769 98767 0.10 31.65 0.34 26 48.5 59.4 420 5.0 40 0.61 400 0.40 1.09 1089.44 42.66 2.357 98632 98770 0.10 33.67 0.37 29 46.5 55.5 420 5.0 40 0.67 400 0.40 1.09 1089.44 42.66 2.357 98700 98774 0.10 37.04 0.45 31 48.5 47.5 425 5.0 40 0.77 400 0.40 1.09 1089.44 42.66 2.357 98828 98781 0.10 42.77 0.61 36 52.0 52.3 425 5.0 40 0.94 400 0.40 1.09 1089.44 42.66 2.357 98796 98790 0.10 52.20 0.89 45 52.9 21.1 412 2.0 60 0.57 400 0.40 1.02 1020.90 58.76 0.693 99116 99121 0.17 6.75 0.20 144 20.8 21.6 425 2.0 60 0.57 400 0.40 1.02 1020.90 58.76 0.693 99106 99121 0.17 6.75 0.19 145 20.8 21.6 428 2.0 60 0.57 400 0.40 1.02 1020.90 58.76 0.693 99105 99121 0.17 6.75 0.19 145 20.8 22.3 425 3.0 60 0.57 400 0.40 1.02 1039.72 53.14 0.879 99108 99061 0.15 9.48 0.23 101 24.8 24.7 425 3.0 60 0.57 400 0.40 1.02 1039.72 53.14 0.879 99058 99061 0.15 9.48 0.22 101 24.5 24.9 428 3.0 60 0.57 400 0.40 1.02 1039.72 53.14 0.879 99054 99061 0.15 9.48 0.22 101 24.5 29.2 425 4.0 60 0.57 400 0.40 1.02 1058.46 47.21 1.147 98999 98998 0.13 13.91 0.26 68 29.3 29.5 423 4.0 60 0.57 400 0.40 1.02 1058.46 47.21 1.147 98995 98998 0.13 13.91 0.26 68 29.2 29.4 420 4.0 60 0.57 400 0.40 1.02 1058.46 47.21 1.147 98995 98998 0.13 13.91 0.26 68 29.2 27.1 430 5.0 60 0.57 400 0.40 1.02 1077.12 40.97 1.540 99072 99041 0.12 21.53 0.27 49 29.3 27.2 430 5.0 60 0.57 400 0.40 1.02 1077.12 40.97 1.540 99071 99041 0.12 21.53 0.27 49 29.3 28.1 430 5.0 60 0.57 400 0.40 1.02 1077.12 40.97 1.540 99055 99041 0.12 21.53 0.27 49 29.1 28,7 425 5.0 60 0.57 400 0.40 1.02 1077.12 40.97 1.540 99045 99041 0.12 21.53 0.27 49 29.0 28.9 430 5.0 60 0.57 400 0.40 1.02 1077.12 40.97 1.540 99041 99041 0.12 21.53 0.27 50 29.0 31.9 428 6.0 60 0.57 400 0.40 1.02 1095.64 34.42 2.131 99038 99139 0.13 35.46 0.26 38 24.2 30.2 430 6.0 60 0.57 400 0.40 1.02 1095.64 34.42 2.131 99064 99139 0.13 35.46 0.26 38 24.5 26.9 432 6.0 60 0.57 400 0.40 1.02 1095.64 34.42 2.131 99115 99139 0.13 35.46 0.26 37 25.2 24.8 428 7.0 60 0.57 400 0.40 1.02 1114.01 27.55 3.041 99191 99193 0.12 63.22 0.28 25 24.6 25.3 430 7.0 60 0.57 400 0.40 1.02 1114.01 27.55 3.041 99183 99193 0.12 63.22 0.28 25 24.5 24.4 430 7.0 60 0.57 400 0.40 1.02 1114.01 27.55 3.041 991% 99193 0.12 63.22 0.28 25 24.7 27.9 420 2.0 40 0.57 400 0.20 1.09 1013.96 61.81 0.950 99015 99019 0.16 8.80 0.21 97 27.6 26.0 420 2.0 40 0.57 400 0.20 1.09 1013.96 61.81 0.950 99054 99019 0.16 8.80 0.21 96 27.9 27.4 420 2.0 40 0.57 400 0.20 1.09 1013.96 61.81 0.950 99026 99019 0.16 8.80 0.21 96 27.7 33.1 422 3.0 40 0.57 400 0.20 1.09 1024.75 58.78 1.184 98941 98959 0.14 11.54 0.23 72 31.9

Table B.l Input parameters and simulation outputs of a foam height correlation (continued)


(mm) VL (cm3)

M (kmol/m3)

T (°C)

G (mm/s)

V«4 (ct$)

Ocoi (mol/mol)

A,' (kg/m3)

A3 (kg/m3) r

(mN/m) fk.

(mPas)

p",target (N/m2)

/>'

(N/m2) r

(mm) Ca

(xl0}) FT Re H

(mm)

47.0 425 5.0 40 0.43 400 0.40 1.09 1089.44 42.66 2.357 98740 98754 0.10 23.57 0.19 19 45.9 48.3 425 5.0 40 0.49 400 0.40 1.09 1089.44 42.66 2.357 98744 98760 0.10 26.94 0.25 22 46.9 48.4 425 5.0 40 0.57 400 0.40 1.09 1089.44 42.66 2.357 98769 98767 0.10 31.65 0.34 26 48.5 59.4 420 5.0 40 0.61 400 0.40 1.09 1089.44 42.66 2.357 98632 98770 0.10 33.67 0.37 29 46.5 55.5 420 5.0 40 0.67 400 0.40 1.09 1089.44 42.66 2.357 98700 98774 0.10 37.04 0.45 31 48.5 47.5 425 5.0 40 0.77 400 0.40 1.09 1089.44 42.66 2.357 98828 98781 0.10 42.77 0.61 36 52.0 52.3 425 5.0 40 0.94 400 0.40 1.09 1089.44 42.66 2.357 987% 98790 0.10 52.20 0.89 45 52.9 21.1 412 2.0 60 0.57 400 0.40 1.02 1020.90 58.76 0.693 99116 99121 0.17 6.75 0.20 144 20.8 21.6 425 2.0 60 0.57 400 0.40 1.02 1020.90 58.76 0.693 99106 99121 0.17 6.75 0.19 145 20.8 21.6 428 2.0 60 0.57 400 0.40 1.02 1020.90 58.76 0.693 99105 99121 0.17 6.75 0.19 145 20.8 22.3 425 3.0 60 0.57 400 0.40 1.02 1039.72 53.14 0.879 99108 99061 0.15 9.48 0.23 101 24.8 24.7 425 3.0 60 0.57 400 0.40 1.02 1039.72 53.14 0.879 99058 99061 0.15 9.48 0.22 101 24.5 24.9 428 3.0 60 0.57 400 0.40 1.02 1039.72 53.14 0.879 99054 99061 0.15 9.48 0.22 101 24.5 29.2 425 4.0 60 0.57 400 0.40 1.02 1058.46 47.21 1.147 98999 98998 0.13 13.91 0.26 68 29.3 29.5 423 4.0 60 0.57 400 0.40 1.02 1058.46 47.21 1.147 98995 98998 0.13 13.91 0.26 68 29.2 29.4 420 4.0 60 0.57 400 0.40 1.02 1058.46 47.21 1.147 98995 98998 0.13 13.91 0.26 68 29.2 27.1 430 5.0 60 0.57 400 0.40 1.02 1077.12 40.97 1.540 99072 99041 0.12 21.53 0.27 49 29.3 27.2 430 5.0 60 0.57 400 0.40 1.02 1077.12 40.97 1.540 99071 99041 0.12 21.53 0.27 49 29.3 28.1 430 5.0 60 0.57 400 0.40 1.02 1077.12 40.97 1.540 99055 99041 0.12 21.53 0.27 49 29.1 28.7 425 5.0 60 0.57 400 0.40 1.02 1077.12 40.97 1.540 99045 99041 0.12 21.53 0.27 49 29.0 28.9 430 5.0 60 0.57 400 0.40 1.02 1077.12 40.97 1.540 99041 99041 0.12 21.53 0.27 50 29.0 31.9 428 6.0 60 0.57 400 0.40 1.02 1095.64 34.42 2.131 99038 99139 0.13 35.46 0.26 38 24.2 30.2 430 6.0 60 0.57 400 0.40 1.02 1095.64 34.42 2.131 99064 99139 0.13 35.46 0.26 38 24.5 26.9 432 6.0 60 0.57 400 0.40 1.02 1095.64 34.42 2.131 99115 99139 0.13 35.46 0.26 37 25.2 24.8 428 7.0 60 0.57 400 0.40 1.02 1114.01 27.55 3.041 99191 99193 0.12 63.22 0.28 25 24.6 25.3 430 7.0 60 0.57 400 0.40 1.02 1114.01 27.55 3.041 99183 99193 0.12 63.22 0.28 25 24.5 24.4 430 7.0 60 0.57 400 0.40 1.02 1114.01 27.55 3.041 991% 99193 0.12 63.22 0.28 25 24.7 27.9 420 2.0 40 0.57 400 0.20 1.09 1013.96 61.81 0.950 99015 99019 0.16 8.80 0.21 97 27.6 26.0 420 2.0 40 0.57 400 0.20 1.09 1013.96 61.81 0.950 99054 99019 0.16 8.80 0.21 % 27.9 27.4 420 2.0 40 0.57 400 0.20 1.09 1013.96 61.81 0.950 99026 99019 0.16 8.80 0.21 % 27.7 33.1 422 3.0 40 0.57 400 0.20 1.09 1024.75 58.78 1.184 98941 98959 0.14 11.54 0.23 72 31.9


Input parameter Physical property Output Hem,

(mm) Well(cm3)

M (kmol/m3)

T (°C)

G (mm/s)

vul(cm )

aCO2 (mol/mol)

Pc (kg/m3)

Pt. (kg/m3)

y (mN/m)

Pt (mPa s)

P* ""r" (N/m2)

P*(N/m2)

r (mm)

Ca (x10)

Fr Re H (mm)

32.3 422 3.0 40 0.57 400 0.20 1.09 1024.75 58.78 1.184 98956 98959 0.14 11.54 0.23 71 32.1 32.9 425 3.0 40 0.57 400 0.20 1.09 1024.75 58.78 1.184 98944 98959 0.14 11.54 0.23 72 32.0 33.0 428 5.0 40 0.57 400 0.20 1.09 1046.09 52.09 1.973 99007 99016 0.14 21.70 0.23 44 32.4 32.4 425 5.0 40 0.57 400 0.20 1.09 1046.09 52.09 1.973 99017 99016 0.14 21.70 0.23 44 32.5 30.6 425 5.0 40 0.57 400 0.20 1.09 1046.09 52.09 1.973 99047 99016 0.14 21.70 0.23 43 32.8 33.0 425 5.5 40 0.57 400 0.20 1.09 1051.36 50.27 2.276 99024 99034 0.14 25.93 0.23 38 32.3 31.9 425 5.5 40 0.57 400 0.20 1.09 1051.36 50.27 2.276 99043 99034 0.14 25.93 0.23 38 . 32.5 33.3 428 5.5 40 0.57 400 0.20 1.09 1051.36 50.27 2.276 99019 99034 0.14 25.93 0.23 38 32.2 30.7 425 6.0 40 0.57 400 0.20 1.09 1056.60 48.40 2.641 99079 99107 0.16 31.26 0.21 36 28.6 27.9 425 6.0 40 0.57 400 0.20 1.09 1056.60 48.40 2.641 99124 99107 0.15 31.26 0.22 35 29.1 32.8 428 6.0 40 0.57 400 0.20 1.09 1056.60 48.40 2.641 99045 99107 0.16 31.26 0.21 36 28.2 24.5 435 7.0 40 0.57 400 0.20 1.09 1066.96 44.47 3.624 99210 99161 0.16 46.68 0.21 26 28.3 24.1 430 7.0 40 0.57 400 0.20 1.09 1066.96 44.47 3.624 99216 99161 0.16 46.68 0.21 26 28.4 24.4 430 7.0 40 0.57 400 0.20 1.09 1066.96 44.47 3.624 99212 99161 0.16 46.68 0.21 26 28.3 25.4 423 5.0 40 0.57 400 0.10 1.09 1024.41 56.95 1.805 99148 99265 0.22 18.16 0.15 70 18.5 29.0 425 5.0 40 0.57 400 0.20 1.09 1046.09 52.09 1.973 99075 99016 0.14 21.70 0.24 43 33.1 33.0 428 5.0 40 0.57 400 0.20 1.09 1046.09 52.09 1.973 99007 99016 0.14 21.70 0.23 44 32.4 39.4 428 5.0 40 0.57 400 0.30 1.09 1067.76 47.32 2.157 98899 98870 0.12 26.11 0.29 33 41.8 40.1 429 5.0 40 0.57 400 0.33 1.09 1074.27 45.92 2.215 98889 98836 0.11 27.63 0.31 30 44.4 46.4 429 5.0 40 0.57 400 0.33 1.09 1074.27 45.92 2.215 98796 98836 0.11 27.63 0.30 31 43.0 40.4 420 5.0 40 0.57 400 0.44 1.09 1098.10 40.82 2.443 98882 98965 0.12 34.28 0.28 31 33.6 36.9 423 5.0 40 0.57 400 0.48 1.09 1106.77 39.00 2.531 98933 98956 0.11 37.18 0.29 29 34.9 34.1 425 5.0 40 0.57 400 0.53 1.09 1117.60 36.74 2.647 98972 98947 0.11 41.26 0.31 26 36.3 41.2 425 5.0 40 0.57 400 0.53 1.09 1117.60 36.74 2.647 98871 98947 0.11 41.26 0.30 27 34.6 31.1 420 5.0 40 0.57 400 0.55 1.09 1121.94 35.84 2.694 99017 98943 0.10 43.06 0.32 25 37.3 13.6 428 5.0 60 0.57 400 0.10 1.02 1012.83 54.13 1.162 99382 99540 0.36 12.30 0.09 181 6.8 19.5 430 5.0 60 0.57 400 0.20 1.02 1034.26 49.66 1.276 99236 99290 0.20 14.72 0.17 92 16.5 18.9 430 5.0 60 0.57 400 0.20 1.02 1034.26 49.66 1.276 99248 99290 0.20 14.72 0.17 92 16.6 19.1 428 5.0 60 0.57 400 0.20 1.02 1034.26 49.66 1.276 99243 99290 0.20 14.72 0.17 92 16.6 18.7 430 5.0 60 0.57 400 0.20 1.02 1034.26 49.66 1.276 99252 99290 0.20 14.72 0.17 91 16.6 18.4 428 5.0 60 0.57 400 0.20 1.02 1034.26 49.66 1.276 99258 99290 0.20 14.72 0.17 91 16.7


00 On


(mm) VL (cm3)

M (kmol/m3)

T (°C)

6 (mm/s) (cm3)

OC02 (mol/mol)

A. , (kg/m ) (kg/m )

r (mN/m)

tk. (mPas)

p'.arfrt

(N/m2) Pl

(N/m2) T

(mm) Ca

(xlO"3) Fr Re H

(mm)

32.3 422 3.0 40 0.57 400 0.20 1.09 1024.75 58.78 1.184 98956 98959 0.14 11.54 0.23 71 32.1 32.9 425 3.0 40 0.57 400 0.20 1.09 1024.75 58.78 1.184 98944 98959 0.14 11.54 0.23 72 32.0 33.0 428 5.0 40 0.57 400 0.20 1.09 1046.09 52.09 1.973 99007 99016 0.14 21.70 0.23 44 32.4 32.4 425 5.0 40 0.57 400 0.20 1.09 1046.09 52.09 1.973 99017 99016 0.14 21.70 0.23 44 32.5 30.6 425 5.0 40 0.57 400 0.20 1.09 1046.09 52.09 1.973 99047 99016 0.14 21.70 0.23 43 32.8 33.0 425 5.5 40 0.57 400 0.20 1.09 1051.36 50.27 2.276 99024 99034 0.14 25.93 0.23 38 32.3 31.9 425 5.5 40 0.57 400 0.20 1.09 1051.36 50.27 2.276 99043 99034 0.14 25.93 0.23 38 . 32.5 33.3 428 5.5 40 0.57 400 0.20 1.09 1051.36 50.27 2.276 99019 99034 0.14 25.93 0.23 38 32.2 30.7 425 6.0 40 0.57 400 0.20 1.09 1056.60 48.40 2.641 99079 99107 0.16 31.26 0.21 36 28.6 27.9 425 6.0 40 0.57 400 0.20 1.09 1056.60 48.40 2.641 99124 99107 0.15 31.26 0.22 35 29.1 32.8 428 6.0 40 0.57 400 0.20 1.09 1056.60 48.40 2.641 99045 99107 0.16 31.26 0.21 36 28.2 24.5 435 7.0 40 0.57 400 0.20 1.09 1066.% 44.47 3.624 99210 99161 0.16 46.68 0.21 26 28.3 24.1 430 7.0 40 0.57 400 0.20 1.09 1066.96 44.47 3.624 99216 99161 0.16 46.68 0.21 26 28.4 24.4 430 7.0 40 0.57 400 0.20 1.09 1066.96 44.47 3.624 99212 99161 0.16 46.68 0.21 26 28.3 25.4 423 5.0 40 0.57 400 0.10 1.09 1024.41 56.95 1.805 99148 99265 0.22 18.16 0.15 70 18.5 29.0 425 5.0 40 0.57 400 0.20 1.09 1046.09 52.09 1.973 99075 99016 0.14 21.70 0.24 43 33.1 33.0 428 5.0 40 0.57 400 0.20 1.09 1046.09 52.09 1.973 99007 99016 0.14 21.70 0.23 44 32.4 39.4 428 5.0 40 0.57 400 0.30 1.09 1067.76 47.32 2.157 98899 98870 0.12 26.11 0.29 33 41.8 40.1 429 5.0 40 0.57 400 0.33 1.09 1074.27 45.92 2.215 98889 98836 0.11 27.63 0.31 30 44.4 46.4 429 5.0 40 0.57 400 0.33 1.09 1074.27 45.92 2.215 98796 98836 0.11 27.63 0.30 31 43.0 40.4 420 5.0 40 0.57 400 0.44 1.09 1098.10 40.82 2.443 98882 98965 0.12 34.28 0.28 31 33.6 36.9 423 5.0 40 0.57 400 0.48 1.09 1106.77 39.00 2.531 98933 98956 0.11 37.18 0.29 29 34.9 34.1 425 5.0 40 0.57 400 0.53 1.09 1117.60 36.74 2.647 98972 98947 0.11 41.26 0.31 26 36.3 41.2 425 5.0 40 0.57 400 0.53 1.09 1117.60 36.74 2.647 98871 98947 0.11 41.26 0.30 27 34.6 31.1 420 5.0 40 0.57 400 0.55 1.09 1121.94 35.84 2.694 99017 98943 0.10 43.06 0.32 25 37.3 13.6 428 5.0 60 0.57 400 0.10 1.02 1012.83 54.13 1.162 99382 99540 0.36 12.30 0.09 181 6.8 19.5 430 5.0 60 0.57 400 0.20 1.02 1034.26 49.66 1.276 99236 99290 0.20 14.72 0.17 92 16.5 18.9 430 5.0 60 0.57 400 0.20 1.02 1034.26 49.66 1.276 99248 99290 0.20 14.72 0.17 92 16.6 19.1 428 5.0 60 0.57 400 0.20 1.02 1034.26 49.66 1.276 99243 99290 0.20 14.72 0.17 92 16.6 18.7 430 5.0 60 0.57 400 0.20 1.02 1034.26 49.66 1.276 99252 99290 0.20 14.72 0.17 91 16.6 18.4 428 5.0 60 0.57 400 0.20 1.02 1034.26 49.66 1.276 99258 99290 0.20 14.72 0.17 91 16.7


Input parameter Physical . roperty Output Hen,

(mm) VLC (cm3)

M (kmol/m3)

T (°C)

G (mm/s)

V1(cm )

(km (mol/mol)

Ac (kg/m3)

Pi. (kg/m3)

7 (mN/m)

iit

(mPa s)

parr*

(N/m2)

,..

(N/m2) r

(mm) Ca

(x 1 0) Fr Re H

(mm)

19.6 428 5.0 60 0.57 400 0.25 1.02 1044.97 47.45 1.338 99226 99210 0.17 16.15 0.20 75 20.6 21.0 428 5.0 60 0.57 400 0.30 1.02 1055.69 45.27 1.402 99193 99144 0.15 17.74 0.23 64 24.0 24.0 430 5.0 60 0.57 400 0.33 1.02 1062.12 43.97 1.442 99134 99110 0.14 18.78 0.24 59 25.5 23.5 428 5.0 60 0.57 400 0.35 1.02 1066.40 43.11 1.469 99141 99089 0.13 19.52 0.25 56 26.9 27.4 430 5.0 60 0.57 400 0.40 1.02 1077.12 40.97 1.540 99068 99041 0.12 21.53 0.27 49 29.2 27.2 430 5.0 60 0.57 400 0.40 1.02 1077.12 40.97 1.540 99071 99041 0.12 21.53 0.27 49 29.3 28.1 430 5.0 60 0.57 400 0.40 1.02 1077.12 40.97 1.540 99055 99041 0.12 21.53 0.27 49 29.1 33.3 428 5.0 60 0.57 400 0.45 1.02 1087.83 38.85 1.614 98968 98999 0.11 23.79 0.29 44 31.0 30.2 428 5.0 60 0.57 400 0.50 1.02 1098.54 36.75 1.691 99016 98961 0.10 26.36 0.32 39 34.4 23.0 427 5.0 60 0.57 400 0.53 1.02 1104.97 35.50 1.740 99136 99047 0.11 28.07 0.30 41 29.3 23.6 425 5.0 60 0.57 400 0.53 1.02 1104.97 35.50 1.740 99124 99047 0.11 28.07 0.30 41 29.1 25.9 425 5.0 60 0.57 400 0.55 1.02 1109.25 34.67 1.772 99085 99043 0.11 29.28 0.30 40 28.9 0.0 440 5.0 90 0.57 400 0.20 0.94 1012.98 46.11 0.763 99684 99565 0.30 9.48 0.11 229 6.9 3.3 440 5.0 90 0.57 400 0.20 0.94 1012.98 46.11 0.763 99635 99565 0.31 9.48 0.11 235 6.6 9.3 439 5.0 90 0.57 400 0.33 0.94 1040.27 41.20 0.867 99457 99385 0.19 12.05 0.17 133 12.5 11.5 436 5.0 90 0.57 400 0.33 0.94 1040.27 41.20 0.867 99399 99385 0.20 12.05 0.17 135 12.2 18.5 440 5.0 90 0.57 400 0.40 0.94 1054.96 38.61 0.928 99235 99315 0.17 13.77 0.19 112 14.2 17.3 440 5.0 90 0.57 400 0.40 0.94 1054.96 38.61 0.928 99259 99315 0.17 13.77 0.20 111 14.3 22.4 450 5.0 90 0.57 400 0.53 0.94 1082.25 33.86 1.055 99147 99214 0.14 17.84 0.25 80 18.3 26.3 440 5.0 90 0.57 400 0.53 0.94 1082.25 33.86 1.055 99077 99214 0.14 17.84 0.24 81 17.7 29.0 425 5.0 40 0.57 400 0.20 1.09 1046.09 52.09 1.973 99075 99016 0.14 21.70 0.24 43 33.1 26.4 425 5.0 40 0.57 400 0.20 1.09 1046.09 52.09 1.973 99118 99016 0.14 21.70 0.24 43 33.6 25.1 425 5.0 50 0.57 400 0.20 1.06 1040.44 50.87 1.569 99133 99167 0.17 17.67 0.20 64 23.0 24.6 429 5.0 50 0.57 400 0.20 1.06 1040.44 50.87 1.569 99141 99167 0.17 17.67 0.20 64 23.0 19.1 428 5.0 60 0.57 400 0.20 1.02 1034.26 49.66 1.276 99243 99290 0.20 14.72 0.17 92 16.6 18.7 430 5.0 60 0.57 400 0.20 1.02 1034.26 49.66 1.276 99252 99290 0.20 14.72 0.17 91 16.6 9.4 430 5.0 70 0.57 400 0.2 0.99 1027.60 48.46 1.060 99467 99395 0.22 12.53 0.15 124 12.6 10.4 435 5.0 70 0.57 400 0.2 0.99 1027.60 48.46 1.060 99439 99395 0.23 12.53 0.15 125 12.5 0.8 435 5.0 80 0.57 400 0.2 0.97 1020.50 47.28 0.894 99670 99485 0.25 10.84 0.13 165 9.7 7.6 435 5.0 80 0.57 400 0.2 0.97 1020.50 47.28 0.894 99521 99485 0.27 10.84 0.13 173 9.0

48.4 425 5.0 40 0.57 400 0.40 1.09 1089.44 42.66 2.357 98769 98767 0.10 31.65 0.34 26 48.5


00 -J

Input parameter Physical property Output HN,

(mm)

YL«H

(cm3) M

(kmol/m3) T

(°C) G

(mm/s) "I (cm3)

OC02 (mol/mol)

PG (kg/m) (kg/m3)

r (mN/m)

T*L (mPas)

p'Mrgl

(N/m2) P'

(N/m2) r

(mm) CA

(xlO-3) Fr Re H

(mm)

19.6 428 5.0 60 0.57 400 0.25 1.02 1044.97 47.45 1.338 99226 99210 0.17 16.15 0.20 75 20.6 21.0 428 5.0 60 0.57 400 0.30 1.02 1055.69 45.27 1.402 99193 99144 0.15 17.74 0.23 64 24.0 24.0 430 5.0 60 0.57 400 0.33 1.02 1062.12 43.97 1.442 99134 99110 0.14 18.78 0.24 59 25.5 23.5 428 5.0 60 0.57 400 0.35 1.02 1066.40 43.11 1.469 99141 99089 0.13 19.52 0.25 56 26.9 27.4 430 5.0 60 0.57 400 0.40 1.02 1077.12 40.97 1.540 99068 99041 0.12 21.53 0.27 49 29.2 27.2 430 5.0 60 0.57 400 0.40 1.02 1077.12 40.97 1.540 99071 99041 0.12 21.53 0.27 49 29.3 28.1 430 5.0 60 0.57 400 0.40 1.02 1077.12 40.97 1.540 99055 99041 0.12 21.53 0.27 49 29.1 33.3 428 5.0 60 0.57 400 0.45 1.02 1087.83 38.85 1.614 98968 98999 0.11 23.79 0.29 44 31.0 30.2 428 5.0 60 0.57 400 0.50 1.02 1098.54 36.75 1.691 99016 98% 1 0.10 26.36 0.32 39 34.4 23.0 427 5.0 60 0.57 400 0.53 1.02 1104.97 35.50 1.740 99136 99047 0.11 28.07 0.30 41 29.3 23.6 425 5.0 60 0.57 400 0.53 1.02 1104.97 35.50 1.740 99124 99047 0.11 28.07 0.30 41 29.1 25.9 425 5.0 60 0.57 400 0.55 1.02 1109.25 34.67 1.772 99085 99043 0.11 29.28 0.30 40 28.9 0.0 440 5.0 90 0.57 400 0.20 0.94 1012.98 46.11 0.763 99684 99565 0.30 9.48 0.11 229 6.9 3.3 440 5.0 90 0.57 400 0.20 0.94 1012.98 46.11 0.763 99635 99565 0.31 9.48 0.11 235 6.6 9.3 439 5.0 90 0.57 400 0.33 0.94 1040.27 41.20 0.867 99457 99385 0.19 12.05 0.17 133 12.5 11.5 436 5.0 90 0.57 400 0.33 0.94 1040.27 41.20 0.867 99399 99385 0.20 12.05 0.17 135 12.2 18.5 440 5.0 90 0.57 400 0.40 0.94 1054.% 38.61 0.928 99235 99315 0.17 13.77 0.19 112 14.2 17.3 440 5.0 90 0.57 400 0.40 0.94 1054.96 38.61 0.928 99259 99315 0.17 13.77 0.20 111 14.3 22.4 450 5.0 90 0.57 400 0.53 0.94 1082.25 33.86 1.055 99147 99214 0.14 17.84 0.25 80 18.3 26.3 440 5.0 90 0.57 400 0.53 0.94 1082.25 33.86 1.055 99077 99214 0.14 17.84 0.24 81 17.7 29.0 425 5.0 40 0.57 400 0.20 1.09 1046.09 52.09 1.973 99075 99016 0.14 21.70 0.24 43 33.1 26.4 425 5.0 40 0.57 400 0.20 1.09 1046.09 52.09 1.973 99118 99016 0.14 21.70 0.24 43 33.6 25.1 425 5.0 50 0.57 400 0.20 1.06 1040.44 50.87 1.569 99133 99167 0.17 17.67 0.20 64 23.0 24.6 429 5.0 50 0.57 400 0.20 1.06 1040.44 50.87 1.569 99141 99167 0.17 17.67 0.20 64 23.0 19.1 428 5.0 60 0.57 400 0.20 1.02 1034.26 49.66 1.276 99243 99290 0.20 14.72 0.17 92 16.6 18.7 430 5.0 60 0.57 400 0.20 1.02 1034.26 49.66 1.276 99252 99290 0.20 14.72 0.17 91 16.6 9.4 430 5.0 70 0.57 400 0.2 0.99 1027.60 48.46 1.060 99467 99395 0.22 12.53 0.15 124 12.6 10.4 435 5.0 70 0.57 400 0.2 0.99 1027.60 48.46 1.060 99439 99395 0.23 12.53 0.15 125 12.5 0.8 435 5.0 80 0.57 400 0.2 0.97 1020.50 47.28 0.894 99670 99485 0.25 10.84 0.13 165 9.7 7.6 435 5.0 80 0.57 400 0.2 0.97 1020.50 47.28 0.894 99521 99485 0.27 10.84 0.13 173 9.0 48.4 425 5.0 40 0.57 400 0.40 1.09 1089.44 42.66 2.357 98769 98767 0.10 31.65 0.34 26 48.5


Input parameter Physical property Output HL, (mm)

VL" R(cm)

M (kmollm3)

T (°C)

G (mm/s)

vi(cm )

ac02 (mol/mol) (kg/m3) (k ig7m3) (m11 :1/m) (melt s)

"Arad

(N/m2)

e (N/m2)

r (mm)

Ca (x10-3)

Fr Re H (mm)

35.0 430 5.0 50 0.57 400 0.40 1.06 1083.55 41.80 1.884 98951 98918 0.11 25.82 0.30 36 37.6 32.1 430 5.0 50 0.57 400 0.40 1.06 1083.55 41.80 1.884 98996 98918 0.11 25.82 0.31 36 38.2 27.2 430 5.0 60 0.57 400 0.40 1.02 1077.12 40.97 1.540 99071 99041 0.12 21.53 0.27 49 29.3 28.1 430 5.0 60 0.57 400 0.40 1.02 1077.12 40.97 1.540 99055 99041 0.12 21.53 0.27 49 29.1 23.2 432 5.0 70 0.57 400 0.40 0.99 1070.18 40.16 1.283 99139 99145 0.14 18.30 0.24 66 22.9 22.3 435 5.0 70 0.57 400 0.40 0.99 1070.18 40.16 1.283 99157 99145 0.14 18.30 0.24 65 23.0 18.7 435 5.0 80 0.57 400 0.40 0.97 1062.79 39.38 1.086 99227 99236 0.15 15.80 0.22 85 18.2 19.8 435 5.0 80 0.57 400 0.40 0.97 1062.79 39.38 1.086 99206 99236 0.15 15.80 0.22 86 18.1 18.5 440 5.0 90 0.57 400 0.40 0.94 1054.96 38.61 0.928 99235 99315 0.17 13.77 0.19 112 14.2 17.3 440 5.0 90 0.57 400 0.40 0.94 1054.96 38.61 0.928 99259 99315 0.17 13.77 0.20 III 14.3


00 00


(mm) yL

(cm3) M

(kmol/m3) T

(°C) G

(mm/s) V*

(cm ) OC02

(mol/mol) A,'

(kg/m ) A3 (kg/m3)

r (mN/m) (mPas)

p*,target

(N/m2) Pl

(N/m2) r

(mm) Ca

(xlO*3) Fr Re H

(mm)

35.0 430 5.0 50 0.57 400 0.40 1.06 1083.55 41.80 1.884 98951 98918 0.11 25.82 0.30 36 37.6 32.1 430 5.0 50 0.57 400 0.40 1.06 1083.55 41.80 1.884 98996 98918 0.11 25.82 0.31 36 38.2 27.2 430 5.0 60 0.57 400 0.40 1.02 1077.12 40.97 1.540 99071 99041 0.12 21.53 0.27 49 29.3 28.1 430 5.0 60 0.57 400 0.40 1.02 1077.12 40.97 1.540 99055 99041 0.12 21.53 0.27 49 29.1 23.2 432 5.0 70 0.57 400 0.40 0.99 1070.18 40.16 1.283 99139 99145 0.14 18.30 0.24 66 22.9 22.3 435 5.0 70 0.57 400 0.40 0.99 1070.18 40.16 1.283 99157 99145 0.14 18.30 0.24 65 23.0 18.7 435 5.0 80 0.57 400 0.40 0.97 1062.79 39.38 1.086 99227 99236 0.15 15.80 0.22 85 18.2 19.8 435 5.0 80 0.57 400 0.40 0.97 1062.79 39.38 1.086 99206 99236 0.15 15.80 0.22 86 18.1 18.5 440 5.0 90 0.57 400 0.40 0.94 1054.96 38.61 0.928 99235 99315 0.17 13.77 0.19 112 14.2 17.3 440 5.0 90 0.57 400 0.40 0.94 1054.96 38.61 0.928 99259 99315 0.17 13.77 0.20 111 14.3

Appendix C

Experimental data of a column foaming experiment

Table C.1 Experimental percent foam volume per packing volume plotted at different

superficial gas velocities and superficial liquid velocities

Superficial liquid Superficial gas velocity Percent foam volume per velocity (m3/m4-hr) (mm/s) packing volume

60 0.11 120 0.11

0.8 241 0.11 241 0.13 241 0.13 301 0.11 60 0.15 120 0.18 181 0.20 240 0.22

1.5 300 0.24 360 0.27 361 0.27 361 0.37 360 0.31 48 0.27 60 0.27 97 0.27

121 0.28 120 0.29 121 0.25

2 3 120 0.24

.120 0.24 121 0.22 181 0.27 180 0.27 181 0.27 180 0.33 180 0.32

189

Appendix C

Experimental data of a column foaming experiment

Table C.l Experimental percent foam volume per packing volume plotted at different

superficial gas velocities and superficial liquid velocities

Superficial liquid velocity (m3/m-hr)

Superficial gas velocity (mm/s)

Percent foam volume per packing volume

60 0.11 120 0.11 181 0.11

0.8 241 0.11 241 0.13 241 0.13 301 0.11 60 0.15 120 0.18 181 0.20 240 0.22

1.5 300 0.24 360 0.27 361 0.27 361 0.37 360 0.31 48 0.27 60 0.27 97 0.27 121 0.28 120 0.29 121 0.25

2.3 120 0.24

2.3 120 0.24 121 0.22 181 0.27 180 0.27 181 0.27 180 0.33 180 0.32

189


superficial gas velocities and superficial liquid velocities (continued)

Superficial liquid velocity (m3/m2-hr)

2.3

Superficial gas velocity (minis)

241


0.29 240 0.29 241 0.28 240 0.33 241 0.30

301 0.33 300 0.38 299 0.35 300 0.33 359 0.33

360 0.31 360 0.33

3.1

60 0.31 121 0.32 181 0.34 241 0.38 301 0.33 301 0.42 301 0.34 360 0.33

3.8

60 0.38 121 0.35 181 0.44 241 0.53 241 0.51 241 0.53

4.6

60 0.44 121 0.44 120 0.46 121 0.44 181 0.44 180 0.43 181 0.44

190



Superficial liquid velocity (m3/m -hr)



241 0.29 240 0.29 241 0.28 240 0.33 241 0.30

2.3 301 0.33

2.3 300 0.38 299 0.35 300 0.33 359 0.33 360 0.31 360 0.33 60 0.31 121 0.32 181 0.34

3.1 241 0.38

3.1 301 0.33 301 0.42 301 0.34 360 0.33 60 0.38 121 0.35

3.8 181 0.44

3.8 241 0.53 241 0.51 241 0.53 60 0.44 121 0.44 120 0.46

4.6 121 0.44 181 0.44

o

00

0.43 181 0.44

190



Superficial liquid Superficial gas velocity Percent foam volume per velocity (m3/m -hr) (mm/s) packing volume

241 0.55

4.6 241 0.53 241 0.60

241 0.53

191



Superficial liquid velocity (m3/m -hr)



241 0.55

4.6 241 0.60

4.6 241 0.53 241 0.53

191

NR88587.pdf - University of Regina

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