Transcript Reactor Selection Strategy
Reaction Engineering for Environmentally Benign Processes Reactor Selection Strategy
M.P. Dudukovic
Module 6 Homogeneous systems Heterogeneous systems Systems (multi-scale) approach
S1
Approach to Reactor Selection
1.
2.
– – Identify number of phases present at reaction conditions (thermodynamics) Single – Homogeneous system Multiple – Heterogeneous systems Identify stoichiometry, number of reactions, energy requirements (e.g. adiabiatic temperature rise/fall) 3.
Identify mechanism (if possible) and plausible reaction pathways and active intermediates 4.
Decide on the purpose of reactor selection Evaluation of kinetic data Data for scale-up Commercial design
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Chemical Reaction Engineering Basics
Molecular Level – Mechanisms and kinetic rates Eddy (Particle) Level – Micromixing & kinetics – Intra phase diffusional effects (Thiele modulus, effectiveness factor) – Inter phase transport effects Reactor Level – Ideal flow patterns (CSTR, PFR) – Non-ideal flow patterns between phases – Contacting patterns – Mixing
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For Homogeneous Systems:
Identify the magnitude of heat transfer requirement Assess the effect of ideal flow patterns on volumetric productivity and selectivity Select the best ideal flow pattern (batch, semi-batch, continuous flow stirred tank reactor – CSTR, plug flow reactor – PFR) Optimize your objective function (related to profit) using as manipulative variables: - Feed reactant concentrations and their ratio - Feed temperature - Reactor temperature or temperature profile Approach the ideal by practical design as much as possible.
Keep things simple whenever possible!
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HOMOGENEOUS SYSTEMS
(Optimizing Volumetric Productivity)
Batch Reactor
t t
0 ,
C A
t
,
C A
C C A A
0 0 1
X A
Moles of A reacted per unit time
t s
shut down time
t
C C A
0
A
dC R A A
reaction t ime
C A
0
VX t
t s A
Continuous Flow Stirred Tank Reactor (CSTR)
F A0 C A0 F A = F A0 (1-X A ) Moles of A reacted per unit time
F A
0
X A
R A
V
T = const.
Plug Flow Reactor (PFR)
F A0 C A0 F A = F A0 (1-X A ) Moles reacted per of A unit time
F A
0
X A
A V
V
1 /[
X A
0
X
A
dX R A A
]
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Volumetric Productivity for Product P then is
F p V
moles of
P
produced reactor vo per unit time lume
For CSTR
F p V
CSTR
p a
R A
For PFR
F p V
PFR
p a
A
1
X A
p a
X
0
A dX
R A A
The ratio of volumetric productivities in the two systems
F p F p V V
PFR CSTR
R A A
Is the ratio of average reaction rate in a PFR and the reaction rate at exit conditions of the CSTR S6
Homogeneous Systems (optimizing selectivity)
A + B 2nd Order P desired product A + A 2nd Order S undesired product • Which is the optimal flow pattern ? • What is the optimal selectivity ? (at fixed feed concentrations, feed ratio of F A0 /F B0 and conversion of B) A B PFR P+S A B P+S A PFR P+S B PFR B A A B initially only B initially only A P+S
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In multiple reactions it is useful to consider the point yield behavior Then in CSTR
R R R A C R
rate of rate of formation disappeara of desired nce of product key reactant
exit
C Ao
C A exit
While in PFR
C R
C C
Ao
A exit dC A
C A C A C A
Production rate of R is maximized:
In a CSTR for systems with d
/dC A
<0 (undesired reactions of higher order than the desired one)
In a PFR for systems with df/dCA>0 (undesired reactions of lower order than the desired one)
In a reactor combination for nonmonotonic yield curve S8
Other Simple Rules Worth Remembering
In consecutive reactions production of intermediate is always more favored in a PFR than in a CSTR For exothermic reactions maximum volumetric productivity is reached at an optimal temperature which is a function of conversion When desired reaction has the highest activation energy select the highest temperature for best selectivity When desired reaction has the lowest activation energy lowest practical temperature optimizes selectivity For intermediate activation energy of desired reaction an optimal temperature or temperature profile can be found
For lumping complex reaction schemes into patterns to analyze see Levenspiel, O., Chem. React. Eng.
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Recognize that selected ideal flow patterns may only be approached in practice.
Determine the deviation from ideal flow patterns by examining the residence time distribution (RTD) of the system either derived from the solution of the flow field or experimentally determined on a reactor prototype (cold flow model), pilot plant or on the actual unit.
E dt
fraction of outflow of residence time around
t
E E
dt
PFR CSTR
fraction of outflow of residence
E
time about
t
exponential decay
E
Between PFR & CSTR
t t t t t
o
t E dt
V Q
Lesser val ues indicate stagnancy 2 1
t
2 o
t
t
0 2 1
dt
0 1
PFR CSTR
Model by dispersion or tanks in series model 2 1 Bad!
Avoid!
t t
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0 .
2 transport limitations can develop on a micro-scale (i.e. in bringing reactants in contact or in supplying them to the soluble catalyst, enzyme or cell). This is particularly important for non-premixed feeds.
We need to assess the scale of the smallest turbulent eddies in the system which is determined by the amount of energy dissipated per unit mass of the system. For example
K
3 1 4 kinematic viscosity energy disspated per unit mass Characteristic diffusion time
D
K
2
D D
molecular diffusivity Characteristic reaction time
D
R
D R
0 .
3 5
R
C R Ao A
o
No microscale transport limitation s Strong microscale effect mixing dominated system In between micromixing models needed!
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Example:
Water Solution :
k
O
10
m
D
k
2
D
2 10 5 10 1 All reactions with
R > O
(1 second ) will not cause transport limitations.
Highly Viscous Solution
D
Only reactions with
R > 10 5 (s)
:
K
2
D
k
2 10 8
O
100 10 4
m
will not cause transport limitations.
For most systems mixing and reaction occur simultaneously and proper micromixing model is needed.
Proper treatment of this topic is not available in most standard reaction engineering text. References and related notes can be obtained upon request.
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Two extreme micromixing models are:
1. Segregated Flow – All fluid elements remain segregated by age on their sojourn through the system and elements of different ages mix only at the exit.
C A S
.
F
.
o
C A b a tch dt
where
dC A b a tch dt
R A
t
0
C A
C A o
2. Maximum Mixedness – All fluid elements of same life expectancy are together at all times.
C A M
.
M
.
C A
0 obtained by solving
dC A d
R A
t
E E dC d
A
0
dt
C A o
C A
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Reactions: System:
Micromixing Effect
A k 1 P 1st order k 2 2A S 2nd order
t
CSTR, = 48 min; k 2 C A0 /k 1 0.5
= Exponential RTD Laboratory System: Large System: 1 L vessel, 1500 rpm 5000 gallon vessel; 300 rpm Selectivity in the Lab.: C P /C S = 98 at X A = 0.98 Selectivity in the Large Unit: C P /C S = 15 at X A = 0.98+ Model Predictions: Maximum Mixedness Flow: Segregated Flow: C P /C S = 100 C P /C s = 4.5
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Key issues associated with selection and scale-up of reactors for homogeneous reactions
Developing sufficient knowledge of molecular level events to propose mechanism and establish reaction pathways, key reactions and their parameters.
Determining optimal ideal flow pattern and maintaining the same flow pattern (same and with scale-up).
Avoiding bypassing and stagnancy with scale-up.
Maintaining same level of micromixing with scale-up is needed but hard as power dissipated per unit volume decays with scale and affects micromixing adversely.
Maintaining adequate heat transfer rate with scale-up is difficult as heat evolved by reaction volume and heat removed surface. With scale-up in general S/V is reduced which may lead to problems unless corrective steps are taken.
Control of temperature, pressure, pH etc. becomes more difficult with increased scale.
Homogenous catalyst or soluble enzyme recovery, a cinch in the lab, becomes a major chore in large units.
Solvent separation is a problem.
Heterogenize the system whenever possible, do not use solvents unless absolutely necessary!
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The objective in multiphase reactor selection and design is to minimize the manufacturing costs in producing the desired marketable product.
For conversion cost-intensive processes one must achieve both high volumetric productivity and high product concentration.
v
F p
p V F
V
v
kg m
kmol
3
h h
volumetri molar c productivi production rate
p
kg p
kmol
molecular reactor vo weight lume ty For recovery cost intensive processes (e.g. often encountered in biotechnology) one must achieve high product concentration
c p (kg/m 3 ).
c c p p
p kmol C p m
3 molar concentrat ion In either case proper reactor selection is required since reactor type and performance affects significantly the whole process.
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Reactor Performanc e
f
Input Operating and Variables ; Rates ; Mixing Pattern -
Conversion
-
Selectivity
-
Production Rate - Flow Rates - Inlet Conc. & Temp.
- Heat Removal - Kinetics - Transport - Macro - Micro
LHS RHS
feed, Q T , C
0
, P
0
L ( C b )
R ( C b , T b ) L h ( C b )
j (
H R j )
j R j ( C b , T b )
f
kinetics ; transport
T , C , P product, Q
Reactor performance determines the number of separation units and their load and hence profoundly affects process economics and profitability.
Production Rate Volume Averaged Reaction Rate Reactor Volume
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In heterogeneous systems the volume averaged reaction rate (volumetric productivity) is a function of:
Molecular scale – kinetics and rate forms Single particle (single eddy) scale effects on diffusion and reaction in the particle, specific phase interfacial area effect on inter-phase mass and heat transfer Reactor scale effect via contacting pattern and phase RTD influence on the average rate and via flow regime effect on phase holdups and inter-phase transport coefficients.
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As a reminder consider the diffusional effects on the rate in a porous particle with uniformly deposited active catalyst in pores Average Rate
R A
particle
p
Where typically
R A
s
p
Per Unit of tan Particle
h p
Volume
p
Particle Effectiven Factor ess 1 With Thiele modulus
p
p
0.1
p
2
D R
0.01 0.001
p
V p S p
10-4 -
|
p
0
R A
particle
R A
S
0.01 0.1
Rate Evaluated at Particle Outside Surface Conditions
|
1.0
|
10
|
100 1000
p
True kinetics, activation energy is observed. Doubling catalyst activity doubles the rate. Rate independent of S p /V p
p
A particle
1
p C A S
k D e
S V p p
C A S n
1 2 Approximately ½ E observed. Reduced order 1
R A
part
.
V S p p
; catalyst activity catalst loading 1 2
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Now one must also consider inter-phase transport
k s S p
C A b
C A s
R A
s
p
And for first order reaction one gets
R A
obs part
0
R A
bulk
1 1
k s S p C A b k v V p
p V p
The denominator contains the sum of external resistance and internal + kinetic resistance.
Of course we need the rate per unit reactor volume so
R A
obs react
1
B
o
R A
bulk
Clearly how much catalyst we packed in (bed voidage B ) affect also volumetric productivity.
Finally flow pattern will affect how (-R A ) bulk affects transport coefficient k s .
p
R A
particle
1
p C A S
is averaged and flow pattern
k D e S p V p C A S n
1 2 Approximately ½ E observed. Reduced order
R A
part
.
V p S p
1 ; catalyst activity 1 2 , catalst loading 1 2
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REACTION :
A
B
P
Gas Limiting Reactant (Completely Wetted Catalyst)
KINETIC RATE per unit :
k
catalyst v
v A
mol
olume
m
3
cat
.
s
RATE IN CATALYST per unit reactor vo :
k v
lume
p
TRANSPORT per unit RATE reactor vo
mol
lume
m
3 1
B react
.
A s s
A
mol
Gas Liquid liquid OVERALL solid : : k s K 1
a p a B
A l A g H a
(APPARENT)
A s
RATE
A
1
mol m
3
m
3
react
.
s
:
react
.
s
A g R A
o k v
1
B
A g H A
1
K l a B
1
k s a p H A
1
B
1
k v
p
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A System Approach to Multiphase Reactor Selection
Economics Reactants Products Reactor Type & Contacting Pattern?
• • • • • •
Process Requirements Maximum selectivity Maximum conversion Maximum productivity Stable Easy scale-up Operability
• • •
Why System Approach?
Number of configurations extremely large Limits to intuitive decision making Innovations are possible
•
Environmental Constraints Minimum pollution S22
Multiphase Reactor Selection Methodology
I.
Volume / Interfacial Area for the Phases
~ d p ~ b for gas-solid systems for gas-liquid systems ~d p and b for G-L-S systems
II. Contacting & Flow Pattern
a) RTD for each phase (PF, backmixed) b) Co – Counter – Cross current?
c) Split addition Product removal in situ, etc.
III. Flow Regime
Homogeneous Churn turbulent Dense phase riser (air lift) Dilute phase riser (spray)
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Example: Recovery of Oil From Oil Shale
Process Requirements (Wish List)
• Maximize “oil” recovery (99%+) • Scale-up to mega-size units ( 500 kg/s feed) • Minimize reactor volume • Handle fines well
>200 G-S Reactor Configurations possible!
After Krishna (1989) S24
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Shell’s SPHER 3 Bed Concept Chevron’s STB (staged turbulent bed) S26
Decisions to be made:
I. Particle Size II. Contacting Pattern a. Overall contacting flow pattern of gas and solid phases: b. RTD of each phase: III. Gas-Solid Fluidization Regime
Krishna (1992), Adv. Chem. Eng.
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Kinetics & Transport Phenomena Affecting Process Performance
Oil Shale Pyrolysis
Wallman et al (1980), AIChE Meeting, San Francisco
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Residence time required for heating up of particle to 95% of T g = 482 °C Residence time required for isothermal backmixed reactor (174 min) Conversion of kerogen 99% Residence time required for isothermal plug flow reactor (8 min)
Large throughputs Volume minimize reactor need small residence times range I need plug flow of solids need particles in
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Desired product (heavy oil) yield improved with small particle size (dp < 2mm).
In grinding shale to make 2mm particles fines may be formed too.
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I. Particle Size Selection Tree II. Contacting Flow Pattern Selection Tree III. Flow Regime Selection Tree S31
To reduce oil degradation, must remove oil as soon as formed
in situ product removal
Wilkins et al (1981), 2 nd World Congress, Montreal
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A. Counter-Current Contacting B. Co-Current Contacting C. Cross-Current Contacting
Reactor volume requirement
Rapid oil removal
need plug flow of solids cross flow for gas S33
• • • •
Proper fluidization regime should now be chosen to accommodate: Desired particle size (small) Desired solids holdup (large) Desired contacting pattern (solids-plug flow, gas short contact time) Excellent heat transfer S34
The “Ideal” Reactor: Multi-Stage Cross-Current Fluidized Bed
Meets the criteria: • Small particles • Plug flow of solids • Short vapor residence time (cross-flow) • Good mixing and heat transfer • Scale-up possible – study one train
Shell Shale Retorting Process (Shell Research)
Krishna (1992)
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For Shale Example
Possible Reactor Combinations
3 particle size range 13 gas solid contacting pattern 5 195 fluidizati on regimes • Sequential design making leads to success without brute force evaluation of all options.
Choice of wish list effects final result. Add: Choice should be based on known technology
Moving bed reactor S36
This example illustrates how consideration of all scales leads to successful reactor selection
It also teaches that in situ separation when possible is of high value and can sometimes be achieved by:
Catalytic distillation Selective adsorption or absorption Membrane separation Other means (e.g. dynamic reactor operation, etc.)
Think Out of the Box!
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Our task in catalytic reactor selection, scale-up and design is to either maximize volumetric productivity, selectivity or product concentration or an objective function of all of the above. The key to our success is the catalyst. For each reactor type considered we can plot feasible operating points on a plot of volumetric productivity versus catalyst concentration.
m v
max
v S a S a
kg kg P cat h
specific activity
x kg cat m
3
reactor
catalyst concentrat ion
x x
max
m
max reactor type and flow regime.
S a
limited.
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Chemists or biochemists need to improve
S a
and together with engineers work on increasing
x
max . Engineers by manipulation of flow patterns affect
m v
max . In
Kinetically Controlled Regime
v
x
,
S a x
max limited by catalyst and support or matrix loading capacity for cells or enzymes In
Transport Limited Regime
v
0
p
S a
1 /
p
2 ,
x p
Mass transfer between gas-liquid, liquid-solid etc. entirely limit
v
and set
m v
max . Changes in
S a
, do not help; alternating flow regime or contact pattern may help!
Important to know the regime of operation S39
Schematic of Bubble Column Type of Photo Reactors (Commercially Used)
A train of bubble columns (sparged reactors) through which liquid toluene and chlorinated products flow in series while chlorine is added into each column and hydrogen is removed from the column.
Typical selectivity to benzyl chloride: 90% But Toluene conversion is less than 30%.
Can one do better?
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Schematic of Photo Reactive Distillation System
Configured into a Semi-Batch Model Allows in situ product removal and toluene recycle.
Selectivity to benzyl chloride: 96% + up to toluene conversion of 98%.
Z. Xu (1998)
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PROBLEM
Production of herbicide intermediate, aryl amino-alcohol (AA) via hydrogenation of aryl nitro-alcohol (NA) Reaction System: Current Reactor: complex semi-batch dribbling liquid reactor with suspended catalyst slurry
DISADVANTAGES:
Low volumetric productivity
Poor selectivity
Catalyst filtration and separation
problems Pressure limitations (due to shaft)
Khadilkar et al., AIChE J., 44(4), 912 (1998) Khadilkar et al., AIChE J., 44(4), 921 (1998)
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Reaction Network
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Conclusions
Liquid trickling flow pattern is preferable to a suspended catalyst mixed slurry to obtain the desired yield and productivity of Amino Alcohol.
Yield improvement is observed with decreasing feed concentration, liquid flow rate and temperature due to suppression of NA decomposition and subsequent side reactions.
Productivity of AA is a complex function of flow, feed concentration and temperature with optimal productivity being determined by the level of acceptable by-product concentrations.
Laboratory trickle bed performance data is shown to be an effective means to obtain the network kinetic parameters by proposing a plausible mechanism and optimizing the reactor model generated data. This is particularly effective in cases where conventional slurry and basked methods are rendered ineffective by the dominance of side reactions.
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1.
2.
3.
4.
References
Dudukovic, M.P., Larachi, F., Mills, P.L., “Multiphase Reactors – Revisited”, Chem. Eng. Science, 541, 1975 1995 (1999).
Dudukovic, M.P., Larachi, F., Mills, P.L., “Multiphase Catalytic Reactors: A Perspective on Current Knowledge and Future Trends”, Catalysis Reviews, 44(11), 123-246 (2002).
Levenspiel, Octave, Chemical Reaction Engineering, 3 rd Edition, Wiley, 1999.
Tranbouze, P., Euzen, J.P., “Chemical Reactors – From Design to Operation”, IFP Publications, Editions TECHNIP, Paris, France (2002).
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