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Flow simulation in industrial cyclone separator

C. Bhasker *

BHEL (R&D) Division, Vikasnagar, Hyderabad 500 093, India

a r t i c l e i n f o

Article history:Received 8 April 2008Received in revised form 14 August 2009Accepted 17 August 2009Available online 25 September 2009

Keywords:Recycle cyclone collectorCirculating fluidized bed combustionCAD modelStructured multi-block gridsCFD – finite volume techniquePressure based algorithmsFlow recirculation – geometry modificationPartition platesPressure dropParticle Trajectories

a b s t r a c t

The problem of ash settling on super-heater tube bank, due to improper velocity distribution, in thecyclone separator used at Circulating Fluidized Bed Combustion (CFBC) has been investigated by meansof computational fluid dynamic techniques. With the help of Computational Aided Design (CAD) softwarepackages, the geometries of recycling cyclone, has been constructed. With the suitable domain decompo-sition for the cyclone geometry, multi-block structured mesh has been generated and exported to com-mercial Computational Fluid Dynamic (CFD) solver – TASCflow. After assembling these grids in the flowsolver, duplicate elements at mating surfaces are eliminated through generalized grid interfaces. Incom-pressible viscous flow for the specified flow conditions are simulated and numerical results are inter-preted through contour plots and streak lines. The velocity distribution pattern obtained from theanalysis exhibits strong flow recirculation with large turbulent eddies in the cyclone outlet. The analysisalso observed high pressure drop across the cyclone separator. To improve the velocity distribution andto reduce the pressure drop, geometry has been modified with the deflector plates in the outlet duct andrepeated the simulation. The results obtained for modified geometry are encouraging and shown theimproved velocity distribution pattern in the outlet duct. The calculation of particle trajectories dependsupon Stokes number, relative velocity of fluid/particles and concentration of particles. If the Stokes num-ber, defined as the ratio of particle response time to system response time is less than one, particlesmotion is inline with the fluid motion. If the Stokes number is greater than one, particle motion deviatesthe fluid streams. Effects of these particle impacts are significant on component surface, especially, whenthey reacts/rebounds the wall surfaces.

� 2009 Elsevier Ltd. All rights reserved.

1. Introduction

Circulating Fluidized Bed Combustion (CFBC) technology, whoseschematic is shown in Fig. 1 holds great promise for the powergeneration, from the point of Indian coals of high ash content. InFig. 1 the legend (1) indicates transport of fuel (low grade coals,high ash rejects, high sulphur coals, Lignites, etc.), (2) high carbonburnout, (3) in situ pollution control (sox control by using limestone), low combustion temperature and staged combustion re-sults), (4) excellent operability, (5) simplified fuel preparationand feeding, i.e., no pulverizing of fuel, only crushing is required,and (6) high heat transfer rate results in compact design of CFBCtechnologies [1–3].

The cross sectional view of cyclone separator along with othercomponents used in CFBC plant are shown in Fig. 2. Flue gas pro-duced entrains the solids out of the combustor to a refractory linedcyclone. The cyclone collects more than 99% of the incoming solids,which travel down the conical bottom to the seal pot blower and

are eventually siphoned back into the combustor. Two positive dis-placement-type blowers supply the required fluidizing air for theseal pot. The flue gas leaves the cyclone top flows onto a convectivepass containing three stages of super-heater and economiser. Atubular air heater forms the last heat recovery surface and it pre-heats the primary air and secondary air streams separately withthe air flowing inside the tubes and gas flowing outside them.The flue gas is then enters in an electrostatic precipitator. Two in-duced draft fans ensure near atmospheric pressure levels at the cy-clone outlet, and exhaust the flue gas to the stack. Although theoperation of the plant with varied load is successful, there wereproblems related to flue gases, which are coming from the cycloneoutlet are settling on the super-heater tubes [4,5] concern the plantefficiency.

Cyclones [6–9] play a critical role in separation of solid particlesin flowing fluids from one component to other in process equip-ment. In this device, the flow enters the constant-diameter partof the cyclone tangentially and accelerates on its way down intothe conical section resulting in a strong swirling flow with complexflow pattern. At the base, the particle-laden flow escapes throughthe lower end, while the rest reverses and swirls along the center-line through exit duct of cyclone separator. The reliable computerdesign [10] for predicting the effect of geometry changes and

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* Address: 402 Residency Apartment, Ashoknagar Bridge, Hyderabad 500 020,India. Tel.: +91 (40) 4011 1584; mobile: +91 (0) 98492 52948.

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Advances in Engineering Software 41 (2010) 220–228

Contents lists available at ScienceDirect

Advances in Engineering Software

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system parameters on cyclone efficiency would be a valuable tool.This in turn helps designer for optimization of cyclone collector forthe specific operating conditions. In order to accomplish this, twotypes of computer packages are normally used – the first type isbased on established empirical rules for specific handling, formaterial example: the geometry is independent of computer de-sign program. Although this type may be adequate for many con-ventional cyclone applications, they do not cater for unusualcyclone geometries. Essentially, they are used to predict an initialdesign, which undergo operational trials to confirm effectiveness.The alternative is to use a computational fluid dynamic package;which computes fluid flow equations including turbulence losses.

The large swirl velocity produces difficulties for computation ofviscous flow in the cyclone separator. Reynolds-Averaged NavierStokes equation approaches with k–e model using standard/RNGwall functions are still widely used technique for prediction ofvelocity pattern and pressure drop across the cyclone separator.

Though the large eddy simulations are best options to predict vis-cous flows in a geometry like cyclone separator, but involves un-steady flows and limits the available computational resources. Inorder to understand the flow pattern in cyclone separator, theanalysis presented in this paper for two aspects – firstly analysesthe flow in the existing configuration to study the velocity distribu-tion inside the cyclone separator. In the later part of investigation,two-phase flow (air and discrete particle) motion are describedwith modifications of outlet duct, based on success obtained withthe use of CFD on complex flow problems used in power plantapplications [11,12].

2. Problem description

The geometry of cyclone separator used in paper manufactur-ing industry is shown in Fig. 3, which is different from the con-ventional cyclone separator, as it is placed between boiler and

Fig. 1. CFBC power plant with the location of cyclone collector.

Fig. 2. Cross sectional view of CFBC plant with several internals.

C. Bhasker / Advances in Engineering Software 41 (2010) 220–228 221


convective pass of power plant. However, its basic geometryresembles with conventional one, in terms of tangential inlet, cy-clone body, conical chamber, vortex finder, etc. In order to ensurethe streamlined flow, outlet duct is attached to it differs from theconventional cyclone used in gas-turbine and other processindustries. The cyclone consists of an upper cylindrical part, witha tangential inlet and lower part with an exit at the apex. Theyare used to separate dispersed heavy substance from a fluid oflower density, the suspension to be separated being injected withhigh velocity tangentially into the cyclone. This result in high spinvelocities within the cyclone, which produce a large centrifugalforce field and hence dense particles drift towards relative thefluid. The separated material leaves the cyclone at its apex, whileclean fluid is discharged at the top through the overflow pipe.

During the operation, it is observed that flue gas settling on thesuper-heater tubes due to improper velocity distribution in the cy-clone separator. As a result, solid particles motion deviates thefluid stream and causes erosive wear on cyclone outlet duct wallsand super-heater tubes. These effects in turn, lead to performancedegradation of equipment and require design alternatives.

3. Computational mesh – grid generation

Approaches [13,14] used commonly for integration of governingdifferential equations are finite difference, finite elements and fi-nite volumes. In all these methods, the solution domain is subdi-vided into discrete volume or elements through computationalgrid in space. Meshing is an integral part of the computer-aidedengineering (CAE) analysis process. The mesh influences the accu-racy, convergence and speed of the solution. The mesh, dependingupon geometry complexities can be body fitted structured multi-block hexa-hedral elements or unstructured tetra-hedral elements.

The tetra-hedral elements have the problem that they do notstretch or twist well, therefore, the grid is limited and isotropic,i.e., all the elements have roughly the same size and shape. Thisis a major problem, when trying to refine the grid in a local area,often the entire grid must be made much finer, in order to getthe point densities required locally. Hence, the multi-block struc-tured, which has lot of flexibility are preferred for most CFD calcu-lations. The industry standard mesh generation software ICEM-CFDprocured has been employed to generate grid for the cyclone col-lector geometry. The CAD surface data of geometry model as IGESformat has been imported in ICEM-CFD.

The geometry engine in the ICEM-CFD provides flexible toolsgeneration of computational mesh for complex geometry by blank,unblank and grouping option. In order to proceed for mesh gener-ation, initialised block is placed on the computational domain andthe same has been divided through horizontal and vertical splittingoptions, according to geometry shape and internals. The resultingblock edges are aligned to geometrical edges using project/associ-ate commands. With this referenced block, with the selection of itsface, topologically connected blocks are constructed for rest of thegeometrical part. To obtain the computational mesh in threedimensions, nodes to master and slave edges are specified. Soft-ware provides several distribution laws for clustering the nodeson boundary surfaces. The pre-view of the nodes on the masterand slave edges with proper direction provides the first insightfor the proper mesh distribution on the geometrical part. The acti-vation of volume mesh, under mesh generation option providesthree dimensional mesh for the specified solver format. After com-pletion of mesh generation different parts, the assembled mesh im-ported in flow solver is shown in Fig. 4.

4. Mathematical formulation

The conservation equations of mass and momentum for incom-pressible fluid flows [15] are written as

@uj

@xj¼ Sm ð1Þ

@quj

@tþ @quiuj

@xjþ @P@xj¼ @sij

@xjþ Sfi

ð2Þ

Fig. 3. Geometrical description of cyclone collector.

Fig. 4. Computational mesh for cyclone collector.

222 C. Bhasker / Advances in Engineering Software 41 (2010) 220–228


where uj is the component velocity, Sm the mass source, uiuj theReynold stress, P the pressure, q the density, t the time, xj the direc-tion, sij the diffusion terms, and Sf1 is the momentum source. Usingaverage of velocity and pressure, these equations can be written as

@�ui

@xj¼ 0 ð3Þ

@�ui

@t@

@xiðuiujÞ ¼ �

1q@P@xiþ @

@xjl @�u@xj

� �� @

@xiðuiujÞ ð4Þ

where �u is the mean velocity, P the Mean pressure, and l is theviscosity.

The turbulent stresses and mean strain fields are assumed to beconnected by the effective viscosity hypothesis is

�q�ui�uj ¼ lt@ui

@xiþ @uj

@xj

� �� 2

3qkdij ð5Þ

where lt is the turbulent viscosity, dij the Kronecker delta, k the tur-bulent kinetic energy, and e is the dissipations of turbulent kineticenergy. In Eq. (5) turbulent viscosity is defined as

lt ¼ clqk2

eð6Þ

The two turbulence quantities appearing in the above equation kand e are obtained from following transport equations

@

@tðqkÞ þ @

@xjðqujkÞ ¼

@

@xj

lt

rk

@k@xj

� �þ Pk � qe ð7Þ

@

@tðqeÞ þ @

@xjðqujeÞ ¼

@

@xj

lt

rk

@e@xj

� �þ e

kðce1Pk � ce2qeÞ ð8Þ

Pk ¼ �u0iu0j@ �ui

@xjð9Þ

where the constants cl, ce1, ce2, e1, and e2 are assumed to have thevalues of .09, 1.44, 1.92, 1.0, and 1.3, respectively. In order to cap-ture the viscous effects, two equation turbulence model based onintensity and length scale with standard wall functions are em-ployed. The commercial solver TASCflow version at the time of sim-ulation contains only few turbulence models besides large eddyflow simulation. The higher order models like SST and Relizabletwo equation models, k–x are good for predicting swirl flows wereunder development and released in later versions. It is of customerinterest to know the flow distribution in the cyclone collector to-wards convective pass comprises tube bundles, where ash deposi-tion concerns the efficiency of the plant. Towards this, indepthinvestigations for this component were aimed to study the flowand pressure losses with existing/modified configuration using ad-vanced pre/post-processors and solver.

4.1. Solver numerics for flow aspects

In the solver, the conservation (mass, moment, and energy)equations are integrated [16] over the volume as

@

@t

Zvqujdv þ

Zvqujdnj ¼ 0 ð10Þ

@

@t

Zquidv þ

Zsqujuidnj ¼ �

Zs

Pdni þZ

sleff

@ui

@xjþ @ui

@xi

� �dnj

þZ

vSuidv ð11Þ

@

@t

Zvq/duþ

Zsquj/dnj ¼

ZsCeff

@/@xj

� �dnj þ

Zv

S/dv ð12Þ

where leff the effective viscosity, Ceff the effective thermal conduc-tivity, / the scalar associated with energy, dni the differential carte-sian components of the outward normal surface vector, v theintegration over volume, s the integration over surface, and dv is

the differential of volume. Integration of Eqs. (10)–(12) over thecontrol volume shown in Fig. 5 yields algebraic form of balance ofconvective and diffusive fluxes across the control volume.The dis-crete form of integral equations across control volume are writtenas

qv q� q0

Dt

� �þX

ip

ðqujDnjÞip; mip ¼ ½qujDnj�0ip ð13Þ

qVui � u0

i

Dt

� �þX

ip

mipðuipÞ ¼X

ip

ðPDniÞip

þX

ip

leff@ui

@xjþ @uj

@xi

� �� Dnj þ Sui ð14Þ

qV/� /0

Dt

!þX

ip

mip/ip ¼X

ip

Ceff@/@xj

Dnj

� �ip

þ S/ ð15Þ

where u0 is the velocity at t = 0, q0 the value of density at t = 0, ip theintegration point, Dt the time step, and Dn is the space step ofcartesian components of the outward normal surface vector. Soft-ware uses algebraic multi-grid interpolation techniques to evaluatefluxes of the variable values at cell faces from the values stored atthe cell center. The principle of this method is based on the fact thaton a given grid, short wave errors are damped out faster than longwave errors. Hence, for overall elimination of errors, multi-gridmethods do not obtain solution with the one numerical grid butby switching between finer and coarser grids during the solution.

The integration of differential equations over finite volume usu-ally leads to a system of coupled linear equations, which needs tobe solved with a suitable algorithm. For the discretisation proce-dures mostly employed, the value of variable at any computationalnode is implicitly linked to the values at six neighbouring nodesonly. Consequently, the coefficients of matrices of the linear equa-tion system to be solved have only five or seven non-zero diagonalelements. Such sparse coefficient matrices often require iterativemethods [17] which require large computer memory for simulta-neous storage of the coefficients for all the variables at all thenodes. One of the principal sources of error in CFD calculationsare due to the discretization of the flow domain into a finite num-ber of small cells over which, the governing equations are inte-grated. Another source of error results from the linearization ofnon-linear equations. The definition of convergence of the iterativescheme used for solving the equation also leaves some scope for er-rors. At any stage of a calculation, each equation will not be satis-fied exactly, and the residual of an equation identifies by howmuch the left-hand-side of the equation differs from the right-hand-side at any point in the space. If the solution is exact thenthe residuals are zero. Exact means that each of the relevant finitevolume equations are satisfied precisely. However, these equations

Fig. 5. Typical control volume.



only model the physics approximately, this does not mean that thesolution exactly matches, what happens in reality. If a solution isconverging, residuals should decrease with successive time steps.

4.2. Boundary conditions and convergence

Computational mesh of the cyclone parts are imported in solverpre-processing module. The flow solver TASCflow code is very sen-sitive towards SI unites and grid quality aspects especially withskew angles. Computational mesh created in millimetre was scaledto metre using transformation option available in the solver. Afterchecking the grid for quality aspects, material properties and phys-ical models are selected. The velocity and pressure conditions areprescribed at inlet and exit boundary faces. In order to capturethe viscous effects, two equation turbulence model based on inten-sity and length scale with standard wall functions are employed.Due to tangential nature of cyclone inlet with its body, generationof hexa-hedral multi-block mesh slightly skewed. Even with this,convergence of numerical simulation faced difficulties howeverwas resolved with suitable under-relaxation factors. Marching ofdiscretized equation on control volume grid points requires goodinitial estimate for faster convergence. The values for turbulenceintensity and length scale are critical and carefully assigned for in-let boundary conditions. Since the flow inside the cyclone collectoris highly rotational and the option of covariant velocity in normaldirection has been used for the initial estimate. In advanced controlparameters, the flag pmass-true has been activated to evaluatemass flux report at inlet and exit boundaries. With the properselection of time step, using upwind 2nd order discretizationscheme, governing equations are iterated, till the maximum targetconvergence value of order .0001 is reached. The simulation con-verged in 86 iterations has took significant CPU clock time onPentium-III intel processor to obtain the numerical results forpost-processing. To evaluate the pressure drop across collectorinlet and exit locations, macro has been written and executed inthe TASCtool. Tasctool is an advanced command language editor,which helps to manipulate the scalars during problem setup andin visualisation of results.

5. Velocity distribution in the existing cyclone separator

The velocity pattern in the horizontal plane is shown in Fig. 6. Itis observed that flow distribution in the cross sectional planeshows strong flow recirculation in the exit duct. It can be seen thatthe flow forms descending and ascending streams which flow par-allel to one another before leaving through vortex tube. Thisbehaviour is expected and due to the fact, that swirling flows havetendency to resist radial motion. The variation of flow distributionindicates the unequal flow in the outlet duct. From this figure, it isalso observed that the flow is taking place in the left side of the cy-clone with 28 m/s while in the rest of the blue color zone is only 3–8 m/s. The pressure loss computation is carried out through amacro based on mass boundary is comes around 5700 Pa.

The present cyclone is having no flow deflector, and hence itgives the flow into the left side of the cyclone, which causes selec-tive erosion of the super-heater tubes and probably, bad heattransfer of the flue gas. Several streaklines released from inletabove cyclone are shown in Fig. 7. The flow lines after followingangular motion creating the recirculation at the exit of cyclone.The flow recirculation in the cyclone collector outlet duct, causeslarge pressure drop across the device and hence reduces the effi-ciency. Simulation of flow in the existing configuration of cycloneseparator also indicates that due to large flow recirculation parti-cles are unable to accelerated in the outlet duct region.

6. Flow simulation in the cyclone collector with modifiedgeometry

The existing viscous steady flow simulation provides valuable in-sights for deceleration of particles due to low velocity prevailing atsome portion of outlet duct. To improve the velocity distribution,geometrical changes with two baffle plates in the outlet duct of thecyclone separator are proposed. With suitable domain decomposi-tion for the modified geometry, multi-block hexa-hedral elementmesh has been generated and shown in Fig. 8. The reason behindadding two partitioned plates in the outlet minimises the flowrecirculation and exhibits better flow distribution in the exit

Fig. 6. Velocity distribution in the middle plane of the cyclone collector.

Fig. 7. Streaklines from the inlet of cyclone collector in the existing configuration.



location. Inside the computational domain, these thick plates giveraises the complexity in flow simulation and requires the treatmentof block-off region/porous medium specification. However, care hasbeen in grid generation process, in such a way that, there are no gridpoints in the thickness region of plates. With the component veloc-ities at inlet and pressure boundary at exit, with suitable initialguess, the viscous flow simulation has been carried out to studythe flow pattern and pressure drop. After successful flow simulation,different size discrete particles are assumed to enter along with fluidin the cyclone separator. With prescribed physical properties of par-ticles, path of the particles in cyclone separator is obtained usingLagrangian Particle Tracking method. Due to presence of more num-ber of grid interfaces, large number of grid nodes and incorporationof two-phase flow motion, the simulation took almost one and halfday CPU time of Intel-III Processor with 256 MB RAM.

7. Motion of solid particle in flowing fluid

Prediction of flows involving a dispersed phase requires sepa-rate calculation of each phase with source terms generated to ac-count for the interaction between the phases. Consider a discreteparticle travelling in a continuous fluid medium. The equation ofmotion for particle in flow fluid, for which detailed derivationsare available [18] are written as

Facc þ Faddedmass ¼ Fbouyancy þ Fvisc;p � Fdrag � Fhistory ð16Þ

Facc ¼ mpdVi

dtFaddedmass ¼

12

mfddtðVi � uiÞ

Fbouyancy ¼ ðmp �mf Þgi Fdrag ¼ CdpD2

8qf jVi � uijðVi � uiÞ

Fvisc;p ¼ mfDuDt

Fhistory ¼32

D2qf

ffiffiffiffiffiffiffiffiptf

p Z t

0

ddtðVi � uiÞ

dsffiffiffiffiffiffiffiffiffiffiffit � sp

where Cd is the Drag force, D the diameter of particle, mp the mass ofthe particle, Vi the velocity of particle, and ui is the velocity of fluid,In general, the pressure gradient and F history force terms are onlysignificant, when the fluid density is comparable to or greater thanthe particle density. In such a case, the equation of particle acceler-ation depends upon the drag, viscous and added mass forces. Basedon the particle Reynolds number defined as

Rep ¼qf jv f � vpjd

- ð17Þ

Drag coefficient for particle (CD) will be obtained from the experi-mental results [19] shown in Fig. 9. The widely applied methodavailable to determine the behaviour of the dispersed phase is totrack several individual particles through the flow field. Each parti-cle represents a sample of particles that follow an identical path.The behaviour of the tracked particles are used to describe the aver-age behaviour of the dispersed phase. This method is called sepa-rated flow analysis has been implemented in TASCflow softwareas Lagrangian tracking model.

The model works under the assumption that particle interac-tions are important in the flows, where the discrete phase volu-metric concentration is greater than 1%. Also there are noparticle source terms to the turbulence equations. The model onlyconsiders spherical inert particles, where particle–particle interac-tions are not considered.

7.1. Computation of particle trajectories

Prediction of particle motion in turbulent flows requires anaccurate estimation of turbulent behaviour and velocity fluctua-tions. Turbulent flows consist of a cascade of turbulent structuresor eddy vortices which transport and dissipate turbulent energy.These eddies have a spectrum of characteristic sizes, life timesand energy levels. A particle travelling through a turbulent flowwould be exposed to this entire spectrum of eddies, interactingwith each for some characteristic time or distance. The challengeis then to find a tractable method to describe the influence of tur-bulent fluid velocity on particle flow. To account for the influenceof turbulent fluid fluctuations on particle motion, the methoddeveloped [20–22] was fine tuned based on turbulent velocity,eddy life time, length scale and was implemented in this solver.

In order to activate particle trajectories module in the solver,execution of tascbob3d module at DOS prompt is required. Priorto this, in the user directory, a grid file prepared for flow simulationmust exist. After reading the grid file, it will display firstly theprompts for block-off and boundary conditions specification formodifications. After keying a (attributes), the pre-processor dis-plays the physical models already chosen. It later asks the user tore-specify the attributes. At this time, user will be asked, whetherflow model includes Lagrangian Particle Tracking to be activated.After user’s positive response with confirmation, it will displaysthe boundary conditions regions for incorporation of inputs forparticles. In the flowing fluid, when a particle approaches to thewall, it may escape through a wall, react, reflect or to be collected.When a particle escapes, tracking of that particle is aborted andany remaining particle mass, momentum and energy are assumedto escape from the domain. If the particle is collected at a wall,tracking process will be terminated. There is no addition of mass,momentum or energy to the fluids but the particle builds up onthe wall as opposed to escaping the system. If the particle reactsat a wall, then its remaining mass, momentum and energy aretransferred to the fluid. When the particles reacts/rebounds, thevelocity of rebounding particle is calculated using the restitutioncoefficients. The restitution coefficients are determined experi-mentally [23,24] according to flow, particle velocity and targetmaterial. If the target material is 410 stainless steel, inert particlesFig. 8. Computational mesh for modified cyclone collector.



like sand/ash impacting on this surface then the expression fornormal and tangential restitution coefficient ratios are written as

et ¼V2t

V1t¼ 1:0� 2:12b1 þ 3:0775b2

1 � 1:1b31 ð18Þ

en ¼V2n

V1n¼ 1:0� 0:4159b1 þ 4:994b2

1 � 0:292b31 ð19Þ

where et, en are the coefficient ratio of impact velocities in tangen-tial and normal direction, V1, V2 are impact velocities before andafter impact of the surface, and b is the impact angle.

Once the particle reaches a flux element boundary, a test is per-formed to determine the type of flux element the particle is aboutto enter. If the flux element is open to fluid flow, then the local gridcoordinates are reset and tracking continues in the next element. Ifthe flux element is a boundary node, then the particle has encoun-tered boundary condition regions like wall, inlet and outlet. Foreach boundary condition, except the wall, there is only one possi-ble particle action that the particle may escapes from an inlet or anoutlet. With these input conditions, boundary conditions are mod-ified for wall with the particle type as reacting, coefficient of resti-tution is 0.7, under particle group, three classes are defined such as10, 100 and 1000 lm size particles. After definition of particlephysical properties such as density and specific heat, temperatures,etc., and injection location, a subpanel shown in Table 1 displaysparticle tracking control to compute erosive wear/impact basedon Finnie [25] formula built in solver.

Normally default values will in above table works fine. How-ever, depending upon requirements, maximum number of steps/element can be changed for more accuracy. If erosive impact/wearis required to be computed other than Finnie formula, CFX-TASC-flow3D provides the flexibility to add precompiled FORTRAN basedcode to the solver. Depending upon particle and target materialtype, users can modify the relevant source code and can be linkedto flow solver.

8. Results and discussion

The velocity contour plots over height of the modified cycloneseparator is shown in Fig. 10, wherein it is observed that the flowin cyclone chamber is highly non-axisymmetric with high swirl,which makes the flow highly turbulent. In the conical chamber,the swirl velocity reduced rapidly in the core region compared to

the cylindrical chamber. It is also noticed that presence of partitionplates reduces the flow circulation in the outlet duct and thusavoiding the settling of particles. As the flow enters in the cycloneseparator, the three dimensional streaklines in Fig. 11 moves to-wards the wall, forming an outer downward vortex flow due tostrong centrifugal force. Few streaklines after reaching bottom ofcyclone separator turns upward and forms the inner upward vor-tex flow. It is clear from the plot that streakline flow shows im-proved flow distribution in outlet duct due to presence ofpartition plates. Fig. 12 describes the different size ash particlestrajectories released from the inlet of cyclone separator. It is ob-served that the particle size 10 lm follows air flow along the wallof vortex tube finder to gas exit.

Fig. 9. Experimental graph for CD over particle Reynolds number.

Table 1Parameters for particle tracking.



Slightly large size particle of 100 lm released from the inlet ofcyclone separator moves along the outer conical wall. This is be-cause the particles have low inertia and associated drag force

decelerates the fluid motion. It also follows the recirculating gasflow back into the cyclone body, where it is captured into the vor-tex core and moves upward to the outlet gas.

The bigger particle of 1000 lm size captured in a particle ropeand later follows the recirculating flow to the vortex finder andseparated from the fluid stream towards cyclone bottom outlet.The particle trajectories obtained in this analysis are also confirmswith the similar analysis for an industrial cyclone used in chemicalindustries [26,27].

9. Conclusions

The problem of ash settling due to improper flow in recyclingcyclone used in Circulating Fluidized Bed Combustion based powerplant, has been investigated by means of computational fluid dy-namic techniques.

It is observed that the flow distribution in the outlet duct ishighly non-uniform, due to large flow recirculation and high pres-sure drop.

Fig. 10. Velocity distribution in different planes along height of the modifiedcyclone collector.

Fig. 11. Streakline flows from the inlet of modified cyclone collector. Fig. 12. Particle trajectories released from inlet of cyclone collector.



The absence of flow deflectors in the outlet duct might be thereason for transportation of fluid flow through one side, in the cy-clone outlet duct.

Depending upon physico-chemical properties of particles, parti-cle paths deviates the fluid flow streams and becomes responsiblefor erosive wear by particle impacts. The velocity contours overheight of the modified collector indicates the flow inside the cy-clone chamber is highly non-axisymmetric with high swirl whichmakes the flow is highly turbulent. The presence of flow deflectorsin the outlet duct not only improves the velocity distribution, butalso reduces the pressure drop.

In the cyclone separator, high swirl velocity and large turbu-lence intensities created by velocity gradients in the upward flowconcern the high pressure drop. The calculation of particle trajecto-ries depends upon relative velocity of fluid and particles, Stokesnumber and concentration of particles.

At the time of simulation of flow inside the cyclone collector,the turbulence model available in the flow solver to account vis-cous effects has provided valuable insights in the flow distributionin the cyclone collector plane to understand the cause of ash depo-sition on super-heater tubes.

If the Stokes number is less than one, the particles sizes aresmall and follows the fluid motion, else deviates the flow streams.In cyclone separator, due to high swirl velocities, bigger and largesize particles move in the downward flow region towards the wall.

The findings obtained from the numerical simulation in theexisting and modified cyclone outlet duct with particle trajectorieshave provided valuable insights to designers to overcome the prob-lem associated with ash deposition on super-heater tubes.

References

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