Week 8 - Simulating Cyclone separator with Discrete Phase Modelling

week 8 challenge:

Aim:

To perform analysis on cyclone separator and calculate the separation efficiency and pressure drop.

Objective:-

1. To write a few words about any four empirical models used to calculate the cyclone separator efficiency.
2. To perform an analysis on a given cyclone separator model by varying the particle diameter from 1 μm to 5 μm and calculate the separation efficiency in each case. Discuss the results. [Use both the velocity's as 3m/sec.]
3. To perform an analysis on a given cyclone separator model by varying the particle velocity from 1 m/sec to 5 m/sec and calculate the separation efficiency and pressure drop in each case. Discuss the results. [Use particle diameter size as 5 μm for all cases & keep flow velocity same as particle velocity]

Cyclone Separator :

Cyclone separators or simply cyclones are separation devices (dry scubbers) that use the principle of inertia to remove particulate matter from flue gases . Cyclone separators is one of many air pollution removers known as precleaners since they generally remove larger pieces of particulate matter.

This prevents finer filtration methods from having to deal with large, more abrasive particles later on. In addition, several cyclone separators can operate in parallel, and this system is known as a multicyclone

Cyclone separators work much like a centrifuge, but with a continuous feed of dirty air. In a cyclone separator, dirty flue gas is fed into a chamber. The inside of the chamber creates a spiral vortex, similar to a tornado. This spiral formation and the separation is shown in Figure . The lighter components of this gas have less inertia, so it is easier for them to be influenced by the vortex and travel up it. Contrarily, larger components of particulate matter have more inertia and are not as easily influenced by the vortex.

Since these larger particles have difficulty following the high-speed spiral motion of the gas and the vortex, the particles hit the inside walls of the container and drop down into a collection hopper. These chambers are shaped like an upside-down cone to promote the collection of these particles at the bottom of the container. The cleaned flue gas escapes out the top of the chamber.

models:

IOZIA AND LEITH MODEL:

Iozia and Leith (1990) logistic model is a modified version
of Barth (1956) model which is developed based on force
balance. The model assumes that a particle carried by the
vortex endures the influence of two forces: a centrifugal force,
Z, and a flow resistance, W. Core length, zc, and core diameter ,dc are given as:

β is an expression for slope parameter derived based on the
statistical analysis of experimental data of a cyclone with D = 170
0.25 m given as:

and dpc is the 50% cut size given by Barth:

where core length, zc, and core diameter, dc, are given as

Li and Wang Model :

The Li and Wang [3] model includes particle bounce or reentrainment and turbulent diffusion at the cyclone wall. A twodimensional analytical expression of particle distribution in the
cyclone is obtained. Li and Wang model was developed based
180 on the following assumptions:

The radial particle velocity and the radial concentration
profile are not constant for uncollected particles within
the cyclone.

Boundary conditions with the consideration of turbu185 lent diffusion coefficient and particle bounce reentrainment on the cyclone wall are:

Koch and Licht Model:

Koch and Licht [2] collection theory recognized the inherently turbulent nature of cyclones and the distribution of gas
residence times within the cyclone. Koch and Licht described
particle motion in the entry and collection regions with the ad- 200
ditional following assumptions:
• The tangential velocity of a particle is equal to the tangential velocity of the gas flow, i.e. there is no slip in the
tangential direction between the particle and the gas.
• The tangential velocity is related to the radius of cy- 205
clone by: u Rn = constant.

A force balance and an equation on the particles collection yields
the grade efficiency ηi:

Lapple Model:

Lapple [1] model was developed based on force balance without considering the flow resistance. Lapple assumed that a par215 ticle entering the cyclone is evenly distributed across the inlet opening. The particle that travels from inlet half width to the
wall in the cyclone is collected with 50% efficiency. The semi
empirical relationship developed by Lapple [1] to calculate a
50% cut diameter, dpc, is:

The collection efficiency of cyclones varies as a function of density, particle size and
cyclone design. Cyclone efficiency will generally increase with increases in particle size
and/or density; inlet duct velocity; cyclone body length; number of gas revolutions in the
cyclone; ratio of cyclone body diameter to gas exit diameter; inlet dust loading;
smoothness of the cyclone inner wall.Similarly, cyclone efficiency will decrease with increases in the parameters such as gas viscosity; cyclone body diameter; gas exit diameter; gas inlet duct area; gas density; leakage of air into the dust outlet.

The efficiency of a cyclone collector is related to the pressure drop across the collector.
This is an indirect measure of the energy required to move the gas through the system.
The pressure drop is a function of the inlet velocity and cyclone diameter. Form the
above discussion it is clear that small cyclones are more efficient than large cyclones.
Small cyclones, however, have a higher pressure drop and are limited with respect to
volumetric flow rates. Another option is arrange smaller cyclones in series and/or in
parallel to substantially increase efficiency at lower pressure drops. These gains are
somewhat compensated, however, by the increased cost and maintenance problems. Also
these types of arrangements tend to plug more easily. When common hoppers are used in
such arrangements, different flows through cyclones can lead to reentrainment problems.

modeling approach:

there are 5 steps in the modeling approach.

• geometry correction(using space claim).
• meshing. (using Ansys mesher).
• setup problem.(using Ansys fluent).
• solution using(Ansys fluent).
• results.(using CFD post).

geometry preparation:

Geometry:

Fluid Volume extracted using SpaceClaim is shown below:

Mesh Details:

here the mesh is created by:

mesh>insert>method>select the body>apply in the geomentry of method>meshing type>cartesian>element size of 5mm

Structural mesh gives the best results, so you can use cutcell meshing approach available in Ansys Meshing.

Size Function: Proximity & Curvature

Boundary Conditions:

Inlet & outlets are as shown above.

Gravity is enabled in the -ve y-direction.

The swirl dominated RNG K-epsilon model is used here to capture the flow more accurately.

The Discrete phase modeling is used to track the flow of the particles.

No of step for particle tracking = 50000

Injection Material : Anthracite (5microns in diameter)

Velocity Inlet: 3m/s

Outlet: Pressure Outlet( Gauge Pressure= 0Pa)

DPM Settings are varied b/w reflect,escape, trap & wall jet.

Reflect: The particle rebounds off the boundary in question with a change in its momentum as defined by the coefficient of restitution.

Escape: Particle escapes out when encountered by the boundary.

Trap: The trajectory calculation is terminated & fate of the particle is recorded as a trap.

Wall-Jet: The wall-jet type boundary condition is applicable for high-temperature walls where no significant liquid film is found & high Weber No impacts when the spray acts as a jet. This model is not applicable to regimes where the film is important.

solution approach and solver requirement:

physics general

here we used pressure based solver type because the mach number is less than 0.3.

mach number=velocity of fluid /speed of the sound.

speed of the sound is 340 m/s

velocity of fluid is 1,2,3, and 5 for different case we used.

by applying the formula we should obtain less than 0.3 so we used pressure based solver type.

solver time in steady state,

beacuse there is no change over a period of time.

gravity enabled.

viscous model.

K epsilon suit for high Reynolds number or in other words proper for simulation of free flow as it relates the rate of kinematic dissipation to the turbulent viscosity.

where reynolds number is defined as the to determine the type of flow pattern as laminar or turbulent while flowing through a pipe.

dispersed phase model:

To release particles from a surface (either a zone surface or a surface you have defined using the items in the Surface menu), you will create a surface injection.

particle size of 5e-6,1e-6,2e-6 and 3e-6 is used in different case.

zone name:

inlet :

velocity of 1m/s,3m/s and 5m/s are used in different case.

DPM Boundary Conditions:-

Inlet and wall:- Reflect

Outlet(Top):- Escape

Outlet(Bottom/dustbin) - Trap

for outlet:

solution initilaze:

here it is used standard initialization you must provide the initial guess.

compute from the inlet.

and click on initialize.

then run the simulation for 500 iteration.

after the iteration is over. file>export>particle historydata>select the injection type>brose the give the location>write.

the above will export the particle data.

then close the ansys fluent.

pre-processing:

open the results (prepost), then import the file which you have exported from the fluent,

then colour the data with anthracite particle time.

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STEP 4 : RESULTS

case1:

3m/s and particle size of 5 microns.

residual of continuity,x,y,z- velocity, k and epsilon.

pressure inlet of the cyclone separator is shown.

here the max velocity is about 25.87 pascal

here we see the velocity at outlet at the end of the iteration is -0.021 pascal

then to compute the pressure and the examine the DPM:

number of particle tracked at the inlet is 420, were number of partcle trapped is 139.

seperation efficiency=(number of particle trapped /number of particle tracked)*100

=>(139/420)*100=33.29%

pressure drop is the difference in total pressure between two points in a fluid-carrying network.

inlet pressure-outlet pressure=25.87-(-0.02)=25.87 pascal

here the below shows the export file :

anthracite particle time:

here it shows the particle time taken in second.

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case2:

2micron 3m/s:

here it shows the velocity is 3m/s and the particle size of about 2micron

it shows the pressure inlet

the below diagram shows the scaled residual of the velocity, continity and k epsilon for different iteration.

it shows the outlet pressure of the top of the cyclone separator.

here it show the particle data and the pressure:

number of particle tracked at the inlet is 420, were number of partcle trapped is 349.

seperation efficiency=(number of particle trapped /number of particle tracked)*100

=>(349/420)*100=83.4%

pressure drop is the difference in total pressure between two points in a fluid-carrying network.

inlet pressure-outlet pressure=25.87-(-0.02)=25.87 pascal

anthracite particle time:

here it shows the particle time taken in second.

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case3:

1micron 3m/s:

here it shows the velocity is 3m/s and the particle size of about 1micron

it shows the pressure inlet

it shows the outlet pressure of the top of the cyclone separator.

the below diagram shows the scaled residual of the velocity, continity and k epsilon for different iteration.

here it show the particle data and the pressure:

Particle Tracking:

number of particle tracked at the inlet is 420, were number of partcle trapped is 395.

seperation efficiency=(number of particle trapped /number of particle tracked)*100

=>(395/420)*100=94%

pressure drop is the difference in total pressure between two points in a fluid-carrying network.

inlet pressure-outlet pressure=25.87-(-0.02)=25.87 pascal

anthracite particle time:

here it shows the particle time taken in second.

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case(4)

results for the varying velocity and kepping the particle size constant i.e 5 micron

here it shows the velocity is 5m/s and the particle size of about 5micron

the below diagram shows the scaled residual of the velocity, continity and k epsilon for different iteration.

it shows the pressure inlet

it shows the outlet pressure of the top of the cyclone separator.

here it show the particle data and the pressure:

number of particle tracked at the inlet is 420, were number of partcle trapped is 308.

seperation efficiency=(number of particle trapped /number of particle tracked)*100

=>(308/420)*100=73%

pressure drop is the difference in total pressure between two points in a fluid-carrying network.

inlet pressure-outlet pressure=75.25-(-0.07)=75.32 pascal

anthracite particle time:

here it shows the particle time taken in second.

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case5:

3m/s and 5 microns.

residuals graph:

the below diagram shows the scaled residual of the velocity, continity and k epsilon for different iteration.

it shows the pressure inlet

it shows the outlet pressure of the top of the cyclone separator.

here it show the particle data and the pressure:

number of particle tracked at the inlet is 378, were number of partcle trapped is 273.

seperation efficiency=(number of particle trapped /number of particle tracked)*100

=>(273/378)*100=72.22%

pressure drop is the difference in total pressure between two points in a fluid-carrying network.

inlet pressure-outlet pressure=18.801-(-0.008)=18.808 pascal

here it shows the velocity is 3m/s and the particle size of about 5micron

anthracite particle time:

here it shows the particle time taken in second.

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case6:

1m/s and 5 microns.

here it show the particle data and the pressure:

number of particle tracked at the inlet is 378, were number of partcle trapped is 319.

seperation efficiency=(number of particle trapped /number of particle tracked)*100

=>(319/378)*100=84.3%

pressure drop is the difference in total pressure between two points in a fluid-carrying network.

inlet pressure-outlet pressure=1.8863-(-0.0007)=1.887 pascal

the below diagram shows the scaled residual of the velocity, continity and k epsilon for different iteration.

it shows the outlet pressure of the top of the cyclone separator.

it shows the pressure inlet

here it shows the velocity is 3m/s and the particle size of about 1micron

anthracite particle time:

here it shows the particle time taken in second.

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conclusion:

the belowtable shows the pressure drop and seperation efficiency for the different velocity and particle sizee.

s.no	particle size(micron)	inlet velocity(m/s)	separation efficiency(%)	pressure drop(pascal)
1	5	3	33.29	25.87
2	2	3	83.4	25.85
3	1	3	94	25.83
4	5	5	73.2	75.32
5	5	3	72.22	18.8
6	5	1	84.3	1.887

1)from the above table the maximum seperation efficiency is obtained when the particle size and the velocity is low.

the ratio of concentration that has been removed from the feed to the initial concentration in the feed.

2)the minimum seperation efficiency is obtained at the 5 microns and 3m/s velocity.

3) the pressure drop is low when the particle size is high and the velocity is low.it shows that when the velocity of the fluid is very low witha particle sixze of higher the velocity at the outlet decreases.

4) the pressure drop is high at themaximum velocity and particle size.

5) it conclude that at the high particle size and less velocity provide us a high separation efficiency and low pressure drop.

--------------------------------------thank you-------------------------------------------------