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Simulation of Propane Dehydrogenation to Propylene through a Radial Flow
Reactor over the Pt-Sn/Al2O3 Catalyst
Article in Chemical Engineering & Technology · September 2015
DOI: 10.1002/ceat.201500082
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Research Article
Seyed M. Miraboutalebi1,2
Leila Vafajoo1
Mohammad Kazemeini3
Moslem Fattahi4
1
Simulation of Propane Dehydrogenation
to Propylene in a Radial-Flow Reactor over
Pt-Sn/Al2O3 as the Catalyst
1
Department of Chemical
Engineering, Islamic Azad
University, South Tehran
Branch, Tehran, Iran.
2
Young Researchers and Elite
Club, South Tehran Branch,
Islamic Azad University, Tehran,
Iran.
3
Department of Chemical and
Petroleum Engineering, Sharif
University of Technology,
Tehran, Iran.
4
Department of Chemical
Engineering, Abadan Faculty of
Petroleum Engineering,
Petroleum University of
Technology, Abadan, Iran.
1
Catalytic paraffin dehydrogenation for manufacturing olefins is considered to be
one of the most significant production routes in the petrochemical industries. A
reactor kinetic model for the dehydrogenation of propane to propylene in a
radial-flow reactor over Pt-Sn/Al2O3 as the catalyst was investigated here. The
model showed that the catalyst activity was highly time dependent. In addition,
the component concentrations and the temperature varied along the reactor radius owing to the occurring endothermic reaction. Moreover, a similar trend was
noticed for the propane conversion as for the propylene selectivity, with both of
them decreasing over the time period studied. Furthermore, a reversal of this
trend was also revealed when the feed temperature was enhanced or when argon
was added into the feed as an inert gas.
Keywords: Catalyst, Propane dehydrogenation, Propylene, Radial-flow reactor, Simulation
Received: February 9, 2015; revised: April 16, 2015; accepted: September 3, 2015
DOI: 10.1002/ceat.201500082
Introduction
Catalytic dehydrogenation of paraffins to olefins has been performed commercially since the late 1930s. During World War
II, catalytic dehydrogenation of butane over Cr/Al2O3 as the
catalyst was utilized for the production of butene to enhance
the octane number of aircraft fuel [1, 2]. In general, dehydrogenation reactions are carried out through a multistep mechanism. Meanwhile, other reactions including coking usually
occurred, leading to catalyst deactivation, thereby lowering the
reaction rate over a period of time [3, 4]. In addition, coke formation and the dehydrogenation reaction unavoidably affected
each other. Thus, semi-experimental models were utilized for
catalyst deactivation descriptions. These were based on introducing a deactivation function in terms of measurable variables
[5].
Olefins have been considered as the feed of many industries
including petrochemical plants [6]. On the other hand, lightalkane dehydrogenation is usually considered as an industrialized manufacturing method of olefins [7]. It ought to be mentioned that, due to the harsh operating conditions required for
the reaction, catalyst deactivation normally occurred very
quickly; hence, continuous regenerative techniques for the catalyst were needed. In this venue, moving-bed reactors with
continuous regenerative systems were employed in some cases
–
Correspondence: Dr. Mohammad Kazemeini (kazemini@sharif.edu),
Department of Chemical and Petroleum Engineering, Sharif University
of Technology, P.O. Box 11365-9465, Tehran, Iran.
Chem. Eng. Technol. 2015, 38, No. 00, 1–10
[8]. In another study, the catalyst regeneration was carried out
periodically in fixed-bed reactors. Here, the bed temperature
was increased to burn out the coke, thus renewing the catalyst
for the endothermic propane dehydrogenation (PDH) [9, 10].
Yet another research article [11] presented the combination of
exothermic and endothermic reactions of this kind. Other
researchers compared simultaneous and sequential methods to
combine non-oxidative PDH and the methane–propane burning reaction on a Pt catalyst in fixed-bed reactors [12, 13].
Propylene has always been mentioned as one of the most
important light olefins according to its usage in petrochemical
plants and its valuable role in downstream chemical products.
This species possesses higher added-value than other petrochemical raw materials like natural gas and naphtha. Besides,
both the economic terms of supply and demand being on the
positive side provided an added advantage for this material [7].
In addition, the increasing demand for light olefins (like this)
due to their environmental impacts drew even more attention
to this chemical [3]. Meanwhile, propylene has been produced
through many different routes. All of these methods were employed to fill up the gap between its demand and supply [3].
Some of these commercial routes are: steam cracking, catalytic
cracking in a fluidized bed, deep catalytic cracking, metathesis,
propyl alcohol dehydration, and propane catalytic dehydrogenation. In the first and second methods, propylene is produced
as a byproduct [7]. Light-paraffin dehydrogenation is considered as common practice in olefin production. The processes
of paraffin dehydrogenation can be divided into two major categories: ordinary paraffin dehydrogenation and oxidative paraffin dehydrogenation. While oxidative dehydrogenation is an
exothermic reaction and is accompanied by water production,
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2
ordinary dehydrogenation is an endothermic reaction
[4, 14–16]. As a consequence of many side reactions affecting
the appropriate yield and catalyst activity, extensive research
has been carried out in recent years on the appropriate catalyst
selection, the optimum operation conditions, and on suitable
reactors [17–21]. On the other hand, radial-flow reactors have
been widely used in processes such as paraffin and ethyl benzene dehydrogenation. Furthermore, their lower pressure drops
and smaller reactor volumes might be counted as their advantages in comparison with conventional tubular reactors [1, 22].
In this regard, PDH reactors are commonly operated at
525–625 C and around atmospheric pressure, assisted by platinum or chromia catalyst supports [3, 23].
Although there are some research studies on the kinetics
of PDH in different reactors, investigations on the impact of
pressure, temperature, and inert gases on the PDH reaction
in a radial-flow reactor have not been published yet. In the
present study, the simulation of PDH aiming towards propylene production in a radial-flow reactor over Pt-Sn/Al2O3 as
the catalyst was investigated. For this purpose, a kinetic
model was proposed to predict the propane conversion and
the propylene selectivity as a function of the inlet feed temperature. Moreover, the catalyst deactivation and process
temperature profiles in terms of the reaction time and reactor radius were studied.
for the present study since it most consistently describes the
considered experimental data. Moreover, it was assumed that
propane absorption was negligible, as confirmed in previous
researches [3, 5].
In addition, the proposed rate expressions for the reactions
of cracking and ethylene hydrogenation are shown in Tab. 2
[3, 5].
2.3 Radial-Flow Reactor Model
In the present study, the PDH reaction in a radial-flow fixedbed reactor (RFBR) was considered. Accordingly [24], the reactor model for an RFBR is provided in Eq. (4):
dnT;i
¼ rb r i
dVreactor
ði ¼ 1; 2; . . . ; kÞ
(4)
where i indicates the i-th chemical component. Eq. (4) was simplified for a cylindrical fixed-bed reactor at a fixed length as
follows:
dyi 2prL
¼
r r
nT b i
dr
(5)
2.4 Material and Energy Balances for Components
2
Reactor Modeling and Simulation
With respect to the initial concentration of the participating
components and the inert material in the RFBR, the material
balances for nT ; yC3 H8 ; yH2 ; yC2 H4 and yAr are written as
below:
2.1 PDH and Side Reactions
Propylene production reactions in the presence of a platinum
catalyst based on alumina have been investigated experimentally [5]. The following reactions were suggested. The main
reaction of PDH to propylene is as follows [3, 5]:
nT ¼
C3H8 > C3H6 + H2
yC3 H8 ¼
(1)
While the above reaction is an equilibrium reaction, other reactions like cracking and ethylene
hydrogenation affecting the main product formation are in the center of the modeling approaches
and simulations carried out in this study [3, 5].
Cracking reaction:
C3H8 fi CH4 + C2H4
0 þ 2y0
0
0
yC0 3 H8 þ yH
C2 H6 þ yC2 H4 þ yAr
2
1 yC3 H6 yCH4 þ yC2 H6
0 Þn0
ðyC0 3 H8 þ yC0 3 H6 þ yCH
T
4
nT
Model
Power law
LHHW-1
Ethylene hydrogenation:
(3)
rC3 H8 ¼ k1 PC3 H8 rC3 H8 ¼
LHHW-2
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PC3 H6 PH2
Keq
!
k1 KC3 H8 ðPC3 H8 ðKC3 H6 =KC3 H8 ÞðPC3 H6 PH2 =Keq ÞÞ
1 þ PC3 H8 =KC3 H8 þ ðPC3 H6 =KC3 H6 Þ
k1 ðPC3 H8 1þð
PC3 H6 PH2
PC3 H6
KC3 H6
Three different models have been proposed for the
main PDH reaction rate [5] and are provided in
Tab. 1. Out of these, the Langmuir-HinshelwoodHougen-Watson 2 (LHHW-2) model was chosen
(7)
Kinetic equation
r1 ¼
2.2 Proposed Mechanism and Kinetics
of the PDH Reaction
yC3 H6 yCH4
(6)
Table 1. Proposed models for the PDH reaction.
(2)
C2H4 + H2 fi C2H6
n0T
Keq
Þ
Þ
Table 2. Reaction rate expressions for the cracking and ethylene hydrogenation
reactions.
Cracking reaction
r2 ¼ k2 PC3 H8
Ethylene hydrogenation
r3 ¼ k3 PC2 H4 PH2
ª 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim
Chem. Eng. Technol. 2015, 38, No. 00, 1–10
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Research Article
yH2 ¼
0 y0
0
0
ðyH
C3 H6 þ yC2 H6 ÞnT
2
yC2 H4 ¼
yAr
nT
3
where
þ yC3 H6 yC2 H6
0
ðyC0 2 H4 yCH
þ yC0 2 H6 Þn0T
4
nT
(8)
Cm ¼
þ yCH4 yC2 H6
(9)
y 0 n0
¼ Ar T
nT
(10)
Moreover, the material balances for other components [24]
are provided as:
dyC3 H6 2prLrb ¼
1 yC3 H6 ar1 yC3 H6 r2 þ 2 yC3 H6 r3
dr
nT
(11)
dyCH4 2prLrb yCH4 ar1 þ ð1 yCH4 Þr2 yCH4 r3
¼
dr
nT
(12)
dyC2 H6 2prLrb ¼
yC2 H6 ar1 yC2 H6 r2 þ 1 yC2 H6 r3
dr
nT
(13)
(14)
where DH1, DH2, and DH3 are the reaction enthalpies of the
corresponding reactions (1), (2), and (3), respectively.
2.5 Coke Formation and Deactivation Model
Several authors have developed different models for the coke
formation of the PDH reaction. A rather popular mechanistic
model is called the monolayer-multilayer coke growth model
(MMCGM) [25]. This was generalized and modified [26], has
been employed by many authors [3, 5, 27–29], and was also
utilized in the present study. Tab. 3 indicates three catalyst activity models for the PDH reaction that have been investigated
previously [5].
The D3 model was chosen for the catalyst activity [3–5] in
the present model, owing to the lower errors resulting from its
implementation:
C
a ¼ ð1 g1 Cm Þ þ g2 Cm exp g3 M
Cm
Table 3. Catalyst activity models.
Model
Activity
D1
a =(1 – aCm)2
D2
a = (1 – g1Cm) + g2(Cm/(Cm + CM))
D3
a = (1 – g1Cm)+g2Cm exp[–g3(CM/Cm)]
Chem. Eng. Technol. 2015, 38, No. 00, 1–10
k1c t
1 þ Cmax k1c t
(16)
CM ¼ k2c t
(17)
Eag1 1
1
g1 ¼ g01 exp
R
T T0
(18)
and
Eaic 1
1
kic ¼ k0ic exp
T T0
R
(19)
2.6 Reaction Kinetic Constants and DH Correlations
According to the Arrhenius equation chemical kinetics and
results available in the literature, the reaction and equilibrium
constants can be written as in Eqs. (20)–(22) [3, 5, 24].
ki ¼ k0i exp
Furthermore, the energy balance for the reactor regarding
the three considered reactions was determined as follows:
dT
2prLrb
¼
½ðDH1 ar1 Þ þ ðDH2 r2 Þ þ ðDH3 r3 Þ
dr nT CP;mix
2
Cmax
Eai 1
1
T T0
R
(20)
DH 1
1
kC3 H8 ¼ k0 exp
R
T T0
(21)
15394 148728
Keq ¼ exp 16:858 · 105
þ
T
T2
(22)
In accordance with classical thermodynamics, the final reaction heat involved at temperature T can be written as Eq. (23)
[30].
DHR;T ¼ DHR;298 þ DaðT 298Þ þ
þ
in which
DHR;298 ¼
Da ¼
Db ¼
(15)
Dg ¼
X
X
X
Db 2
T 2982
2
Dg 3
T 2983
3
X
(23)
Wi DHf;i;298
(24)
Wi ai
(25)
Wi bi
(26)
W i gi
(27)
Values of the thermodynamic parameters and components
of the model are presented in Tabs. 4 and 5.
3
Solution Method and Procedure
The developed model was solved utilizing the 4th-order
Runge-Kutta technique in the radial direction with appropriate
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Table 4. Values of a, b, and g for different materials participating in the considered reaction, obtained from [30, 31].
a
b [·103]
g [·106]
C3H8
1.213
28.785
–8.824
C3H6
1.637
22.706
–6.915
H2
3.249
0.422
–
CH4
1.702
9.081
–2.164
C2H4
1.424
14.394
–4.392
C2H6
1.131
19.225
–5.561
2.5
–
–
Component
Ar
Table 5. Model values used in the present simulation
[4, 5, 12, 21, 23, 24].
Parameter
Value
L [m]
15
–1
a0 [kgcatkgcoke ]
–1
a2 [kgcatkgcoke ]
–1
Cmax [kgcokekgcat ]
Tm [K]
700
394
1.04 ·10–3
793.15
–1
Ea1 [J mol ]
34 570
Ea2 [J mol–1]
137 310
Ea3 [J mol–1]
154 540
Ea1c [J mol–1]
38 430
Ea2c [J mol–1]
125 510
Eag1 [J mol–1]
9610
k01 [mol kg–1s–1P–1]
8.74 ·10–8
k02 [mol kg–1s–1P–1]
7.75 ·10–10
k03 [mol kg–1s–1P–1]
3.9 ·10–11
k01c [kgcokekgcat–1s–1]
3.9
–1 –1
k02c [kgcokekgcat s ]
k C3 H 6
2.42 ·10–8
3.46
–1
DHC3 H6 [J mol ]
–85,817
–1
124 260
–1
81 280
–1
DH3 [J mol ]
–136 960
R [m]
0.75–1.5
DH1 [J mol ]
DH2 [J mol ]
–1
nT0[mol s ]
237.5
T [K]
813/848/873
P [Pa]
105
initial conditions. It ought to be noted that the temperature
and the component concentrations as well as all other variable
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parameters involved needed updating over the reactor radius
increments for each iteration cycle. Additionally, at the end of
each iteration cycle, the step size was halved until the convergence criterion was reached. The calculation flow chart as well
as the appropriate initial and boundary conditions for the system used in this research are provided in Tab. 5 and Fig. 1.
4
Results and Discussion
As a key step in any simulation work, after developing a mathematical model, it has to be verified. This was done for the present work through a comparison of the results generated by the
model with those available in the open literature [29, 32, 33].
The results are shown in the parity plot of Fig. 2. It can be concluded that this model was verified utilizing independently
obtained experimental data, with a maximum error of 8 %. It is
worth mentioning that the preparation parameters of the catalysts in references [29, 32, 33] are not the same, which may
have led to different particle sizes and catalytic performances.
To clarify the aforementioned fact, the utilized model in this
study predicted the experimental results for the different catalyst structures with good accuracy rather than reconfirming the
robustness of the present model.
Fig. 3 illustrates the catalyst activity as a function of the reactor radius and time. It reveals that the catalyst activity diminished over time due to the coke formation progressing from
roughly 1 to 0.3 U (i.e., 100 % down to 30 %) in about 2 h.
Moreover, as a result of the occurring endothermic reaction
and the temperature drop in the radial direction during this
period of time, the rate of the reactions kept decreasing. Nonetheless, a slight increase in activity towards the end of the reactor was observed at the end of this time period.
As mentioned above, the PDH reaction was endothermic,
due to which the reactants were converted in the radial directions while the temperature fell. Fig. 4 shows the temperature
profile in the radial direction of the reactor, falling gradually
from 820 to 750 K. It was a predictable conclusion (from both
Figs. 3 and 4) that the maximum reaction rate would be
observed in the reactor radius range of 0.7–1 m, where the
maximum temperature drop occurred.
Fig. 5 reveals the unsteady-state profiles of the propane conversion and the propylene selectivity, respectively. It is shown
in Fig. 5 a that the propane conversion grew modestly from
> 9 % to about 10 % over time, at a pressure of 100 kPa and a
temperature of 813 K.
On the one hand, the behavior revealed in Fig. 5 a was a consequence of the cumulative conversion of all involved species
mentioned earlier in this paper. In addition, the slope of the
graph in this figure declined over time, emphasizing the catalyst deactivation and showing that other undesired reactions
became more pronounced compared to the main one. On the
other hand, as the reactants were converted along the radius,
the bed temperature decreased due to the endothermic nature
of the reaction, resulting in a reduction of the rate constants
and thus lowering the reaction rates; in turn, reaction progress
occurred. Meanwhile, Fig. 5 b demonstrates that the propylene
selectivity decreased from approximately 77 % to 70 % over
time. As the rationale for this behavior it can once again be
ª 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim
Chem. Eng. Technol. 2015, 38, No. 00, 1–10
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5
lene selectivity. In other words, the yield was not
the exact criterion for decision making in order to
investigate the performance of the reaction system
or for achieving an extremely stable catalytic performance. In the present model, considering the
catalyst deactivations, the sharp changes in the propane conversion and propylene selectivity seem to
be rational.
Both trends observed in Fig. 5 a, b were repeated
as the feed temperature was enhanced. The results
of raising the temperature to 848 and 873 K at
100 kPa pressure are shown in Fig. 5.
It is noteworthy that PDH is a highly endothermic reaction; hence, it was to be expected that the
propane conversion increased while the propylene
selectivity dropped with respect to the input feed
temperature enhancement. This latter phenomenon can be attributed to the rate enhancements of
the side reactions. In other words, progress of the
undesired side reactions became pronounced compared with that of the main one. As such, the
unsteady behaviors of the propane conversion and
the propylene selectivity were explained. These
trends were revealed at all temperatures varying
from 813 to 873 K (Fig. 5).
Fig. 6 demonstrates the effect of the inert gases
(e.g., argon) on the propane conversion and propylene selectivity. It is displayed that the inert gases
helped to increase the propane conversion even
though the propylene selectivity decreased. This
was attributed to the argon gas increasing the heat
capacity of the mixture. This was in turn revealed
to be a consequence of the endothermicity of the
reaction requiring more energy input at higher
temperatures. Thus, utilizing an inert gas led to a
lower reaction temperature drop compared with an
inert gas-free system.
5
Conclusions
A mathematical model for PDH towards propylene
production in a radial-flow reactor over commercial Pt-Sn/Al2O3 as the catalyst was developed. The
results demonstrated that parameters such as the
activity of the catalyst, the reactor temperature, and
the feed composition were pronouncedly dependent on the time and on the radial spatial direction.
In addition, it was noteworthy that these variables
influenced each other rather dramatically. Furthermore, the developed model showed that the propane conversion decreased over time while it inFigure 1. Scheme of the process calculation for the model developed in this
creased when the feed temperature was enhanced.
study.
On the other hand, the propylene selectivity
revealed the reverse behavior as a result of the progressing side
pointed out that this was due to the side (i.e. undesired) reacand undesired reactions. In other words, the model predicted a
tions taking place more pronouncedly compared with the main
decrease of the selectivity towards propylene as a function of
one in this system. Besides, the propylene yield almost did not
the feed temperature with progressing time. In addition, adding
change with the reaction time due to the fact that the propylene
an inert gas into the feed caused an enhancement of the proyield is the product of the propane conversion and the propy-
Chem. Eng. Technol. 2015, 38, No. 00, 1–10
ª 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim
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6
Model Propane Conversion (mol.%)
60
R² = 0,9446
50
40
30
20
10
0
0
10
20
30
40
Propane Conversion from the References (mol.%)
50
60
Figure 2. Parity plot of the propane conversion data from the
developed model versus the experimental values obtained
from [29, 32, 33].
0.9
0.8
1
0.7
0.9
Activity
0.8
0.6
0.7
0.6
0
0.5
2000
0.4
0.4
4000
0.3
t (s)
0.2
1.5
0.5
0.3
6000
1.4
1.3
1.2
1.1
r (m)
1
0.9
0.8
0.7
8000
Figure 3. Impact of the time and the reactor radius on the catalyst activity in the studied system.
pane conversion while reducing the propylene selectivity. This
was attributed to the increased heat capacity of the resulting
mixture. In the future, it might be interesting to add some
material(s) of nonreactive nature (with the feed) possessing a
high heat capacity and to observe the propane conversion and
propylene selectivity behaviors, further investigating this idea
of inert gas addition.
The authors have declared no conflict of interest.
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Symbols used
a
CM
Cm
E
DH
k
kic
[–]
[kgcokekgcat–1]
[kgcokekgcat–1]
[J mol–1]
[J mol–1]
[mol kg–1s–1Pa–1]
[kgcokekgcat–1s–1]
Keq
L
nT
[Pa]
[m]
[mol s–1]
ª 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim
activity
multilayer coke
monolayer coke
activation energy
reaction enthalpy
reaction constant
kinetic constant of coke
formation
reaction equilibrium constant
reactor length
gas molar flow
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810
820
800
810
T (K)
800
790
790
780
780
770
770
760
750
0
1000
2000
3000
t (s)
4000
5000
6000
7000
1.5
1.4
1.3
1.2
1.1
1
0.9
0.8
0.7
760
r (m)
Figure 4. Unsteady variations of the temperature along the reactor radius for the studied system.
a)
b)
Figure 5. Unsteady-state profile of (a) the propane conversion and (b) the propylene selectivity at P = 100 kPa, generated by the model.
Chem. Eng. Technol. 2015, 38, No. 00, 1–10
ª 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim
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68.5
9.8
68
9.7
67.5
9.65
67
9.6
66.5
9.55
9.5
0
P
R
r
r
T
Vreactor
y
1000
[Pa]
[m]
[kg m–3]
[m]
[K]
[m3]
[–]
2000
3000
4000
Time(s)
5000
pressure
reactor radius
density
reactor radial distance
temperature
reactor volume
component mole fraction
Subscripts
b
c
eq
f
max
mix
m
M
6000
7000
[7]
[8]
[9]
[10]
[11]
bed
coke
equilibrium
fraction
maximum
mixture
monolayer
multilayer
[12]
[13]
[14]
[15]
[16]
References
[1]
[2]
[3]
[4]
[5]
[6]
Propylene Selectivity (mol.%)
Propane Conversion (mol.%)
9.75
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M. M. Bhasin, J. H. McCain, B. V. Vora, T. Imai, P. R. Pujadó,
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2013, 30 (1), 55–61.
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Catal. 2012, 107 (1), 141–155.
M. P. Lobera, C. Téllez, J. Herguido, M. Menéndez, Appl.
Catal., A 2008, 349 (1/2), 156–164.
E. Ziarifar, S. M. Fakhrhoseini, H. Ghiassi, Pet. Sci. Technol.
2013, 31 (6), 596–602.
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[17]
[18]
[19]
[20]
[21]
[22]
[23]
66
8000
Figure 6. (a) Unsteady-state propane conversion profile and (b)
propylene selectivity at 813 K
and 100 kPa in the presence of
argon, obtained by the developed model.
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Simulation of Propane
Dehydrogenation to Propylene in a
Radial-Flow Reactor over Pt-Sn/Al2O3
as the Catalyst
0.9
0.8
1
0.7
0.9
0.8
Activity
Research Article: Modeling of the
dehydrogenation of propane to
propylene in a radial-flow reactor over
Pt-Sn/Al2O3 shows that the catalyst
activity, reactor temperature, and feed
composition highly depend on the time
and the radial position. Adding an inert
gas into the feed enhances the propane
conversion and reduces the propylene
selectivity, probably due to the
increased heat capacity of the resulting
mixture.
0.6
0.7
0.6
0
0.5
S. M. Miraboutalebi, L. Vafajoo,
M. Kazemeini*, M. Fattahi
2000
0.4
t (s)
0.2
1.5
0.5
0.4
4000
0.3
0.3
6000
1.4
1.3
1.2
1.1
r (m)
1
0.9
0.8
0.7
8000
Chem. Eng. Technol. 2015, 38 (XX),
XXX K XXX
DOI: 10.1002/ceat.201500082
ª 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim
Chem. Eng. Technol. 2015, 38, No. 00, 1–10