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Enhancement of CO conversion in a novel slurry bubble column reactor for methanol synthesis
Journal of Natural Gas Science and Engineering 21 (2014) 170e183
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Enhancement of CO conversion in a novel slurry bubble column reactor for methanol synthesis K. Salehi a, S.M. Jokar b, J. Shariati a, M. Bahmani b, M.A. Sedghamiz b, M.R. Rahimpour b, * a b
Department of Chemical Engineering, Darab Branch, Islamic Azad University, Darab, Iran Chemical Engineering Department, School of Chemical and Petroleum Engineering, Shiraz University, Shiraz 71345, Iran
a r t i c l e i n f o
a b s t r a c t
Article history: Received 17 July 2014 Received in revised form 22 July 2014 Accepted 24 July 2014 Available online
This paper is dealing with the simulation of a commercial size slurry bubble column reactor (SBCR) for catalytic conversion of synthesis gas (CO þ CO2 þ H2) to methanol and comparison of the results especially carbon monoxide removal with gas-phase model in the quasi-steady state condition. For this purpose it was assumed that the flow pattern of gas is plug, and axial dispersion model was considered for liquidesolid phase. The results of the model for Shiraz petrochemical complex feedstock show that the production rate of methanol in a commercial SBC reactor is lower than conventional gas-phase methanol synthesis. This disadvantage is corrected by the modified feed which includes 5% CO and the 95% of the conventional feed. This novelty results in the same methanol production rate with the conventional gas-phase reactor. Besides the same methanol production rate, CO injection to the feed, causes water production noticeably reduced during methanol synthesis via CO2 hydrogenation. Consequently lower catalyst deactivation rate and higher methanol production rate are achieved. © 2014 Elsevier B.V. All rights reserved.
Keywords: Methanol Slurry-bubble column reactor Conventional methanol process Single-type reactor Catalyst deactivation Quasi-steady state
1. Introduction Due to its physical and chemical characteristics, methanol is a cheap and clean liquid alternative fuel and the starting chemical for formaldehyde and other solvents production. Methanol use in current-technology vehicles has some distinct advantages and disadvantages. Positive point is, methanol has a higher octane rating than gasoline. This reduces “knock” in the modern engines and can enhance fuel efficiency by adjusting the engine's compression ratio. Methanol high heat of vaporization results in lower peak flame temperatures than gasoline and lower nitrogen oxide emissions. However, energy density of methanol is approximately half of the one for gasoline that reduces the range a vehicle can travel on an equivalent tank of fuel. Methanol can be produced from the widely available materials such as coal and natural gas as well as biomass, and there is a potential to introduce methanol as a low cost and nature-friendly fuel. Conventionally, methanol is produced in gas-phase systems (in conventional fixed bed reactors) from a feedstock consisting of CO/CO2/H2 over a CuO/ZnO/Al2O3 catalyst. Generally, the potential drawbacks of industrial packed bed methanol reactors are pressure drop across the reactor, poor
* Corresponding author. Tel.: þ98 711 2303071; fax: þ98 711 6287294. E-mail address: [email protected] (M.R. Rahimpour). http://dx.doi.org/10.1016/j.jngse.2014.07.030 1875-5100/© 2014 Elsevier B.V. All rights reserved.
heat transfer rate, low production capacity and low catalyst particle effectiveness factors because of severe diffusional limitations for catalyst particle sizes used. Smaller particle sizes are infeasible in fixed-bed systems because of pressure drop considerations. In order to avoid serious pressure drop, the effective diameter of catalyst particles in fixed-bed reactor is usually over 3 mm, which brings a certain inner mass transfer resistance. Also, the factors affecting the production rate in industrial methanol reactors are parameters such as thermodynamic equilibrium limitations, catalyst deactivation and variation in stoichiometric proportion. Since methanol o synthesis is a high exothermic reaction ðDH298 ¼ 90:97 kJ mol1 Þ, and the conversion of the synthesis gas (CO þ H2) must be controlled at a low level in order to avoid possible overheating of the catalyst bed, the economic efficiency of the traditional gas phase methanol synthesis is unsatisfied (Wang et al., 2005; Rahimpour et al., 2008; Zhai et al., 2008; Rahimpour and Elekaei, 2009). Many research works have been accomplished for improving gas phase systems. For instance, Rahimpour and Ghader (2003, 2004) investigated the PdeAg membrane reactors performance for methanol synthesis, Rahimpour et al. (2003) and Rahimpour (2007) have presented strategies to enhance the ability of methanol synthesis reactor using a mixture of fresh and partially deactivated catalyst, Rahimpour (2008) proposed a two-stage catalyst bed reactor with high temperature in the first bed and low
K. Salehi et al. / Journal of Natural Gas Science and Engineering 21 (2014) 170e183
temperature in the second bed to enhance the reactor performance and finally Rahimpour and Lotfinejad (2008) presented dynamic model for studying PdeAg membrane in a dual-type reactor and showed that methanol production can be increased in membrane dual-type reactor. Also to overcome the problems associated with gas-phase systems, many reactor designs such as SBCRs and trickle bed reactors (TBRs) have been proposed (Zhai et al., 2008). In the late 1970s the liquid phase methanol synthesis was introduced in order to utilize CO-rich syngas from coal gasification. American Air products and Chemicals exploited the three phase SBCRs for methanol synthesis with CuO/ZnO/Al2O3 catalyst in the 1980s and built an industrial demonstration plant in 1997, which showed economic advantages (Maretto and Krishna, 1999; Van der Laan et al., 1999; Krishna and Sie, 2000; Li and Prakash, 2000; Wu and Gidaspow, 2000; Setinc and Levec, 2001; Rados et al., 2003; Zhai et al., 2008; Wang et al., 2011; Rahimpour et al., 2012). The liquid phase is used to absorb the heat released during the reaction. In general, SBCRs are preferred for fast and highly exothermic reactions. Since they provide some advantages such as better catalyst utilization (the size of catalyst particles ranges from 5 to 150 mm and solid loading ranges up to 50% volume), good heat and mass transfer characteristics due to the good interface contacting and high level of back mixing, usually no moving parts, ease of operation, low operating and maintenance costs, nearly isothermal operation and low pressure drop (Setinc and Levec, 1999, 2001; Shaikh and Al-Dahhan, 2007; Wang et al., 2007). Early SBCR models were reviewed by Ramachandran and Chaudhari, Deckwer and Fan (Gamwo et al., 2003). They required holdup correlations as an input and did not compute flow patterns. One of the best models applied for the FischereTropsch (FeT) conversion of syngas in an SBCR is that of Prakash and Bendale which gave syngas conversion and production as a function of temperature, pressure and space velocity. Input parameters with considerable uncertainty that influenced production rates were the gas holdup, the mass transfer coefficient and the dispersion coefficient. Van der Laan et al. extended such a model to compute product distribution using a product selectivity model. Degaleesan et al. measured dispersion coefficient needed as an input for a model like this (Gamwo et al., 2003). Wu and Gidaspow (2000) proposed a transient, two-dimensional hydrodynamic model for the production of methanol in SBCRs. Their model predicted down flow of catalyst at the walls and oscillatory particle and gas flow at the center (Wu and Gidaspow, 2000). Gamwo et al. (2003) proposed two Computational Fluid Dynamics (CFD) models; first model based on the kinetic theory of granular flow and the second one was based on the catalyst viscosity as an input. In SBC reactors, the phase back-mixing has been historically modeled using one of the two limiting ideal flow reactors; completely stirred tank or plug flow reactor. More recently, the phase back-mixing is modeled using the axial dispersion model (ADM) or the multi-cell model (MCM). Schluter et al. using a numerical simulation found the predictions of the ADM and MCM models to be similar (Rados et al., 2003). A new key issue which is recently reported for SBCRs is that the water produced during methanol synthesis via CO2 hydrogenation greatly reduces methanol synthesis rate by suppressing reaction. Water produced during methanol synthesis from CO2 conversion accelerates the crystallization of Cu and ZnO contained in a Cu/ZnObased catalyst to lead the deactivation of the catalyst. On the other hand, the catalyst is only slightly deactivated during methanol synthesis through a higher CO conversion, since only a small amount of water is produced during the reaction, and no
171
remarkable crystallization of Cu and ZnO occurred in the catalyst (Rahimpour and Ghader, 2003). One potential novel concept is injecting CO to the feed to improve methanol production rate and lower catalyst deactivation rate. In this study a one dimensional model with plug flow pattern for gas and axial dispersion model for liquidesolid suspension as a homogeneous phase was suggested for SBC reactor and mass balance equations were applied for two phases. Also it was assumed that the total heat of reaction which was produced in the process was subsequently removed. We considered quasisteady-state model simpler than dynamic model for simulation of an SBC reactor which was placed theoretically for conventional methanol reactor of Shiraz Petrochemical Complex and numerical simulation was utilized to compare results of novel SBC reactor with conventional gas-phase reactor. The effect of CO injection to the feed on the methanol production rate was also investigated. 2. Reactor configurations 2.1. Single type gas-phase reactor Fig. 1 shows the schematic diagram of a single-type methanol reactor. This reactor type is based on a vertical shell and tube heat exchanger. The catalyst is packed in vertical tubes and surrounded by the boiling water. The technical design data of the catalyst pellet and input data of the gas-phase methanol reactor are summarized in Tables 1 and 2 (Rahimpour and Lotfinejad, 2008). 2.2. Liquid-phase (SBC) reactor Fig. 2 shows a schematic diagram of a slurry bubble column reactor for methanol synthesis. Liquid phase contains an inert liquid such as paraffin oil, paraffin wax, decahydronaphthalene, tetrahydronaphthalene and etc. to absorb the heat of reaction and transfer the catalyst particles which disperse in liquid, and gas bubbles which go upward through liquid. Mass transfer is occurred between gas bubbleseliquidesolid particles and reaction is accomplished on the particles surfaces (Wu and Gidaspow, 2000; Gamwo et al., 2003; Wang et al., 2007). 3. Reaction scheme and kinetics for gas and slurry phase methods The syngas required for methanol synthesis contains CO2/CO/H2 and the following reactions occur on the catalyst surface (Rahimpour, 2008) in both gas and slurry method.
CO þ 2H2 4CH3 OH; CO2 þ H2 4CO þ H2 O;
DH ¼ 90 kJ=mol DH ¼ 412 kJ=mol
CO2 þ 3H2 4CH3 OH þ H2 ;
DH ¼ 49:2 kJ=mol
(1)
(2) (3)
The kinetics of low-pressure methanol synthesis (in gas-phase reactors) over commercial CuO/ZnO/Al2O3 catalyst has been widely investigated. Graaf et al. kinetic model, which includes hydrogenation of CO, CO2 and the reversed wateregas shift reactions is commonly used. The correspondent rate expressions for the hydrogenation of CO, CO2 and reversed wateregas shift reactions are (Rezaie et al., 2005):
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Fig. 1. A schematic diagram of a conventional single-type methanol synthesis loop.
2
3
3 fCH OH 7 6 k1 KCO 4fCO fH22 3 5
=
1 2
=
fH KP1 2
(4)
=
1 þ KCO fCO þ KCO2 fCO2
3 2 12 KH2 O 4f þ fH O 5 H2
1
=
r1 ¼
KH2
2
2
2
3
3 fCH OH fH O 7 6 k2 KCO 4fCO fH22 3 2 5
=
3
=
2
(5)
=
1 þ KCO fCO þ KCO2 fCO2
3 2 12 4f þ KH2 O fH O 5 H2
1
=
r2 ¼
fH2 KP2
KH2
2
2
fCO fH O k3 KCO2 fCO2 fH2 ðKP32Þ 3 2 r3 ¼ 12 KH2 O fH2 O 5 1 þ KCO fCO þ KCO2 fCO2 4fH2 þ
(6)
=
1
=
KH2
2
The reaction rate constants, adsorption equilibrium constants and reaction equilibrium constants in the kinetic expressions are tabulated in Tables 3e5 (Rezaie et al., 2005). Few studies have been published concerning the liquid phase process, in comparison to numerous papers for the gas phase methanol synthesis. Results show clearly the disagreement between the reported kinetic equations for two processes.
This phenomenon may be due to the presence of the liquid phase. The presence of liquid assures that in spite of gas phase, all active sites are at the same temperature in liquid phase. Setinc and Levec (1999) showed that most of the kinetic models of methanol synthesis have been developed for CO rich feed stocks, they satisfactorily matched their experimental data, while at very low CO2 concentrations (or very low CO2/(CO2 þ CO) ratio) these models failed completely. These models are also capable of predicting the decrease of the methanol production rate due to the water absorption on the catalyst surface as CO2 concentration increases (Graaf et al., 1988; Setinc and Levec, 1999). Therefore a relatively low CO2/CO ratio is used in the three-phase synthesis and water production can be neglected (Setinc and Levec, 1999). In this study the kinetic equation of Von Wededel et al. (Setinc and Levec, 1999) considering methanol synthesis only via CO conversion was applied in the reactor simulation. Equations (7) and (8) represent Von Wedel kinetic model (Setinc and Levec, 1999):
99; 360 0:4 0:18 cH2 cCO 6:8793 rCH3 OH ¼ 4:9409 1012 exp Rg T 107; 500 0:13 cCH3 OH 1012 exp Rg T (7)
Table 2 Specifications of synthesis gas. Feed
Table 1 Catalyst and reactor specifications for gas phase reactor. Parameter
Value
Unit
rS
1770 5.47 103 5 0.004 626.98 0.123 2962 7.022
[kg m3] [m] [kJ kg1 K1] [W m1 K1] [m2 m3] [e] [e] [m]
dP cpS
lC
aV 3 S/t Number of tubes Tube length
Composition (mole %) CH3OH CO2 CO H2O H2 N2 CH4 Total molar flow rate per tube Pressure Inlet temperature (K)
Value 0.50 9.40 4.60 0.04 65.90 9.30 10.26 0.64 76.98 503
Unit [e] [e] [e] [e] [e] [e] [e] [mole s1] [bar] [K]
K. Salehi et al. / Journal of Natural Gas Science and Engineering 21 (2014) 170e183
173
Fig. 2. Hydrodynamic of a slurry reactor for methanol synthesis.
Table 3 Reaction rate constants (Rezaie et al., 2005).
av hf ðT Ts Þ þ rB a
k ¼ A expðB=ðRg TÞÞ
A
B
k1 k2 k3
(4.89 ± 0.29) 107 (1.09 ± 0.07) 105 (9.64 ± 7.3) 1011
113,000 ± 300 87,500 ± 300 152,900 ± 11,800
4.1. Conventional gas-phase reactor In the gas-phase methanol synthesis at the quasi-steady state conditions, the balances are typically for convection and transport to the solid-phase. The mass and energy balances for the solid phase are expressed by Rezaie et al. (2005) and Rahimpour and Lotfinejad (2008):
i ¼ 1; 2; 3; …; N 1
(9)
Table 4 Adsorption equilibrium constants (Rezaie et al., 2005).
KCO KCO2 1 KH2 O =KH22
(10)
where yis and Ts are the solid-phase mole fraction and temperature, respectively. The following two conversion equations are written for the fluid phase (Rezaie et al., 2005):
(8)
4. Model equations for quasi-steady state conditions
K ¼ A expðB=ðRg TÞÞ
hri DHf;i ¼ 0
i¼1
rH2 ¼ 2rCH3 OH and rCO ¼ rCH3 OH
kgi ðyi yis Þ þ hri rB a ¼ 0;
N X
A 5
(2.16 ± 0.44) 10 (7.05 ± 1.39) 107 (6.37 ± 2.88) 109
Ft dyi þ av ct kgi ðyis yi Þ ¼ 0 AC dz
(11)
Ft dT pDi þ av hf ðTs TÞ þ U ðT TÞ ¼ 0 cpg dz AC AC shell shell
(12)
Catalyst deactivation model for commercial methanol synthesis has been adopted from Hanken (Rezaie et al., 2005; Rahimpour, 2008), where TR, Ed and Kd are the reference temperature, activation energy and deactivation constant of catalyst, with the numerical values of 513 K, 91,270 J mol1 and Kd, 0.00439 h1 respectively.
Table 5 Reaction equilibrium constants (Rezaie et al., 2005). B
kP ¼ 10ððA=TÞBÞ
A
B
46,800 ± 800 61,700 ± 800 84,000 ± 1400
KP1 KP2 KP3
5139 3066 2073
12.621 10.592 2.029
=
174
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Table 6 Coefficients for Henry's constant evaluation.
Hydrogen Carbon monoxide Carbon dioxide Methanol Water
Table 9 Specifications of synthesis gas and reactor design for slurry and gas phase reactor.
a (bar mol1)
b (J mol1)
Feed
78.192 109.87 429.52 8190.6 7936.7
2854.0 939.7 8969.5 30,410 37,421
Composition (mole%) CH3OH CO2 CO H2O H2 N2 CH4
0.5 9.4 4.6 0.04 65.9 9.3 10.26
Total molar flow rate Inlet temperature Inlet pressure Reactor diameter Slurry height
1895.68 523 53 3 7
Table 7 Input data of slurry reactor simulation (Wu and Gidaspow, 2000). Feed composition
Value (mole%)
CH3OH CO2 CO H2 N2
0.0 13 51 35 1
Total molar flow rate Pressure Inlet temperature
Unit [e] [e] [e] [e] [e] [mole s1] [bar] [K]
47.86 53 523
da Ed 1 1 ¼ Kd exp a5 dt Rg T TR
(13)
4. 5.
6.
Initial condition for this ordinary differential equation is: at t ¼ 0, a ¼ 1. 4.2. Slurry bubble-column reactor SBCRs can operate either in the homogeneous or heterogeneous (churn-turbulent) flow regime. In the homogeneous regime, the gas flow rate is low, and small bubbles of gas (1e10 mm) are uniformly distributed into the slurry phase (liquid þ catalyst particles). In the heterogeneous regime some small bubbles combine in clusters to form large bubbles (20e70 mm). These large bubbles travel up through the column at high velocities (1e2 m/s) and have the effect of churning up the slurry phase, while small bubbles are entrained in the slurry phase and as a good approximation have the same back-mixing characteristic of the slurry phase (Behkish et al., 2002; De Swart and Krishna, 2002). However the modeling of a slurry bubble column reactor for methanol synthesis in this study is based on the following assumptions. 1. The plug flow model has been assumed for the gas phase and so the diffusional term in comparison with convection term in mass balance equation has been neglected. 2. The slurry phase is modeled by an axial dispersion model. 3. Due to the very small particle size of catalysts, the effectiveness factor is taken as unity and the liquidesolid mass transfer Table 8 Comparison between the simulation results and Air Products' (1991) RUN E-8.1.
CO conv. (%) Superficial gas velocity (m/s) Gas holdup (%) Reactor diameter (m) Slurry height (m) Solid holdup (%) Total catalyst (g) CH3OH (tons/day) Errora % a
jCH3 OHRun CH3 OHSimu: j CH3 OHRun
100.
Simulation
RUN E-8.1
15.8 0.15 29.5 0.57 5.08 26.8 567
13.5 0.15 29.5 0.57 5.08 26.8 567
10.6 18.7
8.93 e
7.
Value
Unit [e] [e] [e] [e] [e] [e] [e] mol s1 K bar m m
resistance is neglected. Therefore liquid and solid phase is a homogeneous phase which reaction occurs in this phase. The model assumes isothermal conditions within the reactor and catalyst particles. Methanol synthesis occurs just through CO hydrogenation and water gas shift reaction is in the dynamic equilibrium (Wang et al., 2005). The deactivation of the catalyst in a slurry phase methanol synthesis is still a problem for commercialization. The experimental results of X. Zhai et al. indicated that Cu composition of catalyst had not changed significantly during the reaction, and sintering of Cu particles of the catalyst was the main reason of the deactivation. This deactivation procedure has been affected by the time on stream and the temperatures at which sintering may occur that directly related to the melting temperature (Zhai et al., 2008). In this work, the deactivation of catalyst particles is considered the same as of the gas phase methanol synthesis which depends on temperature only. Pressure along the reactor length is not constant and pressure drop is calculated according to the following relation (Li and Prakash, 2000):
DP ¼ rg 3 g þ rl 3 l þ rs 3 s gDz
(14)
Based on the above assumptions, the mass balances are applied over a differential element of reactor at steady state conditions as following equations: For gas phase:
dUg Ci;g ðkl aÞi c*i;l ci;l ¼ 0 dz
(15)
And for liquid phase: Table 10 The comparison of methanol production rate in industrial plant, gas phase model and slurry phase model. Time (day)
Plant (tons/day)
Gas-phase model (tons/day)
Slurry-phase model (tons/day)
0 100 200 300 400 500 600 700 800 900 1000 1100 1200
295.0 296.5 302.6 284.3 277.9 278.2 253.0 274.0 268.1 275.5 274.6 262.9 255.2
308.8 297.03 289.1 283.09 278.19 274.03 270.41 267.19 264.3 261.67 259.25 257.02 255.18
195.7854 161.6251 150.9195 144.1356 139.1529 135.2063 131.9565 129.1920 126.7891 124.666 122.7657 121.0471 119.4794
K. Salehi et al. / Journal of Natural Gas Science and Engineering 21 (2014) 170e183
175
(b)
(a)
(c)
(d)
(e)
Fig. 3. Comparison of species (a) methanol, (b) CO2, (c) CO, (d) H2, (e) H2O mole fractions along the reactor axis between the conventional reactor, and the slurry reactor at the same conditions.
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3 l El
d2 ci;l dz2
dUss ci;l þ ðkl aÞi c*i;l ci;l ahri Cs ¼ 0 dz
(16)
The solubility of each species in liquid (in this work Squalane, C30H62) is calculated using Henry's law:
c*i;l ¼
Pi Hei
(17)
where Pi is a partial pressure of species i, in the gas phase and the numerical values of Henry's constant for H2, CO, CO2 and CH3OH in Squalane are tabulated in Table 6 (Setinc and Levec, 1999). Energy balance for entire system is:
3 sl lax
Fig. 4. Methanol production rate at time zero versus percentage of CO injected to the feed.
X v2 T A DH aeff Heat ðT Tsat:water Þ ¼ 0 þ 3 s rs ahr i f i ACS vz2 (18)
It was assumed that the slurry temperature is uniform along the reactor due to the high suspension heat conductivity lax.
(a)
(b)
(c)
(d)
Fig. 5. Comparison of (a) methanol, (b) CO2, (c) CO and (d) H2 mole fractions along the reactor axis between the conventional reactor with the main feed composition and the slurry reactor in the case of 5% CO injection to 95% of the feed.
K. Salehi et al. / Journal of Natural Gas Science and Engineering 21 (2014) 170e183
(a)
177
(b)
Fig. 6. Comparison of (a) CO and (b) H2 conversions along the reactor length in the cases of the conventional feed and 5% CO injection to 95% of conventional feed.
According to the assumption 6, approximate catalyst activation “a” can be calculated at any time by Hanken model (equation (13)). 5. Numerical solution The governing equations of slurry reactor model are solved at quasi-steady-state conditions. To solve this set of equations, reactor is divided into 100 separate sections and forward finite difference approximation is applied. This procedure replaces the differential equations by a non-linear algebraic set of equations and the NewtoneRaphson method is used to solve these set of equations in each section. Gas-phase and slurry-phase reactor outputs have been compared by Rezaie et al. (2005). 6. Results and discussion 6.1. Model validation for slurry reactor Model validation is carried out by simulation of Air Products' (1991) RUN E-8 series for methanol synthesis (Wu and Gidaspow, 2000). Feed composition and flow rate are tabulated in Table 7, the technical design specifications of Air Products' reactor and the results of this simulation at time zero (activation is unity) which is within the error bounds of the model LaPort's RUN E-8.1 are shown in Table 8. This systematic error is based on the kinetic equation as shown by Setinc and Levec (1999). It should be noted, all of data in this work will include this error. 6.2. Model validation of proposed slurry reactor and gas-phase for methanol synthesis in Shiraz petrochemical complex feedstock Model validation of slurry reactor was carried out by comparison of the conventional process data with model results under the design specifications of slurry methanol synthesis reactor of Air Product but with the reactor size and input data of Shiraz Petrochemical Complex reactor (Tables 8 and 9). Table 10 shows the methanol production rate of plant, gas phase and slurry reactor models respectively. The results of slurry reactor
model and Rezaie et al. model (Rezaie et al., 2005) are illustrated in Fig. 3(a)e(d). Results clearly show that, because of low methanol production rate due to the high (CO2/CO2 þ CO) ratio, slurry reactor is not suitable for this feed. Fig. 3(a) shows the lower methanol mole fraction in the slurry bubble reactor rather than the conventional gas-phase reactor in the case of the same feed composition. While the methanol mole fraction decreased in the slurry reactor, Fig. 3(b) and (d) shows that CO2 and H2 mole fraction increased through the reactor. Since the water mole fraction increased in the slurry bubble reactor than the conventional reactor for the same feed composition, as shown in Fig. 3(e), the crystallization of active metal species on the catalyst basis would be increased and the catalyst activity decreased. Next step contains the change in feed composition by adding additional CO to the feed under the condition of constant flow rate of the main feed and CO injection flow rate. This change increases the conversion of gas phase due to the higher inlet superficial velocity (Maretto and Krishna, 1999). Fig. 4 illustrates the methanol production rate in the presence of CO injection condition from 0% to 10% of conventional feed. As shown in Fig. 4, if the SBCR entrance feed approximately equals 95% of the main feed and 5% of CO injected, production rate of methanol will be the same as conventional system. As it can be seen from Fig. 4, larger amount of CO% injection leads higher amount of methanol production, according to the lower water production from CO2 hydrogenation. Since the methanol production rate increased by higher CO% injection, catalyst activity reduces through the pollutant specification of CO. As a result the optimum CO% injection must be considered in order to achieve the desired amount of the methanol production rate. Fig. 5(a)e(d) shows the comparison of species CH3OH, CO, CO2 and H2 mole fractions in conventional gas-phase and slurry methanol synthesis in the case of 5% CO injection. As mentioned above, þ17.8% errors in the results of slurry reactor should be considered. Fig. 5(a) shows the positive effect of CO injection on the increasing of the methanol production rate based on the higher
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catalyst activity in the presence of the lower water production rate, also Fig. 5(b) represents the grow up trend for CO2 mole fraction based on the same reason. Figs. 6(a) and (b) and 7(a)e(d) show the comparison of CO and H2 conversion and CH3OH, CO2, CO and H2 mole fraction in the case of the conventional feed and 5% CO injection to the 95% of feed respectively. Fig. 6(b) shows that the 5% of injected CO to the conventional feed results in higher value of H2 conversion and lower one for H2 mole fraction, as illustrated in Fig. 7(d). Fig. 6(a) shows that, the CO conversion in the case of 5% of injected gas is lower than conventional feed. While the excess amount of CO injected to the reactor, higher methanol mole fraction achieved, as shown in Fig. 7(a), according to the higher catalyst activity and lower water production rate and the amount of unreacted CO also increases in the reactor, so the CO conversion decreases and the CO mole fraction increases as it can be clearly seen in Fig. 7(c). Fig. 8(a) and (b) reveals the methanol production rate along the reactor length and methanol production rate with time in both
cases. Fig. 9 shows the comparison of the catalyst activity in the conventional and SBC reactors with time. Fig. 8(a) reveals that the methanol production rate increases thorough the reactor at the specific time interval, also Fig. 8(b) shows that the time has the negative effect on the methanol production rate. As it can be seen from Fig. 9, the catalyst activity decreases by passing the time, this dropping trend is based on the two deactivation phenomenon. The prior is the sintering in the case of high temperature and the latter is the fouling in the presence of pollutant such as higher amount of CO, so the methanol production rate and the catalyst activity decrease by the time. It can be seen from Fig. 9 that, activity of catalyst in the presence of 5% of injected CO is higher than the conventional feed. This behavior is also related to the noticeably decreasing in the water production rate through CO2 hydrogenation in the slurry reactor with higher CO/(CO þ CO2) ratio and consequently lower catalyst crystallization. In Fig. 10, the methanol production rate at three different temperatures in the case of 5% CO injection to 95% of conventional feed
(a)
(b)
(c)
(d)
Fig. 7. Comparison of (a) CH3OH, (b) CO2, (c) CO and (d) H2 mole fraction in the cases of the conventional feed and 5% CO injection to 95% of conventional feed.
K. Salehi et al. / Journal of Natural Gas Science and Engineering 21 (2014) 170e183
(a)
179
(b)
Fig. 8. Comparison of methanol production rate (a) along the reactor length at time zero and (b) respect to time with the conventional feed and 5% CO injection to 95% of the conventional feed.
along the reactor length and time is shown. Higher temperature, increases the equilibrium constant of methanol synthesis reaction, but sintering as a source of catalyst deactivation also increases by temperature, so an optimum condition must be considered. Fig. 11(a)e(g) shows three dimensional plots of CO and H2 conversion, CO, CO2, H2 and CH3OH mole fractions and methanol production rate along the reactor length and time in the case of 5% CO injection to 95% of conventional feed. Fig. 11(a) and (b) shows that the maximum conversion of CO and H2 has been occurred at the start time, according to the higher catalyst activity, and the exit coordinate of the reactor.
Consequently CO and H2 mole fraction are vice versa, as shown in Fig. 11(c) and (f). Methanol mole fraction and the methanol production rate are the function of catalyst activity. At the time zero, the catalyst activity is maximum, so the methanol production rate, Fig. 11(g), and methanol mole fraction, Fig. 11(e), hit the maximum at time zero and the exterior interval of the reactor. Figs. 12 and 13 illustrate the comparison between CO removal in conventional gas phase reactor, slurry reactor with the conventional feed and the slurry reactor with 5% of CO injection to the feed versus the reactor length and the time respectively.
Fig. 9. Comparison of catalyst activity in conventional an SBC reactors with time.
Fig. 10. Effect of temperature on the methanol production rate with time.
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K. Salehi et al. / Journal of Natural Gas Science and Engineering 21 (2014) 170e183
Fig. 11. Three dimensional plots of (a) CO and (b) H2 conversion, (c) CO,(d) CO2, (e) H2 and (f) CH3OH mole fraction and (g) methanol production rate along the reactor length and time in the case of 5% CO injection to 95% of conventional feed.
Fig. 12 illustrates that the value of CO removal in the slurry reactor is higher than the conventional reactor. In addition, when the feed composition in the slurry reactor changes by addition of 5% of CO injection, final CO removal increased by 200%, from 150 tones per day to a little higher than 300 tones per day. This noticeably increasing in CO removal is regarding to the lower deactivation rate based on the lower water production rate among the slurry reactor, as shown in Fig. 9. Since the catalyst activity has been decreased by the time, according to the sintering and fouling procedures, the CO removal shows the falling trend in Fig. 13. It can be clearly seen that, however the CO removal in the slurry reactor with the modified feed composition is larger than the one in the slurry reactor with the conventional feed and also the conventional gas-phase reactor.
7. Conclusion Results clearly show that slurry bubble reactor for methanol synthesis, is not suitable for common feedstock of Shiraz Petrochemical Company, regarding to its high feed ratio of CO2/ (CO2 þ CO) which causes to reduce the methanol production rate in proposed reactor model in comparison to conventional gas phase process. Many researches, reported that in the slurry bubble reactor, methanol synthesis occurs through CO hydrogenation only, and therefore low value of CO2/(CO2 þ CO) ratio should be applied. As a result in conventional feedstock such as Shiraz Petrochemical feedstock, CO should be injected to the feed in order to reduce the ratio of CO2/(CO2 þ CO). In this study by injecting 5% CO to 95% of
Fig. 12. The comparison of CO removal along the rector length in the conventional gas phase reactor, slurry reactor with conventional feed and slurry reactor with 5% CO injection to the feed along.
K. Salehi et al. / Journal of Natural Gas Science and Engineering 21 (2014) 170e183
181
And the diffusivity of component i in the gas mixture and in the binary systems is as:
1y Dim ¼ PN yi
(A-4)
i
j¼i Dij
vffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi u , Mi þ 1 M j 3 2 3 p yci2 þ ycj2
3 u 107 T 2 t1
=
(A-5)
=
=
Dij ¼
kl a ¼ 0:18Sc0:6
rL vA MB
2:84
rg Ug
0:49
e2:66CV
(A-6)
And the axial dispersion coefficient of the liquid phase is calculated using the relation proposed by Deckwer et al. (De Swart and Krishna, 2002):
El ¼ 0:768Ug0:32 D1:34 T
Fig. 13. The comparison of CO removal with time in the conventional gas phase reactor, slurry reactor with conventional feed and slurry reactor with 5% CO injection to the feed.
conventional feed, it can be seen that methanol production rate is the same that of the gas phase system. By CO injection to the feed, water has been produced during methanol synthesis via CO2 hydrogenation which accelerates the catalyst deactivation and reduces methanol production rate dramatically. CO is an important cause of pollution and a hazardous material in many industrial processes work with catalysts, which must be removed anyway and this method can be used in this case. Results showed that the methanol production rate has been increased by increasing the temperature while the catalyst deactivation rate also showed the upward trend based on the sintering phenomenon. Appendix A. Auxiliary correlations To complete the simulation, auxiliary correlations should be added to the model. The main auxiliary correlations encountered in the formulation of a slurry bubble column reactor are mass and heat transfer.
(A-7)
A.2. Heat transfer correlations The overall heat transfer coefficient Ushell and aeff in gas phase and liquid phase methanol synthesis respectively are estimated using the relations (A-8) (Rezaie et al., 2005) and (A-11) (De Swart and Krishna, 2002)
1 1 ¼ þ Ushell hi
Ai ln Do=D i 2pLKw
þ
Ai 1 Ao ho
(A-8)
hi is the heat transfer coefficient between the gas phase in the tube side and reactor wall and is obtained by the correlation (A-9) and ho is the heat transfer coefficient of boiling water in the shell side which is estimated by equation (A-10).
0:407 hi cp m2=3 0:458 rug dp ¼ cp rm K 3B m ho ¼ 7:96ðT Tsat Þ3
p pa
(A-9)
0:4
U3r g sl ¼ 0:1 rsl cpsl Ug ghsl
(A-10) !14
rsl cpsl lsl
1 2
A.1. Mass transfer correlations
aeff
In the current work, mass transfer coefficient for the components in gas-phase is as equation (A-1) (Rezaie et al., 2005) and the volumetric mass transfer coefficient of species i, in the liquid side of gaseliquid interface in slurry reactor is calculated using the equation of Behkish et al. (equation (A-6)) (Behkish et al., 2002):
For superficial gas velocities exceeding 0.1 m/s the heat transfer coefficient is to be calculated from above equation by taking Ug equal to 0.1 m/s. Parameters in the above equation are defined as (De Swart and Krishna, 2002):
kgi ¼ 1:17Re0:42 Sc0:67 ug 103 i
(A-1)
where the Reynolds and Schmidt numbers have been defined as:
2Rp ug Re ¼ m Sci ¼
m rDim 104
(A-11)
rsL ¼ cs rp þ ð1 cs ÞrL
(A-12)
cpsL ¼ Ws cps þ ð1 Wc ÞcpL
(A-13)
cs rp
cs rp rL þ rL
(A-2)
Wc ¼
(A-3)
hsL ¼ hL ð1 þ 4:5cs Þ
(A-14)
(A-15)
182
lsL ¼ lL
K. Salehi et al. / Journal of Natural Gas Science and Engineering 21 (2014) 170e183
2lL þ lp 2cs lL lp 2lL þ lp þ cs lL lp
lax ¼ EL cpsL rsL
Pa
(A-16)
(A-17)
where all parameters are defined in Appendix B. Appendix B. Symbols a av AC ACS AHeat cCO cCO2 cH2 ci,g ci,l cpg cps cpsl cs Cs ct CV DAB Dij Dim DT Ed El fi Ft ho hi Ht DHfi He kla k1 k2 k3 kgi K Kd Ki Kpi Kw L MB N P
activity of catalyst specific surface area of catalyst pellet (m2 m3) cross sectional area of each tube in gas phase reactor (m2) cross sectional area of slurry tank without coolant tubes heat transfer area in slurry reactor (m2) concentration of CO in liquid (mol l1) concentration of CO2 in liquid (mol l1) concentration of H2 in liquid (mol l1) concentration of i, in gas phase (mol m3) concentration of i, in liquid phase (mol m3) specific heat of the gas at constant pressure (J mol1) specific heat of the solid at constant pressure (J mol1) heat capacity of the liquidesolid suspension (J kg1 K1) catalyst concentration in the liquid solid suspension (m3 m3) catalyst concentration in the liquid solid suspension (kg m3) total gas concentration (mol m3) volumetric solid concentration in slurry (m3 m3) diffusion coefficient of component i in liquid (m2 s1) binary diffusion coefficient of component i in j (m2 s1) diffusion coefficient of component i in the mixture (m2 s1) reactor diameter (m) activation energy used in the deactivation model (J mol1) dispersion coefficient of liquid (m2 s1) partial fugacity of component i (bar) total molar flow rate per tube (mole s1) heat transfer coefficient between coolant stream and reactor wall (W m2 K1) heat transfer coefficient between fluid phase and reactor wall (W m2 K1) reactor height (m) enthalpy of formation of component i (J mol1) Henry's constant (bar mol1 l) volumetric mass transfer coefficient of i, in liquid side of gaseliquid interface (s1) reaction rate constant for the 1st rate equation (mol kg1 s1 bar1) reaction rate constant for the 2nd rate equation (mol kg1 s1 bar1) reaction rate constant for the 3rd rate equation (mol kg1 s1 bar1) mass transfer coefficient for component i (m s1) conductivity of fluid phase (W m1 K1) deactivation model parameter constant (h1) adsorption equilibrium constant for component i (bar1) equilibrium constant based on partial pressure for component i thermal conductivity of reactor wall (W m1 K1) length of reactor (m) molecular weight of liquid (kg kmol1) number of components total pressure (bar)
DP r Rg Rp Re Sc Sci t T TR Ts Tsat Tshell u Ug Ushell
yA yi yis Wc z
atmospheric pressure (bar) pressure drop (Pa) reaction rate in slurry phase (mol kg1 h1) universal gas constant (J mol1 K1) particle diameter (m) Reynolds number Schmidt number (n/DAB) Schmidt number of component i time (s) temperature within reactor (K) a reference temperature for activity estimation (K) temperature of solid phase (K) saturated temperature of boiling water at operating pressure (K) temperature of coolant stream (K) linear velocity of gas phase in gas phase methanol reactor (m s1) superficial gas velocity in slurry reactor (m s1) overall heat transfer coefficient between coolant and process streams in gas phase model (W m2 K1) solute molar volume (m3 kmol1) mole fraction of component i in fluid phase (mol mol1) mole fraction of component i in solid phase (mol mol1) catalyst weight fraction in suspension axial reactor coordinate (m)
Greek letters void fraction of catalytic bed 3g gas holdup 3L liquid holdup 3s void fraction of catalyst h catalyst effectiveness factor lax suspension effective axial heat conductivity (W m1 K1) lc thermal conductivity of catalyst (W m1 K1) ll thermal conductivity of liquid (W m1 K1) lsl thermal conductivity of liquidesolid suspension (W m1 K1) m viscosity of fluid phase (kg m1 s1) n stoichiometric coefficient in gas phase correlations n kinematic viscosity (m2 s1) r density of fluid phase (kg m3) rB density of catalytic bed (kg m3) rL liquid density (kg m3) rg gas density (kg m3) rs density of catalyst (kg m3) rsl density of the liquidesolid suspension (kg m3) t tortuosity of catalyst aeff overall heat transfer coefficient between coolant and process streams in slurry phase model (W m2 s1) hsl viscosity of the liquidesolid suspension (kg m1 s1) 3B
References Behkish, A., et al., 2002. Mass transfer characteristics in a large-scale slurry bubble column reactor with organic liquid mixtures. Chem. Eng. Sci. 57 (16), 3307e3324. De Swart, J., Krishna, R., 2002. Simulation of the transient and steady state behaviour of a bubble column slurry reactor for FischereTropsch synthesis. Chem. Eng. Process. Process Intensif. 41 (1), 35e47. Gamwo, I.K., et al., 2003. CFD models for methanol synthesis three-phase reactors: reactor optimization. Chem. Eng. J. 93 (2), 103e112. Graaf, G., et al., 1988. Kinetics of the three phase methanol synthesis. Chem. Eng. Sci. 43 (8), 2161e2168. Krishna, R., Sie, S., 2000. Design and scale-up of the FischereTropsch bubble column slurry reactor. Fuel Process. Technol. 64 (1), 73e105. Li, H., Prakash, A., 2000. Influence of slurry concentrations on bubble population and their rise velocities in a three-phase slurry bubble column. Powder Technol. 113 (1), 158e167.
K. Salehi et al. / Journal of Natural Gas Science and Engineering 21 (2014) 170e183 Maretto, C., Krishna, R., 1999. Modelling of a bubble column slurry reactor for FischereTropsch synthesis. Catal. Today 52 (2), 279e289. Rados, N., et al., 2003. Modeling of the FischereTropsch synthesis in slurry bubble column reactors. Catal. Today 79, 211e218. Rahimpour, M., 2007. A dual-catalyst bed concept for industrial methanol synthesis. Chem. Eng. Commun. 194 (12), 1638e1653. Rahimpour, M., 2008. A two-stage catalyst bed concept for conversion of carbon dioxide into methanol. Fuel Process. Technol. 89 (5), 556e566. Rahimpour, M., Elekaei, H., 2009. Enhancement of methanol production in a novel fluidized-bed hydrogen-permselective membrane reactor in the presence of catalyst deactivation. Int. J. Hydrogen Energy 34 (5), 2208e2223. Rahimpour, M., Ghader, S., 2003. Theoretical investigation of a Pd-membrane reactor for methanol synthesis. Chem. Eng. Technol. 26 (8), 902e907. Rahimpour, M., Ghader, S., 2004. Enhancement of CO conversion in a novel PdeAg membrane reactor for methanol synthesis. Chem. Eng. Process. Process Intensif. 43 (9), 1181e1188. Rahimpour, M.R., Lotfinejad, M., 2008. Co-current and countercurrent configurations for a membrane dual type methanol reactor. Chem. Eng. Technol. 31 (1), 38e57. Rahimpour, M.R., et al., 2003. Incorporation of flexibility in the design of a methanol synthesis loop in the presence of catalyst deactivation. Chem. Eng. Technol. 26 (6), 672e678. Rahimpour, M.R., et al., 2012. A novel slurry bubble column membrane reactor concept for FischereTropsch synthesis in GTL technology. Chem. Eng. Res. Des. 90 (3), 383e396.
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Rahimpour, M., et al., 2008. Application of hydrogen-permselective Pd-based membrane in an industrial single-type methanol reactor in the presence of catalyst deactivation. Fuel Process. Technol. 89 (12), 1396e1408. Rezaie, N., et al., 2005. A comparison of homogeneous and heterogeneous dynamic models for industrial methanol reactors in the presence of catalyst deactivation. Chem. Eng. Process. Process Intensif. 44 (8), 911e921. Setinc, M., Levec, J., 1999. On the kinetics of liquid-phase methanol synthesis over commercial Cu/ZnO/Al2O3 catalyst. Chem. Eng. Sci. 54 (15), 3577e3586. Setinc, M., Levec, J., 2001. Dynamics of a mixed slurry reactor for the three-phase methanol synthesis. Chem. Eng. Sci. 56 (21), 6081e6087. Shaikh, A., Al-Dahhan, M.H., 2007. A review on flow regime transition in bubble columns. Int. J. Chem. Reactor Eng. 5 (1). Van der Laan, G.P., et al., 1999. Multicomponent reaction engineering model for Fecatalyzed FischereTropsch synthesis in commercial scale slurry bubble column reactors. Chem. Eng. Sci. 54 (21), 5013e5019. Wang, J., et al., 2005. Mathematical simulations of the performance of trickle bed and slurry reactors for methanol synthesis. Comput. Chem. Eng. 29 (11), 2474e2484. Wang, T., et al., 2007. Slurry reactors for gas-to-liquid processes: a review. Ind. Eng. Chem. Res. 46 (18), 5824e5847. Wang, Y., et al., 2011. Modeling study for FischereTropsch synthesis in slurry bubble column reactors. J. Fuel Chem. Technol. 39 (12), 961e966. Wu, Y., Gidaspow, D., 2000. Hydrodynamic simulation of methanol synthesis in gaseliquid slurry bubble column reactors. Chem. Eng. Sci. 55 (3), 573e587. Zhai, X., et al., 2008. Study on the deactivation phenomena of Cu-based catalyst for methanol synthesis in slurry phase. Fuel 87 (4), 430e434.
Contents lists available at ScienceDirect
Journal of Natural Gas Science and Engineering journal homepage: www.elsevier.com/locate/jngse
Enhancement of CO conversion in a novel slurry bubble column reactor for methanol synthesis K. Salehi a, S.M. Jokar b, J. Shariati a, M. Bahmani b, M.A. Sedghamiz b, M.R. Rahimpour b, * a b
Department of Chemical Engineering, Darab Branch, Islamic Azad University, Darab, Iran Chemical Engineering Department, School of Chemical and Petroleum Engineering, Shiraz University, Shiraz 71345, Iran
a r t i c l e i n f o
a b s t r a c t
Article history: Received 17 July 2014 Received in revised form 22 July 2014 Accepted 24 July 2014 Available online
This paper is dealing with the simulation of a commercial size slurry bubble column reactor (SBCR) for catalytic conversion of synthesis gas (CO þ CO2 þ H2) to methanol and comparison of the results especially carbon monoxide removal with gas-phase model in the quasi-steady state condition. For this purpose it was assumed that the flow pattern of gas is plug, and axial dispersion model was considered for liquidesolid phase. The results of the model for Shiraz petrochemical complex feedstock show that the production rate of methanol in a commercial SBC reactor is lower than conventional gas-phase methanol synthesis. This disadvantage is corrected by the modified feed which includes 5% CO and the 95% of the conventional feed. This novelty results in the same methanol production rate with the conventional gas-phase reactor. Besides the same methanol production rate, CO injection to the feed, causes water production noticeably reduced during methanol synthesis via CO2 hydrogenation. Consequently lower catalyst deactivation rate and higher methanol production rate are achieved. © 2014 Elsevier B.V. All rights reserved.
Keywords: Methanol Slurry-bubble column reactor Conventional methanol process Single-type reactor Catalyst deactivation Quasi-steady state
1. Introduction Due to its physical and chemical characteristics, methanol is a cheap and clean liquid alternative fuel and the starting chemical for formaldehyde and other solvents production. Methanol use in current-technology vehicles has some distinct advantages and disadvantages. Positive point is, methanol has a higher octane rating than gasoline. This reduces “knock” in the modern engines and can enhance fuel efficiency by adjusting the engine's compression ratio. Methanol high heat of vaporization results in lower peak flame temperatures than gasoline and lower nitrogen oxide emissions. However, energy density of methanol is approximately half of the one for gasoline that reduces the range a vehicle can travel on an equivalent tank of fuel. Methanol can be produced from the widely available materials such as coal and natural gas as well as biomass, and there is a potential to introduce methanol as a low cost and nature-friendly fuel. Conventionally, methanol is produced in gas-phase systems (in conventional fixed bed reactors) from a feedstock consisting of CO/CO2/H2 over a CuO/ZnO/Al2O3 catalyst. Generally, the potential drawbacks of industrial packed bed methanol reactors are pressure drop across the reactor, poor
* Corresponding author. Tel.: þ98 711 2303071; fax: þ98 711 6287294. E-mail address: [email protected] (M.R. Rahimpour). http://dx.doi.org/10.1016/j.jngse.2014.07.030 1875-5100/© 2014 Elsevier B.V. All rights reserved.
heat transfer rate, low production capacity and low catalyst particle effectiveness factors because of severe diffusional limitations for catalyst particle sizes used. Smaller particle sizes are infeasible in fixed-bed systems because of pressure drop considerations. In order to avoid serious pressure drop, the effective diameter of catalyst particles in fixed-bed reactor is usually over 3 mm, which brings a certain inner mass transfer resistance. Also, the factors affecting the production rate in industrial methanol reactors are parameters such as thermodynamic equilibrium limitations, catalyst deactivation and variation in stoichiometric proportion. Since methanol o synthesis is a high exothermic reaction ðDH298 ¼ 90:97 kJ mol1 Þ, and the conversion of the synthesis gas (CO þ H2) must be controlled at a low level in order to avoid possible overheating of the catalyst bed, the economic efficiency of the traditional gas phase methanol synthesis is unsatisfied (Wang et al., 2005; Rahimpour et al., 2008; Zhai et al., 2008; Rahimpour and Elekaei, 2009). Many research works have been accomplished for improving gas phase systems. For instance, Rahimpour and Ghader (2003, 2004) investigated the PdeAg membrane reactors performance for methanol synthesis, Rahimpour et al. (2003) and Rahimpour (2007) have presented strategies to enhance the ability of methanol synthesis reactor using a mixture of fresh and partially deactivated catalyst, Rahimpour (2008) proposed a two-stage catalyst bed reactor with high temperature in the first bed and low
K. Salehi et al. / Journal of Natural Gas Science and Engineering 21 (2014) 170e183
temperature in the second bed to enhance the reactor performance and finally Rahimpour and Lotfinejad (2008) presented dynamic model for studying PdeAg membrane in a dual-type reactor and showed that methanol production can be increased in membrane dual-type reactor. Also to overcome the problems associated with gas-phase systems, many reactor designs such as SBCRs and trickle bed reactors (TBRs) have been proposed (Zhai et al., 2008). In the late 1970s the liquid phase methanol synthesis was introduced in order to utilize CO-rich syngas from coal gasification. American Air products and Chemicals exploited the three phase SBCRs for methanol synthesis with CuO/ZnO/Al2O3 catalyst in the 1980s and built an industrial demonstration plant in 1997, which showed economic advantages (Maretto and Krishna, 1999; Van der Laan et al., 1999; Krishna and Sie, 2000; Li and Prakash, 2000; Wu and Gidaspow, 2000; Setinc and Levec, 2001; Rados et al., 2003; Zhai et al., 2008; Wang et al., 2011; Rahimpour et al., 2012). The liquid phase is used to absorb the heat released during the reaction. In general, SBCRs are preferred for fast and highly exothermic reactions. Since they provide some advantages such as better catalyst utilization (the size of catalyst particles ranges from 5 to 150 mm and solid loading ranges up to 50% volume), good heat and mass transfer characteristics due to the good interface contacting and high level of back mixing, usually no moving parts, ease of operation, low operating and maintenance costs, nearly isothermal operation and low pressure drop (Setinc and Levec, 1999, 2001; Shaikh and Al-Dahhan, 2007; Wang et al., 2007). Early SBCR models were reviewed by Ramachandran and Chaudhari, Deckwer and Fan (Gamwo et al., 2003). They required holdup correlations as an input and did not compute flow patterns. One of the best models applied for the FischereTropsch (FeT) conversion of syngas in an SBCR is that of Prakash and Bendale which gave syngas conversion and production as a function of temperature, pressure and space velocity. Input parameters with considerable uncertainty that influenced production rates were the gas holdup, the mass transfer coefficient and the dispersion coefficient. Van der Laan et al. extended such a model to compute product distribution using a product selectivity model. Degaleesan et al. measured dispersion coefficient needed as an input for a model like this (Gamwo et al., 2003). Wu and Gidaspow (2000) proposed a transient, two-dimensional hydrodynamic model for the production of methanol in SBCRs. Their model predicted down flow of catalyst at the walls and oscillatory particle and gas flow at the center (Wu and Gidaspow, 2000). Gamwo et al. (2003) proposed two Computational Fluid Dynamics (CFD) models; first model based on the kinetic theory of granular flow and the second one was based on the catalyst viscosity as an input. In SBC reactors, the phase back-mixing has been historically modeled using one of the two limiting ideal flow reactors; completely stirred tank or plug flow reactor. More recently, the phase back-mixing is modeled using the axial dispersion model (ADM) or the multi-cell model (MCM). Schluter et al. using a numerical simulation found the predictions of the ADM and MCM models to be similar (Rados et al., 2003). A new key issue which is recently reported for SBCRs is that the water produced during methanol synthesis via CO2 hydrogenation greatly reduces methanol synthesis rate by suppressing reaction. Water produced during methanol synthesis from CO2 conversion accelerates the crystallization of Cu and ZnO contained in a Cu/ZnObased catalyst to lead the deactivation of the catalyst. On the other hand, the catalyst is only slightly deactivated during methanol synthesis through a higher CO conversion, since only a small amount of water is produced during the reaction, and no
171
remarkable crystallization of Cu and ZnO occurred in the catalyst (Rahimpour and Ghader, 2003). One potential novel concept is injecting CO to the feed to improve methanol production rate and lower catalyst deactivation rate. In this study a one dimensional model with plug flow pattern for gas and axial dispersion model for liquidesolid suspension as a homogeneous phase was suggested for SBC reactor and mass balance equations were applied for two phases. Also it was assumed that the total heat of reaction which was produced in the process was subsequently removed. We considered quasisteady-state model simpler than dynamic model for simulation of an SBC reactor which was placed theoretically for conventional methanol reactor of Shiraz Petrochemical Complex and numerical simulation was utilized to compare results of novel SBC reactor with conventional gas-phase reactor. The effect of CO injection to the feed on the methanol production rate was also investigated. 2. Reactor configurations 2.1. Single type gas-phase reactor Fig. 1 shows the schematic diagram of a single-type methanol reactor. This reactor type is based on a vertical shell and tube heat exchanger. The catalyst is packed in vertical tubes and surrounded by the boiling water. The technical design data of the catalyst pellet and input data of the gas-phase methanol reactor are summarized in Tables 1 and 2 (Rahimpour and Lotfinejad, 2008). 2.2. Liquid-phase (SBC) reactor Fig. 2 shows a schematic diagram of a slurry bubble column reactor for methanol synthesis. Liquid phase contains an inert liquid such as paraffin oil, paraffin wax, decahydronaphthalene, tetrahydronaphthalene and etc. to absorb the heat of reaction and transfer the catalyst particles which disperse in liquid, and gas bubbles which go upward through liquid. Mass transfer is occurred between gas bubbleseliquidesolid particles and reaction is accomplished on the particles surfaces (Wu and Gidaspow, 2000; Gamwo et al., 2003; Wang et al., 2007). 3. Reaction scheme and kinetics for gas and slurry phase methods The syngas required for methanol synthesis contains CO2/CO/H2 and the following reactions occur on the catalyst surface (Rahimpour, 2008) in both gas and slurry method.
CO þ 2H2 4CH3 OH; CO2 þ H2 4CO þ H2 O;
DH ¼ 90 kJ=mol DH ¼ 412 kJ=mol
CO2 þ 3H2 4CH3 OH þ H2 ;
DH ¼ 49:2 kJ=mol
(1)
(2) (3)
The kinetics of low-pressure methanol synthesis (in gas-phase reactors) over commercial CuO/ZnO/Al2O3 catalyst has been widely investigated. Graaf et al. kinetic model, which includes hydrogenation of CO, CO2 and the reversed wateregas shift reactions is commonly used. The correspondent rate expressions for the hydrogenation of CO, CO2 and reversed wateregas shift reactions are (Rezaie et al., 2005):
172
K. Salehi et al. / Journal of Natural Gas Science and Engineering 21 (2014) 170e183
Fig. 1. A schematic diagram of a conventional single-type methanol synthesis loop.
2
3
3 fCH OH 7 6 k1 KCO 4fCO fH22 3 5
=
1 2
=
fH KP1 2
(4)
=
1 þ KCO fCO þ KCO2 fCO2
3 2 12 KH2 O 4f þ fH O 5 H2
1
=
r1 ¼
KH2
2
2
2
3
3 fCH OH fH O 7 6 k2 KCO 4fCO fH22 3 2 5
=
3
=
2
(5)
=
1 þ KCO fCO þ KCO2 fCO2
3 2 12 4f þ KH2 O fH O 5 H2
1
=
r2 ¼
fH2 KP2
KH2
2
2
fCO fH O k3 KCO2 fCO2 fH2 ðKP32Þ 3 2 r3 ¼ 12 KH2 O fH2 O 5 1 þ KCO fCO þ KCO2 fCO2 4fH2 þ
(6)
=
1
=
KH2
2
The reaction rate constants, adsorption equilibrium constants and reaction equilibrium constants in the kinetic expressions are tabulated in Tables 3e5 (Rezaie et al., 2005). Few studies have been published concerning the liquid phase process, in comparison to numerous papers for the gas phase methanol synthesis. Results show clearly the disagreement between the reported kinetic equations for two processes.
This phenomenon may be due to the presence of the liquid phase. The presence of liquid assures that in spite of gas phase, all active sites are at the same temperature in liquid phase. Setinc and Levec (1999) showed that most of the kinetic models of methanol synthesis have been developed for CO rich feed stocks, they satisfactorily matched their experimental data, while at very low CO2 concentrations (or very low CO2/(CO2 þ CO) ratio) these models failed completely. These models are also capable of predicting the decrease of the methanol production rate due to the water absorption on the catalyst surface as CO2 concentration increases (Graaf et al., 1988; Setinc and Levec, 1999). Therefore a relatively low CO2/CO ratio is used in the three-phase synthesis and water production can be neglected (Setinc and Levec, 1999). In this study the kinetic equation of Von Wededel et al. (Setinc and Levec, 1999) considering methanol synthesis only via CO conversion was applied in the reactor simulation. Equations (7) and (8) represent Von Wedel kinetic model (Setinc and Levec, 1999):
99; 360 0:4 0:18 cH2 cCO 6:8793 rCH3 OH ¼ 4:9409 1012 exp Rg T 107; 500 0:13 cCH3 OH 1012 exp Rg T (7)
Table 2 Specifications of synthesis gas. Feed
Table 1 Catalyst and reactor specifications for gas phase reactor. Parameter
Value
Unit
rS
1770 5.47 103 5 0.004 626.98 0.123 2962 7.022
[kg m3] [m] [kJ kg1 K1] [W m1 K1] [m2 m3] [e] [e] [m]
dP cpS
lC
aV 3 S/t Number of tubes Tube length
Composition (mole %) CH3OH CO2 CO H2O H2 N2 CH4 Total molar flow rate per tube Pressure Inlet temperature (K)
Value 0.50 9.40 4.60 0.04 65.90 9.30 10.26 0.64 76.98 503
Unit [e] [e] [e] [e] [e] [e] [e] [mole s1] [bar] [K]
K. Salehi et al. / Journal of Natural Gas Science and Engineering 21 (2014) 170e183
173
Fig. 2. Hydrodynamic of a slurry reactor for methanol synthesis.
Table 3 Reaction rate constants (Rezaie et al., 2005).
av hf ðT Ts Þ þ rB a
k ¼ A expðB=ðRg TÞÞ
A
B
k1 k2 k3
(4.89 ± 0.29) 107 (1.09 ± 0.07) 105 (9.64 ± 7.3) 1011
113,000 ± 300 87,500 ± 300 152,900 ± 11,800
4.1. Conventional gas-phase reactor In the gas-phase methanol synthesis at the quasi-steady state conditions, the balances are typically for convection and transport to the solid-phase. The mass and energy balances for the solid phase are expressed by Rezaie et al. (2005) and Rahimpour and Lotfinejad (2008):
i ¼ 1; 2; 3; …; N 1
(9)
Table 4 Adsorption equilibrium constants (Rezaie et al., 2005).
KCO KCO2 1 KH2 O =KH22
(10)
where yis and Ts are the solid-phase mole fraction and temperature, respectively. The following two conversion equations are written for the fluid phase (Rezaie et al., 2005):
(8)
4. Model equations for quasi-steady state conditions
K ¼ A expðB=ðRg TÞÞ
hri DHf;i ¼ 0
i¼1
rH2 ¼ 2rCH3 OH and rCO ¼ rCH3 OH
kgi ðyi yis Þ þ hri rB a ¼ 0;
N X
A 5
(2.16 ± 0.44) 10 (7.05 ± 1.39) 107 (6.37 ± 2.88) 109
Ft dyi þ av ct kgi ðyis yi Þ ¼ 0 AC dz
(11)
Ft dT pDi þ av hf ðTs TÞ þ U ðT TÞ ¼ 0 cpg dz AC AC shell shell
(12)
Catalyst deactivation model for commercial methanol synthesis has been adopted from Hanken (Rezaie et al., 2005; Rahimpour, 2008), where TR, Ed and Kd are the reference temperature, activation energy and deactivation constant of catalyst, with the numerical values of 513 K, 91,270 J mol1 and Kd, 0.00439 h1 respectively.
Table 5 Reaction equilibrium constants (Rezaie et al., 2005). B
kP ¼ 10ððA=TÞBÞ
A
B
46,800 ± 800 61,700 ± 800 84,000 ± 1400
KP1 KP2 KP3
5139 3066 2073
12.621 10.592 2.029
=
174
K. Salehi et al. / Journal of Natural Gas Science and Engineering 21 (2014) 170e183
Table 6 Coefficients for Henry's constant evaluation.
Hydrogen Carbon monoxide Carbon dioxide Methanol Water
Table 9 Specifications of synthesis gas and reactor design for slurry and gas phase reactor.
a (bar mol1)
b (J mol1)
Feed
78.192 109.87 429.52 8190.6 7936.7
2854.0 939.7 8969.5 30,410 37,421
Composition (mole%) CH3OH CO2 CO H2O H2 N2 CH4
0.5 9.4 4.6 0.04 65.9 9.3 10.26
Total molar flow rate Inlet temperature Inlet pressure Reactor diameter Slurry height
1895.68 523 53 3 7
Table 7 Input data of slurry reactor simulation (Wu and Gidaspow, 2000). Feed composition
Value (mole%)
CH3OH CO2 CO H2 N2
0.0 13 51 35 1
Total molar flow rate Pressure Inlet temperature
Unit [e] [e] [e] [e] [e] [mole s1] [bar] [K]
47.86 53 523
da Ed 1 1 ¼ Kd exp a5 dt Rg T TR
(13)
4. 5.
6.
Initial condition for this ordinary differential equation is: at t ¼ 0, a ¼ 1. 4.2. Slurry bubble-column reactor SBCRs can operate either in the homogeneous or heterogeneous (churn-turbulent) flow regime. In the homogeneous regime, the gas flow rate is low, and small bubbles of gas (1e10 mm) are uniformly distributed into the slurry phase (liquid þ catalyst particles). In the heterogeneous regime some small bubbles combine in clusters to form large bubbles (20e70 mm). These large bubbles travel up through the column at high velocities (1e2 m/s) and have the effect of churning up the slurry phase, while small bubbles are entrained in the slurry phase and as a good approximation have the same back-mixing characteristic of the slurry phase (Behkish et al., 2002; De Swart and Krishna, 2002). However the modeling of a slurry bubble column reactor for methanol synthesis in this study is based on the following assumptions. 1. The plug flow model has been assumed for the gas phase and so the diffusional term in comparison with convection term in mass balance equation has been neglected. 2. The slurry phase is modeled by an axial dispersion model. 3. Due to the very small particle size of catalysts, the effectiveness factor is taken as unity and the liquidesolid mass transfer Table 8 Comparison between the simulation results and Air Products' (1991) RUN E-8.1.
CO conv. (%) Superficial gas velocity (m/s) Gas holdup (%) Reactor diameter (m) Slurry height (m) Solid holdup (%) Total catalyst (g) CH3OH (tons/day) Errora % a
jCH3 OHRun CH3 OHSimu: j CH3 OHRun
100.
Simulation
RUN E-8.1
15.8 0.15 29.5 0.57 5.08 26.8 567
13.5 0.15 29.5 0.57 5.08 26.8 567
10.6 18.7
8.93 e
7.
Value
Unit [e] [e] [e] [e] [e] [e] [e] mol s1 K bar m m
resistance is neglected. Therefore liquid and solid phase is a homogeneous phase which reaction occurs in this phase. The model assumes isothermal conditions within the reactor and catalyst particles. Methanol synthesis occurs just through CO hydrogenation and water gas shift reaction is in the dynamic equilibrium (Wang et al., 2005). The deactivation of the catalyst in a slurry phase methanol synthesis is still a problem for commercialization. The experimental results of X. Zhai et al. indicated that Cu composition of catalyst had not changed significantly during the reaction, and sintering of Cu particles of the catalyst was the main reason of the deactivation. This deactivation procedure has been affected by the time on stream and the temperatures at which sintering may occur that directly related to the melting temperature (Zhai et al., 2008). In this work, the deactivation of catalyst particles is considered the same as of the gas phase methanol synthesis which depends on temperature only. Pressure along the reactor length is not constant and pressure drop is calculated according to the following relation (Li and Prakash, 2000):
DP ¼ rg 3 g þ rl 3 l þ rs 3 s gDz
(14)
Based on the above assumptions, the mass balances are applied over a differential element of reactor at steady state conditions as following equations: For gas phase:
dUg Ci;g ðkl aÞi c*i;l ci;l ¼ 0 dz
(15)
And for liquid phase: Table 10 The comparison of methanol production rate in industrial plant, gas phase model and slurry phase model. Time (day)
Plant (tons/day)
Gas-phase model (tons/day)
Slurry-phase model (tons/day)
0 100 200 300 400 500 600 700 800 900 1000 1100 1200
295.0 296.5 302.6 284.3 277.9 278.2 253.0 274.0 268.1 275.5 274.6 262.9 255.2
308.8 297.03 289.1 283.09 278.19 274.03 270.41 267.19 264.3 261.67 259.25 257.02 255.18
195.7854 161.6251 150.9195 144.1356 139.1529 135.2063 131.9565 129.1920 126.7891 124.666 122.7657 121.0471 119.4794
K. Salehi et al. / Journal of Natural Gas Science and Engineering 21 (2014) 170e183
175
(b)
(a)
(c)
(d)
(e)
Fig. 3. Comparison of species (a) methanol, (b) CO2, (c) CO, (d) H2, (e) H2O mole fractions along the reactor axis between the conventional reactor, and the slurry reactor at the same conditions.
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3 l El
d2 ci;l dz2
dUss ci;l þ ðkl aÞi c*i;l ci;l ahri Cs ¼ 0 dz
(16)
The solubility of each species in liquid (in this work Squalane, C30H62) is calculated using Henry's law:
c*i;l ¼
Pi Hei
(17)
where Pi is a partial pressure of species i, in the gas phase and the numerical values of Henry's constant for H2, CO, CO2 and CH3OH in Squalane are tabulated in Table 6 (Setinc and Levec, 1999). Energy balance for entire system is:
3 sl lax
Fig. 4. Methanol production rate at time zero versus percentage of CO injected to the feed.
X v2 T A DH aeff Heat ðT Tsat:water Þ ¼ 0 þ 3 s rs ahr i f i ACS vz2 (18)
It was assumed that the slurry temperature is uniform along the reactor due to the high suspension heat conductivity lax.
(a)
(b)
(c)
(d)
Fig. 5. Comparison of (a) methanol, (b) CO2, (c) CO and (d) H2 mole fractions along the reactor axis between the conventional reactor with the main feed composition and the slurry reactor in the case of 5% CO injection to 95% of the feed.
K. Salehi et al. / Journal of Natural Gas Science and Engineering 21 (2014) 170e183
(a)
177
(b)
Fig. 6. Comparison of (a) CO and (b) H2 conversions along the reactor length in the cases of the conventional feed and 5% CO injection to 95% of conventional feed.
According to the assumption 6, approximate catalyst activation “a” can be calculated at any time by Hanken model (equation (13)). 5. Numerical solution The governing equations of slurry reactor model are solved at quasi-steady-state conditions. To solve this set of equations, reactor is divided into 100 separate sections and forward finite difference approximation is applied. This procedure replaces the differential equations by a non-linear algebraic set of equations and the NewtoneRaphson method is used to solve these set of equations in each section. Gas-phase and slurry-phase reactor outputs have been compared by Rezaie et al. (2005). 6. Results and discussion 6.1. Model validation for slurry reactor Model validation is carried out by simulation of Air Products' (1991) RUN E-8 series for methanol synthesis (Wu and Gidaspow, 2000). Feed composition and flow rate are tabulated in Table 7, the technical design specifications of Air Products' reactor and the results of this simulation at time zero (activation is unity) which is within the error bounds of the model LaPort's RUN E-8.1 are shown in Table 8. This systematic error is based on the kinetic equation as shown by Setinc and Levec (1999). It should be noted, all of data in this work will include this error. 6.2. Model validation of proposed slurry reactor and gas-phase for methanol synthesis in Shiraz petrochemical complex feedstock Model validation of slurry reactor was carried out by comparison of the conventional process data with model results under the design specifications of slurry methanol synthesis reactor of Air Product but with the reactor size and input data of Shiraz Petrochemical Complex reactor (Tables 8 and 9). Table 10 shows the methanol production rate of plant, gas phase and slurry reactor models respectively. The results of slurry reactor
model and Rezaie et al. model (Rezaie et al., 2005) are illustrated in Fig. 3(a)e(d). Results clearly show that, because of low methanol production rate due to the high (CO2/CO2 þ CO) ratio, slurry reactor is not suitable for this feed. Fig. 3(a) shows the lower methanol mole fraction in the slurry bubble reactor rather than the conventional gas-phase reactor in the case of the same feed composition. While the methanol mole fraction decreased in the slurry reactor, Fig. 3(b) and (d) shows that CO2 and H2 mole fraction increased through the reactor. Since the water mole fraction increased in the slurry bubble reactor than the conventional reactor for the same feed composition, as shown in Fig. 3(e), the crystallization of active metal species on the catalyst basis would be increased and the catalyst activity decreased. Next step contains the change in feed composition by adding additional CO to the feed under the condition of constant flow rate of the main feed and CO injection flow rate. This change increases the conversion of gas phase due to the higher inlet superficial velocity (Maretto and Krishna, 1999). Fig. 4 illustrates the methanol production rate in the presence of CO injection condition from 0% to 10% of conventional feed. As shown in Fig. 4, if the SBCR entrance feed approximately equals 95% of the main feed and 5% of CO injected, production rate of methanol will be the same as conventional system. As it can be seen from Fig. 4, larger amount of CO% injection leads higher amount of methanol production, according to the lower water production from CO2 hydrogenation. Since the methanol production rate increased by higher CO% injection, catalyst activity reduces through the pollutant specification of CO. As a result the optimum CO% injection must be considered in order to achieve the desired amount of the methanol production rate. Fig. 5(a)e(d) shows the comparison of species CH3OH, CO, CO2 and H2 mole fractions in conventional gas-phase and slurry methanol synthesis in the case of 5% CO injection. As mentioned above, þ17.8% errors in the results of slurry reactor should be considered. Fig. 5(a) shows the positive effect of CO injection on the increasing of the methanol production rate based on the higher
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catalyst activity in the presence of the lower water production rate, also Fig. 5(b) represents the grow up trend for CO2 mole fraction based on the same reason. Figs. 6(a) and (b) and 7(a)e(d) show the comparison of CO and H2 conversion and CH3OH, CO2, CO and H2 mole fraction in the case of the conventional feed and 5% CO injection to the 95% of feed respectively. Fig. 6(b) shows that the 5% of injected CO to the conventional feed results in higher value of H2 conversion and lower one for H2 mole fraction, as illustrated in Fig. 7(d). Fig. 6(a) shows that, the CO conversion in the case of 5% of injected gas is lower than conventional feed. While the excess amount of CO injected to the reactor, higher methanol mole fraction achieved, as shown in Fig. 7(a), according to the higher catalyst activity and lower water production rate and the amount of unreacted CO also increases in the reactor, so the CO conversion decreases and the CO mole fraction increases as it can be clearly seen in Fig. 7(c). Fig. 8(a) and (b) reveals the methanol production rate along the reactor length and methanol production rate with time in both
cases. Fig. 9 shows the comparison of the catalyst activity in the conventional and SBC reactors with time. Fig. 8(a) reveals that the methanol production rate increases thorough the reactor at the specific time interval, also Fig. 8(b) shows that the time has the negative effect on the methanol production rate. As it can be seen from Fig. 9, the catalyst activity decreases by passing the time, this dropping trend is based on the two deactivation phenomenon. The prior is the sintering in the case of high temperature and the latter is the fouling in the presence of pollutant such as higher amount of CO, so the methanol production rate and the catalyst activity decrease by the time. It can be seen from Fig. 9 that, activity of catalyst in the presence of 5% of injected CO is higher than the conventional feed. This behavior is also related to the noticeably decreasing in the water production rate through CO2 hydrogenation in the slurry reactor with higher CO/(CO þ CO2) ratio and consequently lower catalyst crystallization. In Fig. 10, the methanol production rate at three different temperatures in the case of 5% CO injection to 95% of conventional feed
(a)
(b)
(c)
(d)
Fig. 7. Comparison of (a) CH3OH, (b) CO2, (c) CO and (d) H2 mole fraction in the cases of the conventional feed and 5% CO injection to 95% of conventional feed.
K. Salehi et al. / Journal of Natural Gas Science and Engineering 21 (2014) 170e183
(a)
179
(b)
Fig. 8. Comparison of methanol production rate (a) along the reactor length at time zero and (b) respect to time with the conventional feed and 5% CO injection to 95% of the conventional feed.
along the reactor length and time is shown. Higher temperature, increases the equilibrium constant of methanol synthesis reaction, but sintering as a source of catalyst deactivation also increases by temperature, so an optimum condition must be considered. Fig. 11(a)e(g) shows three dimensional plots of CO and H2 conversion, CO, CO2, H2 and CH3OH mole fractions and methanol production rate along the reactor length and time in the case of 5% CO injection to 95% of conventional feed. Fig. 11(a) and (b) shows that the maximum conversion of CO and H2 has been occurred at the start time, according to the higher catalyst activity, and the exit coordinate of the reactor.
Consequently CO and H2 mole fraction are vice versa, as shown in Fig. 11(c) and (f). Methanol mole fraction and the methanol production rate are the function of catalyst activity. At the time zero, the catalyst activity is maximum, so the methanol production rate, Fig. 11(g), and methanol mole fraction, Fig. 11(e), hit the maximum at time zero and the exterior interval of the reactor. Figs. 12 and 13 illustrate the comparison between CO removal in conventional gas phase reactor, slurry reactor with the conventional feed and the slurry reactor with 5% of CO injection to the feed versus the reactor length and the time respectively.
Fig. 9. Comparison of catalyst activity in conventional an SBC reactors with time.
Fig. 10. Effect of temperature on the methanol production rate with time.
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K. Salehi et al. / Journal of Natural Gas Science and Engineering 21 (2014) 170e183
Fig. 11. Three dimensional plots of (a) CO and (b) H2 conversion, (c) CO,(d) CO2, (e) H2 and (f) CH3OH mole fraction and (g) methanol production rate along the reactor length and time in the case of 5% CO injection to 95% of conventional feed.
Fig. 12 illustrates that the value of CO removal in the slurry reactor is higher than the conventional reactor. In addition, when the feed composition in the slurry reactor changes by addition of 5% of CO injection, final CO removal increased by 200%, from 150 tones per day to a little higher than 300 tones per day. This noticeably increasing in CO removal is regarding to the lower deactivation rate based on the lower water production rate among the slurry reactor, as shown in Fig. 9. Since the catalyst activity has been decreased by the time, according to the sintering and fouling procedures, the CO removal shows the falling trend in Fig. 13. It can be clearly seen that, however the CO removal in the slurry reactor with the modified feed composition is larger than the one in the slurry reactor with the conventional feed and also the conventional gas-phase reactor.
7. Conclusion Results clearly show that slurry bubble reactor for methanol synthesis, is not suitable for common feedstock of Shiraz Petrochemical Company, regarding to its high feed ratio of CO2/ (CO2 þ CO) which causes to reduce the methanol production rate in proposed reactor model in comparison to conventional gas phase process. Many researches, reported that in the slurry bubble reactor, methanol synthesis occurs through CO hydrogenation only, and therefore low value of CO2/(CO2 þ CO) ratio should be applied. As a result in conventional feedstock such as Shiraz Petrochemical feedstock, CO should be injected to the feed in order to reduce the ratio of CO2/(CO2 þ CO). In this study by injecting 5% CO to 95% of
Fig. 12. The comparison of CO removal along the rector length in the conventional gas phase reactor, slurry reactor with conventional feed and slurry reactor with 5% CO injection to the feed along.
K. Salehi et al. / Journal of Natural Gas Science and Engineering 21 (2014) 170e183
181
And the diffusivity of component i in the gas mixture and in the binary systems is as:
1y Dim ¼ PN yi
(A-4)
i
j¼i Dij
vffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi u , Mi þ 1 M j 3 2 3 p yci2 þ ycj2
3 u 107 T 2 t1
=
(A-5)
=
=
Dij ¼
kl a ¼ 0:18Sc0:6
rL vA MB
2:84
rg Ug
0:49
e2:66CV
(A-6)
And the axial dispersion coefficient of the liquid phase is calculated using the relation proposed by Deckwer et al. (De Swart and Krishna, 2002):
El ¼ 0:768Ug0:32 D1:34 T
Fig. 13. The comparison of CO removal with time in the conventional gas phase reactor, slurry reactor with conventional feed and slurry reactor with 5% CO injection to the feed.
conventional feed, it can be seen that methanol production rate is the same that of the gas phase system. By CO injection to the feed, water has been produced during methanol synthesis via CO2 hydrogenation which accelerates the catalyst deactivation and reduces methanol production rate dramatically. CO is an important cause of pollution and a hazardous material in many industrial processes work with catalysts, which must be removed anyway and this method can be used in this case. Results showed that the methanol production rate has been increased by increasing the temperature while the catalyst deactivation rate also showed the upward trend based on the sintering phenomenon. Appendix A. Auxiliary correlations To complete the simulation, auxiliary correlations should be added to the model. The main auxiliary correlations encountered in the formulation of a slurry bubble column reactor are mass and heat transfer.
(A-7)
A.2. Heat transfer correlations The overall heat transfer coefficient Ushell and aeff in gas phase and liquid phase methanol synthesis respectively are estimated using the relations (A-8) (Rezaie et al., 2005) and (A-11) (De Swart and Krishna, 2002)
1 1 ¼ þ Ushell hi
Ai ln Do=D i 2pLKw
þ
Ai 1 Ao ho
(A-8)
hi is the heat transfer coefficient between the gas phase in the tube side and reactor wall and is obtained by the correlation (A-9) and ho is the heat transfer coefficient of boiling water in the shell side which is estimated by equation (A-10).
0:407 hi cp m2=3 0:458 rug dp ¼ cp rm K 3B m ho ¼ 7:96ðT Tsat Þ3
p pa
(A-9)
0:4
U3r g sl ¼ 0:1 rsl cpsl Ug ghsl
(A-10) !14
rsl cpsl lsl
1 2
A.1. Mass transfer correlations
aeff
In the current work, mass transfer coefficient for the components in gas-phase is as equation (A-1) (Rezaie et al., 2005) and the volumetric mass transfer coefficient of species i, in the liquid side of gaseliquid interface in slurry reactor is calculated using the equation of Behkish et al. (equation (A-6)) (Behkish et al., 2002):
For superficial gas velocities exceeding 0.1 m/s the heat transfer coefficient is to be calculated from above equation by taking Ug equal to 0.1 m/s. Parameters in the above equation are defined as (De Swart and Krishna, 2002):
kgi ¼ 1:17Re0:42 Sc0:67 ug 103 i
(A-1)
where the Reynolds and Schmidt numbers have been defined as:
2Rp ug Re ¼ m Sci ¼
m rDim 104
(A-11)
rsL ¼ cs rp þ ð1 cs ÞrL
(A-12)
cpsL ¼ Ws cps þ ð1 Wc ÞcpL
(A-13)
cs rp
cs rp rL þ rL
(A-2)
Wc ¼
(A-3)
hsL ¼ hL ð1 þ 4:5cs Þ
(A-14)
(A-15)
182
lsL ¼ lL
K. Salehi et al. / Journal of Natural Gas Science and Engineering 21 (2014) 170e183
2lL þ lp 2cs lL lp 2lL þ lp þ cs lL lp
lax ¼ EL cpsL rsL
Pa
(A-16)
(A-17)
where all parameters are defined in Appendix B. Appendix B. Symbols a av AC ACS AHeat cCO cCO2 cH2 ci,g ci,l cpg cps cpsl cs Cs ct CV DAB Dij Dim DT Ed El fi Ft ho hi Ht DHfi He kla k1 k2 k3 kgi K Kd Ki Kpi Kw L MB N P
activity of catalyst specific surface area of catalyst pellet (m2 m3) cross sectional area of each tube in gas phase reactor (m2) cross sectional area of slurry tank without coolant tubes heat transfer area in slurry reactor (m2) concentration of CO in liquid (mol l1) concentration of CO2 in liquid (mol l1) concentration of H2 in liquid (mol l1) concentration of i, in gas phase (mol m3) concentration of i, in liquid phase (mol m3) specific heat of the gas at constant pressure (J mol1) specific heat of the solid at constant pressure (J mol1) heat capacity of the liquidesolid suspension (J kg1 K1) catalyst concentration in the liquid solid suspension (m3 m3) catalyst concentration in the liquid solid suspension (kg m3) total gas concentration (mol m3) volumetric solid concentration in slurry (m3 m3) diffusion coefficient of component i in liquid (m2 s1) binary diffusion coefficient of component i in j (m2 s1) diffusion coefficient of component i in the mixture (m2 s1) reactor diameter (m) activation energy used in the deactivation model (J mol1) dispersion coefficient of liquid (m2 s1) partial fugacity of component i (bar) total molar flow rate per tube (mole s1) heat transfer coefficient between coolant stream and reactor wall (W m2 K1) heat transfer coefficient between fluid phase and reactor wall (W m2 K1) reactor height (m) enthalpy of formation of component i (J mol1) Henry's constant (bar mol1 l) volumetric mass transfer coefficient of i, in liquid side of gaseliquid interface (s1) reaction rate constant for the 1st rate equation (mol kg1 s1 bar1) reaction rate constant for the 2nd rate equation (mol kg1 s1 bar1) reaction rate constant for the 3rd rate equation (mol kg1 s1 bar1) mass transfer coefficient for component i (m s1) conductivity of fluid phase (W m1 K1) deactivation model parameter constant (h1) adsorption equilibrium constant for component i (bar1) equilibrium constant based on partial pressure for component i thermal conductivity of reactor wall (W m1 K1) length of reactor (m) molecular weight of liquid (kg kmol1) number of components total pressure (bar)
DP r Rg Rp Re Sc Sci t T TR Ts Tsat Tshell u Ug Ushell
yA yi yis Wc z
atmospheric pressure (bar) pressure drop (Pa) reaction rate in slurry phase (mol kg1 h1) universal gas constant (J mol1 K1) particle diameter (m) Reynolds number Schmidt number (n/DAB) Schmidt number of component i time (s) temperature within reactor (K) a reference temperature for activity estimation (K) temperature of solid phase (K) saturated temperature of boiling water at operating pressure (K) temperature of coolant stream (K) linear velocity of gas phase in gas phase methanol reactor (m s1) superficial gas velocity in slurry reactor (m s1) overall heat transfer coefficient between coolant and process streams in gas phase model (W m2 K1) solute molar volume (m3 kmol1) mole fraction of component i in fluid phase (mol mol1) mole fraction of component i in solid phase (mol mol1) catalyst weight fraction in suspension axial reactor coordinate (m)
Greek letters void fraction of catalytic bed 3g gas holdup 3L liquid holdup 3s void fraction of catalyst h catalyst effectiveness factor lax suspension effective axial heat conductivity (W m1 K1) lc thermal conductivity of catalyst (W m1 K1) ll thermal conductivity of liquid (W m1 K1) lsl thermal conductivity of liquidesolid suspension (W m1 K1) m viscosity of fluid phase (kg m1 s1) n stoichiometric coefficient in gas phase correlations n kinematic viscosity (m2 s1) r density of fluid phase (kg m3) rB density of catalytic bed (kg m3) rL liquid density (kg m3) rg gas density (kg m3) rs density of catalyst (kg m3) rsl density of the liquidesolid suspension (kg m3) t tortuosity of catalyst aeff overall heat transfer coefficient between coolant and process streams in slurry phase model (W m2 s1) hsl viscosity of the liquidesolid suspension (kg m1 s1) 3B
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