Utikar2010 PDF
Utikar2010 PDF
Utikar2010 PDF
Hydrodynamic Simulation
of Cyclone Separators
Utikar1, R., Darmawan1, N., Tade1, M., Li1, Q, Evans2, G.,
Glenny3, M. and Pareek1, V.
1Department of Chemical Engineering, Curtin University of Technology, Perth, WA 6845,
2Centre for Advanced Particle Processing, University of Newcastle, Callaghan, NSW 2308,
3BP Kwinana Refinery Pty Ltd, Mason Road, Kwinana, WA 6167,
Australia
1. Introduction
Cyclone separators are commonly used for separating dispersed solid particles from gas
phase. These devices have simple construction; are relatively inexpensive to fabricate and
operate with moderate pressure losses. Therefore, they are widely used in many engineering
processes such as dryers, reactors, advanced coal utilization such as pressurized and
circulating fluidized bed combustion and particularly for removal of catalyst from gases in
petroleum refinery such as in fluid catalytic cracker (FCC). Despite its simple operation, the
fluid dynamics and flow structures in a cyclone separator are very complex. The driving
force for particle separation in a cyclone separator is the strong swirling turbulent flow. The
gas and the solid particles enter through a tangential inlet at the upper part of the cyclone.
The tangential inlet produces a swirling motion of gas, which pushes the particles to the
cyclone wall and then both phases swirl down over the cyclone wall. The solid particles
leave the cyclone through a duct at the base of the apex of the inverted cone while the gas
swirls upward in the middle of the cone and leaves the cyclone from the vortex finder. The
swirling motion provides a centrifugal force to the particles while turbulence disperses the
particles in the gas phase which increases the possibility of the particle entrainment.
Therefore, the performance of a cyclone separator is determined by the turbulence
characteristics and particle-particle interaction.
Experimental and numerical studies have been carried out in the last few decades to
develop a better understanding of the flow field inside the cyclone separators. In the early
years, empirical models were built (e.g. Shepherd & Lapple, 1939; Lapple, 1951; Barth, 1956;
Tengbergen, 1965; Sproul, 1970; Leith & Licht, 1972; Blachman & Lippmann, 1974; Dietz,
1981 and Saltzmann, 1984) to predict the performance of industrial cyclones. However,
these models were built based on the data from much smaller sampling cyclones therefore;
they could not achieve desired efficiency on industrial scales as the industrial cyclone
operates in the turbulent regime while sampling cyclones operate under the transitional
conditions. One of the major drawbacks of these empirical models is the fact that they ignore
two critical factors that determine the performance of a cyclone namely the unsteadiness
and asymmetry. Many flow phenomena such as high turbulence, flow reversal, high
Source: Computational Fluid Dynamics, Book edited by: Hyoung Woo OH,
ISBN 978-953-7619-59-6, pp. 420, January 2010, INTECH, Croatia, downloaded from SCIYO.COM
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242 Computational Fluid Dynamics
vorticity, circulating zones and downflow also occur. The empirical models do not include
these phenomena in their analysis and hence are limited in their application.
Computational fluid dynamics (CFD) models on the other hand can accurately capture these
aspects and thus can take a significant role in analyzing the hydrodynamics of cyclone
separators. A validated CFD model can be a valuable tool in developing optimal design for
a given set of operating conditions. However, cyclone separators pose a peculiar fluid flow
problem. The flow in cyclone separators is characterized by an inherently unsteady, highly
anisotropic turbulent field in a confined, strongly swirling flow. A successful simulation
requires proper resolution of these flow features. Time dependent turbulence approaches
such as large eddy simulation (LES) or direct numerical simulation (DNS) should be used
for such flows. However, these techniques are computationally intensive and although
possible, are not practical for many industrial applications. Several attempts have been
made to overcome this drawback. Turbulence models based on higher-order closure, like
the Reynolds Stress Model, RSM, along with unsteady Reynolds averaged Navier – Stokes
(RANS) formulation have shown reasonable prediction capabilities (Jakirlic & Hanjalic,
2002). The presence of solids poses additional complexity and multiphase models need to be
used to resolve the flow of both the phases.
In this chapter we review the CFD simulations for cyclone separators. Important cyclone
characteristics such as the collection efficiency, pressure and velocity fields have been
discussed and compared with the experimental data. Several significant parameters such as
the effect of geometrical designs, inlet velocity, particle diameter and particle loading, high
temperature and pressure have also been analysed. The chapter discusses peculiar features
of the cyclone separator and analyses relative performance of various models. Finally an
example of how CFD can be used to investigate the erosion in a cyclone separator is
presented before outlining general recommendations and future developments in cyclone
design.
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Hydrodynamic Simulation of Cyclone Separators 243
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244 Computational Fluid Dynamics
literature. The subsequent sections discuss available CFD models and their predictive
capabilities with respect to the flow field, pressure drop and collection efficiency.
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Hydrodynamic Simulation of Cyclone Separators 245
of the interactions between the two phases. Accordingly, a classification based on the
importance of the interaction mechanisms has been proposed (Elghobashi, 1994). Depending
namely dilute and dense two-phase flow can be distinguished (See figure 2). For αp < 10–6
on the existence of mutual, significant interaction between particles, two different regimes
and L/dp > 80, the influence of particles on the gas can be neglected. This is known as ‘‘one-
way coupling’’. The influence of the particle phase is pronounced at higher volume fractions
and has to be accounted for. This is known as ‘‘two way coupling’’. For larger particles at
higher volume fraction (αp > 10–3, L/dp < 8), the interparticle interactions become important,
both through the physical collisions and indirect influence on the nearby flow field. The
collisions can lead to coalescence and break-up, which must then be considered. This regime
is frequently called the ‘‘four-way coupling’’regime. The Eulerian-Lagrangian approach is
more suited to dilute flows with one- or two-way coupling. The approach is free of
numerical diffusion, is less influenced by other errors and is more stable for the flows with
large gradients in particle velocity. The treatment of realistic poly-dispersed particle systems
is also straightforward. These attributes make Eulerian-Langrangian approach more suitable
for the simulation of gas – particle in cyclone separators. The Eulerian-Lagrangian approach
is discussed in section 1.3.2.
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246 Computational Fluid Dynamics
anisotropy and achieve realistic simulations (Hoekstra et al., 1999). While stressing the need
for a higher order turbulence model, one needs to keep in mind that as we resolve larger
ranges of time and length scales, the computational requirements escalate tremendously. A
trade-off between the accuracy and speed of computation is therefore needed for practical
simulations.
Of the three available approaches to capture the turbulent characteristics, namely RANS,
LES and DNS, RANS approach are the oldest approach to turbulence modeling. In the
unsteady RANS, an ensemble averaged version of the governing equations that also
includes transient terms is solved. Turbulence closure can be accomplished either by
applying the Boussinesq hypothesis, i.e. using an algebraic equation for the Reynolds
stresses or by using the Reynolds stress model (RSM), i.e. by solving the transport equations
for the Reynolds stresses. In the LES approach, the smaller eddies are filtered and are
modeled using a sub-grid scale model, while the larger energy carrying eddies are
simulated. The DNS solves fully-resolved Navier – Stokes equations. All of the relevant
scales of turbulent motion are captured in direct numerical simulation. This approach is
extremely expensive even for simple problems on modern computing machines. Until
sufficient computational power is available, the DNS will be feasible only for model
problems; leaving the simulation of industrial problems to LES and RANS approaches.
Although LES of full-size equipment is possible, it is still costly partly due to the escalating
computational cost near the wall region. The unsteady RANS approaches are comparatively
far less expensive.
Within the RANS approach, comparative studies have been performed for different
turbulence models. Hoekstra et al. (1999) compared the relative performance of the k-ε
model, RNG k-ε model (a variation of the k-ε model based on renormalization group theory)
and Launder, Reece, Rodi and Gibson (LRRG) models (a differential RSM model). The
simulations were compared with Laser Doppler Anemometry (LDA) velocity
measurements. Tests were performed with three different vortex finder diameters, which
produced three different swirl numbers. The results for the tangential velocity are shown in
Figure 3. For all runs, the k-ε model predicted only the inner vertex structure clearly
contradicting the experimental observations showed two distinguishing vortices. The RNG
k-ε model showed significant improvement, while the RSM exhibited the best behavior.
Pant et al. (2002) and Sommerfeld and Ho (2003) have also reported similar observations.
Gimbun et al. (2005) studied the effect of temperature and inlet velocity on the cyclone
pressure drop. They compared four different empirical models, the k-ε model, and the RSM
with the experimental data. Their study of the effect of the inlet velocity on the pressure
drop found that the RSM gave the closest agreement with the experimental results. The
superiority of the RSM over other models has been established by Meier et al. (1999), Xiang
et al. (2005), Qian et al. (2006), Wan et al. (2008) and Kaya et al. (2009). These investigations
of various characteristics of cyclone separator flow field, such as velocity profiles, pressure
drop, effect of particle size, mass loading, separation efficiency, effect of pressure and
temperature, have reemphasized the ability of the RSM for realistic prediction of the flow
field inside cyclone separators.
Although, the superiority of the RSM over the other models has been established, it is still
not clear which is the most suitable form of the RSM for cyclone separator simulations as
both algebraic and differential RSMs have been employed. Between these two, the
differential form of the RSM is more accurate and should be preferred over the algebraic
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Hydrodynamic Simulation of Cyclone Separators 247
Fig. 3. Comparison of tangential velocity profiles (Adapted from Hoekstra et al., 1999)
form when the extra cost of the calculation is affordable (Hogg & Leschziner, 1989). Within
the differential RSMs, the difference between a basic and an advanced differential RSM is
also of relevance. For example, Grotjans et al. (1999) compared the predictions of various
turbulence models with LDA measurements for the tangential velocity profile in an
industrial hydrocyclone. Turbulence models including two differential RSM
implementations, the basic Launder, Reece, Rodi (LRR) implementation and the advanced
Speziale, Sarkar and Gatski (SSG) implementation along with the standard k-ε and a k-ε
model modified to account for the streamline curvature (the k-ε cc model) were tested. They
found the flow field to be highly sensitive to the model choice, whereas the pressure
distribution predictions were relatively robust. The typical Rankine profile was obtained
only by means of the RSMs. The SSG model produced more acceptable results compared to
the LRR model in the lower part of the cyclone. The LRR model also underpredicted
tangential velocity near the cyclone center.
Despite a number of advances, the ability of unsteady RANS simulations with advanced
RSM to accurately predict complex flow structures has not been fully established. Only
relatively stable and ordered flows have been simulated. In order to fully establish their
viability for cyclone separator simulations, these models should be tested for conditions of
highly incoherent and variable PVC. Meanwhile, LES simulation of swirling and cyclone
flows is presently becoming a new standard (Derksen, 2008). Derksen and van den Akker
(2000) were among the first to simulate the PVC phenomenon by means of LES simulations.
The capabilities of LES to simulate the turbulent flow in a cyclone separator have been
reported by Shalaby et al. (2005), Derksen (2003), Derksen et al. (2006) and Shalaby et al.
(2008). Early simulations (Derksen & van den Akker, 2000) were limited to small scale
cyclones at a moderate inlet Reynolds number. With increasing computational power,
simulation of industrial scale equipment (with Re = 280000) have been reported (Derksen et
al. 2006). The LES approach seems to offer a very realistic simulation. However due to the
scale and complexity of today’s industrial cyclone separator simulations, the unsteady
RANS approach with higher order turbulence closures is the only practical approach that
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248 Computational Fluid Dynamics
offers affordable realistic predictions of flow inside cyclone. It is only a matter of time that
resolved simulations using LES will become the preferred alternative. The behavior of
particles and their interaction with continuous phase is paramount in cyclone separators
and should be accounted for regardless of the turbulence models.
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Hydrodynamic Simulation of Cyclone Separators 249
extremely intensive method for predicting the cyclone performance. Several alternatives
have been proposed, based on average, frozen and periodic LES-velocity fields. Amongst
these methods, the periodic approximation produces closest match to experimental data,
however, it is the most costly costly method in terms of computational requiremnts. Using
this approximation, the simulation results are much closer to the experimental data than the
classical Lagrangian tracking (Derksen, 2003).
Depending on the particle size distribution, agglomeration may also become an important
factor in predicting the cyclone efficiency. Particle sizes ranging from 1 to 10 μm tend to
agglomerate due to the turbulent flow. For this range of particle size the turbulence induced
motion is more dominant compared to that of both Brownian motion and gravitational
motions. Van der Waal forces are considerably strong enough between the particles to result
in particle agglomeration and bigger size particles. Sommerfeld and Ho (2003) observed that
the separation efficiency increased considerably for smaller particles in an agglomerating
regime. Although, the predictions were not in a perfect agreement with the measurements
regarding the grade efficiency curve, they revealed the importance of particle agglomeration
on the total separation efficiency.
At higher solid concentrations, the interactions between the two phases become significant
and a two-way coupling for the momentum between the particulate and fluid phases needs
to be considered. Traditionally, the particle-source-in cell (PSIC) model (Crowe et al. 1977) is
used for this purpose. In this model, the flow field is calculated first without the particle-
phase source terms until a converged solution is achieved. A large number of ‘‘parcels’’ (i.e.
discrete particles representing large groups with the same properties) are then tracked
through the flow field. The source terms are then obtained from these tracks for a second
Eulerian calculation of the gas flow. The procedure is repeated iteratively until convergence
is achieved. The accuracy of this method depends on the number of parcels. Typically a
minimum of 10000 to 20000 parcels are used. Computational effort also escalates as the
number of particles needed to represent the dispersed phase increases. For this reason, two-
way coupling therefore is still uncommon. Derksen et al. (2008) studied the effect of mass
loading on the gas flow and solid particle motion in a Stairmand high efficiency cyclone
separator using a two-way coupled Eulerian-Lagrangian simulation. They observed that
compared to one-way coupling the two-way coupled simulation yield higher overall
efficiencies. They found that the dependence of the separation efficiency on the inlet solid
loading is the result of two competitive two effects namely, the attenuation of the swirl,
which lowers the efficiency due to a lowered centrifugal force, and the attenuation of
turbulence, which augments the efficiency through a decreased turbulent diffusion of
particles.
The standard Lagrangian approach neglects the particle-particle interactions. However at
higher solid concentration, these interactions must be included. The discrete element
method (DEM) solves the force balance on individual particles and takes into consideration
both the particle-particle and particle-gas interactions and has been used to simulate the
motion of particles for highly dense flows (Zhu et al. 2007). This approach gives information
about the position and velocities of individual particles. Conventional DEM approaches
assume a simplified flow field and are not suitable for simulating the particle flow in
cyclone separators. Recent advances in DEM and its coupling with the CFD codes has
allowed simulation of particle flow within complex flow fields (e.g. Chu et al. 2009), but at
this stage the method remains very costly and is limited by the number and size of particles.
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250 Computational Fluid Dynamics
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Hydrodynamic Simulation of Cyclone Separators 251
(a) (b)
Fig. 4. Typical axial velocity profile (a) V pattern and (b) W pattern (Adapted from Harasek
et al. 2008)
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252 Computational Fluid Dynamics
C C
D D
D
A
B B
-23.3 m/s 13.0 m/s
(a) (b) (c)
Fig. 5. (a) Contours of radial velocity at a vertical plane (b) Contours of radial velocity at
horizontal cut off section B-B and C-C (c) radial velocity profile at section D-D
B B
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Hydrodynamic Simulation of Cyclone Separators 253
Typical contour plots of the tangential velocity in both vertical and horizontal planes are
shown in figures 6a and 6b, respectively. Figure 6c shows comparison of numerical and
experimental results for tangential velocities from Wang et al. (2006). The cyclone has an
asymmetrical shape and as can be seen from figure 6a, the axis of the cyclone does not
exactly coincide with the axis of the vortex. The Rankine vortex can also be visualized.
Figure 6b shows the plot of the tangential velocity across horizontal lines. It is observed that
the inlet speed is accelerated up but then it decreases when the gas spins down along the
cyclone wall. At a certain point flow reversal takes place and the gas flows in the reverse
direction to the exit. Before entering the vortex finder, the gas collides with the follow-up
flow and velocity decreases sharply. This causes energy loss and pressure drop. The
tangential velocity is highly dependent on the geometrical design, wall friction and particle
loading. Wang et al. (2006), Wan et al. (2008) and Raoufi et al. (2009) have demonstrated the
use of CFD in reasonably predicting the tangential velocity under varied conditions.
The temperature also has an effect on the tangential velocity (Shi et al., 2006). A minor
decrease is noticed at the area of the inner vortex with increasing the temperature. The
overall and maximum tangential velocity is also decreases on increasing the temperature. As
the gas moving toward the vortex finder, the area of inner vortex become narrower and the
outer vortex become wider. The main reasons for the changes are that on increasing the
temperature the gas density decreases and viscosity increases. Furthermore, the centrifugal
force is proportional to the square of the tangential velocity, therefore higher temperature
causes the centrifugal force to decrease hence the lower separation efficiency.
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254 Computational Fluid Dynamics
Shepperd and Lapple (1939), Casal and Martinez (1983), Dirgo (1988), Coker (1993), as well
as with CFD predictions using the k-ε model and the RSM model. The result showed that
the RSM model produced the closest pressure drop prediction. The k-ε results showed a
reasonably good prediction at about 14% -18% deviation. The CFD studies on gas-solid flow
in a cyclone separator by Wang et al. (2006) using the RSM model also showed an acceptable
agreement with experimental data for Stairmand high efficiency cyclone Hoekstra et al.
(1999).
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Hydrodynamic Simulation of Cyclone Separators 255
(FCC) operate at high temperatures and pressures. The operating temperature and pressure
will influence the gas density and viscosity and their effect on the drag force. Therefore, for
these industries, the operating temperatures and pressures are the important parameters
that determine the pressure drop in the cyclone. Shin et al. (2005) (See figure 8) conducted
numerical and experimental study on the effect of temperature and pressure on a high
efficiency cyclone separator. They found that the pressure drop decreases at a higher
pressure and lower temperature. Higher pressures and lower temperatures increase the gas
density which in turn creates a higher dynamic pressure hence the higher pressure drop.
This trend is confirmed by similar experimental and numerical studies by Gimbun et al.
(2005) and Shi et al. (2006)
Fig. 8. Comparison of experimental and numerical result for pressure drop at a given flow
rate in a elevated pressure and temperature ( Adapted from Shin et al., 2005)
5. Collection efficiency
The fraction of solids separated at the outlet is defined as the collection efficiency. Since
cyclone separators usually handle various sizes of particles, the efficiencies are defined
according to a continuous narrow interval of particular group size particles. The swirling
motion within the cyclone separator causes large particles to travel swiftly to the cyclone
walls and roll down to the outlet. On the other hand, the smaller particles are often drifted
in upward spiral flow due to the slower speed and escape through the gas outlet. This
typically yields an S shaped curve for the collection efficiency. Particle collection is the net
effect of various forces acting on the particles. It is well known that the collection efficiency
is governed by the centrifugal, gravitational and drag forces (Blachmann & Lipmann, 1974).
Factors such as the particle-particle and particle-wall interaction also influence the cyclone
efficiency. Their effect is not yet fully understood and hence often neglected in empirical
modelling. Further, the empirical models are based on the lab scale data. Depending on the
operating conditions, the flow inside the cyclone can be laminar, transitional or turbulent for
the lab scale equipment. The actual industrial cyclones operate in the turbulent regime
where the friction and its corresponding outcomes are significant. Therefore the particle
collection efficiency models based on the lab scale data may not accurately predict the
collection efficiency for industrial cyclones. At lower mass loading (<5-10 g/m3) the
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256 Computational Fluid Dynamics
empirical models perform reasonably well (Cortes and Gil, 2007). Many cyclone separator
systems of industrial interest such as the FCC, PFBC and CFBC are well known for handling
high particle loadings, where, the interphase and interparticle processes become important
and the predictive ability of the conventional models is poor. Numerical studies then
become necessary to achieve a better understanding of the cyclone collection efficiency.
5.1 Effect of mass loading, particle diameter and inlet velocity on cyclone efficiency
Qian et al. (2006) investigated the effect of mass loading on the collection efficiency. The
results of their simulation are shown in figure 10. The collection efficiency is defined as the
ratio of mass flow rate at the inlet and outlet for a converged steady condition. It is clearly
evident that the collection efficiency increase on increasing the particle loading. The result is
consistent with most of the previous studies (like Stern et al. 1955). Different mass loading
for various particle group-sizes affect the grade efficiency differently. Smaller particle group
sizes show a higher efficiency increase compared to the larger particle size groups. These
findings are also confirmed by the simulation and experimental study by Luo et al. (1999)
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Hydrodynamic Simulation of Cyclone Separators 257
and Ji et al. (2009). The increase in cyclone efficiency with solid loading is more pronounced
at lower gas velocities (Hoffmann et al. 1991, 1992).
Fig. 10. Separation efficiency simulation result for various inlet particle concentration with
constant inlet velocity (Adapted from Qian et al., 2006)
Mass loading effect is usually coupled with the particle diameter. At lower mass loadings,
the smaller particles (< 10μm) tend to be dispersed and hauled by the gas flow and escape
from the vortex finder at the top of the cyclone separator (Derksen 2003 and Wan et al.
2008). But on increasing the particle mass loading, a sweeping effect of the coarser particle
that sweeps away the smaller particles to the cyclone wall is observed. The swept particles
then roll down and are collected at the bottom of the cyclone. This effect is also responsible
for the formation of agglomerates. Agglomeration causes increased centrifugal force on the
smaller particles improving their collection efficiency. Wan et al. (2008) also note that on
increasing the particle loading, both the downward flow and the axial velocity at the centre
(in upward direction) increase. This aids in higher collection efficiency in the cyclone
separator.
The inlet gas velocity also has an effect on the collection efficiency. The effect is also tightly
related to the particle mass loading. Figure 11 shows the effect of increasing the inlet gas
efficiency increases with the inlet gas velocity. For smaller particle sizes (< 10 μm), the
velocity on the collection efficiency for a given solid loading (Ji et al. 2009). The collection
increase in the efficiency with respect to the gas velocity is more pronounced. As the particle
size increases, the effect of the inlet velocity becomes insignificant. These observations are in
line with the experimental work of Fassani et al. (2000) and Hoffmann et al. (1991). The
higher inlet velocity, results in the higher tangential velocity, thus leading to a higher
centrifugal force and collection efficiency. Patterson and Munz (1989) analyzed the effect of
several parameters including the gas temperature (300K - 2000K), inlet gas velocities (3 m/s
– 42 m/s) and particle loadings (up to 235.2 g/m3) on the cyclone efficiency. Their analysis
showed that there is an increase in the cyclone efficiency especially under high temperature
condition.
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258 Computational Fluid Dynamics
Fig. 11. Grade efficiency for different inlet velocity (Adapted from Ji et al., 2009)
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Hydrodynamic Simulation of Cyclone Separators 259
cyclone separator. Concrete methodology is not yet available to optimize the vortex finder.
Saltzmann et al. (1984) and Iozia et al. (1989) studied the effect of vortex diameter on the
cyclone performance. Kim and Lee (1990) provide information on how the vortex finder and
cyclone body diameter affects the cyclone performance. Lim et al. (2004) evaluated different
geometries of the vortex finders to optimize the performance. Their results concluded that
with smaller vortex finder diameters, the tangential velocity in the inner region of the
cyclone increases resulting in a higher collection efficiency. These findings were supported
by Raoufi et al. (2009) using CFD modelling.
CFD modelling has opened an avenue for the cost effective optimization of the cyclone
geometry. Many geometrical designs have been proposed using CFD studies that can be
used to improve the performance of cyclone separators. The list of these modifications
include, (i) the use of different inlet types (scroll, helicoidal, axial spiral double inlet and
square cyclone inlets) can be found in Cortes and Gil (2007), Wang et al. (1999) and Zhao et
al. (2006), (ii) including a long coned (Lee et al., 2006), and (iii) the variation in body and
cone height (Xiang et al., 2005).
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260 Computational Fluid Dynamics
cluttering on the cyclone walls while swirling down. For the uniform particle size, most
severely eroded sites were the top part of the cyclone cylinder (near the inlet) and the cone
of the cyclone. This observation is in accordance with the experimental findings of Jones et
al. (1979) and Yongdahl et al. (1984). On using a particle size distribution, the most eroded
part in the cyclone was at the intersection between the cyclone cylinder and cone. This
demonstrates the sensitivity of the erosion to particle size distribution.
μm to 160 μm) was simulated using the Lagrangian tracking. The resulting particle
To investigate the effect of particle size distribution, a wider inlet particle size distribution (1
trajectories are shown in Figure 13. It is clearly evident that the larger particles are collected
at the walls while the smaller particles escape downwards in spiral manner. This is because
the drag force on the smaller particles is larger than the centrifugal force preventing their
transportation to the cyclone wall. The results show that the particle with sizes < 40 µm
escape from the bottom of the cyclone after a certain residence time while the particle with
sizes > 60 µm keep spinning around the mid level for significantly longer. Wang et al. (2006)
have shown this phenomenon experimentally using ceramic balls. One possible explanation
lies in the balance of the centrifugal force versus the gravitational force. As the larger
particles roll down the conical part, the centrifugal force on the particle increases because
the radius of the cyclone decreases while the tangential velocity of the particle remain
almost the same. The larger particles will eventually be collected at the solid outlet due to
the particle-particle interaction. However, some of the particles will stay at the cyclone wall.
There also appears to be a critical value of the particle diameter below which the particle is
not expected to be collected at the outlet. The critical value of particle diameter is related to
the cyclone geometry, gas inlet velocity and particle properties.
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Hydrodynamic Simulation of Cyclone Separators 261
Fig. 13. Single particle trajectories of size (a) 5 µm b) 20 µm (c) 40 µm (d) >60 µm
Fig. 14. Comparison of erosion rate with various gas and particle flow rate
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262 Computational Fluid Dynamics
At lower gas velocities, lower momentum is imparted by the gas on the particle, which
sometimes prevents a second rebound to happen and the particle is forced to stay near the
cyclone wall. Consequently, the rate of erosion is lesser at lower velocities. As the gas
velocity is increased, the particle rebound is more likely to happen. Since the particle
rebounds are not perfectly elastic, it reduces the impact angle gradually after the first
rebound, thus increasing the average erosion rate. At even higher gas velocities, the
centrifugal force on the particles increases. This makes some particles reach the cyclone wall
faster. As a consequence, a layer of slow moving particles is formed that protects the walls
from collision by other particles which then reduces the rate of erosion slightly.
7. Summary
Due to their simple and robust construction, cyclone separators are widely used in the
chemical and process industries. In spite of their simple construction, flow patterns inside
cyclones are highly complex and not fully understood. Understanding the flow is critical in
accessing their performance and CFD is a useful tool in providing this information.
However, due to the very nature of the flow, the application of CFD should be exercised
with prudence. In order to accurately resolve the unsteady nature of the flow inside a
cyclone, higher order numerical discretization along with unsteady simulation (unsteady
RANS or LES) are needed. It also requires a higher order turbulence model (atleast second
order like RSM) for the unsteady RANS simulations. For resolving the gas flow field, the
LES provides superior results than the RANS approach. However, the cost of LES is
prohibitive for the industrial-scale devices. Recent developments turbulence modelling such
as the differential RSMs have shown a light of hope to achieve LES level of accuracies at
RANS cost. However, the conditions under which the unsteady RANS solver can be used in
place of the LES need to be explored.
To obtain the particle flow, the Eulerian-Lagrangian formulation with either one way or two
way coupling should be employed. The necessity of capturing the unsteadiness of the gas
flow in combination to the flow of poly-disperse particulates demands far superior
computational power than what is currently available. Therefore, a considerable progress
needs to be made in multiphase flow simulation of cyclones. Factors like interparticle
phenomena and the boundary condition at the wall also need a careful attention. The
advances in the DEM-CFD coupled simulations will bring new insight in the calculation of
highly-loaded cyclones. Nevertheless, the two phase flow simulations have provided some
useful insight into the cyclone operations and have provoked to question the existing
theories on the particle flow and separation in cyclones.
The enormous computational requirements, even for the minimal modelling of cyclone
phenomena, have limited our ability to go beyond a simple understanding of the flow
structures, collection efficiency and global design issues. More systematic research for
addressing the other important issues, such as reasonable estimates of the cyclone natural
length and vortex finder dimensions, is needed. Furthermore, the loss of coherence in the
vortex and the ensuing chaotic flow patterns and the effect of swirl-stabilization are some of
the other topics that remain unanswered. With increasing computational power, it is
envisaged that in the near future we will be able to perform fully resolved simulations on
cyclones which will not only answer the above questions but will also advance our
knowledge of cyclone operations and even optimize them for specific operational
circumstances.
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Hydrodynamic Simulation of Cyclone Separators 263
8. References
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Computational Fluid Dynamics
Edited by Hyoung Woo Oh
ISBN 978-953-7619-59-6
Hard cover, 420 pages
Publisher InTech
Published online 01, January, 2010
Published in print edition January, 2010
This book is intended to serve as a reference text for advanced scientists and research engineers to solve a
variety of fluid flow problems using computational fluid dynamics (CFD). Each chapter arises from a collection
of research papers and discussions contributed by the practiced experts in the field of fluid mechanics. This
material has encompassed a wide range of CFD applications concerning computational scheme, turbulence
modeling and its simulation, multiphase flow modeling, unsteady-flow computation, and industrial applications
of CFD.
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Utikar, R., Darmawan, N., Tade, M., Li, Q, Evans, G., Glenny, M. and Pareek, V. (2010). Hydrodynamic
Simulation of Cyclone Separators, Computational Fluid Dynamics, Hyoung Woo Oh (Ed.), ISBN: 978-953-
7619-59-6, InTech, Available from: http://www.intechopen.com/books/computational-fluid-
dynamics/hydrodynamic-simulation-of-cyclone-separators