gupta (2010)
TRANSCRIPT
-
8/11/2019 Gupta (2010)
1/42
INTERNATIONAL JOURNAL OF CHEMICAL
REACTORENGINEERING
Volume8 2010 ReviewR6
Modeling of Fluid Catalytic Cracking Riser
Reactor: A Review
Raj Kumar Gupta Vineet Kumar
V.K. Srivastava
Thapar University, [email protected] Institute of Technology Roorkee, [email protected] Institute of Technology, [email protected]
ISSN 1542-6580
Copyright c2010 The Berkeley Electronic Press. All rights reserved.
-
8/11/2019 Gupta (2010)
2/42
Modeling of Fluid Catalytic Cracking Riser Reactor:
A Review
Raj Kumar Gupta, Vineet Kumar, and V.K. Srivastava
Abstract
This work aims at compiling the important works on the modeling of a fluid
catalytic cracking (FCC) riser reactor. The modeling of a riser reactor is very
complex due to complex hydrodynamics and unknown multiple reactions, coupledwith mass transfer resistance, heat transfer resistance and deactivation kinetics.
A complete model of the riser reactor should include all the important physical
phenomena and detailed reaction kinetics. As the computational fluid dynamics
(CFD) is emerging as a powerful tool for modeling the FCC riser, various works
on riser modeling using CFD are also included in the paper.
KEYWORDS: fluid catalytic cracking, riser modeling, riser kinetics, riser hydro-
dynamics, CFD modeling
Please send correspondence to Raj Kumar Gupta, phone: +91-175-2393442; email:
-
8/11/2019 Gupta (2010)
3/42
1.
Introduction
Fluid catalytic cracking unit (FCCU) converts heavy hydrocarbon petroleum
fractions into more usable products such as gasoline, middle distillates, and light
olefins. This unit mainly consists of a riser reactor, a catalyst stripper, and a
regenerator. Fluid Catalytic cracking (FCC) is the most important and profitableprocess in petroleum refining industry (Marcilly, 2003).
Riser reactor is the most important part of this unit as the cracking
reactions take place in the riser. Modern FCC units have short diameter risers(0.8-1.2 m) with lengths varying from (30-40 m). In the riser reactor, the contact
time between the gas oil and the catalyst is very short (less than 5 seconds). At the
bottom of the riser, the gas oil feed comes in contact with the hot regeneratedcatalyst coming from the regenerator and consequently vaporizes. As a result, the
cracking reactions start and the density of the oil decreases causing an increase in
the velocity of the vapor/gas phase. The increasing gas phase velocity accelerates
the velocity of the catalyst and the riser behaves as a transport bed reactor. Thecracking reactions by product (coke) gets deposited on the catalyst surface and
decreases its activity as the catalyst moves toward the exit of the riser. At the riser
exit, the deactivated (spent) catalyst is separated from the hydrocarbon productsvapor through specially designed riser termination device and sent to the
regenerator for burning off the coke from its surface. The product vapors are sent
to the main fractionator for recovery.Many researchers have worked on the various aspects of riser modeling.
Corella and Frances (1991a) reviewed the works related to FCC riser modeling
and listed some of the assumptions made by the early workers. Biswas and
Maxwell (1990) discussed the process and catalyst related developments in fluidcatalytic cracking process. Otterstedt et al. (1986) reviewed the problems
associated with fluid catalytic cracking of heavy oil fractions. This work aims at
compiling the work done by various researchers for modeling the different aspectsof fluid catalytic cracking riser reactor.
2.
Riser Modeling
Modeling of riser reactor is very complex due to complex hydrodynamics,
unknown multiple reactions coupled with mass transfer and heat transferresistances. Also, the conditions keep changing all along the riser height due to
cracking which causes molar expansion in the gas phase and influences the axial
and radial catalyst density in the riser. In the literature, numerous models of FCCriser are available with varying degrees of simplifications and assumptions. A
complete physical model of the FCC riser reactor should include all the
phenomena shown in Figure 1.
Gupta et al.: Modeling of Fluid Catalytic Cracking Riser Reactor: A Review
Published by The Berkeley Electronic Press, 2
-
8/11/2019 Gupta (2010)
4/42
Figure 1. Physical model of gas-liquid-solid flow and reaction in FCC riser
reactor (Source: Gao et al., 2001)
In the present work, various aspects of riser modeling are organized into:feed atomization and vaporization, hydrodynamics, cracking kinetics, interphase
heat transfer and mass transfer, and catalyst deactivation.
2.1. Feed atomization and vaporization
Vaporization of liquid feed is a key step in the FCC reaction process. In an FCC
riser reactor, liquid feed is sprayed into a flow of hot, fluidized catalyst. Feedmolecules are cracked only after they are transported in the vapor phase to an
active site in the solid catalyst. The gas oil is fed into the riser through feed
Characteristics of gas
phase flow and reaction
Gas
phase
Momentum
transfer
Heat
transfer
Mass
Transfer
Turbulent
energy transfer
Turbulent flow characteristics of
catalyst particle phase
Solid
phase
Spray
phase
Flow and vaporization
characteristics of feed spray phase
2 International Journal of Chemical Reactor Engineering Vol. 8 [2010], Review
http://www.bepress.com/ijcre/vol8/R6
-
8/11/2019 Gupta (2010)
5/42
nozzles. The size of feed droplet affects the vaporization rate and hence the
performance of the riser.
Atomization of feed into fine drops facilitates high rates of heat transfer
between catalyst and feed and thus fast vaporization of the feed drops. Whereas,large feed drops vaporize slowly leading to low gas velocities in the riser entry
zone thus lowering the drag force exerted on the catalyst. Slow vaporization offeed also leads to very high catalyst to vaporized feed ratio coupled with high
catalytic activity and higher temperature in the riser entry zone. These factors can
lead to undesirable secondary cracking reactions. Dean et al. (1982) showed that
the heat-transfer-rate between feed droplets and catalyst particles variesexponentially with droplet size. The smaller droplet diameter leads to faster
evaporation rates, better mixing with the catalyst, and uniform cooling of the
catalyst.Faster vaporization rates can be realized by effective feed atomization into
fine drops (Mauleon and Courelle, 1985; Avidan et al., 1990). Most of the newdevelopments related to feed injection systems therefore have their primaryobjective as the atomization of feed into very minute drops (Johnson et al., 1994).
Mauleon and Courcelle (1985) obtained the experimental data, for various initial
droplet sizes, for feed atomization nozzles (Table 1) for a nozzle exit velocity of
50 m/s.
Table 1. Experimental data for feedstock atomization (Source: Mauleon and
Courcelle, 1985)
Droplet size (m) 500 100 30
Relative no. of droplets 1 125 4630Droplets per catalyst particle 0.001 0.11 4
Vaporization time (ms) for 50% vaporizationfor 90% vaporization
220 11 4
400 20 8
Johnson et al. (1994) showed that proper nozzle design could improve the
gas oil conversion by 1.4 wt% and gasoline yield by 5 wt%. Goelzer (1986) andBienstock et al. (1991) have reported the improvement in conversions and yield
patterns due to the replacement of feed injection system of older designs by newer
ones. Buchanan (1994) did extensive work on the heat-transfer coefficients ofgas/solids and liquid/gas/solids systems. He considered two different schemes for
the direct contact between droplets and catalyst particles: the first schemeassumes that infinitely fast heat transfer occurs as soon as a droplet contacts aparticle; the second scheme assumes that true direct contact between a droplet and
a hot particle is prevented by the Leidenfrost effect, that is, the vapors evolving
from the droplet surface push back the particle, and heat transfer occurs through a
Gupta et al.: Modeling of Fluid Catalytic Cracking Riser Reactor: A Review
Published by The Berkeley Electronic Press, 2
-
8/11/2019 Gupta (2010)
6/42
thin gas film. For typical FCC conditions, he found that the time required for
complete vaporization of a 100 m droplet ranges from 0.3 to 30 ms depending
on the model selection. He further showed that the time required to vaporize a
droplet was directly related to its size and concluded that the vaporization timeswere proportional to the 1.1 to 1.5 power of initial droplet diameter.
Mirgain et al. (2000) modeled the homogeneous vaporization (in gasphase) and heterogeneous vaporization (on collision with catalyst particles) of the
feed drops. Authors attempted to understand the physical phenomena affecting oil
vaporization by considering a conceptual mixing chamber and made the following
conclusions for FCC risers and downers: homogenous vaporization cannotvaporize feedstock droplets of the same size as used in current FCC feedstock
sprays, and mixing of the feedstock droplets into a vigorously agitated suspension
of hot catalyst particles is needed for complete, fast vaporization; the Leidenfrosteffect does not occur, and direct contact between droplets and particles is
unavoidable; the best results for heterogeneous vaporization are obtained with acatalyst jet of intermediate porosity (70-95%).
Nayak et al. (2005) proposed a phenomenological model to predict the
heat transfer coefficient of droplet vaporization in gassolid flow. The model
relates the evaporation rate of droplet with rate of collisions of solid particles,
specific heat capacities of solid and liquid, latent heat of vaporization, relativevelocity of gas and liquid and temperatures of three phases. With the help of one
adjustable parameter, the model captures the key features of heat transfer between
liquid drop and gassolid mixture. The model also accommodated the presence ofmultiple volatile components in feed oil and boiling of oil over a range of
temperatures instead of a specific boiling point. Authors used this approach to
simulate evaporation of liquid drops injected in FCC risers.
2.2. Hydrodynamics
After complete vaporization of feed, only solid phase (catalyst & coke) and vapor
phase (steam, hydrocarbon feed and product vapor) are left. The vapor phase
expands due to cracking and accelerates the solid phase. Both vapor and solidsmove upwards, and velocities of both phases keep on increasing along the riser
height. The simplest hydrodynamic models assume plug flow for both the phases.
However, there is considerable back mixing in the solid phase because of slipbetween the solid and vapor phase which makes the prediction of solid velocity
profile difficult. The gas-solid suspension density within the riser is greatlyinfluenced by both gas superficial velocity and solids mass flux, and therefore,
these operating parameters directly affect heat transfer, mass transfer, andchemical reaction rates (Berruti et al., 1995).
4 International Journal of Chemical Reactor Engineering Vol. 8 [2010], Review
http://www.bepress.com/ijcre/vol8/R6
-
8/11/2019 Gupta (2010)
7/42
Risers exhibit an axial solids holdup distribution showing densification at
the entry point of solids. The holdup decreases along the riser height as the solids
are accelerated by the gas (acceleration zone) and eventually the fully developed
flow condition is reached where the solids holdup is invariant with the riser height(fully developed flow region). At the outlet of the FCC riser, the riser termination
device enhances local back-mixing that results in an increase in the suspensiondensity. Some of the early studies provided some experimental evidence that the
riser flow structure consists of two characteristic regions: a dilute gas-solid
suspension travelling upwards in the center (core) and a dense phase of particle
clusters, or strands, moving downward along the wall (annulus). Such core-annulus structure is usually assumed for modeling the riser reactor.
In order to examine the gas-solid flow patterns, a CFB riser can generally
be divided into two distinct regions (Weinstein et al., 1984; Matsen, 1988). In thelower part of the CFB riser there is a dense region that is considered to be a
turbulent or bubbling fluidized region. In the upper part of CFB riser there is adilute region that is considered as a transport region. A third region ofdensification may be present depending on the exit geometry. Bai et al. (1992)
and Xu (1996) have considered five sections in CFB risers: acceleration,
developed bottom-dense, transition, top-dilute, and exit. An inflection point,Zinf,
was defined by Li and Kwauk (1980) and Li et al. (1981) to demarcate the lowerdense section and top-dilute section. Sabbaghan et al. (2004) considered lower
dense region, located right above the distributor, and the upper region. They
further divided the upper region into three zones: acceleration, fully developed,and deceleration or exit. In contrast to the upper dilute zone of the riser, where
several studies on local flow structure have been conducted, there exist only few
studies concerning the flow structure in the acceleration zone of a riser.Several modeling efforts, of CFB risers, employing different mathematical
formulations are reported in literature to predict the relationship between solidconcentration, operating conditions, and riser geometry. Harris and Davidson
(1994) proposed three broad categories of these models: (i) the models that
predict the axial variation of the solid suspension density, but not the radialvariation; (ii) the models that predict the radial variation and the high average slip
velocities by assuming two or more regions, such as core-annulus or clustering
annulus flow models; and (iii) the models which are based on the numerical
modeling of the conservation equations for mass, momentum, and energy for gasand solid phases. The type (i) models are mathematically straightforward and
compares well with the experimental data. However, the highly empirical natureof these models makes them unsuitable for design and scale-up purposes.Experimental evidence suggests that the core-annulus formulation of type (ii)
models better approximates the time-averaged radial flow structure in CFB risers
than the clustering annular models, especially in fast fluidization regime. Their
Gupta et al.: Modeling of Fluid Catalytic Cracking Riser Reactor: A Review
Published by The Berkeley Electronic Press, 2
-
8/11/2019 Gupta (2010)
8/42
main drawback is the requirement of experimental data. The type (iii) models are
the most rigorous, but the required simplifying assumptions limit their usefulness
for design purposes.
The selection of a particular type of model depends on its intendedapplication. Models of type (i) and type (ii) are best suited to investigate the effect
of operating conditions and riser dimensions on the riser flow structure. Thesemodels can be easily coupled with the reaction kinetic models to simulate the
performance of CFB risers (Pugsley et al., 1992; Bolkan-Kenny et al., 1994).
Type (iii) models are suitable to investigate the local flow structure and the
impact of geometry in CFB risers. Type (i) models account for increased solidsholdup higher than predicted by using single particle settling velocities.
Yerushalmi et al. (1976) experimentally studied the axial solids distribution in
CFB risers. They observed that the increased solids holdup causes the clusteringof particles. The clustering is responsible for large slip velocities measured
experimentally, because of the high settling velocity of the cluster as compared tothe single particle settling velocity.
For fully developed region in the industrial-scale FCC risers, Matsen
(1976) reported that the slip factor (), defined as the ratio of interstitial gas
velocity to average solids velocity, is approximately 2. For FCC powders van
Swaaij et al. (1970) reported slip factors in the range 1.6 2.2. Patience et al.(1992) developed an empirical correlation for calculating the slip factor,
considering the effect of particle characteristics, riser diameter, and gas velocity
on the slip factor:
41.00
47.0
6.5
1 tp FrFrV
U
(1)
The drag force is exerted on the particles by the carrier gas. This force
controls the slip velocity between the two-phases, and the acceleration of the
particulate phase. The drag coefficient, CD, can be estimated by standard drag
curve. Littman et al. (1993) showed that the drag curve may severely overestimatethe value of CD. Pugsley and Berruti (1996) modified the equation for standard
drag coefficient for use in their work.
Type (ii) models characterize the radial solids distribution and explain thereason for the higher solids holdups. At the riser wall, the velocity of the solid and
vapor stream is nearly zero and the effect of back mixing is also prominent. The
velocity is maximum at the center of the riser and minimum near the wall. Sincethe flow in the riser is turbulent, the wall effect is confined to a small portion of
the riser cross section. In the rest of the cross section the velocity is almost same.
Hence the flow can be divided into two regions; one is a turbulent core region inthe centre and an annulus region near the wall. Also, the radial measurements of
6 International Journal of Chemical Reactor Engineering Vol. 8 [2010], Review
http://www.bepress.com/ijcre/vol8/R6
-
8/11/2019 Gupta (2010)
9/42
particle velocity and solids flux are approximately parabolic, often with negative
velocities along the riser wall. Grace et al (1990) experimentally measured the
downward particle velocity at the riser wall ranging from 0.5 to 1.5 m/s.
A core-annulus type of flow pattern in CFBs has been shown to exist inseveral studies (Capes and Nakamura, 1973; Hartge et al., 1988; Bader et al.,
1988; Berruti and Kalogerakis, 1989; Tsou and Gidaspow, 1990; Rhodes, 1990;Samuelsberg and Hjertager, 1996; Sun and Gidaspow, 1999; Huilin and
Gidaspow, 2003). Brereton and Stromberg (1986), Jin et al. (1998), and
Schnitzlein and Weinstein (1988) showed in their works that the Geometry of the
CFB riser considerably influences its hydrodynamics. Zhou et al. (1994, 1995)measured the particle concentrations in the risers of square cross section and
predicted a core-annulus flow structure. Author predicted that the exit effects are
more significant in a square riser than in a riser of circular cross-section. van derMeer et al. (1999) studied the dimensionless groups for hydrodynamic scaling of
a CFB. Authors demonstrated that at least five dimensionless groups are requiredfor full hydrodynamic scaling of a CFB. Viitanen (1993) conducted tracer studieson the industrial scale riser reactor to obtain axial and radial dispersion
coefficients which are useful for modeling purposes.
Internal recirculation of solids in CFB risers occurs due to interchange of
solids between heterogeneous flow structures. In a FCC riser reactor, internalcirculation of deactivating catalyst particles affects the reactor performance. Wirth
(1991) developed a model for the momentum transfer arising from collisions
between discrete particles and clusters dispersed throughout the riser cross-section. Pugsley and Berruti (1995) modified the model of Wirth (1991) by
considering the solids flow in core and annulus regions and calculated the core-to-
annulus solids interchange coefficient. Senior and Brereton (1992) showed that avalue of 0.2 m/s for core-to-annulus solid interchange coefficient gave the best fit
of their experimental data of axial suspension density profile. Pugsley and Berruti(1996) presented a type (ii) predictive model based on fundamental principles and
empirical relations. Godfroy et al. (1999) described a simple two-dimensional
hydrodynamic model for CFB riser in fully developed region. The modelpredicted solid holdup, radial void fraction, and the radial profiles of axial gas and
solid velocity and mass flux. Density is calculated using a correlation based on
slip factor, and the radial voidage profile is calculated solely on the basis of cross-
sectional average void fraction.Horio et al. (1988) and Horio and Tekei (1991) proposed core-annulus
clustering flow structures in their models. Bhusarapu et al. (2006) in theirexperimental studies predicted the clustering phenomena throughout the risercross-section (more likely near the wall) along with the particle exchange between
core and annulus. The clusters play a major role in axial dispersion of particle and
gas, radial distribution of particles, chemical reaction, and heat transfer at the
Gupta et al.: Modeling of Fluid Catalytic Cracking Riser Reactor: A Review
Published by The Berkeley Electronic Press, 2
-
8/11/2019 Gupta (2010)
10/42
wall, and thus affect the overall performance of a CFB (Huilin et al., 2005).
Sabbaghan et al. (2004) in their hydrodynamic model of the acceleration zone
considered that all solids moved as clusters in the riser (cluster based approach) as
rigid spheres. In this approach, the solid phase experiences higher drag force thanthe single particle based approach. Authors used the correlations proposed by Xu
and Kato (1999) for the cluster size. The effective drag coefficient for clusters canbe obtained by using the correlations proposed by Mostoufi and Chaouki (1999)
and Turton and Levenspiel (1986). The formulas used by the authors for the
estimation of cluster size and effective drag coefficient are listed in Table 2.
Subbarao (2010) proposed a model for the cluster size estimation. The modelpredicted the cluster size as a function of fluid and particle properties, and riser
diameter.
Table 2. Correlations for cluster size and effective drag coefficient
Correlations for cluster size:
cl
p
p
cl Ad
d
p
gpmfd
MQ
MgUA
)2(
))(1)(3333(
21
2
gUU
UM mfsmf
mfs
mf
)1(2
Correlations for effective drag coefficient:
09.1
657.0
0,Re163001(
413.0Re173.01
Re
24
p
p
p
DC
0,DD fCC mf
p
clt
d
dArm 33.0.22.0 Re02.3
Most hydrodynamic models of type (i) and type (ii) attempt to predict gas-
solid flow in risers using correlations mostly based on experimental data
generated for cold-flow conditions. In cold-flow studies, the solids are accelerated
4)1(
)( 7.4
01
mft
mf
mfs
p
gp UUU
gQ
8 International Journal of Chemical Reactor Engineering Vol. 8 [2010], Review
http://www.bepress.com/ijcre/vol8/R6
-
8/11/2019 Gupta (2010)
11/42
by the incoming gas and as a result, the gas velocity along the riser decreases as it
loses momentum in accelerating the solids. Arastoopour and Gidaspow (1979)
and Theologos and Markatos (1993) predicted, for vertical pneumatic conveying,
that the gas velocity decreases as the solid particles accelerate; the solid volumefraction therefore decreases due to increase in solid velocity at a constant solid
mass flux. However, in a FCC riser reactor the gas phase expands due to cracking,resulting in the gas velocity increase along the riser height.
Gupta et al. (2007) predicted the phase velocities and increase in molar
flux of gas all along the riser height (Figure 2). Malay et al. (1999) and Han and
Chung (2001b), in their FCC riser simulations, have also predicted similar phasevelocity profiles. Also, density, viscosity, and void fraction change due to
modifications in the operating conditions (temperature and pressure) and because
of mole generation (Leon-Becerril et al. 2004). Correlations proposed in type (i)and type (ii) lumped hydrodynamic models ignore these variations. Sundaresan
(2000) have also concluded that the main challenge in modeling the performanceof multiphase flow reactors is to integrate detailed chemistry and transportmodels.
Riser height (m)0 5 10 15 20 25 30 35
Velocity(m/s)
0
2
4
6
8
10
12
14
GasPhasemolarflux
(kmol/m
2.s
)
0.10
0.15
0.20
0.25
0.30
0.35
0.40
Gas Phase velocity
Solid phase velocity
Gas phase molar flux
Figure 2. Axial phase velocity and gas phase molar flux profiles in FCC riser
(Source: Gupta et al., 2007)
Gupta et al.: Modeling of Fluid Catalytic Cracking Riser Reactor: A Review
Published by The Berkeley Electronic Press, 2
-
8/11/2019 Gupta (2010)
12/42
In the last two decades, many researchers have shown great potential for
employing CFD for the simulation of type (iii) models. Two different classes of
CFD models can be made: Eulerian-Eulerian models and Eulerian-Lagrangian
models. Eulerian-Eulerian models consider both gas and solid phases ascontinuous and fully interpenetrating. The equations employed are a
generalization of the NavierStokes equations for interacting continua. Owing tothe Eulerian representation of the particle phases, Eulerian-Eulerian models
require additional closure laws to describe the rheology of particles. In most
recent continuum models constitutive equations according to the kinetic theory of
granular flow are incorporated. Eulerian-Lagrangian models solve the Newtonianequations of motion for each individual particle, taking into account the effects of
particle collisions and forces acting on the particle by the gas. In the Eulerian
approach, an arbitrary control volume in a stationary reference frame is used toderive the basic governing equations. In Lagrangian approach, equations are
derived by considering a control volume (material volume) such that the velocityof the control volume surface always equals the local fluid velocity.
Two types of type (iii) models are used for the particulate phase
turbulence: the concentration-dependent solid viscosity model and the kinetic
theory of granular flow model with and without gas turbulence. The solids
viscosity is needed to account for the energy dissipation between solid particles.The model with solids viscosity as an input was first proposed by Tsuo and
Gidaspow (1990). Authors used the solid viscosity reported by Gidaspow et al.
(1989) in their model. The computation of viscosity by the method of Gidaspowet al. (1989) becomes highly inaccurate when there is strong down-flow of solids.
Miller and Gidaspow (1992) determined the solid viscosity for FCC particles
from a mixture momentum balance, neglecting transient effects and assuming thatthe gas and solid velocity gradient are of same order. The authors proposed a
linear correlation between solid viscosity and solid concentration. Sun andGidaspow (1999) used the viscosity data predicted by Miller and Gidaspow
(1992) in their model. The authors predicted core-aanular flow in the riser and a
unique phenomena: an off-center maximum flux. Gidaspow et al. (1996) proposeda better correlation for solid viscosity, partially based on the kinetic theory of
granular flow:
0
3/1165.0 gss (2)
The radial distribution function, g0, used in the above equation accountsfor the probability of particle collisions. The value ofg0is near 1.0 when the flow
is dilute and becomes infinity when the flow is so dense that motion of particles is
impossible. The equations for radial distribution function are given by Carnahan
and Starling (1969) and by Bagnold (1954). Gidaspow and Huilin (1998) found
10 International Journal of Chemical Reactor Engineering Vol. 8 [2010], Review
http://www.bepress.com/ijcre/vol8/R6
-
8/11/2019 Gupta (2010)
13/42
the experimental data to lie between these theoretical expressions. Huilin and
Gidaspow (2003) used equation (2) in their model. Authors predicted two types of
core-annulus flow regimes at high solids flux: a regime with a parabolic flux and
downflow at the wall and a regime with a low flux at the pipe center and amaximum near the wall with no downflow. Gidaspow and Huilin (1998) proposed
an equation of state for determining solids pressure, incorporating the effect ofcohesive pressures as a function of volume fraction of particles. Authors
concluded that the derivative of the solids pressure with respect to volume
fraction can be used in the hydrodynamic models for predicting the particle and
velocity distribution profiles inside the CFBs.The pioneering work of Lun et al. (1984) applied the kinetic theory of
gases to granular flow. The kinetic theory approach uses a one equation model to
determine the turbulent kinetic energy (granular temperature) of the particles. Thegranular temperature is defined as the sum of the squares of random particle
oscillations in three directions. The kinetic theory approach for granular flowallows the determination of the viscosity of the solids in place of empiricalrelations. Using this theory the viscosity of particles can be computed from
granular temperature measurements (Gidaspow and Huilin, 1996) or from
granular pressure measurements (Chen et al. 1994). Sinclair and Jackson (1989)
applied the granular flow model to a fully developed flow in a pipe. Ding andGidaspow (1990) derived the expressions for solids viscosity and pressure of a
dense gas-solid flow. Mathesian et al., (2000), Neri and Gidaspow (2000), Van
Wachem et al. (2001) used the kinetic theory of the granular flow to simulate gassolid flow in risers. Das et al. (2004) in their model, based on the kinetic theory of
granular flow, incorporated an extra transport equation correlating the gas phase
and solid phase fluctuating motion. The authors proposed a solution algorithmthat allows simultaneous integration of all the model equations in contrast to the
sequential multi-loop algorithms commonly used in riser simulations. Huilin et al.(2005) used a cluster based approach and predicted the hydrodynamics of cluster
flow in circulating fluidized beds. Authors showed a considerable improvement in
the model predictions using cluster based approach as compared to the modelbased on original kinetic theory of granular flow. Lu et al. (2008) presented a gas-
solid multi-fluid model with two granular temperatures of the dispersed particles
and the clusters in risers, to predict the hydrodynamics of dispersed particles and
clusters flow in CFBs.In addition to the basic governing equations developed from the universal
laws, it is necessary to develop relevant constitutive equations and equations ofstate for the fluids under consideration to close the system of equations. Severalclosure models have been proposed to define the appropriate constitutive
equations for binary or multi-phase flows based on the kinetic theory of granular
flow. The constitutive equations are needed to close the solid phase momentum
Gupta et al.: Modeling of Fluid Catalytic Cracking Riser Reactor: A Review
Published by The Berkeley Electronic Press, 2
-
8/11/2019 Gupta (2010)
14/42
conservation equation for phase stress tensor, solid pressure, and momentum
exchange between the solid and gas phases.
The gas solid momentum exchange coefficient is assumed to only include
the drag contribution. Several drag models exist for the gas-solid interphaseexchange coefficient. Almuttahar and Taghipour (2008) in their CFD model
compared the performance of different drag models. Authors concluded that theGidaspow et al. (1992), Arastoopour et al. (1990), and Syamlal and OBrien
(1987) drag models predicted similar profiles for the solid volume fraction and
axial particle velocity; however, the Syamlal OBrien drag model, based on
minimum fluidization velocity of the particle, showed a better solid volumefraction prediction at the core area. Heynderickx et al. (2004) studied the effect of
particle clustering on the interphase momentum-transfer coefficient by
introducing the concept of effective drag. Authors concluded that for solidsfractions greater than 1%, clustering phenomena become increasingly important,
resulting in an appreciable decrease of the interphase momentum-transfercoefficient.
According to the turbulent flow behavior of FCC particles and void
fraction profile observed in experiments, four zones (dense phase, subdense
phase, subdilute phase, and dilute phase zone) can be identified in a turbulent
fluidized bed (Gao et al., 2009). Authors have summarized the various dragmodels applicable in these zones. Jiradilok et al. (2006) used the standard kinetic
theory based model with the modified drag (corrected for clusters) suggested by
Yang (2004), and simulated the turbulent fluidization of FCC particles in a riser.In addition to the drag force model, the flow behavior may be influenced
by inelastic interparticle collisions resulting in kinetic energy dissipation. The
restitution coefficient, e, represents the elasticity of particle collisions and rangesfrom fully inelastic (e= 0) to fully elastic (e= 1). Goldschmidt et al. (2001) and
Therdthianwong et al. (2003)reported that in the kinetic theory model there is adegree of sensitivity to the coefficient of restitution.
The simulations performed by Jiradilok et al. (2006) with the coefficient
of restitution of 0.99 did not give a good resolution for the bubble formation in thebottom part of turbulent fluidized bed. Therefore, the coefficient of restitution
was reduced to get reasonable results for the turbulent regime due to the increased
effect of particleparticle collisions in the dense phase. Authors used a value of
0.9 for their model simulation.Gao et al. (2009) reported that increasing the valueof restitution coefficient from 0.9 to 0.95, the coexisting dilute and dense phase in
the turbulent fluidized bed could be correctly predicted.The boundary conditions for the particulate turbulent energy (granular
temperature) and axial velocity are complex; a particle colliding with the wall
may slide or bounce back tangentially depending on the value of the angle of
collision, as described by Jenkins (1992). In two-fluid model, the collisional angle
12 International Journal of Chemical Reactor Engineering Vol. 8 [2010], Review
http://www.bepress.com/ijcre/vol8/R6
-
8/11/2019 Gupta (2010)
15/42
is not accounted for explicitly by the boundary conditions. There are two limits in
collisional exchange of momentum and kinetic energy between particles and wall:
a small-friction/all-sliding limit and a large-friction/no-sliding limit. Jenkins and
Louge (1997) have suggested that the appropriate boundary conditions could befound by interpolating between these two limits. Another type of boundary
condition commonly used in fluidization was derived by Johnson and Jackson(1987). This boundary condition uses a specularity coefficient, which may depend
on the flow conditions, to characterize the extent of sliding and bouncing back.
The use of specularity coefficient allows more flexibility in adjusting this
parameter to fit a certain flow behavior (Benyahia et al., 2005).For FCC riser modeling, most works used EulerianEulerian approach
where the dispersed solid particles are treated as interpenetrating continuum
(Theologos and Markatos, 1993; Benyahia et al., 2003; Zimmermann andTaghipour, 2005; Lan et al. 2009). Few works have used EulerianLagrangian
approach (Nayak et al. 2005; Wu et al., 2010). In this approach, the motion ofsolid catalyst particles is modeled in the Lagrangian framework and the motion ofcontinuous phase is modeled in the Eulerian framework. This approach offers a
more natural way to simulate complex particle level processes like cracking
reactions. Also, heat and mass transfer and chemical reactions occurring at the
individual particle scale can be conveniently accounted using this approach. Theapproach however requires significantly more computational resources and
therefore rarely used for dense gassolid risers.
Theologos and Markatos (1993) proposed a three dimensionalmathematical model considering two phase flow, heat transfer, and three lump
reaction scheme in the riser reactor. The authors developed the full set of partial
differential equations that describes the conservation of mass, momentum, energyand chemical species for both phases, coupled with empirical correlations
concerning interphase friction, interphase heat transfer, and fluid to wall frictionalforces. The model can predict pressure drop, catalyst holdup, interphase slip
velocity, temperature distribution in both phases, and yield distribution all over
the riser. Theologos et al. (1997) coupled the model of Theologos and Markatos(1993) with a ten lump reaction scheme to predict the yield pattern of the FCC
riser reactor. Theologos et al. (1999) accounted for feed atomization effect on
riser performance in their CFD model. Gao et al. (1999) developed a model
that predicted three-dimensional, two-phase flow inside the riser-type reactor. Theauthors used a thirteen lump kinetic scheme and demonstrated that excessive
cracking occurred beyond the 10 m riser height, and resulted in the increase of by-products yield at the expense of desirable products. Authors further extended thismodel to three-phase flow model (Gao et al., 2001) by incorporating the effect of
feed vaporization.
Gupta et al.: Modeling of Fluid Catalytic Cracking Riser Reactor: A Review
Published by The Berkeley Electronic Press, 2
-
8/11/2019 Gupta (2010)
16/42
Benyahia et al. (2003) presented a two phase 2-D flow model using
transient Eulerian approach with a simple three lumps kinetic scheme.
Zimmermann and Taghipour (2005) simulated the hydrodynamics and reaction
kinetics of gas-solid fluidized beds containing fluid catalytic cracking (FCC)particles. The authors included the kinetic term in an additional transport equation
for modeling the reaction kinetics. Novia et al. (2007) developed a model tosimulate the 3-D hydrodynamics and reaction kinetics (3-lump) in FCC riser
reactor. Baurdez et al. (2010) proposed a method for steady-state/transient, two-
phase gassolid simulation of a FCC riser reactor. Authors used a simple four
lump kinetic model to demonstrate the feasibility of the method.Nayak et al. (2005) used the EulerianLagrangian approach to simulate
simultaneous evaporation and cracking reactions occurring in FCC riser reactors.
Wu et al. (2010) used EulerianLagrangian approach for the simulation of gas-solid flow in FCC process. Authors concluded that by using this approach the
catalyst activity can be calculated in time by tracking the history of particlemovement undergoing the heat transfer and chemical reactions. Therefore, theeffect of the residence time distributions of catalyst particles on the reactor
performance is well revealed by considering the instantaneous catalyst
deactivation.
2.3 Cracking kinetics
Describing the kinetic mechanism for the cracking of petroleum fractions is
difficult because of the presence of thousands of unknown components in a
petroleum fraction. However, the important chemical reactions occurring during
catalytic cracking are given by Gates et al. (1979).For modeling of cracking kinetics, Weekman and Nace (1970) divided the
FCC feed stock and products into three components (lumps): the original
feedstock, the gasoline (boiling range C5 4100F), and the remaining C4s (dry
gas and coke); and developed a predictive kinetic model for the FCC riser. The
kinetic parameters of the model were evaluated using the experimental data. This
model was capable of predicting gasoline yield. However, it did not predict thecoke yield separately.
Prediction of coke is important as the coke supplies the heat required for
endothermic cracking reactions in the reactor. Lee et al. (1989) proposed a fourlump kinetic model by separating the coke from the three lump model of
Weekman and Nace (1970). The rate constants and activation energies for thereaction scheme were obtained by regression using the experimental data of Wang
(1974). This four lump kinetic scheme was used by several investigators (Farag etal., 1993; Zheng, 1994; Gianetto et al., 1994; Ali and Rohani, 1997; Blasetti et al.,
1997; Gupta and Subba Rao, 2001; Han and Chung, 2001a; Abul-Hamayel et al.,
14 International Journal of Chemical Reactor Engineering Vol. 8 [2010], Review
http://www.bepress.com/ijcre/vol8/R6
-
8/11/2019 Gupta (2010)
17/42
2002; Gupta and Subba Rao, 2003; Jia et al., 2003; Nayak et al., 2005;
Hernandez-Barajas et al., 2009) for the analysis of many other aspects of FCC
modeling. The model is still popular because of its simplicity, and ease of
formulation and solution of kinetic, material and energy equations.This simple lumping approach for kinetic modeling was further extended
by various researchers by increasing the number of lumps in their models. Effortsmade in this direction are: five lump models proposed by Larocca et al. (1990)
and Ancheyta-Juarez et al. (1999), six lump model by Coxson and Bischoff
(1987) and Takatsuka et al. (1987), ten lump model by Jacob et al. (1976), eleven
lump model by Mao et al. (1985), Sa et al. (1985) and Zhu et al. (1985), twelvelump model by Oliveira (1987), thirteen lump model by Sa et al. (1995), and
nineteen lump model by Pitault et al. (1994).
Jacob et al. (1976) included the chemical composition of the feed in their tenlump kinetic model by considering the paraffins, naphthenes, aromatic rings and
aromatic substituent groups in light and heavy fuel oil fractions. Their model alsoaccounted for the nitrogen poisoning, aromatic adsorption and time dependentcatalyst decay. Rate constants of the model were determined using the
experimental data obtained in a fluidized dense bed with a commercial FCC
catalyst. This model is used by Arbel et al. (1995), Ellis et al. (1998), and Nayak
et al. (2005) for their FCC modeling studies. This idea was further extended byOliveira (1987), Coxson and Bischoff (1987), and Theologos et al. (1997) for the
kinetics studies of FCC riser reactor. Ten lump scheme for catalytic cracking of
gas oil is shown in Figure 3.Oliveira (1987) proposed a twelve lump scheme in which the coke lump of
ten lump scheme of Jacob et al. (1976) is divided into two gas lumps (gas 1 and
gas 2) and a coke lump. Sa et al. (1995) proposed a thirteen lump kinetic modelconsidering coke and cracking gas as two separate lumps and dividing the
aromatic part of the vacuum residue into two parts, (in resin and asphaltenefraction & in saturate and aromatic fraction). Pitault et al. (1994) developed a
nineteen lump kinetic model comprising twenty five chemical reactions, this
kinetic scheme was used by Derouin et al. (1997) in their hydrodynamic modelfor the prediction of FCC products yields for an industrial FCC unit.
Gupta et al.: Modeling of Fluid Catalytic Cracking Riser Reactor: A Review
Published by The Berkeley Electronic Press, 2
-
8/11/2019 Gupta (2010)
18/42
PH = wt% paraffinic molecules, 6500F+
NH = wt% naphthenic molecules, 6500F+
SH = wt% aromatic side chains, 6500F+
AH = wt% carbon atoms among aromatic rings, 6500F+
PL = wt% paraffinic molecules, 4300-650
0F
NL = wt% naphthenic molecules, 4300-650
0F
SL = wt% aromatic side chains, 4300-650
0F
AL = wt% carbon atoms among aromatic rings, 4300-650
0F
G = gasoline lump (C5- 4300F)
C = C-lump (C1to C4+coke)
Figure 3. Ten lump scheme for catalytic cracking (Source: Coxson and
Bischoff, 1987)
Another method called structure-oriented lumping (SOL) was developed
by Quann and Jaffe (1992) for describing the composition, reactions andproperties of complex hydrocarbon mixtures. This lumping technique represents
individual hydrocarbon molecules as a vector of incremental structural features
thus a mixture of hydrocarbons can be represented as a set of these vectors, eachwith an associated weight percent. This type of representation of molecules
provides a convenient framework for constructing reaction networks of arbitrarysize and complexity, for developing molecular-based property correlations, and
for incorporating existing group contribution methods for the estimation ofmolecular thermodynamic properties. Christensen et al. (1999) used the SOL for
specifying the reaction chemistry of FCC feedstocks using over 3000 molecular
Gasoline
PL NL SL AL
PH NH SH AH
C-Lump
16 International Journal of Chemical Reactor Engineering Vol. 8 [2010], Review
http://www.bepress.com/ijcre/vol8/R6
-
8/11/2019 Gupta (2010)
19/42
species with over 60 reaction rules and generated a network of 30,000 elementary
chemical reactions. They included the monomolecular reactions (cracking,
isomerization, and cyclyzation), bimolecular reactions (hydrogen transfer, coking,
and disproportionation), and the effects of thermal cracking and metal-catalyzeddehydrogenation for the reaction network generation. The kinetic parameters for
the model were regressed using a wide range of FCC process conditions, feedcompositions, and catalyst formulations. The integrated FCC process model
developed by the authors using this kinetic model is claimed to be capable of
predicting the complex non-linear phenomena of FCC units.
Feng et al. (1993) proposed single-events method for the FCC kineticmodeling. This method permits a mechanistic description of catalytic cracking
based on the detailed knowledge of the mechanism of various reactions involving
the carbenium ions. Determination of the kinetic constants for these single eventsrequires some key reactions of pure hydrocarbons.
Based on the single-events method, Dewachtere et al. (1999) developeda kinetic model for catalytic cracking of VGO in terms of elementary steps ofchemistry. For the reaction network generation, all likely chemical species are
considered and accounted for in each lump. Fifty single event rate parameters
were determined from an extensive experimental program on catalytic cracking of
key components with relevant structures. Landeghem et al. (1996) proposed anew kinetic model based on the molecular description of cracking and hydrogen
transfer reactions. This scheme is an intermediate approach between simple
lumping of cuts and single events method. The authors determined the kineticconstants of the model using a microactivity test reactor.
The concept of continuous description of catalytic cracking of petroleum
fractions incorporating kinetics and other physical rate steps using advancedcomputational techniques is proposed by Peixoto and de Medeiros (2001). They
characterized the petroleum fractions using multi indexed concentrationdistribution function (CDF) developed by Aris (1989). Authors used the twelve
lump scheme, instantaneous adsorption hypothesis of Cerqueira (1996) and
deactivation hypothesis of Oliveira (1987) in their work.Recently, Gupta et al. (2007) proposed a new kinetic scheme based on
pseudocomponents cracking and developed a semi-empirical model for the
estimation of the rate constants of the resulting reaction network. Fifty
pseudocomponents (lumps) are considered in this scheme resulting in more than10,000 reaction possibilities. The model can be easily used to incorporate other
aspects of the riser modeling. This kinetic model is used by Gupta and Kumar(2008) in a three phase FCC riser model and by Ruqiang et al. (2008) for theproduction planning optimization of FCC.
Various other works on kinetic modeling include: a study (Fisher, 1990)
on the effect of feedstock variations on the catalytic cracking yields; a study
Gupta et al.: Modeling of Fluid Catalytic Cracking Riser Reactor: A Review
Published by The Berkeley Electronic Press, 2
-
8/11/2019 Gupta (2010)
20/42
(Farag et al., 1993) on the effects of metal traps in a FCC catalyst contaminated
with high levels of nickel and vanadium using pulse reaction technique for testing
of FCC catalysts in a down-flow micro activity reactor at different carrier gas
flows and at different temperatures; a strategy proposed by Ancheyta-Juarez et al.(1997) to estimate kinetic constants for the three lump, four lump and five lump
kinetic models that decreases the number of parameters to be estimatedsimultaneously; a modeling study (Wallenstein and Alkemade, 1996) on FCC
catalyst selectivity using the experimental data from a microactivity test reactor; a
rate constants sensitivity analysis by Pareek et al. (2002) by grouping 20 rate
constants of Weekmans kinetic model (Weekman, 1979) in five categories byusing CATCRACK developed by Kumar et al. (1995); a new approach by Ng et
al. (2002) for determining product selectivity in gas oil cracking using a four lump
kinetic model; a study (Hagelberg et al., 2002) of the kinetics of gas oil crackingon a FCC equilibrium catalyst with short contact times using a novel isothermal
pulse reactor; a bulk molecular characterization approach (Bollas and Vasalos,2004) for the simulation of the effect of bulk properties of FCC feedstocks on thecrackability and coking tendency; an eight-lump kinetic model for secondary
reactions of FCC gasoline proposed by Wang et al. (2005); a study on the effect
of catalyst to oil ratio, temperature, residence time, and feed composition on
products selectivities and product distribution by Dupain et al. (2006); and anapproach (Hernandez-Barajas et al., 2009) based on representing rate constantswith a continuous probability distribution function for the estimation of kinetic
parameters in lumped catalytic cracking reaction models.
2.4 Interphase heat transfer and mass transfer
After the complete vaporization of feed droplets, a vapor phase (hydrocarbons andsteam) and a solid phase (catalyst particles) exist in the riser. There is
considerable temperature difference in these phases near the bottom of the riser.
Since, the temperature influences the reaction rates the prediction of interphase
heat transfer becomes important.From heat transfer point of view, very early models assumed isothermal
riser. Most of the riser models assume instantaneous thermal equilibrium between
the vapor and solid phases at the riser inlet. There have been very fewexperimental measurements of heat-transfer rate between gases and suspended
fine particles, and only limited correlations are available (Bandrowski and
Kaczmarzyk 1978; Kato et al. 1983).Generally the experimental observations on heat transfer coefficients
between gas and particles are expressed as Nusselt number as a function ofReynolds number based on single particle diameter (Kunii and Levenspiel, 1991):
18 International Journal of Chemical Reactor Engineering Vol. 8 [2010], Review
http://www.bepress.com/ijcre/vol8/R6
-
8/11/2019 Gupta (2010)
21/42
3/1
3/203.0
g
gpg
p
g
p
VU
d
kh
(3)
Theologos et al. (1999) developed a 3-D mathematical model that predicts
the two-phase flow, heat transfer and chemical reaction in catalytic cracking riser
reactor. They used a correlation of Nusselt number as a function of Reynoldsnumber. The model was used to assess the effects of interphase heat transfer in
the overall performance of the riser. Gupta and Subba Rao (2001) used modified
Nusselts number proposed by Buchanan (1994). Wu et al. (2010) used acorrelation for Nusselt number that is proposed by Ranz and Marshall (1952).
Jepson (1986) has developed a non-isothermal transport reactor model
incorporating an empirical gas-particle heat-transfer correlation.
External mass transfer resistances in the riser are neglected in most of theworks on FCC riser modeling (Corella and Frances, 1991a; Martin et al., 1992;
Ali et al., 1997; Derouin et al., 1997; Theologos et al., 1999; Das et al., 2003,
Berry et al., 2004; Gupta et al., 2007). However, considering mass transferresistance between the phases helps in predicting the concentration of the reacting
species at the catalyst surface. Flinger et al. (1994) in their model considered mass
transfer to occur between the two phases. Authors obtained the mass-transfercoefficient as a fitting parameter based on the conversion profile in a commercial
FCCU. Like external heat transfer, mass transfer may be expressed as Sherwood
number as a function of the Reynolds number based on single particle diameter.Gupta and Subba Rao (2001) and Nayak et al. (2005) modeled the interphase
mass transfer using the correlation for Sherwood number proposed by Ranz and
Marshall (1952). Han and Chung (2001b) calculated the diffusion coefficients
using the correlation proposed by Baird and Rice (1975):
3/43/1)(35.0 DgUD gf (4)
Intrapellet mass transfer has the effect of decreasing the reactant
concentration within the pellet. Consequently, the average rate will be less thanwhat it would be in the absence of internal concentration gradient (Smith, 1981).Pruski et al. (1996) determined adsorption coefficients for four lumps, while
cracking gas oil. Bidabehere and Sedran (2001) developed a model to study the
effects of diffusion, adsorption, and reaction at high temperature inside theparticles of commercial FCC catalysts and experimentally studied the relative
importance of these phenomena using two equilibrium catalysts and n-hexadecaneas a test reactant in a riser simulator reactor. Al-Khattaf and de Lasa (2001)
described the effects of diffusion on activity and selectivity of FCC catalysts.
Gupta et al.: Modeling of Fluid Catalytic Cracking Riser Reactor: A Review
Published by The Berkeley Electronic Press, 2
-
8/11/2019 Gupta (2010)
22/42
Atias and de Lasa (2004) studied adsorption and diffusion under reaction
conditions similar to those of fluid catalytic cracking (FCC) by performing
experiments in a novel fluidized CREC riser simulator using FCC catalysts of
various crystallite sizes. The CREC riser simulator, used by the authors,facilitated the assessment of adsorption parameters on FCC catalysts under
reaction conditions and the decoupling in their evaluation from that of intrinsickinetic parameters. Their study is more close to the FCC conditions as compared
to the earlier studies that are done at low temperatures under low or no reactivity
conditions. Dupian et al. (2006) have discussed the external and internal mass
transfer correlations used for modeling the FCC riser.
2.5 Catalyst deactivation
During the cracking reactions, FCC catalyst gets deactivated due to the deposition
of coke on the catalyst surface. Most of the popular theories on deactivation arebased on the time-on stream concept. Many researchers (Voorhies, 1945;Wojciechowski, 1968, 1974; Nace, 1970; Gross et al., 1974) have used this
concept to formulate various empirical functions for accounting the effect of
catalyst decay on the cracking kinetics.
Various models for time dependent catalyst decay have been proposed fordifferent lengths of contact time. Models of Weekman (1968) and Nace et al.
(1971) used relatively high contact times (1.2 to 40 min), and Models of Paraskos
et al. (1976) and Shah et al. (1977) used relatively low contact times (0.1 to 10 s).Froment and Bischoff (1990) proposed a mechanistic based model considering
catalyst decay rate as a function of the fraction of active sites and the
concentration of the reactants.Corella et al. (1985) studied the catalyst decay for a wide range of contact
times (2 to 200 s) considering homogeneous and non homogeneous catalystsurfaces. Authors showed that the order of deactivation kinetics decreases with
the contact time, taking values 3, 2, and 1, successively. They further justified the
change of order of deactivation with the different contact times by showing thediscrepancy in the values of these constants obtained by Weekman (1968) and
Nace et al. (1971) for relatively large contact times, and Paraskos et al. (1976) and
Shah et al. (1977) for short contact times. The deactivation equations proposed byvarious authors are listed in Table 3.
20 International Journal of Chemical Reactor Engineering Vol. 8 [2010], Review
http://www.bepress.com/ijcre/vol8/R6
-
8/11/2019 Gupta (2010)
23/42
Table 3. Empirical equations proposed for the catalyst deactivation (Source:Gupta, 2006)
Author Kinetic equation of activity d
differential integrated
Weekman (1968) -da/dt = a a = e-t
1
Weekman and Nace
(1970)
-da/dt =
A-1/
(+1/)
a = A-
A-1/
(+1)/
(if d 1)
Wojciechowski
(1968)
-da/dt = Aag a = [1+(g-1)At]
-
1/(g-1)
A g
(if g 1)
Corella et al. (1985) -d(k0a)/dt =
k0(1-d)
( k0a)d
integrated ford=1
d=2
d=3
12
3
a = average activity of catalyst
t = time= average deactivation functiond = order of deactivation
k0= cracking kinetic constant, average value for all the reactants present in feed
Corella et al. (1986) determined the kinetic parameters of cracking and of
deactivation for a given feed-catalyst system. Corella and Menendez (1986)developed a model in which the catalyst surface was assumed to be non-
homogeneous with acidic sites of varying strength. Corella and Monzon (1988)
developed a model for deactivation and coking kinetic relations between activity,concentration of coke and time on stream for four different mechanisms of coke
formation and growth. Corella and Frances (1991b) correlated the deactivation
kinetic constant with the commercial feedstock and commercial catalysts andproposed overall deactivation orders ranging from 1.4 to 2.7.
There is no specific function that can be used for the deactivation.
Different empirical equations have been used by various researchers to fit their
experimental data. However, there are two functions that fit the experimental data
quite well: power function and exponential function. The exponential function ismore widely used. Larocca et al. (1990) reported that the catalyst deactivation can
be represented by both an exponential decay function and a power decay functionwith an average exponent of 0.1to 0.2. Kraemer et al. (1991) used the data from
two different experimental reactors and showed that exponential decay function or
Gupta et al.: Modeling of Fluid Catalytic Cracking Riser Reactor: A Review
Published by The Berkeley Electronic Press, 2
-
8/11/2019 Gupta (2010)
24/42
power law function could equally represent the data; however, the power law
assumes the unrealistic limits of infinite catalyst activity at zero time-on-stream
and requires two parameters to describe deactivation. They further concluded that
the simple first order decay function is an effective equation for describing thecatalyst activity decay for short reaction times (less than 20 seconds).
Al-Khattaf and de Lasa (1999) have estimated the effective gas oildiffusivity in Y-zeolites. The effectiveness factor for gas oil cracking was
calculated for 1 m and 0.1m zeolite. Authors showed that diffusional
constraints have a major impact on primary cracking reactions and on gasoline
composition. Den Hollander et al. (2001)determined the performance of coked(0.56wt% coke on catalyst) and fully regenerated FCC catalyst by cracking a
hydrowax feedstock in a micro-riser equipment. Authors predicted that the
activity of coked catalyst was lower but was still significant, and the selectivitywas similar to the regenerated catalyst.
Lopez-Isunza (2001) presented a mechanistic model to study thedeactivation of FCC catalyst by combining interphase and intraparticle masstransfer interactions with the cracking reactions in an isothermal, ideally mixed
fluidized bed in which reactions occur inside the cylindrical pore in a single pellet
(microsphere) cracking catalyst. The deactivation of the catalyst is modeled using
Langmuir-Hinshelwood expression. Corella (2004) developed a selectivedeactivation kinetic model for the commercial FCC catalysts and feedstocks.
3.
Conclusions
Feed atomization into small droplets of uniform size is desired as it helps inavoiding side reactions thereby improving the yields of desirable products. The
smaller feed diameter leads to faster evaporation rates, a better mixing with
catalyst, and uniform cooling of the catalyst. This leads to reduction in undesiredthermal cracking.
Also, it is desired that the feed is distributed evenly throughout
the entire cross section of the riser so that the temperature distribution in the riser
entry zone is improved.The three phase, 3-D models can capture the real hydrodynamic in the
riser, especially in the feed entry zone. Computational fluid dynamics is a
powerful tool that may be used to model the complex phenomena in the riser
entry zone. Also, in FCC riser models, incorporating the effect of cracking on thehydrodynamics helps in better predictions of the physical phenomena.
There are a number of kinetic models/schemes available in the literature.
However, in most of the FCC riser simulation studies either four lump or ten lumpkinetic schemes are used. Use of detailed kinetic models by the researchers is
limited in order to avoid the mathematical complexity. CFD models may be used
to incorporate more detailed kinetics with complex hydrodynamics.
22 International Journal of Chemical Reactor Engineering Vol. 8 [2010], Review
http://www.bepress.com/ijcre/vol8/R6
-
8/11/2019 Gupta (2010)
25/42
Considering Interphase heat transfer resistance and mass transfer
resistances in the model gives realistic phase temperature and concentration
profiles and influences the kinetic constants and rate of the cracking reactions
eventually leading to better prediction of product yields.In most of the models of FCC risers, a very simplified deactivation model
(assuming first order deactivation for all the reactions) is used. However, Corella(2004) have shown that the deactivation orders are not same for all the reactions.
The use of variable deactivation order may be explored in future models.
Nomenclature
A parameter in correlation of Xu and KatoAr Archimedes number, ds
3g(s-g)g/
2
CD effective drag coefficientCD,0 standard drag coefficient
D riser diameter (m)Df effective diffusion coefficient (m
2/s)
dcl cluster diameter (m)
dp particle diameter (m)Fr Froude number, u0/(gD)
0.5
Frt Froude number based on the terminal settling velocity of single
particle, Vt/(gD)0.5
f drag force correction factor
g gravitational acceleration (m/s2)
hp interface heat transfer coefficient between catalyst and gas phases[kJ/(s m2K)]
kg thermal conductivity of gas [kJ/(s m K)]M2 parameter in correlation of Xu and Kato
m parameter in correlation of Mostoufi and Chaouki
Q1 parameter in correlation of Xu and Kato
Rep particle Reynolds number, dpgVp/Ret particle Reynolds number based on terminal velocity, dpgUt/
Us solid superficial velocity (m/s)
Ug gas velocity (m/s)Umf gas velocity at incipient of fluidization (m/s)
Uo superficial gas velocity (m/s)Ut terminal velocity (m/s)Vp average particle velocity (m/s)
Gupta et al.: Modeling of Fluid Catalytic Cracking Riser Reactor: A Review
Published by The Berkeley Electronic Press, 2
-
8/11/2019 Gupta (2010)
26/42
Greek letters
average axial voidage
mf voidage at incipient of fluidizations solid volume fraction
cl cluster density (kg/m3)
g gas density(kg/m3)
p particle density(kg/m3)
g gas viscosity (Pa.s)s particulate viscosity
References
Abul-Hamayel M.A., Siddiqui M.A.B., Ino T., Aitani A.M., Applied Catalysis A:General, 2002, 237, 71-80.
Al-Khattaf S. and de Lasa H., Diffusion and reactivity of gas oil in FCCcatalysts, The Canadian Journal of Chemical Engineering, 2001, 79, 341-
348.
Al-Khattaf S.and de Lasa H.1., Activity and Selectivity ofFluidized Catalytic
Cracking in a Riser Simulator: the role of Y-Zeolite crystal size,
Industrial and Engineering Chemistry Research, 1999, 38, 1350-1 356.
Ali H., and Rohani S., Dynamic modeling and simulation of a riser-type fluid
catalytic cracking unit, Chemical Engineering and Technology, 1997, 20,118-130.
Ali H., Rohani S., and Corriou J. P., Modeling and control of a riser type fuid
catalytic cracking (FCC) unit, Transactions of the Institution of Chemical
Engineers Part A, 1997, 75, 401.
Almuttahar A., and Taghipour F., Computational fluid dynamics of high densitycirculating fluidized bed riser: study of modeling parameters, Powder
Technology, 2008, 185, 11-23.
Ancheyta-Juarez J., Lopez-Isunza F., Aguilar-Rodriguez E., A strategy for
kinetic parameter estimation in the fluid catalytic cracking process,
Applied Catalysis A: General, 1999, 177, 227-235.
Ancheyta-Juarez J., Lopez-Isunza F., Aguilar-Rodrguez E., and Moreno-
Mayorga J. C., A strategy for kinetic parameter estimation in the fluidcatalytic cracking process, Industrial and Engineering Chemistry
Research, 1997, 36, 5170-5174.
24 International Journal of Chemical Reactor Engineering Vol. 8 [2010], Review
http://www.bepress.com/ijcre/vol8/R6
-
8/11/2019 Gupta (2010)
27/42
Arastoopour H., and Gidaspow D.,Vertical pneumatic conveying using four
hydrodynamics Models, Industrial and Engineering Chemistry
Fundamentals 1979, 18, 123-130.
Arastoopour H., Pakdel P., Adewumi M., Hydrodynamic analysis of dilute gas
solids flow in a vertical pipe, Powder Technology, 1990, 62, 163170.
Arbel A. Huang Z., Rinard I.H., Shinnar R. and Sapre A.V., Dynamics and
control of fluidized catalytic crackers. Modeling of the current generation
FCCs, Industrial Engineering Chemistry Research, 1995, 34, 1228-1243.
Aris R., Reactions in continuous mixtures, AIChE Journal, 1989, 35, 539-548.
Atias J. A., de Lasa H., Adsorption and catalytic reaction in FCC catalysts using
a novel fluidized CREC riser simulator, Chemical Engineering Science,
2004, 59, 56635669.
Avidan A.A., Edwards M., and Owen H., Innovative improvements highlight
FCCs past and future, Oil and Gas Journal, 1990, 88(2), 33-58.
Bader R., Findley J., and Knowlton T.M., P. Basu and J.F. Large Eds., Gas-solidflow patterns in a 30.5-cm diameter circulating fluidized bed, In
Circulating fluidized Bed Technology II, 1988, 123-137, Pergamon Press,
Oxford.
Bagnold R. A. Experiments on a gravity-free dispersion of large solid spheres in
a Newtonian fluid under shear, Proceedings of The Royal Society of
London, 1954, A225, 49, London.
Bai D.-R., Jin Y., Yu Z.-Q., and Zhu J.-X., The axial distribution of the cross-
sectionally averaged voidage in fast fluidized beds, Powder Technology,
1992, 71, 51-58.
Baird H. M., and Rice R. G., Axial dispersion in large unbaffled columns,
Chemical Engineering Journal, 1975, 9, 171-174.
Bandrowski J., and Kaczmarzyk G., Gas-to-particle heat transfer in verticalpneumatic conveying of granular materials, Chemical Engineering
Science, 1978, 33, 1303.
Baudrez E., Heynderickx G. J., Marin G. B. Steady-state simulation of fluidcatalytic cracking riser reactors using a decoupled solution method with
feedback of the cracking reactions on the flow, Chemical Engineering
Research and Design, 2010, 88, 290-303.
Gupta et al.: Modeling of Fluid Catalytic Cracking Riser Reactor: A Review
Published by The Berkeley Electronic Press, 2
-
8/11/2019 Gupta (2010)
28/42
Benyahia S., Ortiz A.G., and Paredes J.I.P., Numerical analysis of a reacting
gas/solid flow in the riser section of an industrial fluid catalytic cracking
unit, International Journal of Chemical Reactor Engineering, 2003,
Volume 1, Article A41.
Benyahia S., Syamlal M., and OBrien T.J., Evaluation of boundary conditions
used to model dilute, turbulent gas/solid flows in a pipe, Powder
Technology, 2005, 156, 62-72.
Berruti F., Chaouki J., Godfroy L., Pugsley T.S., and Patience G.S.,
Hydrodynamics of circulating fluidized bed risers: a review, The
Canadian Journal of Chemical Engineering, 1995, 73, 579-602.
Berruti, F. and Kalogerakis N., Modelling the internal flow structure of
circulating fluidized beds, The Canadian Journal of Chemical
Engineering, 1989, 67, 1010-1014.
Berry T.A., McKeen T.R., Pugsley T.S., and Dalai A.K., Two-dimensional
reaction engineering model of the riser section of a fluid catalytic crackingunit, Industrial and Engineering Chemistry Research, 2004, 43 (18),
5571-5581.
Bhusarapu S., Al-Dahhan M. H., and Dudukovic M. P., Solids flow mapping in agassolid riser: mean holdup and velocity fields, Powder Technology,
2006, 163, 98-123.
Bidabehere C.M., and Sedran U., Simultaneous diffusion, adsorption, and
reaction in fluid catalytic cracking catalysts, Industrial and EngineeringChemistry Research, 2001, 40, 530-535.
Bienstock M. G., Draemel D. C., Shaw D. F., and Terry P.H., Modernizing
FCCUs for improved profitability, Akzo catalysts symposium, fluid
catalytic cracking, Scheveningen, 1991, 6577, The Netherlands.
Biswas J., and Maxwell I.E., Recent process and catalyst related developments in
fluid catalytic cracking, Applied Catalysis, 1990, 63, 197-258.
Blasetti A., and de Lasa H., FCC riser unit operated in the heat-transfer mode:
Kinetic modeling, Industrial and Engineering Chemical Research, 1997,
36, 3223-3229.
Bolkan-Kenny Y. G., Pugsley T. S., and Berruti F., Computer simulation of the
performance of fluid Catalytic cracking (FCC) risers and downers,
Industrial and Engineering Chemistry Research, 1994, 33, 3043-3052.
26 International Journal of Chemical Reactor Engineering Vol. 8 [2010], Review
http://www.bepress.com/ijcre/vol8/R6
-
8/11/2019 Gupta (2010)
29/42
Bollas G.M., Vasalos I.A., Bulk Molecular Characterization Approach for the
Simulation of FCC Feedstocks, Industrial and Engineering Chemistry
Research, 2004, 43, 3270-3281.
Brereton C.M.H., and Stomberg L., P. Basu Ed., Some aspects of the fluid
behavior of fast fluidized beds, In circulating fluid bed technology, 1986,
133-143, Permagon Press, Toronto.
Buchanan J. S., Analysis of heating and vaporization of feed droplets in fluidizedcatalytic cracking risers, Industrial and Engineering Chemistry Research,
1994, 33, 31043111.
Capes C., and Nakamura K., Vertical pneumatic conveying: an experimental
study with particles in the intermediate and turbulent flow regimes, The
Canadian Journal of Chemical Engineering, 1973, 51, 31-38.
Carnahan N. F., and Starling, K. E., Equation of state for nonattracting rigid
spheres, Journal of Chemical Physics,1969, 51, 635-636.
Cerqueira H.S., Modelageme simulacao do craqueamento catalitico de gasoleoem leito fixo: Formacao do coque, M.Sc. Thesis (in Portuguese), 1996,
Universidade Federal do Rio de Janeiro, Brazil.
Chen J.C., Polashenski W., and Tuzla K., Normal solid stress in fluidized beds,
AICHE Meeting, Preprint Volume for Fluidization and Fluid-Particle
Systems, 1994, San Francisco.
Christensen G., Apelian M.R., Hickey K.J., and Jaffe S.B., Future directions in
modeling the FCC process: an emphasis on product quality, ChemicalEngineering Science, 1999, 54, 2753-2764.
Corella J., On the modeling of the kinetics of the selective deactivation ofcatalysts. Application to the fluidized catalytic cracking process,
Industrial and Engineering Chemistry Research, 2004, 43, 4080-4086.
Corella J., Bilbao R., Molina J.A., and Artigas A., Variation with time of themechanism, observable order, and activation energy of the catalyst
deactivation by coke in the FCC process, Industrial and Engineering
Chemistry Process Design and Development, 1985, 24, 625-636.
Corella J., Fernandez A., and Vidal J.M., Pilot plant for the fluid catalyticcracking process: determination of the kinetic parameters of deactivation
of the catalyst, Industrial and Engineering Chemistry Process Design and
development, 1986, 25, 554-562.
Gupta et al.: Modeling of Fluid Catalytic Cracking Riser Reactor: A Review
Published by The Berkeley Electronic Press, 2
-
8/11/2019 Gupta (2010)
30/42
Corella J. and Frances E., M. L. Occelli Ed., Analysis of the riser reactor of a
fluid cracking unit: Model based on kinetics of cracking and deactivation
from laboratory tests, in Fluid catalytic cracking-II: Concepts in catalyst
design, ACSsymposium series, 1991a, 452, 165182, American ChemicalSociety, Washington.
Corella J., and Frances E., C.H. Bartholomew and J.B. Butt Eds., On the kinetic
equation of deactivation of commercial cracking (FCC) catalysts withcommercial feedstocks, In Catalyst Deactivation, Studies in Surface
Science and Catalysis, 1991b, volume 68, 375-381, Elsevier, Amsterdam.
Corella J., and Menedez M., The modelling of the kinetics of deactivation of
monofunctional catalysts with and acid strength distribution in their non-homogeneous surface. Application of the deactivation of commercial
catalysts in the FCC process, Chemical Engineering Science, 1986, 41,
1817-1826.
Corella J., and Monzon, A., Deactivation and coking kinetic relations betweenactivity, concentration of coke and time-on-stream for different
mechanisms of formation and growth of the coke, Ann. Quim., 1988, 84,
205-220.
Coxson P.G., and Bischoff K.B., Lumping Strategy, 1. introduction techniquesand application of cluster analysis, Industrial and Engineering Chemistry
Research, 1987, 26, 1239-1248.
Das A.K., Baudrez E., Martin G.B., and Heynderickx G.J., Three-dimensional
simulation of a fluid catalytic cracking riser reactor, Industrial and
Engineering Chemistry Research, 2003, 42, 2602-2617.
Das A.K., De Wilde J., Hegnderickx G.J., Marin G.B., Vierendeels J., and Dick
E., CFD simulation of dilute phase gassolid riser reactors: Part I-a newsolution method and flow model validation, Chemical Engineering
Science, 2004, 59, 167186.
Dean R., Mauleon J. L. and Letzsch W., Total introduces new FCC process Oil
and Gas Journal, 1982, 80, 168-176.
Den Hollander M.A., Makkee M., and Moulijn J.A., Prediction of the
performance of coked and regenerated fluid catalytic cracking catalyst
mixtures. Opportunities for process flexibility, Industrial and Engineering
Chemistry Research, 2001, 40, 1602-1607.
Derouin C., Nevicato D., Forissier M., Wild G., and Bernard J.R.,
Hydrodynamics of riser units and their impact on FCC operation,
Industrial and Engineering Chemistry Research, 1997, 36, 4504-4515.
28 International Journal of Chemical Reactor Engineering Vol. 8 [2010], Review
http://www.bepress.com/ijcre/vol8/R6
-
8/11/2019 Gupta (2010)
31/42
Dewachtere N.V., Santaella F., and Froment G.F., Application of a single-event
kinetic model in the simulation of an industrial riser reactor for the
catalytic cracking of vacuum gas oil, Chemical Engineering Science,
1999, 54, 3653-3660.
Ding J., and Gidaspow D., A bubbling fluidization model using kinetic theory of
granular flow, AlChE Journal, 1990, 36, 523-538.
Dupain X., Makkee M., Moulijn J.A., Optimal conditions in fluid catalyticcracking: a mechanistic approach, Applied Catalysis A: General, 2006,
297, 198-219.
Ellis R.C., Li X., and Riggs J.B., Modeling and optimization of a model IV
fluidized catalytic cracking unit, AIChE Journal, 1998, 44, 2068-2079.
Farag H., Ng S., and de Lasa H., Kinetic modeling of catalytic cracking of gasoils using in situ traps (FCCT) to prevent metal contamination, Industrial
and Engineering Chemistry Research, 1993, 32, 1071-1080.
Feng W., Vynckier E., and Froment G.F., Single event kinetics of catalyticcracking, Industrial and Engineering Chemistry Research, 1993, 32,
2997-3005.
Fisher I.P., Effect of feedstock variability on catalytic cracking yields, Applied
Catalysis, 1990, 65, 189-210.
Flinger M., Schipper P. H., Sapre A. V., Krambeck F. J., Two phase cluster in
riser reactors: impact of radial density distribution on yields, Chemical
Engineering Science, 1994, 49, 5813-5818.
Froment G.F., and Bischoff K.B., Chemical reactor analysis and design, Wiley
Series in Chemical Engineering, 2nd
edition, 1990, John Wiley, New York.
Gao J., Lan X., Fan Y., Chang J., Wang G., Lu C., and Xu C., CFD modelingand validation of the turbulent fluidized bed of FCC particles, AICHE
Journal, 2009, 55, 1680-1694.
Gao J., Xu C., Lin S., Yang G., and Guo Y., Simulation of gas-liquid-solid 3-
phase flow and reaction in FCC riser reactors, AIChE Journal, 2001, 47,
677-692.
Gao J., Xu C., Lin S., Yang G., and Guo Y., Advanced model for turbulent gas-
solid flow and reaction in FCC riser reactor, AIChE Journal, 1999, 45,
1095-1113.
Gupta et al.: Modeling of Fluid Catalytic Cracking Riser Reactor: A Review
Published by The Berkeley Electronic Press, 2
-
8/11/2019 Gupta (2010)
32/42
Gates B.C., Katzer J.R., and Schuit G.C.A., Chemistry of catalytic processes,
1979, McGraw-Hill, New York.
Gianetto, A., Faraq, H., Blasetti, A., and de Lasa, H., FCC catalyst forreformulated gasolines. Kinetic modeling, Industrial and Engineering
Chemistry Research, 1994, 33, 3053-3062.
Gidaspow D., Bezburuah R., and Ding J., Hydrodynamics of circulating
fluidized beds, kinetic theory approach, Fluidization VII, Proceedings of
the 7th
Engineering Foundation Conference on Fluidization, 1992, 7582.
Gidaspow D., and Huilin L., Equation of state and radial distribution functions of
FCC particles in a CFB, AIChE Journal, 1998, 44, 279-293.
Gidaspow D., and Huilin L., Collisional viscosity of FCC particles in a CFB,
AIChE Journal, 1996, 42, 25032510.
Gidaspow D., Tsuo, Y.P., and Luo, K.M., Computed and experimental cluster
formation and velocity profiles in circulating fluidized beds, Fluidization
IV, International Fluidization Conference, 1989, Alberta, Canada.
Godfroy L., Patience G.S., and Chauki J., Radial hydrodynamics in risers,
Industrial and Engineering Chemistry Research, 1999, 38, 81-89.
Goelzer A., Asphalt molecule shattering in S & Ws FCC feed distributor,question and answer sessions with short communications, Ketjen catalyst
symposium, 1986, 18-23, Scheveningen, The Netherlands.
Goldschmidt M.J.V., Kuipers J.A.M., and Van Swaaij, W.P..M., Hydrodynamicmodelling of dense gasfludized beds using the kinetic theory of granular
flow: effect of restitution coefficient on bed dynamics, Chemical
Engineering Science, 2001, 56, 571578.
Grace, J. R., High-velocity fluidized bed reactors, Chemical Engineering
Science, 1990, 45, 1953-1966.
Gross B., Nace D.M., and Voltz S.E., Application of a kinetic model forcomparison of catalytic cracking in fixed bed microrecator and a fluidized
dense bed, Industrial and Engineering Chemistry Process Design and
Development, 1974, 13, 199-203.
Gupta A., and Subba Rao D., Effect of feed atomization on FCC performance:
simulation of entire unit, Chemical Engineering Science, 2003, 58, 4567-
4579.
30 International Journal of Chemical Reactor Engineering Vol. 8 [2010], Review
http://www.bepress.com/ijcre/vol8/R6
-
8/11/2019 Gupta (2010)
33/42
Gupta A., and Subba Rao D., Model for the performance of a fluid catalytic
cracking (FCC) riser reactor: effect of feed atomization, Chemical
Engineering Science, 2001, 56, 4489-4503.
Gupta R. K., Modeling and simulation of fluid catalytic cracking unit, Ph.D.
Thesis, 2006, Thapar University, Patiala, India.
Gupta R.K., and Kumar V., Fluid catalytic cracking riser modeling in heat
transfer mode, Chemical Product and Process Modeling, 2008, Volume
3, Issue 1, Article 11.
Gupta R.K., Kumar V., and Srivastava V.K, A new generic approach for themodeling of fluid catalytic cracking (FCC) riser reactor, Chemical
Engineering Science, 2007, 62, 4510-4528.
Hagelberg P., Eilos I., Hiltunen J., Lipiainen K., Niemi V.M., Aittamaa J., KrauseA.O.I., Kinetics of catalytic cracking with short contact times, Applied
Catalysis A: General, 2002, 223, 7384.
Han I.S., and Chung C.B., Dynamic modeling and simulation of a fluidizedcatalytic cracking process. part I: process modeling, Chemical
Engineering Science, 2001(a), 56, 1951-1971.
Han I.S., and Chung, C.B., Dynamic modeling and simulation of a fluidized
catalytic cracking process. Part II: Property estimation and simulation,
Chemical Engineering Science 2001(b), 56, 1973-1990.
Harris B. J., Davidson J. F. and Xue Y., A. A. Avidan Ed., Axial and radial
variation of flow in circulating fluidized bed risers. In CirculatingFluidized Bed Technology IV, 1994, 103-110, American Institute of
Chemical Engineers, New York.
Hartge, E. U., RensnerD.and Werther J., P. Basu and J. F. Large Eds., Solids
concentration and velocity in circulating fluidized beds, In Circulating
Fluidized Bed Technology II,1988, 165-180, Pergamon Press, New York.
Hernandez-Barajas J.R., Vazquez-Roman R., and Felix-Flores Ma. G., A
comprehensive estimation of kinetic parameters in lumped catalytic
cracking reaction models, Fuel, 2009, 88, 169-178.
Heynderickx G.J., Das A.K., DeWilde J., and Marin, G.B., Effect of clusteringon gassolid drag in dilute two-phase flow, Industrial and Engineering
Chemistry Research 2004, 43, 46354646.
Gupta et al.: Modeling of Fluid Catalytic Cracking Riser Reactor: A Review
Published by The Berkeley Electronic Press, 2
-
8/11/2019 Gupta (2010)
34/42
Horio M., Morishita K., Tachibana O., and Murata M., P. Basu and J. F. Large
Eds., Solids distribution and movement in circulating fluidized beds, in
Circulating Fluidized Bed Technology II, 1988, 147-154, Pergamon
Press, New York .
Horio M., and Xikei Y., P. Basu, M. Horio and M. Hasatani Eds., Macroscopic
structure of recirculating flow of gas and solids in circulating fluidizedbeds, In Circulating Fluidized Bed Technology III, 1991, 207-212,
Pergamon Press, New York.
Huilin L., and Gidaspow D., Hydrodynamic simulation of gas-solid flow in ariser, Industrial and Engineering Chemistry Research, 2003, 42, 2390-
2398.
Huilin L., Qiaoqun S., Yurong H., Yongli S., Ding J., Xiang L., Numerical study
of particle cluster flow in risers with cluster-based approach, ChemicalEngineering Science, 2005, 60, 6757 6767.
Jacob S.M., Gross B., Voltz S.E., and Weekman V.W., jr., A lumping andreaction scheme for catalytic cracking, AIChE Journal, 1976, 22, 701-
713.
Jenkins J.T., Boundary conditions for rapid granular flow: flat, frictional walls,Journal of Applied Mechanics Transactions of ASME, 1992, 59 120
127.
Jenkins J.T., and Louge M.Y., On the flux of fluctuating energy in a collisional
grain flow at a flat frictional wall, Physics of Fluids, 1997, 9, 28352840.
Jepson S.C., Computer Simulation of a Non-Isothermal Vertical Pneumatic
Transport Reactor for Naphtha Pyrolysis, M.S. Thesis, 1986,
Northwestern University, Evanston, Illinois.
Jia C., Rohani S., Jutan A., FCC unit modeling, identification and modelpredictive control, a simulation study, Chemical Engineering and
Processing, 2003, 42, 311-325.
Jin Y., Yu Z., Qi C. and Bai D., M. Kwauk and D. Kunii Eds., The influence ofexit structures on the axial distribution of voidage in fast fluidized bed, In
Fluidization 88: Science and Technology, 1988, 165-173. Science Press,Beijing.
32 International Journal of Chemical Reactor Engineering Vol. 8 [2010], Review
http://www.bepress.com/ijcre/vol8/R6
-
8/11/2019 Gupta (2010)
35/42
Jiradiloka V., Gidaspow D., Damronglerd S., Koves W. J., and Mostofi R.,
Kinetic theory based CFD simulation of turbulent fluidization of FCC
particles in a riser, Chemical Engineering Science 2006, 61, 5544 5559.
Johnson D. L., Avidan A. A., Schipper P. H., Miller R. B., and Johnson T. E.,
New nozzle improves FCC feed atomization, unit yield patterns, Oil and
Gas Journal. 1994, 92(43), 80-86. for granular materials, with application
to plane shearing, Journal of Fluid
Johnson P.C., and Jackson R., Frictionalcollisional constitutive relations
Mechanics, 1987, 176, 67 93.
Kato K., Onozawa I., Noguchi Y., Gas-particle heat transfer in a dispersed bed,
Journal ofChemical Engineering of Japan, 1983, 16, 178-182.
Kraemer D., Larocca M., and de Lasa H.I., Deactivation of cracking catalyst inshort contact time reactors: alternative models, The Canadian Journal of
Chemical Engineering, 1991, 69, 355-360.
Kumar S., Chadha A., Gupta R., and Sharma, R., CATCRACK: A processsimulator for an integrated FCC-regenerator system, Industrial and
Engineering Chemistry Research, 1995, 34, 3737-3748.
Kunii D., and Levenspiel O., Fluidization Engineering, 2nd
edition, 1991,
Butterworth-Heinemann, Boston.
Lan X., Xu C., Wang G., Wu L., and Gao J., CFD modeling of gassolid flow
and cracking reaction in two-stage riser FCC reactors, Chemical