Scale-up Strategies in Stirred and Aerated Bio Reactor
184
SCALE-UP STRATEGIES IN STIRRED AND AERATED BIOREACTOR MUHD. NAZRUL HISHAM BIN HJ. ZAINAL ALAM A thesis submitted in fulfilment of the requirements for the award of the degree of Master of Engineering (Bioprocess) Faculty of Chemical and Natural Resources Engineering Universiti Teknologi Malaysia MAY 2005
Transcript of Scale-up Strategies in Stirred and Aerated Bio Reactor
SCALE-UP STRATEGIES IN STIRRED AND AERATED BIOREACTOR
MUHD. NAZRUL HISHAM BIN HJ. ZAINAL ALAM
A thesis submitted in fulfilment of the
requirements for the award of the degree of
Master of Engineering (Bioprocess)
Faculty of Chemical and Natural Resources Engineering
Universiti Teknologi Malaysia
MAY 2005
iii
To my beloved mother and father
iv
ACKNOWLEDGEMENT
I would like to express my grateful thanks to a number of people contributed to
the completion of this thesis.
I am grateful to my supervisor, Dr. Firdausi Razali for following this project to
start and for his assistance in so many ways throughout the course of my studies. Dr.
Firdausi followed me through and helped me complete my work over a long period of
time facing many obstacles, without whom, I would not be at this point now.
I would also like to record my thanks to Mohd. Sabri Sethpa and Nor Zalina
Othman of the Chemical Engineering Pilot Plant (CEPP), Universiti Teknologi Malaysia
for their assistance, support and sharing of their knowledge during this endeavor.
I am also totally in debt to my parents whose financial assistance, time and
immense support was needed to help me complete my work. I had received numerous
helps and support from my fellow coursemates and friends, I would like to thank them.
Thanks again to Dr. Firdausi Razali, Mohd. Sabri, Nor Zalina, my family and
friends for their significant contributions to my needs during the long hours.
v
ABSTRACT
The scale-up studies based on the constant oxygen transfer coefficient (kLa)
from 16 liter to 150 liter of aerated and agitated bioreactor were performed. The
studies included the investigation on the significance of hydrodynamic difference
between Rushton and marine impeller on the kLa at 16 liter scale. By employing
both static and dynamic gassing out techniques, the kLa values were calculated at
different sets of impeller speeds and air flow rates performed in various viscosities
and temperatures in the 16 liter and 150 liter BioengineeringTM stirred bioreactor.
Empirical correlation was employed to correlate and investigate the dependence of
kLa on specific power input and superficial air velocity. Our experimental results
discovered that the Rushton turbine was more effective in gas distribution and
provide a greater oxygen transfer rate than the marine impeller. In maintaining a
constant kLa upon scale-up from 16 to 150 liter, the specific power input and the
superficial air velocity cannot be maintained, adjustment has to be done. Specific
power input from 0.0001 to 4.2 kW/m3 and superficial air velocity within the range
of 9 x 10-4 to 7 x 10-3 m/s was tested to maintain a constant value of kLa upon scale-
up in distilled water and CMC solution model. The operating variables employed at
150 liter scale successfully gave a comparable kLa values as in 16 liter scale. Hence,
the calculated scaling-up factor for impeller speed and air flow rate were 0.28 and
3.1, respectively. In order to investigate the potential of employing scaling-up
protocol developed in this work, the kinetic profiles of E.coli batch fermentation at
16 and 150 liter were compared. By employing the scaling-up factors, the proposed
scale-up protocol managed to provide the similar trend of cell growth, glucose
consumption and oxygen uptake rate upon scale-up based on the constant kLa. It
may be concluded that the similar kLa for both scales was successfully achieved by
employing the proposed scale-up protocol.
vi
ABSTRAK
Kajian pengskalaan naik berdasarkan pekali pemindahan oksigen (kLa) yang
malar daripada 16 liter ke 150 liter telah dijalankan di dalam bioreaktor teraduk
berudara. Ujikaji ini melibatkan kajian ke atas perbezaan hidrodinamik yang ketara
antara pengaduk Rushton dan marin terhadap kLa pada skala 16 liter. Dengan
melakukan teknik penyingkiran gas secara statik dan dinamik, nilai-nilai kLa dikira
pada set kelajuan putaran pengaduk dan kadar alir udara yang berbeza, kepada
pelbagai kelikatan dan suhu dalam bioreaktor (BioengineeringTM) 16 dan 150 liter.
Korelasi empirikal telah dilaksanakan untuk mengkorelasi dan mengkaji
kebergantungan kLa terhadap kuasa masukan tentu dan halaju gas luaran.
Keputusan-keputusan eksperimen menunjukkan bahawa turbin Rushton adalah lebih
efektif dalam penyebaran gas dan membekalkan kadar pemindahan oksigen yang
lebih daripada pengaduk marin. Dalam mengekalkan kLa yang malar semasa
pengskalaan naik, kuasa masukan tentu dan halaju gas luaran tidak dapat
dikekalkan, penyelarasan harus dilakukan. Kuasa masukan tentu daripada 0.0001 ke
4.2 kW/m3 dan halaju gas luaran dalam lingkungan 9 x 10-4 ke 7 x 10-3 m/s telah diuji
untuk mengekalkan nilai kLa yang malar semasa pengskalaan naik dalam model air
suling dan larutan CMC. Pembolehubah operasi yang dilaksanakan memberikan
nilai-nilai kLa yang boleh dibandingkan dengan nilai pada 16 liter. Oleh yang
demikian, faktor pengskalaan naik yang diperolehi adalah 0.28 bagi putaran
pengaduk dan 3.1 bagi kadar alir udara. Bagi mengkaji keupayaan protokol
pengskalaan naik yang dibentuk, profil-profil kinetik fermentasi E.coli pada skala 16
dan 150 liter telah dibandingkan. Dengan menggunakan faktor pengskalaan naik,
protokol pengskalaan naik yang dicadangkan berupaya memberikan perilaku yang
sama dalam pertumbuhan sel, penggunaan glukosa dan kadar penggunaan oksigen
ketika pengskalaan naik berasaskan nilai kLa yang malar. Ia mungkin dapat
disimpulkan bahawa kLa yang sama pada kedua-dua skala berjaya diperolehi dengan
pelaksanaan protokol pengskalaan naik yang dicadangkan.
vii
TABLE OF CONTENTS
CHAPTER TITLE PAGE
Declaration ii
Dedication iii
Acknowledgement iv
Abstract v
Abstrak vi
Table of Contents vii
List of Tables xi
List of Figures xiv
List of Symbols xviii
Greek Letters xx
List of Appendices xxi
1 INTRODUCTION 1
1.1 Research Background 1
1.2 Motivation 3
1.3 Research Objectives and Scope 4
viii
2 LITERATURE REVIEW 7
2.1 The Dynamics of Mass Transfer Process in Bioreactor 7
2.2 Measurement of Dissolved Oxygen 9
2.3 Factors Affecting Dissolved Oxygen Transfer in
Bioreactor
11
2.3.1 Transport of Oxygen in Gas-Liquid Phase 11
2.3.2 Effect of Bubble Size on the Oxygen Transfer 15
2.3.3 Influence of Temperature on the Oxygen
Transfer
16
2.3.4 Overall Gas Pressure and Oxygen Partial
Pressure
16
2.4 Oxygen Transfer Coefficient, kLa 18
2.4.1 Static Gassing Out Technique 19
2.4.2 Dynamic Gassing Out Technique 21
2.5 Power Consumption in Bioreactor 23
2.5.1 Reynolds Number 23
2.5.2 Power in Ungassed System 24
2.5.3 Power in Gassed System 26
2.6 Agitation and Aeration in Bioreactor 27
2.7 Oswald-de Waele Model 28
2.7.1 Carboxy Methyl Cellulose (CMC)
Characteristic
30
2.8 Scale-up: Strategies Related to Mass Transfer 31
2.8.1 Choice of Scale-Up Procedure 32
2.8.2 Scale-up on Basis of Constant Oxygen Transfer
Coefficient, kLa
33
2.8.3 Scale-up on Basis of Constant Power
Consumption per Unit Liquid Volume, Pg/VL
34
2.8.4 Scale-up on Basis of Constant Superficial
Velocity, vg
36
2.8.5 Scale-up on Basis of Constant Impeller Tip
Speed
37
ix
3 METHODOLOGY 38
3.1 Bioreactor Start-up 38
3.2 Bioreactor Dimension 39
3.3 Investigation at 16 Liter Bioreactor 41
3.3.1 Operational Conditions at 16 Liter Scale 41
3.3.2 Determination of Probe Response Time 42
3.3.3 Determination of the kLa 43
3.4 Scale-up on Constant kLa at 150 Liter Bioreactor 44
3.4.1 Scale-up Protocol 44
3.4.2 Operating Conditions at 150 Liter Scale 49
3.5 The Oxygen Transfer Coefficient Correlation 49
3.6 Rheology Measurement 51
3.6.1 Concentric Viscometer Analysis 52
3.6.2 Rheological Behavior of CMC Solution 53
3.7 Fermentation of E.coli at 16 Liter Bioreactor 55
3.7.1 Microorganism 55
3.7.2 Inoculum Preparation at 16 Liter Scale 56
3.7.3 Batch Fermentation of E.coli 56
3.7.4 Sampling and Analytical Methods 57
3.7.5 Dynamic Technique in kLa Measurement 57
3.7.6 Gravimetric Analysis 59
3.8 Test of Scale-up Approach on Live Culture 59
3.8.1 E.coli Fermentation at 150 liter Bioreactor 59
4 RESULTS AND DISCUSSION 61
4.1 Introduction 61
4.2 Hydrodynamics Difference between Rushton and
Marine Impeller
62
4.2.1 Proportional Effect of Agitation and Aeration
Rates on KLa
62
x
4.2.2 Effect of Temperature on Oxygen Transfer Rate 66
4.2.3 Rate Limiting Step of Liquid Viscosities on KLa 67
4.2.4 The Significance Difference of Specific Power
Input
69
4.2.5 The Influence of Mixing and Flow Patterns on
KLa
71
4.3 The Dependence of KLa on the Operational Parameters
at 16 Liter Scale
75
4.4 Evaluation of the Scale-up Protocol 78
4.4.1
4.4.2
4.4.3
Determination of Operating Variables at 150
Liter Bioreactor
Operating Variables on a Basis of Constant KLa
The Consequences of Scale-up Exercise Based
on Constant KLa
79
81
85
4.4.4 The Dependence of KLa on the Operational
Parameters at 150 Liter Scale
94
4.5 The Performance of E.coli Batch Fermentation at 16
and 150 Liter Scale
97
4.5.1 Dependence of KLa on the Operational
Parameter in E.coli Fermentation
100
5 CONCLUSIONS AND RECOMENDATIONS 104
5.1 Conclusions 104
5.2 Recommendations for Future Studies 106
6 REFERENCES 107
7 APPENDICES 112
xi
LIST OF TABLES
TABLE NO. TITLE PAGE
1.1 Values of parameter 'b' and 'c' from several works that
estimated from the empirical relationship proposed by
Cooper et al. (1944)
2
2.1 Different scale-up criteria and their consequences 32
3.1 Dimensions of 16 liter and 150 liter bioreactor 39
3.2 Operating conditions and techniques to determine the
oxygen transfer coefficient (kLa) reported in several works
41
3.3 Operating variables at 16 liter bioreactor 42
3.4 Operating variables at 150 liter bioreactor 49
3.5 Oswald-de Waele model at various CMC concentrations 54
3.6 Batch fermentation medium for production of E.coli 56
3.7
4.1
4.2
4.3
4.4
Operating conditions for E.coli fermentation at 150 liter
Increase of kLa values at higher operating temperature in
Rushton turbine and marine impeller at different impeller
speeds
Increase of kLa values at higher operating temperature in
Rushton turbine and marine impeller at different air flow
rates
Increase of kLa values at high broth viscosities in Rushton
turbine and marine impeller at different impeller speeds
Increase of kLa values at high broth viscosities in Rushton
turbine and marine impeller at different air flow rates
59
66
66
68
68
xii
4.5 Turbulence parameter in the 16 liter bioreactor for Rushton
turbine and marine impeller at different impeller speeds and
air flow rates
73
4.6
4.7
4.8
4.9
4.10
4.11
4.12
4.13
Comparison of experimental values of constant ‘b’ and ‘c’
between Rushton turbine and marine impeller in different
operating temperatures
Comparison of experimental values of constant ‘b’ and ‘c’
between Rushton turbine and marine impeller in different
liquid viscosities
Comparison of experimental values of constant ‘a’ between
Rushton turbine and marine impeller in different operating
temperatures
Comparison of experimental values of constant ‘a’ between
Rushton turbine and marine impeller in different liquid
viscosities
Determination of air flow rates at 150 liter scale on the basis
of constant volumetric power input with superficial velocity
Determination of impeller speeds at 150 liter scale on the
basis of constant volumetric power input with superficial
velocity
Determination of impeller speeds at 150 liter scale on the
basis of constant volumetric power input with impeller tip
speed
Determination of air flow rates at 150 liter scale on the basis
of constant volumetric power input with impeller tip speed
75
76
78
78
79
80
80
80
4.14
4.15
4.16
4.17
Base line in predetermined the operating variables at 150
liter scale
The proposed operating variables at 150 liter bioreactor
Results of the ‘trial-and-error’ step in distilled water at 30oC
Operating variables at 150 liter scale on a basis of constant
kLa
81
81
82
83
xiii
4.18
4.19
4.20
4.21
4.22
4.23
4.24
The values of constant ‘b’ and ‘c’ upon scale-up from 16
liter to 150 liter at different operating temperature in air-
water system
The values of constant ‘b’ and ‘c’ upon scale-up from 16
liter to 150 liter at different liquid viscosities in air-viscous
system
The values of range of operating parameters varied upon
scale-up from 16 liter to 150 liter at different operating
temperature in air-water system
The values of range of operating parameters varied upon
scale-up from 16 liter to 150 liter at different liquid
viscosities in air-viscous system
Comparison of constant ‘b’ between E.coli culture broth
with air-water system in 16 liter and 150 liter
Comparison of experimental values of constant ‘b’ and ‘c’
upon scale- up of E.coli fermentation from 16 liter to 150
liter
The values of range of operating parameters varied upon
scale-up from 16 liter to 150 liter in E.coli Fermentation
95
95
96
96
101
102
103
xiv
LIST OF FIGURES
FIGURE NO. TITLE PAGE
2.1 Steps for transfer of oxygen from gas bubble to cell 9
2.2 (a) Sensor response time measurement 11
2.2 (b) Integral method for measuring the sensor time constant 11
2.3 Concentration gradient for gas-liquid oxygen transfer 12
2.4 Flow patterns in agitated bioreactors as a function of
the impeller Speed (N) and the gas flow rate (Q)
15
2.5 Mass balance of oxygen transfer during aerobic
fermentation
19
2.6 Profile of dissolved oxygen concentration in static
gassing out
20
2.7 Profile of dissolved oxygen concentration in dynamic
technique
22
2.8 Power number v/s Reynolds number for various impeller
geometries
26
2.9 Deviation of pseudoplastic fluids from Newtonian fluids
behaviour
29
3.1
3.2
3.3
Geometry of the bioreactor (BioengineeringTM)
Type of agitator (a) Marine impeller (b) Rushton turbine
Scale-up protocol on basis of constant oxygen transfer
coefficient, kLa
40
41
45
3.4
3.5
The ‘trial-and-error’ loop at 150 liter scale in the scale-
up protocol
A concentric cylinder viscometer
47
52
xv
3.6 Viscosity (kg/m.s) change with shear Rate (s-1) for CMC
solution
54
3.7 Deviation from Newtonian behaviour due to CMC
presence in the fluid at 30oC
55
3.8 Steps in E.coli fermentation at 150 liter scale 60
4.1
4.2
4.3
4.4
4.5
4.6
Dependence of kLa on impeller speed, N at different
temperature for Rushton turbine and marine impeller
Dependence of kLa on impeller speed, N at different
viscosities for Rushton turbine and marine impeller
Dependence of kLa on air flow rate, Q at different
temperature for Rushton turbine and marine impeller
Dependence of kLa on air flow rate, Q at different
viscosities for Rushton turbine and marine impeller
Dependence of kLa on volumetric power consumption,
Pg/VL at different temperature for Rushton turbine and
marine impeller
Dependence of kLa on volumetric power consumption,
Pg/VL at different viscosities for Rushton turbine and
marine impeller
63
63
65
65
70
70
4.7 Flow pattern produce by impellers. (a) axial-flow (b)
radial-flow
72
4.8
4.9
Dependence of kLa on volumetric superficial air velocity,
vg at different temperature for Rushton turbine and
marine impeller
Dependence of kLa on volumetric superficial air velocity,
vg at different viscosities for Rushton turbine and marine
impeller
74
74
4.10 Dependence of kLa on impeller speed in distilled water at
different temperatures (a) T = 30oC (b) T = 40oC (c)T =
50oC
85
4.11 Dependence of kLa on impeller speed in CMC solution at
different concentrations (a) CMC 0.25%(w/v) (b) CMC
0.5%(w/v) (c) CMC 1% (w/v)
86
xvi
4.12 Dependence of kLa on volumetric power consumption in
distilled water at different temperatures (a) T = 30oC (b)
T = 40oC (c)T = 50oC
87
4.13 Dependence of kLa on volumetric power in CMC
solution at different concentrations (a) CMC 0.25%(w/v)
(b) CMC 0.5%(w/v) (c) CMC 1% (w/v)
88
4.14 Dependence of kLa on air flow rate in distilled water at
different temperatures (a) T = 30oC (b) T = 40oC (c)T =
50oC and CMC solution at different concentrations (d)
CMC 0.25%(w/v) (e) CMC 0.5%(w/v) (f) CMC 1%
(w/v)
90
4.15
4.16
4.17
Dependence of kLa on superficial air velocity in distilled
water at different temperatures (a) T = 30oC (b) T = 40oC
(c)T = 50oC
Dependence of kLa on superficial air velocity in CMC
solution at different concentrations (a) CMC 0.25%(w/v)
(b) CMC 0.5%(w/v) (c) CMC 1% (w/v)
Dependence of Reynolds number on impeller speed in
(a) water (T=30oC) (b) water (T=40oC) (c) water
(T=50oC) (d) CMC 0.25%(w/v) (e) CMC 0.5%(w/v) (f)
CMC 1% (w/v)
91
92
93
4.18 Growth curve and substrate consumption of recombinant
E.coli in 16 and 150 liter
97
4.19 Specific oxygen uptake rate of recombinant E.coli in 16
and 150 liter
98
4.20 Oxygen transfer rate of recombinant E.coli in 16 and 150
liter
99
4.21 Dependence of kLa on (a) volumetric power consumption
and (b) superficial air velocity for recombinant E.coli
fermentation
100
4.22 Comparison of dependence of kLa on volumetric power
consumption between recombinant E.coli fermentation
and air-water system in (a) 16 liter (b) 150 liter
101
xvii
4.23 Comparison of dependence of kLa on superficial air
velocity between recombinant E.coli fermentation and
air-water system in (a) 16 liter (b) 150 liter
102
xviii
LIST OF SYMBOLS
a - Specific interfacial area (m-1)
a’ - Constants in Cooper's et al. (1944) equation
A - Parameter in Meztner-Otto's equation
b - Constants in Cooper's et al. (1944) equation
c - Constants in Cooper's et al. (1944) equation
C* - Dissolved oxygen saturation concentration in liquid
or solubility (mg/L)
CoL - Initial dissolved oxygen concentration (mg/L)
CL - Dissolved oxygen concentration (mg/L)
CO2,CRIT - Critical value of dissolved oxygen concentration (mg/L)
cp - Oxygen concentration measured by sensor (-)
CX - Biomass concentration (g cell/L)
CMC - Carboxyl methyl cellulose (-)
Di
DS
-
-
Impeller diameter (m)
Sparger diameter
Dt - Tank/vessel diameter (m)
g - Acceleration due to gravity (m.s-2)
H
HL
-
-
Henry’s law constant (kPa.L/mg)
Liquid height
HT - Tank/vessel height (m)
kG - Gas phase oxygen transfer coefficient (s-1 or hr-1)
kL - Liquid phase oxygen transfer coefficient (s-1 or hr-1)
KG - Overall gas phase oxygen transfer coefficient (s-1 or hr-1)
KL - Overall liquid phase oxygen transfer coefficient (s-1 or hr-1)
xix
kLa - Volumetric oxygen transfer coefficient (s-1 or hr-1)
m - Constant in Michel & Miller's equation
n - Flow behaviour index in power-law model (-)
N - Impeller speed (rpm)
Np - Power number (-)
NA - Aeration number (-)
NFR - Froudes number (-)
NRE - Reynolds number (-)
pAG - Partial pressure of oxygen (kPa)
pT - Total pressure of system (kPa)
Po - Ungassed power consumption (W)
Pg - Gassed power consumption (W)
Q - Air flow rate (m3/s)
Qo - Overall oxygen uptake rate per unit volume of broth (mg O2/L.s)
qO2 - Specific oxygen uptake rate per gram cells (mg O2/g cell.s)
rO2 - Specific oxygen uptake rate per gram cells (mg O2/g cell.s)
t
Ti
-
-
Time (s or hr)
Impeller thickness
V’i - Impeller tip speed
VL
VT
-
-
Liquid volume (m3)
Total volume
vg - Superficial air velocity (m/s)
(w/v)
Wi
-
-
Mass per unit volume (-)
Impeller width
X - Dry cell weight (g cell/L)
yA - Mole fraction of oxygen in gas phase (-)
yAG - Mole fraction of oxygen in gas phase (-)
xx
GREEK LETTERS
C
i
E.coli
-
-
-
Spacing between impeller
Top impeller distance from top plate
Escherichia coli
k - Consistency index in power-law model (Pa.sn)
- Shear rate (s-1)
L - Liquid viscosity (kg/m.s)
app - Apparent viscosity in Oswald-de Waele model (Pa.s)
- Shear stress (N/m2)
L - Liquid density (kg/m3)
xxi
LIST OF APPENDICES
APPENDIX TITLE PAGE
A1 Specification of Dissolved Oxygen Electrode 112
A2 Derivation of Concentric Viscometer Analysis 117
B Rheology Analysis on Carboxy Methyl Cellulose
(CMC)
119
C1 Static Gassing-Out Technique Calculation 123
C2 Dynamic Gassing-Out Technique Calculation 129
C3 Gravimetric Analysis 133
D1 Summary for Analysis at 16 Liter Scale for Turbine
Impeller
134
D2 Summary for Analysis at 16 Liter Scale for Marine
Impeller
138
D3 Results for the Determination of Operating Variables at
150 liter Bioreactor
142
D4 Summary for Analysis at 150 Liter 148
E1 Summary of E.coli Fermentation at 16 Liter Scale 152
E2 Summary of E.coli Fermentation at 150 Liter Scale 155
F F-Test for Equality of Kinetic Profiles at 16 and 150
liter E.coli Fermentation
159
CHAPTER 1
INTRODUCTION
1.1 Research Background
In the aerobic fermentations, sufficient supply of oxygen to the
microorganisms is very crucial. Oxygen is sparingly soluble in the water (i.e. 10
ppm at 1 atm) and its transfer rate is always limited particularly through the gas-
liquid interfaces (Bailey and Ollis, 1986). The limited solubility of oxygen in water
is a physical constraint on bioreactor aerobic operation. This problem becomes
worse especially in the larger scales since maintaining such homogeneous
environment is no longer easy due to increased mixing time. The consequent
anaerobic conditions result in lower fermentation performance and yields.
Systematic engineering approaches to tackle this problem have been reported by a
number of works (Arjunwadkar et al., 1998; Badino Jr et al., 2001, Cooper et al.,
1944). The oxygen transfer capacity in a bioreactor depends on the mechanical
design and geometry of the air distributor, bioreactor aspect ratio, impeller type, and
the agitation rate. All of them can be related to the oxygen transfer coefficient (kLa).
Cooper and his co-workers (1944) proposed that the kLa may be empirically
linked to the gassed power consumption per unit volume of broth (Pg/VL) and the
superficial air velocity (vg) as described by the following equation.
c
g
b
L
gL v
V
Paak ' (1.1)
2
In this equation, the values of the constants 'b' and 'c' may vary considerably,
depends on the bioreactor geometry and operating conditions. Data in Table 1.1
summarise the values of constant 'b' and 'c' from several works. Constant ‘b’
represents the level of dependence of kLa on the agitation, while, constant ‘c’
represents the level of dependence of kLa on the sparging rate applied to the system.
Table 1.1 Values of parameter 'b' and 'c' from several works that estimated from
the empirical relationship proposed by Cooper et al. (1944)
Author Constant‘b’
Constant‘c’
Type of impeller
LiquidModel
LiquidVolume
Cooper et al.(1944)
0.95 0.67 N/A Air-watersystem
66 L
Shukla et al.(2001)
0.68 0.58 Disc turbine and pitched
bladeturbine
Air-water system
5.125 L
Shukla etal.((2001)
0.725 0.892 Disc turbine and pitched
bladeturbine
Yeastfermented
broth
5.125 L
Badino Jr. etal. (2001) 0.47 0.39
Flat-bladedisc style turbine
Aspergillus’sfermented
broth
10 L
Martinov & Vlaev (2002)
0.84 0.4 Narcissusblade
(2% w/v) CMC solution
50 L
Martinov & Vlaev (2002)
0.82 0.4 Narcissusblade
(0.5% w/v) Xanthan gum
solution
50 L
Arjunwadkaret al. (1998)
0.68 0.4 Disc turbine and pitched
bladeturbine
(0.7% w/v) CMC solution
5.125 L
As supplying adequate oxygen is the centre of the issue in aerobic
fermentation, maintaining a similar oxygen transfer coefficient or kLa has been
frequently employed as the basis of scaling up exercises. Scale-up criteria that
commonly used to maintain constant kLa are i) the gassed power number per unit
liquid volume (Pg/VL), the superficial air velocity (vg), the sparging rate (vvm) and
bioreactor geometrical and operational constants such as ratio of liquid height to tank
diameter (Hi/DT), impeller diameter (Di), impeller rotation number (N), impeller tip
3
speed (NDi), pump rate of impeller (Q), pump rate of impeller per unit volume (Q/V)
and Reynolds number.
1.2 Motivation
The oxygen transfer coefficient, kLa plays an important role towards carrying
out the design, scaling up and economic of the process. Efforts have been focused in
improving the design and scaling up studies to achieve adequate supply of oxygen at
higher scales (Martinov & Vlaev, 2001, Juarez & Orejas, 2001, Arjunwaadkar et al.,
1998). Their works employed the correlation proposed by Cooper et al. (1944) and
demonstrated the effects of agitation and aeration at different combination of
impellers in prediction of kLa values at the laboratory scales. The most commonly
methods in determining the kLa are the static and the dynamic gassing-out
techniques. As contrast to the static gassing-out technique, the live culture was used
in the dynamic gassing-out technique. Both of these techniques have been employed
by Martinov & Vlaev (2001), Juarez & Orejas (2001), Arjunwaadkar et al. (1998)
and Shukla et al. (2001).
Scaling up studies performed in this work used the correlation developed by
Cooper et al. (1944). The kLa values achieved at 16 liter scale were compared with
the values at 150 liter scale. Since the scaling up factor is not proportionally
increasing, the ‘trial-and-error’ within predicted range was performed. The
effectiveness of this scaling up protocol was tested in the real E.coli fermentation.
Identical growth profiles at both scales conclude that comparable oxygen transfer at
150 liter was successfully achieved. There has been a significant advance in the
understanding of scale-up of stirred aerated bioreactors as reported by several
authors. Shukla et al. (2001) works highlight on the performance of the impeller
used upon scaling up of yeast biotransformation medium on a basis of constant kLa.
Wong et al. (2003) employed the correlations proposed by Wang et al. (1979) in
scaling up on a basis of constant kLa and air flow rate per unit volume, (Q/V). The
work by Hensirisak (1997) concerned more on the performance of microbubble
dispersion to improved oxygen transfer upon scale-up. The work by Wernesson &
4
Tragardh (1999) reported the influence of power input per unit mass on the
hydrodynamics of the bioreactor.
In spite of these observations, the engineering focus continued to be on
maintaining the volumetric oxygen transfer constant on scale-up. Humphrey et al.
(1972) addressed that; researchers still do not have an absolute basis for scale-up. As
a matter of fact, biochemical engineers still practice scale-up a black art in which
they attempt to maintain constant and operating the aeration rate well below gas
flooding conditions. In this study, scale-up strategy proposed by Shukla et al. (2001)
and Garcia-Ochoa et al. (2000) will be further improved. The challenge and aims of
this study is to manipulate the constant in the empirical correlation proposed by
Cooper et al. (1944) and provide a scaling-up factor upon scale-up from 16 liter to
150 liter scale in a basis of constant kLa.
1.3 Research Objectives and Scope
The objectives of this research are:
1) To investigate the significance of hydrodynamic difference between Rushton
turbine and marine impellers on the oxygen transfer in 16 liter bioreactor.
2) To develop a simple approach that provides a reliable protocol for scaling-up
exercise based on constant oxygen transfer rate in stirred aerated bioreactor.
3) To evaluate the potential of employing the scaling-up protocol developed in
this study in the actual fermentation.
In order to achieve these objectives, the following scope of work shall be covered:
1) Evaluation of oxygen transfer coefficient, kLa by using static and dynamic
gassing-out techniques.
5
2) Study the effect of fermentation system and operational parameters by:
i) Vary impeller speeds, volumetric air flow rate and temperature in 16
liter bioreactor.
ii) Mimic a pseudoplastic behaviour by using carboxy methyl cellulose
(CMC) to compare the effect of Newtonian and non-Newtonian fluids
on kLa.
3) Investigate the dependence of oxygen transfer coefficient on superficial air
velocity and volumetric gassed power input at 16 liter bioreactor using
Rushton turbine and marine impeller.
4) Investigates the effect of impeller type on the dependence of oxygen transfer
coefficient on superficial air velocity and volumetric gassed power input in:
i) 16 liter and 150 liter at different viscosities namely 0.25, 0.5 and 1
%(w/v) of CMC solutions.
ii) 16 liter and 150 liter bioreactor at different temperatures namely 30o,
40o and 50 oC.
5) Graphically determine, compare, and analyze the coefficients in the empirical
correlation proposed by Cooper et al. (1944) at:
i) 16 liters for Rushton turbine and marine impeller.
ii) 16 liter and 150 liter at different viscosities namely 0.25, 0.5 and 1
%(w/v) of CMC solutions.
iii) 16 liter and 150 liter bioreactor at different temperatures namely 30o,
40o and 50 oC.
6
6) Compare time-course profiles of growth, glucose consumption, specific
oxygen uptake rate (OUR), and kLa at 16 liter and 150 liter bioreactor.
CHAPTER 2
LITERATURE REVIEW
2.1 The Dynamics of Mass Transfer Process in Bioreactor
In the bioreactors, cell-growth is promoted or maintained to allow the
formation of products such as a metabolite (e.g. antibiotic substances, alcohol and
citric acid), biomass (e.g. Baker’s yeast or Single Cell Protein), transformed
substrate, or purified solvent (e.g. in water reclaimation). System based on macro-
organism cultures (consisting of mammalian or plant cells) are usually referred to as
“tissue cultures” while those based on dispersed non-tissue forming cultures of
microorganisms such as bacteria, yeast and fungi are loosely referred to as
“microbial” reactors (Moo-Young & Blanch, 1981). In enzyme reactors, substrate
transformation is promoted without the life support system of whole cells (enzymic
saccharification of polysaccharides to make syrup). Frequently these reactors
employ “immobilized-enzymes” where solid or semi-solid supports are used to
internally entrap or externally attach the biocatalyst so that it is not lost as in “free
enzyme” systems, and may be reused in a process.
In virtually all of these reactors, several phases are involved and substrates
and nutrients must be transferred from one phase to another. To be effective in
achieving the desired degree of conversion of reactants to products or supplying
sufficient nutrients for maintenance of cell viability, interphase heat and mass
8
transfer must occur to a sufficient extent. One of the key nutrients for all aerobic
cells is oxygen, which is sparingly soluble in water. Supply of oxygen from the gas
phase to the liquid phase is critical in most aerobic fermentations (Bailey and Ollis,
1986). These are to maximise the air sparging rate to place as much air (oxygen) into
contact with the liquid and also maximise the agitation of the liquid which will help
to break-up the air bubble to the smallest possible. Minimizing the bubble size,
maximise its surface area will minimise the thickness of the liquid film surrounding
the bubble and reduce the limiting factor of the oxygen transfer into liquid and
eventually to the organism (Michael, 1997) as illustrated in Figure 2.1. The transfer
of oxygen from gas bubble to cell is described in the following steps.
(i) Transfer through the bulk gas phase is relative fast.
(ii) The gas-liquid interface itself contributes negligible resistance.
(iii) The liquid film around the bubbles is a major resistance to oxygen
transfer.
(iv) In a well-mixed bioreactor, concentration gradients in the bulk liquid are
minimised and mass transfer resistance in this region is small. However,
rapid mixing can be difficult to achieve in viscous fermentation broths or
in very large bioreactors; if this is the case, oxygen transfer resistance in
the bulk liquid may be an important factor.
(v) Because single cells are much smaller than gas bubbles, the liquid film
surrounding each cell is much thinner than the film surrounding the
bubbles, the liquid film surrounding transfer can generally be neglected.
On the other hand, if cells form “large” clumps, the liquid film resistance
can be great enough to be significant.
(vi) Resistance at the cell-liquid interface is small enough to generally
neglected.
(vii) When the cells are in clumps, intra-particle resistance is likely to be
significant as the oxygen must diffuse through a large solid pellet of cells
to reach the individual interior cells. The magnitude of this resistance
depends on the size of the clumps, the larger the clump, the more
resistance.
9
(viii) Intra-cellular oxygen-transfer resistance is negligible because of the very
small distances of transfer.
Figure 2.1 Steps for transfer of oxygen from gas bubble to cell (Doran, 1996)
2.2 Measurement of Dissolved Oxygen
The type of electrode used in this study is a polarographic electrode. The
basic arrangement for the polarographic electrode is given in Figure A.1 in Appendix
A1. A polarographic electrode usually contains a platinum or gold cathode, a silver
or silver chloride anode and potassium chloride as electrolyte. For the polarographic
electrodes, the reaction proceeds as follows.
Cathodic reaction : O2 + 2H2O + 2e- H2O2 + 2 OH-
H2O2 + 2e- 2 OH-
Anodic reaction : Ag + Cl- AgCl + e-
Overall reaction : 4Ag + O2 + 2 H2O + 4 Cl- 4 AgCl + 4 OH-
10
The main components of the sensors are the oxygen permeable membrane,
the working electrode, the electrolyte solution and a possible reference electrode. A
voltage is applied between the gold (platinum or silver) cathode and the anode that
consists of either lead or silver (Ag/AgCl), and causes the oxygen to react
electrochemically. Increasing of the oxygen concentration will results a higher
electric current. The current in the sensor is measured and, after calibration,
converted into dissolved oxygen concentration. The reaction tends to produce
alkalinity in the medium together with a small amount of hydrogen peroxide. The
chloride ions are provided by the KCl electrolyte solution. For this reason and for
removing these alkaline hydroxide ions, the solution has to be replaced from time to
time (James, 1992). The other important parameter of the sensor is the response
time. It can be measured by making a step change in oxygen partial pressure in the
measurement medium and measuring the sensor response. The sensor can be
approximated as a first order system:
dt
dccc p
pp (2.1)
Where
c = oxygen concentration in the measurement sample
cp = oxygen concentration measured by the sensor
p = sensor time constant
The time constant, p is the time when the sensor response reaches 63.7% of
the ultimate response as shown in Figure 2.2. The significant of the sensor response
time has been reported by several authors namely Nielsen et al. (2003), Badino et al.
(2001) and Martinov & Vlaev (2002).
11
timep
c
c p
0.36
1.0 1.0
(a) (b)
Area above the curveis p
time
c
c p1
Figure 2.2 (a) Sensor response time measurement (b) Integral method for
measuring the sensor time constant
2.3 Factors Affecting Dissolved Oxygen Transfer in Bioreactor
2.3.1 Transport of Oxygen in Gas-Liquid Phase
Diffusion of molecules occurs in the direction required to eliminate the
concentration gradient. If the gradient is maintained by a constant supply of oxygen
to the region of the lower concentration, then the diffusion will be continuous. This
system is often used in mass transfer operations (Michael, 1997). Transfer of a
solute such as oxygen from the gas phase to the liquid can be represented in the
schematic diagram as shown in Figure 2.3.
12
Figure 2.3 Concentration gradient for gas-liquid oxygen transfer (Doran, 1996)
Oxygen is transferred from the gas phase into the liquid phase. The
concentration of oxygen in the bulk liquid phase is CAL and at the gas-liquid interface
in the liquid is CALi. The concentration of oxygen in the bulk gas phase is CAG and at
the gas-liquid interface in the gas is CAGi. The rate of mass transfer of the oxygen
through the gas boundary layer is:
NAG = kGa (CAG – CAGi) (2.2)
Similarly, the rate of oxygen transfer through the liquid boundary is:
NAL = kLa (CALi – CAL) (2.3)
where
kG = gas phase oxygen transfer coefficient
kL = liquid phase oxygen transfer coefficient
If we assume that equilibrium exists at the interface, we can write:
ALiAGi mCC (2.4)
13
where m = distribution factor
Incorporating the equilibrium relationship into 2.2 and 2.3 we obtain the results:
ALAGLG
A mCCak
m
akN
1 (2.5)
and
ALAG
LGA C
m
C
akamkN
11 (2.6)
Where the overall gas-phase oxygen transfer coefficient, KG is defined by the
equation:
ak
m
akaK LGG
11 (2.7)
Similarly, the overall liquid phase oxygen transfer coefficient, KL is defined by the
equation:
akamkaK LGL
111 (2.8)
Equation 2.8 is the mass transfer relationship of interest. Therefore, from
rearranging Equations 2.6 and 2.8 we can write the equation:
ALAG
LA Cm
CaKN (2.9)
and using the equilibrium concentration expressed as:
14
ALAG C
m
C * (2.10)
Which is the liquid-phase concentration of oxygen (known as the solubility C*AL) in
equilibrium with CAG, we come up with Equation 2.11 from combination of Equation
2.9 and 2.10.
NA = KLa (C*AL – CAL) (2.11)
It is generally difficult to evaluate the interfacial area (a); however, when a
gas is sparged through a liquid, the interfacial area will depend on the size and
number of gas particles present. This also depends on other factors such as medium
composition, stirrer speed and gas flow rate (Michael, 1997). Oxygen is poorly
soluble gas in the liquid, then the liquid phase oxygen transfer resistance dominates
in Equation 2.8 and kGa is much larger than kLa and means that KLa is approximately
equal to kLa and the equation simplifies to:
NA = kLa (C*AL – CAL) (2.12)
Since 1/mkGa is approximately equal to zero.
Where
NA = rate of oxygen transfer per unit volume of fluid (g mol/m3s)
kL = liquid-phase oxygen transfer coefficient (m/s)
a = gas-liquid interfacial area per unit volume (m2/m3)
CAL = actual dissolved oxygen concentration in the broth (g mol/m3s)
C*AL = oxygen concentration in the equilibrium with the gas phase
(g mol/m3s), also known as the solubility
The difference (C*AL – CAL) between the maximum possible and actual
oxygen concentrations in the liquid represents the concentration difference driving
force for mass transfer.
15
2.3.2 Effect of Bubble Size on the Oxygen Transfer
The effects of the bubble size have been investigated by Al-Masry (1999).
The most important property of air bubbles in the bioreactor is their size. More
interfacial area (a) is provided if the gas is disintegrated into small bubbles and
provide a better gas dispersion in the bioreactor. As illustrated in Figure 2.4, the
flow patterns in agitated air sparged bioreactors is a function of both impeller speed
(N) and the air sparging rate (Q), both of which also affect the bubble size and the
number of bubbles. Therefore this, affects the interfacial area (a) available for mass
transfer. For a given volume of gas, more interfacial area (a) is provided if the gas is
dispersed into many small bubbles rather than a few large ones. Since the efficiency
of oxygen transport is approximately proportional to the ratio of the bubble surface
area to the bubble volume, the smaller size of the micro bubbles increased oxygen
transfer rate in the bioreactor. In addition, smaller bubbles have a longer dwell time
in liquid because of their slower bubble-rise velocities, allowing more time for the
oxygen to dissolve (Doran, 1996).
Figure 2.4 Flow patterns in agitated bioreactors as a function of impeller speed
(N) and the gas flow rate (Q) (Doran, 1996)
16
2.3.3 Influence of Temperature on the Oxygen Transfer
The temperature of an aerobic fermentation affects both the overall solubility
of the oxygen, C*AL and the mass transfer coefficient, kLa. As reported by Nielsen et
al. (2003), when temperature is increased, the solubility of the oxygen C*AL drops, so
the driving force the oxygen transfer (C*AL-CA) is reduced. At the same time,
diffusivity of the liquid surrounding the bubbles is increased, resulting in an
increased in the value of kLa. The temperature between 30oC to 50oC used in this
study is within the range at which the rate of oxygen transfer is more likely to
increase. However, at much higher temperature than 40oC, the solubility of the
oxygen drops significantly, adversely affecting the oxygen transfer driving force. In
addition, with the increased of temperature, dissolved oxygen tends to pass through
the liquid-film resistance and escapes to atmosphere due to evaporation. The
significant of the oxygen solubility was specifically described in Perry & Green
(1997).
2.3.4 Overall Gas Pressure and Oxygen Partial Pressure
The total pressure and the oxygen partial pressure used during the aeration of
the broth affect the value of the solubility of the dissolved oxygen. For solutions, the
equilibrium relationship between these parameters follows Henry’s Law.
PAG = PT yAG = HC*AL (2.13)
where
PAG = partial pressure of oxygen (kPa)
PT = total pressure of the system (kPa)
yAG = mole fraction of oxygen in the gas phase (dimensionless)
H = Henry’s Law constant (kPa.L/mg)
C*AL = solubility of oxygen in the liquid (mg/L)
17
If the total pressure or the concentration of oxygen is increased at constant
temperature, the solubility increases and therefore the mass transfer also increase. It
must be remembered that the dissolved oxygen electrode, whether galvanic or
polarographic measures the oxygen partial pressure in the fermentation broth and not
the dissolved oxygen concentration directly. To convert this to dissolved oxygen
concentration, it is necessary to know the solubility of oxygen in the liquid at the
temperature and partial pressure of measurement (Doran, 1996). Without prior
knowledge of the oxygen solubility in the solution of interest, the oxygen
concentration in mg O2/ L (CL) cannot be determined directly with a sensor. The
solubility of gases in liquid media for slightly to moderate soluble gases is described
by Henry’s law (Perry & Green, 1997):
AA
A yH
P
H
PC (2.14)
Where
CA = concentration in the liquid phase (mg/L)
PA = gas phase partial pressure of oxygen (atm)
H = Henry’s coefficient (atm-liter/mg)
yA = mole fraction of oxygen in the gas phase
The solubility of oxygen in the broth is a function of the media composition,
temperature and pressure. The dependency with temperature and pressure can be
quantified accurately enough by applying Henry’s law. However, the dependency
with the medium composition is rather difficult to describe and is normally neglected
(Pirt, 1975).
18
2.4 Oxygen Transfer Coefficient, kLa
KLa indicates the rate of oxygen transfer in the fermentation broth. To
determine the total oxygen transfer rate in a bioreactor, the total surface area
available for mass transfer, a, has to be known. Separate determination of kL and “a”
is difficult to evaluate and sometimes impossible. The combined term of kLa is
usually reported as the oxygen transfer coefficient rather than just kL (Doran, 1996).
Charles and Wilson (1994) reported that rate of mass transfer is directly proportional
to the driving force for transfer and the area available for the transport process to take
place. Generally, techniques for the measurement of kLa values in aerated and stirred
vessels are dependant on an unsteady state mass balance for the system as illustrated
in Figure 2.5.
A number of correlations have been reported by several workers namely Ryu
and Humphrey (1972), Yagi and Yoshida (1975) and Zlokarnik (1978). However,
despite it simplicity, Equation 2.15 has been frequently employed in many works as
summarised in Table 1.1. The kLa correlations employed in this work relate the kLa
to the gassed power consumption per unit volume of broth (Pg/VL) and the superficial
gas velocity (vg) as originally proposed by Cooper et al. (1944).
cg
b
L
gL v
V
Paak ' (2.15)
Where the values of the constants b and c may vary considerably, depends on the
system geometry, the range of variables covered and the experimental methodology
used.
19
Gas flow outOxygen out
Oxygen absorbed byorganism= x Q O2
Oxygen transfer= KLa (C* - C)
LIQUIDPHASE
GASPHASE
Gas flow in Oxygen in
Figure 2.5 Mass balance of oxygen transfer during aerobic fermentation (Charles
& Wilson, 1994)
2.4.1 Static Gassing-Out Technique
In this technique, first described by Wise (1951), the oxygen concentration of
the solution is lowered by gassing the liquid out with nitrogen gas, so that the
solution is scrubbed free of oxygen. The deoxygenated liquid is then aerated and
agitated and the increase in dissolved oxygen was monitored using the dissolved
oxygen probe. The profile for static gassing out method is illustrated in Figure 2.6
(Stanbury and Whitaker, 1984). The rate of oxygen transfer given by Equation 2.12
is used to calculate the kLa value:
NA = kLa (C* – CL) (2.12)
20
Air OnN2 Off
Air OffN2 OnCL
t
Figure 2.6 Profile of dissolved oxygen concentration in static gassing out
technique (Stanbury & Whitaker, 1984)
In practical, experiments are carried out commencing from an oxygen free liquid and
the oxygen concentration will rise such that:
dt
dCN L
A (2.16)
Assuming that the liquid is well mixed and there is no oxygen uptake. Combining
both Equation 2.12 and 2.16 we obtain:
LLL CCak
dt
dC * (2.17)
Basically, C* was assumed to be constant and integrating both side of Equation 2.17
with respect to time in order to calculate the kLa value:
L
Lo
C
C
t
LLL
dtakdCCC 0
*
1 (2.18)
L
Lo
L CC
CC
tak
*
*
ln1
(2.19)
21
The oxygen transfer coefficient, kLa, is calculate by plotting a graph of ln [(C*-
CoL)/(C*-CL)] against time. It would give a straight line through the origin and slope
of the graph is kLa. This technique was recently practiced by Martinov & Vlaev
(2002), Shukla et al. (2001), Arjunwadkar et al. (1998) and Nielsen et al. (2003). It
was adopted in this work because of its simplicity. VantRiet and Tramper (1991)
suggested that this method should not be employed for vessel over one meter high.
2.4.2 Dynamic Gassing-Out Technique
The dynamic gassing-out technique is based on the respiratory action of a
growing culture to vary the oxygen concentration in the broth (Taguchi and
Humprey, 1966). The procedure involves switching off the air supply so that the
oxygen concentration in the broth falls due to the respiratory activity of the biomass.
The air supply is switched off when the dissolved oxygen level of the bioreactor is at
steady state. Garcia-Ochoa et al. (2000) reported that, it is important not to switch
off the air supply for too long because the metabolism of the organism will slow
down. In some cases the organism will switch to anaerobic respiration. In either
case the results are affected adversely. The decrease of dissolved oxygen level can
be described in the following equation.
xOL Cr
dt
dC2
(2.20)
Where
CL = actual dissolved oxygen concentration in the broth
(g mol/m3s)
rO2 = specific respiration rate (mmoles O2/g cells.h)
Cx = dry weight of cells per volume (g cell mass/m3)
After a time, the air supply is switched back on and the oxygen concentration will
rise again until it returns to the initial steady state value. The oxygen material
balance in an aerated batch bioreactor with growing organisms is given by:
22
xOLLL CrCCak
dt
dC2
* (2.21)
Where
kL a = liquid-phase oxygen transfer coefficient (hr-1)
C* = oxygen concentration in the equilibrium with the gas phase
(g mol/m3s), also known as the solubility
The equation can be rearranged to result in a linear relationship as:
xOL
LL Cr
dt
dC
akCC
2
1* (2.22)
The term, rO2Cx, can be obtained by measuring the slope of the CL v/s time
curve in Figure 2.7. Therefore, from Equation 2.22, the plot of CL versus (dCL/dt
+rO2Cx) will results in a straight line which has the slope of (-1/kLa) and the y-axis
intercept of C*. Similar dynamic gassing-out technique was performed by Badino et
al. (2001) and Garcia-Ochoa et al. (2000).
dt
dCLAir On
Air OffCL
t
Figure 2.7 Profile of dissolved oxygen concentration in dynamic gassing out
technique (Garcia-Ochoa et al., 2000)
23
2.5 Power Consumption in Bioreactor
Knowledge and information of the power requirement in bioreactors is
required for scaling up exercise. The power correlation employed in this work is
similar to the power correlation employed in Badino et al. (2001) and Shukla et al.
(2001). In general, power consumption in bioreactor depends on the dimensionless
power number, NP and Reynolds number, NRe as summarised by Rushton et al.
(1950).
2.5.1 Reynolds Number
Stirring enhances the transport of nutrients especially oxygen in the culture
liquid. In turbulent flow, two molecules of liquid move in relation of each other.
The relative velocity between the nutrient solution and the individual cell should be
about 0.5 m s-1 (Mohamad et al., 2001). Types of flow can be characterized by the
dimensionless Reynolds number, NRe. The Reynolds number is calculated as
follows:
L
LiNDN
2
Re (2.23)
Where Di = impeller diameter
N = impeller speed (rps)
L = liquid density (kg/m3)
L = liquid viscosity (Newton.sec/m2)
The Reynolds number describes the flow only at periphery of the stirrer. To
distribute the turbulence homogenously within the entire reactor, an impeller of
appropriate shape and diameter must be used. The flow rate is crucial to the
distribution of turbulence. However, as turbulence may damage filamentous
organisms, there are frequently limitations on how fast a system can be stirred. The
24
definition of the Reynolds number for non-Newtonian is much more complicated
since the apparent viscosity is not constant for non-Newtonian fluids and varies with
the shear rates or velocity gradients in the vessel. Calculation of power consumption
in bioreactor for non-Newtonian fluids basically is same as the Newtonian fluids,
with some modification on the Reynolds number. Reynolds number used is as
follows (Geankoplis, 1993).
app
LiNDN
2
Re (2.24)
2.5.2 Power in Ungassed System
Rushton et al. (1950) summarised that the power consumption for a given
system cannot be predicted theoretically, therefore empirical correlations have been
developed to predict the power required. The power consumption for stirring non-
aerated fluids depends upon fluid properties, L and L, the stirrer rotation rate, N
and the impeller diameter, Di. The latter is expected to vary with impeller Reynolds
number in a different manner for each flow regime: laminar, transition or turbulent.
Ungassed power consumption (Po) was obtained through a graph of power number
(Np) as a function of Reynolds number (NRe) for both Newtonian and non-Newtonian
fluid in a different type of flow regime.
The power number, Np is generally used for correlating agitator power
requirement. It is not the motor requirement because of the friction losses. The
power number has been defined as a dimensionless parameter relating to the energy
required by stirred bioreactors. It is calculated as follows.
p
iL
o NDN
P53
(2.25)
25
Where
Po = power in ungassed system (W)
Ni = impeller speed (rps)
L = liquid density (kg/m3)
Di = impeller diameter (m)
The power number was correlated with Reynolds number for several types of stirrer
as shown in Figure 2.8. In the turbulent regime, the Reynolds number is large,
inertial forces dominate viscous forces and thus the dependence of the power number
on the Reynolds number will vanish. Therefore power input is independent of
Reynolds number.
(2.26)53iio DNP
Where Np = constant
As in the laminar flow, the relation is more nearly given by:
or32iio DNP
Re1
pN (2.27)
In the transient range of mixing speed (NRe = 10 to 104), there is no simple
correlation between the power number and the Reynolds number. Disc impellers
have a higher power number than flat blade or propeller stirrers. In bioreactors
where a vortex is formed, another dimensionless number, Froudes number is useful.
It is described as follows:
g
DNN i
Fr
2
(2.28)
Where
g = gravitational acceleration, 9.81 m s-2
26
Figure 2.8 Power number Vs Reynolds number for various impeller geometries
(Aiba et al., 1973)
2.5.3 Power in Gassed System
The power required to agitate gassed liquid systems is less than for ungassed
liquids since the apparent density and viscosity of the liquid phase decrease upon
gassing. When gas is introduced into an agitated tank, the bulk liquid density and
viscosity in the tank decrease as a result of the formation of gas dispersion. This
alteration of the fluid properties is reflected in changes to the power required for
agitation. At low impeller speeds, the gas rises through the impeller region without
being effectively dispersed. This condition is known as flooding. At higher impeller
speeds beyond the point of flooding, there is a reduction in the power drawn by the
impeller due to the change in the overall liquid density. This reduction in power has
been correlated with the aeration number. The reduction in gassed system power,
Pg/Po is generally given as a function of the ratio of the superficial air velocity to the
impeller tip speed (Bailey and Ollis, 1986).
Ao
g NfP
P (2.29)
27
Where aeration number,3i
A ND
QN (2.30)
and superficial air velocity,2
4
tg D
Qv (2.31)
As reported by Chia-Hua Hsu (2003), superficial air velocity is the average
speed of bubble velocity which rising from the bottom of bioreactor to the liquid
surface. It is strongly affected by a liquid dispersion and an important factor for
bioreactor design. The gassed power consumption (Pg) was estimated through a
traditional correlation, proposed by Michel and Miller (1962), obtained for
experimental system used in cultivations:
45.0
56.0
32
Q
NDPmP io
g (2.32)
Where
m = constant (depends on impeller type and geometric form)
Q = volumetric gas flow rate (m3/s)
2.6 Agitation and Aeration in Bioreactor
The degree of agitation has been demonstrated to have profound effect on the
oxygen transfer efficiency of an agitated bioreactor. Banks (1977) claimed that
agitation assisted oxygen transfer in many ways. Agitation increases the area
available for oxygen transfer by dispersing the air in the culture fluid in the form of
small bubbles. Agitation also delays the escape and prevents coalescence of air-
bubbles. Banks (1977) also reported that agitation decreases the thickness of liquid
film at gas-liquid interface by creating turbulence in the culture fluid. Aeration
supplies the necessary oxygen to the microorganism agitation maintains uniform
conditions within the bioreactor. Another reason for air sparging and mechanical
28
mixing in bioreactor is to remove carbon dioxide and other possible toxic gaseous
metabolic byproducts which are produced in the broth (Hensirisak, 1997).
Geankoplis (1993) has proved the importance of baffles in increasing the turbulence
within bioreactor and prevent entrainment of bubbles in the vortex that would
damage the cells.
Martinov & Vlaev (2002), Shukla et al. (2001) and Arjunwadkar et al. (1998)
demonstrated the influenced of aeration and agitation on oxygen transfer of
bioreactor at various scale. Hensirisak (1997) observed that direct sparging of gases
into a stirred bioreactor may be most critical than agitation to the health of cultured
cells. In most cases, the impeller must provide enough mixing to keep cells or gasses
homogenously while creating as little fluid force as possible. These effects need to
be minimized by reducing the impeller tip speed and power input per unit volume as
much as feasible. Stanbury and Whitaker (1984) reported the flooding phenomenon
occurred at high flow rates will results in extremely low oxygen transfer rates. Chia-
Hua Hsu (2003) addressed that, for mechanical agitated bioreactor, the air flow rate
employed rarely falls outside the range of 0.5 to 1.5 volume of air per volume of
medium per minute (vvm).
2.7 Oswald-de Waele Model
Bailey and Ollis (1986) highlight the influence of broth rheology on power
consumption, mixing, heat and mass transfer rates. Norwood (1960) claimed that
non-Newtonian viscosity can have very important practical effects on bulk flow and
on heat and mass transfer. For an example, in a stirred bioreactor, the shear rate is
highest near the impeller and decrease rather sharply with distance from it. The
simulated pseudoplastic broth employed in this work was to demonstrate the
deviation of CMC solution from the Newtonian fluid behaviour. Theoretically, the
deviation of the pseudoplastic fluid was shown in Figure 2.9. The behaviour of
pseudoplastic fluid has been successfully investigated by Garcia-Ochoa et al. (2000),
Martinov & Vlaev (2002), Shukla et al. (2001) and Arjunwadkar et al. (1998).
29
Pseudoplastic Fluids
Newtonian Fluids
Shea
r ra
te,
Deviation
Shear stress,
Figure 2.9 Deviation of pseudoplastic fluids from Newtonian fluids behaviour
(Bailey & Ollis, 1986)
Their work described the flow behaviour and determined the power-law
quantities by employing the Oswald-de Waele model via Equation 2.33 (Garcia-
Ochoa, 2000).
(2.33)nk
Where
= shear stress (N/m2)
= shear rate (s-1)
k = consistency index (Pa.sn)
n = flow behaviour index (-)
Power law models are very useful from the engineering stand point,
especially when compared to the non linear and unquantified multi parametric
equations of state which has been developed for molecular considerations. However,
power law models fail to predict the Newtonian behaviour frequently observed at
very high and very low shear rates and the equations are not dimensionally sound.
Different composition of broth has different degrees of psedoplasticity and the value
of effective shear rate in the bioreactor was determined according to the equation
proposed by Metzner and Otto (1962):
AN (2.34)
30
and the apparent viscosity as:
(2.35)1napp ANk
Where
A = Metzner and Otto constant (depend on impeller type). It was assume to
be 11.5, for Rushton turbine (Garcia-Ochoa et al., 2000) and 10, for
marine impeller (Nagata, 1975)
N = impeller speed (rpm)
It was found that the apparent viscosity ( app) decreases with increasing of
shear rate for pseudoplastic fluids as reported by Bailey and Ollis (1986).
2.7.1 Carboxy Methyl Cellulose (CMC) Characteristic
Pseudoplastic behaviour of the filamentous culture may be mimicked using
carboxy methyl cellulose (CMC) solution. Carboxy methyl cellulose is used as a
thickener in food manufacturing. CMC is produced from natural sources (from wood
pulp). It is user friendly and non toxic. CMC is stable only over a small pH range of
approximately 5 to 10. However it was suggested that the range of maximum
stability is much smaller than this, being in the range of pH 7 to 9. Dispersion of the
gums may be difficult and require a stringent procedure. If the gums are added in a
haphazard manner they may form lumps in the solution (Brooke & Halsall, 2002).
31
2.8 Scale-up: Strategies Related to Mass Transfer
Bailey and Ollis (1986) discovered that optimal process conditions found at
laboratory scale may not be optimal in larger bioreactors. There is a serious scaling
problem. Hensirisak (1997) defined the scale-up as a procedure for the design and
construction of a large scale system on the basis of a result of experiments with small
scale equipment. Kossen and Oosterhuis (1985) divided the approach for scale-up
into four widely recognized steps namely fundamental methods, semifundamental
methods, dimensional analysis and rules of thumb.
Fundamental methods are based on the application of turbulence models for
description of the influence of operating conditions and geometrical design of the
bioreactor on the flow pattern in the reactor. In semifundamental methods,
simplified equations are applied to obtain a practical approximation of the process.
Dimensional analysis is based on keeping the values of dimensionless groups of
parameters constant during a scale-up. The rules of thumb method is the most
common method. The scale-up criterions most frequently used are constant specific
power input (Pg/VL), constant kLa, constant tip speed of the agitator and constant
dissolved oxygen concentration. Application of the rules of thumb method is very
simple, but it is also a very weak method. There could be a complete shift in the
limiting regime above a certain scale.
The different scale-up criteria normally result in entirely different process
conditions on a production scale. It is impossible to maintain all the parameters in
the same ratio to one another. These consequences are shown in Table 2.1. In
practical application, all four methods are used in combination with each other and
sometimes the trial and error method must be also included. The success of scale-up
processes are usually confirmed by experimental results which show that there is no
difference between small and large scale fermentation carried out under the same
oxygen transfer (Hensirisak, 1997).
32
Table 2.1 Different scale-up criteria and their consequences (Kossen and
Oosterhuis, 1985)
Value at 10 m3 ( V = 10 L ) Scale-up Criterion
P P/V N ND Re N/D
Equal P/V 103 1 0.22 2.15 21.5 0.022
Equal N 105 102 1 10 102 0.1
Equal tip speed 102 0.1 0.1 1 10 10-2
Equal Re number 0.1 10-4 10-2 0.1 1 10-3
Equal shear to flow ratio 108 105 10 102 103 1
2.8.1 Choice of Scale-Up Protocol
There is no single method of aeration-agitation scale-up, which can be
applied with high probability of success to all fermentation process carried out in
conventional stirred, sparger and aerated bioreactors. Mohamad et al. (2001) stated
that all the scale-up methods involved assumptions whose validity is open to
question under certain circumstances or conditions. However, to a large extent the
nature of the fermentation process and the conditions under which it is carried out
dictate the choice, because it will be apparent that the applicability of the different
scale-up procedures is dependent upon process conditions.
Scale-up on the basis of constant impeller tip speed would be obviously the
method of choice when an organism sensitive to a mechanical damage and shear rate
was the most important consideration. The work of Steel and Maxon (1962,1966)
has suggested that this method may be applicable to the viscous non-Newtonian
cultures of filamentous microorganisms, which are of such great industrial
importance. Scale-up on the basis of constant measured volumetric transfer
coefficient is time consuming in that it does not allow for prediction of results,
although it can be used in conjunction with other methods (Aiba et al., 1965) to
obviate this difficulty. The fact that none of the commonly employed physical or
chemical techniques for determination of kLa are suitable for use with pilot and
33
production scale bioreactors is a further difficulty with respect to this procedure.
Scale-up on the basis of constant power consumption per unit volume, despite its
limitations, is probably the best general procedure. Successful cases of scale-up
using this procedure have been recorded in the scientific literature (Chia-Hua Hsu,
2003). Irrespective of which method is employed, the aeration efficiency chosen for
scale-up purposes should ideally be that which permits maximum productivity but
avoids excessive and therefore uneconomic power consumption.
2.8.2 Scale-up on Basis of Constant Oxygen Transfer Coefficient, kLa
This criterion is important and most commonly used to evaluate the aeration
efficiency in aerobic fermentation where supplying sufficient oxygen is the intention
to satisfy the need of the microorganism as reported by Hubbard et al. (1994), Herbst
& Schumpe (1992) and Ju & Chase (1992). In this method, aeration efficiency is
measured on the small scale under conditions, which have been previously
established as optimal for product formation by using one of the recognized
techniques for determination of kLa. Employing the similar technique, conditions are
then found by experiment on the large scale, which will support the same aeration
efficiency. Shukla et al. (2001) successfully demonstrated the scale-up of bioreactor
on a basis of constant kLa in the biotransformation medium. For the scaling up of
aerobic fermentation, the effect of gas liquid mass transport is the most significant
factor (Hubbard et al., 1994). Therefore, scale-up in aerobic fermentation is often
performed on the basis of keeping the value of kLa constant.
34
2.8.3 Scale-up on Basis of Constant Power Consumption per Unit Liquid
Volume, Pg/VL
Scale-up on the basis of constant power input per unit liquid volume is widely
practiced. This method is based on assumed proportionality between power
consumption per unit liquid volume and aeration efficiency. Such proportionality is
almost certainly of more limited application than is generally realized, even under of
fully turbulent flow. Unfortunately, it is not always possible to work under
conditions of turbulent flow. When highly viscous cultures (e.g. fungi and
streptomycetes) are employed, it becomes impossible to maintain turbulent flow even
at very high agitator shafts (Mohamad et al., 2001). Geankoplis (1993) stated that, if
the same power consumption is obtained on both scales of operation, and assuming
proportionality between power consumption per unit liquid volume and aeration
efficiency, then similar aeration efficiency should result on both scales.
Rushton’s equation and the gassed power consumption (Pg) proposed by
Michel and Miller (1962) applies here.
53iLpo DNNP (2.36)
45.0
56.0
32
Q
NDPmP io
g (2.37)
It can be shown that by combining both Equations 2.36 and 2.37, it will yield an
expression for both ungassed and gassed power consumption. The divergence
between values of the exponent on N and Di in the expressions is sufficiently small
to be ignored for the practical purpose.
45.0
56.0
13722
Q
DNNmP iLp
g (2.38)
35
Therefore, we may write the derivation as:
252.0
85.515.39.09.0
Q
DNmNP iLp
g (2.39)
For equal power per unit liquid volume:
2
2
1
1
V
P
V
P gg (2.40)
The subscripts 1 and 2 refer to the small and large scales respectively. If
geometrically similar vessels are employed in scale-up, the value of the geometry
dependent constant will be the same for both scales, thus:
442
22
2
121
1
TT
g
TT
g
HD
P
HD
P (2.41)
22
2
2
121
1
TT
g
TT
g
HD
P
HD
P (2.42)
Substituting Pg1 and Pg2 for both scales into Equation 2.42.
22
2252.0
2
85.52
15.32
9.09.0
121
252.01
85.51
15.31
9.09.0
TT
iLp
TT
iLp
HDQ
DNmN
HDQ
DNmN (2.43)
The following equation is used for scaling-up on basis of constant power input per
unit liquid volume:
22
2252.0
2
85.52
15.32
121
252.01
85.51
15.31
TT
i
TT
i
HDQ
DN
HDQ
DN (2.44)
36
2.8.4 Scale-up on Basis of Constant Superficial Air Velocity, vg
Cooper et al. (1944) demonstrated the proportionality between aeration
efficiency and power consumption per unit liquid volume when the superficial air
velocity was maintained at a constant value. In scaling up on the basis of constant
power consumption per unit liquid volume, it is therefore necessary to alter the
volumetric air flowrate in order to maintain a constant superficial air velocity on both
scales of operation. The required air flow rate on the larger scale may be calculated
by using Equation 2.45.
21 gg vv (2.45)
Substitute Equation 2.31 in Equation 2.45.
22
221
1 44
TT D
Q
D
Q (2.46)
Thus, with geometrically similar vessels, the required volumetric air flowrate is:
2
1
212
T
T
D
DQQ (2.47)
37
2.8.5 Scale-up on Basis of Constant Impeller Tip Speed
The basis of this method is that the impeller tip speed is maintained at a
constant value during scale-up. Thus:
V’i1 = V’i2 (2.48)
Where
V’i= impeller tip speed, ( N Di).
2211 NDND ii (2.49)
Therefore, the required impeller speed for larger scale is as follows:
2
112
i
i
D
DNN (2.50)
Application of this scale-up method is with organisms which are particularly
susceptible to shear or mechanical damage. This application has been extensively
investigated by Midler and Finn (1966). They have successfully scale-up a protozoa
culture in stirred bioreactors on the basis of constant impeller tip speed.
CHAPTER 3
METHODOLOGY
3.1 Bioreactor Start-up
Standard operating procedure was employed in this preparation. All
mechanical parts (safety valve, manometer, exhaust air filter etc.), temperature probe,
pH probe and oxygen probe were ensured in place and mounted to the vessel. A
calibration using standard procedures was performed on both the pH and dissolved
oxygen electrodes. All connections from vessel to controller and computer were
connected properly. The bioreactor was filled approximately 2/3 full with distilled
water to keep the electrodes submerged and keep them from drying out. All valves
for the utilities namely cooling water, air and steam supply were opened. The inlet
pressure gauge for both the air flow and cooling water supply and inlet pressure
regulator for plant steam was set to operate at approximately 3 to 4 bar. In order to
control the bioreactor, the FERMTM (Switzerland) simulation program was selected.
The bioreactor was set at a steady temperature of 30oC (room temperature). Other
parameters namely pH and dissolved oxygen concentration may vary constantly
throughout the start-up period. Note that, it is not necessary to set up any of the feed
ports unless it involved sterilization process because of the presence of cells.
Meaning so, the feed port was not prepared at preliminary stage. At this stage, it
only involved the use of distilled water and a simulated pseudoplastic broth.
This procedure was performed in both 16 liter and 150 liter scale. During
start-up period, the bioreactor was allowed to run at impeller speed of 600 rpm and at
air flowrate of 9 l/min in the 16 liter scale. At 150 liter scale, the bioreactor was
39
warmed up at impeller speed of 150 rpm and the air flow rate was set at 30 l/min.
The bioreactor was warmed up for at least 30 minutes before performing any
experimental works. The bioreactor was operated when all the operating parameters
such as temperature, pH, dissolved oxygen concentration, impeller speed and air
flow rate are stable.
3.2 Bioreactor Dimension
The dimension of bioreactor is summarised in Table 3.1.
Table 3.1 Dimensions of 16 liter and 150 liter bioreactor
Dimension 16 Liter Bioreactor 150 Liter Bioreactor
Total volume, VT (m3)
Working volume, VL (m3)
Vessel height, HT (m)
Liquid height, HL (m)
Vessel diameter, DT (m)
Surface area, as (m2)
0.016
0.01
0.507
0.393
0.2
0.0005
0.15
0.1
1.143
0.825
0.41
0.132
Impeller type
Number of impellers
Impeller diameter, Di (mm)
Impeller thickness, Ti (mm)
Impeller width, Wi (mm)
Ratio impeller to vessel diameter
Top impeller distance from
top plate, i (m)
Spacing between impeller, C (m)
Rushton
2
70
3
14
0.35
0.26
0.155
Marine
1
80
3
-
0.4
0.2535
-
Rushton turbine
2
200
3
40
0.49
0.47
0.52
Sparger diameter, DS (m)
Sparger distance from bottom
impeller (m)
Baffles
0.095
0.055
Yes
0.205
0.073
Yes
40
The geometry of the bioreactor and the design of the impeller used in the bioreactor
are illustrated in Figure 3.1 and Figure 3.2, respectively.
DT
Di
i
HT
C
DS
Figure 3.1 Geometry of the bioreactor (BioengineeringTM)
DiDi
Figure 3.2 Type of agitator (a) Marine impeller (b) Rushton turbine
41
3.3 Investigation at 16 Liter Bioractor
3.3.1 Operational Conditions at 16 Liter Scale
Based on the previous works as summarised in Table 3.2, the operating
variables for the experiment in 16 liter bioreactor were determined.
Table 3.2 Operating conditions and techniques to determine the oxygen transfer
coefficient (kLa) reported in several works
Impeller speed Air flow rate Technique Used Cooper et al.(1944)
N/A N/A Sulfite oxidation
Shukla et al.(2001)
50 – 300 rpm 0.293 – 1.56 vvm Dynamic gassing out
Badino Jr. et al.(2001)
300 – 700 rpm 0.2 – 1 vvm Modified dynamic
Martinov & Vlaev (2002)
0.1 < Pg/VL < 2 kW m-3
3.3 x 10-3 < vg < 6.6 x 10-3 ms-1
Static gassing out
Arjunwadkar etal. (1998)
400 – 750 rpm 0.29 – 0.975 vvm Dynamic gassing out
The operating variables for the experimental work in the 16 liter scale vessel
were given in Table 3.3. For each combination of impeller speeds and air flow rates,
the experiments were performed on distilled water at temperature of 30oC, 40oC and
at 50oC. The initial pH was set to operate at 7 + 0.03 for the entire experiment. The
liquid viscosity was increased by dissolving the Carboxy Methyl Cellulose to
obtained the concentrations of 0.25%(w/v), 0.5%(w/v) and 1%(w/v) at 30oC. The
experiment was repeated by using the marine impeller for comparison. The physical
properties of CMC solution and distilled water are given in Table A.2 and A.3 in
Appendix A 1, respectively.
42
Table 3.3 Operating variables at 16 liter bioreactor
Scale Impeller speeds,
N
Air flow rates,
Q
Liquid model Impeller
type
16 liter 200 – 1000 rpm 3 – 15 l/min Water & CMC Rushton turbine
16 liter 200 – 1000 rpm 3 – 15 l/min Water & CMC Marine impeller
3.3.2 Determination of Probe Response Time
The probe response time was determined to correct the transmission delay
and the lag in response of polarographic membrane oxygen probe used. This was
done on 10 liter cell-free distilled water in 16 liter bioreactor. The time constant
given in the specifications was less than 45 seconds for approximately 98% of
dissolved oxygen saturation concentration.
The impeller was set at 600 rpm and the air supply was set at 9 l/min of air.
The bioreactor was ensured to run at a steady temperature of 30oC. The change in
the dissolved oxygen concentration was allowed to reach 100% of saturation value.
Then, both of the agitation and aeration were switched off and the inlet valve of the
nitrogen tank was opened immediately until the oxygen probe indicated complete
removal of oxygen. Then, the inlet valve of nitrogen tank was closed and both
impeller and air supply was turned on to allow 100% oxygen saturation.
The change of dissolved oxygen concentration was monitored on line by
means of polarographic electrode and the value obtained was noted down manually
for every 5 second interval. Finally, the response curve of dissolve oxygen
concentration against time for determination of the probe response time was plotted.
The above procedure was repeated for reproducibility checking. The electrode
response time attained was illustrated in Figure A.2 in Appendix A1.
43
3.3.3 Determination of kLa
The rate of oxygen transfer from air bubbles to a liquid in a batch stirred
bioreactor was given by the following relationship.
)( *LL
L CCakdt
dC (2.17)
The oxygen transfer rate (OTR) was determined by implementing 'the static gassing
out' method as explained by Stanbury and Whitaker (1984). The change in dissolved
oxygen concentration (CL) in the liquid phase was detected by using a polarographic
oxygen probe. The nitrogen tank was connected into the feed port of the bioreactor
and was set to deliver an inlet pressure of 10 psig.
The experimental work was started after the dissolved oxygen concentration
reached 100% saturation value. The aeration of the bioreactor was interrupted by
switching off the air flow and the medium was purged with nitrogen until 0% oxygen
saturation was reached. As the dissolved oxygen concentration reaches below 10%
of saturation value, the air flow was restarted and the inlet valve of the nitrogen tank
was closed. Simultaneously, the chart is marked to show time zero. The oxygen
tension was allowed to increase and approaches 100% saturation value. When the
dissolved oxygen tension stabilizes at 100% saturation value, the above steps were
repeated for reproducibility checking. The delayed response time was offset by the
electrode response time.
In order to calculate the kLa, Equation 2.17 was firstly integrated with respect
to the time taken for the oxygen concentration to reach the saturation level from the
lowest point.
L
Lo
L CC
CC
akt
*
*
ln1
(3.1)
44
Then, the kLa value is determined by reciprocating the slope obtained from the semi
logarithmic plot of time (t) versusL
Lo
CC
CC*
*
. Note that the dissolved oxygen
electrode records oxygen concentration as percentage of maximum dissolved
oxygen. In this research, the dissolved oxygen saturation concentration in the liquid
or C* that calculated from the Henry's Law was quoted from the table that presented
in Perry and Green (1997). The oxygen saturation concentrations are presented in
Table A.4 in Appendix A1.
3.4 Scale-up on Constant kLa at 150 Liter Bioreactor
3.4.1 Scale-up Protocol
The scale-up protocol applied involved the application of rule of thumb, trial
and error, interpolation and extrapolation on the basis of keeping the value of kLa
constant as the scale increases. The protocol was summarised in Figure 3.3. The
scale-up performed by firstly, investigate the kLa values in 16 liter vessel. Upon
obtaining the kLa values in the 16 liter scale, the limitations for the operating
variables in the 150 liter bioreactor were computed. In order to design the
operational conditions at 150 liter scale, scale-up on the basis of constant power
consumption per unit liquid volume, Pg/VL, constant superficial velocity, vg and
constant impeller tip speed, NDi was performed using the scale-up equations.
45
Investigationof kLa at 16 liter scale
Application of scale-up equations to determine operating conditions at 150 liter scale
Fix new operating conditions at 150 liter bioreactor
Implement the similar techniqueat 150 liter scale for determination of kLa
Interpolation andextrapolation to achieve the same value of kLa
Evaluation of scale-up consequences
Similar kLa value ?
trial and error
No
Yes
Figure 3.3 Scale-up protocol based on constant oxygen transfer coefficient, kLa
46
The following equations are the scale-up equations to be employed in the
scale-up protocol.
(1) Constant power consumption per unit liquid volume, Pg/VL.
22
2252.0
2
85.52
15.32
121
252.01
85.51
15.31
HDQ
DN
HDQ
DN
T
i
T
i (3.2)
(2) Constant superficial velocity, vg.
2
1
212
T
T
D
DQQ (3.3)
(3) Constant impeller tip speed, NDi.
2
112
i
i
D
DNN (3.4)
By knowing the impeller speeds, N1 and air flow rates, Q1 at 16 liter scale,
Equation 3.2, 3.3 and 3.4 was used to determine the impeller speeds and air flow
rates at 150 liter scale. At different scale-up criterions, the allowable operating range
at 150 liter vessel was predicted. Incorporating Equation 3.3 and Equation 3.4 into
Equation 3.2 will yield the scale-up equations in predicting the impeller speeds and
the air flow rates at 150 liter scale. The equations are as follows:
(1) Constant power consumption per unit liquid volume, Pg/VL with constant
superficial velocity, vg.
2
1
212
T
T
D
DQQ (3.5)
47
85.521
21
252.01
15.3
1
22
2252.0
285.5
115.3
12
iT
Ti
DHDQ
HDQDNN (3.6)
(2) Constant power consumption per unit liquid volume, Pg/VL with constant
impeller tip speed, NDi.
2
112
i
i
D
DNN (3.7)
85.512
22
15.31
252.0
1
12
1252.0
185.5
215.3
22
iT
Ti
DHDN
HDQDNQ (3.8)
The operating variables (N2 and Q2) achieved in solving Equation 3.5, 3.6, 3.7
and 3.8 was used a base line in ‘trial-and-error’ step upon scaling-up a bioreactor
from 16 liter to 150 liter on a basis of constant kLa. The ‘trial-and-error’ loop in
determination of the operating conditions at 150 liter scale was shown in Figure 3.4.
Fix New Operating Conditions Trial and error • Impeller Speed, N2
Interpolation and Extrapolationto achieve kLa value
Experiment by using Static Gassing Out Method
• Air Flow Rate, Q2
Figure 3.4 The ‘trial-and-error’ loop at 150 liter scale in the scale-up protocol
48
In providing a similar oxygen transfer coefficient, kLa as in the 16 liter
bioreactor, the impeller speeds and the air flow rates was manipulated. Interpolation
and extrapolation was carried out to determine the operating variables at 150 liter
bioreactor.
(1) Interpolation
Operating conditions (N or Q) kLa value attained
x1 y1
x y
x2 y2
11212
1 xxxyy
yyx (3.9)
where x is the value of the operating conditions (N or Q) required.
(2) Extrapolation
kLa value attained Operating conditions (N or Q)
x1 y1
x y
xx
yy
2
1 (3.10)
where y is the value of the operating conditions (N or Q) required.
The scaling-up factor upon scaling-up based on constant kLa from 16 liter to
150 liter bioreactor were calculated by using the equations below:
1
21 N
NR (3.11)
1
22 Q
QR (3.12)
where subscripts 1 and 2 for impeller speed, N and air flow rate, Q
refer to small (16 liter) and large (150 liter) scales respectively.
49
3.4.2 Operational Conditions at 150 Liter Scale
At 150 liter bioreactor, different combinations of operating conditions were
applied. The impeller speeds and air flow rates were determined by matching the kLa
in both 16 and 150 liter scales. The range of operating conditions designed was
summarised in Table 3.4. The similar technique of ‘static gassing out’ was
implemented to determine the value of kLa. Experiments were carried out under the
same experimental conditions namely pH, temperature and rheology properties as in
the 16 liter scale.
Table 3.4 Operating variables at 150 liter bioreactor
Scale Impeller speeds, N Air flow rates, Q Liquid model
150 liter (1st Trial) 50 – 250 rpm 10 – 50 l/min Water & CMC
150 liter (2nd Trial) 60 – 300 rpm 10 – 50 l/min Water & CMC
3.5 The Oxygen Transfer Coefficient Correlation
With the scale-up criteria selected (kLa), superficial air velocity, vg and the
specific power data, Pg/VL were correlated using the equation proposed by Cooper et
al. (1944) via Equation 3.5.
cg
b
L
gL v
V
Paak ' (3.13)
Ungassed and gassed power consumption was estimated at predetermined
operating conditions (N and Q) for both scales. The ungassed power consumption
(Po) was determined from the plot of power number (Np) versus Reynolds number
(NRe) for both Newtonian and non-Newtonian fluid in a different type of flow regime
(Rushton et al., 1950). The plot is given in Figure 2.8.
50
p
iL
o NDN
P53
(3.14)
The Reynolds number (NRe) was calculated from the following equation.
For Newtonian fluids:
L
LRE
iNDN
2
(3.15)
For non-Newtonian fluids:
app
LiNDN
2
Re (3.16)
The gassed power consumption (Pg) was estimated through a correlation
proposed by Michel and Miller (1962).
45.0
56.0
32
Q
NDPmP io
g (3.17)
Where m depends on the impeller geometry for which in this case, the value of m
is 0.832 for both disc turbine impeller and marine impeller (Badino Jr. et al., 2001).
As for the superficial air velocity (vg), it was calculated by using the equation below:
2
4
tg D
Qv (3.18)
Note that, these calculations were performed for both type of impellers at 16 liter
and set of impeller speeds and air flow rates attained at 150 liter from interpolation
and extrapolation upon scale-up on basis of constant kLa. In order to determine the
51
dependence of kLa on stirrer speed and aeration, the following correlations should be
firstly determined.
(i) Logarithmic plot of kLa against (Pg/VL) at constant superficial air
velocity, vg. The mean gradient of the lines will give the exponent b of
Equation 3.13.
(ii) Logarithmic plot of kLa against (vg) at constant Pg/VL. The mean gradient
of the lines will give the exponent c of Equation 3.13.
Further analysis was done by constructing a logarithmic plot of kLa values with
respect to impeller speed, Pg/VL and gas superficial velocity, vg to observe the effect
of agitation, aeration and power consumption in bioreactor on kLa.
3.6 Rheology Measurement
In order to determine the characteristic of rheological properties of any fluids,
a concentric cylinder viscometer as shown in Figure 3.5 was used. By changing the
speeds and spindle types, a range of viscosity ranges can be measured.
Measurements were made using the same spindle at different speeds to detect and
evaluate the rheological properties of the tested fluid (Brooke & Halsall, 2002). The
viscosity for each solution was measured by means of a Brookfield viscometer model
LVT using the spindle number 1 at 30oC (room temperature). The measurement was
performed at various spindle speeds ranges from 0.3 to 60 rpm. The value of
viscosity was obtained by multiplying the reading attained from the viscometer with
the viscosity factor given in the user manual. Finally, a profile of viscosity against
shear rate was constructed to determine the behaviour of the CMC solutions.
52
Figure 3.5 A concentric cylinder viscometer
3.6.1 Concentric Viscometer Analysis
Culture broths of filamentous microorganism normally show pseudoplastic
behaviour. To provide such behaviour, the rheological properties were altered to
mimic the filamentous culture broth. It was done by dissolving the carboxy methyl
cellulose (CMC) into the liquid to prepare a CMC solution at concentrations of
0.25%(w/v), 0.5%(w/v) and 1%(w/v). After adding the CMC to the distilled water,
the solution was lefted for 24 hours to ensure that the hydrocolloids were fully
hydrated and maximum viscosity has been reached. The analysis was done on each
of the CMC solutions prepared. Derivation on the concentric viscometer analysis is
presented in Appendix A2. The value of shear stress, was determined from
Equation 2.33 and the value of shear rate, was determined from Equation 3.19.
shear rate, 22
21
22
21
2 /.*/.2 rrrrr (3.19)
53
As previously mentioned, non-Newtonian broth behaviour was described by
Oswald-de Waele model (Garcia-Ochoa et al., 2000) as represented in the Equation
2.33. A logarithmic plot of shear stress, with respect to shear rate, will give an
intercept of the consistency index, k and the gradient was the value of flow behaviour
index, n respectively. The apparent viscosity was determined by using the equation
as described by Oswald-de Waele model via Equation 3.20.
1napp ANk (3.20)
Where A, for turbine stirrer type value was assumed to be 11.5 (Garcia-Ochoa et al.,
2000) and value for marine impeller was assumed to be 10 (Nagata, 1975). The
calculation for the apparent viscosity, app was performed at different stirrer speeds
as previously mentioned.
3.6.2 Rheological Behavior of CMC Solution
The trend in Figure 3.6 demonstrates that the decrease of shear rate ( ) at
different spindle speeds proves that the CMC exhibits pseudoplastic characteristic.
This characteristic matches with the rheology of the filamentous cultures as cited in
Brooke & Halsall (2002). This was easily analyzed by plotting the shear rate ( )
against the shear stress ( ) for different concentration of CMC concentrations as
illustrated in Figure 3.6. As shown in Figure 3.6, all the CMC solutions showed a
shear thinning and non-Newtonian pseudoplastic behaviour. As would be expected,
increases in the concentration of CMC lead to an increase in the apparent viscosity of
the solutions. The pseudoplastic nature of the CMC solutions is caused by
interactions between the CMC molecules. The analysis on the CMC solutions is
given in Appendix B.
54
0
0.01
0.02
0.03
0.04
0.05
0.06
0.07
0 0.2 0.4 0.6 0.8 1 1.2
shear rate,
visc
osity
,
1%(w/v) CMC
0.5%(w/v) CMC
0.25%(w/v) CMC
Figure 3.6 Viscosity (kg/m.s) change with shear rate (s-1) for CMC solution
From the measurement of CMC viscosity by using a Brookfield viscometer
model LVT and data analysis, the parameter attained for the Oswald-de Waele model
was shown in Table 3.5.
Table 3.5 Oswald-de Waele model at various CMC concentrations
CMC concentrations Consistency index, k
(Pa.sn) x 103
Flow behavior index, n
0.25%(w/v)
0.5%(w/v)
1%(w/v)
6.16
14.6
53.9
0.7654
0.8825
0.9501
The Power Law indices of the CMC solutions, shows that with more CMC
present, the power law index of the solutions decreases. So as the amount of CMC
was increased, the solution becomes more non-Newtonian. This is illustrated in
Figure 3.7.
55
0
0.2
0.4
0.6
0.8
1
1.2
0 0.01 0.02 0.03 0.04 0.05 0.06
Shear stress, (N/m2)
(s-1
)Sh
ear
rate
, 0.5%(w/v) CMC
0.25%(w/v) CMC
1%(w/v) CMC
Newtonian Fluids
Figure 3.7 Deviation from Newtonian behaviour due to CMC presence in the
fluid at 30oC
3.7 Fermentation of E.coli at 16 Liter Bioreactor
3.7.1 Microorganism
The fermentation process was carried out by using the Recombinant E.coli
ARP012 without the protein expression. Stock cultures were maintained on LB agar
slants containing 10 g/L bactotryptone (Merck, Germany), 5 g/L sodium chloride
(Merck, Germany), 5 g/L yeast extract (Merck, Germany) and 15 g/L agar (Hamburg
Chemicals, Germany). The prepared slants were maintained at 4oC and subcultured
every three months.
56
3.7.2 Inoculum Preparation at 16 Liter Scale
The culture medium used for the preparation of inoculum is as described in
Table 3.6. Inoculum was prepared in a 2 liter Erlenmeyer flask containing 1 liter of
the culture medium. The medium was autoclaved at 121oC for 20 minutes. Glucose
was sterilized separately at 110 oC for 10 minutes to avoid caramelization, and then
was combined aseptically with the balance of media. Ampicilin was added after the
medium was autoclaved. A single colony from above plate was inoculated into the
prepared medium. A small loopful of bacteria was lifted from the agar plate and the
loop was swirled in the culture medium to dislodged it. The medium was incubated
overnight (approximately 10 to 14 hours) on 250 rpm orbital shaker at 37oC. All
experimental works were carried out aseptically and no antifoam or any other
substance was added to this inoculum prior to introduction into the bioreactor upon
start-up of the reaction.
Table 3.6 Batch fermentation medium for production of E.coli
Component Concentration (g/L)
Bactotrytone (Merck, Germany) 10.3
Yeast extract (Merck, Germany) 5.2
Sodium chloride (Merck, Germany) 10.3
Glucose (Sigma, USA) 21
Ampicilin (Boehringer Mannheim, Germany) 0.012
3.7.3 Batch Fermentation of E.coli
Batch fermentations were carried out in the 16 liter bioreactor with total broth
volume of 11.5 liter. The medium was autoclaved in situ at 121oC for 20 minutes.
0.5 liter of glucose solution was sterilized separately and was pumped in after the
vessel cooled down. 1 liter of seed culture was transferred into 10 liter bioreactor.
6M NaOH, 2M H2SO4 and silicon-based antifoam was prepared and connected to the
bioreactor. Throughout the fermentation, the medium pH was maintained at 7.0 +
57
0.1. The temperature was controlled at 37 oC and the dissolved oxygen concentration
was maintained above 20% saturation value. Antifoam was added manually when
foaming occurred.
3.7.4 Sampling and Analytical Methods
Twenty mililiter samples from fermentation were taken at 1 hour interval.
Biomass was determined as OD at 600 nm absorbance using spectrophotometer
model Ce 2011 (2000 series) (Cecil Instrument, England). Glucose measurements
were performed off-line using a glucose analyzer (Model YSI 2700 select, Yellow
Springs Instrument Co. Inc., USA). The measurements of kLa were carried out by
changing the airflow rate, Q between 10 l/min to 14 l/min and varied the stirrer speed
from 550 rpm to 750 rpm. Any change in agitation and aeration rate outside this
range did not produce any significant variation in kLa. Fermentation was monitored
until the cells came to the stationary phase.
3.7.5 Dynamic Technique in kLa Measurement
The following mass balance equation was used for the dissolved oxygen in
batch fermentation:
xOLLL CrCCak
dt
dC2
* (3.21)
where the first term on the right hand side of Equation 3.21 is the oxygen transfer
rate (OTR) and the second term is the oxygen uptake rate of the culture (OUR). The
measurement of OUR and OTR was made using dynamic technique proposed by
Taguchi and Humphrey (1966) in two stages. In the first stage, the inlet of airflow
was shut down and a decrease of oxygen dissolved concentration due to cellular
respiration was observed, which was recorded by a polarographic oxygen probe. The
58
OUR was determined by change in the dissolved oxygen concentration after stopping
air flow. In this condition, Equation 3.21 can be simplified to:
xOL Cr
dt
dC2
(3.22)
The dissolved oxygen concentration was maintained higher than 20% of
saturation value to ensure that the microorganisms were not going to be damaged due
to lack of oxygen. The OUR was obtained from the slope of the linear regression of
the change in dissolved oxygen concentration, CL against time. The first stage was
employed to obtained the value of specific respiration rate, rO2 by dividing the OUR
by the biomass concentration.
In the second stage, the inlet of airflow to the bioreactor was restarted at
predetermined values and will increase the dissolved oxygen concentration. Under
these conditions, Equation 3.21 can be rearranged to result in a linear relationship as:
xOL
LL Cr
dt
dC
akCC
2
1* (3.23)
From Equation 3.23, the plot of CL versus (dCL/dt +rO2Cx) will result in a
straight line which has the slope of (-1/kLa) and the y-axis intercept of C*. This
technique was employed at different combinations of impeller speed and airflow
rates as mentioned previously. The calculation for the static and the dynamic
gassing-out technique is shown in Appendix C1 and Appendix C2, respectively.
59
3.7.6 Gravimetric Analysis
The cell dry weight was determined by centrifuging predetermined dilutions
of the sample. The supernatant was discarded, and the pellet was resuspended in
deionized water for further washing. The suspension was recentrifuged and the
pellet was resuspended for absorbance measurement at 600 nm of wavelength.
Measurements were done using a Ce 2011 (2000 series) (Cecil Instrument, England)
spectrophotometer. Measured suspensions were then placed into tared aluminum
dishes and dried at 100 0C for 24 to 48 hours. The correlation between dry cell
weight concentration (X) and OD was then determined as a linear correlation X =
0.42 OD600nm - 0.04 (see Appendix C3).
3.8 Test of Scale-up Approach on Live Culture
3.8.1 E.coli Fermentation at 150 liter Bioreactor
Constant kLa was selected as scale-up criteria in this work. Media and
inoculum protocol were as in 16 liter bioreactor. Steps for the E.coli fermentation at
150 liter scale were illustrated in Figure 3.8. The scale-up was done according to the
previous scale-up protocol employed using cell-free distilled water and CMC
solutions. The impeller speeds and air flow rates at 150 liter scale were determined
using the scale-up ratio attained. Upon achieving the scale-up ratio for impeller
speeds and air flow rates, the operating conditions for E.coli fermentation was
designed. The operating conditions for E.coli fermentation was shown in Table 3.7.
Table 3.7 Operating conditions for E.coli fermentation at 150 liter
Impeller speed
(rpm)
Air flow rate
(l/min)
Temperature
(oC)
pH % Oxygen
Concentration
60 - 360 25 - 35 37 7 > 20%
60
INOCULUM DEVELOPMENT
Stock Culture Shake FlaskSeed Bioreactor
16 liter
Production Bioreactor 150 liter
Figure 3.8 Steps in E.coli fermentation at 150 liter scale
CHAPTER 4
RESULTS AND DISCUSSION
4.1 Introduction
The discussion on this chapter focuses on the results obtained from
employing the proposed scale-up protocol. The scale-up protocol was employed in
scaling-up bioreactor on a basis of constant kLa from 16 liter to 150 liter bioreactor.
Investigation was firstly performed to evaluate the effect of temperature, power
input, superficial velocity and liquid viscosity on the oxygen transfer coefficient, kLa,
at predetermined range of impeller speeds and air flow rates. The significance of
hydrodynamic differences between marine impeller and Rushton turbine was clearly
emphasized in this chapter. Discussion also includes the results attained upon
application of the scale-up equations in determining the allowable operating range at
150 liter vessel. In order to achieve a similar value of kLa as in the 16 liter scale, the
‘trial-and-error’ was carried out based on the operating limitations at 150 liter
bioreactor. Various characteristic which may influence the kLa value and the scale-
up consequences upon scaling-up from 16 liter to 150 liter bioreactor was discussed.
The validity of the proposed scale-up protocol was tested in the actual fermentation
environment. The results obtained for the recombinant E.coli fermentation at 16 liter
and 150 liter scale was compared and evaluated.
62
4.2 Hydrodynamics Difference between Rushton and Marine Impeller
Investigation was performed on the significance of hydrodynamic difference
between Rushton and marine impellers on the oxygen transfer rate in 16 liter
bioreactor. The static gassing-out technique was employed to measure the kLa at the
various operational conditions. At different viscosities and temperatures, the
impeller speed was varied from 200 to 1000 rpm at constant aeration rate of 0.9 vvm
and the air flow rate was varied from 0.3 to 1.5 vvm under constant agitation at 600
rpm. Two different designs of impeller show a resemblance in the dependence of
kLa on the superficial air velocity. A similar effect on the increasing of temperatures
and viscosities was also achieved. However, a significance difference in the
dependence of kLa on the volumetric gassed power input and difference in mixing
capacity was observed between the Rushton and marine impellers. The results are
presented and discussed in the following section.
4.2.1 Proportional Effect of Agitation and Aeration Rates on KLa
The result shows that the oxygen transfer coefficient, kLa was a strong
function of the agitation in both Rushton turbine and marine impeller. This is
illustrated in Figure 4.1 and 4.2. Based on the trend achieved in Figure 4.1 and 4.2, it
was seen that agitation rate in the bioreactor has a proportional effect on kLa. This
shows that an increase on the impeller speed will increase the oxygen transfer rate in
the bioreactor. As illustrated in Figure 4.2, a very low kLa values (lower than 0.01)
was attained especially in the CMC solution at low agitation rate of 300 rpm. It
proved that the effect of agitation was hardly notice at agitation below than 300 rpm.
Under this condition, the agitation system was incapable of maintaining the turbulent
flow conditions and hence, unable to enhanced the oxygen transfer in the bioreactor.
Nevertheless, the oxygen transfer rate increase from 20% to 40% as the agitation rate
was increased. The results obtained successfully confirmed that the fact of increase
in impeller speed will increase the kLa in the bioreactor as cited by Martinov &
Vlaev (2002).
63
R2R = 0.94
R2R = 0.97
R2R = 0.97
R2M = 0.93
R2M = 0.91
R2M = 0.96
0.001
0.01
0.1
100 1000Impeller speed, N (rpm)
kLa
(s-1
)
Rushton 30°C
Rushton 40°C
Rushton 50°C
Marine 30°C
Marine 40°C
Marine 50°C
400 600 800200
Figure 4.1 Dependence of kLa on impeller speed, N at different temperature for
Rushton turbine and marine impeller
R2M = 0.97
R2M = 0.98
R2M = 0.93
R2R = 0.99
R2R = 0.90
R2R = 0.92
0.001
0.01
0.1
100 1000Impeller speed, N (rpm)
kLa
(s-1
) R
usht
on
0.001
0.01
0.1
1
kLa
(s-1
) M
arin
e
1% - Rushton
0.5% - Rushton
0.25% - Rushton
1% - Marine
0.5 - Marine
0.25% - Marine
200 400 600 800
Figure 4.2 Dependence of kLa on impeller speed, N at different viscosities for
Rushton turbine and marine impeller
64
A similar trend as in the dependence of kLa on impeller speed was also
achieved for the dependence of kLa on the air flow rate in Rushton turbine and
marine impeller. This is shown in Figure 4.3 and Figure 4.4. As the aeration rate
was increased from 3 l/min to 15 l/min, the kLa values achieved was proportionally
increased. In both trend of kLa dependence on impeller speed and air flow rate, it
clearly shows that agitation affected the kLa significantly compared to the effect of
aeration on kLa. Between agitation rates of 200 to 1000 rpm, there was nearly a ten-
fold increased in the observed kLa. The kLa values improve twice as the aeration
rates are increased. Even though the result showed that the air flow rate has a
relatively small effect on kLa, one could see the general trend of higher kLa at higher
gas flow rate due to the parallel rise of gas hold-up in the gas dispersion equipment.
However, a deviation from the trend in the dependence of kLa on air flow rate for the
marine impeller experiments was observed. Nevertheless, similar behaviour on the
linear dependence of kLa on the agitation and aeration rates was seen for both
Rushton and marine impellers.
The increase of the kLa due to the agitation and sparging was due to the
decrease of bubble size and subsequently led to the increase of the specific interfacial
area resulting in higher interfacial contact between the gaseous and liquid phase for
the oxygen transfer. Increase in residence time of the bubbles in the liquid due to
agitation also contributed to increase kLa. Agitation delays the escapes of air bubbles
from the liquid, breaks the bubbles and prevents it from coalescence. Most
importantly, higher agitation provides a better oxygen transfer because its decreases
the thickness of the gas liquid film at the gas-liquid interface by creating turbulence
in the culture. This is consistent with what was reported in the literature review
where agitation and aeration rates have a proportional effect on kLa (Arjunwadkar et
al., 1998, Shukla et al., 2001, and Martinov & Vlaev, 2002).
65
R2R = 0.84
R2R = 0.90
R2R = 0.97
R2M = 0.84
R2M = 0.96
R2M = 0.88
0.001
0.01
0.1
1 10 100Air Flow Rate, Q (l/min)
kLa
(s-1
)
Rushton 30°C
Rushton 40°C
Rushton 50°C
Marine 30°C
Marine 40°C
Marine 50°C
Figure 4.3 Dependence of kLa on air flow rate, Q at different temperature for
Rushton turbine and marine impeller
R2M = 0.87
R2M = 0.94
R2M = 0.90
R2R = 0.97
R2R = 0.98
R2R = 0.83
0.001
0.01
0.1
1 10
Air Flow Rate, Q (l/min)
100
L
0.001
0.01
0.1
kLa
(s-1)
Mar
ine
1% - Rushton0.5% - Rushton0.25 - Rushton1% - Marine0.5% - Marine0.25% - Marine
ka
(s-1)R
usht
on
Figure 4.4 Dependence of kLa on air flow rate, Q at different viscosities for
Rushton turbine and marine impeller
66
4.2.2 Effect of Temperature on Oxygen Transfer Rate
Increase of temperature improve the oxygen transfer rate and reduce the
oxygen solubility as tabulated in Table A.4 in Appendix A1. Investigation on the net
effect was found to be crucial and was performed at different type of impellers
namely Rushton turbine and marine impeller by varying the temperature from 30oC
to 50oC. The increase of kLa in the bioreactor by operating at higher temperature in
Rushton turbine and marine impeller at different agitation rates are presented in
Table 4.1. A proportional increase of temperature and kLa was also achieved at
different air flow rates for both Ruhton and marine impellers as presented in Table
4.2.
Table 4.1 Increase of kLa values at higher operating temperature in Rushton
turbine and marine impeller at different impeller speeds
Rushton Turbine Impeller Speed, N (rpm) Distilled Water ( T) 200 400 600 800 1000kLa (s-1) at T = 30oC 0.0073 0.0198 0.0226 0.0393 0.0749kLa (s-1) at T = 40oC 0.0113 0.0253 0.0357 0.045 0.00793kLa (s-1) at T = 50oC 0.0149 0.0283 0.0426 0.0487 0.0845
Marine Impeller Impeller Speed, N (rpm) Distilled Water ( T) 200 400 600 800 1000kLa (s-1) at T = 30oC 0.004 0.0071 0.0092 0.0147 0.0288kLa (s-1) at T = 40oC 0.0068 0.0086 0.0134 0.0194 0.0249kLa (s-1) at T = 50oC 0.0079 0.0119 0.0187 0.021 0.0325
Table 4.2 Increase of kLa values at higher operating temperature in Rushton
turbine and marine impeller at different air flow rates
Rushton Turbine Air Flow Rate, Q (l/min) Distilled Water ( T) 3 6 9 12 15kLa (s-1) at T = 30oC 0.0213 0.0243 0.0259 0.0374 0.0407kLa (s-1) at T = 40oC 0.0236 0.0276 0.0332 0.0471 0.0513kLa (s-1) at T = 50oC 0.0266 0.0356 0.0470 0.0625 0.0675
Marine Impeller Air Flow Rate, Q (l/min) Distilled Water ( T) 3 6 9 12 15kLa (s-1) at T = 30oC 0.0042 0.0087 0.0092 0.0135 0.015kLa (s-1) at T = 40oC 0.0076 0.0082 0.0134 0.0135 0.0137kLa (s-1) at T = 50oC 0.008 0.0131 0.0187 0.0159 0.0288
67
It is demonstrated from the results tabulated in Table 4.1 and 4.2 that the kLa
value increases with increase of temperature. Oxygen solubility in water decreases
from 7.55 mg/L to 5.61 mg/L as the temperature is increased from 30oC to 50oC.
This is clearly observed in Table A.4 in Appendix A1. Although the oxygen
solubility significantly decreases at higher temperature, the net increase of the kLa
observed in this experiment was due to the improved oxygen transfer through a series
of transport resistances between the bubbles and the liquid. Our data were in
agreement with the report published by Nielsen et al. (2003) because of the increase
in the oxygen transfer coefficient, kLa.
In order to provide sufficient oxygen in the liquid phase, the system will
require greater amounts of oxygen to saturate. One way to accomplish this was to
increase the aeration rate in the bioreactor. However, by referring to Equation 2.22,
enhanced of oxygen transfer rate was due to an increase in dCL/dt, which result to an
increase in kLa or an increase in the driving force term, C* - C. The difference in
oxygen solubility in the liquid phase is the driving force that increases the oxygen
transfer rate in bioreactor. Though the pattern of increase in temperature with
respect to kLa were comparable for Rushton turbine and marine impeller, the effect
was insignificant compared to the effect of other operational parameters namely
agitation, liquid viscosity and the volumetric power consumption on kLa.
4.2.3 Rate Limiting Step of Liquid Viscosities on KLa
The gas-liquid interface is one of the barriers in the biocatalytic system and is
frequently the rate-determining step in gas-liquid transfer process. The strong
influence of broth viscosities on the oxygen transfer coefficient, kLa is shown in
Table 4.3 and 4.4. This result is also depicted in Figure 4.2 and 4.4. The results are
consistent with what being reported by Martinov & Valev (2002).
68
Table 4.3 Increase of kLa values at high broth viscosities in Rushton turbine and
marine impeller at different impeller speeds
Rushton Turbine Impeller Speed, N (rpm) CMC solution ( ) 200 400 600 800 1000
kLa (s-1) at 0.25%w/v 0.0034 0.0173 0.0214 0.0257 0.0387kLa (s-1) at 0.5%w/v 0.0027 0.0154 0.0203 0.0222 0.0305kLa (s-1) at 1%w/v 0.0013 0.0063 0.012 0.019 0.0257
Marine Impeller Impeller Speed, N (rpm) CMC solution ( ) 200 400 600 800 1000
kLa (s-1) at 0.25%w/v 0.0025 0.0041 0.012 0.0122 0.0236kLa (s-1) at 0.5%w/v 0.0023 0.0067 0.0075 0.012 0.017kLa (s-1) at 1%w/v 0.0017 0.003 0.0054 0.0082 0.0093
Table 4.4 Increase of kLa values at high broth viscosities in Rushton turbine and
marine impeller at different air flow rates
Rushton Turbine Air Flow Rate, Q (l/min) CMC solution ( ) 3 6 9 12 15
kLa (s-1) at 0.25%w/v 0.0211 0.0213 0.0216 0.0283 0.0346kLa (s-1) at 0.5%w/v 0.0145 0.0171 0.0207 0.0265 0.0321kLa (s-1) at 1%w/v 0.0068 0.0102 0.0121 0.0163 0.0188
Marine Impeller Air Flow Rate, Q (l/min) CMC solution ( ) 3 6 9 12 15
kLa (s-1) at 0.25%w/v 0.0024 0.0082 0.012 0.0124 0.0139kLa (s-1) at 0.5%w/v 0.0039 0.008 0.0075 0.0099 0.0097kLa (s-1) at 1%w/v 0.0032 0.0041 0.0054 0.0055 0.0056
A sharp decrease of kLa up to 40% in both Rushton and marine impellers was
observed. The decrease in kLa was caused by an increase of broth apparent
viscosities from 0.25%(w/v) to 1%(w/v) of CMC solution. The result also shows
that under the same agitation and aeration rates, the kLa is highest in the air-water
system than that in the CMC solutions. In the Rushton turbine, maximum value of
kLa was 304.2 hr-1 at air-water system at 50oC and lowest kLa value attained was 4.68
hr-1 at 1%(w/v) CMC solutions at 30oC. As for the marine impeller, maximum value
of kLa was 117 hr-1 at air-water system at 50oC and lowest kLa value attained was
6.12 hr-1 at 1%(w/v) CMC solutions at 30oC. A viscous solution does not take up
oxygen as well as water. Identical results were obtained for both Rushton and
marine impeller.
69
The increase pseudoplastic behaviour of the liquid significantly altered the
mechanical property of the liquid. Consequently, lower Reynolds number (i.e. lower
mixing level or lower turbulence) in the viscous liquid in comparison to Newtonian
liquid at the same agitation and airflow rate was obtained. It is also believed that the
accumulation of the polymers (CMC) at the gas-liquid interface may responsible to
the increase of the oxygen transfer resistance from the air bubbles to the liquid. In
general, introducing polymer into the liquid will suppress the turbulence and increase
the oxygen transfer resistance. On the other hand, the reduction of power-law, due to
polymer presence, lowers the gas hold-up and decreases the interfacial area.
Consequently, a drop in oxygen transfer rate occurs. The variation in the kLa values
attained was consistent with what found in the literature by Arjunwadkar et al.
(1998), Shukla et al. (2001) and Martinov & Vlaev (2002).
4.2.4 The Significance Difference of Specific Power Input
Correlation proposed by Michel and Miller (1962) in Equation 3.9 was used
to compute the significance difference of volumetric power consumption per unit
volume by the Rushton and marine impellers on the kLa. The dependence of kLa on
volumetric power consumption for Rushton and marine impellers at different
temperature and viscosities is illustrated in Figure 4.5 and 4.6, respectively. It is
clear from the plots that the kLa depends on the power consumption, bearing a close
resemblance to the correlations found in the literature (Shukla et al., 2001, Martinov
& Vlaev, 2002, and Wernersson & Tragardh, 1999). The trend in Figure 4.5 and 4.6
shows that the kLa increase as the specific power input increases. It is evident that
the Rushton turbine provided a greater oxygen transfer rate compared to that of
marine impeller. In order to reach kLa ~ 26.28 hr-1 in air-water system at 30oC,
marine impeller requires 22.4 Wm-3 while Rushton turbine requires 12.7 Wm-3. On
the other hand, to reach kLa ~ 33.48 hr-1 in strong pseudoplastic fluid the values are
461 Wm-3 and 227 Wm-3 for the marine impeller and Rushton turbine, respectively.
Consequently, the same oxygen transfer rate was obtained by the Rushton turbine at
lower power consumption.
70
R2M = 0.93
R2M = 0.91
R2M = 0.96
R2R = 0.94
R2R = 0.97
R2R = 0.97
0.001
0.01
0.1
1 100 10000
Pg/VL (W/m3)
kLa
(s-1
) R
usht
on
0.001
0.01
0.1
1
kLa
(s-1
) M
arin
e
Rushton 30°CRushton 40°CRushton 50°CMarine 30°CMarine 40°CMarine 50°C
Figure 4.5 Dependence of kLa on volumetric power consumption, Pg/VL at
different temperature for Rushton turbine and marine impeller
R2M = 0.97
R2M = 0.98
R2M = 0.93
R2R= 0.99
R2R = 0.89
R2R = 0.92
0.001
0.01
0.1
1 100 10000
Pg/VL (W/m3)
kLa
(s-1
) R
usht
on
0.001
0.01
0.1
1
kLa
(s-1
) M
arin
e
1% - Rushton0.5% - Rushton0.25% - Rushton1% - Marine0.5 - Marine0.25% - Marine
Figure 4.6 Dependence of kLa on volumetric power consumption, Pg/VL at
different viscosities for Rushton turbine and marine impeller
71
However, the power required for the marine impeller to provide the same
agitation and aeration rates was much lower as compared to the Rushton turbine.
The measured volumetric power consumption for marine and Rushton impeller was
in the range of 0.002 kW/m3 to 0.5 kW/m3 and from 0.01 kW/m3 to 2 kW/m3
respectively. As illustrated in the power curve shown in Figure 2.8, power provided
by Rushton turbine is 5 times higher than the marine impeller one. Under the same
Reynolds number, Rushton turbine offers better local mixing and a greater kLa than
the marine impeller. This fact may look strange on the general conclusion that equal
power per unit volume and superficial gas velocity leads to the same kLa regardless
of the impeller type (Geankoplis, 1993).
Interestingly, power reduction (up to 5%) in the specific power input for both
Rushton and marine impeller was also observed. This power reduction was more
dominant especially on introduction of the gas in a viscous liquid, where there are
tendency for the gas to get accumulate behind the impeller blade and form a cavity
(Stanbury and Whitaker, 1984). The reduction in Pg/Po in the increase of liquid
viscosities however, does not significantly affect the oxygen transfer rate in the
bioreactor.
4.2.5 The Influence of Mixing and Flow Patterns on KLa
Agitation creates velocities in the fluid, which will result in a pumping flow
and a circulation flow in the tank. It is the convective flow that transports heat and
mass in the bioreactor over long distances, whereas the turbulent part of the flow
creates local mixing. Different flow pattern by Rushton and marine impellers as
illustrated in Figure 4.4 significantly affects the mixing capacity and kLa in the
bioreactor. Radial flow pattern by the Rushton turbine drives the liquid radially from
the impeller causes a compartmentalization problem when strong pseudoplastic
fluids are introduced into the liquid which results in a development of stagnant zones
away from the impellers. The axial-flow pattern created by the marine impeller
produced a higher turbulence compared to the Rushton turbine at the same agitation
rates. Under this condition, a better bulk mixing is in favours of marine impeller.
72
(a) (b)
Figure 4.7 Flow pattern produce by impellers. (a) axial-flow (b) radial-flow
The impeller speeds employed was to maintain the turbulence region in both
Newtonian and non-Newtonian. However, at low agitation rates in the viscous liquid
system, the two phases did not appear to be completely dispersed. Large gas bubbles
were observed in the CMC solutions at concentration of 0.5%(w/v) and 1%(w/v),
indicating that the gas and the liquid phases were not well dispersed. The Reynolds
number which indicates the turbulence in the bioreactor for Rushton turbine and
marine impeller are compared in Table 4.5. In the air-water system, the flow was
always in the developed turbulent regime and the Reynolds number exceeds 2 x 104.
Unlike in air-water system, the flow regime for mixing of the CMC solutions at
concentration of 1%(w/v) was transitional ( 460 < NRE < 2600) because of the high
apparent viscosities. Although a very low power number, Np (0.5 to 0.35) was
observed, the marine impeller manages to provide a high turbulence regime with a
Reynolds number as high as 2 x 105. This value is nearly a tenfold higher compared
to the value attained for the Rushton turbine.
73
Table 4.5 Turbulence parameter in the 16 liter bioreactor for Rushton turbine
and marine impeller at different impeller speeds and air flow rates
Air-water system Air-viscous system
Rushton
turbine
Marine
impeller
Rushton
turbine
Marine
impeller
Power number, Np 5 0.35 - 0.5 3.5 - 5 0.35 – 0.5
Reynolds number,
NRE
20156-146980 26443-191566 467-117487 616-127500
Impeller speed, N 200 – 1000 rpm 200 – 1000 rpm
Air flow rate, Q 3 – 15 l/min 3 – 15 l/min
A larger diameter of marine impeller would give better bulk mixing, however,
Rushton turbine are preferable for breaking up gas bubbles and promoting oxygen
transfer to the liquid. This will favour turbulent mixing over bulk mixing and
increased the kLa. Hence, a higher kLa values was attained in Rusthon turbine
compared to the marine impeller. This is illustrated in Figure 4.8 and 4.9. Although
liquid phase mixing is crucial, the effect of aeration rate on kLa values was also due
to the shearing and dispersing of gas bubbles, which leads to an increased of kLa and
contact times. The results attained consistent with the reports by other works
(Shukla et al., 2001, Badino Jr. et al., 2001, and Arjunwadkar et al., 1998).
74
0.005
R2R = 0.84
R2R = 0.90
R2R = 0.98
R2M = 0.84
R2M = 0.96
R2M = 0.88
0.001
0.01
0.1
0.001 0.01vg (m/s)
kLa
(s
R2M = 0.87
R2M = 0.94
R2M = 0.90
R2R = 0.97
R2R = 0.98
R2R = 0.83
0.001
0.01
0.1
0.001 0.01vg (m/s)
kLa
(s-1)
Rus
hton
0.001
0.01
0.1
kLa
(s-1)
Mar
ine
1% - Rushton0.5% - Rushton0.25 - Rushton1% - Marine0.5% - Marine0.25% - Marine
0.005
-1)
Rushton 30°CRushton 40°CRushton 50°CMarine 30°CMarine 40°CMarine 50°C
0.005
Figure 4.8 Dependence of kLa on volumetric superficial air velocity, vg at
different temperature for Rushton turbine and marine impeller
Figure 4.9 Dependence of kLa on volumetric superficial air velocity, vg at
different viscosities for Rushton turbine and marine impeller
75
4.3 The Dependence of KLa on the Operational Parameters at 16 Liter Scale
The kLa values obtained were correlated with respect to the superficial air
velocity, vg and the specific power consumption, Pg/VL, as shown in Equation 3.5.
cg
b
L
gL v
V
Paak ' (3.5)
The correlation proposed by Cooper et al. (1944) was less complex because it only
considered the effect of volumetric power consumption, Pg/VL and superficial air
velocity, vg on kLa. The analysis in correlating the kLa values with the operating
variables are summarised in Appendix D1 and Appendix D2 for Rushton and marine
impellers, respectively. Results in Table 4.6 summarise the constants in the
empirical correlation obtained at different operating temperatures for Rushton and
marine impellers. The experimental values of constant ‘b’ and ‘c’ between Rushton
turbine and marine impeller in different liquid viscosities are compared and
presented in Table 4.7.
Table 4.6 Comparison of experimental values of constant ‘b’ and ‘c’ between
Rushton turbine and marine impeller in different operating temperatures
Constant ‘b’ Constant ‘c’Liquidsystem
Temperature(oC) Marine
ImpellerRushtonTurbine
MarineImpeller
RushtonTurbine
30 0.356 0.420 0.773 0.40640 0.261 0.356 0.427 0.501Water-air50 0.266 0.318 0.693 0.605
76
Table 4.7 Comparison of experimental values of constant ‘b’ and ‘c’ between
Rushton turbine and marine impeller in different liquid viscosities
Constant ‘b’ Constant ‘c’ Liquidsystem
Temperature (oC) Marine
ImpellerRushtonTurbine
MarineImpeller
RushtonTurbine
Water-air 30 0.356 0.420 0.773 0.4060.25%(w/v) CMC - air
30 0.439 0.450 1.084 0.278
0.5%(w/v) CMC - air
30 0.381 0.431 0.555 0.485
1%(w/v) CMC - air
30 0.368 0.563 0.375 0.626
The parameter estimates (constant ‘b’ and ‘c’) reflect the influence of
volumetric power consumption and superficial air velocity on kLa. Constant ‘b’ is
the slope of the graph at constant air flow rate. The magnitude of ‘b’ represents the
level of dependence of kLa on the agitation. Constant ‘c’ is the slope of the graph at
constant agitation speed. The magnitude of ‘c’ represents the level of dependence of
kLa on the sparging rate applied to the system. A higher value of constant ‘b’ and ‘c’
means that a stronger dependency of kLa on operating variables and a steeper slope in
the logarithmic plots. A strong dependence means that a small change in the
operating variables (power input or superficial velocity) will significantly affect the
kLa values. Observing the results shown in Table 4.6 and 4.7, Rushton turbine
showed a strong dependence of the kLa on the volumetric power consumption and
the marine impeller has a strong dependence of kLa on superficial air velocity. The
results also indicate that for Rushton turbine, a variation in temperatures and
viscosities will results in an insignificant decrease and small increase in constant ‘b’,
respectively. Also noted that the constant ‘c’ increased with the increased of
temperatures and viscosities. However, in the marine impeller the values of constant
‘c’ drops significantly with the increased of broth viscosity.
Reviewing the parameter estimates presented in Table 4.6 and Table 4.7, it is
observed that for air-water system, ranges of values for Rushton turbine are within
0.32 < b < 0.42 and 0.4 < c < 0.6. For air-viscous liquid system, the constants are
0.45 < b < 0.56 and 0.27 < c < 0.63. As for the marine impeller, the constants
attained are within 0.26 < b < 0.36 and 0.43 < c < 0.77 for air-water system. For air-
77
viscous liquid system, the constants are 0.36 < b < 0.44 and 0.37 < c < 1.08. These
values are tested for specific power consumption within range from 0.01 to 2 kW/m3
and 0.002 to 0.5 kW/m3 for Rushton and marine impellers respectively. The
operating variables were correlated at corresponding ranges of superficial air velocity
of 1.5 x 10-3 to 8 x 10-3 and at apparent viscosity of 0.81 to 35 cP for Rushton and
marine impellers. The predictions of the empirical equation agreed well with the
measured data within 15% and 30% of average and maximum standard error,
respectively.
The values attained are unique to the bioreactor used and fell within the
acceptable range if published data in Table 1.1 (section 1.1) are taken as a
comparison. Kawase and Moo-Young (1988) proposed that in promoting a good
oxygen transfer in the bioreactor, the value of constant ‘b’ and ‘c’ should not fall
beyond the range of 0.37 < b < 0.8 and 0.2 < c < 0.84, respectively. By employing
the empirical correlation proposed by Cooper et al. (1944) at different impeller
speeds and air flow rates, the values of constant ‘b’ and ‘c’ achieved are within the
range proposed by Kawase and Moo-Young (1988). This proved that the operating
variables selected are suitable and applicable in determining a wide range of kLa
values and promotes a good oxygen transfer rate in the bioreactor. The straight-line
trend (indicated by excellent regression coefficients) of the kLa with respect to the
operating variable values in the logarithmic plots presented in Figure 4.1, 4.2, 4.3,
4.4, 4.5, 4.6. 4.8 and 4.9 signifies that the experimental work matched with the
published results.
Constant ‘a’ is the slope of graph at constant volumetric power consumption
and superficial gas velocity. The constant ‘a’ in the empirical correlation cannot be
compared directly with the results from the published works because constant ‘a’
represents the characteristic of the process condition to measure the value of kLa in
the bioreactor. The values of constant ‘a’ are summarised in Table 4.8 and Table 4.9
at different liquid temperatures and viscosities, respectively. The process condition
may influence the value of constant ‘b’ and ‘c’ significantly. The process condition
include the type of impeller, number of impeller, geometry of bioreactor, liquid
model used, working volume of bioreactor, and type of aeration employed.
78
Table 4.8 Comparison of experimental values of constant ‘a’ between Rushton
turbine and marine impeller in different operating temperatures
Constant ‘a’ Liquid system Temperature (oC) Marine
ImpellerRushtonTurbine
30 0.2034 0.018740 0.0523 0.0013Water-air 50 0.2583 0.1678
Table 4.9 Comparison of experimental values of constant ‘a’ between Rushton
turbine and marine impeller in different liquid viscosities
Constant ‘a’ Liquid system Temperature (oC) Marine
ImpellerRushtonTurbine
Water-air 30 0.2034 0.01870.25%(w/v) CMC -
air30 0.5361 0.0057
0.5%(w/v) CMC - air 30 0.0322 0.01631%(w/v) CMC - air 30 0.076 0.011
4.4 Evaluation of the Scale-up Protocol
The performance of 16 liter and 150 liter bioreactor on the oxygen transfer
rate was compared at various temperatures and viscosities by employing the
proposed scale-up protocol as illustrated in Figure 3.3. Similar values of kLa attained
at 16 liter bioreactor are maintained upon scale-up to 150 liter by manipulation of
power input and aeration rates. The kLa at 150 liter was matched with was obtained
at 16 liter by adjusting the impeller rotation speed and air flow rates. The scale-up
was performed by considering the dynamic similarity in both scales (16 liter and 150
liter) and assumed equality in turbulence in hydrodynamic. The efficiency and
consequences in employing the scale-up protocol was evaluated in the following
section.
79
4.4.1 Determination of Operating Variables at 150 Liter Bioreactor
The scale-up equations was applied in order to determine the minimum and
the maximum value of the operating variables (impeller speeds and air flow rates)
upon scale-up on a basis of constant kLa from 16 liter to 150 liter bioreactor. The
results for the determination of air flow rates and impeller speeds at 150 liter scale on
the basis of constant volumetric power input with superficial velocity are tabulated in
Table 4.10 and Table 4.11, respectively. The results for the determination of
impeller speeds and air flow rates at 150 liter scale on the basis of constant
volumetric power input with impeller tip speed are presented in Table 4.12 and Table
4.13, respectively.
Table 4.10 Determination of air flow rates at 150 liter scale on the basis of
constant volumetric power input with superficial velocity
Q1 (l/min) Q1(m3/s) DT2 (m) DT1 (m) Q2 (m
3/s) Q2 (l/min) 3691215
0.00050.00010.000150.00020.00025
0.410.410.410.410.41
0.20.20.20.20.2
0.000210.000210.000210.000210.00021
12.607525.21537.822550.43
63.0375
The operating variables achieved at 150 liter scale were calculated based on
different types of scale-up criterion. It cannot be adopted directly in order to achieve
a similar kLa values at 150 liter bioreactor. However, the results attained are used as
a base line in determining the operating variables at 150 liter to achieve the similar
value of kLa as in the 16 liter scale. These operating variables were set as the upper
level and the lower level in the ‘trial-and-error’ step. It represents the inner-loop of
the proposed scale-up protocol. The base line and the constraint of the operating
variables at 150 liter bioreactor are shown in Table 4.14. In referring to the operating
variables achieved and the limitation in allowable operating range at 150 liter vessel,
it was found that the value of air flow rates are a bit out of range. Therefore, two sets
of operating variables were proposed to obtain a similar kLa values as in the 16 liter
bioreactor. The proposed operating variables at 150 liter bioreactor are presented in
Table 4.15.
81
Table 4.14 Base line in determining the operating variables at 150 liter scale
Scale-up criteria Operating
Variables Constant Pg/VL and
ND
Constant Pg/VL and
vg
Allowable
Operating Range at
150 liter
Impeller
Speed, N2
65.2 – 326 rpm 70 – 350 rpm 50 – 600 rpm
Air Flow Rate,
Q2
12.6 – 63 l/min 30.7 – 153 l/min 5 – 100 l/min
Table 4.15 The proposed operating variables at 150 liter bioreactor
Scale Impeller speeds, N Air flow rates, Q Liquid model
150 liter (1st Trial) 50 – 250 rpm 10 – 50 l/min Water & CMC
150 liter (2nd Trial) 60 – 300 rpm 10 – 50 l/min Water & CMC
4.4.2 Operating Variables on a Basis of Constant KLa
From the proposed agitation and aeration rates, the kLa attained at 150 liter
are closely matched with the kLa in the 16 liter scale. The objective of the ‘trial-and-
error’ step in the scale-up protocol was to achieve a comparable operating condition
in both scales and to determine the scaling-up factor upon scale-up from 16 liter to
150 liter bioreactor. By manipulation of the power input and the superficial air
velocity, a comparable kLa values was successfully achieved. The results of the
‘trial-and-error’ step in distilled water at 30oC are shown in Table 4.16. Similar
results are obtained for other operational parameters namely at different viscosities
and temperatures. The results are depicted in Table D.1, D.2, D.3, D.4 and D.5 in
Appendix D3.
82
Table 4.16 Results of the ‘trial-and-error’ step in distilled water at 30oC
Vary impeller speed at constant aeration16 liter 150 liter New Operating
ConditionsN1
(rpm) Q1
(l/min) kLa(s-1)
Trial N(rpm)
Q(l/min)
kLa(s-1)
N2
(rpm) Q2
(l/min) 1 50 30 0.00588200 9 0.00732 60 30 0.007375
59.5 30
1 100 30 0.0181400 9 0.01982 120 30 0.0197
120 30
1 150 30 0.0296600 9 0.02262 180 30 0.0325
133.6 30
1 200 30 0.0362800 9 0.03932 240 30 0.0419
221.75 30
1 250 30 0.04071000 9 0.07492 300 30 0.0574
391.5 30
Scale-up ratio, R1 (average value) = 0.3
Vary air flow rate at constant agitation16 liter 150 liter
(1st Trial) 150 liter
(2nd Trial) N1
(rpm) Q1
(l/min) kLa(s-1)
N(rpm)
Q(l/min)
kLa(s-1)
N2
(rpm) Q2
(l/min) kLa(s-1)
600 3 0.0213 150 10 0.015 180 10 0.0194
600 6 0.0243 150 20 0.0211 180 20 0.0248
600 9 0.0259 150 30 0.0295 180 30 0.0329
600 12 0.0374 150 40 0.0371 180 40 0.0373
600 15 0.0407 150 50 0.0416 180 50 0.044
From interpolation and extrapolation:- New Operating Conditions
Q2
(l/min) N2
(rpm) 13.5 18019 180
21.4 18040 180
45.1 180Scale-up ratio, R2 (average value) = 3.27
83
It was known that the geometry of the bioreactor is the same in both scales.
However, the dimensions are difference as the scale increases. Different in mixing
and liquid rheology may also cause a difficulty in scaling-up of a bioreactor (Al-
Masry, 1999). Thus, the CMC solution and the air-water solution were used as a
model solution for non-Newtonian fluid and Newtonian fluid, respectively.
Parameters like pH, temperature and liquid viscosity are kept under tight control and
remain the same upon scaling-up on a basis of constant kLa. At different type of
liquid solution and operating variables, the scaling-up factor was determined. The
new operating variables at 150 liter scale and the scaling-up factor are shown in
Table 4.17.
Table 4.17 Operating variables at 150 liter scale on a basis of constant kLa
Liquid System Operating
Variables Air-water
System
Air-Viscous
System
Impeller Speed, N2 59 – 395 rpm 30 – 311 rpm
Air Flow Rate, Q2 9.3 – 54 l/min 7 – 50 l/min
Scale-up Factor, R
Scale-up Impeller
Speed, R1
0.318 0.245
Scale-up Air Flow Rate,
R2
3.41 2.85
In referring to the results attained in Table 4.17, scale-up protocol based on
constant kLa was successfully employed in this study. However, the scale-up factor
achieved for the non-Newtonian system is clearly different from the Newtonian one.
This variation is possibly due to the rising of the pseudoplasticity on oxygen transfer
rate upon scale-up. The scaling factor to be employed upon scale-up from 16 liter to
150 liter vessel on a basis of constant kLa is the average value of the scaling-up factor
in both Newtonian and the non-Newtonian system. The results obtained were in
agreement with the mass transfer law as stated by Geankoplis (1993). It was stated
84
that the greater the scale of operation, the harder to maintained the oxygen transfer
rate in the bioreactor.
Scale-up of the bioreactor from 16 liter to 150 liter scale must meet the
oxygen transfer requirements while maintaining a low variation in power input and a
controlled flow pattern. Technically, in order to obtain a similar value of kLa in both
scales, the differential in the constant ‘b’ and ‘c’ was kept as low as possible.
Therefore, to lower the hydrodynamics difference upon scale-up, the scaling-up
factor was computed. The scaling-up factor is the normalized value of operating
variables (impeller speeds and air flow rates) at larger scale to the smaller scale. The
scaling-up factor was calculated to observe the influence on the operating conditions
at 150 liter scale if the impeller speed and the air flow rate in the 16 liter was varied.
Upon achieving the impeller speeds and air flow rates at 150 liter scale, several
hydrodynamic parameters namely the impeller Reynolds number, the volumetric
power input and the superficial air velocity in the bioreactor were computed to define
the bioreactor operating conditions at larger scales. The significance and the
consequences of the hydrodynamic difference upon scale-up were evaluated based
on the dependence of the kLa on the operating variables. These will be further
discussed in the next section.
85
4.4.3 The Consequences of Scale-up Exercise Based on Constant KLa
In scaling-up from 16 to 150 liter, at different temperatures and viscosities,
proportionality of kLa to the aeration efficiency and specific power input was
obtained. This identical behavior of oxygen transfer rate with respect to the
operating variables demonstrate the validity of the proposed scale-up protocol in
keeping the kLa value constant upon scale-up. Figure 4.10 and 4.11 illustrates the
dependence of kLa on impeller speed in distilled water and CMC solutions at
different temperatures and viscosities, respectively.
R2 = 0.99 R
2 = 0.97
0.001
0.01
0.1
10 100 1000Impeller speed, N (rpm)
kLa
(s-1
)
N (16 liter)
N (150 liter)
R2 = 0.99 R2 = 0.94
0.001
1
0.0
0.
0 100 1000
Impeller speed, N (rpm)
k La
(s-1
)
1
1
N (16 liter)
N (150 liter)
R2 = 0.99 R2 = 0.97
0.001
0.01
0.1
10 100 1000Impeller speed, N (rpm)
kLa
(s-1
)
N (16 liter)
N (150 liter)
(a) (b)
(c)
Figure 4.10 Dependence of kLa on impeller speed in distilled water at different
temperatures (a) T = 30oC (b) T = 40oC (c)T = 50oC
86
R2 = 0.98 R
2 = 0.90
0.001
0.01
0.1
10 100 1000Impeller speed, N (rpm)
k La
(s-1
)
N (16 liter)
N (150 liter)
R2 = 0.94 R2 = 0.92
0.0
0.1N (16 liter)
N (150 liter)
01
0.
10 100 1000Impeller speed, N (rpm)
kLa
(s-1
)
01
(a) (b)
R2 = 0.98 R2 = 0.99
0.001
0.01
0.1
10 100 1000Impeller speed, N (rpm)
kLa
(s-1
)
N (16 liter)
N (150 liter)
(c)
Figure 4.11 Dependence of kLa on impeller speed in CMC solution at different
concentrations (a) CMC 0.25%(w/v) (b) CMC 0.5%(w/v) (c) CMC 1% (w/v)
In comparison to the results attained at 16 liter scale, the impeller speed
significantly change as the scale increases. It was found that the impeller speed was
greater at 16 liter scale as illustrated in Figure 4.10 and Figure 4.11. Due to large
impeller diameter at 150 liter scale, a low rotational speed was sufficient to provide
the same agitation rate and maintained the oxygen transfer rate upon scale-up. The
impeller speeds employed were completely different in both scale, however, the
dependence of kLa on the volumetric power consumption is almost identical to each
other upon scale-up from 16 liter to 150 liter bioreactor at different temperatures and
viscosities.
87
Figure 4.12 shows the dependence of kLa on volumetric power consumption
in distilled water at different temperatures.
0.001
0.01
0.1
0.01
0.1
1 10 100 1000 10000Pg/VL (W/m
3)
kLa
(s-1
)
16 liter 150 liter
R2 = 0.99
R2 = 0.98
1 10 100 1000 10000P /V (W/m3)
k La
(s-1
)
16 liter 150 liter
R2 = 0.99
R2 = 0.94
g L
(a) (b)
0.01
0.1
1 10 100 1000 10000Pg/VL (W/m
3)
kLa
(s-1
)
16 liter 150 liter
R2 = 0.97
R2 = 1
(c)
Figure 4.12 Dependence of kLa on volumetric power consumption in distilled
water at different temperatures (a) T = 30oC (b) T = 40oC (c)T = 50oC
The results in Figure 4.12 proved that upon scaling-up, a similar slope and the
plots are coincide with each other meaning that equal kLa dependency on power
input was successfully achieved. In comparison with the dependence of kLa on
volumetric power consumption in the Newtonian fluid, the non-Newtonian fluid
which is the air-viscous system caused a slight variation on the dependence of kLa on
the volumetric power consumption upon scale-up from 16 to 150 liter scale. From
observation in the bioreactor upon operation, it was seen that stagnant zones
developed was larger at 150 liter scale due to the compartmentalization. The
88
dependence of kLa on volumetric power consumption in CMC solution at different
liquid viscosities is presented in Figure 4.13.
0.001
0.0
0.
1 10 100 1000 10000
Pg/VL (W/m3)
kLa
(s-1
)
1
0.001
0.01
0.1
1 10 100 1000 10000Pg/VL (W/m
3)
kLa
(s-1
)
16 liter 150 liter
R2 = 0.98
R2 = 0.89
16 liter 150 liter
R2 = 0.95
R2 = 0.92
1
0.001
0.01
0.1
0.1 1 10 100 1000 10000Pg/VL (W/m
3)
kLa
(s-1
)
16 liter 150 liter
R2 = 0.99
R2 = 0.98
(a) (b)
(c)
Figure 4.13 Dependence of kLa on volumetric power in CMC solution at different
concentrations (a) CMC 0.25%(w/v) (b) CMC 0.5%(w/v) (c) CMC 1% (w/v)
As illustrated in Figure 4.12 and 4.13, the specific power input required to
keep the kLa value constant at 150 liter was lower compared to the 16 liter scale
experiment. The volumetric power consumption computed at 150 liter scale is 53%
lower than the power attained at 16 liter bioreactor. This may be resulted from the
increase in the liquid volume and the gassing effect at larger scale significantly
changes the power consumption upon scale-up (Michel and Miller, 1962). This
agrees with the general opinion that not everything can be maintained constant upon
scale-up (Kossen and Oosterhuis, 1985).
89
The slopes in the logarithmic plots in Figure 4.13 are similar in both scales
even though the plots are not coinciding with each other. The dependency of kLa on
the power input in non-Newtonian fluid was compared in order to observe the
differences upon employing the scaling-up factor in scaling-up on a basis of constant
kLa. As seen in Figure 4.12 and Figure 4.13, equal volumetric power consumption
may be achieve if higher power input was employed. Nevertheless, by doing so, it
will create a deviation in the kLa value upon scale-up from 16 liter to 150 liter.
Different impeller speed at higher scale will result in a different power input upon
scale-up. However, the dependence of kLa on the volumetric power consumption
was equivalent in both Newtonian and non-Newtonian fluids upon scale-up from 16
to 150 liter vessel.
Similarly as the impeller speed, the air flow rate was significant altered at
higher scale. This is illustrated in Figure 4.14. Figure 4.14 shows the dependence of
kLa on the air flow rate upon scale-up from 16 liter to 150 liter bioreactor based on
constant kLa in different liquid viscosities and operating temperatures. The air flow
rate was proportionally increased as the scale increases. Based on the logarithmic
plots in Figure 4.14, by implying the scaling-up factor for the air flow rate, similar
kLa values as in 16 liter scale was successfully achieved in the 150 liter bioreactor.
The increase of air flow rates necessitates in compensating with increase of
bioreactor volume. A greater volume at 150 liter and changes in surface to volume
ratio upon scale-up, a higher air flow rates was employed. In order to maintain the
kLa at 150 liter scale, it requires increasing the air flow rates up to three times higher.
The air flow rates were also increased at 150 liter scale to create similar turbulence
and provide adequate oxygen supply as in the 16 liter scale. This finding was
consistent with the results reported by Maranga et al. (2004).
90
R2 = 0.84 R2 = 0.99
0
0.
.01
1
1 10 100Air flow rate,Q (l/min)
k La
(s-1
)
16 liter
150 liter
R2 = 0.90 R2 = 0.95
0.01
0.1
1 10 100Air flow rate,Q (l/min)
k La
(s-1
)
16 liter
150 liter
(a) (b)
R2 = 0.98 R2 = 0.98
0
0.
.01
1
1 10 100Air flow rate,Q (l/min)
k La
(s-1
)
16 liter
150 liter
R2 = 0.83 R2 = 0.99
0.01
0.1
1 10 100Air flow rate,Q (l/min)
k La
(s-1
)
16 liter
150 liter
(c) (d)
R2 = 0.92 R2 = 0.99
0
0.
.01
1
1 10 100Air flow rate,Q (l/min)
k La
(s-1
)
16 liter
150 liter
R2 = 0.98 R2 = 0.98
0.001
0.01
0.1
1 10 100Air flow rate,Q (l/min)
k La
(s-1
)
16 liter
150 liter
(e) (f)
Figure 4.14 Dependence of kLa on air flow rate in distilled water at different
temperatures (a) T = 30oC (b) T = 40oC (c)T = 50oC and CMC solution at different
concentrations (d) CMC 0.25%(w/v) (e) CMC 0.5%(w/v) (f) CMC 1% (w/v)
91
The air flow rates at 150 liter scale may be different from the air flow rates at
16 liter scale, however, the superficial air velocity are almost identical in both scales.
This is illustrated in Figure 4.15 and Figure 4.16 for Newtonian fluid and non-
Newtonian fluid, respectively.
0.01
1
0.001 0.01vg (m/s)
-1
0.
0.01
0.1
0.001 0.01vg (m/s)kL
a (s
-1)
16 liter 150 liter
R2 = 0.95
R2 = 0.90
16 liter 150 liter
R2 = 0.99
R2 = 0.84
kLa
(s)
(a) (b)
0.01
0.1
0.001 0.01vg (m/s)
k La
(s-1
)
16 liter 150 liter
R2 = 0.98
R2 = 0.98
(c)
Figure 4.15 Dependence of kLa on superficial air velocity in distilled water at
different temperatures (a) T = 30oC (b) T = 40oC (c)T = 50oC
92
0.01
0.
001 0.01vg (m/s)
kLa
(s-1
)
1
0.01
0.1
0.001 0.01vg (m/s)
kLa
(s-1
)
16 liter 150 liter
R2 = 0.99
R2 = 0.98
16 liter 150 liter
R2 = 0.99
R2 = 0.83
0.
(a) (b)
0.01
0.1
0.001 0.01vg (m/s)
kLa
(s-1
)
16 liter 150 liter
R2 = 1
R2 = 0.97
(c)
Figure 4.16 Dependence of kLa on superficial air velocity in CMC solution at
different concentrations (a) CMC 0.25%(w/v) (b) CMC 0.5%(w/v) (c) CMC 1% (w/v)
In referring to the logarithmic plots in Figure 4.15 and Figure 4.16, unlike the
dependence of kLa on the volumetric power consumption, the dependence of kLa on
the superficial air velocity are not coinciding with each other. It was found that the
superficial air velocity in the 16 liter vessel was higher compared to the 150 liter
ones. However, the slopes of the trend achieved are the same in both scales of
operation. In practicing the scale-up protocol, a maximum aeration of 1.5 vvm was
applied at 16 liter bioreactor and only 0.5 vvm of aeration was employed at 150 liter
scale. This may be due to the high residence time of bubbles, greater volume and
higher vessel in 150 liter scales (Maranga et al., 2004). Interestingly, by
manipulating the operating variables a similar turbulence was successfully achieved
in promoting a similar oxygen transfer rate in both scales. The turbulence in both
scales was compared at different impeller speeds as shown in Figure 4.17.
93
R2 = 1
R2 = 1
10000
100000
1000000
10 100 1000Impeller speed, N (rpm)
Rey
nold
s nu
mbe
r, N
RE
16 liter
150 liter
R2 = 1
R2 = 1
10000
100000
1000000
10 100 1000Impeller speed, N (rpm)
Rey
nold
s nu
mbe
r,N
RE
16 liter
150 liter
(a) (b)
R2 = 1
R2 = 1
R2 = 1
R2 = 1
1000
10000
100000
10 100 1000Impeller speed, N (rpm)
Rey
nold
s nu
mbe
r, N
RE
16 liter
150 liter
R2 = 1R2 = 1
100
1000
10000
10 100 1000Impeller speed, N (rpm)
Rey
nold
s nu
mbe
r, N
RE
16 liter
150 liter
10000
100000
1000000
10 100 1000Impeller speed, N (rpm)
Rey
nold
s nu
mbe
r, N
RE
16 liter
150 liter
R2 = 1
R2 = 0.99
10000
100000
1000000
10 100 1000Impeller speed, N (rpm)
Rey
nold
s nu
mbe
r, N
RE
16 liter
150 liter
(c) (d)
(e) (f)
Figure 4.17 Dependence of kLa on Reynolds number in (a) water (T=30oC) (b)
water (T=40oC) (c) water (T=50oC) (d) CMC 0.25%(w/v) (e) CMC 0.5%(w/v) (f)
CMC 1% (w/v)
94
Based on the results presented in the previous logarithmic plots, equal liquid
motion was attained and the corresponding velocities are approximately the same in
both scales. Hence, equal mixing capacity was also achieved for both Newtonian
and non-Newtonian fluids upon scale-up from 16 liter to 150 liter bioreactor. It was
discovered that the operating temperature and the liquid viscosities are independent
of scale. Similar temperature was employed at 150 liter scale and it did not show a
significant effect on kLa upon scale-up (see Figure 4.12 and 4.15). A variation of kLa
dependence on the operating parameters in the non-Newtonian fluid showed that it is
difficult to maintain a similar hydrodynamics in the non-Newtonian fluid compared
to the Newtonian ones. The impeller speeds, air flow rates, volumetric power
consumption and the superficial air velocity was known to be the manipulate
variables and scale-dependent in employing the scale-up factor upon scale-up from
16 liter to 150 liter bioreactor on a basis of constant kLa. The following section will
be focussing on the significance of the constants in the empirical correlation upon
scaling-up the bioreactor.
4.4.4 The Dependence of KLa on the Operational Parameters at 150 Liter
Scale
Upon scaling-up from 16 liter to 150 liter bioreactor, a constant kLa was
successfully achieved in both scales. Similar empirical correlation was employed in
both scales and the parameter estimates (constant ‘b’ and ‘c’) was compared to
observe the significance of these constants upon scale-up based on constant kLa. The
operating variables namely the volumetric power consumption and the superficial air
velocity were correlated with the kLa values attained in the 150 liter scale. The
results are summarised in Appendix D4. It was previously illustrated in the
logarithmic plots that the trend of kLa dependency on the operating variables was
almost identical in both scales. However, to examine how close the slope of the
logarithmic plots was, the constant ‘b’ and ‘c’ in both scales were compared. Table
4.18 summarised the value of constant ‘b and ‘c’ in both scales at different operating
95
temperature in air-water system. Where else, Table 4.19 showed the value of
constant ‘b and ‘c’ in both scales at different liquid viscosities in air-viscous system.
Table 4.18 The values of constant ‘b’ and ‘c’ upon scale-up from 16 liter to 150
liter at different operating temperature in air-water system
Constant ‘b’ Constant ‘c’ Liquid system Temperature (oC) 16 liter 150 liter 16 liter 150 liter 30 0.4196 0.388 0.4063 0.549340 0.3561 0.3541 0.5009 0.4491Water-air 50 0.3179 0.3207 0.6046 0.5257
Table 4.19 The values of constant ‘b’ and ‘c’ upon scale-up from 16 liter to 150
liter at different liquid viscosities in air-viscous system
Constant ‘b’ Constant ‘c’ Liquid system Temperature (oC) 16 liter 150 liter 16 liter 150 liter
0.25%(w/v) CMC - air
30 0.4485 0.4282 0.278 0.4458
0.5%(w/v) CMC - air
30 0.4305 0.4421 0.4849 0.4611
1%(w/v) CMC - air
30 0.5626 0.4177 0.6264 0.5449
As presented in Table 4.18, the exponent value of constant ‘b’ in distilled
water is almost similar in both scales. Meaning that, the degree of kLa dependence
on volumetric power consumption is identical in both scales. A minor variation in
the exponential value of kLa dependence on the superficial velocity (constant ‘c’)
was obtained in the air-water system upon scale-up. In the air-viscous system, the
values of constant ‘b’ are comparable in both scales except for 1%(w/v) CMC
solution where the values are a bit different. As summarised in Table 4.24, identical
trend are not accomplished for the dependence of kLa on the superficial air velocity
in the air-viscous system. This proved that, under the same oxygen transfer rate, it
was difficult to maintain a similar kLa dependency on superficial air velocity upon
scale-up from 16 to 150 liter. This has been previously reported by Wernersson and
Tragardh (1999). However, by employing the scale-up protocol, the differences of
the superficial air velocity in both scales were lowered.
96
In order to compare the performance of 16 liter and 150 liter bioreactor, the
operating variable namely impeller speed and air flow rate was changed in order to
maintain the kLa value constant at higher scale. The range of operating parameters
varied upon scale-up from 16 liter to 150 liter vessel to obtain a similar kLa value are
presented in Table 4.20 and Table 4.21 in the Newtonian and non-Newtonian fluid,
respectively. The results attained are consistent with the literature reported by
Wernersson and Tragardh (1999).
Table 4.20 The values of range of operating parameters varied upon scale-up
from 16 liter to 150 liter at different operating temperature in air-water system
Scale of operation Manipulated Variables 16 liter 150 liter Range of constant ‘b’ 0.32 < b < 0.42 0.32 < b < 0.39 Range of constant ‘c’ 0.4 < c < 0.6 0.44 < c < 0.54 Range of Pg/VL 0.0013 < Pg/VL < 2 kW/m3 0.001 < Pg/VL < 4.2
kW/m3
Range of vg 1.6 x 10-3 < vg < 8 x 10-3
m/s 1.7 x 10-3 < vg < 7 x 10-3
m/s
Table 4.21 The values of range of operating parameters varied upon scale-up
from 16 liter to 150 liter at different liquid viscosities in air-viscous system
Scale of operation Manipulated Variables 16 liter 150 liter Range of constant ‘b’ 0.45 < b < 0.56 0.41 < b < 0.44 Range of constant ‘c’ 0.27 < c < 0.63 0.44 < c < 0.54 Range of Pg/VL 0.0013 < Pg/VL < 2 kW/m3 0.0001 < Pg/VL < 1.7
kW/m3
Range of vg 1.6 x 10-3 < vg < 8 x 10-3
m/s 9 x 10-4 < vg < 6 x 10-3 m/s
It was discovered that the constant ‘b’ may influence the volumetric power
consumption and the constant ‘c’ may significantly effects the superficial air velocity.
By employing the same empirical correlation in both scales, both of these values
need to be matched upon scale-up. Hence, the impeller speeds and the air flow rates
are important manipulated variables in scaling-up on a basis of constant kLa. In
predicting the kLa values, an average deviation of 10% and maximum deviation of
20% standard error was expected. The experiment data fitted well with the empirical
correlation proposed by Cooper et al. (1944) with a high correlation coefficient, R2.
97
4.5 The Performance of E.coli Batch Fermentation at 16 and 150 Liter Scale
The scale-up workability was tested by comparing the results of fermentation
kinetic at 16 liter with 150 liter. The different dependency of kLa on important
transport properties makes scale-up something of an art. Therefore, in scaling-up
E.coli fermentation from 16 liter to 150 liter scale, the kLa was taken as the scale-up
criteria and oxygen was assumed as the only growth limiting factor. By employing
the scale-up factor, the impeller speeds and the air flow rates in 150 liter scale were
designed. The summary of the E.coli fermentation in 16 liter and 150 liter scale are
shown in Appendix E1 and Appendix E2, respectively. Time-course profiles of cell
growth, glucose consumption, specific oxygen uptake rate and kLa dependence on
operating variables at 16 liter and 150 liter were compared to observe the
significance differences in maintaining a constant kLa upon scale-up. The kinetic
profiles of cell growth and glucose consumption are illustrated in Figure 4.18.
0
0.5
1
1.5
2
2.5
3
3.5
4
4.5
5
0 1 2 3 4 5 6 7 8 9 10
time (h)
0
5
10
15
20
25
Subs
trat
e (g
/L)
Biomass (16 liter)
Biomass (150 liter)
Substrate (16 liter)
Substrate (150 liter)
t(g/
Lig
hD
ryC
ellW
e
Figure 4.18 Growth curve and substrate consumption of recombinant E.coli
in 16 and 150 liter
98
As presented in Figure 4.18, the E.coli strain exhibits a similar profile of
growth in 16 and 150 liter. A maximum cell density reached was 4.6745 g/l and
4.4645 g/l in 16 liter and 150 liter scale, respectively. Both profiles showed a sharp
increase after an hour of fermentation until a stationary phase was reached. As
shown in Figure 4.14, glucose consumption in both scales was 11.8 g/l through out
the entire fermentation and was not completely consumed. This proved that the
substrate (carbon source) was not limiting the cell growth until the end of the
fermentation. Similar kinetic profiles of cell growth and glucose consumption
obtained at 16 and 150 liter is reflected by the similar kLa upon scale-up.
The specific oxygen uptake rate (qO2) of the E.coli strain is illustrated in
Figure 4.19. The maximum specific oxygen consumption rate was found to be
431.55 mg O2 per g cell.h and 630.81 mg O2 per g cell.h in 16 liter and 150 liter
bioreactor, respectively. It was observed that the consumption rate was higher at the
beginning of the exponential phase and maintained almost a constant rate as the
fermentation proceeds.
0
100
200
300
400
500
600
700
0 2 4 6 8time (h)
q O
2 (m
g O
2 / g
cel
l. h)
16 liter
150 liter
10
Figure 4.19 Specific oxygen uptake rate of recombinant E.coli in 16 and 150 liter
99
In scaling-up bioreactor, it is necessitates to overcome the oxygen transport
limits on cell growth and provide a similar kLa values in both scales. The profile of
oxygen transfer rate (OTR) is illustrated in Figure 4.20. It was observed that the kLa
was increased as high as 155.95 h-1 and 145.99 h-1 in compensating with the oxygen
demand of E.coli strain in 16 liter and 150 liter scale, respectively. It was seen that
an identical profiles of oxygen transfer rate was achieved in both scales. Hence, the
operating variables employed at both scales were sufficient to provide the oxygen
required to exceed the limitation of oxygen consumption by cells and maintain the
dissolved oxygen level approximately constant except during the oxygen-deficient
conditions.
0
20
40
60
80
100
120
140
160
180
0 2 4 6 8time (h)
Oxy
gen
Tra
nsfe
r R
ate,
kLa
(h-1
)
16 liter
150 liter
10
Figure 4.20 Oxygen transfer rate of recombinant E.coli in 16 and 150 liter
The kinetic profiles may not be coinciding with each other; however, F-test
for the equality of kinetic profiles for E.coli fermentation in 16 liter and 150 liter
scale was performed to demonstrate the similarity of these profiles. The results of
the F-test are presented in Appendix F. Similar kinetic profiles of cell growth,
glucose consumption, specific oxygen uptake rate and oxygen transfer rate achieved
in both scales demonstrated that the scale-up protocol was successfully employed in
the E.coli fermentation at 16 and 150 liter scale.
100
4.5.1 Dependence of KLa on the Operational Parameter in E.coli Fermentation
The dependence of kLa on the volumetric power consumption and superficial
air velocity were determined at the exponential growth phase of the E.coli
fermentation. At 16 liter scale, the kLa dependence on the operating variables was
plotted at constant agitation rate (i.e. 650 rpm) and constant aeration rate (i.e. 12
l/min). At 150 liter scale, it is plotted at constant impeller speed (i.e. 244 rpm) and
constant air flow rate (i.e. 30.2 l/min). This is illustrated in Figure 4.21. As shown
in Figure 4.21, at different sparging rate; similar trend of kLa dependence on
superficial air velocity was achieved. However, the slope of kLa dependence on the
volumetric power consumption at 150 liter scale deviate from the trend obtained for
16 liter scale. To maintain the kLa above 140.4 hr-1, there is an increase in specific
power input at 150 liter scale nearly twice compared to the power input attained at 16
liter. This is the consequence of the increase of impeller speed to maintain the kLa
value constant upon scale-up and to provide a similar turbulence in the E.coli
fermentation at both scales.
0.01
0.1
0.01
0.1
0.001 0.01vg (m/s)
kLa
(s-1
)
150 liter 16 liter
R2 = 0.91 R2 = 0.92
100 1000 10000
Pg/VL (W/m3)
ka
(s-1
)
150 liter 16 liter
R2 = 0.99
R2 = 1
L
(a) (b)
Figure 4.21 Dependence of kLa on (a) volumetric power consumption and (b)
superficial air velocity for recombinant E.coli fermentation
The constant in the empirical correlation employed in the E.coli fermentation
was compared with the constant attained for the air-water system. Figure 4.22
showed the dependence of kLa on volumetric power consumption between
recombinant E.coli fermentation and air-water system in 16 and 150 liter scale.
101
0.01
0.1
R2 = 0.99
0.01
0.1
100 1000 10000Pg/VL (W/m
3)
kLa
(s-1
)
150 liter-E.coli
150 liter-Water
R2 = 1
100 1000 10000
Pg/VL (W/m3)
kLa
(s-1
)
16 liter-E.coli
16 liter-Water
R2 = 0.99
(a) (b)
Figure 4.22 Comparison of dependence of kLa on volumetric power consumption
between recombinant E.coli fermentation and air-water system in (a) 16 liter (b) 150
liter
It is clear from the logarithmic plots in Figure 4.22; the trend of the kLa
dependency was comparable in the air-water system and the real culture. The slopes
achieved were also are not very different in both system and the values are presented
in Table 4.22.
Table 4.22 Comparison of constant ‘b’ between E.coli culture broth with air-
water system in 16 liter and 150 liter
Constant ‘b’ Liquid system Temperature(oC) 16 liter 150 liter
E.coli 37 0.5469 0.3016Water-air 40 0.3561 0.3541
The dependence of kLa on the superficial air velocity in E.coli fermentation
and the air-water system are illustrated in Figure 4.23. The similarity of slopes in the
trend was proved by comparing the value of constant ‘c’ in both E.coli fermentation
and the air-water system. The results are presented in Table 4.28. As shown in the
Table 4.23, the kLa shows a strong dependency on the superficial air velocity in
E.coli system and the air-water system at both 16 and 150 liter scale.
102
R2 = 1 R2 = 0.95
0.01
0.1
0.001 0.01vg (m/s)
kLa
(s-1
)
150 liter-E.coli150 liter-Water
R2 = 0.91
0.01
0.1
0.001 0.01 0.1vg (m/s)
kLa
(s)
16 liter-E.coli
16 liter-Water
R2 = 0.92
-1
(a) (b)
Figure 4.23 Comparison of dependence of kLa on superficial air velocity between
recombinant E.coli fermentation and air-water system in (a) 16 liter (b) 150 liter
Table 4.23 Comparison of experimental values of constant ‘b’ and ‘c’ upon scale-
up of E.coli fermentation from 16 liter to 150 liter
Constant ‘b’ Constant ‘c’ Liquid system Temperature(oC) 16 liter 150 liter 16 liter 150 liter
E.coli 37 0.5469 0.3016 0.8638 0.9359Water-air 40 0.3561 0.3541 0.5009 0.4491
As previously demonstrated, a comparable result in both E.coli system and
the air-water system has come in agreement with the several opinions that assume
that the bacterial broth behaves like Newtonian fluid (Bailey and Ollis, 1986). The
trend lines are not coinciding with each other because different impeller speeds and
air flow rates was employed in both cases. The difference may also due to the
change of E.coli broth from Newtonian fluid to a more complex fluid upon surplus
addition of antifoam and increasing of biomass concentration. This will increase the
shear stresses, inhibit fluid motion close to the bubble and reduce the interfacial
circulation within the bubble. Extensive addition of antifoam immobilizes the
bubble interface and reduces the rate at which fresh liquid can be brought into
contact with bubble surface. A higher power required to provide mixing and
turbulence in the broth upon addition of antifoam. This phenomenon was explained
by Al-Masry (1999).
103
In predicting the kLa values, the empirical equations in E.coli system at both
scales are in good agreement with the experimental data with a 3% maximum
experimental error. The range of operating parameters varied upon scale-up of E.coli
fermentation from 16 liter to 150 liter vessel to obtain a similar kLa value is
presented in Table 4.24.
Table 4.24 The values of range of operating parameters varied upon scale-up
from 16 liter to 150 liter in E.coli Fermentation
Scale of operation Manipulated Variables 16 liter 150 liter Constant ‘b’ value 0.5469 0.3016Constant ‘c’ value 0.8638 0.9359Range of Pg/VL 0.27 < Pg/VL < 0.7 kW/m3 0.27 < Pg/VL < 1.6 kW/m3
Range of vg 5.3 x 10-3 < vg < 7.4 x 10-3 3 x 10-3 < vg < 4.6 x 10-3
m/s Reynolds number, NRE 6.4 x 104 < NRE < 8.7 x
1041.6 x 105 < NRE < 2.9 x
105
CHAPTER 5
CONCLUSIONS AND RECOMENDATIONS
5.1 Conclusions
Marine impeller provided a better bulk mixing, however gave low mixing
power. On the other hand, Rushton turbine provided a better mixing power but
resulted in compartmentalization problem. The significance of hydrodynamic
difference between Rushton turbine and marine impeller on the oxygen transfer rate
at 16 liter bioreactor was successfully confirmed. From the experimental data, it was
evident that the kLa increased with the volumetric gassed power input and superficial
air velocity. The results showed that the liquid temperature and viscosity
significantly affected the oxygen transfer rate in the bioreactor. The Rushton turbine
was more effective in gas distribution and gave greater oxygen transfer than that of
the marine impeller. However, in viscous environment, marine impeller provided
better mixing. By using the correlation introduced by Cooper et al. (1944) (i.e. kLa =
a’ (Pg/VL)b (vg)c), the agitation speed and airflow rate was empirically associated
with the oxygen transfer coefficient. The magnitude of ‘b’ and ‘c’ in this equation
represented the degree of dependence of kLa on the agitation and sparging rate
applied to the system respectively. The constant ‘a’ was dependent on the broth
conditions, impeller types and the geometry of the bioreactor. These parameter
values were estimated through experimental work. Hence, the values obtained were
unique. Our results indicated that the estimates agreed well with the published data
by Arjunwadkar et al. (1998), Shukla et al. (2001) and Martinov and Vlaev (2003)
(refer Table 1.1).
105
Simple protocol for scaling-up exercise based on constant kLa in stirred
aerated bioreactor was developed. The dependence of kLa on the specific power
input and superficial air velocity at 16 and 150 liter bioreactor operated at different
liquid viscosities and temperatures were compared. This was achieved by evaluating
the effect of increasing broth viscosity on the oxygen transfer rate. Similar trend of
kLa dependence on the volumetric gassed power consumption and superficial air
velocity showed that the effects of agitation speed and aeration rate on the oxygen
transfer rate in both scales were identical. The scaling-up protocol developed in this
study was tested by comparing the kinetic profiles of E.coli batch fermentation at 16
and 150 liter. Similar trend E.coli growth, oxygen uptake rate (OUR) and oxygen
transfer rate (OTR) at both scales demonstrated that the scale-up protocol based on
constant kLa was successfully implemented in this work.
From our study, the following conclusions may be drawn.
1. The changes of kLa due to agitation by Rushton turbine impeller was more
pronounced in comparison to the marine one. On the other hand, the effect of
sparging rate on kLa was more dominant in the marine system in comparison
to the turbine. Hence, the significance of hydrodynamic difference between
Rushton turbine and marine impeller on the oxygen transfer rate at 16 liter
bioreactor was successfully confirmed.
2. The dependence of kLa on volumetric gassed power consumption was more
evident in 16 liter than in 150 liter scale. Hence, the impeller speed gave
significant effect on the kLa at 16 liter scale compared to 150 liter scale.
3. The manipulation of specific power input and superficial air velocity may be
a useful approach in maintaining a constant kLa value upon scale-up from 16
to 150 liter bioreactor.
106
4. Similar kinetic profiles of E.coli growth, glucose consumption, oxygen
uptake rate (OUR) and oxygen transfer rate (OTR) were most likely resulted
from the similar oxygen transfer at both scales. This proved that the
proposed scale-up strategy worked in predicting fermentation kinetic at
higher scale.
5.2 Recommendations for Future Studies
1. As the scale increases, gas distribution in the bioreactor region becomes
problematic. Therefore, investigation on the oxygen profile is crucial and
worth pursuing in gaining further insight on measurement of kLa in the
biorector. This investigation may be performed on the high pseudoplastic
fluids i.e. Xanthan gum solution, a non-coalescent liquid i.e. Na2SO4 and
on the filamentous culture broth.
2. The empirical correlation proposed by Cooper et al. (1944) only concerns
on the effect of the sparging rate and the impeller rotational speed on the
kLa. Study may be extended to other empirical equations developed by
other workers such as Ryu and Humphrey (1972), Yagi and Yashida
(1975) and Zlokarnik (1978).
3. The validity of the scale-up protocol proposed in this work may be further
tested in scales higher than 150 liter bioreactor.
4. The scale-up protocol proposed in this work was based on the rules of
thumb technique. Other scale-up approaches such as fundamentals
method, semi-fundamentals method, dimensional analysis and time-
regime analysis may be investigated in scaling-up stirred aerated
bioreactor on the basis of constant kLa.
107
REFERENCES
Aiba, S., Humphrey, A. E., and Mills, N. F. (1973). Biochemical Engineering. 2nd
ed. Tokyo: University Tokyo Press.
Aiba, S., Suzuki, K., and Kitai, S. (1965). Progress Report No. 27 of Biochemical
Engineering Laboratory. Japan: University of Tokyo.
Al-Masry, W.A. (1999). Effects of Antifoam and Scale-up on Operation of
Bioreactors. Biochem. Eng. Proc. 38: 197-201.
Arjunwadkar, S. J., Sarvanan, K., Kulkarni, P. R., and Pandit, A. B. (1998). Gas-
Liquid Mass Transfer in Dual Impeller Bioreactor. Biochem. Eng. 1: 99-
106.
Badino Jr, A. C., Facciotti, M. C. R., and Schmidell, W. (2001). Volumetric oxygen
Transfer Coefficients (kLa) in Batch Cultivations involving Non-Newtonian
Broths. Biochem. Eng. 8: 111-119.
Bailey, J., and Ollis,O. (1986). Biochemical Engineering Fundamental. 2nd ed.
New York: Mc Graw-Hill.
Banks, G. T. (1977). Aeration of Moulds and Streptomycete Culture Fluids. Enz.
Ferment. Biotechnol. 1: 72-110.
Brooke, M., and Halsall, J. (2002). Tailored Rheology in the Formulation of an
Oral Adsorbent. Leicestershire, U.K.: Loughborough University.
Charles, M., and Wilson, J. (1994). Fermenter Design in Bioprocess Engineering.
New York: John Wiley & Sons.
108
Chia-Hua Hsu (2003). Characterization of a Centrifugal, Packed-bed Reactor for
Xanthan Gum Production. University of Maryland: Ph.D. Thesis.
Cooper, C. M., Fernstrom, G. A., and Miller, S. A. (1944). Performance of Agitated
Gas-Liquid Contactors. Ind. Eng. Chem. 36: 504-509.
Doran, P. M. (1996). Bioprocess Engineering Principles. London.: Academic
Press.
Garcia-Ochoa, F., Gomez, E., and Santos, V. E. (2000). Oxygen Transfer and
Uptake Rates during Xanthan Gum Production. Enzy. Microbial. Technol.
27: 680-690.
Geankoplis, C. J. (1993). Transport Processes and Unit Operations. 3rd ed. New
York: Prentice Hall.
Hensirisak, P. (1997). Scale-up the Use of a Microbubble Dispersion to Increase
Oxygen Transfer in Aerobic Fermentation of Baker Yeast. Virginia
Polytechnic Institute and State University: Msc. Thesis.
Herbst, H., and Schumpe, A. (1992). Xanthan Production in Stirred Tank
Fermentation: Oxygen Transfer and Scale-up. Chem. Eng. Technol. 15:
425-434.
Hubbard, D. W., Ledger, S. E., and Hoffman, J. A. (1994). Scaling-up Aerobic
Fermentation which Produce non-Newtonian and Viscoelastic Broths.
Netherlands: Klover Academic Publishers.
James, J. W. 1992). Operational Modes of Bioreactor. Oxford, London:
Butterworth-Heinemann Ltd.
Ju, L. K., and Chase, G. G. (1992). Improved Scale-up Strategies of Bioreactors. J.
Bioproc. Eng. 8(1-2): 49-53.
109
Juarez, P., and Orejas, J. (2001). Oxygen Transfer in a Stirred Reactor in
Laboratory Scale. Latin. American. App. Research. 31: 433-439.
Kawase, Y., and Moo-Young, M. (1988). Chem. Eng. Res. Des. 66: 284.
Kossen, N. W. F., and Oosterhuis, N. M. G. (1985). Modelling and Scaling-up of
Bioreactors in Biotechnology. 2nd ed. Weinheim, German: VGH-Verlag.
Maranga, L., Cunha, A., Clemente, J., Cruz, P., and Carrondo, M. J. T. (2004).
Scale-up of Virus-like Particles Production: Effects of Sparging, Agitation
and Bioeractor Scale on Cell Growth, Infection Kinetics and Productivity.
Biotechnol. 107: 55-64.
Martinov, M., and Vlaev, S. D. (2002). Increasing Gas-Liquid Mass Transfer in
Stirred Power Law Fluids by Using a New Saving Energy Impeller. Chem.
Biochem. Eng. 16: 1-6.
Meztner A. B., and Otto R. E. (1962). Agitation of non-Newtonian fluids. AIChe.
1: 3-10.
Midler, M., and Finn, R. K. (1966). Model System for Evaluating Shear in the
Design of Stirred Fermenters. Biotechnol. Bioeng. 8: 71.
Michael, A. M. (1997). Bioreactor Control of Dissolved Oxygen during Batch
Growth of E.Coli. University of Western Ontario: Msc. Thesis.
Michel, B. J., and Miller, S. A. (1962). Power Requirements of Gas-Liquid Agitated
Systems. AIChe: 262.
Mohamad, R., Ariff, A., Mohd. Yusoff, H., and Kamal, M. N. (2001). Fermenter
Design and Scale-up. University Putra Malaysia: Fermentation Unit
Technology. Bioscience Institute.
110
Moo-young, M., and Blanch, H. W. (1981). Advance in Biochemical Engineering.
3rd ed. New York: Springer-Verlay.
Nagata, S. (1975). Mixing: Principles and Applications. Tokyo: Kodansha.
Nielsen, D. R., Daugulis, A. J., and McLellan, P. J. (2003). A Novel Method of
Simulating Oxygen Mass Transfer in Two-Phase Partitioning Bioreactors.
Biotechnol. Bioeng. 83: 735-742.
Norwood, K. W., and Metzner, A. B. (1960). AIChE. 6: 432.
Perry, R. H., and Green, D. W. (1997). Perry’s Chemical Engineers Handbook. 7th
ed. New York: Mc Graw-Hill.
Pirt, S. J. (1975). Principles of Microbe and Cell Cultivation. Hulsted Press, New
York: John Wiley & Sons.
Rushton, J. H., Costich, E. W., and Everett, H. J. (1950). Power Characteristics of
Mixing Impellers. Chem. Eng. Prog. 46(2): 467.
Ryu, D. Y., and Humphrey, A. E. (1972). Ferment. Technol. 50: 424.
Shukla, V. B., Parasu, U., Kulkarni, P. R., and Pandit, A. B. (2001). Scale-up
Biotransformation Process in Stirred Tank Reactor using Dual Impeller
Bioreactor. Biochem. Eng. 8: 19-29.
Steel, R., and Maxon, W. D. (1962). Biotechol. Bioeng. 4: 231-240.
Steel, R., and Maxon, W. D. (1966). Biotechnol. Bioeng. 8: 99-115.
Stanbury, P. F., and Whitaker, A. (1984). Principles of Fermentation Biotechnology.
New York: Pergamon Press.
111
Taguchi, H., and Humphrey, A. E. (1966). Dynamic Measurement of Volumetric
Oxygen Transfer Coefficient in Fermentation System. Ferment Technol. 44:
881.
Vantriet, K., and Tramper, J. (1991). Basic Biorector Design. New York: Marcel
Dekker.
Wang, D. I. C., Cooney, C. L., Demain, A. L., Dunnill, P., Humphrey and Lilly, M.
D. (1979). Fermentation and Enzyme Technology. New York: John Wiley
& Sons.
Wise, W. S. (1951). The Measurement of the Aeration of Culture Media. Gen.
Micro. 5: 167-177.
Wong, I., Garcia, M. A., Rodriguez, I., Ramos, L. B., and Olivera, V. (2003).
Fermentation Scale-up for Production of Antigen K88 Expressed in
Escherichia coli. Proc. Biochem. 38: 1295-1299.
Wernersson, E. S., and Tragardh, C. (1999). Scale-up of Rushton Turbine Agitated
Tanks. Chem. Eng. Sci. 54: 4245-4256.
Yagi, H., and Yoshida, F. (1975). Ind. Eng. Chem. Proc. Des. Dev. 14: 488.
Zlokarnik, M. (1978). Adv. Biochem. Eng. 8: 133.
112
Appendix A1
Specification of Dissolved Oxygen Electrode
Figure A.1: Basic Arrangement of Dissolved Oxygen Electrode
(BioengineeringTM)
Technical Data of Dissolved Oxygen Electrode (BioengineeringTM)
1) Measuring Principle: Amperometric (polarographic)
Design Features: Rustproof steel fitting, suitable for vertical or lateral
mounting;
Cathode: Pt Anode: Ag / AgCl
Response Time: 98% in less than 45 sec
Output Signal: Approximately 10-12 to 10-17 A
2) Dissolved Oxygen Electrode Measuring Amplifier
Input Impedance: 1013 Ohm
Polarisation Voltage of the Probe Perfectly Constant: 675 mV
Measuring ranges: 0-800 mm Hg, 0-200 mm Hg or 0-100 mm Hg.
114
Physical Properties of Carboxy Methyl Cellulose
1) Preparation of Carboxy Methyl Cellulose (CMC)
In order to prepare a CMC solution at various concentrations, the following equation was
used:-
xx MVx
100
% (1)
Table A.1 shows the calculations and measurements for the preparation of 0.25%(w/v),
0.5%(w/v) and 1%(w/v) of CMC solutions. The same calculation was repeated in preparing
the CMC solutions at respective concentrations for 10 liter and 100 liter scale.
Table A.1: Calculations of CMC solutions for Rheology Analysis
(%w/v) of CMC, x Mass of CMC (g), Mx Volume of Distilled Water (ml), Vx
0.25 1.5 600
0.5 3 600
1.0 6 600
2) Determination of Density for Carboxy Methyl Cellulose Solution
In order to determine the CMC solution density at various concentrations, the following
equation was used and the value attained was shown in Table A.2:-
CMCCMC
bcb
V
MM (2)
Table A.2: Calculations of CMC Solutions Density at Various Concentrations
(%w/v) of CMC Mass of
beaker(g), Mb
Mass of beaker with
CMC(g), Mb+c
Volume of CMC
solution (ml), VCMC
CMC
(kg/m3)
0.25 254.16 868.55 600 988.3
0.5 254.16 847.14 600 1023.98
1.0 106.297 158.631 50 1046.68
115
Physical Properties of Distilled Water
Table A.3 shows the physical properties of distilled water at various temperatures which has
been taken from “Transport Processes and Unit Operations 3rd Ed.”.
Table A.3: Heat-Transfer Properties of Liquid Water (Geankoplis, 1993)
116
Table A.4: Oxygen Solubility in Air Saturated Pure Water in mg O2/L at an Overall
Pressure of a Water-Vapor Saturated Atmosphere of 760 mm Hg (Perry’s
Chemical Engineering Handbook 7th Edition)
Temperature (oC) Solubility,S (mg O2/L)
0 14.57
2 13.79
4 13.08
6 12.42
8 11.81
10 11.26
12 10.74
14 10.27
16 9.83
18 9.43
20 9.06
22 8.71
24 8.39
26 8.09
28 7.81
30 7.55
32 7.30
34 7.07
36 6.84
38 6.63
40 6.42
42 6.23
44 6.06
46 5.90
48 5.75
50 5.61
117
Appendix A2
Derivation of Concentric Viscometer Analysis
The following derivation was based on the concentric cylinder viscometer as shown
in Figure 3.1. The equations were derived to determine the shear rate, value which
based on the concentric cylinder viscometer. For non-Newtonian viscous liquids, the
shear stress was taken to be function of the shear rate as was defined as:
. (3)
For non-Newtonian viscous liquids, the apparent viscosity was also taken to be
function of shear rate and was defined as:
f (4)
In steady state, the torque measure on the inner cylinder (using the conservation of
momentum) was given by:
LrLr ....2...2 12
12
1 (5)
where was the fluid shear stress at radius r. The shear rate was given by:
drdwrdrwdrrdwwdrr /./ (6)
So, rearranging equation 5 for , and substituting this together with equation 5 for
into equation 3, we get:
drdwrLr /.....2/ 21 (7)
118
This gives:
....2// 31 Lrdrdw (8)
Assume that the viscosity, constant across the width of the gap. Therefore:
22
211 /1/1*2/1*...2/ rrL (9)
22
211 /1/1*...4/ rrL (10)
From equations 6 and 7 we can get an expression for the shear rate.
....2//. 21 Lrdrdwr (11)
Substituted equation 10 into 11 to get a value for the shear rate:
22
21
22
21
2 /.*/.2 rrrrr (12)
142
Appendix D3
Results for the Determination of Operating Variables at 150 liter Bioreactor
Table D.1 Results of the ‘trial-and-error’ step in distilled water at 40oC
Vary impeller speed at constant aeration16 liter 150 liter New Operating
ConditionsN1
(rpm) Q1
(l/min) kLa(s-1)
Trial N(rpm)
Q(l/min)
kLa(s-1)
N2
(rpm) Q2
(l/min) 1 50 30 0.0057200 9 0.01132 60 30 0.0071
70.28 30
1 100 30 0.0195400 9 0.02532 120 30 0.0247
123.2 30
1 150 30 0.0303600 9 0.03572 180 30 0.034
184.2 30
1 200 30 0.0421800 9 0.0452 240 30 0.0427
217.9 30
1 250 30 0.05021000 9 0.07932 300 30 0.0581
395 30
Scale-up ratio, R1 (average value) = 0.325
Vary air flow rate at constant agitation16 liter 150 liter
(1st Trial) 150 liter
(2nd Trial) N1
(rpm) Q1
(l/min) kLa(s-1)
N(rpm)
Q(l/min)
kLa(s-1)
N2
(rpm) Q2
(l/min) kLa(s-1)
600 3 0.0236 150 10 0.0183 180 10 0.0242
600 6 0.0276 150 20 0.0251 180 20 0.0315
600 9 0.0332 150 30 0.0305 180 30 0.0336
600 12 0.0471 150 40 0.0393 180 40 0.0418
600 15 0.0513 150 50 0.0402 180 50 0.0492
143
From interpolation and extrapolation:- New Operating Conditions
Q2
(l/min) N2
(rpm) 9.85 18014.7 18030 18047 180
52.13 180Scale-up ratio, R2 (average value) = 3.29
Table D.2 Results of the ‘trial-and-error’ step in distilled water at 50oC
Vary impeller speed at constant aeration16 liter 150 liter New Operating
ConditionsN1
(rpm) Q1
(l/min) kLa(s-1)
Trial N(rpm)
Q(l/min)
kLa(s-1)
N2
(rpm) Q2
(l/min) 1 50 30 0.0103200 9 0.01492 60 30 0.011
73.8 30
1 100 30 0.0223400 9 0.02832 120 30 0.0285
120 30
1 150 30 0.0359600 9 0.04262 180 30 0.0445
172.88 30
1 200 30 0.0505800 9 0.04872 240 30 0.0612
195.09 30
1 250 30 0.06751000 9 0.08452 300 30 0.0708
358.05 30
Scale-up ratio, R1 (average value) = 0.31
Vary air flow rate at constant agitation16 liter 150 liter
(1st Trial) 150 liter
(2nd Trial) N1
(rpm) Q1
(l/min) kLa(s-1)
N(rpm)
Q(l/min)
kLa(s-1)
N2
(rpm) Q2
(l/min) kLa(s-1)
600 3 0.0266 150 10 0.0243 180 10 0.0285
600 6 0.0356 150 20 0.0298 180 20 0.0363
600 9 0.047 150 30 0.0353 180 30 0.0441
600 12 0.0625 150 40 0.0445 180 40 0.0519
600 15 0.0675 150 50 0.0479 180 50 0.0626
144
From interpolation and extrapolation:- New Operating Conditions
Q2
(l/min) N2
(rpm) 9.33 18019.1 18033.7 18050 180
53.9 180Scale-up ratio, R2 (average value) = 3.55
Table D.3 Results of the ‘trial-and-error’ step in 0.25%(w/v) CMC solution at
30oC
Vary impeller speed at constant aeration16 liter 150 liter New Operating
ConditionsN1
(rpm) Q1
(l/min) kLa(s-1)
Trial N(rpm)
Q(l/min)
kLa(s-1)
N2
(rpm) Q2
(l/min) 1 50 30 0.0033200 9 0.00342 60 30 0.0072
50 30
1 100 30 0.0146400 9 0.01732 120 30 0.0171
120 30
1 150 30 0.0218600 9 0.02142 180 30 0.0242
147.4 30
1 200 30 0.0278800 9 0.02572 240 30 0.035
188.3 30
1 250 30 0.03371000 9 0.03872 300 30 0.0373
311.3 30
Scale-up ratio, R1 (average value) = 0.27
Vary air flow rate at constant agitation16 liter 150 liter
(1st Trial) 150 liter
(2nd Trial) N1
(rpm) Q1
(l/min) kLa(s-1)
N(rpm)
Q(l/min)
kLa(s-1)
N2
(rpm) Q2
(l/min) kLa(s-1)
600 3 0.0211 150 10 0.016 180 10 0.0174
600 6 0.0213 150 20 0.0199 180 20 0.0226
600 9 0.0216 150 30 0.0218 180 30 0.0243
600 12 0.0283 150 40 0.0265 180 40 0.032
600 15 0.0346 150 50 0.0284 180 50 0.0343
145
From interpolation and extrapolation:- New Operating Conditions
Q2
(l/min) N2
(rpm) 17.1 18017.5 18017.8 18035.2 18050 180
Scale-up ratio, R2 (average value) = 3.3
Table D.4 Results of the ‘trial-and-error’ step in 0.5%(w/v) CMC solution at
30oC
Vary impeller speed at constant aeration16 liter 150 liter New Operating
ConditionsN1
(rpm) Q1
(l/min) kLa(s-1)
Trial N(rpm)
Q(l/min)
kLa(s-1)
N2
(rpm) Q2
(l/min) 1 50 30 0.0031200 9 0.00272 60 30 0.0043
43.5 30
1 100 30 0.0109400 9 0.01542 120 30 0.0155
120 30
1 150 30 0.0187600 9 0.02032 180 30 0.0218
165.5 30
1 200 30 0.0255800 9 0.02222 240 30 0.0287
182.2 30
1 250 30 0.02951000 9 0.03052 300 30 0.0354
258.5 30
Scale-up ratio, R1 (average value) = 0.26
Vary air flow rate at constant agitation16 liter 150 liter
(1st Trial) 150 liter
(2nd Trial) N1
(rpm) Q1
(l/min) kLa(s-1)
N(rpm)
Q(l/min)
kLa(s-1)
N2
(rpm) Q2
(l/min) kLa(s-1)
600 3 0.0145 150 10 0.0136 180 10 0.016
600 6 0.0171 150 20 0.0168 180 20 0.0203
600 9 0.0207 150 30 0.0187 180 30 0.0218
600 12 0.0265 150 40 0.0209 180 40 0.0282
600 15 0.0321 150 50 0.0249 180 50 0.033
146
From interpolation and extrapolation:- New Operating Conditions
Q2
(l/min) N2
(rpm) 9.1 18013.4 18022.7 18037.3 18048.1 180
Scale-up ratio, R2 (average value) = 3.3
Table D.5 Results of the ‘trial-and-error’ step in 1%(w/v) CMC solution at 30oC
Vary impeller speed at constant aeration16 liter 150 liter New Operating
ConditionsN1
(rpm) Q1
(l/min) kLa(s-1)
Trial N(rpm)
Q(l/min)
kLa(s-1)
N2
(rpm) Q2
(l/min) 1 50 30 0.0021200 9 0.00132 60 30 0.0028
30.9 30
1 100 30 0.0089400 9 0.00632 120 30 0.0113
82.9 30
1 150 30 0.016600 9 0.0122 180 30 0.0204
124.5 30
1 200 30 0.0188800 9 0.0192 240 30 0.0226
200 30
1 250 30 0.02471000 9 0.02572 300 30 0.0265
277.8 30
Scale-up ratio, R1 (average value) = 0.22
Vary air flow rate at constant agitation16 liter 150 liter
(1st Trial) 150 liter
(2nd Trial) N1
(rpm) Q1
(l/min) kLa(s-1)
N(rpm)
Q(l/min)
kLa(s-1)
N2
(rpm) Q2
(l/min) kLa(s-1)
600 3 0.0068 150 10 0.0095 180 10 0.011
600 6 0.0102 150 20 0.0138 180 20 0.0143
600 9 0.0121 150 30 0.0161 180 30 0.0205
600 12 0.0163 150 40 0.0179 180 40 0.0219
600 15 0.0188 150 50 0.0207 180 50 0.024
147
From interpolation and extrapolation:- New Operating Conditions
Q2
(l/min) N2
(rpm) 7.16 150
11.63 15016.05 15031.1 15043.2 150
Scale-up ratio, R2 (average value) = 2.4
159
Appendix F
F-Test for Equality of Kinetic Profiles at 16 and 150 liter E.coli Fermentation
The objective of the F-test is to test if the standard deviations of two populations are
equal. The hypothesis that the two equal standard deviations is rejected if:
F > F ( , N1-1,N2-1) for an upper one-tailed test
F < F (1- , N1-1,N2-1) for a lower one-tailed test
The output for an F-test is summarized as below.
Type of kinetic profile : Biomass Concentration, X (g/L)
Scale 16 liter 150 liter
Mean 2.844 2.600
Variance 2.453 2.603
Observations 10 10
Degree of freedom 9 9
Significant level 0.05 0.05
F-test value 0.942
P (F<= f) one-tailed test 0.465
F critical one-tailed test 0.3146
Type of kinetic profile : Specific Oxygen Uptake Rate, qOUR (mg O2/ g cell.h)
Scale 16 liter 150 liter
Mean 151.682 186.109
Variance 13159.985 30480.755
Observations 10 10
Degree of freedom 9 9
Significant level 0.05 0.05
F-test value 0.432
P (F<= f) one-tailed test 0.113
F critical one-tailed test 0.3146
160
Type of kinetic profile : Substrate Consumption, S (g/L)
Scale 16 liter 150 liter
Mean 15.077 16.330
Variance 15.297 12.725
Observations 10 10
Degree of freedom 9 9
Significant level 0.05 0.05
F-test value 1.202
P (F<= f) one-tailed test 0.394
F critical one-tailed test 3.179
Type of kinetic profile : Oxygen Uptake Rate, OUR (mg O2/ L.h)
Scale 16 liter 150 liter
Mean 374.004 360.18
Variance 19259.898 20233.303
Observations 10 10
Degree of freedom 9 9
Significant level 0.05 0.05
F-test value 0.952
P (F<= f) one-tailed test 0.471
F critical one-tailed test 0.3146
Type of kinetic profile : Oxygen Transfer Rate, OTR (h-1)
Scale 16 liter 150 liter
Mean 107.166 108.308
Variance 1987.186 1994.990
Observations 10 10
Degree of freedom 9 9
Significant level 0.05 0.05
F-test value 0.996
P (F<= f) one-tailed test 0.498
F critical one-tailed test 0.3146
