Week 8 - Simulating Cyclone separator with Discrete Phase Modelling

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.

Four empirical models used to calculate the cyclone separator efficiency :

1. 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,

2. 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:

3. 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:

4. 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.

GEOMETRY:

Fluid Volume extracted using SpaceClaim.

MESHING:

MESH METRIC:

Size Function: Proximity & Curvature

Min Element Size: 10mm

No of Nodes: 113728

No of Elements: 59175 Boundary

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:

 

RESULTS:

CASE1: In this case, we are making the velocity constant and we are visualizing the difference in results for different particle

size.

Results for the particle size of 1 micron with a velocity of 3m/s:

RESIDUAL PLOT:

PRESSURE AT INLET:

PRESSURE AT OUTLET:

Separation Efficiency in % = (52 / 98) * 100

Separation Efficiency = 53.06 %.

Results for the particle size of 2 micron with a velocity of 3m/s:

RESIDUAL PLOT:

 

PRESSURE AT INLET:

 

PRESSURE AT OUTLET:

Separation Efficiency in % = (75 / 98) * 100 

Separation Efficiency = 76.53 %.

Results for the particle size of 5 micron with a velocity of 3m/s:

RESIDUAL PLOT:

PRESSURE AT INLET:

PRESSURE AT OUTLET:

TOTAL PRESSURE:

Now,

 Pressure drop = Total inlet pressure - Total Outlet Pressure

                         = 33.93 – 4.099

 Pressure drop =29.83 Pa

PARTICLE TRACKING:

Separation Efficiency in % = (98 / 98) * 100

Separation Efficiency = 100 %.

CASE2: Results for the varying velocity and  kepping the particle size constant i.e 5 micron.

Inlet velocity of the particle and the discrete phase is same i.e 1m/s:

RESIDUAL PLOT:

PRESSURE AT INLET:

PRESSURE AT OUTLET:

TOTAL PRESSURE:

Pressure drop  = Total inlet pressure - Total Outlet Pressure

                      = 3.15 – 0.36

Pressure drop  =2.79 Pa

PARTICLE TRACKING:

Separation Efficiency in % = (7 / 98) * 100

Separation Efficiency = 7.14 %.

Inlet velocity of the particle and the discrete phase is same i.e 3m/s:

RESIDUAL PLOT:

PRESSURE AT INLET:

PRESSURE AT OUTLET:

TOTAL PRESSURE:

Pressure drop  = Total inlet pressure - Total Outlet Pressure

                      = 33.93 – 4.09

Pressure drop  =29.83 Pa

 

PARTICLE TRACKING:

Separation Efficiency in % = (98 / 98) * 100

Separation Efficiency = 100 %.

 

Inlet velocity of the particle and the discrete phase is same i.e 5m/s:

 

RESIDUAL PLOT:

PRESSURE AT INLET:

 

PRESSURE AT OUTLET:

 

TOTAL PRESSURE:

Pressure drop  = Total inlet pressure - Total Outlet Pressure

                      = 98.93 – 12.04

Pressure drop  =86.89 Pa

PARTICLE TRACKING:

Separation Efficiency in % = (98 / 98) * 100

Separation Efficiency = 100 %.

CONCLUSION:

1. Simulation is done for particle size varying from 1 m to 5 m with air and particle velocity as 3m/s. From the video, it is

observed that heavier particle is trapped at the bottom outlet and lighter particles are escaped at the outlet 1. But we can

also see that lighter particles also get trapped at the bottom outlet because of interaction between lighter and heavier

particles and there is an exchange of inertial forces between them as a result there is a transfer of Kinetic energy from

heavier particle to the lighter particle, as a result, we can observe a certain number of heavier particles escapes through the

top outlet.The collection efficiency of cyclones varies as a function of particle size, density, and cyclone design.

2. Cyclone efficiency will generally increase with the increase in particle size, density, inlet duct velocity, cyclone body length,

number of gas revolutions in the cyclone, the ratio of cyclone body diameter to gas exit diameter, inlet dust loading,

smoothness of the cyclone inner wall.

3. The efficiency of the cyclone will decrease with an increase in the parameters such as gas viscosity, cyclone body diameter,

gas exit diameter, gas inlet duct area, gas density, leakage of air into dust outlet. With the increase in inlet velocity or particle

size the efficiency increases..

4. Pressure drop occurs because of the following components:

Loss due to the expansion of gas in the cyclone chamber.

Loss due to rotational kinetic energy.

Loss due to wall frictional forces.