Experimental and CFD Investigations of Light Alkane

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Experimental and CFD Investigations of Light Alkane Dehydrogenation in a Fluidized Bed Reactor Yupeng Du, Abdallah S Berrouk, Lejing Sun, Weizhen Sun, Deren Fang, and Wanzhong Ren Energy Fuels, Just Accepted Manuscript • DOI: 10.1021/acs.energyfuels.9b00474 • Publication Date (Web): 03 Apr 2019 Downloaded from http://pubs.acs.org on April 5, 2019

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Experimental and CFD Investigations of Light Alkane Dehydrogenation in a Fluidized Bed Reactor Yupeng Du1 Abdallah S. Berrouk 2, 3,*, Lejing Sun1, Weizhen Sun1, Deren Fang1, Wanzhong Ren1 1College

of Chemistry & Chemical Engineering, Yantai University, Yantai 264005, China

2Mechanical

Engineering Department, Khalifa University of Science and Technology, Petroleum Institute, PO Box 127788, Abu Dhabi, UAE,

3Center

for Catalysis and Separation, Khalifa University of Science and Technology, PO Box 127788, Abu Dhabi, UAE.

* To whom the correspondence should be addressed. E-mail: [email protected]

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Abstract An experimental set up and three-dimensional computational fluid dynamics (CFD) model are developed for light alkanes (pure propane, iso-butane, n-butane and their mixtures) dehydrogenation reactor that is a key part of a pilot-scale circulating fluidized bed (CFB) apparatus. Experimental findings indicate that the reaction temperature (T) and the gas hourly space velocity (GHSV) have a significant influence on the dehydrogenation process of the different light alkanes. As for propane and under the optimal conditions of T=600oC and GHSV=2350h-1, the conversion of C3H8 is 39% and the yield of C3H6 is 33%. The conversion of i-C4H10 is found to be 49% and a yield of 45% for iso-butane (i-C4H8) under the conditions of T=580oC and GHSV=1700h-1 is achieved. For n-butane and under the conditions of T=580oC and GHSV=1700 h-1, the conversion of n-C4H10 reaches 40% with a yield of 32%. Optimal conditions for the different light alkanes’ mixtures are also obtained. A 3D reactive CFD model is built and validated using some of the experimental data. The CFD model validation indicates that the predicted product distributions are in very good agreement with experimental data. Using the developed CFD model, hydrodynamics and species concentration distributions in the reactor are quantified for better understanding of the performance of the fluidized bed reactor. Using the CFD simulations together with experimental data, material balance of the pilot-scale CFB unit for propane dehydrogenation is obtained. The CFD methodology, developed in this study, is shown to be capable of helping engineering design and operation optimization of industrial CFB used for light alkanes dehydrogenation process. 2 ACS Paragon Plus Environment

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Keywords: fluidized bed reactor; light alkanes; dehydrogenation; CFD; process optimization


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1. Introduction The direct dehydrogenation of alkanes to alkenes has been commercially developed since 1930s 1. Due to the world demand for light olefins monomer (i.e. propylene and butylene) for polymers manufacture, the dehydrogenation of light alkanes to olefins is becoming a reaction of growing importance. Traditionally, propylene and butylene have been mainly produced as an ethylene byproduct in steam cracking (∼75% in 1998), fluid catalytic cracking units (∼24%), and only 3% by on-purpose light alkane dehydrogenation2. This trend has changed over the last two decades because of the more rapidly developing market for polypropylene and butyl rubber as compared to the one for ethylene derivatives3. This has increased the interest in light alkane-to-alkene processes as an economically attractive alternative4. Compared to the direct catalytic dehydrogenation of light alkanes, the oxidative dehydrogenation of them is potentially much more economical since it is exothermic and is carried out at lower reaction temperatures 5-7. However, the oxidative dehydrogenation process is known for its low selectivity of final products since hydrocarbons can be easily over-oxidized

8, 9.

Apart from the non-oxidative and

oxidative reaction conditions, some novel light alkane dehydrogenation processes have been proposed recently, including the use of a two-zone fluidized bed reverse flow reactors

12.

10,

membrane reactors

11,

and

However, the economic and operation problems linked to these more

sophisticated designs have prevented their commercial implementation 2. Consequently, only the direct catalytic dehydrogenation of light alkanes has been industrialized as a process for propylene and butylene production 4. 4 ACS Paragon Plus Environment

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A major problem with the direct dehydrogenation of light alkanes to olefins is the fast deactivation of the dehydrogenation catalyst because of coke formation. Therefore it requires frequent regeneration of the spent catalyst to recover its activity 4, 10.

Further difficulties are the

highly endothermic nature of the reaction and the equilibrium limitations that require operation at high temperatures and at pressure close to atmospheric

13, 14.

Current industrial processes

employ either fixed beds (Lummus/Houdry CATOFIN process, adiabatic fixed beds; Phillips STAR process, parallel tubular fixed beds; BASF/Linde process, parallel tubular fixed beds) or moving beds (UOP Oleflex process, adiabatic moving bed) with alumina-supported platinum or chromium catalyst

2, 4, 15.

All these developed processes that use fixed or moving beds are still

facing the problems of frequent regeneration of catalysts and/or reaction heat supply despite the existence of few costly solutions. This has triggered the use of the fluidized bed technology for dehydrogenation processes 16 as it is the case for Snamprogetti/Yarsintez FBD-3/4 process

16, 17.

In the FBD process, the catalyst is restored to its initial performance in the regenerator by burning the small quantity of coke formed on it, and then supplied the necessary reaction heat to the reactor using the hot solid catalysts as a thermal medium. The analysis of fluid flow, heat and mass transfers, coupled with chemical conversions within fluidized bed reactors has been an area of intensive research

2, 18.

For many decades,

engineers have managed to obtain better insights into these systems through both experiments and simulations. One of the simulation tools that has been in use to study processes based on fluidized bed technology, is computational fluid dynamics (CFD) 19-29. Although the use of CFD 5 ACS Paragon Plus Environment

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to simulate geometrically complex flows in fluidized bed reactors is often prohibitive for routine design and control of fluidized bed chemical reactors 19, the real contribution of CFD in this area is to provide more fundamental understanding of the transport and reaction phenomena in these reactors 30. Indeed, CFD can be used to obtain detailed three-dimensional velocity, species, and temperature fields that need to be analyzed in order to improve engineering designs

21.

Also,

CFD can be used to investigate situations which are not amenable to experimental testing 31. As a result, a wide range of studies has emerged in the literature that involve numerical simulations of hydrodynamics, heat transfer and cracking reactions in Circulating Fluidized Beds (CFB). A large body of these numerical investigations was carried out using the Two-Phase Model (TFM) coupled with lump kinetic models to account for the chemical reactions32. Two-fluid models are continuum models that use an Eulerian description for both fluid and solid phases 33. Kinetic Theory of Granular Flow is used to derive closure relations for the solid phase to be treated as a second fluid phase.

In contrast to Two-fluid models, another class of models

named Computational Particle-Fluid Dynamics (CPFD) models has emerged. In CPFD models, particles’ motion is tracked using a Lagrangian description of the solid phase. For these models, many aspects such as void fraction calculation34, phases’ coupling

35,

and particle collision

handling36 are to be resolved accurately and efficiently in order for these models to be computationally tractable for real-life engineering applications. CPFD models are generically divided into two categories depending on how particles collision is handled. The first category is Discrete Element/Particle model (DPM/DEM) in which particles and their collisions are 6 ACS Paragon Plus Environment

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individually tracked based on the soft-sphere or hard-sphere methods 37. The main advantage of DPM/DEM approach is that complexities such as polydispersity are straightforwardly dealt with. However, the dynamics of each particle must be calculated and particle-particle (P-P) contacts must be entirely resolved. Consequently, the computational overhead becomes large even for small-size applications with few hundreds of thousands of particles. Recent efforts made towards the parallelization of DEM/DPM algorithms have made the use of this category of CPFD models possible for industrial systems populated with few millions of particles

38.

This limitation in

terms of applications has triggered the development of the second category of CPFD models which is the Multi-Phase Particle-in-Cell model (MP-PIC). MP-PIC model is a hybrid of the continuum and discrete approaches to describing the solid phase. MP-PIC model has advantages of both approaches, namely, particles are grouped in clouds that are individually tracked, but contacts are evaluated in average using a continuum description of the solid-phase stress 39. For that purpose, closures for the solid-phase stress and drag force are needed.

As a consequence,

commercial chemical reactors that are often populated with several billions of particles (typically ~ 1013) can be represented using MP-PIC model using only ~106 clouds of real particles with similar physical properties such as size and density40. A more detailed cpmparison between these approaches in the context of fluidized beds can be found in Gera et al. 41 and Alobaid42 The aim of this study is to investigate experimentally and numerically, and then optimize the dehydrogenation process of light alkanes. For this purpose, a pilot-scale circulating fluidized bed (CFB) apparatus is built and numerically modelled to improve our understanding of the 7 ACS Paragon Plus Environment

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effects of fluid flow, heat, and mass transfer on propane dehydrogenation in CFB reactor. This two-legged investigation should serve as an initial report on engineering design of light alkane dehydrogenation processes and plants. To the best of the authors’ knowledge, this is the first report on CFD simulations of the direct dehydrogenation of propane in fluidized bed reactors. The present paper is organized as follows: In section 2, the experimental pilot-scale CFB apparatus for light alkane dehydrogenation processes is presented and briefly described. Then experimental investigations of operating conditions for catalytic dehydrogenation of pure propane, n-butane and iso-butane and their mixtures are studied and optimized. Numerical studies on the effects of fluid flow, heat, and mass transfer on propane dehydrogenation in the CFB reactor are presented in Section 3. In this section, a three-dimensional CFD model for CFB is developed and verified for propane dehydrogenation to propylene. Finally, a material balance of the whole pilot-scale CFB apparatus is set and some conclusions on the design are reported.

2. Experimental Setup 2.1 Materials All reagents including propane (>99%), iso-butane (>99.5%) and n-butane (>98%) were purchased from commercial sources and used without any treatment.

The used catalyst is a

chromium oxide supported on Al2O3 catalysts which is prepared by using an impregnation method 43-45. Table 1 lists the main physiochemical properties of the dehydrogenation catalyst.


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Table 1 - Main physiochemical properties of the Cr/Al2O3 dehydrogenation catalyst. Particle diameter distribution/% w(Cr2O3)/%

w(Al2O3)/%

15.01

80.22

SBET

Shape

/(m2·g-1)

133

Spherical

25~45

45~75

75~100

100~200

µm

µm

µm

µm

8.48

48.75

29.34

13.43

Mean diameter /µm

70

2.2 Apparatus A pilot-scale circulating fluidized bed apparatus (see Fig.1a and Fig. 1b) is employed to carry out experimental studies on light alkane dehydrogenation processes. In the pilot-scale setup, a 64 mm internal diameter stainless steel tube, with a porous plate as gas distributor, is used as reactor for the dehydrogenation of light alkanes (see Fig.2). The reaction temperature is measured by a thermocouple inside a thermowell, at the center of the catalyst bed. A 80 mm internal diameter stainless steel tube is utilized as catalysts regenerator, where the coke deposited on spent catalysts is burned out by using air. Both reactor and regenerator are believed to be operated in bubbling or turbulent fluidization regime. The solid catalysts are circulated between the reactor and the regenerator through transport pipes and a riser, where nitrogen acts as a lifting gas. The catalyst circulation rate is controlled with two electromagnetic valves. All feed streams, includes light alkanes, air and nitrogen, are mass flow controlled. The effluents from the fluidized bed reactor are analyzed by using an on-line gas chromatography equipped with a FID detector and a capillary column (Kromat Al2O3/Na2SO4 50m × 0.53mm × 15μm). Another 9 ACS Paragon Plus Environment

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on-line gas chromatography equipped with a TCD detector and a packed column (TDX-01) is employed to analyze flue gases from the outlet of the regenerator. Since dehydrogenation reactions only take place in the fluidized bed reactor, the CFD model is just developed for the CFB reactor in the present study. However, material balance of the whole CFB setup is summarized and obtained based on both experimental data and CFD simulations.

2.3 Optimizations of Process Operating Conditions Regarding an industrial chemical process, operating conditions are commonly crucial to both the yield and the quality of goal products. Among those operating conditions, temperature, pressure and space time are the most essential and also readily to be tuned

4, 46, 47.

Specifically

speaking, as for the light alkane dehydrogenation processes, low pressure operation is beneficial to the dehydrogenation reaction since it is a molecule expansion reaction

4, 47.

Therefore, light

alkane dehydrogenation processes are commonly operated at pressure close to atmospheric. Consequently, in the present study, just temperature and space time were experimentally optimized for light alkane dehydrogenation processes at atmosphere pressure by employing the aforementioned pilot-scale CFB setup.


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Fig.1(a) - Pilot-scale circulating fluidized bed (CFB) experimental apparatus (1 - Fluidized bed reactor; 2,3 - Spent catalyst transport pipe; 4 - Regenerator; 5 - Regenerated catalyst transport pipe; 6 - Riser; 7,8 - Electromagnetic valve; 9 - Riser base ; 10 - Mass flow meter; 11 – preheater; 12 - Condensation pipe; 13 - Liquid storage tank; 14 - Back pressure valve).


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Fig. 1(b) Pilot-scale CFB apparatus

Fig.2 - Geometry and mesh of the fluidized bed reactor. 12 ACS Paragon Plus Environment

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2.3.1 Propane dehydrogenation process The effects of changing reaction temperature and gas hourly space velocity (GHSV) on the conversion of propane and the selectivity and yield of propylene are investigated and shown in Fig.3a and 3b.

Fig.3 - The effects of (a) changing reaction temperature at GHSV=2350h-1 and P=0.1MPa and (b) gas hourly space velocity (GHSV) at T=600oC and P=0.1MPa on the conversion of propane and the selectivity and yield of propylene.

It can be seen from Fig.3a that at GHSV=2350h-1 and P=0.1MPa, as reaction temperature increases, the conversion of propane increases. This can be ascribed to the highly endothermic nature of the dehydrogenation reaction (H=124.3kJ/mol)13. Although high temperature accelerates rates of all reactions, it is more beneficial to the forward reaction, i.e. the propane dehydrogenation reaction, compared to the backward path (i.e. propylene hydrogenation reaction) when at far from thermodynamic equilibrium state 4. From Fig.3a, one can also observe that the 13 ACS Paragon Plus Environment

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selectivity of propylene decreases as the temperature increases. Such a tendency is also reported by Dixit et al. 48 and Ye et al. 49. The decreased selectivity may be owing to the thermal cracking of propane and propylene as well as the increase in formation rate of byproducts, such as methane and ethane, as temperature increases. At temperature of 600°C, an acceptable value of the yield of propylene (i.e. 33.21 wt%) is obtained. Fig.3b shows a decrease in the conversion of propane and an increase in the selectivity of propylene as GHSV increases at T=600oC and P=0.1MPa. This may be due to the fact that a higher GHSV gives rise to a shorter residence time of gaseous mixture. Therefore, the conversion of propane decreases because of the short contact time between propane and catalysts. However, since a high GHSV can prevent target products from over-cracking, the selectivity of propylene is promoted. The highest value of the yield of propylene (i.e. 33.21wt%) is obtained at GHSV of 2350h-1.

2.3.2 iso-butane dehydrogenation process The effects of changing reaction temperature and gas hourly space velocity (GHSV) on the conversion of iso-butane and the selectivity and yield of iso-butene are investigated and shown in Fig.4a and 4b.


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Fig.4 - The effects of (a) changing reaction temperature at GHSV=1700h-1 and P=0.1MPa and (b) gas hourly space velocity (GHSV) at T=580oC and P=0.1MPa on the conversion of iso-butane and the selectivity and yield of iso-butene.

It can be seen from Fig.4a that at GHSV=1700h-1 and P=0.1MPa as temperature increases, the conversion of iso-butane increases initially at a fast rate and then slows down. This can be ascribed to the highly endothermic nature of the iso-butane dehydrogenation reaction (H=117.6kJ/mol) 4 as well as the dehydrogenation reaction rates are accelerated. From Fig.4a, one can also observe that the selectivity of iso-butene decreases fast as the reaction temperature increases. Such a tendency is also reported by Liu et al. 50 and Vernikovskaya et al. 51. Due to the co-effects of increasing conversion and decreasing selectivity as temperatures increases, the yield of iso-butene increase quickly at first and then tend to be steady from the temperature of 580°C. Fig.4b shows a decrease in the conversion of propane decreases and an increase in the selectivity


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of propylene as GHSV increases at T=580oC and P=0.1MPa. The highest value of the yield of iso-butene (i.e. 45.17 wt%) is obtained at GHSV of 1700h-1.

2.3.3 n-butane dehydrogenation process The effects of changing reaction temperature and gas hourly space velocity (GHSV) on the conversion of n-butane and the selectivity and yield of butylene are investigated and shown in Fig.5a and 5b.

Fig.5 - The effects of (a) changing reaction temperature at GHSV=1700h-1 and P=0.1MPa and (b) gas hourly space velocity (GHSV) at T=580oC and P=0.1MPa on the conversion of n-butane and the selectivity and yield of butylene.

As can be seen from Fig.5a, at GHSV=1700h-1 and P=0.1MPa, the conversion of n-butane is increasing as reaction temperature increases. One can also observe from Fig.5a that the 16 ACS Paragon Plus Environment

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selectivity of butylene decreases fast as the temperature increases. Such a tendency is also reported by Zhu et al. 52 and Natarajan et al. 53. The yield of butylene is almost no more elevated after the temperature of 580°C. Fig.5b shows a decrease in the conversion of n-butane and an increase in the selectivity of butylene as GHSV increases at T=580oC and P=0.1MPa. The highest value of the yield of butylene (i.e. 32.24wt%) is obtained at GHSV of 1700h-1. To summarize, one can see from Fig3, Fig4, and Fig5 that, dehydrogenation processes of pure propane, iso-butane and n-butane show quite similar tendency as temperature and GHSV changes. Differences only lie in the optimum values of reaction temperature and GHSV when treating various light alkane feedstocks. Therefore, the used dehydrogenation catalyst may further be utilized to treat light alkane mixtures under optimized operating conditions.

2.3.4 Propane/iso-butane dehydrogenation process The effects of changing reaction temperature on the conversion of light alkane mixtures and the selectivity and yield of light olefins are investigated and shown in Figure 6a~c. The light alkane mixture is compound of propane and iso-butane in various proportions (20 wt% propane and 80 wt% iso-butane; 40 wt% propane and 60 wt% iso-butane; 60 wt% propane and 40 wt% iso-butane; 80 wt% propane and 20 wt% iso-butane).


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Fig.6 - The effects of (a~c) changing reaction temperature at GHSV=2000h-1 and P=0.1MPa and (d~f) gas hourly space velocity (GHSV) at T=590oC and P=0.1MPa on the conversion of propane/iso-butane mixture and the selectivity and yield of propylene/iso-butene mixture.

The produced light olefins are mainly considered as propylene and iso-butene. It can be seen from these figures that as temperature increases, conversions of all light alkane mixtures with 18 ACS Paragon Plus Environment

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different compositions of propane and iso-butane increase, while the total selectivity of propylene and iso-butene deceases within the studied temperature range. The total yield of light olefins increases initially at a fast rate and then slows down at temperature of 590°C. It can also be seen from Figure 6a~c that even at the same reaction temperature, different light alkane mixtures present various dehydrogenation performances. For instance, at temperature of 590°C, as the content of iso-butane in the light alkane mixtures increases, the conversions of light alkanes, the selectivity and yield of light olefins increase; whiles they decrease as the content of propane increase. This can be ascribed to the different molecular structures of propane and iso-butane. The C-H bonds in iso-butane are more readily to be activated and broken than that in propane 54, 55. The effects of changing GHSV on the conversion of light alkanes and the selectivity and yield of light olefins at T=590oC and P=0.1MPa are investigated and shown in Figure 6d~f. As can be seen from these figures, when GHSV increases, conversions of all light alkane mixtures with different composition of propane and iso-butane decrease, whiles the total selectivity of propene and iso-butene increases within the studied GHSV range. As GHSV increases, the total yield of light olefins decreases initially at a fast rate and then slows down at GHSV of 2000h-1. It can also be seen from Figure 6d~f that at the same GHSV, as the content of iso-butane in the light alkane mixtures increases, both the conversions of alkane mixtures and the selectivity and yield of light olefins increase. Especially from Figure 6f, one can observe that the higher content of iso-butane in light alkanes mixtures, the more readily the effect of GHSV on light alkane 19 ACS Paragon Plus Environment

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conversion and the products yield. Therefore, in practice industrial production, proper operating conditions should be paid more attention. As for the pilot-scale CFB unit, the appropriate operational conditions are 590°C and 1700h-1 when treating propane and iso-butane mixtures as feedstock. If the reaction temperature increases or GHSV decreases further, the alkanes conversion and the olefins yield just increase with a slight change. However, the energy consumption (affected by reaction temperature) might increase dramatically or the treatment throughput (affected by GHSV) of the unit would decrease substantially.

2.3.5 n-butane/iso-butane dehydrogenation process According to experimental investigations in pure iso-butane and n-butane dehydrogenation processes in Section 2.3.2 and 2.3.3, it is believed that treating n-butane and iso-butane mixtures as dehydrogenation feedstock is technically viable. It is also economically interesting since the butane need not to be separated into n-butane and iso-butane, consequently saving invests and cost. However, regarding butane mixtures made up of different proportion of n-butane and iso-butane, the optimum operating conditions may vary. The effects of changing reaction temperature on the conversion of butane mixtures (n-butane and iso-butane mixtures in various proportions) and the selectivity and yield of butylene (n-butene + iso-butene) at GHSV=1700h-1 and P=0.1MPa are shown in Figure 7a~c. It can be seen from these figures that, when temperature increases, conversions of butanes increase, whiles the selectivity of butylene deceases within the studied temperature range. 20 ACS Paragon Plus Environment

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Fig.7 - The effects of (a~c) changing reaction temperature at GHSV=1700h-1 and P=0.1MPa and (d~f) gas hourly space velocity (GHSV) at T=580oC and P=0.1MPa on the conversion of butanes and the selectivity and yield of butylenes.

Consequently, the yield of butylene increases initially at a fast rate and then slows down at 580°C as temperatures increases. As can also be seen from Figure 7a~c, at the same temperature, as the content of iso-butane in the butane mixtures increases, the conversion of butane mixtures, 21 ACS Paragon Plus Environment

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the selectivity and yield of butylene increase. This can be ascribed to the different molecular structures of iso-butane and n-butane. Because of the steric hindrance, the C-H bond length in iso-butane is a bit longer than that in n-butane so that the C-H bond energy is weaker and easier to be broken 54. The effects of changing GHSV on the conversion of butane mixtures and the selectivity and yield of butylene at T=580oC and P=0.1MPa are investigated and shown in Figure 7d~f. As can be seen from these figures, when GHSV increases, the conversion of butane mixtures decreases whiles the selectivity of butylene increase within the studied GHSV range. The yield of butylene decreases initially at a slow rate and then speed up at 1700h-1 as GHSV increases. It can also be seen from Figure 7d~f, at the same GHSV, as the content of iso-butane in the butane mixtures increases, the conversions of butane mixtures, the selectivity and yield of butylene products increase. Especially from Figure 7f, one can observe that the higher content of iso-butane in butane mixtures, the more readily the effect of GHSV on butane conversion and butylene yield. Therefore, in practice industrial production, proper operating conditions should be paid more attention. As for the pilot-scale CFB unit, the appropriate operational conditions are 580°C and 1700h-1 when treating n-butane and iso-butane mixture as feedstock. If the reaction temperature increases further or GHSV decreases, the total butane conversion and butylene yield increase with a just slight change. But the energy consumption would increase dramatically or the throughput of the unit would decrease substantially.


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2.3.6 Propane/n-butane/iso-butane dehydrogenation process Fig.8 shows the effects of reaction temperature and GHSV on the conversion of light alkane mixture (propane + iso-butane + n-butane) and the selectivity and yield of olefins (propylene + butylene). The contents of propane, iso-butane and n-butane in the dehydrogenation feestock are 33%, 54% and 13%, respectively. This is a typical composition of FCC liquid petroleum gas (LPG) 56. It can be seen from Figure 8 that at GHSV=2000h-1 and P=0.1MPa, as the temperature increases, the total conversion of light alkanes increase while the selectivity of the corresponding light olefins decrease.

Fig.8 - The effects of (a) changing reaction temperature at GHSV=2000h-1 and P=0.1MPa and (b) gas hourly space velocity (GHSV) at T=590oC and P=0.1MPa on the conversion of light alkanes (propane/iso-butane/n-butane=33/54/13) and the selectivity and yield of light olefins (propylene and butylene).


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As a result, the total yield of propylene and butylene increases as the reaction temperature increases. However, the total olefins yield tends to be steady when temperature is over 600oC, since the selectivity decrease dramatically. As can be seen from Fig 8b at T=590oC and P=0.1MPa, the conversion of alkane feedstock decrease and the selectivity of olefin products increase as GHSV increases, resulting in the decrease of propylene and butane. Under the operating conditions of 590oC and 2000h-1, the conversion of light alkane reaches 44.02%, the selectivity surpasses 89.43%, resulting in the yield of 39.37% of light olefins.

3. CFD investigations 3.1. Governing equations and constitutive relations To simulate the two-phase flow within the pilot-scale propane dehydrogenation (PDH) reactor, the Eulerian-granular multiphase granular model coded in ANSYS Fluent software is employed

57.

Table 2 summarizes the governing equations and constitutive relations for the

multiphase model. To account for chemical reactions, the species concentration and energy transport equations are also considered. In order to close the solids stress, the kinetic theory for granular flow (KTGF) is adopted. Many studies have indicated that the drag force on the particulate phase due to the gas phase is greatly affected by the heterogeneous flow structures characterizing two-phase flows in fluidized beds 23, 58-60. In this study, a drag model based on the energy minimization multi-scale (EMMS) methodology that takes this flow structure heterogeneity into consideration is chosen

20, 61

since the PDH reactor is operated in the 24

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bubbling/turbulent fluidization regime. In the EMMS-based drag model, bubbles are considered as meso-scale structures 20, 62.

Table 2 - Governing equations and constitutive relations. Continuity equation ( k  g , s )

Radial distribution function

  k  k      k  k v k   0 t

1/3 g 0  1   s /  s , max    

1

Momentum equation ( k  g , s; l  s, g )

Solid phase viscosity

  k  k v k      k  k v k v k  t   k pg    τ k   k  k g  K lk  v l  v k 

 s   s , kin   s , col

Energy equations

 s , kin 

 t



g

 g C pg Tg      g  g v g C pg Tg  n

  W Q

      grad Tg  

 t

  C s

s

i 1

i

ri

 s d s  s  s  6 3  e

2  1  5 1  e  3e  1  s g 0   

4 5

 s ,col   s  s d s g 0 1  e 

 Qsg

T      s  s v s C psTs   Qsg

s



Granular temperature equation

ps s

3   s s s       s s v s s  2  t 

Component continuity equation





 τ s : v s    ks  s    3 s  t



g

 g Yi      g  g u g Yi      Dg  grad  Yi    Wi

Collisional energy dissipation 12

Stress equation

   s2  s g 0 1  e 2 

 g  2  g S g   g g   v g

Inter-phase drag coefficient

τ s    ps   s s   v s   2  s S s

K sg  150

dp 

3/s 2

 s  g u g  us  s2  g , for  g  0.74  1.75 2 dp gd p


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Deformation rate

 s g  g u g  u s 3 K sg  CD wEMMS , 4 dp

1 1 T S k   k vk   vk     k   v k I   2 3

where,

Solid phase pressure

CD 

ps   s  s  s 1  2 s g 0 1  e  

for  g  0.74

0.687 24   , for Re  1000 1  0.15  Re p  p  Re p 

CD  0.44,

for Re p  1000

3.2. Reaction kinetics Many investigators studied the reaction mechanism of catalytic dehydrogenation of propane to propylene with various catalysts

13, 14, 51, 63, 64.

A great number of different kinetic models are

developed. In this study, the kinetic model proposed by Sun

65

is adopted, since the model is

developed with a fixed bed reactor and thermo gravimetric analysis (TGA) for the very Cr2O3/Al2O3 catalyst which is also used in the pilot-scale CFB experimental apparatus as shown in Figure 1. As for the kinetic model, four reaction paths are identified as shown in Table 3. Where, Cc and Cmax are the coke content in catalyst and the maximum coke content in catalyst, respectively. Kinetic parameter values for this kinetic model are listed in Table 4.

3.3. Simulation settings The configuration and the mesh of the PDH fluidized bed reactor are shown in Fig.2. Hexahedral cells are used for most of the computation zones, except for the regions near the propane inlet and the regenerated catalyst inlet, where tetrahedral cells are employed. The total 26 ACS Paragon Plus Environment

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number of cells is about 32,000 in which nearly 22,000 cells are of hexahedral type. The averaged cell size is about 80 times the particle diameter, which is 70μm. Such resolution is deemed acceptable since many previous investigations

20, 22, 66

that used coarse-grid simulations

of fluidized bed along with EMMS drag yielded reasonable predictions if the cell size is within the range of 10~100 times the particle diameter.


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Table 3 - Reaction kinetics model.(53) no.

reaction names

reaction formula

kinetic equations

R1

Propane dehydrogenation:

C3 H 8  C3 H 6  H 2

 PC H  PH 2 r1  k1  a   PC3 H8  3 6  K eq 

  

 Ea  1 1   k1  k01  exp   1      R  T Tm  

a  exp    Cc  K eq  exp 124912  127.9T  0.00675T 2  / 8.31 / T 

R2

Coke formation

C3 H 6  3CH 0.5  2.25H 2

R3

Cracking reaction

C3 H 8  CH 4  C2 H 4

R4

Ethylene hydrogenation

C2 H 4  H 2  C2 H 6

dC  k2   Cmax  Cc  dt

 Ea  1 1   k2  k02  exp   2      R  T Tm  

r3  k3  PC3H8

 Ea  1 1   k3  k03  exp   3      R  T Tm  

r4  k4  PC2 H 4  PH 2

 Ea  1 1   k4  k04  exp   4      R  T Tm  


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Table 4 - Reaction kinetics parameters.(53) Parameter

Value

k01

0.065 (mmol/(g·s))

Ea1

38.5 (kJ/mol)

Tm

823.15 (K)

α

793 (g catalyst/g coke)

Cmax

0.001 (g coke/g catalyst)

k02

0.003 (1/s)

Ea2

219.5 (kJ/mol)

k03

1.68e-5 (mmol/(g·s))

Ea3

287.1 (kJ/mol)

k04

2.33e-5 (mmol/(g·s))

Ea4

159.0 (kJ/mol)

The velocity-inlet boundary condition is prescribed for all stream inlets as shown in Fig.2, including the lifting gas (N2) inlet, propane inlet, as well as the regenerated catalyst inlet. The velocity-inlet boundary is also prescribed for the bottom spent catalyst outlet. In order to keep a constant solids inventory in the fluidized bed, the mass flow rates at the regenerated catalyst inlet and spent catalyst outlet add up to zero. The solids volume fraction for regenerated catalyst inlet is set to be 0.5 and coke content to be 0.01%. The solids volume fraction and the coke content at 29 ACS Paragon Plus Environment

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the spent catalyst outlet are set equal to those in the neighboring cells. The top product gas outlet is prescribed as pressure-outlet boundary condition with a gauge pressure of 0.1MPa. On the wall, the no-slip boundary is set for the gaseous phase, while a partial-slip boundary condition is set for the particulate phase. Both the gaseous and particulate phases are treated as mixtures in CFD simulations. There are seven species in the gas mixture, i.e., C3H8, C3H6, H2, CH4, C2H6, C2H4 and N2. In particular, N2 is introduced as an inert gas that does not react with the other chemical substances. All the other six species are consumed or produced in the course of chemical reactions and their mass changes are expressed in forms of source terms on the right hand side of the species transport equations in Table 1. The physical properties, including the molecular weight, heat capacity, thermal conductivity and viscosity, of each gas species is obtained from ANSYS Fluent materials database. The particulate phase has two species, i.e. coke and catalyst, for which the same heat capacity (1220 J/(kg·K)) and thermal conductivity (0.0454 W/(m·K)) are assigned. The catalyst density is 1800 kg/m3. The densities for gas and solid mixtures are calculated with the incompressible ideal gas equation and the volume-weighted mixing law, respectively. The other properties for both mixtures are based on the mass-weighted mixing law. The algebraic form of the granular temperature model is chosen in our simulations to ensure better convergence. Simulations were run on a high-performance computing machine. CFD computation is carried out for a total of 80s of real time to ensure that the simulation duration was long enough to mimic the desired operating conditions. Time-averaged distributions of variables are computed 30 ACS Paragon Plus Environment

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covering a period of the last 40 s of the simulation time. Operating conditions simulated herein are summarized in Table 5.

Table 5 - Operating conditions. Item

Value

Lifting nitrogen inflow rate

4.0 L/min

Propane inflow rate

12.5 L/min

Regenerated catalyst inflow rate

6.0 kg/h

Spent catalyst outflow rate

6.0 kg/h

Gauge pressure at top exit

0.1 MPa

Catalyst inventory in the PDH reactor

0.8 kg

Mean particle diameter

70 μm

Averaged temperature in the bed

600 °C

3.4. Model Verification and hydrodynamics Table 6 compares the numerically predicted product yield distributions at the outlet of the pilot scale PDH reactor with experimental data. As it can be seen from Table 6, good agreements of between the numerical results and experimental data are obtained which is a good indication that the developed three-dimensional CFD model could simulate quite reasonably the performance of the PDH fluidized bed reactor. 31 ACS Paragon Plus Environment

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Table 6 - Comparison simulation results and experimental data for mass fraction of the gaseous products (mass fractions are recalculated by removing N2). CFD simulation

Experiment

Error (%)

YC3H8

57.59

60.51

4.83

YC3H6

35.24

33.21

6.11

YH2

1.96

1.68

16.67

YCH4

1.51

1.24

21.77

YC2H6

1.38

1.07

28.97

YC2H4

1.11

0.94

18.09

YCH0.5

1.21

1.35

10.37

Conversion of C3H8

42.41

39.49

7.39

Selectivity of C3H6

83.09

84.10

1.20

For further validation of the developed CFD model, time-averaged contours of pressure and time-averaged and instantaneous distributions of solids volume fraction across the whole PDH reactor are also investigated. Fig.9 shows the time-averaged contour of pressure along the plane (y=0) and the time-averaged axial profile of pressure along the height of the PDH reactor. It can be observed from Fig.9 that there is a larger drop of pressure at the reaction section of the PDH reactor 32 ACS Paragon Plus Environment

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compared to the ones at the sedimentation section and the lifting section. The predicted pressure drop in the reaction section and sedimentation section is about 1860Pa which is in a very good agreement with the experimental value (1.9kPa). This pressure drop occurring in the reaction section is due to the fact that almost all catalyst particles are fluidized in this region of the PDH reactor. The latter can be verified by observing the time-averaged and instantaneous distributions of solids volume fraction across the whole PDH reactor as shown in Fig.10. The latter depicts a typical bubbling fluidization state for the reaction section with bed surface at the elevation of around 1.85m.

Fig.9 - Time-averaged contour of pressure at plane (Y=0) and axial pressure distribution along the height of the PDH reactor. 33 ACS Paragon Plus Environment

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Fig.10 - Time-averaged and transient contours of solids volume fraction.

Figs. 11a and 11b show the axial profile of time-averaged solids volume fraction along the PDH reactor height and the radial profile of time-averaged solids volume fraction at the height of 0.9m, respectively. As it can be seen from Fig.11a, time-averaged solids volume fractions at different cross sections in the reaction zone of the PDH reactor (H=0.8~1.85m) have values of about 0.1, while the solids volume fraction in the other sections are quite low. As Fig.11b shows, the highest solids volume fraction is near the wall while the lowest values are deviating from the center, which causes an asymmetry in the radial profile. This trend may be caused by the strong 34 ACS Paragon Plus Environment

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back mixing of solid catalysts near the wall, which is verified by the radial profile of time-averaged particle velocity at the height of 0.9m as shown in Fig.11c. The latter shows that the time-averaged particle velocity is negative near the PDH reactor wall, which is an indication of a significant catalyst backflow.

Fig.11 - Axial profile of time-averaged solids volume fraction along the PDH reactor height, and the radial profiles of time-averaged solids volume fraction and particle velocity at the height of 0.9m.


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3.5. Distributions of gaseous products in the PDH reactor Propylene and hydrogen are the two main target products of PDH process. However, inevitable byproducts such as methane, ethane, and ethylene are also produced. Fig.12 shows the time-averaged contours of mass fractions of C3H8, C3H6, H2, CH4, C2H6 and C2H4 on the plane (y=0). Fig.13 gives the transient contours of mass fractions of the gaseous products at the cross section (z=0.9m).

Fig.12 - Time-averaged contours of mass fraction of gaseous products at y=0.


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Fig.13 - Transient contours of mass fraction of gaseous products at z=0.9m and t=40s.

From Fig.12 and Fig.13, similar distributions can be observed for C3H6 and H2 with differences in magnitude. This is due to the fact that reactions producing C3H6 and H2 are identical and the mass diffusivity is set the same for all species in the gas mixture in the CFD model. Similar distributions are also observed for C2H4 and CH4 since the ethylene and methane are both produced through the cracking reaction of propane as listed in Table 3. The reaction rate of the ethylene hydrogenation, through which C2H4 and H2 were converted to C2H6, is not fast enough to influence the concentration distributions of C2H4 and H2

14.

Fig.14 quantifies mass

fraction evolution of C3H8, C3H6, H2, CH4, C2H6 and C2H4 along the height of PDH reactor. As it can be observed from both Fig.12 and Fig.14, the reactions seem to be almost completed near the 37 ACS Paragon Plus Environment

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elevation of 1.85m, above which the concentration distributions in both axial and radial directions appear to be uniform.

Fig.14 - Axial distributions of gaseous products along the height of PDH reactor.

3.6. Material balance of the pilot-scale CFB unit for propane dehydrogenation Based on both experimental data and the CFD simulation of the PDH fluidized bed reactor, the material balance of the whole pilot-scale CFB apparatus is obtained as shown in Fig.15. It can be observed from Fig.15 that the treatment capacity of the pilot-scale setup is about 20 tons of propane per year. Data presented in Fig.15 may be helpful for to chemical engineers or process engineers to design industrial plants with larger capacities.


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Fig.15 - Material balance of the pilot-scale CFB unit for propane dehydrogenation.

4. CONCLUSIONS An optimization study of the operating conditions for dehydrogenation process of light alkanes (propane, iso-butane, n-butane and their mixtures) is carried out using a pilot-scale circulating fluidized bed (CFB) unit. Experimental findings indicate that:  Reaction temperature (T) and the gas hourly space velocity (GHSV) have great influences on both conversion and yield of the light alkanes’ dehydrogenation process.  As for propane and under the optimal conditions of T=600oC and GHSV=2350h-1, the conversion of C3H8 is 39% and the yield of C3H6 is 33%. 39 ACS Paragon Plus Environment

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 The conversion of i-C4H10 is found to be 49% and a yield of 45% for iso-butane (i-C4H8) under the conditions of T=580oC and GHSV=1700h-1 is achieved.  For n-butane and under the condition of T=580oC and GHSV=1700 h-1, the conversion of n-C4H10 reaches 40% with a yield of 32%.  Optimal conditions for the different light alkanes’ mixtures are also obtained. Also, a three-dimensional CFD model is developed for the above experimental set up and used to study propane dehydrogenation process. Hydrodynamics and species concentration distributions in PDH reactor are predicted using the developed CFD model and they show a good agreement with experimental data. CFD model’s predictions reveal that:  Similar distributions can be observed for C3H6 and H2 with differences in magnitude.  Similar distributions are also observed for C2H4 and CH4 since the ethylene and methane are both produced through the cracking reaction of propane.  The reaction rate of the ethylene hydrogenation, through which C2H4 and H2 were converted to C2H6, is not fast enough to influence the concentration distributions of C2H4 and H2.  Based on mass fraction evolution of C3H8, C3H6, H2, CH4, C2H6 and C2H4 along the height of PDH reactor, it is concluded that all reactions seem to be almost completed near the elevation of around 1.85m


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Finally, a material balance of the pilot-scale CFB unit for propane dehydrogenation is set based on CFD and experimental data in order to help design optimized industrial PDH plants

AUTHOR INFORMATION Corresponding Authors * E-mail addresses

[email protected]; [email protected]

Notes The authors declare no competing financial interest.

ACKNOWLEDGMENT This work is financially supported by the Startup Foundation for Doctors of Yantai University (HY17B11), Shandong Provincial Natural Science Foundation, China (ZR2017LB022), and a project of Shandong Province Higher Educational Science and Technology Program(J17KB075).


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NOMENCLATURE Roman Letters

Ah

deactivation constant

a

deactivation function of catalyst

CD

drag coefficient

cp

heat capacity, J/(kg·K)

d

diameter, m

e

coefficient of restitution

g

gravity, m/s2

K

reaction rate constant

Qr

reaction heat, J/(m3·s)

ri

reaction rate of each species, kg/(m3·s)

Re

Reynold number

t

time, s

T

temperature, K

v

velocity, m/s

Yi

mass fraction of each species

Greek Letters 

volume fraction

s

granular temperature, m2/s2 42 ACS Paragon Plus Environment

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s

granular conductivity, kg/(m·s)



thermal conductivity, W/(m2·K)



stress tensor, Pa



density, kg/m3

Operators



transverse gradient operator

Subscripts

g

gas phase

s

solid phase


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REFERENCES (1) Miraboutalebi, S. M.; Vafajoo, L.; Kazemeini, M.; Fattahi, M., Chem. Eng. Technol. 2015, 38, 2198-2206. (2) Behnam, M.; Dixon, A. G.; Nijemeisland, M.; Stitt, E. H., Ind. Eng. Chem. Res. 2010, 49, 10641-10650. (3) Amghizar, I.; Vandewalle, L. A.; Van Geem, K. M.; Marin, G. B., Engineering 2017, 3, 171-178. (4) Sattler, J. J.; Ruiz-Martinez, J.; Santillan-Jimenez, E.; Weckhuysen, B. M., Chem. Rev. 2014, 114, 10613-53. (5) Al-Ghamdi, S.; Moreira, J.; de Lasa, H., Ind. Eng. Chem. Res. 2014, 53, 15317-15332. (6) Li, Z.; Peters, A. W.; Bernales, V.; Ortuno, M. A.; Schweitzer, N. M.; DeStefano, M. R.; Gallington, L. C.; Platero-Prats, A. E.; Chapman, K. W.; Cramer, C. J.; Gagliardi, L.; Hupp, J. T.; Farha, O. K., ACS Cent. Sci. 2017, 3, 31-38. (7) Nawaz, Z.; Wei, F., Ind. Eng. Chem. Res. 2012, 52, 346-352. (8) Cavani, F.; Ballarini, N.; Cericola, A., Catal. Today 2007, 127, 113-131. (9) Atanga, M. A.; Rezaei, F.; Jawad, A.; Fitch, M.; Rownaghi, A. A., Appl. Catal. B: Environ. 2018, 220, 429-445. (10) Gascón, J.; Téllez, C.; Herguido, J.; Jakobsen, H. A.; Menéndez, M., AIChE J. 2006, 52, 3911-3923. (11) Peters, T. A.; Liron, O.; Tschentscher, R.; Sheintuch, M.; Bredesen, R., Chem. Eng. J. 2016, 305, 191-200. (12) Annaland, M. v. S.; Nijssen, R. C., Chem. Eng. Sci. 2002, 57, 4967. (13) Rashidi, M.; Nikazar, M.; Rahmani, M.; Mohamadghasemi, Z., Chem. Eng. Res. Des. 2015, 95, 239-247. (14) Lobera, M. P.; Téllez, C.; Herguido, J.; Menéndez, M., Appl. Catal. A: Gen. 2008, 349, 156-164. (15) Sanfilippo, D.; Miracca, I., Catal. Today 2006, 111, 133-139. (16) Sanfilippo, D., Catal. Today 2011, 178, 142-150. (17) Kotelnikov, G. R.; Komarov, S. M.; Bespalov, V. P.; Sanfilippo, D.; Miracca, I., Stud. Surf. Sci. Catal. 2004, 147, 67-72. (18) Dudukovic, M. P., Science 2009, 325, 698-701. (19) Du, Y.; Zhao, H.; Ma, A.; Yang, C., Ind. Eng. Chem. Res. 2015, 54, 8732-8742. (20) Lu, B.; Luo, H.; Li, H.; Wang, W.; Ye, M.; Liu, Z.; Li, J., Chem. Eng. Sci. 2016, 143, 341-350. (21) Chang, J.; Meng, F.; Wang, L.; Zhang, K.; Chen, H.; Yang, Y., Chem. Eng. Sci. 2012, 78, 128-143. (22) Wang, J.; Liu, Y., Powder Technol. 2010, 197, 241-246. (23) Benyahia, S., AIChE J. 2012, 58, 3589-3592. 44 ACS Paragon Plus Environment

Page 45 of 46 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

Energy & Fuels

(24) Zhao, Y.; Li, H.; Ye, M.; Liu, Z., Ind. Eng. Chem. Res. 2013, 52, 11354-11364. (25) Zhu, Y.-P.; Chen, G.-Q.; Luo, Z.-H., Macromol. React. Eng. 2014, 8, 609-621. (26) Berrouk, A.S.; Huang, A.; Bale, S.; Thampi, P.; Nandakumar, K., Advanced Powder Technology. 2017, 28(11), 2947-2960. (27) Berrouk, A.S.; Pornsilph, C.; Bale, S.; Du, Y.; Nandakumar, K., Energy & Fuels. 2017, 31(5), 4758-4770 (28) Yang Q.; Berrouk, A.S.; Du, Y.; Zhao, H.; Yang, C.; Abdur Rakib, M.; Mohamed, A.; Taher, A., Applied Mathematical Modelling. 2016, 40(21-22), 9378-9397 (29) Du, Y.; Yang, Q.; Berrouk, A.S.; Yang, C.; Al Shoaibi, A., Energy & Fuels. 2014, 28(11), 6830-6840 (30) Yang, C.; Du, Y.; Zhao, H., Chem. Ind. Eng. Prog. 2015, 34, 608-616. (31) Lu, B.; Wang, W.; Li, J.; Wang, X.; Gao, S.; Lu, W.; Xu, Y.; Long, J., Chem. Eng. Sci. 2007, 62, 5487-5494. (32) Shah M.T.; Utikar, R.P.; Pareek, V.K.; Evans, G.M; Joshi J.B., chemical engineering research and design, 2016, 111, 403–448 (33) Anderson T. B., Ind. Eng. Chem. Fundamen. 1967, 6 (4), 527-539. (34) Wu C.L.; Zhan, J. M.; Li Y.S.; Lam K.S.; Berrouk A.S., Chem. Eng. Sci., 2009, 64 (6), 1260-1266. (35) Wu C.L.; Berrouk, A.S.; Nandakumar K., Chem. Eng. J., 2009, 152 (2), 514-529. (36) Wu C.L.; Berrouk, A.S.; Nandakumar K., Powder Tech. 2010, 197 (1), 58-67. (37) Tsuji, Y.; Ishida, T., Powder Tech., 1992, 71 (3), 239-250 (38) Wu C.L.; Berrouk A.S.; Nandakumar, K., Chem. Eng. Sci. 2008, 118 (21), 221-244. (39) Snider, D.M.; O'Rourke, P.J.; Andrews, M.J. , Int. J. Multiphase Flow 1998, 24 (8), 1359-1382. (40) Snider, D.M., J. Comp. Phy. 2001, 170 (2), 523-549. (41) Gera, D.; Gautam, M.; Tsuji, Y., Kawagushi, T.; Tanak, T., Powder Technology, 1998, 98 , 38-47 (42) Alobaid, F., Powder Technology, 2015, 286, 342-360 (43) Fang, D.; Zhao, J.; Li, W.; Fang, X.; Yang, X.; Ren, W.; Zhang, H., J. Energ. Chem. 2015, 24, 101-107. (44) Fang, D.; Ren, W.; Liu, L.; Liu, S.; Zhang, L.; Qin, Y.; Li, T. A high-impact catalyst for low-carbon alkane dehydrogenation and its preparation approach. ZL 201410265574.1, 2014-06-13, 2014. (45) Fang, D.; Ren, W.; Liu, B.; Wang, T.; Zhang, H. A preparation method for mesoporous materials and catalysts. ZL 201210197359.3, 2012-06-14, 2012. (46) Yang, H.; Xu, L.; Ji, D., React. Kinet. Catal. Lett. 2002, 76, 151. (47) M.M Bhasin, J. H. M., B.V Vora, Appl. Catal. A: Gen. 2001, 221, 397-419. (48) Dixit, M.; Kostetskyy, P.; Mpourmpakis, G., ACS Catal. 2018, 8, 11570-11578. 45 ACS Paragon Plus Environment

Energy & Fuels 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

Page 46 of 46

(49) Ye, G. H.; Wang, H. Z.; Duan, X. Z.; Sui, Z. J.; Zhou, X. G.; Coppens, M. O.; Yuan, W. K., AIChE J. 2019, 65, 140-150. (50) Liu, J. F.; Zhou, W.; Jiang, D. Y.; Wu, W. H.; Miao, C. X.; Wang, Y.; Ma, X. B., Ind. Eng. Chem. Res. 2018, 57, 11265-11270. (51) Vernikovskaya, N. V.; Savin, I. G.; Kashkin, V. N.; Pakhomov, N. A.; Ermakova, A.; Molchanov, V. V.; Nemykina, E. I.; Parahin, O. A., Chem. Eng. J. 2011, 176-177, 158-164. (52) Zhu, Q. Q.; Wang, G. W.; Zhang, H. L.; Zhu, X. L.; Li, C. Y., Appl. Catal. A: Gen. 2018, 566, 113-120. (53) Natarajan, P.; Khan, H. A.; Yoon, S.; Jung, K. D., J. Ind. Eng. Chem. 2018, 63, 380-390. (54) Coperet, C., Chem. Rev. 2010, 110, 656–680. (55) Marcinkowski, M. D.; Darby, M. T.; Liu, J. L.; Wimble, J. M.; Lucci, F. R.; Lee, S.; Michaelides, A.; Flytzani-Stephanopoulos, M.; Stamatakis, M.; Sykes, E. C. H., Nat. Chem. 2018, 10, 325-332. (56) Xu, C.; Yang, C., Petroleum refining engineering. Chemical industry press: Beijing, China, 2009. (57) ANSYS, I. ANSYS Fluent theory guide (release 14.0). http://www.ansys.com. (58) Wang, W.; Li, J., Chem. Eng. Sci. 2007, 62, 208-231. (59) Li, T.; Benyahia, S., AIChE J. 2013, 59, 3624-3632. (60) Yang, N.; Wang, W.; Ge, W.; Wang, L.; Li, J., Ind. Eng. Chem. Res. 2004, 43, 5548-5561. (61) Shi, Z.; Wang, W.; Li, J., Chem. Eng. Sci. 2011, 66, 5541-5555. (62) Ullah, A.; Hong, K.; Chilton, S.; Nimmo, W., Powder Technol. 2015, 281, 129-137. (63) Fridman, V. Z., Appl. Catal. A: Gen. 2010, 382, 139-147. (64) Gascón, J.; Téllez, C.; Herguido, J.; Menéndez, M., Appl. Catal. A: Gen. 2003, 248, 105-116. (65) Sun, W. Study on the effects of operating conditions on propane dehydrogenation over a Cr/Al2O3 catalyst. Yantai University, Yantai, China, 2017. (66) Lu, B.; Wang, W.; Li, J., Chem. Eng. Sci. 2009, 64, 3437-3447.


Experimental and CFD Investigations of Light Alkane

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