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Computational Fluid Dynamic Modelling of

Zinc Slag Fuming Process

A Thesis Presented for the Degree of Doctor of Philosophy

By

Md. Nazmul Huda

Faculty of Engineering and Industrial Sciences

Swinburne University of Technology

Melbourne, Australia

2012

i

To My To My To My To My Beloved ParentsBeloved ParentsBeloved ParentsBeloved Parents

ii

Declaration

The candidate hereby declares that the work in this thesis, presented for the degree of

Doctor of Philosophy submitted to the Faculty of Engineering and Industrial Sciences,

Swinburne University of Technology; is that of the candidate alone and has not been

submitted previously, in whole or in part, in respect of any other academic award and

has not been published in any form by any other person except where due reference is

given, and has been carried out during the period from January 2008 to November

2011 under the supervision of A/Prof. Jamal Naser and Prof. Geoffrey Brooks from

Swinburne University of Technology, Melbourne, Australia and Prof. Markus Reuter

and Mr. Robert Matusewicz from Outotec Pty. Ltd., Melbourne, Australia.

---------------------------------------

Md. Nazmul Huda

Certification

This is to certify that the above statement made by the candidate is correct to the best

of our knowledge.

A/Prof. Jamal Naser

Prof. Geoffrey Brooks

iii

Abstract

Slag fuming is a reductive treatment process for molten zinciferous slags for

extracting zinc in the form of metal vapour by injecting or adding a reductant source

such as pulverized coal or lump coal and natural gas. The process has been operative

since 1930’s for recovering zinc from lead blast furnace slag. Though slag fuming is a

well-established process and has been industrially operative for over eighty years,

there is only limited understanding of the process kinetics and fluid flow behaviour

inside the slag fuming furnace. The purpose of this study is detailed fluid dynamic

analysis including combustion behaviour, gas-liquid momentum interaction,

generation of splashing due to gas injection process in slag fuming furnace, analysis of

fuming behaviour at different locations of the furnace by using computational fluid

dynamic (CFD) modelling technique.

This PhD thesis focuses on the Computational Fluid Dynamic (CFD) modelling study

of the zinc slag fuming process. In the first stage of the present research, a

Computational Fluid Dynamic (CFD) modelling study of the Top Submerged Lance

(TSL) gas injection process was carried out in a laboratory scale isothermal air-water

model. The multiphase flow simulation, based on Euler-Euler approach, elucidated the

effect of swirl and non-swirl flow inside the bath. The effects of lance submergence

level and air flow rate were also investigated in that phase. The simulation results for

velocity fields and generation of turbulence in the bath were validated against existing

experimental data from the previous water model experimental study of Morsi et al.

[1].

In the next stage of the research, a Computational Fluid Dynamic (CFD) model of the

pilot plant scale top submerged lance slag fuming furnace was developed to

investigate details of fluid flow, combustion behaviour, reaction kinetics and heat

transfer in the furnace. The model integrates submerged CH4 combustion at the lance

tip and chemical reactions with the heat, mass and momentum interfacial interaction

between the phases present in the system. Commercial CFD package AVL Fire 2009.2

(AVL, Graz, Austria) coupled with a number of user defined subroutines in

FORTRAN programming language were used to develop the model. The model is

based on 3-D Eulerian multiphase flow approach and it predicted the velocity and

iv

temperature field of the molten slag bath, generated turbulence, vortex and plume

shape at the lance tip. The model also predicted the mass fractions of slag and gaseous

components inside the furnace. The model was validated by adopting the macro – step

validation approach by using the zinc fuming rate against the pilot plant scale

experimental study on top submerged lance zinc fuming process carried out by

Waladan et al. [2].

Finally, the developed CFD model for TSL furnace was extended for submerged coal

combustion instead of CH4 combustion and applied to a conventional tuyere blown

slag fuming furnace. The model considered a thin slice of a conventional tuyere blown

slag fuming furnace consisting two opposing set of tuyere. The model was developed

in Eulerian multiphase flow approach by employing 3D hybrid unstructured

orthographic grid system. The aim was to investigate details of fluid flow, submerged

coal combustion dynamics, coal utilization behaviour, jet penetration behaviour, bath

interaction conditions and generation of turbulence in the bath. The model was

developed by coupling the CFD with the kinetics equations developed by Richards et

al. for a zinc slag fuming furnace. The model predicted the velocity, temperature field

of the molten slag bath, generated turbulence and vortex, coal utilization behaviour

from the slag bath. The jet penetration depth at the tuyere tip was validated against the

experimental study carried out by Hoefele and Brimacombe [3].

v

Acknowledgements

I would like to express my heartiest gratitude to a number of great persons who

contributed to my PhD journey in innumerable ways - academically, professionally

and psychologically.

First and foremost, I offer my sincerest gratitude to my supervisor Dr Jamal Naser, for

his contributions of time, ideas, and arrangement for funding to make my Ph.D.

experience productive and stimulating. In particular, I appreciate his invaluable and

enterprising guidance throughout the execution of this project. He has supported me

throughout this challenging journey with his patience and knowledge, whilst allowing

me the room to work in my own way. In addition, he was always accessible and

willing to help his students with their research. From the beginning, he inspired me to

successfully complete my degree. He provided me with appropriate direction,

technical support and became more of a mentor and friend, than a supervisor.

I gratefully thank my second supervisor Professor Geoffrey Brooks for his constant

encouragement, valuable suggestions throughout the project and patience in reading

and correcting the thesis within a short period of time. I feel myself truly honoured to

be a part of this research group and to have the opportunity to work with my

supervisors. One simply could not wish for better or friendlier supervisors. I mastered

the research techniques and have been well trained by my supervisors from the initial

to the final level of my degree.

I have been truly inspired by my industrial supervisors Professor Markus Reuter and

Mr. Robert Matusewicz, throughout this successful journey. I gratefully acknowledge

their constant support, valuable discussions and contributions on the pilot plant data

used in this study.

I would also like to take the opportunity to express my gratitude to my beloved wife,

Maimuna Musarrat, for her inspiring support towards the end of this tiring journey.

She came in my life as the greatest blessing and has been inspiring me to finish it on

vi

time. She provided me with immense mental support and accelerated my strengths

during the writing of this thesis.

From my childhood, I have been fortunate enough to have the most beloved siblings in

the world. I wish to express my sincerest gratitude to all of my siblings for their

continual support from the very beginning of my study life till now. No one could

wish to have better siblings than I have.

In my daily work I have been blessed with a friendly and cheerful group of fellow

students. Thanks to members of the High Temperature Processing Group of the

Faculty of Engineering and Industrial Science for their ongoing support and good

humour.

I wish to thank all of my friends outside the department for bearing with me and their

understanding. I offer my regards and blessings to all of my friends here in

Melbourne, my housemates and colleagues. My special thanks to Mustafa Tareq,

Adity Tareq, Abdul Aziz and Shovin Aziz, who have always treated me as a member

of their family in Australia. They gave me strength to stand for who I am and provided

me with mental support whenever I was in need of it.

I'm sure I've forgotten someone. I assure you that this is a shortcoming on my part and

not on yours. I beg you to forgive me for my oversight.

Finally I gratefully acknowledge the financial and other support received for this

research from the Faculty of Engineering and Industrial Science, Swinburne

University of Technology.

Above all, this thesis is dedicated to my beloved parents, Md. Ishaque and

Meherunnesa Begum. They both are the true inspirations and love of my life. They

sacrificed everything for me to let me grow and achieve every success of my life.

Their unconditional love and continual support in all that I have done till now are the

keys to all my achievements.

vii

Table of Contents

Declaration .................................................................................................................... ii

Certification ................................................................................................................... ii

Abstract ......................................................................................................................... iii

Acknowledgements ......................................................................................................... v

Table of Contents ....................................................................................................... vii

Lists of Figures ............................................................................................................ 12

Lists of Tables .............................................................................................................. 18

Nomenclature............................................................................................................... 19

Chapter 1 ..................................................................................................................... 22

1 Introduction ......................................................................................................... 23

1.1 Primary Research Theme .............................................................................. 24

1.2 Research Overview ....................................................................................... 25

1.3 Contributions of this research ....................................................................... 26

1.4 Publications from present research ............................................................... 28

1.5 Thesis Structure ............................................................................................. 29

Chapter 2 ..................................................................................................................... 31

2 Process Overview of TSL Technology and Zinc Extraction ........................... 32

2.1 Gas Injection into molten system .................................................................. 32

2.2 Development of TSL Technology ................................................................. 32

2.3 Operating Principle of TSL Technology ....................................................... 33

2.4 History of Zinc .............................................................................................. 36

2.5 Physical and chemical properties of zinc ...................................................... 39

2.6 Uses of zinc ................................................................................................... 40

2.7 Extraction Methods ....................................................................................... 45

2.7.1 Primary zinc production .......................................................................... 45

viii

2.7.1.1 Hydrometallurgical/ Electrolytic route ............................................ 48

2.7.1.2 Pyrometallurgical route.................................................................... 50

2.7.2 Slag Fuming/ Secondary zinc production ............................................... 54

2.7.2.1 Conventional Slag Fuming Operation ............................................. 56

2.7.2.2 Application of TSL Technology in Zinc Processing ....................... 58

CHAPTER 3 ................................................................................................................ 66

3 Literature Review................................................................................................ 67

3.1 Cold Model Investigations ............................................................................ 67

3.1.1 Experimental studies ............................................................................... 68

3.1.2 Swirl and Non-swirl Investigation .......................................................... 70

3.1.3 Formation of Bubbles and Splashing ...................................................... 73

3.1.4 Bath mixing characteristics ..................................................................... 79

3.1.5 Numerical Investigation .......................................................................... 80

3.2 Review of Zinc Slag Fuming Process ........................................................... 83

3.2.1 Slag fuming by conventional tuyere blown process ............................... 84

3.2.2 Slag fuming by TSL process ................................................................... 87

3.2.3 Other studies based on zinc extraction .................................................... 90

3.3 Research Objectives ...................................................................................... 92

Chapter 4 ..................................................................................................................... 94

4 Modelling Techniques and Model Features ...................................................... 95

4.1 CFD Modelling ............................................................................................. 95

4.1.1 Finite Volume Method ............................................................................ 97

4.2 Multiphase Flow Modelling .......................................................................... 98

4.2.1 Approaches to Multiphase Modelling ..................................................... 98

4.2.1.1 The Euler-Lagrange Approach ........................................................ 98

4.2.1.2 The Euler-Euler Approach ............................................................... 99

4.2.1.2.1 Homogeneous Model ................................................................ 100

4.2.1.2.2 Multi-fluid Model ...................................................................... 100

4.2.1.2.3 VOF Model ................................................................................ 100

4.3 Model Geometry and Computational Methodology ................................... 101

ix

4.3.1 Air water Model .................................................................................... 102

4.3.1.1 Model Features .............................................................................. 103

4.3.1.2 Governing Equations ..................................................................... 104

4.3.1.2.1 Continuity .................................................................................. 104

4.3.1.2.2 Momentum conservation ........................................................... 104

4.3.1.2.3 Interfacial Momentum Exchange .............................................. 106

4.3.1.3 Boundary conditions ...................................................................... 107

4.3.1.3.1 Inlet ............................................................................................ 107

4.3.1.3.2 Outlet ......................................................................................... 108

4.3.1.3.3 Wall ........................................................................................... 109

4.3.1.4 Initial Conditions and Fluid Properties .......................................... 110

4.3.2 Zinc Fuming TSL Model ...................................................................... 111

4.3.2.1 Slag Composition ........................................................................... 112

4.3.2.2 Model Features .............................................................................. 114

4.3.2.3 Governing Equations ..................................................................... 115

4.3.2.3.1 Enthalpy conservation ............................................................... 115

4.3.2.3.2 Interfacial Energy Exchange ..................................................... 116

4.3.2.3.3 Combustion Modelling .............................................................. 117

4.3.2.3.4 Chemical Reactions in the Slag Bath ........................................ 118

4.3.2.3.5 Interfacial Mass Exchange ........................................................ 120


4.3.2.4.1 Inlet ............................................................................................ 120

4.3.2.4.2 Outlet ......................................................................................... 121

4.3.2.4.3 Wall ........................................................................................... 121


4.3.3 Conventional Tuyere blow model ......................................................... 124

4.3.3.1 Model Geometry and computational mesh .................................... 124

4.3.3.2 Slag Composition ........................................................................... 127

4.3.3.3 Model Features .............................................................................. 127

4.3.3.4 Governing equations ...................................................................... 128

4.3.3.4.1 Coal combustion ........................................................................ 128

4.3.3.4.2 Devolatilization ......................................................................... 130

4.3.3.4.3 Gas Phase Combustion .............................................................. 131

4.3.3.4.4 Char oxidation ........................................................................... 132

x

4.3.3.4.5 Chemical Reactions in the Slag Bath ........................................ 133


4.3.3.5.1 Inlet ............................................................................................ 134

4.3.3.5.2 Outlet ......................................................................................... 134

4.3.3.5.3 Wall ........................................................................................... 134

4.3.3.5.4 Symmetry .................................................................................. 135


Chapter 5 ................................................................................................................... 137

5 Cold Flow CFD Model of the TSL Gas Injection Process ............................. 138

5.1 Test of Grid Independence .......................................................................... 138

5.2 Results and Discussion ................................................................................ 141

5.2.1 Effect of Swirl Intensity ........................................................................ 141

5.2.2 Effect of Submergence Level ................................................................ 148

5.2.3 Effect of Air Flow Rate ......................................................................... 150

5.2.4 Mixing in the Liquid Bath ..................................................................... 152

5.2.5 Turbulence Mixing ................................................................................ 152

5.2.6 Mean Convective Mixing ...................................................................... 156

5.2.7 Effect of Density ................................................................................... 158

5.2.8 Effect of Viscosity................................................................................. 160

Chapter 6 ................................................................................................................... 161

6 Numerical Investigation of Zinc Fuming Bath in TSL Furnace ................... 162

6.1 Test of Grid Independency .......................................................................... 162


6.2.1 Bath Behaviour...................................................................................... 165

6.2.2 Combustion Behaviour ......................................................................... 171

6.2.3 Zinc Fuming Behaviour ........................................................................ 175

6.2.4 Effect of Lance submergence level ....................................................... 180

Chapter 7 ................................................................................................................... 186

7 CFD Modelling of Conventional Zinc Fuming Furnace ................................ 187

xi

7.1 Test of Grid Independency .......................................................................... 187


7.2.1 Bath behaviour ...................................................................................... 190

7.2.2 Jet Penetration ....................................................................................... 196

7.2.3 Bath zones ............................................................................................. 200

7.2.4 Fuming Behaviour ................................................................................. 201

Chapter 8 ................................................................................................................... 205

8 Conclusions and Recommendations ................................................................ 206

8.1 Conclusions ................................................................................................. 206

8.2 Recommendations for further work ............................................................ 208

References: ................................................................................................................. 210

12

Lists of Figures

Figure 1-1: Schematic diagram of combustion zone and molten metal bath of a TSL

furnace ........................................................................................................................... 24

Figure 2-1: A cutaway schematic diagram of the typical Outotec Ausmelt TSL furnace

[12] ................................................................................................................................ 34

Figure 2-2: Schematic representation of Indian method for producing zinc [23] ......... 36

Figure 2-3: William Champion’s Zinc smelting furnace [23] ...................................... 37

Figure 2-4: Zinc demand by First use in 2005 estimates [26]....................................... 40

Figure 2-5: Zinc demand by End use in 2003 estimates [26] ....................................... 41

Figure 2-6: Zinc consumption in the World during 1960-2005 (kilo tonne) [26] ........ 41

Figure 2-7: Schematic diagram of Multiple Hearth Roaster (Image taken from

www.energytek.com.tw) ............................................................................................... 46

Figure 2-8: Schematic diagram of a fluidised bed roaster [26] ..................................... 47

Figure 2-9: Schematic diagram of an electrolytic cell .................................................. 50

Figure 2-10: Schematic illustration of the slag fuming process .................................... 55

Figure 2-11: Schematic of fuming furnace cross section [18] ...................................... 56

Figure 2-12: A schematic diagram of a rectangular tuyere blow conventional slag

fuming operation (Image taken from US Patent by Quarm [22]) ................................ 57

Figure 2-13: Korea Zinc’s integrated flow sheet using TSL technology to recover zinc

and lead from various slags and residues created during primary zinc and lead

concentrate processing [Hoang et al. [39]] ................................................................... 59

Figure 2-14: Schematic diagram of the zinc fumer at Onsan, Korea [Choi et al. [33]] 59

Figure 2-15: Flow circuit of the zinc fuming plant at Onsan, Korea. (Floyd et al. [25])61

Figure 2-16: Flow circuit of ISP Slag Fumer at Hachinohe, Japan. (Floyd et al. [37]] 62

13

Figure 2-17: Flow circuit of the commercialised TSL zinc technology to recover zinc

from primary leach residues (Image taken from Hoang et al. [12]).............................. 64

Figure 2-18: Conceptual flow circuit of the TSL Direct Zinc Smelting technology

(Image taken from Hoang et al. [12])............................................................................ 65

Figure 3-1: Schematic of the submerged plasma process for the high temperature

fuming of zinc from zinc containing residues [Image taken from Verscheure et al.] ... 90

Figure 3-2: Schematic diagram of the Enviroplas pilot plant (Image taken from Latif

[104]) ............................................................................................................................. 92

Figure 4-1: Schematic diagram of the air-water model .............................................. 102

Figure 4-2: Mid Plane cross sectional view of generated grid for CFD analysis ....... 103

Figure 4-3: Velocity vectors (m/s) for swirl air injection at the lance tip (Q=2.67 x 10-3

m3/s, H/L=2/3, Ф =57.5o) ........................................................................................... 108

Figure 4-4: Schematic diagram of the modelled furnace for Outotec TSL pilot plant111

Figure 4-5: Generated grid of the modelled pilot plant scale TSL furnace for CFD

analysis ........................................................................................................................ 112

Figure 4-6: Simplified phase relationships for the reduction step in an Outotec TSL

furnace for the components FeOx, ZnO, CaO and SiO2 generated by FACT Sage

[101] for the given temperature, partial pressure as well as the lime content. ............ 113

Figure 4-7: Schematic view of the modelled thin slice rectangular tuyere blow furnace

(Isometric Layout) ....................................................................................................... 125

Figure 4-8: (a) Generated surface mesh, (b) Volume mesh for CFD analysis (course

grid) ............................................................................................................................. 126

Figure 4-9: Coal combustion process flow chart ........................................................ 130

Figure 5-1: Mean tangential velocity (m/s) distribution for different grid

configurations .............................................................................................................. 140

14

Figure 5-2: Axial velocity (w) distribution (m/s) for the water model simulation ..... 143

Figure 5-3: Axial velocity (w) distribution (m/s) from experimental results of Morsi et

al. [1] ........................................................................................................................... 145

Figure 5-4: Tangential velocity (v) distribution (m/s) for the water model simulation146

Figure 5-5: Tangential velocity (v) distribution (m/s) from experimental results of

Morsi et al. [1] ............................................................................................................. 147

Figure 5-6: Mean tangential velocity comparison between swirl and non-swirl flow

from the simulation results and comparison with water model experiment of Morsi et

al. [1] (z/Z= 0.92, H/L= 2/3, Q=2.67 x 10-3

m3/s) ....................................................... 148

Figure 5-7: Average volume fraction of water at 68.0=Z

z for different submergence

level for the water model simulation (Q=2.67 x 10-3

m3/s, Ф = 57.5

o) ....................... 149

Figure 5-8: Relation between vertical penetration distance for annulus air injection

(va

L ) and modified Froude number (m

Fr ) as derived from the water modelling

simulation results (H/L=1/3, Ф = 0o) .......................................................................... 151

Figure 5-9: Turbulent Kinetic energy (k) distribution (m2/s2)- (a) Q=2.67 x 10-3

m3/s,

H/L=2/3, Ф = 0o, t = 60 sec, (b) Q=2.67 x 10

-3 m

3/s, H/L=2/3, Ф = 57.5

o, t = 60 sec 153

Figure 5-10: Turbulent kinetic energy (k) distribution (m2/s

2) from experimental

results of Morsi et al. [1] ((a) Q=2.67 x 10-3

m3/s, H/L=2/3, Ф = 0

o, (b) Q=2.67 x 10

-3

m3/s, H/L=2/3, Ф =57.5

o) ............................................................................................ 154

Figure 5-11: Volume fraction for water after 180 seconds (Q=2.67 x 10-3

m3/s,

H/L=2/3, Ф =57.5o) ..................................................................................................... 155

Figure 5-12: Velocity vectors for liquid phase (m/s) after 180 seconds

(Q=2.67 x 10-3

m3/s, H/L=2/3, Ф =57.5

o) ................................................................... 156

Figure 5-13: Volume exchange effectiveness along radial direction from present water

model simulation (Q=2.67 x 10-3

m3/s, H/L=1/3) ....................................................... 157

15

Figure 5-14: Contours for volume exchange effectiveness from present water model

simulation .................................................................................................................... 158

Figure 5-15: Average volume fraction at 40mm height (z/Z=0.66) above the liquid

bath (Q=2.67 x 10-3

m3/s, H/L=1/3, Ф = 57.5

o) .......................................................... 159


bath .............................................................................................................................. 159

Figure 6-1: Mean tangential velocity distributions for different grid configurations (Qa

= 0.05 kg/s, Qf = 0.0035 kg/s, LH ′′ = 1/5) ................................................................ 163

Figure 6-2: Volume fraction distribution for molten slag phase along the vertical cross

section in X-Z plane at four different time step of the transient simulation (Qa = 0.05

kg/s, Qf = 0.0035 kg/s, LH ′′ = 1/3), (a) 13th

second, (b) 13.5th

second, (c) 20.5th

second and (d) 32nd

second. ........................................................................................ 167

Figure 6-3: Volume fraction distribution for molten slag phase along the cross section

in X-Y plane (top view of the modelled furnace) at different time steps of the transient

simulation (Qa = 0.05 kg/s, Qf = 0.0035 kg/s, LH ′′ = 1/3), (a) 21.5th

second, (b) 22nd

second .......................................................................................................................... 168

Figure 6-4: Iso-contour plot of the molten slag phase at different time steps of the

transient simulation (Qa = 0.05 kg/s, Qf = 0.0035 kg/s, LH ′′ = 1/3), (a) 25th

second,

(b) 26.5th

second .......................................................................................................... 169

Figure 6-5: Streamlines distribution of the molten slag phase showing slag phase

movement inside the furnace at different time steps of the transient simulation (Qa =

0.05 kg/s, Qf = 0.0035 kg/s, LH ′′ = 1/3), (a) 16.5th

second, (b) 27th

second............. 170

Figure 6-6: Velocity vectors inside the furnace in the molten slag bath: (Qa = 0.05

kg/s, Qf = 0.0035 kg/s, LH ′′ = 1/5) ........................................................................... 171

16

Figure 6-7: Species mass fraction (kg/kg) distribution for (a) CH4, (b) CO2 (c) CO and

(d) O2 ........................................................................................................................... 173

Figure 6-8: Temperature distribution for molten slag phase only (b) Species mass

fraction (kg/kg) distribution for O2 (Qa = 0.05 kg/s, Qf = 0.0035 kg/s, LH ′′ = 1/5) . 174

Figure 6-9: Fumed zinc distribution inside the furnace (a) at initial stage (after 1

second) (b) after 30 seconds (Qa = 0.05 kg/s, Qf = 0.0035 kg/s, LH ′′ = 1/5) ............ 175

Figure 6-10: ZnO distribution in the slag bath at different depths below the lance tip

along a line in radial direction from the lance (Qa = 0.05 kg/s, Qf = 0.0035 kg/s,

LH ′′ = 1/5) ................................................................................................................ 177

Figure 6-11: CO mass fraction (kg/kg) distribution along the radial direction at

different depths below the lance tip (Qa = 0.05 kg/s, Qf = 0.0035 kg/s, LH ′′ = 1/5) 178

Figure 6-12: Zinc fuming rate from some published experimental work ................... 178

Figure 6-13: Fuming rate from present simulation results (Qa = 0.05 kg/s, Qf = 0.0035

kg/s, LH ′′ = 1/5) and comparison with experimental data (Curve regenerated from

CZF5 of Figure 11 from Waladan et al. [2]) ............................................................... 179

Figure 6-14 (a): Zinc fuming rate and amount of splash at different heights above the

bath (Qa = 0.05 kg/s, Qf = 0.0035 kg/s, LH ′′ = 1/3) ................................................. 181

Figure 6-15: Comparison of zinc fuming rate and amount of splash at h/H = 0.09

above the bath for three submergence levels (Qa = 0.05 kg/s, Qf = 0.0035 kg/s) ....... 184


above the bath for three submergence levels (Qa = 0.05 kg/s, Qf = 0.0035 kg/s) ....... 184

Figure 6-17: Overall zinc fuming rate comparison for three different lance

submergence levels (Qa = 0.05 kg/s, Qf = 0.0035 kg/s) .............................................. 185

Figure 7-1: Mean upward velocity, W (m/s) distribution of slag phase for three

different grids along axial direction (Uo = 67.8 m/s, d/D = 0.5, h/H = 0.02) ............. 189

17

Figure 7-2: Slag phase volume fraction distribution (a) mid-plane cut at X-Z plane (b)

Iso-contour plot of slag phase ..................................................................................... 192

Figure 7-3: (a) Diagram showing injection phenomena in zinc fuming, (b) schematic

representation of the sequence of reactions in the bath (both the figures are taken from

Richards et al.[21]) ...................................................................................................... 193

Figure 7-4: (a) Injected coal mass at the tuyere tip (b) Average coal mass along the

axial direction from the tuyere tip(Uo = 86 m/s, d/D = 0.5, h/H = 0.02).................... 195

Figure 7-5: Turbulent kinetic energy distribution inside the modelled furnace (Uo = 86

m/s) .............................................................................................................................. 195

Figure 7-6: Gas phase volume fraction at tuyere 1 tip showing jet penetration length

(lp) and jet expansion angle ( Θ ) for Uo = 86 m/s ...................................................... 197

Figure 7-7 (a): Comparison of the CFD results of tuyere jet penetration length (lp) with

correlation provided by Hoefele and Brimacombe [3] from experimental work........ 198

Figure 7-8: Velocity vectors of the slag phase inside the molten slag bath (Uo = 86

m/s) .............................................................................................................................. 201

Figure 7-9: ZnO distribution in the slag bath along the axial direction from the tuyere

tip at three different heights from the bottom wall (Uo = 86 m/s) .............................. 202

Figure 7-10: Schematic illustration of the tuyere tip jet and coal behaviour as observed

from the present simulation ......................................................................................... 202

18

Lists of Tables

Table 2-1: Physical and chemical properties of zinc [24] ............................................. 39

Table 2-2: Typical operating results of the zinc fumer at Onsan, Korea. [Floyd et al.

[37]] ............................................................................................................................... 60

Table 2-3: Typical operating conditions of the Hachinohe Smelter, Japan [Floyd et al.

[37]] ............................................................................................................................... 63

Table 4-1: Slag composition for TSL Zinc Fuming Model ........................................ 113

Table 4-2: Fluid and thermal properties of molten slag phase for TSL model ........... 123

Table 4-3: Injection conditions (TSL model).………………………………………119

Table 4-4: Comparisons of the simulation and plant data…..………………………121

Table 4-5: Initial Slag Composition for Tuyere blow model……………………….123

Table 4-6: Fluid and thermal properties of molten slag phase ……………………...131

Table 5-1: Overview of computational grids .............................................................. 139

Table 5-2: Overview of the simulation and experimental conditions ......................... 140

Table 5-3: Simulation conditions and corresponding figures ..................................... 141


Table 6-2: Injection conditions (CFD and Experimental) .......................................... 164


19

Nomenclature

cA pre-exponential factor

vA pre-exponential factor

DC drag coefficient

D cylinder diameter

Do outlet diameter of the cylinder

bD bubble diameter

mkD

, diffusion coefficient (m

2/s)

od outer diameter of the lance

id inner diameter of the lance

cE activation energy constant

vE activation energy constant

mFr modified Froude number

f body force vector

g gravitational body force (m/s2)

H lance submergence level for air-water model

H ′ lance submergence level for TSL pilot plant model

k turbulent kinetic energy

vK rate constant

gask total number of chemical species

L liquid level in the cylinder for air-water model

L′ liquid level in the cylinder for TSL pilot plant model

20

l vertical depth from the lance tip for TSL pilot plant model

pl jet penetration length at the tuyere tip

vaL vertical penetration distance for air jet injected through annulus

N number of phases

P local pressure

AP atmospheric pressure

Q air flow rate through lance for air-water model

aQ air flow rate through lance for TSL pilot plant model

fQ fuel flow rate through lance for TSL pilot plant model

R universal gas constant (J K-1

mol-1

)

bRe bubble Reynolds number

r radial distance from the centre point

pR radius of the coal particle

kS species source term

tSc turbulent Schmidt number

pT temperature of the coal particle

gT gas temperature

t

kT phase k Reynolds stress

V released volatiles

v velocity vector

fV ultimate volatile content

X radial coordinate

Y tangential coordinate

21

Z axial coordinate

Greek letters

µ molecular viscosity (N·s/m2)

tµ turbulent viscosity

SIt ,µ shear induced turbulent viscosity

BIt ,µ bubble induced turbulent viscosity

α volume fraction

ρ density (kg/m3)

τ shear stress

δ kronecker delta function

ε dissipation rate

22

Chapter 1

23

1 Introduction

Pyrometallurgy is one of the fundamental branches of extractive metallurgy. It is an

ancient technology which has defined significant stages of human development [4].

Smelting and refining operations are the major process of any pyrometallurgical route,

which is achieved through gas injection process. For the purpose of refining and

smelting ferrous and non-ferrous materials, gas injection process has been successfully

in operation since the 1800s. Based on the mode of injection, gas injection process can

be classified into following four categories:

Top submerged injection (TSL/Sirosmelt Furnace)

Top non-submerged injection (BOF steelmaking, Hismelt, Mitsubishi Smelter)

Bottom blow using tuyeres or nozzles (Bessemer, QSL furnace)

Side blow (horizontal or inclined) using tuyeres or nozzles (Pierce Smith

converter, Noranda reactor)

The major purpose of gas injection process is to create agitation in the molten metal

bath to accelerate mixing and promote refining reactions. Guthrie [5-9] described the

detail hydrodynamics of gas-stirred melts and fluid flows in metallurgy. Submerged

gas injection is known to be an effective way of stirring the bath for mixing, refining

and smelting due to the rigorous agitation achieved. The idea of submerged injection

was first proposed by Sir Henry Bessemer in 1860 for his bottom blown Bessemer

steelmaking process. Since then submerged gas injection has played an important role

in metals refining processes.

Top submerged lance (TSL) technology (also known as Sirosmelt) has been in

successful operated and established world wide as an effective smelting technology.

This unique Australian technology was developed by Dr. John Floyd [10] at the

Commonwealth Scientific and Industrial Research Organisation (CSIRO) in the

1970s. Since it’s invention, TSL technology has been used to both ferrous and non-

ferrous metallurgical process industries.

24

1.1 Primary Research Theme

This thesis is primarily focused on computational fluid dynamic (CFD) investigation

of the zinc slag fuming behaviour in a top submerged lance (TSL) zinc fuming

furnace. The primary objective was to predict lance tip combustion and bath

interaction conditions in order to achieve the maximum combustion efficiency and

control over the desired operating conditions in a TSL furnace. Though TSL

technology is successfully operating around the world, a complete understanding of

the non-isothermal process in three dimensional flow field structure including

submerged combustion and chemical reactions still needs thorough investigation.

Process optimization through real plant observation is difficult and gaining insight into

such a complex industrial system through the application of high temperature

experimentation is also hard to achieve. The process involves a very high temperature

robust combusting environment with interfacial mass, momentum and energy transfer

and complex chemical reactions among the species of the phases.

Figure 1-1: Schematic diagram of combustion zone and molten metal bath of a TSL

furnace

25

With the advancement of high performance computing facilities, computational fluid

dynamic (CFD) modelling technique has evolved as a powerful tool for the

researchers working in the metallurgical field. CFD can predict flows ranging from

simple single phase flows to complex multiphase flows in high temperature

combusting environment associated with metallurgical process industries. A number

of studies are reported in the open literature employing CFD tool for investigating

smelting and refining operations [11-18]. Successful and efficient development of a

CFD model can predict the fluid flow behaviour, combustion behaviour, generation of

turbulence and splashing and other fluid dynamic parameters inside the furnace.

Hence, CFD was chosen as the modelling tool for a comprehensive analysis of the

zinc fuming TSL furnace.

1.2 Research Overview

The current research consists of three major stages, starting with cold flow air-water

CFD model, followed by the CFD model of the non-isothermal pilot plant scale zinc

slag fuming furnace and finally extension of the developed model into the

conventional tuyere blow furnace configuration. All the models were developed by

different versions of AVL FIRE (AVL, Graz, Austria). The second and the third stage

work incorporate a number of User Defined Subroutines in FORTRAN programming

language. Details of the developed models and modelling techniques are described in

Chapter 4. The three stages are summarized as follows:

In the first step, a cold flow isothermal air-water model of a laboratory scale

top submerged lance gas injection process was developed. A comprehensive

analysis of fluid dynamic behaviour of the TSL gas injection process was

carried out by CFD technique in 3D hybrid unstructured grid system. This

model was successfully validated against an experimental study of Morsi et al.

[1].

In stage two, a pilot plant scale CFD model of zinc fuming TSL furnace was

developed. The model integrates submerged CH4 combustion at the lance tip,

interfacial mass, momentum and energy exchange and chemical reactions in

26

the slag bath. Despite some limitations, the zinc fuming rate predicted by the

model agreed reasonably well with the experimental data of Waladan et al. [2].

Finally, the developed code was further extended to be applied to a

conventional tuyere blow zinc slag fuming furnace to check the applicability of

the developed code in other furnace configurations. The submerged

combustion code for CH4 was extended for coal combustion. The model

incorporates submerged multiphase coal combustion with devolatilization, char

oxidation and char chemical reaction. Details of the kinetics of the zinc slag

fuming process for a conventional zinc fuming furnace were described by

Richards et al. [19-21]. The chemical reactions in the developed CFD model

were based on the kinetic theory of Richards et al. [19-21]. A detailed fluid

dynamic analysis, tuyere tip combustion behaviour, coal utilization behaviour

and slag fuming behaviour at different furnace locations of the process were

analysed in the developed model.

1.3 Contributions of this research

The air-water simulation results from the first stage of the research showed that 2/3

lance submergence level provides better mixing and high liquid velocities for

generation of turbulence inside the water bath. However, it is also responsible for

generating more splash in the bath compared to 1/3 submergence level. An approach

generally used by Heating, Ventilation and Air Conditioning (HVAC) system

simulation was applied in that stage to predict the convective mixing phenomena. The

simulation results for the air-water system showed that, mean convective mixing for

swirl flow is more than twice than that of non-swirl in close proximity to the lance. A

semi-empirical equation was proposed from the results of present simulation to

measure the vertical penetration distance of the air jet injected through the annulus of

the lance in the cylindrical vessel of the model, which can be expressed as,

( ) 4745.0275.0 miova FrddL −= 1.1

27

After the successful validation of the air-water model in the first stage, the model was

extended to measure the degree of splash generation at certain heights above the free

surface for different liquid density, as an exploratory step towards the development of

a more complex pilot plant scale combusting system.

Investigation of the pilot plant scale zinc fuming TSL furnace predicted that the % of

ZnO in the slag bath decreases linearly with time and is broadly consistent with the

experimental data. The model results further predicted that the rate of ZnO reduction is

controlled by the diffusion of ZnO from the bulk slag to slag-gas interface and rate of

gas-carbon reaction. Three different lance submergence levels were considered to

study the effect of lance submergence level on splash generation and overall fuming

rate. The overall fuming rate for 1/3 lance submergence level were found to be 0.25 to

0.4 wt%/min, which is around 1.3 times higher than 1/5 lance submergence level.

In the third stage, tuyere jet penetration length ( pl ) was compared with the equation

provided by Hoefele and Brimacombe [3] from isothermal experimental work

(equation 1-2) and found 2.26 times higher, which is due to coal combustion and gas

expansion at high temperature.

( ) ( ) 35.046.07.10 lgFr

o

P Nd

lρρ′=

1.2

The jet expansion angle measured for the slag system studied is 85o for the specific

inlet conditions during the simulation time studied. Highest coal penetration distance

was found to be l/L = 0.2, where l is the distance from the tuyere tip along the centre

line and L is the total length (2.44m) of the modelled furnace. The model also

predicted that 10% of the injected coal bypasses the tuyere gas stream un-combusted

and carried to the free surface by the tuyere gas stream, which contributes to zinc

oxide reduction near the free surface.

28

1.4 Publications from present research

Following papers have resulted from the present research:

Journals:

1) N. Huda, J. Naser, G. Brooks, M.A. Reuter, and R. Matusewicz: CFD

Modelling of Swirl and Non-swirl gas Injections Into Liquid Baths Using Top

Submerged Lances. Metallurgical and Materials Transactions B, 2010, vol

41(1), pp. 35-50


Modelling of Zinc Fuming Process in Top Submerged Lance Smelting

Furnace. Metallurgical and Materials Transactions B, 2012. vol 43(1): p. 39-

55.


Investigation of Submerged Combustion Behaviour in a Tuyere Blown Slag

Fuming Furnace. Published online in Metallurgical and Materials Transactions

B, 2012, DOI: 10.1007/s11663-012-9686-7

Conference Publications and Presentations

1) N. Huda, J. Naser, G. Brooks, M.A. Reuter, and R. Matusewicz: “CFD

Modelling of Gas Injections in Top Submerged Lance Smelting” in TMS

Annual General Meeting. San Francisco, California, USA, 15-19 February,

2009, pp. 95-102.

2) N. Huda, J. Naser, G. Brooks, M.A. Reuter, and R. Matusewicz: “CFD

Modelling of Top Submerged Lance Gas Injection”, in High Temperature

Processing Symposium, Melbourne, Australia, 9 February, 2009

3) N. Huda, J. Naser, G. Brooks, M.A. Reuter, and R. Matusewicz: “Combustion

Modelling of Top Submerged Lance furnace by using CFD tool”, in High

Temperature Processing Symposium, Melbourne, Australia, 8-9 February,

2010, ISBN 978-0-9806708-0-6

4) N. Huda, J. Naser, G. Brooks, M.A. Reuter, and R. Matusewicz: “A

Computational Fluid Dynamic Modelling study of slag fuming in Top

Submerged Lance Smelting Furnace” in World Congress on Engineering.

London, UK, 30th

June- 2nd

July, 2010.

5) N. Huda, J. Naser, G. Brooks, M.A. Reuter, and R. Matusewicz: “Applications

of CFD Modelling in Metallurgical Process Industries”, in 15th

Biennial

Computational Techniques and Applications Conference (CTAC 2010),

Sydney, Australia, 28th

November – 1st December, 2010.

29

6) N. Huda, J. Naser, G. Brooks, M.A. Reuter, and R. Matusewicz: “Applications

of CFD Modelling in Smelting Industries – Some Recent Developments”,

in High Temperature Processing Symposium, Melbourne, Australia, 7-8

February, 2011, ISBN 978-0-9806708-2-0.

7) N.Huda, J. Naser, G. Brooks: CFD Modelling of Combustion Behaviour in

Slag Fuming Furnaces. TMS Annual General Meeting (International Smelting

Technology Symposium) Orlando, Florida, USA, 11-15 March, 2012, pp. 251-

258

1.5 Thesis Structure

A detail description of the overview of TSL technology including its development and

operation is presented in Chapter 2. Chapter 2 also contains process overview of zinc

extraction which highlights the history of zinc, its uses and extraction methods

including hydro and pyro-metallurgical circuits of zinc extraction. Then a review of

the previous studies based on gas injection process, TSL model studies and zinc

fuming kinetics are presented in Chapter 3. Chapter 3 begins with the current state of

knowledge on gas injection process and cold model experimental studies on gas

injection, followed by top submerged lance investigations – including modelling and

experimental work. At the end of Chapter 3, a comprehensive literature survey based

on zinc slag fuming process is also cited.

Chapter 4 begins by describing the methods of numerical investigation and CFD

modelling approach for current research followed by procedure of solving the

governing equations for fluid motion, combustion, interfacial phenomena and

chemical reactions. The detailed description and dimensions of the developed models,

methodologies and boundary conditions used in this research program are discussed in

the last portion of chapter 4.

A detailed hydrodynamic analysis of the top submerged lance gas injection process is

discussed in Chapter 5. In this chapter, effect of swirl and non-swirl flow, gas

injection rate, lance submergence level, density and viscosity is discussed for air-water

system. Chapter 6 demonstrates the results obtained from the developed CFD model

of the pilot plant scale zinc fuming TSL furnace. Chapter 7 recapitulates the zinc

fuming behaviour for a different furnace configuration – i.e. side injection through

30

tuyeres. Experimental results and validation of the developed models is outlined in

each of the corresponding chapters. Both Chapters 6 and 7 discusses the results of the

developed CFD model for zinc fuming process and examines the process variables

that influence the zinc fuming rate. Finally conclusions from the study are drawn and

recommendations for future work are suggested in Chapter 8.

31

Chapter 2

32

2 Process Overview of TSL Technology and Zinc

Extraction

This Chapter begins with an overview of Top Submerged Lance (TSL) furnace, its

history and development, followed by its basic working principle. Then, the chapter

will focus on the history and extraction of zinc both from its ores and from

metallurgical wastes or slags, different uses of zinc and available extraction methods.

At the end of this chapter, application of TSL technology to slag fuming process is

discussed.

2.1 Gas Injection into molten system

Gas injection in pyrometallurgy plays significant roles through creating mixing,

promoting interfacial reactions, producing an interface between phases, promoting

foaming and supplying energy into the system by combustion. Gas injection can also

be used as a medium to inject solids into the molten bath (i.e. combustion and

reductant coal). Different types of gas injection process commonly used in

pyrometallurgy have been discussed in Chapter 1 (Section 1). This Chapter will focus

on the development, operation and working principle of the TSL technology, as the

primary research theme is based on top submerged lancing (TSL) system.

2.2 Development of TSL Technology

The Top Submerged Lance (TSL) technology was developed by CSIRO scientist Dr.

John Floyd and his team during the 1970s. Initially it was called High temperature

submerged combustion, then SIROSMELT. It was then commercialized by the then

Ausmelt Limited (Now known as Outotec Ausmelt) and Xstrata Technology formerly

known as Isasmelt (Mount Isa Mines). The technology has been successfully

implemented in over 35 furnaces worldwide in 23 locations in 14 countries by Outotec

Ausmelt for the production of tin, copper, nickel, lead, platinum group metals, zinc

and aluminium [4].

33

2.3 Operating Principle of TSL Technology

The top submerged lance (TSL) furnace is a long cylindrical furnace with the lance

positioned centrally. It is a high temperature bath smelting process that uses the

vertically suspended lance to inject process air, oxygen and fuel to molten slag bath

for submerged combustion to supply energy and to increase the stirring to promote

reactions in the molten metal bath. Hence, acute process phenomena like primary

combustion, energy transfer, feed material dissolution, slag-metal reaction, take place

in the severely agitated slag layer. The addition of post combustion air with the lance

shroud system is used to maximize the recovery of energy available in the system. The

furnaces are tightly sealed and operate under a slightly negative pressure to eliminate

fugitive emissions to the environment. Feed material is supplied through a sealed port

in the top of the furnace. The Outotec TSL furnace treats a wide range of feed

materials [10]:

copper, nickel, lead, tin and polymetallic concentrates

copper and lead secondaries

zinc bearing residues

various waste materials and ferrous feedstock

The lance is suitable for operation under oxidizing, neutral, or reducing conditions to

provide a better control of the slag chemistry at the lance tip and gas-rise region of the

slag bath. The slag used for nonferrous processing applications, generally are solutions

of the oxides of iron, calcium, silicon, and aluminum. The composition is controlled

primarily to remove the unwanted components in the feed to the furnace, with fluxing

employed to provide the required viscosity at the chosen temperature of operation [4].

The vertically positioned lance consists of a series of concentric steel pipes through

which air, oxygen and fuel are delivered to the molten bath. The lance submergence

causes a high rate of heat and mass transfer between the molten bath and the slag

layer. The depth of submergence can also be varied which provides a better control of

the furnace to operate in different furnace condition. There is also a flexibility to use

different types of fuel. Another important factor that needs to be mentioned here is that

the lances are non consumable. During operation, the outer portion of the lance that

34

will be submerged is coated with a solidified slag layer before lowering into the slag

bath and then is operated with a submergence of about 100 to 500 mm in a bath of 800

to 2000 mm depth, depending on the requirements of the application [4]. The lance tip

operates submerged under the slag with lance material protected by the frozen slag

layer. This frozen slag layer is induced by the cooling effect of a swirled gas flow in

an outer annulus of the lance [22].

Figure 2-1 shows a diagram of the Ausmelt TSL furnace:

Figure 2-1: A cutaway schematic diagram of the typical Outotec Ausmelt TSL furnace

[12]

35

The reactor can either be used as primary smelters or for slag or waste treatment in

production of zinc, tin, copper, nickel, lead, platinum-group metals, and aluminum.

The furnace possesses five main reaction regions described by Floyd [4],

The combustion region at the lance tip.

The gas-rise region above the lance tip, where gases generated and any solid

un-reacted feed material at the lance tip further react with each other and the

surrounding and entrained slag.

The splash-cascade region, where ejected liquid slag ejected falls back into the

slag bath.

The post combustion region, where air and/or oxygen is injected into the

splash region of the gas space above the bath.

The bath region significantly beneath the lance-tip level, where slag and metal

phases are relatively quiescent compared with the violently agitated top region

of the bath.

There are other features and facilities of TSL furnace that are in common with other

furnace systems—flue off take, various ports, tap holes or tapping weirs, refractory or

cooled containment systems, etc. Variable level of submergence of the lance in the

bath allows the operator to control the degree of turbulence in the bath and the extent

of splashing of the slag cascade above the bath.

Details of the zinc extraction process by available TSL technique, future possible TSL

methodology and other available technologies from zinc concentrates, residues and

slags are described in the later part of this chapter.

36

2.4 History of Zinc

Zinc, also known as spelter, with atomic number 30, is the first element of group 12 in

periodic table. The word “zinc” is derived from the Persian word ‘sing’ meaning

stone. Before discovering zinc in its metallic form, its ores were used for making brass

and zinc compounds were used for healing wounds and sore eyes. In 13th

Century,

manufacture of zinc oxide was described by Marco Polo in Persia to serve for medical

purposes. Zinc is believed to be first discovered in India in the metallic form by 1374,

which was the eighth known metal at that time [23].

The Hindus described how the new “tin-like” metal was made by indirectly heating

calamine with organic matter in a covered crucible fitted with a condenser in the book

- Rasaratnassamuchchaya in fourteenth century [24]. Zinc vapor was evolved and

the vapor was air cooled in the condenser located below the refractory crucible (as

shown in Figure 2-2).

Figure 2-2: Schematic representation of Indian method for producing zinc [23]

The Chinese learnt about the manufacturing process in the 17th century. From India,

zinc manufacture moved to China where it developed as an industry to supply the

needs of brass manufacture. The Europeans came to know about the existence of the

metal much later, around the end of the 16th century. The first zinc smelter developed

in Europe was in 1743, at Bristol, in the UK. In that smelter, a vertical retort procedure

for zinc extraction was adopted, proposed by an Englishman William Champion

(1709-1789) [24] (as shown in Figure 2-3). Based on that procedure, in 1743 a zinc

37

smelter was established at Bristol in the United Kingdom. A charge of calamine and

carbon was sealed into a clay crucible having a hole in the bottom. This was luted onto

an iron tube extending below the crucible furnace into a cool chamber below. The

closed end of the iron tube sat in a tub of water and it was here that the metallic zinc

was collected (shown in Figure 2-3). The distillation took a total of about 70 hours to

yield 400 kg of metal from all 6 crucibles positioned in the furnace. An annual

production rate of 200 tons was suggested for the works at that time [24].

Figure 2-3: William Champion’s Zinc smelting furnace [23]

In 1758, William’s brother, John, patented the calcination of zinc sulfide to oxide for

use in the retort process, thereby laying the foundation for the commercial zinc

practice which continued well into the twentieth century. The English zinc industry

was concentrated in Bristol and Swansea [24].

A major breakthrough in the technological development of zinc extraction was made

by a German scientist Johann Ruberg (1751-1807), who built the first zinc smelting

works in Wessola in Upper Silesia in 1798 incorporating a horizontal retort process.

Improved fuel efficiency and convenient charging and discharging capabilities are

some of the advantages of the horizontal retort process. The initial raw material used

was zinc galmei (calamine), a by-product of lead and silver production. Later, it

became possible to produce zinc directly from smithsonite, an easily smelted ore. This

was shortly followed by the use of zinc blend, which had first to be converted into the

38

oxide by roasting. After this development, other smelting works were soon erected in

Silesia near the deposits, in the areas around Liège in Belgium, in Aachen, in the

Rhineland and Ruhr regions in Germany. The first Belgian plant was built by Jean-

Jacques Daniel Dony (1759-1819) in 1805 and also used horizontal retorts but of

slightly different design. Zinc production in the United States started in 1850 using the

Belgium process and soon became the largest in the world. In 1907, world production

was 737,500 tons of which the USA contributed 31%, Germany 28%, Belgium 21%,

United Kingdom 8%, and all other countries 12% [24].

Sheet production had begun soon after finding out the exceptional resistive capacity of

zinc towards atmospheric corrosion. The possibility of rolling zinc at 100-150°C was

discovered as early as 1805 and the first rolling mill was built in Belgium in 1812.

More such mills were built in Silesia from 1821 onwards. The oldest anticorrosion

process - hot-dip galvanizing, was introduced in 1836 in France. In the United States,

the rich ore deposits led to rapid growth in zinc production in 1840, so that by 1907,

Germany, which had for long been the world’s leading producer of zinc, was left

behind [24].

39

2.5 Physical and chemical properties of zinc

Zinc is a moderately reactive lustrous bluish-white metal placed in group IIB of the

periodic table. It is nonmagnetic in nature and its common oxidation state is +2.

Metallic zinc is brittle and crystalline at ordinary temperature but at 100 °C to 210 °C

(212 °F to 410 °F), it becomes ductile and malleable and can easily be beaten into

various shapes [25]. It creates fumes of zinc oxide while burning in air with a bright

bluish-green flame. It is a barely reactive metal that will combine with oxygen and

other non-metal and also reacts with dilute acids and alkalis. It releases Hydrogen

while reacting with dilute acids. It is the 27th

most commonly found element in earth’s

crust and it is fully recyclable [23]. It can be recycled indefinitely without losing its

physical or chemical properties.

Some general physical and atomic properties of zinc are mentioned in the following

Table 2-1:

Table 2-1: Physical and chemical properties of zinc [24]

Phase Solid

Atomic number 30

Isotopes 10

Density 7.14 gm. cm-3

Melting point 419.530 C (692.53

0 F)

Boiling point 9070 C (1180

0 F)

Heat of fusion 7.32 kJ mol-1

Heat of vaporization 123.6 kJ mol-1

Specific heat capacity (at 250 C) 25.470 J mol

-1 K

-1

Crystal structure Hexagonal

Oxidation state +2, +1 and 0

Magnetic ordering Diamagnetic

Electrical resistivity (20 °C) 59.0 nΩ·m

Thermal conductivity (300 K) 116 W·m−1

·K−1

Thermal expansion (25 °C) 30.2 µm·m−1

·K−1

40

2.6 Uses of zinc

Over the centuries, zinc as a metal has gone through substantial changes both in the

extraction methods and in the way that it is used. The broad categories of end use

remain much the same, i.e. coatings to protect iron and steel, building/ construction,

automotive/transport, household appliance, fittings, toys, zinc alloy castings, sheet for

building applications and a range of chemical applications. Figure 2-4 and Figure 2-5

are two statistical graphs showing the zinc demand by primary use and by auxiliary

use. Primary uses of zinc after production includes corrosion protection for steel

(galvanizing, zinc thermal spraying, electroplating, zinc rich paints), die casting and

gravity casting, brass, aluminium alloys, magnesium alloys, batteries, rolled zinc

sheets and zinc oxide, zinc stearate and other zinc compounds for chemical and

pharmaceutical industries.

Figure 2-4: Zinc demand by First use in 2005 estimates [26]

41

Figure 2-5: Zinc demand by End use in 2003 estimates [26]

Figure 2-6: Zinc consumption in the World during 1960-2005 (kilo tonne) [26]

Figure 2-6 shows the World demand for zinc increased from 3000 to 11000 kilo

tonne/year during 1960 to 2005. Some of the major uses of zinc are summarized

below:

42

Protecting Steel

Protecting steel from corrosion by metallurgically bonding to steel is zinc’s major

contribution. Zinc increases the durability of steel by protecting it against corrosion.

Zinc does so by two ways – by providing a physical barrier and cathodic protection.

When iron and zinc are both exposed to corrosive medium, they constitute an

electrolytic cell where layer of coated zinc act as cathode, and zinc is attacked

preferentially since its reduction potential of -0.76 is lower than that of iron, which is -

0.41 [27]. The process of metallurgical bonding between steel and zinc is known as

hot dip galvanizing. Some noticeable benefits of zinc coated steel are long service life,

low maintenance cost and minimal service interruption.

Other Coatings

Other than galvanizing, there are some more methods of zinc coating to protect

fabricated steel or sheets of steel such as electroplating (also known as electro

galvanizing), flame sprayed coatings, sherardising, mechanical plating and using zinc

rich paints. The use of zinc in paint industry is also increased in last couple of years.

Improved coatings have encouraged the development of new applications. For

example, galvanized steel with a fine surface finish is used to produce the parts of car

bodies that are vulnerable to corrosion. Such applications have been cited as a major

factor in the market for zinc [26].

Human Health

Zinc is an essential element for human health. For proper functioning of the immune

system, digestion, reproduction, taste and smell and many other natural process,

adequate daily intake of Zinc is essential. Zinc deficiency is now recognized as one of

the important risks to human health and is one of the leading causes of illness and

disease in low- income countries [25].

In Alloy making

In alloy making industry (like brass), zinc plays a noteworthy contribution. Other than

brass, there are series of alloys for coatings have been produced recently. Some of

43

those are Galvalume and Galfan. Galvalume consists of about 55% aluminium and

45% zinc with a small amount of silicon. It is being used extensively around the world

as it has better atmospheric corrosion resistance than pure zinc. Galfan is a zinc and

5% aluminium alloy containing small amounts of rare earth metals which has a

substantial and growing niche market in which its properties are valuable. Its

corrosion resistance is better than that of zinc and it retains some cathodic protection

capability [26].

Zinc castings

Another growth area is that of zinc castings which is based on new alloys and new

technology. Zinc casting now has a family of alloys - the specifier can choose the

alloy and casting process most suited to their product. Zinc alloy castings are unique,

particularly when produced by the pressure die casting process. They can be made to

extremely close tolerances, with excellent surface finish, have a range of useful

mechanical properties (especially ductility) and can receive a wide range of applied

finishes. As a result, zinc castings find a range of applications from automobiles to zip

fasteners. The development of new alloys and dramatic improvements in process

control enabled zinc castings to hold their own in many areas, particularly where

strength and applied finishes are required [26].

In medicine industry

Zinc is also used in medicine industry as it is responsible for the function of about 60

enzymes in human body. Besides oral medicine, zinc is also used in making ointments

for different dermatological treatment [26].

Energy conservation

Zinc is also a source of energy. Zinc batteries have been used for many decades. Zinc

gives a good combination of physical and electrochemical properties. Zinc is a good

reducing agent and it can produce high cell voltage. It has an excellent power density

and is one of the most stable metals in aqueous electrolyte solutions [26].

Zinc in Space:

44

United States National Aeronautics and Space Administration (NASA) scientists were

looking for a coating that could withstand the extreme temperature of space travel.

Then they discovered zinc-oxide as a fruitful solution. Researchers developed a zinc

based coating capable of withstanding thermal cycling between 180o

C and -180o

C

and the bombardment of ultraviolet exposure. Zinc oxide coating is now routinely

used in protecting components of spacecraft [25].

Besides all the uses mentioned above, zinc oxide is used in the manufacture of paints,

rubber products, cosmetics, pharmaceuticals, floor coverings, plastics, printing inks,

soaps, textiles, electrical equipments etc. Zinc has also the phosphorescent property

which makes it possible to glow in the dark. By virtue of this property, it is also a key

ingredient in making X-ray, TV screens [26].

45

2.7 Extraction Methods

Zinc can either be extracted from mined ores or metallurgical waste (discarded slags)

containing significant amount of zinc. Based on the extraction methods, zinc

production can be broadly categorised into two types, namely

Primary zinc production

Slag fuming/ Secondary zinc production

2.7.1 Primary zinc production

Primary zinc production refers to extracting zinc from ores. Ores containing zinc are

widespread geologically and geographically. Zinc ores typically may contain 3 to 11%

zinc in association with cadmium, lead, copper, gold, silver, iron as well as some other

minor elements [25]. Rarely is the ore, as mined, rich enough to be used directly by

pyro or hydrometallurgical operation. After extracting the ore from mines, it needs to

be concentrated before it goes for further processing. The concentration process of

zinc ores is accomplished at or near the mine by crushing, grinding, and floatation

process. Concentrated zinc ores usually contain 55% zinc.

Zinc is found primarily in earth’s crust as zinc sulphide (ZnS) or zinc blende. Some

ores are found as [25]

Calamine (ZnCO3) – 67% Zn

Hemimorphite or (Zn4Si2O7(OH)2.H2O). – 54.2% Zn

Zincite (ZnO)

Willemite (Zn2SiO4) – 58.5% Zn

Once concentrated, the zinc ores is transferred to smelters for the production of zinc or

zinc oxide. Reduction of zinc sulphide concentrates to metallic zinc is accomplished

through either electrolytic deposition from a sulfate solution or by distillation in retorts

or furnaces. Both of these methods begin with the elimination of most of the sulphur

in the concentrate through a roasting process. Roasting is high temperature oxidation

of zinc sulphide concentrates usually carried out at 700~800o C with air blow through

46

which it converts to an impure zinc oxide known as calcine. This is a solid-gas

reaction and the reaction is exothermic which increases the temperature up to 1000o C.

At a temperature of around 950°C, oxidisation of the zinc, iron and sulphur occurs.

The sulphur is collected as SO2 and is used to make sulphuric acid (H2SO4) - a

commercial by-product. Roaster types include multiple-hearth, suspension, or

fluidized bed. The following reactions occur during roasting process,

2

SOZnO22

O3ZnS2 +→+ 2.1

3SO2

2O

2SO2 →+ 2.2

In a multiple-hearth roaster, the concentrate drops through a series of 9 or more

hearths stacked inside a brick-lined cylindrical column (see Figure 2.7). As the feed

concentrate drops through the furnace, it is first dried by the hot gases passing through

the hearths and then oxidized to produce calcine. It usually operates at atmospheric

pressure and at about 690°C (1300°F) temperature. Operating time depends upon the

composition of concentrate and the amount of the sulphur removal required. Multiple

hearth roasters have the capability of producing a high-purity calcine.

Figure 2-7: Schematic diagram of Multiple Hearth Roaster (Image taken from

www.energytek.com.tw)

47

Suspension roasters are also un-pressurized, but operate at a relatively higher

temperature of about 980°C (1800°F) than the multiple hearth roasters. In this type of

roaster, the concentrates are blown into a combustion chamber very similar to that of a

pulverized coal furnace. The roaster consists of a refractory-lined cylindrical steel

shell, with a large combustion space at the top and 2 to 4 hearths in the lower portion,

similar to those of a multiple hearth furnace.

Finely ground sulphide concentrates are suspended and oxidized in a feedstock bed

supported on an air column in a fluidised bed roaster. Both in the suspension roaster

and in the fluidised bed roaster, the reaction rates for desulphurization are more rapid

than in the older multiple-hearth processes. Fluidized-bed roasters operate under a

pressure slightly lower than atmospheric and at temperatures averaging 1000°C

(1800°F). In the fluidized-bed process, no additional fuel is required after ignition has

been achieved. The major advantages of this roaster are greater throughput capacities

and greater sulphur removal capabilities.

Figure 2-8: Schematic diagram of a fluidised bed roaster [26]

Roasted calcine is the raw material for either the electrolytic process or the

pyrometallurgical process to get the final product. Thus, the final product of the zinc

companies, which is the slab zinc, follows two different routes:

48

Hydrometallurgical route, and

Pyrometallurgical route

2.7.1.1 HYDROMETALLURGICAL/ ELECTROLYTIC ROUTE

De-sulphurized calcine from the roaster follows three basic steps in the electrolytic

processing, namely:

a. Leaching

b. Purification

c. Electrolysis

c. Leaching

Leaching is a very common technique in extractive metallurgy to make soluble salts of

metal. Leaching for roasted calcine is carried out by two steps known as double

leaching. In the first step, the calcine, after being reduced to powder form, are leached

with neutral or slightly acidic solution with the liquid passing counter-current to the

flow of calcine, which produce zinc sulphate from a portion of calcine. In this process,

only a portion of the zinc oxide enters into solution.

ZnO + H2SO4 = ZnSO4 + H2O 2.3

The remaining calcine is then leached in a strong acidic solution which dissolves the

remainder of the zinc oxide, along with metallic impurities, such as arsenic, antimony,

cobalt, germanium, nickel, and thallium. Insoluble zinc ferrite, formed during

concentrate roasting by the reaction of iron with zinc, remains in the leach residue,

along with lead and silver. Insoluble zinc ferrite, formed during concentrate roasting

by the reaction of iron with zinc, remains in the leach residue, along with lead and

silver. Lead and silver are then typically shipped to a lead smelter for recovery, while

the zinc is extracted from the zinc ferrite to increase recovery efficiency [28].

b. Purification

The zinc sulphate solution, before proceeding to the electrowinning process, should

follow the purification steps to maximise zinc removal during electrolysis. Presence of

49

impurities in the electrolytic solution may enhance the hydrogen production instead of

zinc metal. The purification process is usually carried out in a large agitated tank to

remove the metallic impurities which would otherwise intercede with zinc deposition

process during electrolysis. After purification, concentrations of these impurities are

limited to less than 0.05 milligram per liter (4 x 10-7 pounds per gallon). A number of

reagents are added in a sequence of steps to enforce this job. The solution is

neutralised and the precipitates i.e. metallic co-products together with any unwanted

contaminants, are removed by filtration. The process takes place at temperatures

ranging from 40 to 85°C (104 to 185°F), and pressures ranging from atmospheric to

240 kilopascals (kPa) (2.4 atmospheres) [28].

c. Electrolysis

The refined solution is then electrolyzed in a cell fitted with a lead anode and an

aluminum cathode. The process is also known as electro-winning. The process works

by passing an electric current through the solution in a series of cells. This causes the

zinc to deposits on the cathodes (aluminum sheets) and oxygen to form at the anodes.

Sulfuric acid is also formed in the process and reused in the leaching process. The

cathode is immersed in the solution for 24 – 48 hours during which time the zinc is

deposited on the aluminum cathode from which it is subsequently stripped [25].

Figure 2.9 shows a schematic diagram of electrolytic cell. Electrolytic zinc smelters

contain as many as several hundred cells. A portion of the electrical energy is

converted into heat, which increases the temperature of the electrolyte. Electrolytic

cells operate at temperature ranges from 30 to 35 °C (86 to 95 °F) and at atmospheric

pressure. A portion of the electrolyte is continuously circulated through the cooling

towers both to cool and concentrate the electrolyte through evaporation of water. The

cooled and concentrated electrolyte is then recycled to the cells. This process accounts

for approximately one-third of all the energy usage when smelting zinc [25].

50

Figure 2-9: Schematic diagram of an electrolytic cell

There are two common processes for electrowinning the metal: the low current density

process, and the Tainton high current density process. The former uses a 10% sulfuric

acid solution as the electrolyte, with current density of 270–325 amperes per square

meter. The latter uses 22–28% sulfuric acid solution as the electrolyte with a current

density of about 1,000 amperes per square meter. The latter gives better purity and has

higher production capacity per volume of electrolyte, but has the disadvantage of

running hotter and being more corrosive to the vessel in which it is done. In either of

the electrolytic processes, each metric ton of zinc production expends about

3,900 kW·h (14 GJ) of electric power [25].

The final process takes place in the foundry where the zinc takes its final form, either

as a metal with a purity of 99.95% or as an alloy together with copper, aluminium or

magnesium. The zinc is cast into various forms (normally ingots or plates) with

weights from 9 kg to 4 tons.

2.7.1.2 PYROMETALLURGICAL ROUTE

High reaction rate resulting in high production rate of zinc and ability to accommodate

a wide variety of zinc bearing materials as feed are the advantageous factors of

pyrometallurgical route over the electrolytic process. On the contrary, downgraded

purity in final product (around 98%) is the major drawback of this route. Basic

working principle of this route is reducing the calcine by carbon in retort. There are

also several pyrometallurgical processes that reduce zinc oxide using carbon, then

distil the metallic zinc from the resulting mix in an atmosphere of carbon monoxide.

The four types of commercial pyrometallurgical processes are the Belgian-type

51

horizontal retort process, the New Jersey Zinc continuous vertical-retort process, the

blast furnace process and the St. Joseph Minerals Corporation's (electrothermic)

process [25]. The reduction process gives the zinc as vapor from which zinc metal is

obtained by condensing. A portion of this metal is used in alloying purposes and from

the other portion pure zinc is obtained through redistilation. Basic reaction occurring

in carbon retort is,

The electrothermic distillation retort process was developed in USA by the St. Joe

Minerals Corporation in 1930 [25]. Electrothermic processing of calcine begins with a

downdraft sintering operation, in which grate pallets are joined to form a continuous

conveyor system. Combustion air is drawn down through the conveyor, and impurities

such as lead, cadmium, and halides in the sinter feed are driven off and collected in a

bag filter. The product sinter typically includes 48% zinc, 8% iron, 5% aluminium, 4%

silicon, 2.5% calcium, and smaller quantities of magnesium, lead, and other metals.

Product sinter and, possibly, secondary zinc materials are charged with coke to an

electric retort furnace. The charge moves downward from a rotary feeder in the

furnace top into a refractory-lined vertical cylinder. Paired graphite electrodes

protrude from the top and bottom of this cylinder, producing a current flow. The coke

serves to provide electrical resistance, producing heat and generating the carbon

monoxide required for the reduction process. Temperatures of 1400°C (2600°F) are

attained, immediately vaporizing zinc oxides according to the following reaction [28]:

2CO)vapor(ZnCOZnO +→+ 2.4

The zinc vapour and carbon dioxide pass to a vacuum condenser, where zinc is

recovered by bubbling through a molten zinc bath. Over 95 percent of the zinc vapour

leaving the retort is condensed to liquid zinc. The carbon dioxide is regenerated with

carbon, and the carbon monoxide is recycled back to the retort furnace [28].

The blast furnace process was developed by the Imperial Smelting Corporation at

Avonmouth, England. The process starts by charging solid sinter and heated coke into

the top of the blast furnace. Preheated air at 190 to 1,050 °C (370 to 1,920 °F) is

blown into the bottom of the furnace. Zinc vapour and sulphides leave through the top

52

and enter the condenser. Slag and lead collect at the bottom of the furnace and are

tapped off regularly. The zinc is scrubbed from the vapour in the condenser via liquid

lead. The liquid zinc is separated from the lead in the cooling circuit [29].

The New Jersey Zinc process begins by roasting concentrates that are mixed with coal

and briquetted in two stages. The briquettes are then heated in an autogenous coker at

700 °C (1,292 °F) and then charged into the retort. There are three reasons to briquette

the calcine: to ensure free downward movement of the charge; to permit heat transfer

across a practical size cross-section; to allow adequate porosity for the passage of

reduced zinc vapor to the top of the retort. The reduced zinc vapor that is collected at

the top of the retort is then condensed to a liquid [29].

53

A generalised process diagram illustrating primary zinc production is shown in the

following flowchart:

Figure 2.10: Generalised flow diagram of primary zinc production showing two

different routes (Hydrometallurgy and Pyrometallurgy)

Alloying

purposes

Purifying

additives

Crushing, Grinding

and Floatation

Zinc

Ore

Zinc

concentrate

Calcine

ZnO (<1%S)

Leaching

Purification

Electrolysis

Cathode zinc

Melting and

casting

Zinc slab

Sintering

Reducing by

carbon in Retort

Casting

Impure

Zinc

Sulfuric

acid

Sulfuric

acid

Roasting

Acid

plant SO2

Dust and

fume

Redistillation

Pure Zinc

Coke

Silica

54

2.7.2 Slag Fuming/ Secondary zinc production

Slag is a pervasive by product of any pyrometallurgical process, also often known as

metallurgical waste. Three premier sources of slag in the context of industrial practice

are, firstly the gangue material introduced with the concentrate of ore, secondly from

the fluxes deliberately added during the smelting operation, and thirdly by oxidation

of the melt, be it metal or matte [30]. In general, slag is a mixture of molten oxides

which may also contain sulphides and halides in smaller quantity [30].

Significant metal values have been confined as metal oxides in the slag produced by

the smelting industries. Zinc in the slag from the lead-zinc blast furnace or lead blast

furnace, however if its content is lower than 10% or so, is not always recovered [31].

Recovery of these metal values before the slag are finally discarded has got

noteworthy interest of metal producers. For example, the primary production of zinc

and lead produces slag or residues, which contain significant amounts of zinc in the

form of ZnO. The zinc content in the slag depends largely on the type of concentrate

and residue materials, method of extraction and equipment used, which can be

recovered from the slag in its molten state in the form of fume by using a suitable

reducing agent. The process is generally known as slag fuming. Slag fuming is an

important secondary unit operation which is in the extraction of non-ferrous metals

and has been used since the 1930s to recover zinc from lead blast furnace slag [32]. It

is mostly a batch process, in which a reducing mixture of air and pulverized coal or

any other reducing agent is injected into the molten slag, however, Korea Zinc also

fume in continuously operating furnaces [33]. The coal-air mixture reduces the zinc

oxide from the slag to metallic zinc vapour.

Hence, slag fuming can be mentioned as one of the important mode of ‘slag cleaning’.

In metallurgical processing, the term ‘slag cleaning’ refers to the process of recovering

valuable metals from the slag phase. There are two other ways of slag cleaning. One is

‘settling’ by which contained metals or metal sulphides rise or sink to form a distinct

layer from which the slag can be separated [30]. The other one is slag milling and

floatation. This involves grinding the cooled slag and separating metallic and sulphide

particles by a standard rougher-cleaner type circuit [30]. But the most imperious of all

55

technique is the slag fuming process of slag cleaning i.e. recovering the valuable

metals.

The earliest reported experimental work on zinc fuming was conducted in Australia by

Sulphide Corporation at Cockle Creek between 1906 and 1920 [21]. The process has

been operative since 1930’s for recovering zinc from lead blast furnace slag. The

process operates between 1423 and 1573 K. The overall reactions occurring in the

bath are,

( ) ( ) ( )ggslag COZnCZnO +→+ 2.5

( ) COCOC coal 22 →+ 2.6

( ) ( ) ( ) ( )g2ggslag COZnCOZnO +→+ 2.7

Figure 2-10: Schematic illustration of the slag fuming process

The overall chemical reaction in the bath is thought to be controlled by the supply of

carbon to the slag-gas interface [19-21]. The main reaction (2.7) is endothermic and

combustion of fuel in the bath supplies the necessary heat. The vaporized zinc

oxidizes when it comes in contact with the air above the zinc bath. The zinc oxide

fume is subsequently collected in the bag house. Figure 2.11 shows a schematic

diagram of the zinc slag fuming process in the case of a top submerged lance (TSL)

56

smelting furnace. Details of the zinc slag fuming process from kinetic and fluid

dynamic perspective will be discussed in the later part of this thesis.

2.7.2.1 CONVENTIONAL SLAG FUMING OPERATION

Conventional slag fuming process on a rectangular furnace is a primeval process of

zinc fuming from slags. Commercial development of the process was made by the

Anaconda Copper Mining Co. and Consolidated Mining and Smelting Co. in the

1920’s [21]. The process usually carried out in a rectangular water jacketed furnace on

batch basis as shown on the schematic cross sectional view in Figure 2.12.

Approximately 50 tonnes of charge (either molten slag or solid slag) is fed to the

furnace at the beginning of each cycle. Two opposing sets of submerged tuyeres are

employed to inject air and pulverized coal into the molten slag bath to carry out

combustion and reducing reactions. The system usually operated within the

temperature ranges of 1150 to 1300o C (1423 to 1573 K).

Figure 2-11: Schematic of fuming furnace cross section [18]

Within the bath, the reducing agent (pulverized coal – 80% -200 mesh) reduces the

dissolved zinc oxide to metallic zinc vapour in the form of fume which is subsequently

captured in a bag house. The overall reactions occurring in the bath are mentioned in

equations 2.5-2.7. Each fuming cycle also termed as “fuming period”, usually operates

57

for 150 minutes, with additional 30 minutes for charging and tapping. Zinc extraction

takes place only during the fuming period. An integrated slag fuming operating unit is

portrayed in the schematic diagram of Figure 2.13.

Figure 2-12: A schematic diagram of a rectangular tuyere blow conventional slag

fuming operation (Image taken from US Patent by Quarm [22])

As described by Quarm [34], Figure 2.13 shows a schematic diagram of 8 feet x 21

feet slag fuming furnace. The furnace body was built up with water jacketed steel

plates 21, the inner surface of which had a frozen slag layer. The furnace was

connected to a waste heat boiler and then to the bag house by a flue 12. Air supply

comes through line 51, while coal fluidized by a minor part of the air is fed through

line 15 and nozzle 16 inside of each of tuyeres 14. The tuyeres are placed on both of

the opposing side of furnace wall and connected to a shut off valve 19, so that the

malfunctioning tuyeres can be removed for servicing. Through the opening 20, feed is

being fed to the furnace and also to add air to oxidize the fumed zinc into zinc oxide.

58

A tap hole 23 at the bottom of the furnace facilitates the removal of dezinced slag

through a launder 24 into the settling tank 26. Matte droplets are suspended from the

discarded slag in the settling tank 26 which is removed through another tap hole 27 by

the launder 28 into the matte ladle 29. The discarded slag is removed similarly by

another arrangement of launder 31 and slag ladle 32 arrangements.

2.7.2.2 APPLICATION OF TSL TECHNOLOGY IN ZINC PROCESSING

TSL technology is very well established technique for smelting industry operating

successfully around the world by implementing state of the art technologies for

extracting both ferrous and non-ferrous metals. Commercial TSL plants commissioned

around the world for both ferrous and non-ferrous metal processing are reported by

several authors [4, 35-38]. Zinc extraction by TSL furnace has started with pilot plant

studies in 1980s and has progressed to the treatment of close to 800,000 tonnes a year

of zinc bearing feeds in the form of residues and slags [39]. During smelting of zinc-

lead concentrates in Imperial Smelting Process (ISP) and in lead sinter plants such as

in Kivcet or QSL process, significant amount of zinc bearing dust is produced every

year. Because of the volatilization property, zinc, lead and silver can be easily

recovered by fuming process from these discarded slags. Outotec TSL technology has

been successfully adopted for zinc extraction from QSL slag at Onsan Zinc Refinery,

Korea [33, 37] and from ISF slag at Mitsui Mining and Smelting, Hachinohe, Japan

[37]. For processing of lead and zinc bearing intermediate industrial products

(residues, slags), twenty one (21) Outotec Ausmelt TSL furnaces are now in operation,

under design or under construction in South Korea, Japan, India and Australia [40].

Among all, Korea Zinc is the most comprehensive evidence to date as to the success

of TSL technology, comprising an integrated flow sheet of seven interdependent

projects utilising twelve TSL furnaces (10 for specific recovery of zinc) [39]. In 2008,

annual production of zinc by Korea Zinc was 445,000 tonnes, pointing it to a major

producer of zinc in the world [41]. Recently, another two stage zinc extraction process

has been proposed by Hoang et al. [39] from zinc concentrates designated as Direct

Zinc Smelting (DZS).

The zinc fuming plant in Korea Zinc incorporating TSL furnaces was designed to treat

120,000 tpa (tons per year) residue and has commenced its operation in 1995 [33].

59

Floyd et al. [37] describes the detailed working stages and flow diagrams of the zinc

fuming process at Onsan as shown in the Figure 2.14. Choi et al. [33] describes the

detailed working principal, plant description, material handling system, gas handling

system and development phase of the Korea Zinc plant at Onsan. As reported by

Floyd et al. [37], the Korea QSL lead smelter in Onsan, Korea, produces a slag of

typical composition of 20 – 22% Fe, 19 – 22% SiO2, 13 – 16% CaO, 13 – 15% Zn and

<5% Pb.

Figure 2-13: Korea Zinc’s integrated flow sheet using TSL technology to recover zinc

and lead from various slags and residues created during primary zinc and lead

concentrate processing [Hoang et al. [39]]

Figure 2-14: Schematic diagram of the zinc fumer at Onsan, Korea [Choi et al. [33]]

60

Figure 2-13 show the flow sheet of zinc fuming plant and Figure 2-14 show the

schematic diagram of the zinc fumer at Onsan, Korea. The process utilizes two stage

fuming process and uses coal as fuel and reductant and has facilities for oxygen

enrichment to 40% O2 in the lance combustion system [37]. As shown in the Figure

2-14, the first furnace is the smelting furnace and the second furnace is the cleaning

furnace. The cleaning furnace operates at extremely reducing conditions [33].

Magnesite chrome brick is used as the refractory in the furnaces. The cleaning furnace

is designed to have a siphon for continuous tapping of slag and a bottom tap – hole to

extract metal batch wise [33]. The typical operating results of the Korea Zinc, as

reported by Floyd et al. [37], are mentioned below:

Table 2-2: Typical operating results of the zinc fumer at Onsan, Korea. [Floyd et al.

[37]]

Operating Parameters Solid slag feed Liquid slag feed

Smelting rate (tph) 6 12

Temperature (o C) 1250 – 1300

o C 1250 – 1300

o C

Zinc fume % Zn 50 – 55 40 – 45

% Pb 20 – 30 25 – 35

Slag product % Zn 5 – 7 6 – 8

% Pb 0.3 – 0.5 < 1.0

The zinc content in the final slag was 3.5% and the recovery of zinc in the fume oxide

was about 82% [33]. Choi et al. [33] further reported that the furnaces needs to be

operated at higher than 1300o C to lower the final zinc content in the slag less that 1%.

61

The flow circuit of the zinc fuming plant at Onsan, Korea, is shown in the Figure 2-15.

Figure 2-15: Flow circuit of the zinc fuming plant at Onsan, Korea. (Floyd et al. [25])

Lead Concentrates, recycle

streams and fluxes, O2, Air and

coal as fuel and reductant

QSL Furnace Fume to

recycle Lead

Bullion

TSL Furnace

QSL

Slag

Air, O2 and

Coal as fuel

and reductant

Slag granulated

and sent to

cement plant

Waste Heat

Boiler

Bag House

ID Fan

Stack

Fume to Leaching

Zinc

solution to

Electrowin

Pb Residue

to QSL

Furnace

62

Figure 2-16: Flow circuit of ISP Slag Fumer at Hachinohe, Japan. (Floyd et al. [37]]

Sinter, Fume Briquettes, Coke,

Hot Air

ISP Furnace Zinc from

splash

condenser

Lead Bullion

Electric

Furnace

ISP

Slag

Bullion

TSL

Fumer

ID Fan

Stack

Slag granulated and

stockpiled or Used

Speiss

Slag

Evaporative

Cooler

Bag House

63

The slag fuming plant at Hachinohe Smelter, Japan, using TSL furnaces was

commissioned in 1993 for zinc recovery from Imperial Smelting Furnace (ISF) slag.

At that plant, the slag is tapped continuously from the ISP through the fore hearth into

an electric furnace and via launder into the fuming furnace. The slag flows

continuously through the fuming furnace where reducing conditions are supplied by

sub stoichiometric combustion of heavy fuel oil with air and with additions of

reductants such as coke breeze [37]. The flow circuit of the ISP slag fuming circuit at

Hachinohe is shown in Figure 2-16.

As reported by Floyd et al. [37], the typical slag composition of the Hachinohe

Smelter is 37% Fe, 20% SiO2, 14% CaO, 6 – 8% Zn and 0.5 – 1.0 % Pb. The fume is

collected in a baghouse and is returned to the sinter plant as feed material. The final

zinc content in the fumer slag is 3.0%. The typical operating conditions of the

Hachinohe Smelter, as reported by Floyd et al. [37], are mentioned below:

Table 2-3: Typical operating conditions of the Hachinohe Smelter, Japan [Floyd et al.

[37]]

Slag feed rate (tph) 10 – 12

Temperature (o C) 1300 – 1350

o C

Zinc fume % Zn 60

% Pb 12

Slag product % Zn 2 – 3

% Pb 0.1 – 0.3

Moreover, to maximize zinc recovery from primary concentrates, retrofitted TSL

furnaces are installed in a number of plants to extract zinc and other valuable elements

like In and Ge from primary leach residues [39]. A flow sheet of the commercialised

TSL zinc technology to recover zinc from primary leach residues is shown on Figure

2-17.

64

Figure 2-17: Flow circuit of the commercialised TSL zinc technology to recover zinc

from primary leach residues (Image taken from Hoang et al. [12])

More recently Hoang et al [39, 42] proposed a process for direct smelting of zinc from

zinc sulphide concentrates where the roasting process is eliminated by the TSL

smelting process [42]. The technology of Direct Zinc Smelting (DZS) process

involves treating of lower grade unclean concentrates in a combination of

pyrometallurgical recovery of zinc as ZnO fume which further follows the leach and

electrowinning circuit while utilising sulphide sulphur as fuel. Flow circuit of the

conceptual DZS model is presented in Figure 2-18. In the first stage of the two stage

TSL application, sulphide sulphur from the zinc concentrates will be used as energy

carrier and fume 60 – 65% of the zinc content. Molten slag from stage 1 will be used

in stage 2 for further recovery (99%) of zinc to produce final discard benign slag.

65

Figure 2-18: Conceptual flow circuit of the TSL Direct Zinc Smelting technology

(Image taken from Hoang et al. [12])

From the aforementioned discussions, the need for a more fundamental and clear

understanding of the submerged combustion process and detail hydrodynamic

characteristics in addition to chemical kinetics has evolved as obvious. As the primary

focus of this research is the submerged combustion dynamics and detail kinetics of the

zinc slag fuming process, it will be dealt with in the later part of this thesis

extensively.

66

CHAPTER 3

67

3 Literature Review

Since the invention of TSL technology in 1970s numerous studies had been carried

out for fundamental understanding of the process. The aim was to improve the system,

to make it an environmentally friendly, efficient and optimum process in terms of fuel

usage, product quality and waste material. This chapter starts with a comprehensive

literature survey on various experimental and numerical studies carried out on cold

flow top submerged lance gas injection process. An extensive literature survey on top

submerged lance zinc slag fuming process and conventional zinc slag fuming process

is also presented, followed by the research objective of this thesis.

3.1 Cold Model Investigations

Cold model investigations provide the fundamental understanding of the fluid flow

behaviour and other hydrodynamic parameters related to the process. Process

optimization can be achieved through proper manipulation of some hydrodynamic

parameters by cold model investigation. It is treated as the beginning step of the

research that leads to the real plant scale investigation. For gas injection systems in

metallurgical process industries, cold model investigation provides the bath interaction

characteristics due to the injection process, which is impossible to know in real

furnace scenario. Thus cold flow models can play a significant role in understanding

the basic working principle of any process that deals with high temperature robust

combusting environment. Major limitations of the cold model studies are it deals with

isothermal condition, hence unable to provide information on heat transfer phenomena

and combustion behaviour inside the furnace. In addition, if chemical interactions

among the species within the bath are of significant interest, then cold model studies

are not a good solution. Nevertheless, cold flow models are the gateway for research

in any high temperature process.

Cold model studies carried out by the previous researchers are based on both

experimental and numerical techniques. Significant research interest were mostly

based on bath mixing characteristics, formation of bubbles and splashing, effect of

different hydro-dynamic parameters (i. e. lance submergence level, flow rate, lance

68

diameter, lance position, angle of injection). In the subsequent sections, these topics

will be discussed further.

3.1.1 Experimental studies

As discussed in the Introduction (Section 1), gas injection in metallurgical processing

has been in operation since 1800’s. There had been numerous cold modelling studies

on different mode of gas injection systems.

Mazumdar and Guthrie [7] carried out experimental and numerical modelling study on

a 0.3 scale cold flow water model of a 150 ton steelmaking ladle. The experimental

work dealt with some geometrical change of the ladle, like with and without tapered

side walls, and with and without surface baffles around the rising plume. The

numerical modelling study was based on a generalized two dimensional, steady state

computational scheme for predicting flows generated by fully submerged and partially

submerged axi-symmetric gas injection lances.

The authors developed an equation of average plume velocity considering the case of

axi-symmetric gas injection into a cylindrical vessel, based on the previous work of

Sahai and Guthrie [8].

3/1

4/13/131

pR

LQkU β′′= 3.1

Where Up is the average plume velocity, Q is the flow rate, R is ladle radius, L is the

liquid depth and β is a fraction such that 0< β<1.

Morsi et al. [1] developed a similar type of cold flow air-water model of a 150 ton

steel-making ladle as developed by Mazumdar and Guthrie [7]. Morsi et al. [1] used

Laser Doppler Anemometer (LDA) technique to measure the velocity fields inside the

liquid bath. The authors investigated the effect of swirl and non-swirl gas injections

into liquid baths using submerged vertical lances. They reported that swirl gas

injection and two-third lance submergence level promoted better mixing in the bath.

They also examined the applicability of the concept of isotropic turbulence inside the

bath and concluded that it may hold outside the plume region.

69

Similar technique was also used by Taniguchi et al. [43] in a water model experiment

to measure the velocity fields. Taniguchi et al. [43] also measured volumetric

coefficient and free surface fluctuation in a water vessel with 0.145 m radius and 0.2

m height by injecting Nitrogen instead of air. Iguchi et al. [44-51] also carried out

extensive research on cold flow model of both top submerged injection and bottom

injection. Koh and Taylor [52] developed another cold flow air-water model to

measure liquid splashes at the bath surface for different flow rate and different lance

geometries. Jet penetration and liquid splashes in submerged gas injection were also

studied by Igwe et al. [53] through cold flow air-water model. Koria and Singh [54]

carried out another experimental investigation where the influence of different lance

lengths and diameter were studied experimentally on the upstream and downstream

flow properties of gas.

In another experimental study, Morsi et al. [55] investigated the flow field

characteristics within an elliptical liquid bath by using laser diagnostics technique and

high speed photography. The model was designed to reveal the flow behaviour of a

conceptual AusIron furnace design which consists of an elliptical Perspex vessel and

two vertically supported lances. The authors reported that higher flow rate created a

strong recirculation zone at the bottom of the bath. The authors also investigated the

effect of level of submergence for two vertically supported lances and concluded that

lower level of submergence caused a rapid spread of the gas jet at the top section of

the bath and higher submergence level improved the agitation in the bath.

Nilmani and Conochie [56] investigated the effect of viscosity in a cold flow model

top submerged lance experimental rig. The authors also found that the velocity of rise

of gas in the sirosmelt furnace is much higher than in the water model. In their cold

flow experimental study the authors used two gas: air and helium and three liquids:

water, glycerol/water with viscosity of 56 centipoise and glycerol/water with viscosity

of 200 centipoise. The authors reported that increasing liquid viscosity reduces gas

dispersion and with a less dense gas a greater volume flow is required to maintain the

same injection characteristics. Neven et al [57] also used Helium instead of air as the

injected gas into the water in another cold model study. The effect of viscosity of

liquid were also examined through cold flow experimentation by Iguchi et al [47],

where air was injected into a bath containing aqueous glycerol solution through a

70

single hole nozzle installed at the centre of the bottom of an acrylic cylindrical vessel

by means of a compressor. They examined the effects of the viscosity of liquids on the

bubble dispersion and reported that with increasing the viscosity of liquid, bubbles

tended to flock together around the centreline of the vessel and rise after the foregoing

bubble.

3.1.2 Swirl and Non-swirl Investigation

Top submerged lance technology incorporates helical swirler in the annulus area of the

lances to provide a swirling motion into the injected air. Thus, the injected gas jet

through the submerged lances can have either swirling or non-swirling effect. There

have been numerous studies regarding investigation of swirl and non-swirl air

injection into the liquid bath. Nilmani and conochie [56] did some experimental work

on swirl flow investigation and reported that swirler improves the radial dispersion of

gas bubbles, produces finer bubbles and minimises bath slopping and splashing.

Later in the year 1987-88, Dave et al. [58] investigated thoroughly the effect of

constant and variable pitch swirled insert through some experimental work. The

authors investigate the flow characteristics of both fixed and variable pitch inserts in

the case of sirosmelt lance. According to the authors, the swirl flow has the following

benefits over the non-swirl flow:

1. For the same mass flow, swirl flow can provide a higher velocity as compared

to the axial flow.

2. Because of the swirl inserts the fluid has to travel a greater distance through

the annulus which in turn increase the heat transfer rate through the lance to

the outer hot surface and helps to create the protective slag layer outside the

lance in a shorter time.

3. The rotating swirl flow creates a centrifugal force field which has a favourable

convection effect into the molten bath.

The authors subdivided flow behaviour across a given swirler into three regions:

1. Entrance region (flow development)

71

2. Fully developed flow region (constant velocity profile)

3. Decaying flow region

The authors also reported that fully developed flow loss consists of momentum and

frictional pressure loss. They developed two equations for momentum pressure loss

and for frictional pressure loss. The momentum pressure loss equation was given as,

−+

−=∆

c

cbw

iec

g

mA

RR

PA

mP

44

2

3

2

22

111 π

ρρ 3.2

and the frictional pressure loss equation was given as,

θ

ρ

cos

2 2

,

h

whgh

md

VLfP =∆ 3.3

Where helical flow friction factor, hf , can be related to the fully developed helical

Reynolds number and the maximum helical velocity which occurs at the tube radius

wR , can be expressed as,

( )[ ]

z

w

wh VP

RPV

21

22

,

2π+= 3.4

where, average axial velocity,

gc

g

zA

mV

ρ= 3.5

cA represents the flow cross-sectional area of the annulus with an n start helical vane

insert and is given by,

( ) ∫−−=w

cb

R

R

cbwc drntRRA θπ sec22 3.6

Thus by using equation (3.3) and (3.4), the flow losses for fully developed helical flow

in the insert region of a multistart gas injection lance can be estimated for any given

gas flow rate.

Solnordal and Gray [22] also did some experimental work to measure pressure losses

in the lance. The authors investigated swirl decay characteristics, heat transfer

coefficient, pressure losses, heat transfer per unit pumping power and heat transfer

72

mechanism of an operating top submerged lance through experimental work. The

authors reported that helical vane swirler can increase heat transfer coefficient by a

factor of 2.35 times over axial flow values. But swirlers incorporate a great pressure

loss as compared to plain lance and pressure loss due to poor design of the swirler

entrance region contribute up to 80% of the total pressure loss. The authors suggested

using a series of short variable pitch swirlers within the lance, with each swirler

entrance aligned with the bulk flow direction to reduce entrance pressure loss.

Neven et al. [57] reported that the presence of swirler does not have any significant

effect on the bubbling frequency. Shinichiro et al. [59] did some experimental work to

investigate the effect of swirler on formation of fine bubbles. The authors further

proposed an equation to measure the bubble diameter in the bath, which can be written

as,

( ) ( ) 21

31

212

1

=

ρσR

wB 3.7

where w is the tangential velocity, R is the radius of container, σ is surface tension of

molten steel. The authors reported that,

1. An increase in the centrifugal force induced by imparting a swirling motion in

the liquid accelerates in creating fine bubbles.

2. The penetrated volume efficiency of bubbles increases with increasing the

tangential velocity and injected air flow rate.

3. The diameter of bubbles decreases with increasing the tangential velocity.

4. The diameter of bubbles increases with increasing injecting air flow rate.

Iguchi et al. [45] also investigated bubbling phenomena in a cylindrical bath with

centric bottom gas injection by inducing swirl motion. The authors classified swirl

motion as two types depending on the bath depth. First kind of swirl motion is formed

when the bath depth is less or nearly equal to the bath diameter which was caused by

internal forced oscillation due to quasi-periodical bubble formation and in the second

kind bath depth is equal or greater than twice the bath diameter which was formed by

instability of large scale ring vortex enclosing the bubbling jet. The authors also

proposed some empirical correlations for the initiation of swirl motion and swirl

73

period. Later, Iguchi et al. [60] carried out further experiments to investigate the effect

of first kind of swirl motion on the liquid flow characteristics, bubble characteristics,

mass transfer from a solid body immersed in the bath and mixing time of the bath by

using high speed video camera, electro-resistivity probe and Laser Doppler

Velocimeter (LDV). The authors concluded that swirl motion enhanced the mass

transfer coefficient and reduced the mixing time significantly. The authors also

reported that the erosion of vessel wall was also enhanced by swirl motion.

Furthermore, Iguchi et al. [44] investigated the effect of swirl motion at reduced

pressure on the bath surface where several factors such as starting time, period,

amplitude and damping time of swirl motion occurring in a water bath were

experimentally investigated.

Ihira et al. [61] experimentally investigated the effect of multi lance configuration on

the swirl motion and mixing time inside the bath. The authors reported that there are

two types of unsteady motion in the deep water wave regime: swirl and reciprocating

motion.

3.1.3 Formation of Bubbles and Splashing

Formation of bubbles and splashing in high temperature process is an unavoidable

phenomena and key concern of the researchers. Many researchers and operators have

claimed that formation of splash and bubbles is a limiting factor in many gas injected

process. Irons and Guthrie [6] described in detail the formation of bubble in molten

metal bath. Liow et al. [62, 63] investigated thoroughly the dynamics of formation of

splash and discussed the macro scale and micro scale splash formation mechanism and

their effects on metallurgical processes. Liow et al. [63] further reported a number of

sources for formation of splash, which includes:

a. The impingement of drops on liquids

b. Slopping of bath liquid

c. Breakup of gas bubbles at the liquid-gas interface

d. Shearing of liquids by gases, and

e. Impact of packets of fluids on solids

74

The authors [63] studied the splash formation by lances on an industrial scale by

injecting air through the lance into a layer of molten slag in the flash smelting furnace

at the Kalgoorlie Nickel Smelter (KNS). The study shows that the cumulative weight

of the splash collected showed an exponential decrease with an increase in height from

the slag-air interface. They proposed a correlation for the amount of splash collected,

W, at a given height h,

khCeW

−= 3.8

Where, C is the total splash at the free surface, and k is the splash decay constant with

distance.

They also estimated roughly the amount of bubble volume formed at the lance exit by

using following equation,

6.02.1378.1 −= gQV 3.9

Liow et al. [63] reported two different splash formation mechanism from the KNS trial

study. The first mechanism was the formation of the slag sheet around the cavity

formed by the gas injected into the bath. The second mechanism was the Kelvin-

Helmholtz instability mechanism which is responsible for producing finer splash

particles. This mechanism occurs during the break-up of drops by the shearing action

of the gas inside the cavity. The criteria for stability is given by We.Fr<4 where,

( )

( )( )glgl

gl LUWe

ρρρρ

ρρ

+−=

22

22

3.10

gL

UFr

2

= 3.11

where, U is the relative gas to liquid velocity, L characteristic length.

Bubbling frequency and injection dynamics were investigated by Neven et al. [57] by

both cold flow water model and hot combustion testing. The authors validated the

Davidson and Schüler [64] formula for bubbling frequency and bubble volume that is

derived from the force equilibrium between inertial and buoyancy force. Neven et al.

[57] considered that the other two effect in bubbling phenomena - viscosity and

density becomes less important at high flow rates. Force due to inertia results from a

75

fact that a growing gas bubble at the lance tip has to accelerate an amount of liquid

surrounding the bubble. The inertia force corresponds to,

dt

dsV

dt

dF slagI

= ρ..

16

11 3.12

and the buoyancy force,

( )airslagB gVF ρρ −= .. 3.13

where,

ρ = density (kg/m3)

V = volume of the gas bubble (m3)

s = distance between lance tip and centre of the bubble (m)

g = gravitational acceleration (m/s2)

The force equilibrium results in a quite simple formula that gives the bubbling

frequency, freq, as a function of gas flow rate, G:

freq = 2.84 5

1−

G 3.14

Formation and rise of a bubble stream in viscous liquid was investigated by Snabre

and Magnifotcham [65], where they developed a semi-empirical model based on force

balance around the spherical bubble at the instant just previous to detachment,

σFFFFFF idpgb ++=++ 3.15

where,

Buoyancy force, ( )gVF gb ρρ −=

Gas momentum force, 22

4ggag WdF ρ

π= , with

2

4

a

gd

QW

π=

Pressure force, ( )PPdF gap −= 2

4

π

Drag force, *2

2 .4

.2

1dd C

dWF

πρ=

76

Inertial force, γρρ

ρα VF

g

i

+=

Surface tension force, σπσ adF =

Where gW is the gas velocity through the tube, W the average velocity of bubble

expansion, γ the average bubble acceleration, *

dC the average drag coefficient, σ the

surface tension of the liquid, gP the gas pressure in the bubble and P the average liquid

pressure.

Koh and Taylor [52] studied the splashing at the free surface of the sirosmelt bath in

an air-water model using an electrical conductivity method. They measured the

average splash height and total splash volume at various air flow rate for a range of

lance geometries. The authors investigated three modes of gas injection system:

bottom injection, injection through plain lance and injection through swirled lance and

reported that the splash height and volume produced by the top submerged swirled gas

injection system are the smallest. The authors also reported that splash height and

volume are significantly decreased when the swirler is located at the tip of the lance.

The similar findings were also reported by Igwe et al. [53], where they did similar

type of cold flow nitrogen-water experiments to measure the jet penetration and liquid

splashes in submerged gas injection systems. They studied the effect of lance design,

nozzle dimensions, gas driving pressure and liquid densities on jet penetration, bubble

dispersion and liquid splashes. The authors reported that penetration of the jet is a

function of the term, mFr , which is a modification of the jet Froude number,

( )og

g

mdg

vFr

ρρ

ρ

−=

1

2

3.16

Where 1ρ is the liquid phase density, gρ is the density of gas, g is the gravitational

constant, v is gas flow velocity and do is the orifice diameter. The higher is the

modified Froude number, the greater is the horizontal component of the jet

penetration.

Iguchi et al. [51] measured the vertical migration distance of the bubbles from the

lance exit using electro resistivity probe and developed an empirical equation to

77

calculate the vertical migration distance of the air jet for top submerged lance gas

injection which also depends on air flow rate. The empirical equation proposed by

Iguchi et al. [51] for vertical migration distance of the injected air into the liquid bath

can be expressed as,

31

1.4 mnv FrdL = , 2< Frm < 6x103

3.17

where Lv is the vertical migration distance of the injected air, dn is the nozzle inner

diameter at the exit and Frm is the modified Froude number which can be expressed as,

5

2

nL

gg

mgd

QFr

ρ

ρ= 3.18

where gρ is the density of gas, Lρ is the density of liquid, Qg is the gas flow rate and

g is the acceleration due to gravity. In this equation dn is used as the inner diameter of

the nozzle.

Iguchi et al. [48] investigated the mechanism of heat transfer between bubbles and

liquid and the effect of heat transfer on the formation of bubbles and the rising

characteristics of bubbles, using air and helium in a water model. In real conditions,

gas is blown into the molten bath at a temperature much lower than the liquid

temperature and hence heat transfer takes place between bubbles and liquids. So, in

the experimental investigation of by Iguchi et al. [48], air and helium were cooled to -

110o

C and blown into water to investigate the effect of temperature difference and

heat transfer on the formation of bubbles and the rising characteristics of the bubbling

jets. The authors concluded that bubbles tended to spread in the radial direction rather

than upward and gas hold-up for a cold gas injection became relatively large compared

with the ambient gas injections. Komarov and Sano [66] carried out similar type of

experiments to reveal bubble behaviour and heat transfer in preheated gas injection

into liquid baths. In that study, preheated gas (N2, He, Ar-He mixture) were injected

into the bath of volatile (water) and non-volatile (ethylene glycol, methyl carbitol and

ethylene glycol-glycerine mixture) liquid. The results showed that the size of the

rising bubbles decreases as the surface tension decreases, so the bubble diameter

decreases when preheated gas is injected.

78

Kumagai and Iguchi [67] carried out further experimental study of instability

phenomena due to formation of splash at the bath surface in top lance injection. The

authors reported that instability phenomena of the bubbling jet appear when the gas

flow rate is higher than a certain critical value. The phenomena are strongly dependent

on the penetration depth of the bubbling jet into the bath. Iguchi et al. [68] studied the

behaviour of an air-water bubbling jet subjected to Coanda effect. In the case of

eccentric lance gas injection, jet or bubble plume moving near a wall is pulled towards

the wall, attaches to it and finally moves along it. This effect is known as the Coanda

effect, which is caused due to the pressure difference along an eccentrically

submerged lance. In that study, Iguchi et al. [68] measured bubble frequency, gas

holdup, mean bubble rising velocity and mean bubble cord length by using two-needle

electro-resistivity probe. The results showed that, these quantities were hardly

influenced by the side wall of the vessel and the vertical bubbling jet is free from the

Coanda effect.

Iguchi with some other co-workers [46] developed another electro-resistivity probe

being able to continuously measure bubble characteristics in a molten iron bath

agitated by gas injection for two hours. The authors measured axial and radial

distribution of gas holdup, bubble frequency, mean bubble rising velocity and mean

bubble diameter in a molten iron bath at a temperature of 1250oC and compared the

measured values with the previous cold model experimental data and empirical

equations proposed by the same author. Mean bubble rising velocity and bubble

diameter are also measured by Diaz et al. [69]. The authors used a rotary L-shaped

lance to study bubble behaviour and absorption rate of gas injected into liquid bath.

Bubble diameter and bubble rising velocity were measured by using high speed video

recording system and absorption rate of injected CO2 gas in aqueous NaOH solution

was measured by using a pH meter. The authors reported that the lance rotation leads

to decrease in average bubble diameter and the rising velocity as compared with the

stationary lance and also the gas absorption rate for rotary lances is larger than that for

the stationary lance.

79

3.1.4 Bath mixing characteristics

Investigation on bath mixing characteristics has also drawn significant attention of the

researchers for different gas injection system. Uniform and rigorous bath mixing

accelerates the chemical reactions within the bath. There had been numerous studies

on the bath mixing characteristics, mostly based on cold model investigation.

Rankin et al. [70] carried out extensive research based on experimental and numerical

studies to reveal the bath mixing characteristics for top submerged lance injection

systems. The authors used PHOENICS computer code to predict the velocity field and

turbulence mixing inside the bath and carried out some pilot plant trials and air-water

model experiments to validate the PHOENICS simulation results.

Singh and Ghosh [71] conducted experimental studies to determine the mixing time

and mass transfer rates between slag and metals in an LBE (Lance Bubbling

Equilibrium) model by means of conductivity measurement and chemical

decolourization methods. The authors reported that mixing time decreases as the

number of porous plugs increases and volumetric mass transfer coefficient for LBE

method is higher than that for top blowing and bottom blowing process.

Investigation on bath mixing by coaxial gas injection through a nozzle fitted at the

bottom of the bath is carried out by Krishna and Mehrotra [72]. The authors described

the re-circulatory flow pattern generation mechanism in such baths and the effect of

process variables on the two phase plume shape and dimensions. Experimental

techniques of characterising the mixing of liquids in these baths by determining

velocity fields or by estimating mixing parameters such as mixing time, degree of

mixing, etc. was also described by the authors. They also proposed a correlation

between mixing time and various operating variables, based on cold model studies.

Diaz et al. [73] used L-shaped lances to reveal mixing characteristics of gas injection

for rotary lances. The authors measured the mixing time by means of the electrical

conductivity method and used KCL as the tracer which was added to the liquid bath

through a funnel. The authors concluded that mixing time is a function of a number of

variables which are bath depth, gas flow rate, lance rotation speed and elbow length

and proposed the following empirical correlation for mixing time , mixt ,

80

∞mixt 21.216.039.039.044.0 DHLRQ −−−− 3.19

where D is the vessel diameter, H bath depth, L elbow length, R rotation speed, Q gas

flow rate.

Later, Krishnakumar et al. [74] also calculated mixing time by using electrical

conductivity measurement technique, where the authors investigated the mixing

phenomena in a VOD (Vacuum Oxygen Decarburisation) ladle and the effect of

different placements of bottom nozzle with and without a top jet. The authors defined

two degrees of mixing (t95 and t99) for their water model experiments. They finally

concluded that mixing time tend to decrease considerably as the position of the bottom

nozzle is moved away from the centre to the mid-radius irrespective of whether a top

jet is present or not.

3.1.5 Numerical Investigation

Numerical technique is also a powerful tool to investigate different fluid dynamic

characteristics in gas injection processes. Though not much study on numerical

investigation of top submerged lance gas injection system are reported in the open

literature, there are significant research findings on the other types of gas injection

processes based on numerical studies.

Schwarz and Koh [75] first developed a numerical model of bath mixing by swirled

gas injection. They used finite domain computer code PHOENICS to model both flow

within the lance, with and without swirlers. The authors reported that swirl flow

within a lance showed that a recirculating pattern is set up, leading to an increase in

the axial velocity at the lance wall by a factor of about three over the mean flow

velocity which enhanced the heat transfer between the lance wall and the gas. The

simulation results were validated against cold flow air-water model experimental data.

In their numerical investigation, Schwarz and Koh [75] used Prandtl mixing length

model for modelling of turbulence and suggested that a more sophisticated turbulence

and turbulence diffusion models must be used to predict void fraction distribution

accurately. Rankin et al. [70] also used the similar type of PHOENICS code to

simulate the bath mixing process. Liovic et al.[76, 77] developed a numerical model

for simulating transient behaviour of multi-fluid problems. They investigated the gas

81

injection process for top submerged lance as a 2D axisymmetric problem by using

CFD. In their simulation, to get a complete cross-sectional view, the results at the

centreline were mirrored. However, Liovic et al.[76] also reported that, 2D

axisymmetric volume tracking was unable to facilitate the simulation of fully 3D

interfacial phenomena. Due to the complex nature of the flow structure involved in the

gas injection system, detailed understanding of the hydrodynamics of the gas injection

system still needs thorough investigation.

Solnordal and Gray [78] developed a mathematical model of heat flow to an operating

sirosmelt lance which predicts lance wall and air temperatures and thickness of the

slag layer on the lance. The model was used to determine both the heat transfer

coefficient between the vessel contents and the lance and the thermal conductivity of

the slag layer by measuring the distribution of wall temperature and slag thickness on

an operating sirosmelt lance. Turkoglu and Farouk [79] numerically analysed the time

evolution of the flow and temperature fields in industrial scale gas-injected molten

iron baths by using Eulerian approach. The authors used a constant effective viscosity

for the gas phase turbulence and predicted the turbulence in the liquid phase using two

equation ε−k turbulence model.

Shin et al. [80] simulated turbulent combustion phenomena in the gas phase occurring

at the post combustion stage in a bath type smelting reduction process with the help of

mathematical model which combines the Simple Chemical Reaction System (SCRS)

combustion model with instantaneous reaction up to the chemical equilibrium state

allowing the concentration fluctuation and the ε−k turbulence model. The authors

investigated the effects of the injecting method on the oxidation. In their study, the

efficiency of the post combustion operation was evaluated by the post combustion

ratio (PCR) at the outlet of the furnace, where,

∑ ∑

∑+

=coco

co

mm

mPCR

ρρ

ρ

2

2 x 100 (%) 3.20

The authors reported that Post Combustion Ratio (PCR) was elevated with the

decrease of the inlet velocity of the injecting gas and the increase of the lance height

from the iron bath. The results further predicted that oxygen should be injected with

82

the low inlet velocity at the large distance from the iron bath surface in order to attain

the efficient post combustion operation.

Zhu et al. [81] carried out similar type of numerical investigation for the three

dimensional turbulent fluid flow and mixing characteristics in gas-stirred ladles. The

authors investigated the effects of gas flow rate, positions of nozzle and tracer and

inclined wall on the flow pattern, and mixing phenomena. They concluded that

eccentric blowing reduces the mixing time and the mixing time is sensitive to the

alloy/tracer adding position especially for centre blowing. For the ladle with inclined

wall, it has shorter mixing time compared with the cylindrical one. Zhu et al. [81] used

the following experimental correlations proposed by Castillejos and Brimacombe [82]

to model the bubble plume zone by considering some assumptions:

−=

4.2

2/max max

7.0expαα

α

x

x 3.21

where,

α = Volume fraction of gas in the plume zone

maxα = Volume fraction of gas at plume centre line

2/max, αxx = Radial coordinate across the plume; half-value radius

The assumptions are,

1. The fluid flow in gas-stirred systems was driven by buoyancy of bubbles, and

the inertial force of bubbles was neglected.

2. The domain is occupied by a single phase fluid with spatially variable density.

3. The top surface is flat, and no tangential stresses are present.

4. The formation of the plume at the first stage of blowing was neglected and it was

taken as stable during the blowing.

Bernard et al. [83] developed another numerical model where the authors proposed a

simple approximation for the buoyant force in a bubble plume. By assuming a uniform

radius and slip velocity for the entire bubble column, the authors derived an

expression for the vertical acceleration of liquid in the column which is directly

proportional to the injected gas flow-rate and inversely proportional to the depth and

83

velocity. This bubble induced acceleration has been implemented with a ε−k

turbulence model in the MAC3D single-phase CFD code. But this model is not

applicable for stratified liquids in which there is a sharp density gradient between two

weakly stratified layers. Milelli et al. [84] also developed another numerical model for

bubble plume using CFD which focuses on the effect of turbulence in promoting bath

mixing and the application of Large Eddy Simulation (LES) methodology to capture

bubble-induced turbulence effects. In that study, the flow considered is also buoyancy-

driven rather than shear induced.

Morsi et al. [85] carried out a numerical investigation of the top submerged gas

injection system by using CFX 4 which is based on Eulerian – Eulerian two phase

model and drag force, lift force and turbulence dispersion force were taken into

account for the interface between gas and liquid. Morsi et al. [85] assumed same

pressure in both phases on the same computational cell and a constant gas velocity at

the exit of the nozzle which is treated as a mass source term with a corresponding

source term in the axial momentum equation at the nozzle exit.

Fluid flow, bubble distribution and gas-liquid mass transfer in a water model vessel

with gas injection were also analysed numerically by Taniguchi et al. [43]. They

investigated the effect of turbulence on metallurgical reactions in ladles. In that study

the authors applied a mathematical model composed of ε−k model and bubble-

dispersion model. Flow pattern, gas hold-up distribution, velocities, k and ε

distributions were calculated and these results were validated with previous

experimental data obtained by LDV. Another CFD modelling of bubbles, droplets and

particles in metals reduction and refining was developed by Cross et al. [86]. Alessio

[87] also investigated numerically the bubbles dispersion patterns in a gas-stirred

ladle.

3.2 Review of Zinc Slag Fuming Process

Smelting industries often produce slag, containing significant amount metal oxides,

which are often discarded as waste. Significant metal values can be recovered from the

slag by proper treatment. Zinc slag fuming is such a process, where a reductant source

(usually coal) is injected in the molten slag bath to reduce dissolved ZnO from the

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bath into metallic zinc vapour. The process can be carried out in either conventional

tuyere blown furnace or top submerged lance (TSL) smelting furnace. Commercial

development of the process using tuyeres was made by the Anaconda Coper Mining

Co. and Consolidated Mining and Smelting Co. in the 1920’s [21]. The potentiality of

extracting lead and zinc from different source other than the primary ores was

discussed by Ward [88]. Ward [88] discussed the economic values of lead and zinc in

the world market and emphasized for a more suitable environmentally friendly

extraction method for those two valuable metals.

In this section, a comprehensive literature survey on the zinc slag fuming process will

be discussed. As the zinc slag fuming can be carried out by both top submerged lance

smelting furnace and conventional tuyere blown furnace, a detailed literature survey

was carried out on each of the process. Details of the process overview on the zinc

extraction and slag fuming process by employing both top submerged lance and

conventional tuyere blown furnace was discussed on chapter 2 in section 2.7.2.

3.2.1 Slag fuming by conventional tuyere blown process

Though conventional slag fuming has been commercially operative since 1920’s, only

a few studies related to slag fuming kinetics and details of fluid dynamic behaviour

inside the slag fuming furnace has been found in open literature. The earliest studies

were performed in 1950s by Bell et al. [89] and Kellogg [90, 91] and in 1960’s by

Quarm [34, 92, 93] to investigate details of slag fuming behaviour. Later on, Richards

et al. [19-21, 30, 94, 95] carried out extensive research on slag fuming process.

Investigation on slag fuming kinetics carried out by Richards et al. [19-21] comprised

of accumulating several industrial data and mathematical modelling. The industrial

study consisted primarily of slag sampling through five different fuming cycles [21].

From that industrial study, the authors reported that, in general, zinc elimination curve

is linear with time and a portion of the injected coal entrains in the slag [21]. From the

analysis of the tuyere back-pressure fluctuations and movie photographs of the tuyere

tip, they reported that coal-air mixture enters the slag in the form of discrete bubbles.

They divided the fuming furnace into two reaction zones: Reduction zone and

Oxidation zone. In the Reduction zone, the coal entrained in the slag reduces ZnO and

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Fe3O4 which is responsible for fuming. In the Oxidation zone, the remaining coal in

the tuyere gas stream combusts.

Based on the data obtained in industrial studies, Richards and Brimacombe [20]

developed a mathematical model of zinc slag fuming based on the kinetic concept of

the two reaction zone from the industrial studies. The two zones and the water-

jacketed furnace wall had been linked by overall heat and mass balances. The authors

reported that the model had shown consistent results over five different industrial

fuming operations among the eleven industrial fuming cycles tested. They also

reported that about 33% of the injected coal was entrained in the slag, 55% combusted

in the tuyere gas column and 12% bypassed the bath completely. Later on, Cockcroft

et al.[96] improved that mathematical model of zinc slag fuming, based on rate

phenomena such as mass transfer, chemical kinetics and heat transfer and also

including the behaviour of lead in the bath. That improved model predicted that

fraction of coal entrained is greater with increasing nominal tuyere exit velocity and

that oxygen utilization increases as the bath depth is raised. That model also predicted

that the settling and collection of metallic lead will bear importantly on the removal of

lead from high lead slags produced by the QSL and flash smelting processes.

Finally, Richards and Brimacombe [19] elucidated the rate limiting steps of the

fuming process and predicted the influence of process variables on fuming by using

the mathematical model [20]. The model predicts that fuming efficiency reaches

maximum with increasing residence time of coal particles in the slag. The level of

ferric iron in the slag is an important variable affecting the fuming kinetics. The level

of ferric iron in the slag depends on ferrous iron oxidation rate, melting/freezing of

slag at the water-cooled jacket and ferric iron reduction by coal entrained in the slag.

They further reported that, at the beginning for very short span of time, Boudouard

Reaction controls the zinc reduction kinetics. However, after that it is been controlled

by diffusion of ferric iron to the interface between the secondary bubbles containing

the coal and the slag. They also reported that increase in coal entrainment increases the

fuming efficiency. Coal entrainment can be increased by injecting coal in high-

pressure. Cockcroft et al. [97] reported from another study, that high pressure coal

injection increased coal entrainment about 25%, as a result fuming rates were

increased substantially, to between 70 and 90 pct, depending on the charge mix.

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Richards [94] commented that coal entrainment is controlled by injection conditions

whereas bath temperature is a function of coal combustion and ferrous oxide

oxidation.

Another mathematical modelling study of a DC electric furnace for zinc recovery from

lead blast furnace slag has been carried out by Chang et al. [98]. In that work the

authors predicted the momentum and heat transfer from the arc to the slag by algebraic

equations and considered a two dimensional steady state model for electrical current

flow, fluid flow and mass transfer. Kellogg [90] developed the first computer model

for slag fuming process. In that model, Kellogg assumes stepwise equilibrium during

each micro-step (0.1 minute in a 90 minute period). By using Kellogg’s computer

model, Grant [99] derived the thermodynamic properties of slags from the slag fuming

plant data.

Scholey et al. [100] investigated the heat transfer phenomena in water cooled zinc-

fuming furnace jackets for conventional rectangular furnace with submerged tuyeres.

From the industrial measurement, Scholey et al. [100] reported the presence of large

thermal transients or temperature “spikes” in the region immediately above the tuyeres

and commented from a mathematical analysis that these temperature spikes are

associated with sudden slag falloff due to charging and tapping of the furnace and

agitation on the bath surface due to gas injection effects. The authors concluded that

the temperature spikes can be reduced by increasing the number of anchoring fins

which will reduce the crack formation and propagation along the furnace wall.

Other than the batch fuming process, some studies on continuous fuming process was

carried out by Richards [95], Haralampiev and Popov [101]. Haralampiev and Popov

[101] carried out a physical investigation of the continuous fuming process by using

water and 72 weight % glycerine solution. They suggested some changes in the

dimensions of the furnace to facilitate the continuous fuming process. Richards [95]

reported that fuming efficiency (Zn/coal) in continuous fuming was predicted to be

lower than the batch process for equivalent overall slag flow rate. Further industrial

studies have followed the studies by Richards et al. [19-21, 94] and Cockcroft et al.

[96, 97]. Lehner and Lindgren [102] reported the detail of fluid flow behaviour by an

industrial study at Boliden’s zinc fuming plant. They carried out a series of

experiments to investigate the mixing behaviour in the slag by adding radioactive

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gold. They also analysed the fuming behaviour and reported that zinc fuming process

is controlled dominantly by the gas phase.

3.2.2 Slag fuming by TSL process

Slag fuming by using top submerged lance (TSL) technology has been successfully

operating around the world. Zinc slag fuming by TSL technology has started with pilot

plant studies in 1980’s and has progressed to the treatment of close to 800,000 tonnes

a year of zinc bearing feeds in the form of residues and slag [39]. There are a few

studies in the open literature regarding slag fuming behaviour by using TSL

technology, based on both laboratory scale work and pilot plant scale studies.

Suzuki et al. [31] investigated the factors effecting the zinc fuming kinetics such as

gas or slag composition, gas blow rate, slag temperature, viscosity and surface tension.

They carried out laboratory scale experimental work by blowing N2 gas or gas

mixtures of CO, H2 and CH4 with CO2 using a top lance into molten slag containing 6-

12 pct of zinc at 1200-1300o

C. In their research, Suzuki et al. [31] found that

formation of bubbles in the molten slag bath has a great influence on the zinc fuming

kinetics. They reported some important parameters that remarkably effect the

formation of bubbles which are surface tension, viscosity of the liquid. The number of

bubbles became fewer as the values of these physical properties were larger and

therefore each bubble size became larger. Formation of the number of bubbles also

depends on the gas blow rate. The number of bubbles increased with increasing gas

blow rate up to a limiting value, but after exceeding this value it decreased rapidly.

The authors also reported that the forming state of bubbles differed with the kind of

blowing gases, like H2, CO and N2. The authors developed an equation of the zinc

fuming rate from their experimental results, which can be expressed as:

28 2

12/

2aKntn

N−=∆∆ 3.22

where, n∆ is the change of ZnO in slag in the unit of g-mols, a is the activity of ZnO

and 1

K is the equilibrium constant which can be expressed as:

appKozn

/. 2/12

1= 3.23

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znp and

2op are the equilibrium partial pressures of Zn and O2 respectively. The

activity of ZnO may be expressed as:

)/(.. ∑+==i

nnnNa γγ 3.24

where, N represents the mol fraction of ZnO in the slag, γ is the activity coefficient of

ZnO, n is the g-mols of ZnO in the slag and ∑ in is the summation of g-mols of the

components except ZnO.

Denholm et al. [103] carried out the first experimental work on top submerged lance

investigation after its invention and some pilot plant trials. The experiment was done

in CSIRO and emphasised on copper matte converting and zinc slag fuming. That

study was based on four fundamental investigations to have a clear understanding of

working principle and possible implementation of the TSL technology in industrial

zinc fuming applications. The four studies were:

1. Tracer studies to reveal mixing conditions in the bath by swirl and non swirl

air injection.

2. Sampling and analyses of the slag to establish the rate of reduction reactions

during addition of carbonaceous reductants to copper and zinc slag.

3. Gas pressure fluctuations measured on the lance air supply for a range of

lances and operating conditions.

4. Temperature measurements within the lance.

The study emphasised one of the most important aspect of the present research which

is the investigation of zinc slag fuming by both batch and continuous process. The

authors reported that significantly higher carbon utilization rate was achieved when

zinc was fumed in a continuous process than compared to the batch process.

Waladan et al. [2, 104, 105] reported several studies based on the experimental works

of zinc slag fuming process by using top submerged lance. From a pilot plant scale

study Waladan et al. [2] discussed the detail of zinc fuming behaviour, effect of coal

addition rate and coal particle size on the fuming rate. They also discussed the

comparison between conventional tuyere blown process and TSL process of zinc

fuming. Later on, Waladan and Nilmani [105] carried out a crucible scale

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experimental work to investigate the effect of different injection parameters like lance

diameter, gas flow rate, slag bath temperature and different reducing agent on fuming

rate. From their work, the authors reported that high momentum coal injection, a thin

wall lance, intense bath agitation and increasing temperature, all improved fuming

rates. They further reported that there was substantial increase in the fuming rate when

they changed their injection lance from an internal lance diameter of 4 mm to 2 mm.

Reddy et al. [32] carried out another crucible scale laboratory study to recover zinc

from industrial lead blast furnace slag. They investigated zinc fuming behaviour with

and without carbon addition by stirring the slag with air or argon. That study showed

that even without the carbon addition, zinc fuming took place by the diffusion of Fe+2

ions in the melt. They also reported that the type of stirring gas (air or argon) or the

flow rate did not influence the reaction mechanism. Lightfoot et al. [106] also

demonstrated some pilot plant scale trials in addition to crucible scale laboratory study

to investigate the zinc fuming behaviour from slag.

Gupta [107] proposed a method for the production of zinc from zinc oxide and

complex zinc concentrates. The two stage process proposed by Gupta [107] involves

oxidation of zinc sulphide to oxide and dissolution into slag and the fuming of zinc

from the slag by injecting carbonaceous materials into it to produce zinc vapours.

Gupta [107] carried out the experimental study on a laboratory scale TSL setup. The

author discussed the effect of the quantity of air, temperature and concentrate feed rate

on the production of zinc rich slag. The author also reported that smelting temperature

less than 1300oC have a detrimental effect on the viscosity of slag. Neira et al. [108]

carried out another study to recover zinc from the waste oxide generated by Ausmelt

Pyro-processing. In that research, a laboratory evaluation for electrowinning of zinc

electrolytes generated by Aumelt’s TSL pyrometallurgical process was carried out.

They suggested some special treatment to remove impurities before undertaking the

electrowinning process.

Miyake [109] described different aspects and optimized plant operating conditions of a

slag fumer at the Hachinohe Smelter using TSL furnace. Choi and Lee [33],

Matusewicz et al. [110], Sofra et al. [36], Hughes et al. [35], Hoang et al. [42]

described the Outotec’s Top Submerged Lance (TSL) technology for the processing of

secondary zinc feed materials, including zinc plant leach residues and EAF dust.

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3.2.3 Other studies based on zinc extraction

Other than the studies based on conventional slag fuming and TSL slag fuming, there

had been numerous studies on thermodynamic analysis of zinc slag fuming and some

other modified way of slag fuming. In this section, some studies found in open

literature will be discussed briefly.

Jak and Hayes [111] carried out thermodynamic analysis for slag fuming using the

F*A*C*T computer package. They pointed out the effects of slag chemistry on the

liquidus temperatures, subliquidus phase equilibria and thermodynamic properties on

slag fuming by using that computer package. From their thermodynamic analysis, the

authors argued that initial stage of zinc fuming is principally equilibrium controlled

when the zinc concentrations in the slag is high. As zinc concentrations in the slag

decreases, the reaction becomes increasingly controlled by kinetic factors and far

away from equilibrium conditions. The authors compared their thermodynamic data

based on the plant measurements carried out by Grant [99]. Later, Jak and Hayes [112]

and Verscheure et al. [113] discussed the role of slag chemistry in the design of freeze

linings for slag fuming furnaces. The effect of sulphur on the rate of reduction of zinc

oxide from slags was studied by Dal and Rankin [114]. Fumed zinc from the slag bath

usually undergoes re-oxidation process above the bath in the post combustion zone.

Kinetics of zinc vapour oxidation was discussed by Lewis and Cameron [108].

Figure 3-1: Schematic of the submerged plasma process for the high temperature

fuming of zinc from zinc containing residues [Image taken from Verscheure et al.]

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To treat zinc leach residues, electric arc furnace (EAF) dusts, and other zinc-

containing waste materials, Verscheure et al. [115-118] proposed a new high

temperature submerged plasma zinc fuming process. They developed the model by

using the FactSage thermodynamic databases and ChemApp thermodynamic software.

The proposed process is electricity based pyrometallurgical process that uses

submerged plasma torches to supply the necessary heat in the fuming bath. Inside the

plasma torches, the cold blast air is transformed into a high enthalpy plasma gas. The

plasma gas is then mixes with the natural gas (CH4) and injected into the slag bath.

Parallel to this, a mixture of leach residue, petroleum coke, and fluxes is fed

continuously into the slag bath. The investigators reported that the submerged plasma

arc process can operate at higher operational temperatures (1300o C – 1400

o C), as

compared to the conventional zinc fuming process (1200o C – 1250

o C).

Barcza et al. [119] and Latif [120] described the Enviroplas process of zinc recovery

from metallurgical wastes. As reported by Latif [120], the Enviroplas process was

developed at Mintek, South Africa, to treat certain metallurgical wastes, such as lead

blast furnace (LBF) slag, electric arc furnace (EAF) dust, and neutral leach residues

(NLR) from the zinc industry. The process involves smelting of those metallurgical

wastes in a DC arc furnace and subsequent recovery of the volatilized zinc in an ISP

lead splash condenser. In this process, the dry granulated slag are directly charged into

the fuming furnace. Metallurgical coke is employed as a reducing agent and is

delivered to the fuming furnace at a controlled rate. Coals, charcoal or other

carbonaceous materials, low in moisture and volatile content are also used as reducing

agents. Inside the fuming furnace, the zinc and lead oxides from the slags are reduced

to their metals at 1400o C – 1500

o C temperatures. The residual is tapped from the

furnace as required. The volatilized zinc and lead are collected through a refractory

lined duct and condensed in a lead splash condenser (operated at 500o C – 550

o C).

Figure 3-2 shows the schematic diagram of the Enviroplas process.

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Figure 3-2: Schematic diagram of the Enviroplas pilot plant (Image taken from Latif

[104])

Tarasov and Besser [121] discussed the processing of lead and zinc raw materials to

extract from primary ores. Schwarz [122] carried out some study related to primary

zinc production by using computational fluid dynamic (CFD) modelling. That study

dealt with CFD modelling of thickeners only.

3.3 Research Objectives

The research objectives of the present study can be summarized from the above

discussion. As discussed in the primary research theme (section 1.1), combustion

behaviour and zinc fuming behaviour from a pilot plant scale TSL furnace was the

initial research theme. As an initial step, cold modelling analysis of the TSL system

was carried out by using CFD. Literature survey on the cold modelling investigations

of the gas injection system (section 3.1) revealed that the experimental studies dealt

with the effect of lance submergence level, gas injection rate and swirl intensity on the

change of velocity components and turbulence behaviour. None of the studies reported

about the bath mixing characteristics with the change in hydrodynamic parameters

(lance submergence level, flow rate and swirl intensity), splashing behaviour with the

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change in hydrodynamic parameters and liquid properties (density and viscosity),

penetration depth of the injected gas jet for annulus air injection generally used in TSL

process. The numerical studies (Liovic et al.[76, 77], Schwarz and Koh [75]) carried

out for TSL investigation involved 2D axisymmetric grid and in some case the results

at the centreline were mirrored to get the overall behaviour. Due to the complex nature

of the flow structure involved in the gas injection system, detailed understanding of

the hydrodynamics of the gas injection system still needs thorough investigation.

Hence, the aim of the first phase of the present study is to investigate the physical

behaviour of the top submerged gas injection system and to predict the effect of swirl

intensity, lance submergence level and air injection rate on the overall bath mixing and

splash generation by using the 3D hybrid grid system. The vertical depth of

penetration of the air jet injected through the annulus of the lance into the liquid bath,

splashing behaviour inside the bath with the change of density and viscosity of the

liquid were also of the significant interests.

Although commercial slag fuming is well established, literature survey on the zinc

slag fuming process showed there have only been a few numerical modelling studies

on zinc fuming kinetics. Kellogg [90] assumed stepwise equilibrium in his computer

model of the slag fuming process during each micro-step (0.1 minute in a 90 minute

period). No CFD analysis has been found in the open literature regarding slag fuming

to date. The purpose of this study is detailed fluid dynamic analysis including

combustion behaviour, gas-liquid momentum interaction, generation of splashing due

to gas injection process in slag fuming furnace, analysis of fuming behaviour at

different locations of the furnace by using computational fluid dynamic (CFD)

modelling technique. Hence, the second stage of the present study emphasized on

revealing detail of the combustion behaviour, fuming kinetics in the slag bath,

splashing behaviour in a pilot plat scale combusting. Finally, in the third stage,

investigation on tuyere tip combustion dynamics, bath interaction conditions, jet

penetration length, generation of turbulence and coal utilisation behaviour inside the

bath were of significant interest.

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Chapter 4

95

4 Modelling Techniques and Model Features

This chapter describes the governing equations for fluid motion and the numerical

methods used to solve these equations. The description covers the CFD modelling

approach, discretization methods, schemes, turbulence modelling, and difficulties

associated with the solution procedure and methods of overcoming them. A

comprehensive description of the boundary conditions used for the developed models

is presented. Details of meshing and the methodologies used in physical modelling

are also discussed.

4.1 CFD Modelling

CFD stands for Computational Fluid Dynamics. It is an iterative calculation procedure

to obtain the solution of Navier-Stokes equations. The Navier-Stokes equations are

derived from the principle of conservation of mass and momentum. Hence, the

cornerstone of computational fluid dynamics is the fundamental governing equations

of fluid dynamics – the continuity, momentum and energy equations. These equations

speak physics. They are the mathematical statements of three fundamental principles

upon which all of fluid dynamics is based:

The mass of fluid is conserved

Momentum is conserved, i.e. the rate of change of momentum equals

the sum of the forces on a fluid particle (Newton’s second law)

Energy is conserved, i.e. the rate of change of energy is equal to the

sum of the rate of heat addition to and the rate of work done on a

particle (first law of thermodynamics)

The Navier-Stokes equations can predict the fluid flow behaviour in its general form.

From the 1960s onwards, the aerospace industry has integrated CFD techniques into

the design, R & D and manufacture of aircraft and jet engines. Then the method is

being started to apply to simulate different processes in internal combustion engine,

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combustion chambers of gas turbines and furnaces. Increasingly CFD is becoming a

vital component in the design of industrial products and processes. CFD has entered

into the wider industrial community since the 1990s [123]. With the advancement of

high performance computing facilities, Computational Fluid Dynamic (CFD)

modelling technique has evolved as a powerful tool for the researchers working in the

metallurgical field. CFD can predict flows ranging from simple single phase flows to

complex multiphase flows in high temperature combusting environment associated

with metallurgical process industries. Successful and efficient development of a CFD

model can predict the fluid flow behaviour, combustion behaviour, generation of

turbulence and splashing and other fluid dynamic parameters inside the furnace.

Fluid flow behaviour in a system and the related phenomenon like heat and mass

transfer can be represented by a set of non-linear partial differential (or integro-

differential) equations (PDE). Analytical solution of these equations is almost

impossible except in some special cases. To obtain an approximate solution

numerically, a discretization method is used, which approximates the differential

equations by a system of algebraic equations. These equations can then be solved on a

computer, providing a description of the flow field at discrete locations in space and

time. Much as the accuracy of experimental data depends on the quality of tools used,

the accuracy of numerical solutions is dependent on the quality of discretizations used

[124]. There are many different ways by which equations describing fluid flow and

heat transfer can be solved using computational methods. Most commercial and

research codes rely on the following:

Finite Volume

Finite Difference

Finite Element

Spectral Methods

Each of these methods requires the definition of discrete points in space at which

variables like velocity, pressure, temperature etc. will be computed. While the

governing equations are always the same, the particular geometry with initial and

boundary conditions determines a unique solution for each particular problem. This

97

research is based on the finite volume method, as it is the method used by most of the

popular CFD codes currently available. The other methodologies still commonly used

in industry and yield good result for certain types of application.

4.1.1 Finite Volume Method

The Finite Volume Method (FVM) starts with the integral form of the governing

equations, involving surface integrals (e.g. convective and diffusive fluxes) and

volume integrals (e.g. those describing sources and sinks). In case of a transient flow

(i.e. unsteady flow that changes over time), there is also a rate of change term. The

FVM represents the integration of the governing equations over (a finite number of)

contiguous control volumes (CVs) representing the solution domain. Since variable

values are computed only at discrete points, approximations must be used to express

the integrals in terms of unknowns at discrete locations. In this way one algebraic

equation per CV is obtained, linking variable value at the centroid of that CV with

those at neighbour CVs. For the solution domain as whole, a large system of algebraic

equations is obtained. Since these equations are in general non-linear and coupled, the

solution must be sought using iterative solution methods. Iterations means repeating a

sequence of operations over and over, until changes in computed variables becomes

negligible and we declare the process to as “converged”.

Most of the main commercial CFD codes, such FLUENT, STAR-CD, AVL FIRE are

based on FVM scheme. One of the reasons why FVM has succeeded over the other

methods is that it is inherently conservative: irrespective of errors in various

approximations, the discretized equations still fulfil the conservations laws exactly. In

other words, the errors introduced through various approximations affect only the

distribution of variables within solution domain without violating conservation

principles. The FVM is also easier to understand by engineers than some of the other,

more mathematically involved methods, since the term that need to be computed have

a clear physical meaning (e.g. mass or heat flux through a CV face, force at a CV

surface etc.).

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4.2 Multiphase Flow Modelling

Multiphase flow in CFD can be referred to any fluid flow consisting of more than one

phase or component. In multiphase flow, a phase can be defined as an identifiable

class of material that has a particular inertial response to and interaction with the flow

and the potential field in which it is immersed. For example, different-sized solid

particle of the same material can be treated as different phases because each collection

of particles with the same size will have a similar dynamical response to the flow

field. Two phase flow is the simplest case of multiphase flow. Multiphase flow can be

classified according to the state of the different phases or components and therefore

refer to gas-solids flows, gas-liquid flows, liquid-solids flows or gas-particle flows or

bubbly flows and so on.

4.2.1 Approaches to Multiphase Modelling

Computational fluid mechanics (CFD) modelling in recent years have provided the

basis for further insight into the dynamics of multiphase flows. Currently there are two

approaches for the numerical calculation of multiphase flows: the Euler-Lagrange

approach and the Euler-Euler approach.

4.2.1.1 THE EULER-LAGRANGE APPROACH

The Lagrangian discrete phase model follows the Euler-Lagrange approach. This

approach is generally used for highly dispersed flows where the volume fraction of the

dispersed phase is small. The time-averaged Navier-Stokes equations is solved for the

fluid phase which is treated as a continuum, while the dispersed phase is solved by

tracking a large number of particles, bubbles, or droplets through the calculated flow

field. There is exchange of interfacial momentum, mass, and energy between the

dispersed and the continuous phase. A fundamental assumption made in this model is

that the dispersed phase occupies a low volume fraction, even though high mass

loading ( fluidparticle mm ≥ ) is acceptable. The particle or droplet trajectories are

computed individually at specified intervals during the fluid phase calculation. The

model is appropriate for the modelling of spray dryers, coal and liquid fuel

combustion, and some particle-laden flows, but inappropriate for the modelling of

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liquid-liquid mixtures, fluidized beds, gas-liquid flow or any application where the

volume fraction of the secondary phases is not negligible.

4.2.1.2 THE EULER-EULER APPROACH

In Euler-Euler approach the fluid phases are treated mathematically as interpenetrating

continua. Fluids are treated in every computational cell with the concept of phasic

volume fraction. For a two phase flow situation, as the volume of a phase cannot be

occupied by the other phase, each of the phases is considered to occupy a fixed

volume fraction in a computational cell. These volume fractions are assumed to be

continuous functions of space and time and their sum is equal to one. Conservation

equations for each phase are derived to obtain a set of equations, which have similar

structure for all phases. These equations are closed by providing constitutive relations

that are obtained from empirical information, or, in the case of granular flows, by

application of kinetic theory.

The present study is based on Euler-Euler approach, as the research deals with gas

injection process of top submerged lance furnace and understanding the detailed fluid

dynamic and combustion behaviour inside the TSL furnace. Euler-Euler approach was

more suitable for the current research where gas and liquid volume fraction in a

computational cell was of fundamental interest rather than keeping track of the

lagrangian particle phase. The first stage of the research was based on gas (air)

injection in liquid (water) only and understanding the hydrodynamic parameters of the

process. In the second stage, the model was extended for submerged combustion of

gaseous fuel in molten ISF slag for zinc fuming TSL furnace and investigating the

combustion behaviour, reaction kinetics, fuming behaviour inside the furnace.

Gaseous fuel (CH4) was chosen to simulate the combustion behaviour for submerged

combustion at the lance tip. In the third stage, the model was extended for multiphase

submerged coal combustion in rectangular tuyere blow zinc fuming furnace, which

was also carried out in Euler-Euler approach. The aim was to investigate the

hydrodynamic parameters of zinc fuming behaviour from molten slag and understand

the kinetics of submerged coal combustion. The fundamental assumption of that

approach was that coal was assumed to be a separate scalar of the continuum liquid

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phase instead of discrete particles. The detail of the coal combustion modelling is

discussed later (Section 4.3.3.4.1).

The present research was carried out by using the commercial CFD package AVL

FIRE (Version 8.52 and Version 2009.2). The FIRE Eulerian Multiphase Module

allows the use of the following models based on the Euler-Euler approach listed in the

order of increasing accuracy [125]:

Homogeneous (Equilibrium) Model

Multi-fluid Model

Volume-of-Fluid (VOF) Free-Surface Model

4.2.1.2.1 Homogeneous Model

The homogeneous model is the least accurate multiphase model based on the Euler-

Euler

approach. A volume fraction equation is calculated for each phase. However, only a

single

momentum equation is calculated for the phases in momentum equilibrium.

4.2.1.2.2 Multi-fluid Model

In the multi-fluid model, all conservation equations are solved for each phase. Since

the multi-fluid model requires by default the calculation of the complete set of the

conservation equations for each phase, it represents the basis for the Euler-Euler

schemes in the FIRE Eulerian Multiphase Module. The commercial software AVL

FIRE’s user-defined subroutines (UDF) allow customizing the calculation of the mass,

energy and momentum exchange.

4.2.1.2.3 VOF Model

The VOF model is a surface-tracking technique applied to a fixed Eulerian grid

proposed by Hirt and Nichols [126]. This model is designed for two or more

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immiscible fluids where the accurate prediction of the interface between the fluids is

of interest. In the VOF model, a single momentum equation is shared by the fluids,

and the volume fraction of each of the fluids in each computational cell is tracked

throughout the domain. Applications of the VOF model include stratified flows, free-

surface flows, filling, sloshing, the motion of large bubbles in a liquid, the motion of

liquid after a dam break, the prediction of jet break-up (surface tension), and the

steady or transient tracking of any liquid-gas interface.

From the numerical perspective the Volume-of-fluid model is very similar to the

homogeneous model. A single momentum equation is calculated for all phases that

interact using the VOF model. However, the calculation of volume fraction equations

using VOF model is considerably more accurate allowing the sharp resolution of the

interfaces. One of the common defects of the VOF calculation can occur when the

interface is not resolved sharply despite the use of the high-order discretization

techniques for the volume fraction equation – in that case the VOF model degenerates

into the homogeneous model. This is quite common in many practical calculations. It

happens due to very high-resolution requirements of the VOF model that can be often

hard to fulfil.

In the following sections, details of the modelling procedures including model

geometry, solution procedures and governing equations solved for each geometry will

be discussed further.

4.3 Model Geometry and Computational Methodology

Numerical simulations were carried out in three different geometries by considering

three different gas-liquid combinations. First stage of the research considered a

laboratory scale top submerged lance gas injection system with air and water as the

fluid. Then the model was applied to a pilot plant scale top submerged lance zinc

fuming furnace with submerged CH4 combustion and reactions in slag and gas phases

included. In the final stage, a thin slice model of the real plant scale rectangular tuyere

blow zinc fuming furnace was developed. Details of the model geometry,

computational methodology, boundary and initial conditions, fluid properties are

discussed below.

102

4.3.1 Air water Model

A 3D CAD model of the one sixteenth-scale air-water model of a 150-ton steel

making ladle was developed by using CAD tool. The CAD model is similar to the

experimental model of Morsi et al.[1]. A schematic diagram of the model is shown in

Figure 4-1. The vessel has a diameter of D =230 mm and length Z=560 mm. The tank

was filled up to L=150 mm with water. A vertical lance with an annulus of inner

diameter di =12.2 mm and outer diameter d

o=17 mm was fitted at the centre of the

cylindrical vessel. Air was injected through the annulus of the lance into the water

bath. On the top of the cylindrical vessel the outlet was defined by Do= 60 mm. Mid

Plane cross sectional view of generated grid for CFD analysis is shown in Figure 4-2.

Figure 4-1: Schematic diagram of the air-water model

103

Figure 4-2: Mid Plane cross sectional view of generated grid for CFD analysis

4.3.1.1 MODEL FEATURES

The CFD modelling of top submerged gas injection involves multiphase simulation

where gas and liquid phases interact with each other and there is significant

momentum exchange between the phases. The model was developed using the finite

volume method in conventional Eulerian approach by using commercial CFD package

AVL FIRE 8.52. The model developed include the following features,

Unsteady state multiphase solution for momentum and continuity was

considered.

Standard k-ε turbulence model for the turbulence modelling was employed.

A cell centred finite volume approach was used to discretise the governing

equations and the resulting discretised equations were solved iteratively using

segregated approach.

Pressure and velocity were coupled using the SIMPLE algorithm [127].

Least square fit approach was used for the calculation of the derivatives

104

For momentum and turbulence, first order upwind differencing scheme was

used whereas central differencing scheme with second order accuracy was

used for the continuity equation

Swirl flow was injected through the annulus of the lance at 57.5o relative to

radial direction.

4.3.1.2 GOVERNING EQUATIONS

Basic Eulerian equations, describing multiphase non-combusting system are given by

the conservation equations for continuity and momentum equations. Other than the

basic conservation equations, interfacial exchange terms for momentum at the gas-

liquid interface were also modelled. For three-dimensional fluid flow, these

conservation equations can be expressed as:

4.3.1.2.1 Continuity

t

kk

∂

ρα∂+ ∇ kkρα⋅ v

k = ∑

≠=

ΓN

kl,1l

kl k= 1,……,N 4.1

Where, N is the number of phases, kα is volume fraction of phase k, k

ρ is density for

phase k, vk is phase k velocity, klΓ is the interfacial mass exchange between phases k

and l, for this air-water simulation, no interfacial mass exchange terms were

considered. Summation of the volume fractions of the phases present,

11k

k=α∑

Ν

=

4.2

4.3.1.2.2 Momentum conservation

t

vkkk

∂

ρα∂+∇ kkρα⋅ v

k v

k = - kα ∇ p + ∇ kα⋅ ( τ

k + t

kT ) + kα fkρ + ∑Ν

≠= kl,1l

Mkl 4.3

∑Ν

≠= kll ,1

Mkl represents the momentum interfacial interaction between phases k and l, f is

the body force vector which comprises of gravity (g), p is pressure. Detailed

105

description of the momentum interfacial interaction is discussed later. Pressure is

assumed identical for all phases:

p = kp k = 1, ……., N

The phase k viscous stress integral is divided into non-transposed and transposed

terms. It can be expressed as:

τk = kµ (∇ v

k + ∇ vT

k) 4.4

Where, k

µ is the molecular viscosity. For incompressible flow, Reynolds stress,t

kT ,

takes into account the effect of turbulence. According to the Boussinesq hypothesis, it

can be expressed as:

t

kT = - kρ kk vv ′′ = t

kµ (∇ vk + ∇ v

T

k) -

3

2kkkk δρ 4.5

Where, k

δ is the Kronecker delta function and t

kµ is the turbulent viscosity. For

continuous phase, turbulent viscosity has been calculated by adding shear induced

turbulent viscosity with Sato’s viscosity due to bubble induced turbulence [128].

t

cµ = SI,t

cµ + BI,t

cµ 4.6

Where shear induced turbulent viscosity for continuous phase can be expressed as,

SI,t

cµ = µρ Cc

c

2

ck

ε 4.7

Sato’s viscosity due to bubble induced turbulence can be expressed as [128],

BI,t

cµ = C sato cρ D

bv

r dα 4.8

Where, µC = 0.09 and Csato

= 0.6 are dimensionless constant, k is the turbulent kinetic

energy and ε is its dissipation rate which can be obtained by solving equations for the

standard k-ε turbulence model put forward by Launder and Spalding [129]. The

turbulent kinetic energy (k) equation can be expressed as:

∑≠=

+ερα−α+∇

σ

µ+µα⋅∇=ρα⋅∇+

∂

ρα∂ N

kl,1l

klkkkkkk

k

t

kkkkkkk

kkk KPkkvt

k 4.9

k = 1, ………, N

106

∑≠=

N

kll

klK,1

is the interfacial turbulence exchange between phases and Pk is the

production term due to shear.

The turbulence dissipation (ε) equation is,

k

2

kk2k

k

kk1k

N

kl,1l

klk

t

kkkkkkk

kkk

kC

kPCDv

t

ερα−

εα++ε∇

σ

µ+µα⋅∇=ερα⋅∇+

∂

ερα∂∑

≠=ε 4.10

Closure coefficients used in the current study are kσ =1.0, εσ =1.3, C1=1.44, C2=1.92,

µC =0.09.

∑≠=

N

kll

klD,1

represents interfacial dissipation exchange between phases. In the present

simulations turbulence level of the dispersed phase is assumed to be equal to the

continuous phase turbulence level. The turbulence interfacial interaction between the

two phases is thereby neglected.

4.3.1.2.3 Interfacial Momentum Exchange

Momentum interfacial exchange between gas and liquid was modelled by

implementing interfacial momentum source at the gas-liquid interface which includes

drag and turbulent dispersion forces [125]:

Mc = C

D8

1c

ρ iA ′′′ vr

vr + C

TD cρ

ck dα∇ = dM− 4.11

Where, c denotes continuous and d denotes the dispersed phase. The first term in

equation (4.11) represents mean contributions due to drag force and the second term

takes into account the turbulence effect. The turbulence effect is represented by a

global dispersion effect, which is proportional to the void fraction gradient (cited in

[130]).

107

The drag coefficient,D

C , is a function of the bubble Reynolds number, Reb. The

following correlation for drag coefficient,D

C , was used [125]:

( )687.0Re15.01

Re

24b

bDC += Re

b 1000≤ 4.12

=DC 0.438 Reb > 1000

Bubble Reynolds number, Reb, and can be defined as:

c

brb

DvRe

υ= 4.13

Where c

υ is the kinematic viscosity for continuous phase.

Relative velocity is defined as:

vr = v

d - v

c 4.14

The interfacial area density for bubbly flow can be expressed as [125]:

b

di

D

6A

α=′′′ 4.15

Where, Db = 0.01 mm is the bubble diameter and dα is dispersed phase volume

fraction. CTD

= 0.1 in equation (4.11) is the bubble dispersion coefficient.

4.3.1.3 BOUNDARY CONDITIONS

The following boundary conditions were applied in the computational domain for the

air-water model:

4.3.1.3.1 Inlet

All boundary conditions were chosen to match the flow condition of the experimental

study of Morsi et al. [1]. The values of the velocity components and other dependent

variables were prescribed at inlet boundaries. At inlet, mass flow boundary condition

was given for non-swirl flow case with the flow direction defined as normal to the

boundary. Velocity boundary condition was chosen to define swirl flow with a fixed

108

mass flow rate similar to the experimental data. Three velocity components ( v,uvr

and

wr

) were defined at the inlet with resultant velocity creating the swirl flow pattern at

57.5o relative to radial direction. Velocity vectors for swirl flow case at the inlet are

shown in Figure 4-3. Typical turbulence quantities at the inlet of the domain were

calculated from inlet velocities by considering turbulence intensity I = 0.05 where,

81

160−

≅′= (Re).U/uI inlet . The inlet values for dissipation rate was determined from

the Kolmogorov relation:

ε

µ≈εL

kC 23

b4

3

b 4.16

Where, εL is the length scale and bk can be calculated from the turbulence intensity

(I) at inlet by the following equation,

( )2

bb IU2

3k = 4.17

Figure 4-3: Velocity vectors (m/s) for swirl air injection at the lance tip (Q=2.67 x 10-3

m3/s, H/L=2/3, Ф =57.5o)

4.3.1.3.2 Outlet

Outlet boundary conditions are used at the domain boundaries through which the fluid

leaves. The outlet boundaries should be placed sufficiently downstream from the

regions where the flow exhibits significant changes. In this air-water simulation, outlet

was selected at the top wall of the cylindrical vessel where a fully developed flow

109

exists. Static pressure boundary condition was applied at the outlet of the

computational domain with an outlet diameter of 60 mm (see Figure 4-1).

4.3.1.3.3 Wall

The walls were assumed smooth and impermeable. For real flows, the velocity of

fluid, which is in contact with the wall, is equal to the wall velocity. This is known as

a no-slip condition. This condition is usually enforced by specifying the wall velocity

components. The turbulence model implemented in the computational domain is of the

“high Reynolds number” type which means they are not applicable in the near-wall

region. The near-wall region is characterized by large variable gradients and dominant

molecular effects. In order to model the near-wall effects (e.g., viscous damping,

kinematic blocking of the velocity fluctuations normal to the wall) the standard wall

function was employed.

For mean momentum, the wall functions based on the assumed logarithmic velocity

and temperature distributions were used [131]. For turbulent mean velocity, the

following wall function was used:

( )** yEnk

1U l= *y >11.63 4.18

Where, µ

ρ= µ

P

21

p41

*yk

Cy

Where, Py denotes the normal distance from the near wall node “P” to the wall, k =

0.4187 is Von Karman constant, E = 9.0 is an integration constant that depends on the

roughness of the wall and index “P” denotes the values at the centre point of the wall-

nearest control cell. In the momentum equation, the near wall viscosity is defined as

µ=µ*

P

*

Pw

U

y 4.19

The production term in the ε−k equation is calculated from the following equation

for the near wall node “P”,

( )P

21

P

41

wPky

kCP

µτ=ρ 4.20

Where, wτ , wall shear stress, can be calculated from,

110

( ) ( ) ( )Ptwt*

P

21

P

41

P

w UUEyln

kkC−

ρ=τ µ

4.21

( ) ( ) ( ) ( )[ ] wwPwPwPtwt nnUUUUUUrrrrrr

•−−−=− 4.22

Subscript “t” in the above equation denotes the tangential direction, parallel to the wall

surface. Diffusion flux and the value of k at the wall were considered to be zero. No

transport equation is solved for the dissipation rate. Assuming the turbulence is in

local equilibrium, the value of the dissipation was calculated from the following term,

P

23

P

43

Pky

kCµ=ε 4.23

4.3.1.4 INITIAL CONDITIONS AND FLUID PROPERTIES

The flow was started from t = 0 second in all the simulations with small initial values

assigned to k and ε, which made the initial turbulent viscosity roughly equal to the

kinematic viscosity for water. The fluid properties for air and water were taken as the

properties at NTP (T = 293.15 K, P = 1 atm).

The calculation for different injection conditions were solved as unsteady state

problem with time steps of ∆t = 0.01 second. Total time period for each run was 180

seconds which was adequate to obtain time averaged steady state results and also it

ensured numerical stability. Mean values (time averaged) of the transport properties

were calculated for the total simulation period of 180 seconds for each single run. To

get a converged solution, the approach used was to reduce the normalised sum of

absolute residuals to a value of 1.0 x 10-4

for the transport properties. The whole

simulation was carried out by using Swinburne’s Supercomputer in one cluster of 8

Intel Quad Core CPU, each with 2.3 GHZ speed.

Results obtained from several runs for this model including the grid independency test

is discussed in Chapter 5.

111

4.3.2 Zinc Fuming TSL Model

A 3D model of the Outotec TSL zinc fuming pilot plant was developed using CAD

tool. A schematic diagram of the model is shown in Figure 4-4. The modelled furnace

has a diameter of D = 0.5 m and length Z = 1.68 m. The modelled furnace was filled

up to L=0.6 m with ISF slag of composition shown by point A in Figure 4-6. A

vertical lance with an annulus of inner diameter di = 30 mm and outer diameter d

o=

42 mm was fitted at the centre of the furnace. Air was injected through the annulus of

the lance and CH4 as fuel through the central hole into the slag bath. Necessary heat in

the bath for smelting and reduction of the slag is supplied by combusting CH4 at the

lance tip.

A schematic diagram of the modelled furnace is shown on Figure 4-4. Figure 4-5

shows the generated 3D coarse grid, fine grid is not shown here for visual clarity.

Figure 4-4: Schematic diagram of the modelled furnace for Outotec TSL pilot plant

112

Figure 4-5: Generated grid of the modelled pilot plant scale TSL furnace for CFD

analysis

4.3.2.1 SLAG COMPOSITION

In this investigation, the modelled furnace was filled with ISF slag of composition

shown by point A in Figure 4-6. Minor constituents of the ISF slag were not taken into

taken account to avoid complexity. For the given temperature, partial pressure, as well

as the lime contents, the slag constituents are shown in

Table 4-1.

113

Table 4-1: Slag composition for TSL Zinc Fuming Model

Slag Constituent Initial %

ZnO 18%

SiO2 45%

FeO 27%

CaO 10%

Figure 4-6: Simplified phase relationships for the reduction step in an Outotec TSL

furnace for the components FeOx, ZnO, CaO and SiO2 generated by FACT Sage

[101] for the given temperature, partial pressure as well as the lime content.

114


The multiphase flow simulation was based on Eulerian approach where gas and liquid

phases interact with each other and there was significant exchange of momentum and

energy between phases due to robust combusting environment inside the furnace. In

addition to momentum and energy exchange between the phases, there was also mass

exchange at the gas-liquid interface due to the chemical reactions in the slag bath.

Undertaking the simulation was convoluted in a sense that the computational domain

was filled with compressible gas and incompressible slag with an abrupt change of

density, viscosity and other fluid properties at the gas-liquid interface in every

computational cell. The model was developed by using commercial CFD package

AVL FIRE 2009.2 (AVL, Graz, Austria) coupled with a number of user defined

subroutines (UDF), as the available graphical user interface (GUI) of the commercial

CFD package used does not allow combustion in multiphase flow problems. The basic

model features and the subroutines developed in the model are mentioned below,

1. The 3-D governing equations of momentum, continuity, enthalpy and turbulent

flows were solved in unsteady state for an unstructured grid system.

2. Standard k-ε turbulence model [129] was used for the turbulence modelling.

3. A cell centred finite volume approach was used to discretise the governing

equations and the resulting discretised equations were solved iteratively using

segregated approach.

4. For continuity equation, the values of the variables at cell faces were calculated

by employing central differencing approximation scheme with second order

accuracy, which uses a linear interpolation to compute the cell face values. For

other equations such as momentum, turbulent, and energy equations, a first-

order accurate upwind scheme was used.

5. Semi Implicit Method for Pressure Linked Equations (SIMPLE) algorithm

[127] were used to couple the pressure and velocity. In this algorithm, the

velocity (u, v and w) and pressure (P) fields are solved separately and coupling

between these field variables are achieved via velocity and pressure

corrections.

115

6. The subroutines developed in this model are written in FORTRAN

programming language and Intel FORTRAN compiler (version 10.1.019) was

used to compile and couple it with the CFD package. The subroutines include,

a. Subroutine for submerged CH4 combustion and species transport

b. Subroutine for interfacial enthalpy exchange

c. Subroutine for interfacial mass exchange

d. Subroutine for chemical reactions in the slag bath


Basic Eulerian equations, describing multiphase combusting system are given by the

conservation equations for continuity, momentum, energy and species transport. Other

than the basic conservation equations, interfacial exchange terms for mass, momentum

and energy at the gas-liquid interface were also modelled. For three-dimensional fluid

flow, conservation equations for continuity and momentum have already been

described in the previous section (4.3.1.2). In the continuity equation (4.1), the

interfacial mass exchange between phases k and l ( klΓ ) were considered.

In the momentum equation, Sato’s constant (equation 4.7) was reduced for the zinc

fuming TSL model as Csato

= 0.1. For the high temperature combusting system, the

dispersed phase bubble diameter (equation 4.13) was also adjusted as, Db = 0.01 m.

The bubble dispersion coefficient used in equation (4.10) was, CTD

= 0.01.

In addition to the interfacial mass and energy exchange, details of the enthalpy and

species transport equations solved for the multiphase TSL submerged combusting

system are described below.

4.3.2.3.1 Enthalpy conservation

Total enthalpy conservation equation solved for the model can be expressed as,

∑∑≠=≠=

Γ++

∂

∂α+⋅τα⋅∇+′′′α++α⋅∇=ρα⋅∇+

∂

ρα∂

N

kl,1l

klk

N

kl,1l

kl

kkkkkk

t

kkkkkkkkkk

hH

t

pvq)qq(hv

t

h

4.24

116

where kq ′′′ is the enthalpy volumetric source, heat flux, kq , is defined as,

k

k,p

kk h

c

kq ∇= 4.25

where kk is the phase k thermal conductivity, kh is the phase k enthalpy. Turbulent

heat flux, t

kq , equals:

k

T

t

kt

k hq ∇σ

µ= 4.26

Where, t

kµ is the turbulent viscosity defined in equation (4.26) and the turbulent

Prandtl number is adjusted to Tσ =0.5 for better turbulent heat transfer [132].

klΓ and klH in equation (4.24) represents mass and energy interfacial exchange

between phases k and l.

4.3.2.3.2 Interfacial Energy Exchange

Heat generated due to the CH4 combustion at the lance tip was transferred to the

molten slag phase by considering interfacial energy exchange at the gas-liquid

interface. Heat transfer between the two phases was modelled by using the Ranz-

Marshall enthalpy exchange model [133] as follows:

( ) dcdi

b

cc HTTA*Nu

D

kH −=−′′′= 4.27

where, c

k is the thermal conductivity of the molten slag phase, b

D is the bubble

diameter and i

A ′′′ is the interfacial area density defined in equation (4.15).

Nu is the Nusselt number and can be expressed as [133]:

3

1

2

1

6002 PrRe..Nu b+= 4.28

where, bRe is the local bubble Reynolds number, and Pr is the Prandtl number.

117

4.3.2.3.3 Combustion Modelling

Six different species (CH4, O2, N2, CO2, CO, H2O) were considered for gas phase

reaction during the combustion process. By considering TSL pilot plant practice data,

(assuming CO/CO2 = 1), the following equation for CH4 combustion was considered

at the lance tip to supply the necessary heat for ZnO reduction in the slag bath.

( ) 222224 76.3782276.374 NOHCOCONOCH ×+++→++ 4.29

A species transport equation for every species was solved for gas phase reaction,

which can be expressed as:

( ) ( ) kk

t

tm,kkk Sy

ScD.yv.y

t+α

∇

µ+ρ∇=ρ∇α+ρ

∂

∂α

r gask....1k = 4.30

Where, k

y represents the mass fraction of an individual chemical species k, ρ is the

density of gas phase. gask is the total number of chemical species and kS is the mass

source. mk

D,

[m2/s] is the diffusion coefficient for each species k in the mixture and

70.Sct = is the turbulent Schmidt number. Species source terms, kS , in equation

(4.30) was determined by the well-established Eddy Break-up combustion model

[134].

Turbulence controlled combustion model, Eddy Break-up (EBU), is a popular and

efficient model in combustion calculations, which was firstly proposed by Spalding

[135] and modified later by Magnussen and Hjertager [134]. The mean reaction rate

can be written according to Magnussen and Hjertager [134],

+ρ

τ=ρ

⋅

S1

yC,

S

y,ymin

Cr

prprOxfu

R

fufu

4.31

The rate of consumption of fuel is specified as a function of local flow properties, thus

it is dependent upon the turbulent time scale ( Rτ ), which is defined as a ratio of

118

turbulent kinetic energy (K) to its dissipation rate (ε ). The first two terms of the

minimum value of operator simply check if fuel or oxygen is present in limiting

quantity, and the third term is used for a reaction possibility. Cfu and Cpr are empirical

coefficients, and the exact values for these coefficients are dependent on the fuel and

the detailed structure of the turbulent flow field. In the present simulation, Cfu and Cpr

were kept 3.0 and 0.5 respectively.

4.3.2.3.4 Chemical Reactions in the Slag Bath

Other than the combustion reaction in the gas phase defined by equation (4.29), a

number of chemical reactions in the slag bath were considered with the following

scalar transport equation (4.32) solved for every scalar. Scalars considered for slag

phase reaction are ZnO, FeO, SiO2, CaO, C and Zn which fumes off from the slag

bath.

kikikki

t

tm,kkikkkkikk S

ScD.v.

t+φ∇α

φ∇

µ+ρ∇=φρα∇+φρα

∂

∂ 4.32

where kα and kρ is the volume fraction and density of phase k respectively, kiφ is the

value of scalar i of phase k, ki

S is the source term for different scalars. The chemical

reactions in the slag bath are based on the kinetics equations developed by Richards

and Brimacombe [20]. In the mathematical formulations by Richards and Brimacombe

[20], rate of transport of ZnO and ferric iron from the bulk slag to the slag/bubble

interface was expressed by the empirical equation,

( )*

i

sl

iibi CCkAn −= 4.33

Where, bA is the surface area of the secondary bubble/char particle (m2), ik is the

mass transfer coefficient of species i. sl

iC and *

iC are the concentrations of the species

i at the bulk slag and slag/bubble interfaces respectively.

The present simulation takes into account the rate of change of concentrations of every

scalar with respect to time, their convection and diffusion in the slag bath through

119

Equation 4.32. In addition, effect of turbulence in the chemical reactions was also

taken into considerations by applying the effect of turbulent eddies and its dissipation

rate into the chemical reactions which controls the mass transfer of the slag scalars

from the bulk slag to the slag-gas interface. This was done through inclusion of

turbulent time scale ( )kε in the transport equation (Equation 4.32), where k is the

turbulent kinetic energy and ε is its dissipation rate. Diffusion coefficients used in

Equation 4.32 for ZnO and FeO at 1473 K was 2.3x10-10

m2s

-1 , taken from the

calculations carried out by Richards and Brimacombe [20]. However, this molecular

diffusion is quite negligible as compared to turbulent diffusion.

In the simulation, carbon is added in the slag bath as a reductant source. The reaction

between carbon and CO2 gas (Boudouard reaction) described in equation (2.6) has

been considered according to rate kinetics given by Skinner and Smoot [136] for

pulverized bituminous coal char (70 pct through 200 mesh). The same rate kinetics

was also used by Richards et al. [20] for their mathematical modelling studies of slag

fuming. The rate equation follows first order kinetics with respect to solid carbon and

in CO2 partial pressure.

( )20 COaB PRTEexpAr ⋅−= 4.34

Where,

( ) 116

0 s.kgkPa1013.3A −−=

K23600REa =

The model was developed based on gas-liquid Eulerian multiphase flow approach,

hence it considers only two phases – gas and liquid slag. Zn vapour in the gas phase

was considered as a gas phase scalar which transforms from the liquid phase scalar

(ZnO) through the mass interfacial exchange between gas and liquid phases. The coal

char was treated as one of the scalar of the slag phase. The coal char was not treated as

a uniformly distributed dissolved species. A full governing transport equation was

solved to obtain the variable distribution of coal char in the slag. The hydrodynamic

effect of coal particle size was not considered in this study. However, effect of coal

particle size on the chemical reaction was taken into account by using the appropriate

Boudouard reaction rate (equation 4.34) for the coal particle size mentioned above. It

120

was also assumed that only fixed carbon of the coal takes part in the reduction

reaction. Similar assumptions have been used by previous researchers where they

assumed that only fixed carbon in the coal takes part in the reduction reaction [2].

Hence, no evaporation and devolatilization models are considered in the calculation.

4.3.2.3.5 Interfacial Mass Exchange

It is important to emphasize that the interfacial mass exchange occurs at the gas-liquid

interface due to the chemical reaction in the slag phase. The simulation considers

appropriate mass balance in the gas and liquid phases. Liquid ZnO from the slag phase

is being transformed to metallic Zn vapour. Phase transformation between molten slag

and gas phase was considered by the following equation [125],

dcellc

n

d

n

cmxc VC ΓρααΓ −=⋅= 21 4.35

Where, c and d denotes the continuous and dispersed phase, mxC is the rate of phase

transformation, which is defined by the rate of zinc oxide reduction, determined from

the convection, diffusion, turbulence and chemical kinetics. cρ and α is the density

and volume fraction respectively and volume fraction exponent used in the model are

n1 = 1 and n2 = 0.


The boundary conditions used in the pilot plant scale zinc fuming TSL furnace model

are summarized below:

4.3.2.4.1 Inlet

Unlike the air-water model, a combustion chamber is included at the lance tip (see

Figure 4-4 and Figure 4-5) where fuel mixes with air and initiates the combustion

process. All boundary conditions were chosen to match the flow condition of the pilot

plant trials of the Outotec TSL pilot plant. At the lance tip, which was the inlet of the

computational domain, the mass flow boundary condition was used. Details of the

121

mass flow rate at the inlet are provided in Table 4-. At the inlet, three different species

were injected: O2, and N2 through the annulus ring and CH4 through the central hole.

4.3.2.4.2 Outlet

The outlet boundary was selected at sufficiently downstream from the regions of the

slag bath where the flow exhibits significant changes. Hence, a gradient zero boundary

condition was applied at the outlet of the computational domain with an outlet

diameter of 160 mm (see Figure 4-4).

4.3.2.4.3 Wall

A no-slip condition was applied at all walls inside the modelled furnace which

includes furnace inside wall including side wall, top and bottom wall, outside wall of

the cylindrical lance. The wall temperature was set to 1500 K according to the data

obtained from pilot plant study. The CFD model was set up to allow heat flux across

the wall to maintain the wall temperature at 1500 K. Besides, the walls were treated

with Compound Wall Treatment (CWT) proposed by Popovac and Hanjalic [137] to

take care of the near wall effects like viscous damping, kinematic blocking of the

velocity fluctuations normal to the wall.

The Compound Wall Treatment (CWT) ensures a gradual change between viscous

sub-layer formulations and the wall functions. This wall treatment provides the

standard wall function for the large values of y+ as well as the integration of equations

up to the wall (ItW) for the very small values of y+. The CWT model is based on the

description of the mean velocity and temperature profiles proposed by Kader [138],

thus,

ΓΓ 11 −+−++ += e)Eyln(k

eyU 4.36

Where, +

+

+=

yP

)yP(.

r

r

3

4

51

010Γ

Where, k = 0.4187 is Von Karman constant, E = 9.0 is an integration constant that

depends on the roughness of the wall. The production of turbulence kinetic energy near

122

the wall is modified accordingly as low-Re model for small values of y+ and standard

wall function (SWT) for high values of y+.


The usual case of zinc fuming process involves heating up the furnace by ignition,

charging of slag, melting the charge and adding reducing agent before fuming starts.

One complete batch fuming cycle usually takes around 120 to 180 minutes, depending

on the process. The present simulation avoids some of the complexities by initializing

the simulation at high temperature. The simulation starts with a charged furnace of

460 kg molten slag at 1500 K (1227o

C) temperatures and initiation of combustion at

the lance tip to supply the heat necessary for the zinc reduction reaction. Air and fuel

flow rate at the lance tip were provided from real flow rate data from a pilot plant

scale trail. Each run of the computation simulates 0.5 minute of a 10 minute interval of

fuming cycle, which gives a total of 4.5 minutes simulation in a 90 minute industrial

fuming cycle. The timing of simulation is linked to the computational time limitations.

Higher computational power can lead to a longer time simulation. The computation

was carried out on an Intel Xeon Quad Core Z 400 machine with 8 GB RAM and each

processor has a speed of 2.67 GHz. The simulation was run on MPI (Message Passing

Interface) mode [131] which splits the computational domain into four sections, each

of which was computed by a separate processor. Every single run of the simulation of

30 seconds took approximately 20 days.

The flow simulation was started with small initial values assigned to turbulent kinetic

energy (k) and its dissipation rate (ε), which made the initial turbulent viscosity

roughly equal to the kinematic viscosity for molten slag. For the gas phase reaction

given in Equation 4.29, fluid and thermal properties of the different species involved

in the solution process (density, specific heat, dynamic viscosity, molecular weight,

thermal conductivity, diffusion coefficient) have been considered from the internal

thermodynamic database of AVL FIRE [139]. The fluid and thermal properties for

molten slag phase are listed in Table 4-2.

123

Table 4-2: Fluid and thermal properties of molten slag phase for TSL model

Density (kg/m3) [20] 3900

Specific heat (J/kg K) [20] 870

Dynamic viscosity (N s/m2) [20] 0.5

Thermal conductivity (W/m K) [20] 1.5

Turbulent Prandtl number [132] 0.5

Reference pressure (Pa) 100000

Reference temperature 1500 K (1227 oC)

Table 4-3: Injection conditions (CFD and Experimental)

Experimental

conditions (CZF5)

(Waladan et al. [2]

CFD

Calculations

Fuel type Fine Coal CH4

Reductant type Fine Coal Fine Coal

Combustion air (kg/s) 0.06 0.05

Fuel rate (kg/s) 0.035 0.0035

Reductant rate (kg/s) 0.035

Initial zinc content in the

slag (wt %)

10.7 18.0



124

4.3.3 Conventional Tuyere blow model

In this stage of the present study, the developed model for the zinc fuming TSL

furnace was applied to a thin slice model of the conventional tuyere blow furnace.

Submerged combustion model for CH4 was modified for submerged coal combustion

in this investigation. Details of the model features are described below.

4.3.3.1 MODEL GEOMETRY AND COMPUTATIONAL MESH

A two tuyere thin slice model of the conventional tuyere blow slag fuming furnace of

company D mentioned by Richards et al. [21] as shown in Figure 4-7 was developed

using CAD. As mentioned by Richards et al. [21], the slag fuming furnace of company

D has a length of 4.57 m and width 2.44 m (4.57 x 2.44 m2), containing 30 tuyeres

with 56 mm ID for each tuyere. Owing to the computational time limitations, present

study dealt with a thin slice model with two opposing set of tuyeres. The principle aim

was to investigate tuyere tip combustion dynamics, coal utilization behaviour and zinc

fuming kinetics inside the bath. Keeping the width same as the original furnace

dimension (2.44 m), a slice of 0.3 m length was considered along the longitudinal

direction (along Y coordinate in Figure 4-7). The walls in the X – Z plane has been

considered as the symmetry wall. Two opposing set of tuyere were placed on both side

wall of the modelled furnace, the centre of which were placed at 0.1 m above the

bottom wall and 0.15 m along Y coordinate (Y = 0.15m, Z = 0.1 m). Both the tuyere

tips were extruded 0.1m from both the side walls (in Y – Z plane). The modelled

furnace was filled up to L=1.0 m with ISF slag. Figure 4-7 represents the schematic

outline of the developed model. Air as oxidant and coal as fuel was injected through

the tuyeres into the molten slag bath. Necessary heat in the bath for smelting and

reduction of the slag is supplied by combusting coal at the tuyere tip. A comparison of

the simulation and experimental conditions are summarized in Table 4-4 for more

clarity.

125

Figure 4-7: Schematic view of the modelled thin slice rectangular tuyere blow furnace

(Isometric Layout)

Table 4-4: Comparisons of the simulation and plant data

Parameter

Real Furnace of

Company D (Richards

et al. [21]) – Run 1

Present CFD

Simulation

Length (m) 4.57 0.3

Width (m) 2.44 2.44

No. of tuyeres 30 2

Tuyere ID, do (m) 0.056 0.056

Bath weight (tonnes) 45 2.855

Bath height (m) 1 1

Initial zinc content % 11.7 11.7

126

Coal

composition

FC % 60 60

Volatile

content %

20 20

Ash % 18 18

Coal rate through each

tuyere (kg/s)

0.032 0.032

Air flow rate through

each tuyere (kg/s)

0.158 0.158

(a) (b)

Figure 4-8: (a) Generated surface mesh, (b) Volume mesh for CFD analysis (course

grid)

127

4.3.3.2 SLAG COMPOSITION

In this investigation, the modelled furnace was filled with molten slag of composition

shown in Table 4-5. Minor constituents of the ISF slag were not taken into taken

account to avoid complexity. As presented by Richards et al. [21] (Figure 5, Cycle

D1), initial zinc, silica and lime contents are 11.7%, 26%, and 15.3% respectively.

Though, effect of ferric iron is likely to play some role in overall fuming efficiency,

current CFD investigation does not consider the effect of ferric iron, as an attempt to

avoid complexity in chemical reactions. Hence, ferric iron level was considered as

zero. The proportion of minor elements are also not mentioned by Richards et al. [21],

hence, the remaining of the slag composition was considered as FeO.

Table 4-5: Initial Slag Composition for Tuyere blow model

Slag Constituent Initial %

ZnO 11.7

SiO2 26

FeO 47

CaO 15.3


The multiphase flow simulation is based on the principle of interpenetrating continua,

i.e. Euler – Euler approach. In this approach, each phase is governed by the Navier-

Stokes equations. The existing phases share the same volume and penetrate each in

space and exchange mass, momentum and energy. Each phase is described by its

distinctive physical properties and has its own velocity, pressure, concentration and

temperature field. The model was developed by using commercial CFD package AVL

FIRE 2009.2 (AVL, Graz, Austria) coupled with a number of user defined subroutines

(UDF) for submerged coal combustion and gas phase species transport, chemical

reaction in the slag bath and interfacial mass and energy exchange (as described in

Section 4.3.2.2). The notable model features are kept same as the zinc fuming TSL

model (described in Section 4.3.2.2)

128


The governing transport equations describing Eulerian multiphase fluid flow

(continuity, momentum, energy and species transport) were solved in this model. In

addition, mass, momentum and energy interfacial exchange at the gas-liquid interface

were also considered, as described in the zinc fuming TSL model (Section 4.3.2.3).

Interfacial exchange terms (mass, momentum and energy) at the gas-liquid interface

were modelled by applying appropriate interfacial exchange models. Details of the

interfacial mass, momentum and energy exchange models are described in the zinc

fuming TSL CFD modelling work. Coefficients used in the interfacial exchange terms

are as follows:

For shear induced turbulence viscosity, µC = 0.09

Sato’s coefficient for bubble induced turbulence, Csato

= 0.1

Bubble diameter for interfacial momentum and energy exchange, Db = 0.01 m

The bubble dispersion coefficient, CTD

= 0.01

In this part of the research, the gaseous phase CH4 combustion model was modified

for coal combustion. The coal was injected through tuyeres along with air. Details of

the coal combustion modelling are discussed in the following sections.

4.3.3.4.1 Coal combustion

The numerical simulation of raw coal combustion is considered as a complex process

compared with the combustion of other fossil fuel sources because it includes several

complicated physical and chemical processes, which have not been completely

understood. The basic steps of coal combustion are thermal decomposition and the

consequent burnout of the volatile matter and the oxidation of char to leave the

incombustible ash as a final undesirable part. The physical properties (proximate and

ultimate analysis) of coal particle used in the present study are summarized in Table 4-

4. One of the assumptions of the present CFD investigation is that the injected coal

129

through the tuyeres has been considered as a continuum phase rather than discrete

particulate phase. The aim was to avoid complexity, as solid coal particle would

incorporate the third phase other than the gas and liquid, which would bring the

complexity of interfacial exchange terms. The injected coal was treated as one of the

scalars of the slag phase. The coal was not treated as a uniformly distributed dissolved

species. A full governing transport equation was solved to obtain the variable

distribution of coal char in the slag.

Scalar transport equation solved for the injected coal can be written as,

kkkk

t

tm,kkkkkkkk S

ScD.v.

t+φ∇α

φ∇


∂

∂ 4.37

where kα and kρ is the volume fraction and density of phase k respectively, kφ is the

scalar value (injected coal) of phase k, kS is the source term for injected coal, which

was determined through the coal combustion model as described below.

In the third stage of this research, coal combustion was incorporated by three complex

reaction processes. The combustion of dry coal particles mainly includes two complex

reaction processes. The first reaction process is the devolatilization of the dry coal

particle, which includes the reaction of the released hydrocarbon fuel (volatile) which

combusts with the oxygen to produce essentially the water vapor (H2O) and carbon

dioxide (CO2) as final products. The second reaction process is the oxidation of the

residual char that is slower than the devolatilization process. In this study, injected coal

through the tuyeres was considered to participate both in the combustion and in the

reduction reactions within the bath. No water evaporation model was incorporated in

the model as the injected coal was assumed to have negligible moisture content. Total

coal reaction mechanism is shown in the following flow chart:

130

Figure 4-9: Coal combustion process flow chart

4.3.3.4.2 Devolatilization

In the present simulation, the single reaction model of Badzioch and Hawksley [140]

was applied to simulate the coal pyrolysis. The coal, considered in this model, was

assumed to have fixed fraction of volatile matters, char and ash, and its reaction

depends on the local temperature experience, as well as its temperature history. The

rate of production of the volatile is given by the first order reaction as follows:

( )VVKdt

dVfv −= 4.38

Where, V is the product of volatiles that have already released from unit mass of

pulverized coal at time t, fV is the ultimate product of volatiles and vK is the rate

constant given by the Arrhenius form as,

−

p

vv RT

EexpA , where R = 8314 J kmol

-1

K-1

is the universal gas constant, pT is the temperature of coal particle, vA and vE are

the pre-exponential factor and the activation energy constants, respectively, that are

131

determined experimentally for the particular coal. These factors are usually obtained

from the proximate analysis of the coal.

The good selection of the kinetic factors of Arrhenius expression can be considered as

a key issue towards the appropriate prediction of devolatilization rate, particularly in

the combustion zone [140, 141]. Therefore, the devolatilization kinetic factors of the

coal used were chosen to be 2.0x104 (s

-1) and 4.94x10

7 (J.kmol

-1) for the pre-

exponential factor and for the activation factor [142], respectively, in order to

overcome any difficulties during setting up the simulation cases and to get optimum

agreement with the available physical data.

4.3.3.4.3 Gas Phase Combustion

Species source term for CH4 was updated continuously, which is generated inside the

bath as a result of devolatilization process of coal. Detail of the coal devolatilization

process is described in the previous section (Section 4.3.3.4.2). Six different species

(CH4, O2, N2, CO2, CO, H2O) was considered for gas phase reaction during the

combustion process. The following equation for CH4 combustion was considered in

the slag bath,

( ) 222224 N76.37OH8CO2CO2N76.3O7CH4 ×+++→++ 4.39

A species transport equation for every species was solved for gas phase reaction,

which can be expressed as:

( ) ( ) kk

t

tm,kkk Sy

ScD.yv.y

t+α

∇

µ+ρ∇=ρ∇α+ρ

∂

∂α

r gask....1k = 4.40

Where, k

y represents the mass fraction of an individual chemical species k, ρ is the

density of gas phase. gask is the total number of chemical species and kS is the mass

source. mk

D,


70.Sct = is the turbulent Schmidt number.

132

Where, mk

D,


70.Sct = is the turbulent Schmidt number. Species source term, ky

S , in equation

(4.40) were determined by the well-established Eddy Break-up combustion model

[134], as described in Section 4.3.2.3.3. Empirical coefficients Cfu and Cpr for this

investigation were considered as 3.0 and 0.5 respectively.

As shown in the flow chart (Figure 4-9), the remaining char takes part in both

combustion and reduction reaction of the zinc oxide within the bath. A portion of the

remaining char also bypasses the bath un-combusted and un-reacted.

4.3.3.4.4 Char oxidation

The char oxidation rate is an important process in pulverized coal combustion. After

the devolatilization, the remaining char in the coal particle reacts slowly with the

surrounding gases. Therefore, the burnout time of the pulverized coal can be

determined in the furnace by this process [143].

In this study, the char combustion is modelled by a global reaction of order unity

(global power-law), which was proposed by Field et al. [144]. The diffusion rate of

oxygen is calculated by ( )sgd PPK − , where gP is the partial pressure of oxygen in the

bulk phase of the furnace (far from particles boundary layer), sP is the oxygen partial

pressure at the external surface of the particle and dK is expressed by the following

equation [145],

P

PTT

RK Agp

p

d

75.07

2

10*53.2

+=

−

4.41

Where: pR is the radius of the particle, pT is the temperature of the particle, gT is the

gas temperature in the far field, and AP and P are the atmospheric and local pressure

respectively.

133

The rate of char oxidation per unit area of the particle surface is described by sc PK .

The kinetic rate is expressed by the following Arrhenius expression,

−=

p

ccc T

EAK exp 4.42

Where, cA is the pre-exponential factor and cE is the activation energy. Due to the

lack of measured char reactivity data, the recommended values by Wall et al. [146] are

used for cA and cE in this simulation, which are 497 (kg.m-2

.s-1

.atm-1

) and 8540 K

respectively. Finally, the rate of the overall char reaction of a particle can also be

written as followsA

pg

cdP

PRP

KK

2

114

1π

+−−

and can be controlled by the smaller

rates of dK and cK .

4.3.3.4.5 Chemical Reactions in the Slag Bath

Some portion of the remaining char reduces the zinc oxide present within the bath.

Details of the chemical reaction modelling has been described Section 4.3.2.3.4. For

the scalars that involved chemical reactions in the slag bath, the following scalar

transport equation (4.43) was solved for every scalar. Scalars considered for slag

phase reaction are ZnO, FeO, SiO2, CaO, C and Zn which fumes off from the slag

bath.

kikikki

t

tm,kkikkkkikk S

ScD.v.

t+φ∇α

φ∇


∂

∂ 4.43

where kα and kρ is the volume fraction and density of phase k respectively, kiφ is the

value of scalar i of phase k, ki

S is the source term for different scalars.

134


All boundary conditions were chosen to match the flow condition of the plant data

(Company D) given by Richards et al. [21]. The boundary conditions used in the

model are summarized below:

4.3.3.5.1 Inlet

At the tuyere tip, which was the inlet of the computational domain, the velocity

boundary condition was used. Details of the flow rate at the inlet are provided in Table

4-4. At the inlet, both the gas and liquid phase were injected. The gas phase contains

two different species: O2, and N2 and the liquid phase contain coal only.

The plant data presented by Richards et al. [21], shows for company D1, total blast

was 4.0 m3/s and the blast temperature was 460 – 520

o C, which gives the average

blast temperature of 490o C. At each tuyere, volume flow rate of air at STP would be

0.133 m3/s and mass flow rate of 0.158 kg/s. With that specified volume flow rate and

blast temperature, inlet jet velocity was calculated as 139.6 m/s. Hence, at inlet, the

same velocity and blast temperature were kept.

4.3.3.5.2 Outlet

Outlet was defined at the top wall of the computational domain as shown in Figure

4-7. Static pressure boundary condition was applied at the outlet of the computational

domain.

4.3.3.5.3 Wall

All walls inside the modelled furnace, which includes furnace side wall, top and

bottom wall, were applied a no-slip condition. The temperature at the walls was

assumed as 1500 K (1227 oC). As mentioned before (Section 4.3.2.4.3), the CFD

model was set up to allow heat flux across the wall to maintain the wall temperature at

1500 K. Besides, the walls were treated with Compound Wall Treatment (CWT) to

take care of the near wall effects like viscous damping, kinematic blocking of the

velocity fluctuations normal to the wall. Detail of the Compound Wall Treatment

(CWT) has been described in the previous section (Section 4.3.2.4.3).

135

4.3.3.5.4 Symmetry

In the present simulation, it was assumed that symmetric state exists on the two

opposing sides of the furnace as shown by symmetry plane in Figure 4-7. This

treatment of the boundary condition corresponds to the physical assumption that, on

the two sides of boundary, the same physical processes exist. The variable values at the

same distance from the boundary at the two sides are the same. The function of such a

boundary is that of a mirror that can reflect all the fluctuations generated by the

simulation region. When the flow is bounded by a plane of symmetry, the velocity

component normal to this plane is set equal to zero, yielding zero convective flux. In

addition, the normal derivatives of all the remaining variables are set to zero which

implies zero diffusion fluxes.


The conventional zinc fuming process usually comprised of several steps. It begins

with heating up the furnace by ignition, followed by charging of slag, melting the

charge and adding reducing agent before fuming starts. One complete batch fuming

cycle usually takes around 120 to 180 minutes, depending on the process. The present

simulation avoids some of the complexities by initializing the simulation at high

temperature. The simulation starts with a charged furnace of 2855 kg molten slag at

1500 K (1227 oC) temperature and initiation of combustion at the tuyere tip to supply

the heat necessary for the zinc reduction reaction. Air and coal flow rate at the tuyere

tip were provided from plant data as mentioned in Table 4-. Each run of the

computation simulates 1.0 minute of a 10 minute interval of fuming cycle.

Computational time limitation restricts the longer simulation time. The computation

was carried out with a fixed time step of 5 x 10-4

second on an Intel Xeon Quad Core

Z 400 machine with 8 GB RAM and each processor has a speed of 2.67 GHz. The

simulation was run on MPI (Message Passing Interface) mode [131] which splits the

computational domain into four sections, each of which was computed by a separate

processor. Every single run of the simulation of 60 seconds took approximately 15

days.

136

For the gas phase reactions, fluid and thermal properties of the different species

involved in the solution process (density, specific heat, dynamic viscosity, molecular

weight, thermal conductivity, diffusion coefficient) has been considered from the

internal thermodynamic database of AVL FIRE [139]. The fluid and thermal

properties for molten slag phase are listed in Table 4-66.

Table 4-6: Fluid and thermal properties of molten slag phase for Tuyere blow model

Density (kg/m3) [20] 3900

Specific heat (J/kg K) [20] 870

Dynamic viscosity (N s/m2) [20] 0.5

Thermal conductivity (W/m K)

[20]

1.5

Turbulent Prandtl number [132] 0.5

Reference pressure (Pa) 100000

Reference temperature 1500 K (1227 oC)



137

Chapter 5

138

5 Cold Flow CFD Model of the TSL Gas Injection Process

This chapter will focus on the detail hydrodynamic parameters of the cold flow CFD

model of top submerged lance (TSL) gas injection process. Effect of the different

injection parameters (gas flow rate, lance submergence level, swirl intensity) and fluid

properties (liquid density and viscosity) on the bath mixing will be discussed in the

subsequent sections. Details of the modelling techniques are discussed on Chapter 4

(Section 4.3.1).

The aim of the research presented in this chapter is to investigate the physical

behaviour of the top submerged gas injection system and to predict the effect of swirl,

lance submergence level and air injection rate into the liquid bath using the CFD

modelling technique. The present study is a numerical simulation of the cold model

experimental work of Morsi et al.[1]. In the present study, water was used as the

modelling fluid and air was used as the injected gas as it was the basis for the previous

experimental model of Morsi et al.[1].

Mixing within the bath was considered based on both micro-mixing (turbulence

mixing) and macro-mixing (volume exchange effectiveness) approach. A new

approach (volume exchange effectiveness) to express the degree of mixing in the

liquid bath in metallurgical process simulation has been proposed in the current study.

In addition, a modified semi-empirical equation is proposed to measure the vertical

depth of penetration of the air jet injected through the annulus of the lance into the

liquid bath based on the previous experimental study of Iguchi et al. [51].

5.1 Test of Grid Independence

Accuracy of every CFD analysis depends largely on the type of grid used. Hence, grid

generation needs special attention of the investigators. Generally, finer grid gives more

accurate results, but eventually it leads to higher computational expense. Therefore, an

optimum grid resolution is necessary for efficient CFD analysis. The purpose of grid

independency test is to determine the minimum grid resolution required to generate a

solution that is independent of the grid used.

139

In this air-water model, four grid resolutions were tested for grid independency test,

mainly increasing the number of cells in the water bath. Starting with a coarse grid,

number of cells was increased in the region of interest until the solution from each grid

was unchanged for successive grid refinements. All the cells in the calculation domain

were polyhedral with a large number of hexahedral cells. As the computational

domain consisted of hybrid unstructured meshes in curvilinear non-orthogonal

coordinate system with Cartesian base vectors and refined regions in some locations,

mentioning number of cells in each direction is complicated. The computational grid

(213344 cells) used in the present study is too dense for visual presentation. A cross

sectional view of the coarse computational grid in X-Z plane is shown in Figure 4-2,

which consists of total 89492 cells in 360o domain. Meshing procedure was done by

Fame Advanced Hybrid meshing technique [147]. Table 5-1 represents an overview of

the grid information studied in the grid independency test.

Table 5-1: Overview of computational grids

Name Grid Density No of

Computational cells

Grid 1 Coarse 89492

Gird 2 Medium 154072

Grid 3 Fine 213344

Grid 4 Very Fine 361024

Figure 5-1 shows the mean tangential velocity distribution (V) on X-Z plane. The

radial distance (r) is normalised by the radius of the cylinder (R=115mm) and the axial

distance z is normalised by the length of the cylinder (Z=560mm). Both Grid 3 and

Grid 4 gave a very close prediction compared with the experimental results. The

difference in predictions between Grid 3 and Grid 4 was small enough (around 5%) to

suggest that any further grid refinement would not yield a substantially different

profile in that plane. Hence, it was decided that the fine grid resolution (Grid 3) of

213344 cells was sufficient to obtain grid independent results.

140

Figure 5-1: Mean tangential velocity (m/s) distribution for different grid

configurations

(Q=2.67 x 10-3

m3/s, H/L=2/3, Ф =0

o) for water model simulation

Overview of the simulation and experimental conditions are mentioned in Table 5-2.

The calculation for different simulation condition as mentioned in Table 5-2 were

solved as unsteady state problem with time steps of ∆t = 0.01 second. Total time

period for each run was 180 seconds which was adequate to obtain time averaged

steady state results and also it ensured numerical stability.

Table 5-2: Overview of the simulation and experimental conditions

Parameters Experimental

Condition

(Morsi et al. [1])

Present Simulation

Air injection rate

Q (Nm3/s)

Fraction of lance

submergence H/ L

Swirl Intensity

Ф (o)

1.50 x 10-3

2.67 x 10-3

1/3, 2/3

0o, 57.5

o

1.00 x 10-3

1.50 x 10-3

2.00 x 10-3

2.67 x 10-3

3.50 x 10-3

4.00 x 10-3

1/6, 1/3, 2/3

0o, 57.5

o

141

5.2 Results and Discussion

The results discussed here are presented in terms of the three major hydrodynamic

parameters: swirl intensity, gas injection rate and lance submergence level. The

simulation condition and corresponding figures that are described in this paper are

summarised in Table 5-3, referring to air-water system unless otherwise stated.

Table 5-3: Simulation conditions and corresponding figures

Air injection rate

Q (Nm3/s)

Fraction of lance

submergence H/ L

Swirl Intensity

Ф (o)

Figure number

2.67 x 10-3

2.67 x 10-3

2.67 x 10-3

2.67 x 10-3

1.50 x 10-3

1.50 x 10-3

1/3

2/3

1/3

2/3

1/3

1/3

0

0

57.5

57.5

0

57.5

4(d), 5(d), 6(d), 7(d), 16(a)

3, 4(b), 5(b), 6(b), 7(b),8,

12(a), 13(a)

4(c), 5(c), 6(c), 7(c), 16(b)

4(a), 5(a), 6(a), 7(a), 12(b),

13(b)

4(f)

4(e)

5.2.1 Effect of Swirl Intensity

The effect of swirl intensity on axial velocity is shown in Figure 5-2. The figure shows

that the instantaneous axial velocity (w) contours for swirl and non-swirl flow were in

the range of -0.3 to 0.4 m/s. Time instances are mentioned in the corresponding

figures at which contour plots are taken. The colour bar represents the velocity

magnitudes (m/s). The sign in the colour bar indicates the direction of the velocity

(either downward or upward). The axial velocity near the lance shows an upward trend

due to the buoyant force of the rising air bubbles. No significant change in axial

velocity was observed due to swirl. From Figure 4, swirl injection seems to have

larger penetration envelope in the case of 2/3 lance depth, whereas the reverse is true

142

for 1/3 lance depth. This observation can be attributed to the transient nature, sloshing,

and splashing phenomena in the water bath. By comparing Figure 5-2 (a) and (b), it is

clear that there is only a little increase in the axial velocity at the bottom of the tank

and near the top surface of the bath. This trend is also quite clear from Figure 5-2 (c)

and (d). There is some change in axial velocity due to the change in flow rate which

can be seen by comparing Figures 5-2 (c), 5-2 (e) and 5-2 (d), 5-2 (f). These velocity

contours showed reasonable agreement with the experimental results of Morsi et al.

[1] presented in Figure 5-3. Comparison of the Figures 5-2 (b) and 5-3 (b) shows that

there is around 5% discrepancy between the experimental and the simulation results

near the lance tip. Nevertheless, the simulation results predicted some higher value in

the remaining portion of the liquid bath as the movements of the fluid particles was

not uniform and there was generation of turbulence inside the bath. The transient

effect of the flow fields might be one of the factors that caused the discrepancies in the

contour plots between the simulation and experimental results. The contour plots

presented here from the simulation are instantaneous, but in Figure 5-3 the contour

plots from the experimental results of Morsi et al. [1] are time averaged. Time

averaged experimental results are shown here for qualitative validation purpose only.

This validation exercise represents the qualitative accuracy of the present study against

existing experimental data.

5-2 (a) 5-2 (b)

143

5-2 (c) 5-2 (d)

5-2 (e) 5-2 (f)

Figure 5-2: Axial velocity (w) distribution (m/s) for the water model simulation

(a) Q=2.67 x 10-3

m3/s, H/L=2/3, Ф = 57.5

o, t = 60 sec

144

(b) Q=2.67 x 10-3

m3/s, H/L=2/3, Ф =0

o, t = 60 sec

(c) Q=2.67 x 10-3

m3/s, H/L=1/3, Ф = 57.5

o, t = 60 sec

(d) Q=2.67 x 10-3

m3/s, H/L=1/3, Ф = 0

o, t = 60 sec

(e) Q=1.5 x 10-3

m3/s, H/L=1/3, Ф = 57.5

o, t = 60 sec

(f) Q=1.5 x 10-3

m3/s, H/L=1/3, Ф = 0

o, t = 60 sec

Figure 5-4 shows the instantaneous tangential velocity (v) contours on X-Z plane. The

effect of swirl is noticeable from the figures. Significant increase in tangential

velocities will only occur due to the presence of swirl component, which is revealed

by comparing the Figures, 5-4 (a), 5-4 (b) and 5-4 (c), 5-4 (d). The change in

tangential velocity component due to swirl is much higher than the change in axial

velocity component. The tangential velocity distribution in Figure 5-4(d) revealed the

so-called dead water region in the bath. It shows that the bottom half portion of the

liquid bath is almost unaffected by the gas injection process for the case of 1/3

submergence and non-swirl case. The simulation results for tangential velocity

contours are in good agreement with experimental results of Morsi et al. [1], as shown

in Figure 5-5.

5-3 (a) 5-3 (b)

145

5-3 (c) 5-3 (d)

Figure 5-3: Axial velocity (w) distribution (m/s) from experimental results of Morsi et

al. [1]

(a) Q=2.67 x 10-3

m3/s, H/L=2/3, Ф = 57.5

o

(b) Q=2.67 x 10-3

m3/s, H/L=2/3, Ф =0

o

(c) Q=2.67 x 10-3

m3/s, H/L=1/3, Ф =57.5

o

(d) Q=2.67 x 10-3

m3/s, H/L=1/3, Ф =0

o

5-4 (a) 5-4 (b)

146

5-4 (c) 5-4 (d)

Figure 5-4: Tangential velocity (v) distribution (m/s) for the water model simulation

(a) Q=2.67 x 10-3

m3/s, H/L=2/3, Ф = 57.5

o, t = 60 sec

(b) Q=2.67 x 10-3

m3/s, H/L=2/3, Ф = 0

o, t = 60 sec

(c) Q=2.67 x 10-3

m3/s, H/L=1/3, Ф = 57.5

o, t = 60 sec

(d) Q=2.67 x 10-3

m3/s, H/L=1/3, Ф = 0

o, t = 60 sec

5-5 (a) 5-5 (b)

147

5-5 (c) 5-5 (d)

Figure 5-5: Tangential velocity (v) distribution (m/s) from experimental results of

Morsi et al. [1]

(a) Q=2.67 x 10-3

m3/s, H/L=2/3, Ф = 57.5

o

(b) Q=2.67 x 10-3

m3/s, H/L=2/3, Ф =0

o

(c) Q=2.67 x 10-3

m3/s, H/L=1/3, Ф = 57.5

o

(d) Q=2.67 x 10-3

m3/s, H/L=1/3, Ф =0

o

Figure 5-6 shows a comparison of mean tangential velocities between swirl and non-

swirl injection. The experimental data are also presented in Figure 5-6 for validation.

The radial distance (r) is normalised by the radius of the cylinder (R=115mm) and the

axial distance z is normalised by the length of the cylinder (Z=560mm). As expected,

the magnitudes of the tangential velocities are low under non-swirl conditions.

Tangential velocity near the lance shows a significant rise for swirl condition, but

drops off to around zero after r/R ≥ 0.20. The mean tangential velocities are calculated

at z/Z=0.92 which is just below the exit of the lance z/Z=0.91 for H/L = 2/3. The mean

tangential velocity distribution for non-swirl flow agrees well with the existing

experimental values of Morsi et al. [1]. The discrepancy between the two results lies

within a range of 0-10%. But for the case of swirl flow, present simulation shows the

peak value of mean tangential velocity 1.1 at a radial distance of r/R = 0.11, whereas,

from the experimental results of Morsi et al. [1], the peak was found to be 0.7 at a

radial distance of r/R = 0.128. The discrepancies between the experimental and the

simulation results may be attributed to the following,

148

(1) Differencing scheme used for momentum and turbulence is upwind, which

gives false diffusion in complex flow phenomena. However, this trend is quite

reduced by using fine grids in the liquid bath.

(2) The standard k-ε turbulence model [129] may give poor performance in a

number of important cases such as flows with large extra strains (e.g. curved

boundary layers, swirling flows) and rotating flows [148]. Still, the reason for

using this model is because it is well established, most widely validated

turbulence model and it gives excellent performance for many industrially

relevant flows.

(3) Inaccuracy of ± 6% associated with the experimental technique such as

optical component alignment, seeding, filtering, signal processing and

calibration [1].

Figure 5-6: Mean tangential velocity comparison between swirl and non-swirl flow

from the simulation results and comparison with water model experiment of Morsi et

al. [1] (z/Z= 0.92, H/L= 2/3, Q=2.67 x 10-3

m3/s)

5.2.2 Effect of Submergence Level

Different lance submergence level also plays a significant role on the fluid flow

characteristic in the top submerged lance (TSL) gas injection systems. The theory of

greater volume of splash generation put forward by Koh and Taylor [52] is revealed in

the present simulation data. In addition to 1/3 and 2/3 lance submergence level, the

149

simulation was extended for 1/6 submergence level. Figure 5-7 shows the time

averaged volume fraction of water, generated by splashing at 30 mm height above the

bath (z/Z = 0.68). No surface tracking method like Volume of Fluid was used in the

present simulation to quantitatively represent formation of each and every small

droplets generated from splashing. Tracking of each and every small droplets would

require massive computer resources and time. This was avoided in the present study

where the qualitative flow pattern in the liquid bath was of main interest. In the

present simulation, as the approach used was conventional Eulerian, time averaged

volume fraction is measured at certain heights above the liquid bath to get a qualitative

idea of splash. For a more quantitative analysis of the splash formation, surface

tracking methods like Volume of Fluid (VOF) have to be used. From the Figure it is

evident that increasing submergence level generates greater volume of splash. It is due

to an increase in penetration depth of air jet in deeper bath resulting in a greater

release of buoyancy energy, which produces more splashes. This result is also

consistent with the experimental study of Igwe et al. [53]. From the water model

experimental study of Igwe et al. [53], the authors qualitatively reported that the

degree of splashing increased with the increase in depth of submergence.

Figure 5-7: Average volume fraction of water at 68.0=Z

z for different submergence

level for the water model simulation (Q=2.67 x 10-3

m3/s, Ф = 57.5

o)

150

5.2.3 Effect of Air Flow Rate

The depth of penetration of air jet increases with increasing air flow rate, which can be

seen clearly by comparing Figure 5-2 (c), 5-2 (e) and 5-2 (d), 5-2 (f). Figure 5-2 (e)

and 5-2 (f) show the so-called dead water region near the bottom of the cylindrical

vessel used for water modelling. The increase in depth of penetration of air jet

provides better agitation into the bath hence better mixing. The penetration of the air

jet is a function of the term, rF ′ , which is a modification of the jet Froude number put

forward by Igwe et al. [53],

( )dg

vrF

g

g

ρρ

ρ

−=′

1

2

5.1

where 1ρ is the liquid phase density, gρ is the density of gas, g is the gravitational

constant, v is gas flow velocity and d is the orifice diameter. The higher the number,

rF ′ , the greater the jet penetrates into the liquid bath. Iguchi et al. [51] developed a

semi-empirical equation from an air-water experimental study to calculate the vertical

penetration distance of the air jet for top submerged lance gas injection which also

depends on air flow rate. According to Iguchi et al.[51], the semi-empirical equation

for vertical penetration distance of the injected air into the liquid bath can be

expressed as,

31

1.4 mnv FrdL = , 2< Frm < 6x103

5.2

where Lv is the vertical penetration distance of the injected air,

nd is the nozzle inner

diameter at the exit and mFr is the modified Froude number which can be expressed

as,

5

2

nL

gg

mgd

QFr

ρ

ρ= 5.3

where gρ is the density of gas, Lρ is the density of liquid, Qg is the gas flow rate and

g is the acceleration due to gravity. Equation 5-2, however, is not valid for the case of

the annulus air inlet as it is used in swirled lances. For air jet injection through the

annulus of the top submerged lance, a semi-empirical equation is proposed from the

151

present simulation data, based on the relationship proposed by Iguchi et al. [51], which

can be expressed as,

( ) 4745.0275.0 miova FrddL −= 5.4

where, vaL is the vertical penetration distance for air jet injected through annulus, od

and id is the outer and inner diameter of the lance respectively neglecting the

thickness of the lance wall, mFr is the modified Froude number which can be obtained

by Equation 5-3.

Figure 5-8 shows the relation between vertical penetration distance of the annulus air

jet (va

L ) and the modified Froude number (m

Fr ). The coefficients in equation 5-4 are

found from the fitted curve shown in Figure 5-8 with the correlation factor,

0.98R =2. Six different flow rates were used as mentioned in Table 5-2 for 1/3

submergence level and non-swirl flow. Vertical penetration distance of the air jet was

measured as the mean value for different time steps.

Figure 5-8: Relation between vertical penetration distance for annulus air injection

(va

L ) and modified Froude number (m

Fr ) as derived from the water modelling

simulation results (H/L=1/3, Ф = 0o)

152

5.2.4 Mixing in the Liquid Bath

Process kinetics in mixing phenomena in the real Top Submerged Lance (TSL)

smelting furnaces are quite complex. Mixing in the bath in real furnace scenario is

quite vigorous and there are several factors affecting the mixing process, a number of

which are mentioned below:

High temperature chemical reactions in the slag are dominant factors

affecting the mixing phenomena

Expansion of gases in the molten bath due to high temperature and air

injected through the lance accelerates the mixing

Sidewise and vertical movement of the lance in the molten bath affects

the total mixing process

Splashing phenomena at the free surface also increases the mixing

process in the bath

However, in the present simulation, only the isothermal cold model air-water system is

considered. Hence, many of the factors affecting the mixing phenomena are absent. In

the present simulation, the mixing phenomena studied are turbulence mixing through

the turbulent diffusion and macro mixing via convection.

5.2.5 Turbulence Mixing

Figure 5-9(a) and Figure 5-9(b) show the effect of swirl on turbulent kinetic energy (k)

distribution for the same flow rate and submergence level. The colour bar is showing

the magnitude range of the turbulence kinetic energy in the figure from 0 to 0.2 m2/s

2.

Figure 5-10(a) and Figure 5-10(b) show the turbulent kinetic energy distribution from

the experimental results of Morsi et al.[1]. The values obtained from the present study

are consistent with the values observed in the experimental study. Generation of

turbulence near the lance is increased in the case of 2/3 lance submergence level and

swirl flow. The maximum value of turbulent kinetic energy exists near the lance as

expected which was also revealed from existing experimental data. However, this

turbulence is significantly reduced with increasing distance from the lance tip and it

does not exist near the vessel wall. Though there is no noticeable change in turbulent

kinetic energy for swirl and non-swirl injection as shown in Figure 5-10(a) and Figure

153

5-10(b), our present simulation results show a noticeable change in the generation of

turbulent kinetic energy near the lance. The rising gas plume is extended radially from

the lance toward the wall as a result of swirl air injection.

5-9 (a) 5-9 (b)

Figure 5-9: Turbulent Kinetic energy (k) distribution (m2/s2)- (a) Q=2.67 x 10-3

m3/s,

H/L=2/3, Ф = 0o, t = 60 sec, (b) Q=2.67 x 10

-3 m

3/s, H/L=2/3, Ф = 57.5

o, t = 60 sec

154

5-10 (a) 5-10 (b)

Figure 5-10: Turbulent kinetic energy (k) distribution (m2/s

2) from experimental

results of Morsi et al. [1] ((a) Q=2.67 x 10-3

m3/s, H/L=2/3, Ф = 0

o, (b) Q=2.67 x 10

-3

m3/s, H/L=2/3, Ф =57.5

o)

As the relative density of air being very low as compared to water, the velocity of air

in this study does not give sufficient momentum to penetrate into the liquid water and

create turbulence in the whole bath. Formation of bubbles and hence high velocity

gradients, resulting from momentum transfer between the gas and the liquid phase,

provides higher turbulence near the lance. In the region above the lance exit, the rising

bubbles have lost most of their initial momentum. Only the buoyancy forces exerted

by the rising bubbles assist in the generation of turbulence near the lance wall.

155

Figure 5-11: Volume fraction for water after 180 seconds (Q=2.67 x 10-3

m3/s,

H/L=2/3, Ф =57.5o)

Figure 5-11 shows the volume fraction for water after 180 seconds for high injection

rate and 2/3 lance submergence. Figure shows significant asymmetry due to the

sloshing and splashing in the water bath, which represents the transient nature of the

simulation. This is the essence of the 3D transient multiphase flow simulation, which

can give more insights into metallurgical flows of interest. The volume fraction plot

for the non-swirl case (not presented in the paper) showed no significant difference

with the swirl case. Velocity vectors for the same condition are shown in Figure 5-12,

which shows the formation of a weak recirculating vortex just near the top level of the

liquid. Formation of this weak recirculation region is random and transient in nature,

as it was observed from the simulation results. The rising bubbles in the liquid induce

these short-lived vortices. Formation of the recirculating vortex inside the bath is quite

favourable for generation of uniform mixing inside the bath. However, no significant

vortex was observed inside the bath in the present study. The magnitude of the

156

velocity vectors near the wall of the vessel are negligible compared to the values near

the lance. Liquid near the bottom corner of the vessel is almost unaffected by the air

injection process, as it was observed from the present air-water simulation.

Figure 5-12: Velocity vectors for liquid phase (m/s) after 180 seconds

(Q=2.67 x 10-3

m3/s, H/L=2/3, Ф =57.5

o)

5.2.6 Mean Convective Mixing

To measure the convective mixing efficiency inside the physical models, traditional

tracer studies are generally used. In the present study, the mean convective mixing was

evaluated by using the “Volume exchange effectiveness” concept. This approach is

generally used in Heating, Ventilation and Air-conditioning (HVAC) process

simulation [149]. The term “Volume exchange effectiveness”, which is actually a

measure of the mean convective mixing, may be defined as the net exchanged volume

of fluid in each computational cell divided by the volume of that cell and can be

expressed as eefV where,

cell theof Volume

cell nalcomputatio a through rate flow Volume=eefV 5.5

157

It expresses the volume exchange rate through a cell which in-turn represents the

convective mixing. It has the unit of (time)-1

.

Figure 5-13: Volume exchange effectiveness along radial direction from present water

model simulation (Q=2.67 x 10-3

m3/s, H/L=1/3)

Figure 5-13 shows the time averaged volume exchange effectiveness ( eefV ) of the air-

water system for swirl and non-swirl injection at z/Z = 0.84 (which is 10mm below the

lance exit in the water bath) along the radial direction. As shown, swirl flow provides

greater convection mixing for up-to r/R = 0.1. The swirl flow sets up a centrifugal

force field, which has a favourable convection effect. Swirl flow dominates over the

non-swirl in the region ranging from r/R = 0 to 0.1. However, at distance r/R≥ 0.1,

there is no significant change in the convective mixing process due to swirling effect.

This mixing phenomenon is only valid for the air water system, not in the real furnace

scenario. Figure 5-14 shows the contour plots of the eefV for swirl and non-swirl flow.

The plots further confirm that the swirl flow can only increase mixing in the region

very close to the lance for the specific case of the air-water system.

158

5-14 (a) 5-14 (b)

Figure 5-14: Contours for volume exchange effectiveness from present water model

simulation

(a) Q=2.67 x 10-3

m3/s, H/L=1/3, Ф = 0

o, t = 30 sec

(b) Q=2.67 x 10-3

m3/s, H/L=1/3, Ф = 57.5

o, t = 30 sec

5.2.7 Effect of Density

To investigate the effect of density change on the formation of splashing, the liquid

density has been increased to 3 times of density of water. The new fluid has been

denoted as D3 ( 3

3 3000 mkgD =ρ ). The viscosity of that liquid was kept constant as

water. However, it should be noted that due to the lack of experimental data, these

results could not be validated and hence must be considered as exploratory. Therefore,

these results are presented here for discussion only.

159


bath (Q=2.67 x 10-3

m3/s, H/L=1/3, Ф = 57.5

o)


bath

(Q=2.67 x 10-3

m3/s, H/L=1/3, Ф = 57.5

o)

160

The effect of density on the generation of splashing is shown in Figure 5-15 and

Figure 5-16. Figure 5-15 shows the average volume fraction at 40mm (z/Z = 0.66)

above the liquid bath and the generated splash pattern along the radial direction. As

expected, the degree of splash generation for the higher density liquid is reduced

significantly. At 60mm (z/Z = 0.625) height above the liquid bath (Figure 5-16), the

curves show similar trend. The bubbles from the injected air jet through the annulus of

the lance move radially outward and approach the free surface. This trend leads to the

creation of broad spouts in the free surface. The highest expulsion of the rising plume

was in the vicinity of the lance. When the bubbles collapse at the free surface,

formation of splashing occurs.

In the experimental study by Nilmani and Conochie [56], the authors investigated the

effect of different gas density by injecting Helium instead of air. They reported that

with a less dense gas, a greater volume flow is required to maintain the same injection

characteristics. However, no experimental study was found in the open literature on

the formation of splashing for higher liquid density for the case of top submerged

lance gas injection.

5.2.8 Effect of Viscosity

Effect of viscosity on splashing and slopping has been investigated experimentally by

Nilmani and Conochie [56], where the authors used three different liquids of different

viscosity (water, glycerol/water of viscosity 56 centipoise and glycerol/water of

viscosity 200 centipoise). They reported from their experimental study that splashing

and slopping were not as pronounced as in the air-water system. They also reported

that gas penetration of the viscous liquid on the lance axis was also small and

increasing liquid viscosity reduces gas dispersion.

The effect of viscosity change has also been investigated by Liovic et al. [76] on the

formation of splashing by numerical technique. In their numerical simulation, Liovic

et al. [76] used 95% glycerol solution to see the effect of viscosity on the generation of

splashing. They reported that high viscosity suppresses splashing and free surface

distortions. They also reported that high liquid viscosity of the glycerol solution also

damps out bulk bath motion and reduces back-penetration of liquid up the lance

significantly.

161

Chapter 6

162

6 Numerical Investigation of Zinc Fuming Bath in TSL

Furnace

This chapter will focus on the investigation of zinc fuming behaviour inside the top

submerged lance (TSL) furnace by using CFD modelling tool. The research findings

presented in this chapter are obtained from the developed CFD model that includes

submerged combustion in multiphase flow, reactions kinetics in the slag bath and heat,

mass and momentum interfacial interaction between the phases. Details of the model

development of the pilot plant scale TSL furnace including the geometry, generated

volume mesh, equations solved and interfacial exchange terms are discussed in

Chapter 4 (Section 4.3.2). This Chapter begins with the analysis of grid independency

test, followed by results and discussions on the detail zinc fuming kinetics inside the

TSL furnace.

6.1 Test of Grid Independency

Four grid resolutions were tested for grid independency test. Starting with a coarse

grid, number of cells was increased in the region of interest until the solution from

each grid was unchanged for successive grid refinements. Table 6-1 represents an

overview of the grid information studied in the grid independency test. All the cells in

the calculation domain were polyhedral with a large number of hexahedral cells.

Describing the number of cells in each direction is complex as the computational

domain consisted of hybrid unstructured meshes in curvilinear non-orthogonal

coordinate system with Cartesian base vectors and refined regions in some locations.

Regions for refinement in this model include combustion chamber at the lance tip,

area adjacent to the lance tip and surrounding the lance, near the wall, near the exit of

the furnace and in the slag bath. Figure 4-5 shows the generated course grid for the

CFD analysis. The meshing procedure was carried out using the Fame Advanced

Hybrid meshing technique [125].

163


Name Grid Density No of

Computational cells

Grid 1 Coarse 256138

Gird 2 Medium 337755

Grid 3 Fine 415017

Grid 4 Very Fine 581024

Figure 6-1: Mean tangential velocity distributions for different grid configurations (Qa

= 0.05 kg/s, Qf = 0.0035 kg/s, LH ′′ = 1/5)

Figure 6-1 shows the mean tangential velocity distribution (V) on X-Z plane along the

radial direction at a vertical depth of z/Z = 0.774. The radial distance (r) is normalised

by the radius of the cylinder (R=0.25 m) and the axial distance z is normalised by the

length of the cylinder (Z=1.68 m). Both Grid 3 and Grid 4 gave a very close

prediction. The difference in predictions between Grid 3 and Grid 4 was small enough

(around 1%) to suggest that any further grid refinement would not yield a substantially

different profile in that plane. Hence, it was determined that the fine grid resolution

(Grid 3) of 415017 cells was sufficient to obtain grid independent results.

164

For validation exercise of the results presented in this chapter, a pilot plant scale

experimental study carried out by Waladan et al. [2] was considered. Comparisons of

the injection conditions between the present CFD simulation and the experimental

study by Waladan et al. [2] are mentioned in Table 6-2.

Table 6-2: Injection conditions (CFD and Experimental)

Experimental

conditions (CZF5)

(Waladan et al. [2]

CFD

Calculations

Fuel type Fine Coal CH4

Reductant type Fine Coal Fine Coal

Combust air (kg/s) 0.06 0.05

Fuel rate (kg/s) 0.035

0.0035

Reductant rate (kg/s) 0.035

Initial zinc content in the

slag (wt %) 10.7 18.0


Zinc slag fuming is a complex process to simulate and it is necessary to make a

number of assumptions to simplify the simulation. A large number of complex

reactions are involved, such as: reduction of zinc oxide and ferric iron, fuel

combustion, oxidation of ferrous iron oxide, gas-carbon reaction. In the present

simulation, oxidation of ferrous iron oxide is likely to be insignificant, as all the

supplied oxygen is combusted at the lance tip due to stoichiometric combustion. To

avoid complexity, the ferric iron level in the bath was considered as negligible. As the

numerical simulation is based on Euler - Euler approach, the model does not predict

the exact plume shape with a sharp gas-liquid interface for each small gas bubble. The

model could be improved, particularly, incorporating the effect of ferric iron and

providing a more realistic treatment of the behaviour of coal; in addition longer

simulation times could be used. However, the results here represent a significant step

in developing a more comprehensive model.

165

In the following sections, the results will be discussed in-terms of bath behaviour,

combustion behaviour, zinc fuming behaviour and effect of lance submergence level

on generation splashing and zinc fuming behaviour.

6.2.1 Bath Behaviour

Figure 6-2 shows the volume fraction distribution for molten slag phase of the

transient simulation at four different time steps (13th

, 13.5th

, 20.5th

and 32nd

seconds).

The cross sectional view along the vertical X-Z plane was considered in these figures.

The colour bar associated with each figure represents the volume fraction values (0 to

1). Red colour with volume fraction value of 1 indicates 100% slag phase and the blue

colour with volume fraction value of 1E-006 indicates 100% gas phase. The green

colour in between indicates the slag – gas emulsion zone. The generated plume shape

at the lance tip due to gas injection and combustion is clear from this figure. This

plume was not found to be constant in position, rather changing with time, as the

figure shows. There was significant amount of sloshing in the slag bath as well.

Sloshing is a free surface hydrodynamic phenomenon in the bath, where the liquid

phase generates a wavy motion on the free surface of the bath due to turbulence

created by the submerged combustion. On the other hand, splashing is the tearing of

liquid phase in the form of droplets from unstable liquid metal wave peaks in the

continuum bath surface. Slag droplets generated due to splashing may either fly inside

the bath (termed as slag in flight in this paper) or otherwise hits the furnace wall and

falls back to the bath. Figure 6-3 shows another cross section along the X – Y plane

from the top of the modelled furnace. These figures give a clear understanding of the

impact area of the injected gas at the lance tip inside the bath. The mean diameter of

the generated plume along the radial direction (in X – Y plane) was found to be 0.3 m

in the 0.5 m diameter furnace. The mean area of the impact zone at the lance tip was

calculated as 0.071 m2 from the transient simulation in a 0.196 m

2 area of slag bath.

Comparison of the Figure 6-3(a) and Figure 6-3(b) also indicates the transient nature

of the generated plume along the radial direction.

Figure 6-4 shows the iso-contour plot at the gas-liquid interface, indicating velocity of

the molten slag phase with a slag volume fraction of 0.5 (display attribute: slag

166

velocity, iso-surface data: slag volume fraction of 0.5, Qa = 0.05 kg/s, Qf = 0.0035

kg/s, LH ′′ = 1/3). The colour bar with the associated figures represents the slag phase

velocity inside the furnace varying from 0.07 to 0.7 m/s. Figure 6-4(a) and Figure

6-4(b) are captured at 25th

and 26.5th

second time of the transient simulation

respectively. Comparison of the two figures portrays the sloshing and splashing

phenomena inside the furnace in a time interval of 1.5 seconds. Generated movie from

the simulation results showed that the slag in flight (splashes) goes around 1 m high

above the bath surface. This sloshing and splashing phenomena creates a massive

agitation in the slag bath, which accelerates the gas-carbon and gas-slag reactions.

6-2(a) 6-2(b)

167

6-2(c) 6-2(d)

Figure 6-2: Volume fraction distribution for molten slag phase along the vertical cross

section in X-Z plane at four different time step of the transient simulation (Qa = 0.05

kg/s, Qf = 0.0035 kg/s, LH ′′ = 1/3), (a) 13th

second, (b) 13.5th

second, (c) 20.5th

second and (d) 32nd

second.

168

6-3(a)

6-3(b)

Figure 6-3: Volume fraction distribution for molten slag phase along the cross section

in X-Y plane (top view of the modelled furnace) at different time steps of the transient

simulation (Qa = 0.05 kg/s, Qf = 0.0035 kg/s, LH ′′ = 1/3), (a) 21.5th

second, (b) 22nd

second

169

6-4(a) 6-4(b)

Figure 6-4: Iso-contour plot of the molten slag phase at different time steps of the

transient simulation (Qa = 0.05 kg/s, Qf = 0.0035 kg/s, LH ′′ = 1/3), (a) 25th

second,

(b) 26.5th

second

Figure 6-5(a) and Figure 6-5(b) shows the streamlines distribution of the molten slag

phase showing slag phase movement inside the furnace at two different time step of

16.5th

second and 27th

second respectively at a mid-plane cross section along the X – Z

plane. Velocity vectors inside the molten slag bath are shown on Figure 6-6. The

transient simulation showed some recirculation zones as marked in the figure.

Recirculation zones are favourable in improving the bath mixing. While the slag in

flight that falls back to the bath accelerates the bath surface reaction. Slag phase

streamlines from Figure 6-5 shows the slag in flight movement inside the furnace.

170

Some portion of the slag in flight strikes the furnace wall and falls back to the bath

along the wall, as shown in the Figure 6-4.

6-5(a) 6-5(b)

Figure 6-5: Streamlines distribution of the molten slag phase showing slag phase

movement inside the furnace at different time steps of the transient simulation (Qa =

0.05 kg/s, Qf = 0.0035 kg/s, LH ′′ = 1/3), (a) 16.5th

second, (b) 27th

second

171

Figure 6-6: Velocity vectors inside the furnace in the molten slag bath: (Qa = 0.05

kg/s, Qf = 0.0035 kg/s, LH ′′ = 1/5)

6.2.2 Combustion Behaviour

After the initiation of the combustion at the lance tip, the plume becomes larger due to

combustion and associated expansion of the gases in the slag bath. The CFD software

used - AVL FIRE 2009.2 (AVL, Graz, Austria) enables us to capture results at

millisecond time step. Figure 6-7(a) shows the species mass fraction (kg/kg)

distribution of CH4 after 27 seconds of the simulation, which shows CH4 being

combusted completely because of stoichiometric combustion. The colour bar with the

Figure represents the mass fraction (kg/kg) value. Because of the swirling effect in the

annular region of the lance, O2 in the air that comes through the annular region of the

lance tip, mixes well with the CH4 in the combustion chamber and ensures fuel-

efficient combustion at the lance tip. As indicated by the colour bar, CH4 is entering

into the combustion chamber through the central hole of the lance (red colour with

mass fraction = 1.0) and mixes with air, indicated by turning to a green colour with

mass fraction = 0.5 to 0.6. Before the supplied CH4 leaves the combustion chamber,

80% of it is combusted in the combustion chamber and the remaining 20% CH4

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combustion takes place near the lance tip in the bath. Figure 6-7(d) shows the O2 mass

fraction distribution inside the furnace. The figure shows that the supplied O2 through

the annular region of the lance was completely combusted at the lance tip. The

products of combustion include CO, CO2, N2 and H2O vapour. Formation of CO2 and

CO in the bath is shown in Figure 6-7(b) and Figure 6-7(c) respectively. The colour

bar with the Figures represents the mass fraction (kg/kg) value of the respective

figures. As the figures show, mass fraction (kg/kg) of CO2 above the slag bath is

greater than mass fraction (kg/kg) of CO. This is attributed to the fact that, CO2 is

forming not only as a product of combustion of CH4, but also from the ZnO reduction

reaction (Equation 2-7). The CO above the slag bath contributes to increase the

fuming rate from the slag in flight (splash). Comparison of the Figure 6-2 and Figure

6-7(c) points clearly about phenomena that the CO from gas phase comes in contact

with the generated splash or slag in flight inside the furnace. The effect of slag in

flight (splash) on the fuming rate is discussed later (section 6.2.4.)

6-7(a) 6-7(b)

173

6-7(c) 6-7(d)

Figure 6-7: Species mass fraction (kg/kg) distribution for (a) CH4, (b) CO2 (c) CO and

(d) O2

(Qa = 0.05 kg/s, Qf = 0.0035 kg/s, LH ′′ = 1/3)

Figure 6-8 is showing the temperature distribution of the molten slag phase only from

the transient simulation results. Temperature distribution inside the bath was not

uniform and it was governed by the enthalpy conservation and interfacial exchange

terms described in section G. In the boundary conditions the wall temperature was

considered as 1500 K and the initial temperature of the molten slag was considered as

1500 K for the simulation to start. The simulation results revealed that there is non-

uniform temperature distribution in the molten slag bath. This temperature profile

doesn’t imply steady state distribution. These non-uniform temperature distributions

in the slag bath are expected to be uniform with longer simulation time. In addition,

the transport properties of the molten slag phase influence this temperature

distribution in the slag. From the simulation results, the molten slag bath can be

174

divided into three zones: combustion zone near the lance tip, where the temperature

was highest due to the combustion process (1563-1573 K), bath zone below the lance

tip in the slag bath, where the temperature was almost uniform (1550-1563 K) and the

free surface zone away from the central lance of the furnace near the surface area of

the molten slag bath, where there is a thin layer of gas-liquid mixture (1540-1550 K).

In this gas-liquid emulsion zone, the temperature distribution is lowest, as the

endothermic reductions of ZnO by the CO (as mentioned in equation 2-7) takes heat

from that zone. The enthalpy of reduction of ZnO from the slag to the gas phase

(equation 2-7) has been considered in the simulation according to the data provided by

Richards et al. [21] ( 5.192H =∆ kJ/mol). However the model does not include the

post combustion zone and re-oxidation of Zn to ZnO vapour above the bath.

Figure 6-8: Temperature distribution for molten slag phase only (b) Species mass

fraction (kg/kg) distribution for O2 (Qa = 0.05 kg/s, Qf = 0.0035 kg/s, LH ′′ = 1/5)

175

6.2.3 Zinc Fuming Behaviour

The simulation results predicted that zinc fuming initiates from near the lance tip of

the molten slag bath in the combustion zone where CO forms as a product of

combustion of CH4 as mentioned by equation 2-7. CO thus formed initiates the first

fuming process in the bath. Figure 6-9(a) shows the initial stage (after 1 second) zinc

fuming process near the lance tip area. The fuming process accelerates from the bath

near the surface area where the slag phase is more in contact with the gas phase and

carbon reacts directly with CO2 to form CO. Figure 6-9(b) shows the fumed zinc

distribution inside the furnace from the molten slag bath after 30 seconds of

simulation time. The colour bar with each of the figures indicates amount of zinc

fumed in kg, on that specific mid plane section (along X – Z plane).

6-9(a) 6-9 (b)

Figure 6-9: Fumed zinc distribution inside the furnace (a) at initial stage (after 1

second) (b) after 30 seconds (Qa = 0.05 kg/s, Qf = 0.0035 kg/s, LH ′′ = 1/5)

Figure 6-10 shows the amount of ZnO present in the slag bath at different depth along

the radial direction from the lance. ZnO concentration in the slag bath below the lance

tip (l/L=0.1) is found to be 17.1 wt%, which indicates a highest fuming rate of 0.9

wt%/min, for a slag containing 18 wt% ZnO, where l indicates the depth from the

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lance tip as shown in Figure 4-4 and L = (L’- 0.12) = 0.48 m for 1/5 lance

submergence level. Figure 4-4 is provided below for convenience.

Figure 4-4: Schematic diagram of the modelled furnace for Outotec TSL pilot plant

The highest mass fraction of CO was observed in the combustion zone below the lance

tip. As the present simulation is based on Eulerian approach, it does not consider any

sharp gas-liquid interface; rather the zone is a gas-liquid emulsion zone as shown in

Figure 6-2 (green colour between blue and red). The fuming rate near the bath surface

(l/L=0.1) was found as 0.34 to 0.9 wt%/ min, where availability of CO is more and

carbon reaction rate is higher. By comparing Figure 6-2(a) and Figure 6-10, it be

argued that highest fuming rate area is up-to the radial distance r/R = 0.3 in the

generated plume inside the bath. Significant fuming rates were also found at the depth

of l/L=0.2 ranging from 0.2 to 0.579 wt%/ min and 0.13 to 0.35 wt%/min at depth

l/L=0.3. The overall fuming rate from the whole bath is found to be 0.2 to 0.35

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wt%/min for a slag containing 18 wt% ZnO using CH4 as fuel and pulverized coal as

reductant. Batch fuming rates for zinc fuming furnaces using pulverized coal as fuel

and reductant vary between 0.15 to 0.27 wt%/ min for slags containing about 10 wt%

Zn [150] and 0.09 wt%/ min for 9 wt% Zn slag (at 1275o C temperature) [102]. Thus

Figure 6-10 depicts the ZnO reduction behaviour at the gas – liquid interface from the

slag bath at different depth, in addition to the fuming rate.

Figure 6-10: ZnO distribution in the slag bath at different depths below the lance tip

along a line in radial direction from the lance (Qa = 0.05 kg/s, Qf = 0.0035 kg/s,

LH ′′ = 1/5)

The CO mass fraction (kg/kg) distribution along the radial direction at different depths

below the lance tip is shown on Figure 6-11. As indicated by the Figure, the mass

fraction is gradually decreasing at lower depth below the lance tip. The rate of

reduction of ZnO is also decreasing at lower depths, as shown on Figure 6-10. The

concentration gradient of ZnO near the gas-slag interface is indicative of the fact that

diffusion of ZnO from the bulk slag to the slag-gas interface and presence of CO plays

a very important role in overall kinetics. From the slag analysis of some zinc fuming

industrial trials, Richards et al. [21] also found that there was concentration gradients

of Zn and Fe adjacent to some carbon particles in the slag.

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Figure 6-11: CO mass fraction (kg/kg) distribution along the radial direction at

different depths below the lance tip (Qa = 0.05 kg/s, Qf = 0.0035 kg/s, LH ′′ = 1/5)

Figure 6-12: Zinc fuming rate from some published experimental work

179

Figure 6-12 shows zinc fuming rate from some of the published experimental and

modelling work. Fuming rate for fuming cycle A1, B1, C1 and D1 are taken from the

mathematical modelling work of Richards and Brimacombe [20], where the authors

used some plant data for fuming rate to fit the model. The Figure shows that the

fuming rate curves decreases almost linearly with time and follows a zero order

pattern. A similar pattern of zinc fuming rate curve has also been predicted from the

present simulation results, as shown in Figure 6-13.

Figure 6-13 shows the CFD results for zinc fuming rate. The simulation results

showed zinc concentration in the slag decrease linearly with time. The linear time

dependence of the zinc elimination rate reveals the zero order reaction kinetics, which

is consistent with other published work (Figure 6-12). Experimental trials on pilot

plant top submerged lance zinc fuming process were carried out by Waladan et al. [2].

In those experimental trials, zinc fuming from Sulphide Corporation slag containing 8-

12% zinc were investigated using a range of fuel-reductant combinations [2].

Experimental results for fuming trial CZF5 are shown in Figure 6-13 for macro-step

validation purpose.

Figure 6-13: Fuming rate from present simulation results (Qa = 0.05 kg/s, Qf = 0.0035

kg/s, LH ′′ = 1/5) and comparison with experimental data (Curve regenerated from

CZF5 of Figure 11 from Waladan et al. [2])

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6.2.4 Effect of Lance submergence level

As discussed earlier, the highest fuming rate was found to be below the lance tip in the

generated plume inside the slag bath (see results in Figure 6-10). The larger the plume

area, the higher is the fuming rate from the slag bath. In the slag bath, fuming rate was

found to be higher in area of the gas-liquid interface, where ZnO diffuses to the gas-

slag interface and being reduced by the CO present in the gaseous phase. It would be

interesting to see the fuming rate from the slag in flight (above the bath) or generated

splash. Therefore, three different submergence levels ( LH ′′ = 1/5, 1/4 and 1/3) have

been considered in the model to investigate the effect of lance submergence level on

fuming and splash generation. All the submergence levels were investigated with the

same air and fuel flow rate (Qa = 0.05 kg/s, Qf = 0.0035 kg/s). To elucidate the effect

of generated splash (i.e. slag in flight) on the fuming rate, a number of locations were

considered above the slag bath on the X-Y plane (Figure 4-4). The amount of splash

at those specific heights above the slag bath has been characterized by the amount of

volume fraction in flight. The volume fraction and the zinc fuming rates at those

specific heights above the slag bath are shown in Figure 6-14 for 1/3 lance

submergence level. Average volume fractions in flight are plotted on the left vertical

axis and zinc fuming rates (wt%/min) are plotted on the right vertical axis of the

curve. The horizontal axis of the curves shows the normalized radial distance from the

lance tip (r/R), where R = 0.25 m is the radius of the cylindrical furnace. Generated

splash and zinc fuming rates were measured at five different heights (h = 0.1, 0.2, 0.4,

0.6, 0.8) m above the bath. These heights were normalized as h/H = 0.09, 0.18, 0.36,

0.54, 0.73, where h is the height from the bath surface to the top wall of the furnace

and H = 1.08 m is the total distance between the bath surface and top wall of the

furnace (Figure 4-4).

181

Figure 6-14 (a): Zinc fuming rate and amount of splash at different heights above the

bath (Qa = 0.05 kg/s, Qf = 0.0035 kg/s, LH ′′ = 1/3)

Figure 6-14 (b): Zinc fuming rate and amount of splash at different heights above the


182

Figure 6-14 (c): Zinc fuming rate and amount of splash at different heights above the


Figure 6-14(a) shows largest volume of splash is at 100 mm above the bath (h/H =

0.09). The normalized radial distance on the horizontal axis of the curve indicates the

splash pattern. The largest volume fraction of the generated splash at that height was

found to be 0.37 at a radial distance of r/R = 0.45. The minimum zinc fuming rate

measured at that height is 0.03 wt%/min at a radial distance of r/R = 0.2. The zinc

fuming rate (continuous red line curve) gradually increased to 0.12 wt%/min as the

splash volume decreased gradually and gas comes more in contact with the slag phase.

At height h/H = 0.18, average volume fraction of the generated splash reduced to 0.18,

and zinc fuming rate increased to 0.08 – 0.24 wt%/min (dashed blue line curve).

Measured data at the other heights shows that generated splash volume gradually

reduces towards the upward direction of the furnace and zinc fuming rates at those

specific heights gradually increases. The zinc fuming rates presented on the Figure

6-14(a) at different heights are the predicted value of the fumed zinc or reduced ZnO

from the slag present at those specific heights only. Hence, the reader should not

confuse fuming rate from the slag at any plane with the overall fuming rate.

Comparison of the Figure 6-2 and Figure 6-7(c) indicates that reduced volume of

splash far above the bath has large interfacial area and comes more in contact with the

CO available above the bath. This may be more easily described with fact of large

interfacial area between the slag and the gas phase. Definitely, a large droplet or

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splash of slag of 100 mm diameter has less interfacial area than 10 droplets of each 10

mm diameter. These predictions clearly indicate that more the slag phase is exposed to

the gas phase, the higher is the fuming rate. Therefore, a large quantity of fine slag

droplets will promote high fuming rates. Hence fine droplet generation and deeper gas

penetration in the slag bath will maximize the fuming rate. However, the availability

of CO and carbon limits the fuming rate in flight. Hence, the model predicts that the

mass transfer of ZnO from the bulk slag to the slag-gas interface and the CO present in

the gas phase plays a vital role in controlling the overall fuming rate for the specific

simulation time studied. The two other submergence levels ( LH ′′ = 1/5 and 1/4)

showed similar behaviour of splash generation and zinc fuming rate, as shown in the

Figure 6-14(b) and Figure 6-14(c).

For a quantitative comparison among the submergence levels studied, two other

graphs are presented on Figure 6-15 and Figure 6-16 at two different heights above the

bath (h/H = 0.09 and 0.73) respectively. As Figure 6-15 shows, the generated volume

of splash just 100 mm above the bath (h/H = 0.09) has increased for 1/3 lance

submergence level than 1/5 submergence level. The splash pattern has also changed

with the submergence level. Highest volume fraction for 1/5 lance submergence level

at h/H = 0.09 height was found to be 0.25 at a radial distance of r/R = 0.25. Whereas,

for 1/4 lance submergence level, splash volume were increased further away from

lance, at a radial distance of r/R = 0.80 to 1.0.

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above the bath for three submergence levels (Qa = 0.05 kg/s, Qf = 0.0035 kg/s)


above the bath for three submergence levels (Qa = 0.05 kg/s, Qf = 0.0035 kg/s)

185

Not much noticeable change in overall fuming rate has been observed between the 1/5

and 1/4 submergence levels. Figure 6-16 shows a significant increase in the fuming

rate for 1/3 submergence level at a height of h/H = 0.73. Due to the deeper gas

penetration, noteworthy increment in the sloshing and splash generation with large

interfacial area was observed. The increment in the sloshing phenomena agitated the

gas-carbon reaction in the bath surface, which accelerates the production of CO in the

bath surface. This higher production of CO increased the fuming rate from the slag in

flight (splash). The highest fuming rate for 1/3 lance submergence level was measured

as 0.5 wt%/min at h/H = 0.73, which is 1.8 times higher than 1/5 lance submergence

level at the same height. The overall fuming rate for 1/3 lance submergence level were

found to be 0.25 to 0.4 wt%/min, which is around 1.3 times higher than 1/5 lance

submergence level. The bar chart shown on Figure 6-17 is the graphical representation

of the average fuming rates for the three lance submergence levels studied.

Figure 6-17: Overall zinc fuming rate comparison for three different lance

submergence levels (Qa = 0.05 kg/s, Qf = 0.0035 kg/s)

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Chapter 7

187

7 CFD Modelling of Conventional Zinc Fuming Furnace

This chapter will focus on the application of the developed CFD model in other

furnace configuration. The developed CFD model for TSL furnace as described in the

previous chapter was extended for submerged coal combustion instead of CH4 and

applied to a thin slice model of the conventional tuyere blown furnace. Results were

analysed in-terms of combustion behaviour, jet penetration behaviour, bath agitation

and zinc fuming behaviour. Details of the model development including the geometry,

generated volume mesh, equations solved and interfacial exchange terms are discussed

in Chapter 4 (Section 4.3.3). This Chapter begins with the analysis of grid

independency test, followed by results and discussions on the detail of jet penetration

and combustion behaviour of the conventional tuyere blown furnace.

7.1 Test of Grid Independency

Accuracy of every CFD analysis depends largely on the type of grid used. Hence, grid

generation needs special attention of the investigators. Generally, finer grid gives more

accurate results, but eventually it leads to higher computational expense. Therefore, an

optimum grid resolution is necessary for efficient CFD analysis. In the present

simulation, only critical area for grid refinement was at the tuyere tip and the area

surrounding the tuyeres. The meshing procedure was carried out using the Fame

Advanced Hybrid meshing technique [125]. Three different grid resolutions were

tested for grid independency test. Initially with a coarse grid, then mesh refinement

was increased in the region of interest until the solution from each grid was unchanged

for successive grid refinements. The computational grid (176378 cells) used in the

present study is too dense for visual presentation. A figure of the coarse computational

grid (110843 cells) shown in Figure 4-8(b). To mention the number of control

volumes in each direction is complicated as the present computational domain

consisted of hybrid unstructured meshes in curvilinear non-orthogonal coordinate

system with Cartesian base vectors and refined regions in some locations. All the cells

in the calculation domain were polyhedral with a large number of hexahedral cells.

Other than the refinement, the number of cells is mentioned on Table 7-1. The Table

shows the number of the largest control volumes in X, Y and Z direction. In addition

188

to that, the computation domain has been refined in a number of locations. Regions for

refinement in this model include the tuyere tips, area adjacent to the tuyere tips and

surrounding the tuyere, near the wall, near the exit of the furnace and in the slag bath.


Name Grid type Grid Density No of

Computational cells

Grid 1 Medium (60 x 10 x 120) +

Refinements

110843

Gird 2 Fine (80 x 15 x 140) +

Refinements

176378

Grid 3 Very fine (90 x 15 x 150) +

Refinements

214911

Figure 7-1 shows the mean upward velocity distribution (W) on X-Z plane along the

axial direction at a vertical height of h/H = 0.02 and width (along Y direction) of d/D

= 0.5. The axial distance (l) is normalised by the length along X direction (L=2.44 m).

Both Grid 2 and Grid 3 gave a very close prediction. The difference in predictions

between Grid 2 and Grid 3 was small enough (less than 1%) to suggest that any further

grid refinement would not yield a substantially different profile in that plane. Hence, it

was determined that the fine grid resolution (Grid 2) of 176378 cells was sufficient to

obtain grid independent results.

189

Figure 7-1: Mean upward velocity, W (m/s) distribution of slag phase for three

different grids along axial direction (Uo = 67.8 m/s, d/D = 0.5, h/H = 0.02)


Computational fluid dynamic modelling of a multiphase combusting system

incorporating molten slag is a complex process to simulate. The model was simplified

by considering a number of assumptions. Reactions involved in the system are quite

complex, which includes reduction of zinc oxide and ferric iron, submerged

combustion, oxidation of ferrous iron oxide, gas-carbon reaction. In the present

simulation, oxidation of ferrous iron oxide was not taken into consideration. To avoid

complexity, the ferric iron level in the bath was assumed to be negligible. The rest of

the reactions, such as zinc oxide reduction, submerged coal combustion and gas-

carbon reactions were taken into account in the present simulation. Detail kinetics of

the chemical reaction is already described by Richards et al. [19-21]. The aim of the

present research is to investigate tuyere tip combustion dynamics, bath interaction

conditions and generation of turbulence at the tuyere tip inside the bath. Though, with

the available computational power and resources, these aims are hard to achieve

accurately. The actual tuyere tip interaction by tracking each and every single gas

bubble would require a very high powerful computer to solve millions of cells at the

tuyere tip. From the perspective of the CFD resources, the turbulence model itself is

190

not capable to predict the full turbulence behaviour accurately at the tuyere tip. In fact,

no turbulence models in the available literature have the capability to accurately

predict the full comprehensive turbulence behaviour within the bath. The standard k-ε

turbulence model [129] used in the present study may not provide expected

performance in a number of important cases such as flows with large extra strains (e.g.

curved boundary layers, swirling flows) and rotating flows [148]. Still, the model was

used as it is well established, most widely validated turbulence model and it gives

excellent performance for many industrially relevant flows. As the numerical

simulation is based on Euler - Euler approach, the model does not predict the exact

plume shape with a sharp gas-liquid interface for each small gas bubble. The model

could be improved, particularly, taking into account of the ferrous iron oxidation and

incorporating the effect of ferric iron in the bath, using highly dense computational

cells in the bath. However, the results represent a credible step in developing a more

comprehensive CFD model for analogous system.

7.2.1 Bath behaviour

From the CFD analysis of the developed model, a picture of the injection phenomena

emerged including jet and coal penetration into the slag bath, quiescent zones,

recirculation zones, tuyere gas stream behaviour, slag and gas phase velocity

distributions, turbulence behaviour.

Figure 7-2(a) and (b) shows volume fraction distributions of the molten slag phase at a

mid-plane cut along X-Z plane. The pictorial representation of the gas jet and coal

behaviour at the tuyere tip and shape of the tuyere gas column put forward by

Richards et al. [21] are also shown on Figure 7-3(a) and (b). The colour bar with the

associated figures indicates the volume fraction level (1 is indicated by the red colour,

which means 100% slag phase and 0 is indicated by the blue colour, which means 0%

slag phase). The green colour indicates the gas-liquid emulsion zone in the bath. The

simulation results showed that the tuyere gas columns at both the tuyere tip are

wavering in nature with respect to time and position. This is due to the tuyere tip

combustion and associated gas expansion from the combustion phenomena and also

the due to the sloshing phenomena created in the bath free surface. As soon as the gas

jet carrying coal phase injected into the bath, the jet moves horizontally into the

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molten slag entraining with surrounding slag phase and subsequently losing its

horizontal velocity (U). The highest distance the jet travels horizontally into the

molten slag phase is known as jet penetration. Detail description about the depth of

penetration of the gas jet carrying coal will be discussed in the later sections. While

the jet penetrating into the molten slag, horizontal velocity component reduces and at

some point the upward velocity component (W) component becomes significant. The

gas phase mixes with the slag phase and creates the gas-slag emulsion phase, as shown

by the green colour around the jet core in Figure 7-2(a) and (b). Mean upward velocity

distributions of the slag phase along the axial line from the tuyere tip are shown in

Figure 7-1 for inlet condition, Uo = 67.8 m/s. The graph represents the mean upward

velocity (W m/s), which was calculated by time averaging of the velocity components

at every second from 20 seconds to 60 seconds of the simulation time. Highest mean

upward velocity component (W) was found to be 2.46 m/s at an axial distance of l/L =

0.09 from the tuyere tip. Beyond that point along the axial direction (l/L > 0.09), mean

upward velocity component (W) gradually decreases. At the distance of l/L = 0.283,

upward velocity component (W) was found to be 0.01 m/s. This velocity profile

remains almost linear with no major deviation until the axial distance of l/L = 0.75,

which is closest to tuyere 2 (Figure 4-7). Then, it rises again from l/L = 0.8 and

reaches the maximum of 2.48 m/s at a distance of l/L = 0.92. Upward mean velocity

profiles near the two tuyeres are almost similar. Figure 7-2(c) shows the iso-contour

plot at the gas-liquid interface, indicating velocity of the molten slag phase with a slag

volume fraction of 0.3 (display attribute: slag velocity, iso-surface data: slag volume

fraction of 0.3, tuyere inlet velocity Uo = 86 m/s). The generated bubble plume shape

in the tuyere gas column, free surface sloshing phenomena and generated metal fingers

are clear from the figure. From the mid plane cut along X-Z plane (Figure 7-2(b)), slag

volume fractions of 0.3 – 0.5 is visible at 1.5 m height above the bath surface (bath

surface is located at 1 m height from the bottom). Movie generation from the

simulation results showed that, the generated splash strikes both the side wall and the

symmetry walls and slides downward on the wall to the bath. Some splashes that do

not hit any wall, are ejected up-to 1.5 meters above the bath surface and come back to

the bath, which accelerate the mixing process and reactions in the bath surface.

192

7-2 (a) 7-2 (b)

7-2 (c)

Figure 7-2: (a) and (b) volume fraction distribution of slag phase at plane cut at X-Z

plane (b) Iso-contour plot of slag phase showing the slag velocity (Uo = 86 m/s)

193

Figure 7-3: (a) Diagram showing injection phenomena in zinc fuming, (b) schematic

representation of the sequence of reactions in the bath (both the figures are taken from

Richards et al.[21])

Figure 7-4(a) shows the coal mass injected into the molten slag bath through the

tuyeres and Figure 7-4(b) is the graphical representation of the average coal mass

along the axial direction (l/L>0.041) from the tuyere tip. By comparing the Figure

7-2(b) and Figure 7-4(a), scalar fraction of the injected coal shows a portion of the

injected coal entrains in the slag phase. Here, the coal scalar fraction is represented as

a continuum phase colour rather that discrete particulate phase, as the simulation is

based on Eulerian approach (phases are treated as continua). Other than two main

reaction zones pointed out by Richards et al. [21] (reduction in the slag by entrained

coal particles and generation of heat in the tuyere gas stream by combustion of un-

entrained coal), another reaction zone has been predicted by the simulation results,

which is in the free surface. Injected coal that carried away by the gas jet to the free

surface contributes to some extent in overall zinc elimination. Zinc elimination

behaviour from the slag near the free surface will be discussed in the later section.

As shown in Figure 7-4(a), some portion of the injected coal (light blue colour) is

being carried by the tuyere gas stream up-to the free surface of the molten slag bath.

Bath surface height (1m from the bottom wall) is also indicated in that figure. Some

portion of the injected coal is also entrained in the slag bath. To find out the coal mass

injected into the slag at the centre line joining the tuyere centre (at d/D = 0.5, h/H =

0.02 as shown on Figure 7-4(a)), average coal flow rates through the computational

194

cells along the axial direction have been calculated. This graph was plotted by time

averaging the coal mass along that axial line, as shown on Figure 7-4(b). Figure

shows, the injected coal penetrates up-to the distance of l/L = 0.18 along the centre

line from the tuyere tip. This portion of the injected coal in the slag phase take part in

the reduction reaction of ZnO.

Turbulent kinetic energy distributions at the two tuyere tips and inside the bath are

shown on Figure 7-5. Highest turbulence inside the bath was found in front of the

tuyere tips varying from 5 – 7 m2/s

2 over the entire range of simulation time. In the

tuyere gas stream, average turbulence kinetic energy was found to be 1 – 2 m2/s

2.

Generation of turbulence is favourable in accelerating the mixing process, however,

from both the tuyere tips, for l/L > 0.25, no significant generation of turbulence was

predicted.

7-4 (a)

195

7-4 (b)

Figure 7-4: (a) Injected coal mass at the tuyere tip (b) Average coal mass along the

axial direction from the tuyere tip(Uo = 86 m/s, d/D = 0.5, h/H = 0.02)

Figure 7-5: Turbulent kinetic energy distribution inside the modelled furnace (Uo = 86

m/s)

196

7.2.2 Jet Penetration

To investigate the tuyere tip jet behaviour, average jet penetration depth at the tuyere

tip and jet expansion angle was measured from the simulation results. Among all the

parameters describing the jet, penetration depth of the injected jet is the most

important one [151]. Some investigators studied horizontal gas injection behaviour in

fluidized bed, AOD, refining ladle etc. and suggested some correlations regarding jet

penetration depth of gas-solid fluidized bed [151-153]. Zhu et al. [154] compared the

mixing efficiency of different mode of horizontal gas injection in an air-water system.

Hoefele and Brimacombe [3] carried out laboratory experiments of horizontal jet

injected into water, zinc – chloride solution and mercury bath and commented that

penetration length increases with the modified Froude number ( FrN′ ) and the gas-

liquid density ratio

ρ

ρ

l

g . The authors suggested the following equation to predict

the penetration depth,

( ) ( ) 35.0

lg

46.0

Fr

o

P N7.10d

lρρ′= 7.1

Where,

( )[ ]ogl

2

og

Frdg

UN

ρ−ρ

ρ=′ 7.2

is the modified Froude number, od is the diameter of the tuyere, oU is the velocity of

the injected gas at the tuyere exit, g is acceleration due to gravity and the subscript g

and l represents gas and liquid, respectively.

197

Figure 7-6: Gas phase volume fraction at tuyere 1 tip showing jet penetration length

(lp) and jet expansion angle ( Θ ) for Uo = 86 m/s

In the present simulation, three different tuyere jet velocities (50, 67.8 and 86 m/s)

were simulated. To preserve the continuity of same mass flow rate as the plant data

D1 provided by Richards et al. [21] at different tuyere inlet velocity, blast temperature

at inlet were adjusted to maintain the same mass flow rate of 0.158 kg/s. For example,

at 100o C and 200

o C, the air density is 0.946 kg/m

3 and 0.746 kg/m

3 respectively.

Thus, tuyere inlet velocities of 67.8 m/s and 86 m/s maintains the same mass flow rate

of air (0.158 kg/s) at 100o C and 200

o C respectively. Penetration length (lp) and jet

expansion angle ( Θ ) were also measured for each of the three cases. As the present

simulation is based on Euler-Euler approach, where gas and liquid phases act as

interpenetrating continua, there is no sharp gas-liquid interface. Hence, to measure the

jet penetration depth, highest distance of the gas volume fraction of 0.8 from the

tuyere tip has been considered as the jet penetration depth, which has been widely

adopted by others researchers [151, 153]. Figure 7-6 shows the jet penetration length

(lp) and jet expansion angle ( Θ ) from the simulation results. Jet expansion angles

measured for the jet velocity of 67.8 m/s and 86 m/s are 85 to 110 degrees and 75 to

95 degrees respectively. Oryall and Brimacombe [155] measured that the jet

expansion angle for air-mercury system was 155o. As discussed by Zhu et al. [154] the

jet expansion angle would vary between 20o to 155

o based on the liquid density,

viscosity and surface tension. From the present simulation results it is clear that jet

expansion angle is also dependent on the jet injection velocity in addition to fluid

198

properties. Hence, for present the zinc slag fuming process considered, with the

injection conditions (Uo = 86 m/s, slag density of 3900 kg/m3), mean jet expansion

angle was measured as 85o.

Figure 7-7 (a): Comparison of the CFD results of tuyere jet penetration length (lp) with

correlation provided by Hoefele and Brimacombe [3] from experimental work

Figure 7-7(a) is the comparison of the present CFD results of jet penetration length (lp)

with the correlation provided by Hoefele and Brimacombe [3]. To validate the present

model, a no-coal test was carried out where only air jet was injected into the molten

slag bath at high temperature through the tuyeres and penetration depth were

calculated. The results were compared with the equation proposed by Hoefele and

Brimacombe [3], as shown in Figure 7-7(a). The simulation results showed close

correlation with the experimental studies of Hoefele and Brimacombe [3]. In Figure

7-7(a), jet penetration length (lp) is non-dimensionalised with the tuyere diameter (do).

Dimensionless penetration length parameter ( )op dl by using equation (7.1) for three

different tuyere inlet velocities (50, 67.8 and 86 m/s) were calculated both at NTP and

at present simulation conditions (different inlet temperatures and slag density 3900

kg/m3). The penetration length parameter ( )

op dl from present simulation results are

also presented in the Figure. Results from the present CFD simulation with coal

199

combustion shows large discrepancies with the correlation provided by Hoefele and

Brimacombe [3] (equation (7.1)). With the same velocity at NTP, gas has higher

density which increased the total mass flow rate resulting in increased momentum and

penetration length. The correlation in equation (7.1) was developed based on the

experimental work with air and three different liquid (water, zinc – chloride solution

and mercury). The injected jet in that experimental study did not carry any coal

particle, which would impart large amount of momentum on the liquid phase. The

injected coal particles with the jet would have been created larger penetration length.

The significant cause of this discrepancy is due to the combusting environment.

Injected coal imparts a greater momentum in the present simulation in addition to the

combustion at the tuyere tip, which causes the greater penetration distance.

Figure 7-7 (b) shows the decay of jet velocity with distance from orifice. The vertical

axis is showing the jet velocity ratio (Ux/U0), where, Ux is the velocity in the X –

direction and U0 is the inlet jet velocity at the tuyere tip. Dimensionless horizontal

distance from orifice (x/d0) is plotted on the horizontal axis, where x is the horizontal

distance from the orifice and d0 is the diameter of the tuyere (d0 = 0.056 m). Predicted

jet velocity decay for air – water results from Szekely et al. [13] are also shown on the

figure. For the present simulation condition with air – slag (slag density 3900 kg/m3),

the figure shows that the jet velocity decays to nearly zero at x/d0 = 4.129, whereas

for air – water, it decays to almost zero at x/d0 = 9.95.

200

Figure 7-7 (b): Decay of gas velocity with distance from orifice

7.2.3 Bath zones

Velocity vectors inside the molten slag bath are shown in Figure 7-8. A number of

recirculation zones have been observed inside the bath, as indicated in the figure. The

recirculation zones were transient in nature. Based on the slag phase velocity vector

observation, the slag bath can be divided into three zones, namely quiescent zone,

recirculation zone and tuyere gas stream zone. Among the three zones, highest

agitation was observed at the tuyere gas stream zone inside the bath followed by the

recirculation zones. Quiescent zones are found in a number of places such as area

below and above the tuyere near the wall (l/L < 0.041) and near the bottom wall of the

modelled furnace for distance 0.2< l/L > 0.8. Mixing, turbulence, combustion and

chemical reaction rate are found as the lowest in these zones inside the bath. However,

the length of the quiescent zone near the bottom wall mentioned here is quite variable

with respect to the gas injection velocity, coal particle size, coal injection rate and

injection conditions (i.e. pressurized or un-pressurized).

201

Figure 7-8: Velocity vectors of the slag phase inside the molten slag bath (Uo = 86

m/s)

7.2.4 Fuming Behaviour

Zinc slag fuming kinetics was modelled mathematically by Richards et al. [20] by

analysing some industrial zinc fuming plant data. Based on that mathematical model,

the rate controlling steps of zinc fuming process and coal combustion behaviour had

been well described by Richards et al.[19]. The CFD model of the zinc fuming TSL

furnace developed by the present investigators (Huda et al. [156]) revealed some

interesting insights for complex metallurgical flow inside the furnace. The developed

CFD model predicted the fuming behaviour and rate controlling steps in detail for

pilot plant scale zinc fuming top submerged lance (TSL) furnace. The CFD simulation

results by Huda et al. [156] predicted that mass transfer of ZnO from the bulk slag to

the slag-gas interface and rate of gas-carbon reaction (Boudouard reaction) plays the

dominant role in overall fuming efficiency for the simulation time studied. The model

showed, within the slag bath, fuming rate was found to be higher in area of the gas-

liquid interface, where ZnO diffuses to the gas-slag interface and is being reduced by

the CO present in the gaseous phase. The model further predicted that, above the bath,

a large quantity of fine slag droplets promotes a high fuming rate. Hence fine droplet

202

generation and deeper gas penetration in the slag bath will maximize the fuming rate

for a zinc fuming TSL furnace. However, the availability of CO and carbon limits the

fuming rate in flight.

Figure 7-9: ZnO distribution in the slag bath along the axial direction from the tuyere

tip at three different heights from the bottom wall (Uo = 86 m/s)

Figure 7-10: Schematic illustration of the tuyere tip jet and coal behaviour as observed

from the present simulation

203

In this section, zinc fuming behaviour from the present investigation will be discussed

in detail. Figure 7-9 shows the % of ZnO in the slag bath along the axial direction

from the tuyere tip (l/L > 0.041) at three different heights from the bottom wall (h/H =

0.02, 0.1 and 0.2, where h is the height in the bath from the bottom wall and H is the

total height of the modelled furnace, as mentioned in Figure 4-7(a)). At h/H = 0.02,

which is the line joining the tuyere centres, injected coal entrains in the molten slag

bath. However, within the simulation time studied, no significant reduction of ZnO

from the slag at that position was observed. The average fuming rate observed at this

plane is 0.07 wt%/min. From the plant data analysis, Richards et al. [20] found that

33% of the total injected coal entrains in the slag, 55% combusts in the tuyere gas

column and 12% bypasses the bath completely. Entrained coal particles seem to have

less influence on the overall fuming. Since the coal particles are non-wetting, it does

not react directly with the ZnO, but does so via the Boudouard reaction. Within the

simulation time studied, due to the shortage of oxygen around the entrained coal

particles, no CO/CO2 generation was observed. Hence, the model predicts that ZnO

reduction process is limited by absence of CO. This finding has already been

discussed by Huda et al. [156] for a TSL furnace, that the availability of CO at the gas-

liquid interface limits the fuming rate. The present simulation also predicts that the

major portion of the injected coal (50%) is combusted in the tuyere gas column. As a

result, the products of combustion (CO, CO2 and H2O) are predicted to be in the

tuyere gas column and gas-liquid emulsion zone around the column. The presence of

CO at the gas-liquid interface reduces the ZnO present in the slag phase. As Figure 7-9

shows, at a height of h/H = 0.1 (0.5 m from the bottom wall), ZnO reduction is

significant in the gas-liquid emulsion zone. The average zinc fuming rate found at this

plane is 0.11 wt%/min. Slag volume fraction plot (Figure 7-2 (a) and Figure 7-2(b))

shows that there are significant splash formations near the wall due to the shear force

exerted by the high velocity gas jet. The slag in flight falls back to the bath surface and

creates a cavity in the bath around mid surface. A portion of the injected coal also

carried away by the high velocity gas jet which reacts in the free bath surface and

forms CO/CO2. In addition, the entrained coal particles subsequently approach to the

free bath surface, which also undergoes the Boudouard reaction. The generated CO

and agitation due to the sloshing and splashes that comes back to the surface

accelerates the mass transfer of ZnO from the bulk slag to the slag gas interface and

204

formation of Zn by the reduction process. Surprisingly, the bypassed coal un-

combusted from the tuyere gas column seemed to play some role in overall zinc

fuming from the bath surface, as shown on Figure 7-9 at the height of h/H = 0.2. The

shape of the curve in Figure 7-9 at the height of h/H = 0.2 (1.0 m from the bottom

wall) indicates that the model predicts high ZnO reduction rate from the bath surface.

Figure 7-10 is the schematic illustration the tuyere tip gas jet and coal behaviour. At

h/H = 0.2 (1.0 m from the bottom wall), % of ZnO found for the length of 0.3<l/L >

0.7 are from 0.09 to 0.11, which gives an average ZnO of 10% within that length

mentioned after 60 seconds of simulation time studied. Hence, other than the two

reaction zones mentioned by Richards et al. [21] (reduction in the slag by entrained

coal particles and generation of heat in the tuyere gas stream by combustion of un-

entrained coal), one more reaction zone is marked within the bath that contributes to

significant fuming reaction which is in the bath surface as shown in Figure 7-10. The

overall zinc fuming rate predicted at this location is 0.115 wt%/min. Industrial study

by Richards et al. [21] showed that, for Company D (Figure 5 of Richards et al. [21]),

overall zinc fuming rate was 0.125 wt%/min. Other studies reported that, batch fuming

rates for zinc fuming furnaces using pulverized coal as fuel and reductant varies

between 0.15 to 0.27 wt%/ min for slags containing about 10 wt% Zn [150] and 0.09

wt%/ min for 9 wt% Zn slag (at 1275o C temperature) [102]. From the total simulation

time studied, the highest reduction rate of ZnO was observed in the gas-liquid

emulsion zone. Hence, from the simulation results, it is clear that for the time period

studied, zinc fuming is controlled the mass transfer of ZnO from the bulk slag to the

slag-gas interface and rate of gas-carbon reaction within the bath. The rate of mass

transfer is controlled by the level of agitation and generation of turbulence within the

bath.

205

Chapter 8

206

8 Conclusions and Recommendations

8.1 Conclusions

The observations of this research can provide useful information for improving the

process optimization and operating conditions of the slag fuming furnaces, in both

TSL and conventional approach. During the first stage of this research, gas injection

characteristic into water bath was investigated by using the Computational Fluid

Dynamic (CFD) modelling technique and swirled gas injection has found to play some

role in improving the mixing process in the near vicinity of the lance tip. The

simulation results for velocity fields and generation of turbulence inside the bath has

found to be in reasonable agreement with the previous water model experimental

study of Morsi et al. [1]. A semi-empirical equation was developed for the vertical

penetration distance of the annulus air jet into the water bath from the study. The idea

of mean convective mixing by volume exchange concept had revealed that mixing was

non-uniform and concentrated near the lance for the specific air-water system studied.

A study of the mixing process by turbulence mixing through turbulent diffusion also

revealed the similar phenomena. The formation of recirculation zone in the water bath

is quite favourable in creating uniform mixing; however, the recirculation zones

observed in this study were weak for air-water system. The air-water model was used

for higher density liquid by changing the water density as an exploratory step towards

the development of the next stage work.

The pilot plant scale CFD model of the zinc slag fuming process in top submerged

lance smelting furnace was developed in the next stage by using 3D Eulerian

multiphase flow approach. The simulation results give some interesting insights for

complex metallurgical flows and transient concentrations of slag components and

gaseous species inside the molten slag bath. The simulation results predicted the

generated turbulence, splashing and plume shape in the molten slag bath. The rate of

zinc fuming from the slag bath was validated through macro-step validation process

against the pilot plant trials of zinc fuming top submerged lance furnace by Waladan

et al. [2]. Simulation results showed that increased submergence level resulted in

increased fuming rate. Overall zinc fuming rate for 1/3 lance submergence level

( LH ′′ = 1/3) was found to be 1.3 times higher than 1/5 lance submergence level

207

( LH ′′ = 1/5). Increased residence time of the generated splash with large interfacial

area above the slag bath accelerates the fuming rate from the slag in flight. The

sloshing phenomena and splashes that come back to the bath surface increase the gas-

carbon reaction on the bath surface, thus increasing the formation rate of CO, which is

responsible for increased fuming rate from the slag in flight. The simulation results

revealed that the mass transfer of ZnO from the bulk slag to the gas-slag interface and

gas-carbon reaction both play vital roles in controlling the overall fuming rate.

The developed model in the second stage was further extended to submerged coal

combustion and employed to the conventional tuyere blown zinc slag fuming process.

The model gives a clear understanding of the interesting insights for complex

metallurgical flows, tuyere tip gas jet and coal combustion behaviour and overall zinc

fuming behaviour from the slag bath. The simulation results predicted that momentum

exerted by the coal combustion process is the dominant factor for larger jet penetration

length of a tuyere blown system. Three different zone within the bath are identified

which are tuyere gas stream zone, recirculation zone and quiescent zone. Other than

the two main reaction zones mentioned by Richards et al. [21], one more reaction zone

is observed in the bath surface that contributes to significant fuming reaction The

sloshing phenomena and splashes that come back to the bath surface increase the gas-

carbon reaction on the bath surface, thus increasing the formation rate of CO, which is

accelerates the ZnO reduction process from the bath surface. Tuyere jet penetration

length ( pl ) was compared with the equation provided by Hoefele and Brimacombe

from isothermal experimental work ( ( ) ( ) 35.0

lg

46.0

Fr

o

P N7.10d

lρρ′= ) and found 2.26

times higher, which can be attributed to coal combustion and gas expansion at high

temperature. The jet expansion angle measured for the slag system studied is 85o for

the specific inlet conditions during the simulation time studied. Highest coal

penetration distance was found to be l/L = 0.2, where l distance from the tuyere tip

along the centre line and L is the total length (2.44m) of the modelled furnace. The

model also predicted that 10% of the injected coal bypasses the tuyere gas stream un-

combusted and carried to the free surface by the tuyere gas stream, which contributes

to zinc oxide reduction near the free surface.

208

8.2 Recommendations for further work

A few recommendations are now made for future work to extend the completed

research. These recommendations aim to create better understanding of the reaction

kinetics as well as zinc fuming behavior in presence of some special slag constituents.

Coal combustion modelling in the tuyere blown furnace also needs modification. The

recommendations are listed below.

First of all, in the chemical reactions considered, the effect of ferrous iron

oxidation was not taken into consideration. Ferrous iron oxidation within the

bath supposed to play some role in the overall fuming rate, as suggested by

Richards et al. [20]. Hence, inclusion of the oxidation behaviour of ferrous iron

within the bath may lead to improvement of the developed model.

The ferric iron level in the bath was considered as negligible, which also plays

some role in the overall fuming kinetics, though the percentage is small in the

slag constituents. Inclusion of the effect of ferric in the bath may also improve

the results.

In the zinc fuming TSL furnace model, carbon was added in the bath as a

reducing source, assuming only fixed carbon takes part in the reduction

reaction. No devolatilization and char oxidation model was considered, which

would have affected the results to some extent. By providing a more realistic

treatment of the behaviour of coal as a reducing agent, the model can be

improved further.

Coal combustion model incorporated in the tuyere blown furnace model

considered the coal as a continuum phase, rather than discrete particulate

phase. In addition, the coal was considered to have no moisture content, hence

no evaporation model of was considered. Though the burn out time of the

injected coal is very small (in the order of ms), the hydrodynamic effects of the

bypassed solid coal particles would have affected the overall bath behaviour.

Thus, by implementing the coupling of Lagrangian and Eulerian approach to

incorporate the behaviour of solid coal particles can be an improvement of the

model in terms of computing time.

209

Last but not the least, longer simulation time should be considered for better

understanding of the overall process. In other way, zinc fuming rate at low %

of ZnO can be investigated further, which is the scenario of the nearly ending

time of a fuming cycle.

210

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