CFD modeling of gas–solid flow and cracking reaction in two-stage riser FCC reactors

Chemical Engineering Science 64 (2009) 3847 -- 3858

Contents lists available at ScienceDirect

Chemical Engineering Science journal homepage: w w w . e l s e v i e r . c o m / l o c a t e / c e s

CFD modeling of gas–solid flow and cracking reaction in two-stage riser FCC reactors Xingying Lan, Chunming Xu, Gang Wang, Li Wu, Jinsen Gao ∗ State Key Laboratory of Heavy Oil Processing, China University of Petroleum, Beijing 102249, PR China

A R T I C L E

I N F O

Article history: Received 27 August 2008 Received in revised form 25 April 2009 Accepted 14 May 2009 Available online 20 May 2009 Keywords: FCC Two-stage riser Gas–particle turbulent flows Cracking reactions CFD Optimization

A B S T R A C T

The Eulerian–Eulerian approach was applied to simulate the flow behavior and catalytic cracking reactions in the riser reactors of two-stage riser fluid catalytic cracking (TSRFCC) technology. A k −  − kp − p −  gas–solid turbulent flow model was used, which took account of the particle turbulence and the interaction of turbulence between gas and particle phases. A 14-lump kinetics model was used for simulating cracking reactions. The approach and model were validated with both experimental results and commercial data. The distributions of particle fraction volume and velocity, as well as product yields in the TSRFCC riser reactors were first analyzed. The simulations were then carried out for optimization studies to understand the influence of the operating conditions on the performance of commercial TSRFCC riser reactors. The model and results presented here are valuable for the design and optimization of TSRFCC technology. © 2009 Published by Elsevier Ltd.

1. Introduction Fluid catalytic cracking (FCC) is a key and widely used refinery process for converting heavy oils into valuable light products such as gasoline and diesel. About 45% of worldwide gasoline production comes from the FCC process and its ancillary units. Especially for China, due to the lack of hydro-cracking and hydro-conversion units, FCC remains the most important and profitable heavy oil conversion process in the petroleum refining industry. Although the FCC process has been commercially established for over 60 years, the technology continues to evolve to meet new challenges (Chen, 2006). Modern FCC units need to use a wide variety of feedstocks and to adjust operating conditions to maximize production of gasoline, middle distillate, or light olefins to meet different market demands. Nowadays, many improvements have been made on the FCC process, and these new processes have been run in commercial scale, such as twostage riser fluid catalytic cracking (TSRFCC) technology (Shan et al., 2001), a catalytic cracking process for the production of clean gasoline (MIP-CGP) (Han et al., 2006), flexible dual-riser fluid catalytic cracking (FDFCC) technology (Wang et al., 2003), double-riser technology (Henry et al., 2002), millisecond catalytic cracking (MSCC) technology (Schnaith et al., 1998), and deep catalytic cracking (DCC) (Xie, 1997). These technologies obtain better product distribution than conventional FCC. For conventional FCC, the catalyst activity decreases sharply in the riser entry zone so that cracking reactions are carried out with

∗ Corresponding author. Tel.: +86 10 89733993. E-mail address: [email protected] (J. Gao). 0009-2509/$ - see front matter © 2009 Published by Elsevier Ltd. doi:10.1016/j.ces.2009.05.019

quite low catalyst activity in the second half of the riser. Moreover, the catalyst deactivation results in poor product selectivity. The conventional single riser FCC unit has less than optimum product distribution. Thus, Shan et al. (2001) developed TSRFCC technology to improve product distribution. Until now, TSRFCC technology has been applied successfully in eight commercial FCC units (Shan et al., 2006). TSRFCC technology has two risers, whose diameter and length is different from the conventional single riser. The fresh feedstock is introduced into the first-stage riser and subjected to a certain degree of cracking reactions. The coked catalysts with low activity and selectivity are separated from the oil products. Then, the oil products continue cracking reactions over the regenerated catalysts with good activity and selectivity up to the final conversion in the secondstage riser. The two risers share a common disengager and regenerator. A series of TSRFCC derivative technologies have been developed to achieve various product yields. The TSRFCC-I scheme is suitable for enhancing the production of light oil, especially higher ratios of diesel to gasoline (Shan et al., 2006). In the TSRFCC-I scheme, the cracking products from both first- and second-stage risers enter a fractionator and are separated. The products of gas, gasoline, and diesel leave the reaction system, while the heavy cycle oil (HCO) enters the second-stage riser and proceeds cracking reactions over regenerated catalysts. The commercial application of TSRFCC-I technology showed that the light oil yield increased by 4 wt%, while the dry gas yield decreased by more than 1% (Shan et al., 2006). Although TSRFCC-I technology has been applied in eight commercial FCC units, the procedure of the industrial design primarily depending on experience is not able to bring its function into full play. The operation optimization is absolutely necessary in commercial applications of TSRFCC-I technology. The performance of an FCC unit is

3848

X. Lan et al. / Chemical Engineering Science 64 (2009) 3847 -- 3858

dependent on many parameters, such as feed composition, residence time, reaction temperature, catalyst-to-oil (CTO) ratio, hydrocarbon partial pressure, catalyst properties, and riser hydrodynamics, all of which influence the conversion process in their own way (Dupain et al., 2006). The operation optimization of TSRFCC-I technology requires the in-depth understanding of hydrodynamics and reaction behavior in riser reactors. The process in a riser reactor is typically turbulent multiphase flow with reaction and comprises many complex mutual subprocesses, such as cracking reaction, momentum transfer, heat transfer and mass transfer, all of which are known to be interrelated. In the last decade, with the development of computer hardware and computational techniques, computational fluid dynamics (CFD) is becoming widely used to simulate many processes in the chemical industry. The CFD modeling of FCC riser reactors has been performed by several authors and reported in the open literatures (Theologos and Markatos, 1993; Theologos et al., 1997, 1999; Gao et al., 1991, 2001, 2006; Das et al., 2003; Nayak et al., 2005). Theologos and Markatos (1993) developed first a CFD model to predict the two-phase reacting flow inside catalytic cracking riser-type reactors. The model consisted of the full set of partialdifferential equations that describe the conservation of mass, momentum, energy, and chemical species for both phases in the reactor, coupled with empirical correlations concerning interphase friction, interphase heat-transfer, and fluid-to-wall frictional forces. The cracking reaction was simulated by a simple three-lump kinetic model. The simulation showed the most important engineering aspects of a riser reactor including pressure drop, catalyst holdup, interphase slip velocity, catalyst acceleration zone, choking behavior and temperature distributions in both phases, and yield distribution all over the reactor. Then, the CFD model was further incorporated with a detailed 10-lump reaction kinetics scheme and feed spray vaporization effect (Theologos et al., 1997). The model was used to predict the effect of feed-injector geometry on overall reactor performance. Theologos et al. (1999) extended their CFD model to account for feed atomization effects on feedstock vaporization rates, cracking reactions initiation, reactor selectivity, and overall reactor performance. Gao et al. (1999) considered turbulent flow and the diffusion of particle phase which was ignored by Theologos et al. (1997) and developed a three-dimensional two-phase turbulent flow-reaction model based on a modified two-phase turbulent model for the comparatively dense particle phase and incorporating 13-lump kinetics of the residuum cracking reaction. The simulated results revealed details on the motion, the temperature rise, as well as their impacts on the cracking reactions. Accounting for the effect of feed spraying, Gao et al. (2001) established a 3-D gas–liquid–solid three-phase flow-reaction model. The feed vaporization inside the riser reactor was modeled with a set of governing equations for the feed spray droplets. Based on CFD simulation results, Gao et al. (2006) proposed a reaction-terminating technique, injecting quenching media at a predetermined height of the riser reactor at which the product yield was at the optimum level. Das et al. (2003) performed three-dimensional simulation of an industrial-scale fluid catalytic cracking riser reactor using a novel density-based solution algorithm. Nayak et al. (2005) applied Eulerian–Lagrangian approach to model the simultaneous flow, evaporation, and cracking reactions occurring in FCC riser reactors. The influence of key design and operating parameters on the performance of FCC riser reactors, such as initial oil droplet distribution, catalyst inlet temperature, and CTO ratio was investigated by predicted results. The above research demonstrates further that CFD is a powerful tool that enables a better analysis and understanding of the complex phenomena occurring in FCC riser reactors. For the

design and optimization of TSRFCC technology, the CFD method was applied to simulate the two-phase turbulent flow-reaction process in TSRFCC riser reactors. Then, optimization studies were carried out to investigate the influence of operation conditions such as residence time, reaction temperature, and CTO on catalytic cracking reactions. 2. Mathematical model 2.1. Gas–solid flow model The gas–particle flows in risers are extremely complex because of the turbulent flow of both gas and particles with relatively high particle density. To simulate successfully turbulent multiphase flows, it is necessary to take into account the time averaged turbulent behavior and the turbulent interaction between phases. Various authors have utilized different models to model the hydrodynamics of gas–solid multiphase risers. Currently, the Eulerian–Eulerian (two-fluid) model with kinetic theory of granular flow is the most applicable approach to simulate gas–solid flows in risers (Benyahia et al., 2000; Neri and Gidaspow, 2000; Zheng et al., 2001; Chan et al., 2005). In the two-fluid model, all the phases are modeled as interpenetrating continua with similar conservation equations. The interactions between two phases are expressed as additional source terms added to the conservation equations. The kinetic theory of granular flow is used to define the fluid properties of the solid phase through constitutive equations. Detailed discussion on the development of granular flow models was provided by Gidaspow (1994). Sinclair and Jackson (1989) first applied this approach to model the fully developed flow in vertical pipes, and their prediction indicated the applicability of this theory to describe gas–solid flow. Pita and Sundaresan (1993), Nieuwland et al. (1996), Samuelsberg and Hjertager (1996) extended this work and investigated the gas–particle flow in riser reactors. All the work mentioned above was based on the laminar particle phase model. For gas–solid flows at high Reynolds numbers, the gas turbulence is expected to have a noticeable effect on the momentum and energy transfer between both phases. Thus, Bolio et al. (1995) added the interactions between the turbulence of gas and the fluctuations of particles. Meanwhile, Dasgupta et al. (1994), Hrenya and Sinclair (1997), and Cheng et al. (1999) incorporated different formulations to describe the turbulent motions of particles and made these models more effective in predicting turbulent gas–particle flow. Their work showed that the particulate turbulence had an essential influence on the whole flow system, thus it was necessary to add the turbulent effects of particle phase into the gas–particle two-fluid model. Accounting for the turbulence and the turbulent energy dissipation of particles, Zheng et al. (2001) developed an advanced k −  − kp − p −  two-fluid model based on the kinetic theory of granular flow to simulate the turbulent gas–particle flow in a riser reactor. The gas phase is described by the k −  model widely used in singlephase flow, and the particle phase is simulated by combining the kinetic theory of granular flow, which considers the fluctuation of particles, with the particles turbulent kp − p model, which is analogous to the k −  model equation and considers the dissipation of particle turbulent energy. The detailed analysis indicated the particles turbulence and the interaction of turbulence between gas and particle phases influenced the predicted results. In the present study, the flows in TSRFCC risers are very turbulent with high Reynolds numbers. For a reliable modeling of turbulent gas–solid flow phenomena, the particles turbulence and the interaction of turbulence between gas and particle phases should be considered. Therefore, the k −  − kp − p −  two-fluid model

X. Lan et al. / Chemical Engineering Science 64 (2009) 3847 -- 3858

Ah

3849

F Ah

Am

Al

LPG

GO

DG

Ph

Pm

CK

Nl

Pl

Nm

Nh

Fig. 1. Reaction network of the 14-lump FCC kinetic model.

Table 1 Lumps of the 14-lump kinetic model.

General form of gas phase governing equation:

Lump symbol

Lump

Boiling range

Ph Pm Pl Nh Nm Nl FAh Ah Am Al GO LPG DG CK

Heavy paraffinics Medium paraffinics Light paraffinics Heavy naphthenics Medium naphthenics Light naphthenics Heavy aromatics in resin and asphaltene Heavy aromatics except FAh Medium aromatics Light aromatics Gasoline Liquid petroleum gas Dry gas Coke

500 ◦ C+ 350–500 ◦ C 221–350 ◦ C 500 ◦ C+ 350–500 ◦ C 221–350 ◦ C 500 ◦ C+ 500 ◦ C+ 350–500 ◦ C 221–350 ◦ C C5–221 ◦ C C3+C4 C1+C2+H2

proposed by Zheng et al. (2001) was applied to simulate the turbulent two-phase reacting flow inside TSRFCC risers. 2.2. Catalytic cracking kinetic model Chemical reactions of petroleum fractions in FCC risers are numerous and complex. Thermal and catalytic cracking reactions as well as many side reactions, such as hydrogen transfer, are progressing simultaneously. In addition, petroleum fractions are hydrocarbon mixtures with different chemical species reacting at different rates. Thus, the catalytic cracking of petroleum fractions has been traditionally accessed through lumped models in which pseudocomponents are chosen to characterize the whole mixture. In the present work, a 14-lump reaction kinetic model (Zhang, 2005) was considered to represent catalytic cracking reactions. The reaction scheme is shown in Fig. 1, and the 14 lumps are listed in Table 1. The reaction paths and their kinetic parameters are shown in Table 2. 2.3. Governing equations The resulting time-averaged governing equations for steady-state gas–particle reacting flows in a two-dimensional cylindrical coordinate are as follows.



* * * * (u)g + (rv)g =  *x r *r *x *X 

* * + r  r *r *r



 g

+ Sg + Sgp

(1)

g

General form of particle phase governing equation: 

* * * * (u)p + (rv)p =  *x r *r *x *x 

* * + r  r *r *r



+ Sp + Spg

 p

(2)

p

The expression for each item in the governing equations is listed in Tables 3 and 4, the items (g,t , s,t , Gk , Gp , Gkp , Ggp , Gpp ) related to turbulent equations can be found in the paper of Zheng et al. ( 2001). The reaction rate of lump i (source term wi in Table 3) is expressed as Wi = −A0 ·

(Cc ) 1 + Kh CAh

·

g p KY g i i

(3)

where A0 is the correction coefficient of the initial catalyst activity (the ratio of used catalyst activity to that of the catalyst employed in the kinetic experiments), Kh is the adsorption coefficient of aromatics, (Cc ) is the decay function of the catalyst due to coke depositing on the catalyst surface, and calculated by the following equation (Gao et al., 1999):

(Cc ) = (1 + 0.51Cc )−2.78 ·

(4)

The heat of cracking reactions (source term Qr in Table 3) is calculated according to the mass of coke produced from cracking reactions. It is reported that the cracking reactions in FCC process are endothermic reactions, and producing 1 kg coke needs the heat quantity of 9.127×103 kJ (Lin, 2000). Qr equals to 9.127×103 kJ multiply the mass of coke.

3850

X. Lan et al. / Chemical Engineering Science 64 (2009) 3847 -- 3858

Table 2 Kinetic parameters of the 14-lump kinetic model. Path no.

Path

Frequency factor, k0 (m3 /kgcat /s)

Activation energy, E (kJ/kg)

Path no.

Path

Frequency factor, k0 (m3 /kgcat /s)

Activation energy, E (kJ/kg)

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24

Ph→Pm Nh→Nm Ah→Am FAh→Am Ph→Pl Nh→Nl Ah→Al FAh→Al Ph→GO Nh→GO Ah→GO FAh→GO Ph→LPG Nh→LPG Ph→DG Nh→DG Ph→CK Nh→CK Ah→CK FAh→CK Pm→Pl Nm→Nl Am→Al Pm→GO

18.77 19.25 1.817 0.5514 16.38 17.05 1.617 0.4342 0.2266 0.1374 0.0136 0.0054 5.77 6.20 63.18 64.99 3.366 4.754 41.82 40.50 833.90 944.00 773.80 1.263

7.21e+4 7.21e+4 7.21e+4 7.21e+4 7.21e+4 7.21e+4 7.21e+4 7.21e+4 3.04e+4 3.04e+4 3.76e+4 3.76e+4 4.32e+4 4.32e+4 6.32e+4 6.32e+4 5.00e+4 5.00e+4 5.44e+4 5.44e+4 7.21e+4 7.21e+4 7.21e+4 3.04e+4

25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48

Nm→GO Pm→LPG Nm→LPG Am→LPG Pm→DG Nm→DG Am→DG Pm→CK Nm→CK Am→CK Pl→GO Nl→GO Pl→LPG Nl→LPG Al→LPG Pl→DG Nl→DG Al→DG Pl→CK Nl→CK Al→CK GO→LPG GO→DG GO→CK

0.4092 1.506 0.5742 0.0438 5.491 2.013 0.0324 1.704 1.061 5.611 1.257 1.986 2.258 1.506 0.033 15.20 10.14 0.0498 0.1363 0.1491 0.8254 1374.00 343.40 0.066

3.04e+4 4.32e+4 4.32e+4 2.76e+4 6.32e+4 6.32e+4 3.76e+4 5.00e+4 5.00e+4 5.44e+4 3.04e+4 3.04e+4 4.32e+4 4.32e+4 2.76e+4 6.32e+4 6.32e+4 3.76e+4 5.00e+4 5.00e+4 5.44e+4 1.18e+4 1.18e+4 5.61e+4

Table 3 Governing equations of gas phase. Equations

g

g

Sg

Continuity equation

1

0

0

*p * *u + −g e g *x *x *x

Momentum equation in x-direction

ug

e

Momentum equation in r-direction

g

e

Turbulent kinetic energy equation

kg

g +

Dissipation rate equation of turbulent energy

g

Species equation

Yi

Enthalpy equation

hg

g,t k g,t g +  g,t g + Y  g + g,t h

Sgp

  *ug *vg vg 2 2 + + g g kg + e 3 3 r *x *r        *p * *ug * * vg * 2 *ug *vg vg 2 2e vg −g e +   g −   k +  + + re − + + g r g g g g r2 3 e *x r *r *x *r r*r *r *r 3 *r

0

Gk − g g g

Gp

g kg







* * vg + re r*r *x



* + g g gx − *x



− (ug − up ) − (vg − vp )

g

(C1 Gk − C2 g g g )

kg

wi

0

−Qr

Qs

(C3 Gp )

Table 4 Governing equations of particle phase. Equations

p p

Sp

Continuity equation

1

0

0

Momentum equation in x-direction

up

p

−p

Momentum equation in r-direction

p p

Turbulent energy equation of particle phase

kp

s +

s,t k

Dissipation rate equation of turbulent energy

p

s +

s,t 

Temperature of particle equation



 2  + s,t 3 

Enthalpy equation

hp

 s + s,t h

Spg

0    2 *up *vp vp 2 p p kp + p − s

(ug − up ) + + 3 3 r *x *r         2p vp 2 *p * *u * *vp *ps * 2 *up *vp vp −P p p + + p p gr − p p kp +  − s

(vg − vp ) + rp − − + + r2 3 p r *r *x *r r*r *r *r *r 3 *x *r 

*p * *u p p + *x *x *x



Gkp − p p p

p kp

(C1 Gkp − C2 p p p )

Gpp + 0

2 2  p p −  3 p 3



+

* * vp rp r*r *x



+ p p gx −

*ps * − *x *x



Ggp

p kp

(C3 Ggp )

0 −Qs

X. Lan et al. / Chemical Engineering Science 64 (2009) 3847 -- 3858

2.4. Numerical procedure

3851

conditions and riser geometry for three cases are summarized in Table 5. The comparisons of particle phase volume fraction and axial velocity distributions between model predictions and experimental data are shown in Figs. 2 and 3. The simulation predicts reasonably the flow behavior found by the experimental measurements. The particle volume fractions are low and have a nearly uniform value within most of the inner region, and rise rapidly near the wall. On the condition that the particle flux is relatively high and the superficial gas velocity is relatively low, as in Bader's experiment, the predictions verify the annular-core flow structure in the riser. In the annular region, the particles aggregate and there exists solids refluence. However, in the case of Yang's experiment (II), the predicted particle phase flow pattern is not annulus-core flow, but is nearly parabolic due to the low particle flux. This phenomenon can also be found in other researchers' studies (Gao et al., 1999). The predicted volume fraction and velocity of the particle phase are in good agreement with experimental data, which indicate that the k −  − kp − p −  gas–solid turbulent flow model has the capability to simulate both relatively dense and dilute gas–particle flow in the riser.

The governing equations were solved on the Fluent 6.2 package using the finite volume method by Patankar (1980). The secondorder upwind discretization schemes were used to solve the convection terms. The source terms for different governing equations in Tables 3 and 4 were specified by user-defined functions (UDFs) in the C programming language. The source term codes were then compiled and hooked to the FLUENT solver. The Phase Coupled SIMPLE (PCSIMPLE) algorithm, which is an extension of the SIMPLE algorithm of multiphase flows, was used for the pressure–velocity coupling and correction. The risers were simulated in a two-dimensional cylindrical coordinate. The dimensions of the domain in radial and axial directions were equal to those of the actual riser. In the radial direction, the grid spacing was distributed non-uniformly, and more cells were placed closer to the wall to capture the complex flow behavior in this region. The total number of cells used to construct the grid was set at 5,000 (200×25) (axial×radial). The typical computational time for this simulation was 4–6 h on an Intel-xeon 3.06 GHz workstation. The implementation of correct inlet and boundary conditions is critical for a successful simulation of flow hydrodynamics and reaction behavior. At the inlet, all velocities, volume fractions, turbulent energies and their dissipation rates of gas phase and particle phase were specified by the expressions proposed by Zheng et al. (2001), while the mass fractions of lumps were specified constant, which were determined by operating data of commercial TSRFCC unit. At the wall, both gas phase and particle phase obeyed no-slip conditions. Fully developed flow conditions were used at the outlet, and axial conditions were applied at the axis for all variables.

4. Simulation on commercial TSRFCC riser reactor 4.1. Commercial TSRFCC riser reactor The length and diameter of the first-stage riser of the commercial TSRFCC unit simulated is 12.81 and 0.35 m, respectively, that of the second-stage riser is 10.240 and 0.305 m, respectively. Two feedstocks were considered in this study: Dongxin vacuum gas oil (VGO) (Feedstock A) and Gudao VGO (Feedstock B), both with 10% vacuum resid (VR). The feedstock properties and operating conditions are presented in Tables 6 and 7, respectively.

3. Validation of gas–particle turbulent model 4.2. Computational scheme

The k −  − kp − p −  gas–solid turbulent flow model adopted in this work was first validated with the cold-flow experimental data of Bader et al. (1988) and Yang (1991). The operating

The material flow of TSRFCC-I process was shown in Fig. 4, where, A0 represents the fresh feedstock entering the first-stage riser, and A1 and A2 denote the HCO product of the first-stage and second-stage riser, respectively. A3 is the HCO leaving the FCC unit. A4 represents the feedstock entering the second-stage riser and is calculated as shown in Fig. 4. B1 and B2 denote all the cracking products except HCO of the first-stage and second-stage riser, respectively. C0 represents the regenerated catalyst, C1 and C2 are the coked catalyst. In the present work, the regeneration of catalysts is not simulated. It is supposed that the catalysts entering the first-stage and second-stage risers are sufficiency regenerated and the catalyst activity recovers to the initial catalyst activity. According to the material flow of TSRFCC-I process, it is known that the flux and properties of feedstock entering the second-stage

Table 5 Conditions used in the simulation for comparison with experiments. Item

Bader et al.

Yang (I)

Yang (II)

Particle type Particle diameter (m) Particle density (kg/m3 ) Particle mass flux (kg/(m2 s)) Superficial gas velocity (m/s) Diameter of the riser (m) Height of the riser (m)

FCC 76 1714 98 3.70 0.305 11.505

FCC 54 1545 92 4.33 0.14 11

FCC 54 1545 10 4.33 0.14 11

0.35 0.30 0.25

Experimental data Prediction

0.20 0.15

X = 4.0m

0.10 0.05 0.00 0.0

0.2

0.4

0.6 r/R

0.8

1.0

Particle volume fraction

0.16 Particle volume fraction

particle volume fraction

0.40

0.14 0.12 Experimental data Prediction

0.10 0.08 0.06

X = 4.0m

0.04 0.02 0.00 0.0

0.2

0.4

0.6

0.8

1.0

0.16 0.14 0.12 0.10 0.08 0.06 0.04 0.02 0.00 0.0

Experimental data Prediction X = 3.2 m

0.2

r/R Fig. 2. Radial profiles of particle volume fraction. (a) Bader et al., (b) Yang (I) and (c) Yang (II).

0.4

0.6 r/R

0.8

1.0

3852

X. Lan et al. / Chemical Engineering Science 64 (2009) 3847 -- 3858

8

10

12

Experimental data

Experimental data

8

8

X = 4.0m

6 4 2 0

7

Prediction X = 5.6m

Velocity, m/s

Prediction

Velocity, m/s

Velocity, m/s

10

6 4 2

0.4

0.6

0.8

1.0

0.0

4 Experimental data

3

Prediction X = 6.6m

1

-2 0.2

5

2

0 0.0

6

0.2

0.4

r/R

0.6

0.8

1.0

0 0.0

0.2

0.4

0.6

0.8

1.0

r/R

r/R Fig. 3. Radial profiles of particle velocity. (a) Bader et al., (b) Yang (I) and (c) Yang (II).

Table 6 Feedstock properties. Item

Feedstock A

Feedstock B

Density (g/cm3 at 20 ◦ C) Molecular weight Conradson carbon residue (wt%) Group analysis (wt%) Saturates Aromatics Resins Asphaltenes Distillation (◦ C) IBP 10% 30% 50% 70% 90% EP

891.2 1.74

927.4 389 2.12

66.44 22.50 8.78 2.28

64.37 22.74 10.97 1.92

336 391 423 444 474 530 549

B1 + B2 B1 + B2

C1

A1 + B1

A2 + B2

C2

A1 + A2

295 388 420 440 472 522 543

riser-1

riser-2

Table 7 Operating conditions of commercial TSRFCC unit. Operating conditions

Case I Feedstock A

Case II Feedstock B

First-stage Reaction temperature (◦ C) CTO Pressure drop (kPa) Outlet pressure (kPa) Flux of fresh feedstock (kg/s) Inlet temperature of fresh feedstock (◦ C) Flux of regenerated catalysts (kg/s) Inlet temperature of regenerated catalysts (◦ C) Flux of pre-lift steam (kg/s)

500 5.45 36.55 263 4.05 267 22.06 691 0.12

505 5.25 32.56 251 3.71 270 19.50 698 0.12

Second-stage Reaction temperature (◦ C) CTO Pressure drop (kPa) Outlet pressure (kPa) Flux of HCO (kg/s) Inlet temperature of HCO, (◦ C) Flux of regenerated catalysts (kg/s) Inlet temperature of regenerated catalysts (◦ C) Flux of pre-lift steam (kg/s)

506 6.07 41.70 263 1.08 365 6.58 691 0.056

510 5.62 53.35 251 1.11 365 6.24 698 0.056

riser are determined by cracking reactions happening in the firststage riser as well as the second-stage riser. The second-stage riser is strongly interrelated with the first-stage riser. In the simulation process, except for the normal iterations of the solution loop in an

A0

A3

C0 A4 = A1 + A2 - A3 Fig. 4. Material flow of TSRFCC-I process.

Table 8 Commercial data and predicted results of product yields in TSRFCC unit. Product yield (wt%)

Case I Commercial

Predicted

Commercial

Predicted

Dry gas LPG Gasoline Diesel HCO Coke

3.82 12.85 46.98 28.95 1.33 6.07

3.95 12.62 45.94 29.29 2.07 6.13

3.38 11.34 42.12 32.20 4.35 6.61

3.59 11.67 41.63 31.89 4.23 6.99

Case II

X. Lan et al. / Chemical Engineering Science 64 (2009) 3847 -- 3858

25 First-stage riser

0.05 0.04

Particle velocity, m/s

Particle volume fraction

0.06

3853

First-stage riser Second-stage riser

0.03 0.02 0.01

Second-stage riser

20 15 10 5 0

0.00 0.00

0.03

0.06

0.09 r,m

0.12

0.15

0.18

0.00

0.03

0.06

0.09 r,m

0.12

0.15

0.18

Fig. 5. Radial profiles of particle volume fraction and particle velocity in TSRFCC risers.

55

1.0 First-stage riser

First-stage riser Second-stage riser

0.8 Decay function

Gasoline yield, wt%

0.9

Second-stage riser

50

45

40

0.7 0.6 0.5

35

0.4 30 0.00

0.03

0.06

0.09 r,m

0.12

0.15

0.18

Fig. 6. Radial profiles of gasoline yield in TSRFCC risers.

individual riser, several iterations between the two risers must be performed to obtain the material balance of the second-stage riser. 4.3. Results and discussion Table 8 compares the predicted product yields of two feedstocks in the TSRFCC unit with available plant data. The satisfactory agreement of predicted and plant data indicates that the derived model can simulate the performance of commercial TSRFCC riser reactors. The results show that the flow and reaction behavior in Cases I and II is similar, so the following predictions were presented for Case I. Fig. 5 shows the predicted particle phase volume fraction and particle phase velocity in the exit of two risers. The flow behavior of TSRFCC risers is similar to that of the conventional riser shown in Figs. 2 and 3. The particle volume fractions are low and relatively flat in the central region and rapidly increase near the wall, and the predicted particle phase flow pattern is nearly parabolic. The particle velocity of the first-stage riser is higher than that of the second-stage riser due to the higher particle flux and gas velocity in the first riser. Since catalytic cracking reactions must occur over the catalyst, the catalyst particle volume fraction has a great effect on the yield of cracking products. Fig. 6 illustrates the non-uniform radial distribution of gasoline yield in the exit of two risers. The difference of gasoline yield between center and wall region is approximately 4 wt%. The distribution of gasoline yield is essentially influenced by gas–particle flow behavior. From the center to the wall, the cracking

0.3 0

4

8

12

16

20

24

Riser height, m Fig. 7. The profiles of decay function along riser height.

extent is improved due to higher particle concentration and longer residence time, which results in an increase of gasoline yield. Fig. 7 shows the change of the decay function of catalysts along the riser height. For TSRFCC technology, the deactivated catalysts are replaced by regenerated catalysts in the second-stage riser. Hence, the catalyst activity is renewed at the entrance of the second riser. Whether in the first-stage or second-stage riser, the catalyst activity decreases sharply in the riser entry zone, and then slowly in the latter half of the riser. The relative activity at the riser exit is only one third of the initial value. This distribution of catalyst activity has a significant influence on the cracking reactions occurring in TSRFCC riser reactors. Fig. 8 shows the profiles of the overall conversion and cracking product yields along the height of two risers, corresponding to the change of the decay function of catalysts. Generally, the feedstock conversion (defined as the sum of the yields of dry gas, LPG, gasoline, and coke) and product yields increase along the riser height. However, there are `bumps' in the curves when stepping from the first-stage to the second-stage risers, which is just the result as expected as TSRFCC-1 technology. In the TSRFCC-1 technology, the cracking products of the first-stage riser are separated from deactivated catalysts, and the HCO then enters the second-stage riser and continues to crack over regenerated catalysts. The catalyst activity is quite high in the entrance zone of the second-stage riser so that the cracking reactions progress rapidly. As a result, the product yields increase observably in the first one-third of the second-stage riser (the middle of the overall riser). In the conventional single riser, the

3854

X. Lan et al. / Chemical Engineering Science 64 (2009) 3847 -- 3858

80

15.0

60

Gasoline

50

Diesel

40 30 20

0 4

0

8

12

16

20

10.0

Second-stage riser 7.5 First-stage riser

5.0 2.5

Second-stage riser

First-stage riser

10

LPG Coke Drygas

12.5

Conversion

Product yield, wt%

Product yield, wt%

70

0.0

24

0

4

8 12 16 Riser height, m

Riser height, m

20

24

1.5

1.6

23.6

25.0

23.4

24.8 Disel yield, wt%

Disel yield, wt%

Fig. 8. The profiles of conversion and product yields along riser height.

23.2 23.0 Reaction temperature: 500°C

22.8

0.8

0.9

24.4

Reaction temperature: 505°C CTO: 5.25

24.2

CTO: 5.45

22.6 0.7

24.6

1.0 1.1 1.2 1.3 Residence time, s

1.4

1.5

24.0 0.9

1.0

1.1 1.2 1.3 1.4 Residence time, s

Fig. 9. Diesel yields of first-stage riser at various residence time. (a) Feedstock A and (b) Feedstock B.

product yields increase rapidly in the first one-third of the riser height, and then vary gently. Compared with the conventional single riser FCC, TSRFCC-1 technology significantly improves the product yields. In some single riser FCC units, the diesel yield reaches a maximum at about half the riser height and then declines due to overcracking reactions (Gao et al., 1999). In the TSRFCC-1 technology, the diesel product is separated when its yield is going to decrease, and undesirable second cracking is terminated. Furthermore, the sequent cracking reactions of HCO in second-stage riser produce more diesel products. As a whole, TSRFCC-I technology increases the diesel yield substantially. 5. Optimization study For the TSRFCC-1 technology, designed to improve product distribution, the operating conditions such as residence time, reaction temperature, and CTO determine its efficiency, especially the residence time of the first-stage riser. In the following study, the effects of residence time, reaction temperature, and CTO on the product yields will be investigated by numerical simulation. Cases I and II are the base cases for the optimization study, and their operating conditions are given in Table 7. As changing one of the operation conditions, all the other conditions were kept same as the base cases. 5.1. Residence time It is known that catalytic cracking is a complex parallel-series reaction system, and the diesel is the intermediate product. If the feed

Table 9 Product yields of Feedstocks A and B before and after optimized. Product yield (wt%)

Feedstock A Before optimized

Dry gas 3.95 LPG 12.62 Gasoline 45.94 Diesel 29.29 HCO 2.07 Coke 6.13

Feedstock B After optimized

Before optimized

After optimized

3.84 12.58 46.55 29.97 0.98 6.08

3.59 11.67 41.63 31.89 4.23 6.99

3.76 12.15 43.44 32.26 1.08 7.31

conversion is relatively high, the secondary reaction of diesel leads to a decrease of its yield. TSRFCC-I technology separates designedly the diesel when its yield is no more increasing in the first-stage riser. Hence, for different feedstocks, there is an optimum residence time in the first-stage riser to obtain high diesel yield. Fig. 9 shows the diesel yield of the first-stage riser as a function of residence time for Feedstocks A and B, where the variation of residence time was carried out by varying the riser height. The maximum diesel yields of Feedstocks A and B are 23.50 wt% at a residence time of 0.97 s and 24.80 wt% at 1.37 s, respectively. In the commercial operation, the residence times of Feedstocks A and B in the first-stage riser were 1.13 and 1.20 s, respectively. So, the diesel yields in the commercial TSFCC unit were less than optimum due to overcracking of Feedstock A and undercracking of Feedstock B. Feedstock A, a paraffinic feedstock, more easily undergoes cracking reactions than Feedstock B, a middle-naphthenic feedstock.

30

30

25

25 Disel yield, wt%

Disel yield, wt%

X. Lan et al. / Chemical Engineering Science 64 (2009) 3847 -- 3858

20 480°C

15

490°C

10

500°C

3855

20 486°C

15

496°C 505°C

10

515°C

510°C

5

5

520°C

525°C

0

0 0

2

4 6 8 10 First-stage riser height, m

0

12

2

4

6

8

10

12

First-stage riser height, m

Fig. 10. Diesel yields along first-stage riser height at various reaction temperatures. (a) Feedstock A and (b) Feedstock B.

Table 10 Maximum diesel yield at various temperatures for Feedstock A.

Table 11 Product yields at various reaction temperatures.

Reaction temperature (◦ C)

First-stage riser height (m)

Maximum diesel yield (wt%)

480 490 500 510 520

12.4 11.4 10.6 9.8 9.0

21.24 22.37 23.49 24.60 25.72

To obtain more diesel, for Feedstock A, the residence time in the first-stage riser should be shortened, while it should be prolonged for Feedstock B. Table 9 shows the final product yields of the TSRFCC unit on the conditions that the residence times in the first-stage riser are adjusted to optimum times shown in Fig. 9 and other operating conditions are kept unchanged. For Feedstock A, the residence time in the first-stage riser is shortened from 1.13 to 0.97 s, the final yields of diesel and light oil (gasoline and diesel) increase by 0.68 and 1.29 wt%, respectively. For Feedstock B, the residence time is prolonged from 1.20 to 1.37 s, the final yields of diesel and light oil increase by 0.37 and 2.18 wt%, respectively. 5.2. Reaction temperature In the above study, the variation of residence time was carried out by varying the riser height. Since a change of riser height for high diesel yield is not a feasible option for existing units, reaction temperature is considered to vary. One of the characteristics of TSRFCC technology is `subsection reaction'. The reaction temperature of first-stage and second-stage risers can be manipulated individually to obtain good product yields. Fig. 10 illustrates the diesel yields along the first-stage riser height at various reaction temperatures for Feedstocks A and B. From 480 to 520 ◦ C, the diesel yield of Feedstock A increases rapidly at the first 5 m and then decreases slightly in the second half. There is a maximum diesel yield at various riser heights for various temperatures, shown in Table 10. High temperature and correspondingly short residence time in the first riser is desirable to achieve high diesel yields. The trend of the diesel yield of Feedstock B along the first riser height is different from that of Feedstock A. The diesel yield increases monotonically along the riser height, and no decrease is observed even though reaction temperature increases. Compared to Feedstock A, a more severe cracking is required for Feedstock B in the first-stage riser.

Feed

A

B

Reaction temperature (◦ C) (first-stage/ second-stage)

Product yield (wt%)

Dry gas

LPG

Gasoline

Diesel

HCO

Coke

480/506 490/506 500/506 510/506 520/506

3.57 3.76 3.95 4.16 4.37

12.44 12.62 12.80 12.98 13.15

47.86 47.44 46.99 46.52 46.02

27.57 28.25 28.91 29.53 30.12

2.55 1.83 1.17 0.55 0.01

6.01 6.10 6.18 6.26 6.33

500/488 500/497 500/506 500/516 500/525

3.86 3.91 3.95 4.00 4.05

12.67 12.74 12.80 12.87 12.93

46.75 46.87 46.99 47.10 47.20

28.49 28.70 28.91 29.11 29.29

2.13 1.63 1.17 0.70 0.27

6.10 6.15 6.18 6.22 6.26

486/509 496/509 505/510 515/510 525/511

3.30 3.44 3.59 3.74 3.90

11.50 11.59 11.67 11.75 11.82

41.71 41.69 41.63 41.52 41.39

30.44 31.18 31.89 32.56 33.20

6.22 5.18 4.23 3.36 2.57

6.83 6.92 6.99 7.07 7.12

505/488 505/500 505/510 505/519 505/528

3.49 3.54 3.59 3.64 3.69

11.49 11.58 11.67 11.77 11.84

41.38 41.51 41.63 41.73 41.83

31.31 31.60 31.89 32.16 32.42

5.43 4.82 4.23 3.66 3.13

6.90 6.95 6.99 7.04 7.09

Table 11 shows the product yields of Feedstocks A and B at various reaction temperatures. Increasing the reaction temperature of the first or second risers, results in a higher conversion and yields of dry gas, LPG, diesel and coke, except for gasoline yield. Increased reaction temperature of the first-stage riser intensifies cracking reactions and decreases the amount of HCO into the second-stage riser, consequently the gasoline yield decreases slightly. Even though improving reaction temperatures of the first and second risers can enhance the cracking of feedstock, its influence on product distribution is different. Fig. 11 compares the diesel selectivity and light oil yield of Feedstocks A and B at various reaction temperatures. For Feedstock A, when the reaction temperature of the first-stage riser increases from 480 to 520 ◦ C, the diesel selectivity improves by 1.83%, and the light oil yield increases by 0.71 wt%. As the temperature of second-stage riser varies from 488 to 525 o C,

3856

X. Lan et al. / Chemical Engineering Science 64 (2009) 3847 -- 3858

34.5 First-stage Second-stage

30.0

Disel selectivity, %

Disel selectivity,%

30.5

29.5 29.0 28.5

33.5 33.0 32.5 32.0

28.0 480

490 500 510 520 Reaction temperature, °C

530

480

490 500 510 520 Reaction temperature, °C

530

75.0

77.0

74.5

First-stage Second-stage

76.5

Light oil yield, wt%

Light oil yield, wt%

First-stage Second-stage

34.0

76.0 75.5

First-stage Second-stage

74.0 73.5 73.0 72.5 72.0

75.0 480

490 500 510 520 Reaction temperature, °C

530

480

490 500 510 520 Reaction temperature, °C

530

Fig. 11. Effect of reaction temperature on diesel selectivity and light oil yield. (a,b) Feedstock A and (c,d) Feedstock B.

the diesel selectivity improves by 0.26%, and the light oil yield increases by 1.25 wt%. Clearly, the first-stage riser temperature has a pronounced effect on diesel selectivity, whereas the effect of secondstage riser temperature is more significant on light oil yield. However, Feedstock B responds differently to reaction temperature. The second-stage riser temperature has a less prominent effect on diesel selectivity and light oil yield than the first-stage riser temperature.

Table 12 Product yields at various CTO's. Feed

A

5.3. Catalyst-to-oil ratio Another characteristic of TSRFCC-I technology is `catalyst relay'. The coked catalysts are separated from the oil products at the exit of the first-stage riser, and the regenerated catalysts with good activity and selectivity are introduced to the second-stage riser. This allows good catalyst utilization and increases the overall catalytic reactions. The CTO can also be optimized to improve product distribution. The effect of CTO of the first-stage and second-stage risers on the product yields of Feedstocks A and B were shown in Table 12. For Feedstocks A and B, the yields of dry gas, LPG, gasoline, and coke increase with increasing the CTO of the first or second riser, except for the diesel yield. As mentioned above, for Feedstock A, the residence time of the first riser is a little long so that the diesel undergoes secondary cracking reactions. Increasing the CTO further leads to more overcracking, and hence decreases the diesel yield. For feedstock B, though no diesel overcracking is observed in the first-stage riser at 505 ◦ C and CTO 5.27, as the CTO varies from 5.27 to 8.27, the overcracking reactions of diesel oil increase gradually, which results in a decrease of diesel yield. Fig. 12 compares the diesel selectivity and the light oil yield of Feedstocks A and B at various CTO's. The CTO of the first-stage riser has a more pronounced effect on diesel selectivity than that of the

B

CTO (first-stage/ second-stage)

Product yield (wt%)

Dry gas

LPG

Gasoline

Diesel

HCO

Coke

4.45/6.07 5.45/6.07 6.45/6.07 7.45/6.07 8.45/6.07

3.85 3.95 4.03 4.10 4.15

12.58 12.80 12.98 13.12 13.25

46.47 46.99 47.40 47.72 47.99

29.28 28.91 28.59 28.32 28.08

1.74 1.17 0.73 0.41 0.15

6.08 6.18 6.27 6.33 6.38

5.45/5.07 5.45/6.07 5.45/7.07 5.45/8.07 5.45/9.07

3.92 3.95 3.98 4.01 4.03

12.69 12.80 12.89 12.96 13.02

46.68 46.99 47.23 47.41 47.57

28.87 28.91 28.95 28.97 28.99

1.71 1.17 0.72 0.37 0.08

6.13 6.18 6.23 6.28 6.31

4.275.62 5.27/5.62 6.27/5.62 7.27/5.62 8.27/5.62

3.51 3.59 3.65 3.70 3.74

11.51 11.67 11.80 11.89 11.97

40.91 41.63 42.16 42.58 42.92

32.14 31.89 31.67 31.49 31.33

5.02 4.23 3.65 3.21 2.87

6.91 6.99 7.07 7.13 7.17

5.27/4.62 5.27/5.62 5.27/6.62 5.27/7.62 5.27/8.62

3.54 3.59 3.62 3.65 3.68

11.51 11.67 11.80 11.90 11.99

41.32 41.63 41.86 42.04 42.18

31.77 31.89 31.99 32.06 32.12

4.94 4.23 3.67 3.23 2.87

6.92 6.99 7.06 7.12 7.16

second-stage riser. For Feedstock A, when the CTO of the first-stage riser varied from 4.45 to 8.45, the light oil yield increased by 0.32 wt%, while when the CTO of the second-stage riser ranged from 5.07 to

X. Lan et al. / Chemical Engineering Science 64 (2009) 3847 -- 3858

3857

34.0

30.0

First-stage

Disel selectivity, %

Disel selectivity, %

First-stage

29.5

Second-stage

29.0

28.5

33.5

Second-stage

33.0

32.5

32.0

28.0 4

5

6

7 CTO

8

9

10

4

6

7

8

9

7

8

9

CTO

74.5

77.0 First-stage

First-stage

Light oil yield, wt%

Light oil yield, wt%

5

Second-stage

76.5

76.0

75.5

Second-stage

74.0

73.5

73.0

75.0 4

5

6

7 CTO

8

9

10

4

5

6 CTO

Fig. 12. Effect of CTO on diesel selectivity and light oil yield. (a,b) Feedstock A and (c,d) Feedstock B.

9.07, it increased by 1.01 wt%. The CTO of the second-stage riser has a pronounced effect on light oil yield. For Feedstock B, the CTO's of the first and second riser have an equivalent influence on the light oil yield. On all accounts, for Feedstock A, which has cracked to a large extent in the first riser, further increasing the reaction temperature and CTO to enhance cracking in the first-stage riser has not a pronounced action on product distribution. Moreover, it handicaps the function of the second-stage riser, due to the decrease of HCO feedstock entering the second riser. Increasing further reaction temperature and CTO of the second-stage riser can intensify the cracking reaction of HCO over regenerated catalysts, consequently produce more LPG, gasoline, and diesel, hence is favorable for product distribution. For Feedstock B, whose cracking extent is not adequate in the first riser, further increasing the reaction temperature and CTO in the first or second riser can improve the conversion of feedstock and ameliorates the product distribution. For TSRFCC-I technology, the cracking extent in the first and second riser should be matched to obtain optimum product distribution. The feedstock should crack to an appropriate extent in the first-stage riser, and then continue to carry out enhanced becomingly cracking reactions in the secondstage riser.

the interaction of turbulence between gas and particle phases, and a 14-lump kinetics model of catalytic cracking reactions, was used. The satisfactory agreement of simulated results with experimental and commercial data validated the developed CFD model. Optimization studies of two feedstocks cracking on the commercial TSRFCC unit were then carried out by numerical simulation. The results show that the paraffinic feedstock requires shorter residence time to achieve sufficient cracking in the first-stage riser for high diesel yield. Increasing the reaction temperature and CTO in the second-stage riser has a more pronounced effect on product distributions than subjecting the first-stage riser to severe operating conditions. The extent of cracking of middle-naphthenic feedstock is not adequate in the firststage riser, increasing further the reaction severity in both first- and second-stage risers to achieve desirable product yields. Optimizing the extent of cracking in first- and second-stage rises is the key to achieve good product yield for a given feedstock. The above results of optimization studies need to be validated more extensively by means of experimental data. In the future, it is our purpose to validate the results more extensively by means of complete experimental data sets. Nevertheless, the qualitative and quantitative results from CFD modeling are useful for the optimization of existing commercial TSRFCC units, as well as the design and development of TSRFCC technology.

6. Conclusions TSRFCC technology, a new developed FCC process, can significantly improve product distribution. The operation optimization is absolutely necessary in commercial applications of TSRFCC technology. Therefore, the CFD approach was applied to simulate the flow behavior and catalytic cracking reactions in TSRFCC riser reactors, and to carry out optimization studies. A k −  − kp − p −  gas–solid turbulent flow model, which considers the particles turbulence and

Notation Cc C1 , C2 , C3 gr gx k

content of coke on FCC catalysts, wt% constants gravity component in r coordinate direction, m/s2 gravity component in x coordinate direction, m/s2 turbulent kinetic energy, m2 /s2

3858

Ki p ps Qr Qs r S u v wi x Yi

X. Lan et al. / Chemical Engineering Science 64 (2009) 3847 -- 3858

rate constants of cracking reaction, m3 /s kg catalyst pressure, Pa particle pressure, Pa heat of cracking reactions, J/m3 s interphase heat transfer, J/m3 s radial position, m source axial velocity, m/s radial velocity, m/s reaction rates of cracking reaction, kg/m3 s axial position, m mass fraction of lump i

Greek letters



    e g p s g,t s,t  k ,  , Y , h ,  

volume fraction gas–particle drag coefficient, kg/m3 s collisional energy dissipation, kg/m3 s diffusion coefficient, kg/m s turbulent energy dissipation rate, m2 /s3 particle temperature, m2 /s3 effective viscosity of gas phase, N/m2 s laminar viscosity of gas phase, N/m2 s effective viscosity of particle phase, N/m2 s laminar viscosity of particle phase, N/m2 s turbulent viscosity of gas phase, N/m2 s turbulent viscosity of particle phase, N/m2 s density, kg/m3 Prandtl number of turbulent diffusion general variable

Subscripts g i p

gas phase lump solid phase

Acknowledgments The authors acknowledge the support by the National Natural Science Foundation of China through the programs for Distinguished Young Scholars of China (Grant nos. 20725620 and 20525621) and the programs “Multiple Scale Analysis and Scaling-up of Direct Coupled Dual Gas–Solid Fluidized Reaction Systems” (no. 20490202). References Bader, R., Findlay, J., Knowlton, T.M., 1988. Gas/solids flow patterns in a 30.5 cm diameter circulating fluidized bed. In: Basu, P., Large, J.F. (Eds.), Circulating Fluidized Bed Technology 2. Pergamon Press, Oxford, UK, pp. 123–137. Benyahia, S., Arastoopour, H., Knowlton, T.M., Massah, H., 2000. Simulation of particles and gas flow behavior in the riser section of a circulating fluidized bed using the kinetic theory approach for the particulate phase. Powder Technology 112, 24–33.

Bolio, E.J., Yasuna, J.A., Sinclair, J.L., 1995. Dilute turbulent gas–solid flow in risers with particle–particle interactions. A.I.Ch.E. Journal 41, 1375–1388. Chan, C.K., Guo, Y.C., Lau, K.S., 2005. Numerical modeling of gas–particle flow using a comprehensive kinetic theory with turbulence modulation. Powder Technology 150, 42–55. Chen, Y., 2006. Recent advances in FCC technology. Powder Technology 163, 2–8. Cheng, Y., Guo, Y., Wei, F., Jin, Y., Lin, W., 1999. Modeling the hydrodynamics of downer reactors based on kinetic theory. Chemical Engineering Science 54, 2019–2027. Das, A.K., Baudrez, E., Marin, G.B., Heynderickx, G.J., 2003. Three-dimensional simulation of a fluid catalytic cracking riser reactor. Industrial & Engineering Chemistry Research 42, 2602–2617. Dasgupta, S., Jackson, R., Sundaresan, S., 1994. Turbulent gas–particle flow in vertical risers. A.I.Ch.E. Journal 40, 215–228. Dupain, X., Makkee, M., Moulijn, J.A., 2006. Optimal conditions in fluid catalytic cracking: a mechanistic approach. Applied Catalysis A: General 297, 198–219. Gao, J., Xu, C., Lin, S., 2006. Advanced reaction-terminating technique for FCC riser reactor. Petroleum Science and Technology 24, 367–378. Gao, J., Xu, C., Lin, S., Yang, G., Guo, Y., 1999. Advanced model for turbulent gas–solid flow and reaction in FCC riser reactors. A.I.Ch.E. Journal 45, 1095–1113. Gao, J., Xu, C., Lin, S., Yang, G., Guo, Y., 2001. Simulations of gas–liquid–solid 3-phase flow and reaction in FCC riser reactors. A.I.Ch.E. Journal 47, 677–692. Gidaspow, D., 1994. Multiphase Flow and Fluidization: Continuum and Kinetic Theory Description. Academic Press, Boston. Han, W.D., Huang, R.K., Gong, J.H., 2006. Commercial application of new FCC process MIP-CGP. Petroleum Refinery Engineering 36, 1–4. Henry, B.E., Wachter, W.A., Swan, G.A., 2002. Fluid cat cracking with high olefins production. US patent, US. Hrenya, C.M., Sinclair, J.L., 1997. Effects of particle-phase turbulence in gas–solid flows. A.I.Ch.E. Journal 43, 853–869. Lin, S.X., 2000. Petroleum Refining. Petroleum Industry Press, Beijing. Nayak, S.V., Joshi, S.L., Ranade, V.V., 2005. Modeling of vaporization and cracking of liquid oil injected in a gas–solid riser. Chemical Engineering Science 60, 6049–6066. Neri, A., Gidaspow, D., 2000. Riser hydrodynamics: simulation using kinetic theory. A.I.Ch.E. Journal 46, 52–67. Nieuwland, J.J., Annaland, M.V.S., Kuipers, J.A.M., Swaaij, W.P.M., 1996. Hydrodynamic modeling of gas/particle flows in riser reactors. A.I.Ch.E. Journal 42, 1569–1582. Patankar, S., 1980. Numerical Heat Transfer and Fluid Flow. Hemisphere, Washington DC. Pita, J.A., Sundaresan, S., 1993. Developing flow of a gas–particle mixture in a vertical riser. A.I.Ch.E. Journal 39, 541–552. Samuelsberg, A., Hjertager, B.H., 1996. Computational modeling of gas/particle flow in a riser. A.I.Ch.E. Journal 42, 1536–1546. Schnaith, M.W., Sexson, P.A., True, D.R., 1998. New cracking processes have good reliability. Oil & Gas Journal 96, 53–58. Shan, H.H., Dong, H.J., Zhang, J.F., Niu, G.L., 2001. Experimental study of two-stage riser FCC reactions. Fuel 80, 1179–1185. Shan, H.H., Zhang, J.F., Yang, C.H., Ye, Z.G., 2006. Improving FCC product distribution with two-stage riser technology. Petroleum Science and Technology 24, 379–387. Sinclair, J.L., Jackson, R., 1989. Gas–particle flow in a vertical pipe with particle–particle interactions. A.I.Ch.E. Journal 35, 1473–1486. Theologos, K.N., Lygeros, A.I., Markatos, N.C., 1999. Feedstock atomization effects on FCC riser reactors selectivity. Chemical Engineering Science 54, 5617–5625. Theologos, K.N., Markatos, N.C., 1993. Advanced modeling of fluid catalytic cracking riser-type reactors. A.I.Ch.E. Journal 39, 1007–1017. Theologos, K.N., Nikou, I.D., Lygeros, A.I., Markatos, N.C., 1997. Simulation and design of fluid catalytic-cracking riser-type reactors. A.I.Ch.E. Journal 43, 486–494. Wang, L.Y., Wang, G.L., Wei, J.L., 2003. New FCC process minimizes gasoline olefin, increases propylene. Oil & Gas Journal 101, 52–58. Xie, C.G., 1997. Commercial application of deep catalytic cracking catalysts for production of light olefins. Petroleum Technology 26, 825. Yang, Y.L., 1991. Experimental and Theoretical Studies on Hydrodynamics in Cocurrent Upward and Downward Circulating Fluidized Beds. Tsinghua University, Beijing, China. Zhang, P., 2005. Numerical Simulation on Catalytic Cracking Reaction in Two-stage Riser Reactors. China University of Petroleum, Beijing, China. Zheng, Y., Wan, X., Qian, Z., Wei, F., Jin, Y., 2001. Numerical simulation of the gas–particle turbulent flow in riser reactor based on k −  − kp − p −  two-fluid model. Chemical Engineering Science 56, 6813–6822.