Simulation of Cyclone Separator using Ansys Fluent

Objective: To perform an analysis of the cyclone separator and calculate the separation efficiency and pressure drop.

1. Four empirical models used for cyclone separator efficiency.
2. Calculate the separation efficiency and pressure drop for particle size ranging from 1 µm to 10 µm.
3. Calculate separation efficiency and pressure drop by varying inlet velocity of both fluid and particle from 5m/sec to 10m/sec. (Particle size- 5µm)

Given: The CAD model we have as:

Theory:

                                                 `tt\"Cyclone Separator\"`

Cyclone separators are devices which employ centrifugal force by spinning gas stream to separate a particle from the carrier gas. It is also a dust collector which is used for separating the particles from exhaust gases in industries. It is used to separate particles ranging from 10µm to 100µm. There are different types of cyclones but cyclone with tangential inlet is quite popular. Cyclones are used for the removal of large particles for both air pollution control and process use. Application in extreme conditions includes the removal of coal dust in a power plant and the use as a spray dryer or gasification reactor.

Operation: Cyclones works on centrifugal separation principle where exhaust gas coming out from factories contains dust particles. This incoming gas forced to flow through the tangential inlet. Then, it reaches the cylindrical portion where linear flow now gets transformed into swirling motion i.e swirl (outer vortex) is created. During swirling, flow particles come in contact with the wall and they lose their momentum resulting fall into a dust collector due to surface roughness of the wall and conical portion.
The gas due to the centrifugal force moves towards the outer boundary and the outer vortex is maintained. Simultaneously, the swirl continues towards the end and it reverses its direction and the inner vortex is created. The upward movement is mainly due to the low density of the gas, and we now that gas always travels from low pressure to high pressure. The cleaner gas comes out of the vortex finder.

`tt\"CASE SETUP\"`

STEP-1: Import geometry into Spaceclaim.
               

STEP-2: Extract fluid volume since we are interested in fluid flow inside cyclone separator by selecting edges. Suppress other components for physics.

STEP-3: Meshing and Boundary naming.

The naming of Boundaries will be done as:

`tt\"FLUENT SETUP\"`

Solver: 
Type- Pressure based
Velocity formulation- Absolute
Time- STEADY

Enable Gravity along the Y-axis as -9.81 m/s2.

Viscous Model: RNG k-epsilon with Swirl Dominated flow and Standard wall functions.

Discrete Phase Model (DPM):
DPM is used when the flow of the discrete phase (particles) with a continuum is being modeled. DPM is used to track individual particles through the continuum fluid.
Fluent allows us to simulate a discrete second phase in a Lagrangian frame of reference along with solving transport equations for the continuous phase. This second phase consists of spherical particles (which may be taken to represent droplets or bubbles) dispersed in the continuous phase.
Here, in this case, solid particle size ranging from 1µm to 10µm being simulated as a discrete phase in a continuum.

Injection of a solid particle will be done as:

Injection Type- Surface 
Release from surfaces- Inlet
Particle type- Inert
Material- Anthracite (Uniform Diameter distribution)

For Parametric Study:
Velocity- 3 m/sec (CASE-1)
             Input parameter (CASE-2)

Diameter- Input Parameter (CASE-1)
               5µm (CASE-2)

Boundary Conditions:

Inlet-
Velocity magnitude- 3 m/s (For CASE-1)
                                   Input Parameter (For CASE-2)
DPM- Reflect

Outlet_dustbin-
Type- Pressure Based
Gauge Pressure- 0 Pa
DPM- Trap

Outlet_Top-
Type- Pressure Based
Gauge Pressure- 0 Pa
DPM- Escape

Wall-Volume_volume-
Wall Motion- Stationary Wall
Shear Condition- No slip
DPM- Reflect

Method:

Turbulent Kinetic energy and Turbulent Dissipation Rate set to Second-Order Upwind for greater accuracy in swirling flows.

The solution has been initialized using the \"Standard Initialisation Method\".

`tt\"RESULTS\"`

CASE-1: In this case, we have set Particle diameter as input parameter ranging from 1µm to 10µm while keeping particle velocity and Fluid velocity as 3 m/sec.

There are two performance indicators for the functioning of cyclone separator. They are:
1. Separation efficiency
2. Pressure Drop

1. Separation/Collection efficiency: It is defined as a fraction of particles of a given size collected or trapped in the cyclone, compared to those of that size going into the cyclone. It is most properly defined for given particle size.
Collection efficiency of cyclone separator increases with increasing particle mean diameter and density; increasing gas tangential velocity; decreasing cyclone diameter; increasing cyclone length; extraction of gas along with solids through the cyclone legs.

Here, in our study we have summarised the particle data obtained from the simulation as below:

`eta_(s)=(\"Nos. of Particles Trapped\")/(\"Nos. of Particles Tracked\")`

Particles in incomplete indicated they are inside the recirculation zone.

From the graph, it is clear that there is a sudden rise in the separation efficiency of cyclone separator for particle size above 1µm. These devices are useful for particle diameter more than 1µm.

The particle position with time inside cyclone separator has been shown in the below image.

2. Pressure Drop: The \'pressure drop\' here means a drop in total pressure i.e. static pressure and dynamic pressure. In other words, pressure lost during the flow between inlet and Outlet.
The pressure drop across the cyclone is of much importance in a cyclone separator. The
pressure drop significantly affects the performance parameters of a cyclone. The total
pressure drop in a cyclone will be due to the entry and exit losses, and friction and kinetic
energy losses in the cyclone. Normally the most significant pressure drop occurs in the body
due to swirl and energy dissipation.

The Pressure drop over cyclone usually divided into three sections:
1. Losses in Entry
2. Losses in separation space (main cyclon body)
3. Losses in Vortex finder

Pressure Drop in our case is found out as:

From the graph,
Inlet pressure- 28.600571 Pa
Outlet_top pressure- 3.5716778 Pa

`\"Pressure Drop= Inlet Pressure - Outlet Pressure\"`

Pressure drop found as:

`DeltaP= 25.02889 \" Pa\"`

CASE-2: In this case, the Particle diameter is restricted to 5µm whereas particle velocity and fluid velocity changing from 5 m/sec to 10 m/sec.

1. Separation/Collection efficiency: As we can see the increase in particle velocity and fluid velocity increases collection efficiency for particle size 5µm.

2. Pressure Drop: Increase in velocity we can observe an increase in pressure drop.

Particle and Fluid Velocity- 5 m/sec:

From the graph,
Inlet pressure- 81.84399 Pa
Outlet_top pressure- 10.48578 Pa

`DeltaP= 71.35821 \" Pa\"`

Pressure Plot:

Particle and Fluid Velocity- 10 m/sec:

From the graph,
Inlet pressure- 338.32089 Pa
Outlet_top pressure- 44.551758 Pa

`DeltaP= 293.7691 \" Pa\"`

Pressure Plot:

`tt\"CONCLUSION\"`:
In this way, we have studied the effect of particle size, fluid velocity, and particle velocity on separation efficiency and pressure drop of the given cyclone separator.

`***` From the CASE-1 study, we can observe that the Cyclone efficiency has marginally increased as we increase particle size more than 1µm while keeping fluid and particle velocity constant i.e. 3 m/sec.
`***` Since the velocity is 3m/sec for all particle sizes we simulate in CASE-1, the pressure drop remains constant. Thus it is the important parameter for design consideration of cyclone separator.
`***` Cyclone efficiency generally increases with the increase in particle size, inlet duct velocity.
`***`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 as we can observe in CASE-2.

`tt\"Empirical Methods used for Cyclone separator Efficiency\":`

1. Iozia and Leith model:
This model is the modified version of the Barth model which is developed based on force balance. The model assumes that the particle carried by vortex experiences two forces: a centrifugal force and flow resistance.
The collection efficiency of particle diameter is calculated by,
`eta_s= 1/(1+(d_(pc)/d_(p))^beta)`

where dp is a particle diameter.
         dpc is the 50% cut size.
        β is an expression for slope parameter derived based on the
statistical analysis of experimental data of a cyclone with D =
0.25 m given as

dpc is given by,
                     
Core length Zc, and Core diameter dc, is given by:

2. Li and Wang model:
This model introduces particle bounce and turbulent diffusion at the cyclone wall.
This model has been developed based on assumptions:
1. The radial particle velocity and the radial concentration profile are not constant for uncollected particles within the cyclone.
2. Boundary conditions with the consideration of turbulent diffusion coefficient and particle bounce re-entrainment on the cyclone wall are:
                     
3. The tangential velocity is related to the radius of cyclone by: `mu*R^n= \"Constant\"`

The expression of the collection efficiency for a particle of any size is given as:

`eta_i= 1 - exp(-lamda*theta_1)`

`\"where, \" theta_1= 2*pi*((S+L))/a`

3. Koch and Licht model:
This model recognized the inherently turbulent nature of cyclones and the distribution of gas residence times within the cyclone. This model described particles motion in the entry and collection regions with the following assumptions:
1. 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.
2. The tangential velocity is related to the radius of cyclone by: `mu*R^n= \"Constant\"`

`eta_i= 1 - exp{-2[(G*tau_i*Q)/D^3*(n+1)]^(0.5/(n+1))}`

`\"where, \"G= (8* K_c)/(K_a^2*K_b^2)`

`n= 1-{1-((12D)^0.14)/2.5}{(T+460)/530}^0.3`

`tau= (rho_p*d_(p)^2)/(18mu)`

G is a factor related to the configuration of the cyclone, n is related to the vortex, and τ is the relaxation term.

4. Lappel Model:
This model was developed based on a force balance without considering the flow resistance. This model assumes that particle 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 to calculate a
50% cut diameter, dpc, is,

`d_(pc)=[(9mub)/(2pi*N_e*nu_i*(rho_p-rho_g))]^(1/2)`

where, Ne is the number of revolutions

`N_e= (1/a)*[h+(H-h)/2]`

The efficiency of collection of any size of a particle is given by,

`eta_s= 1/(1+(d_(pc)/d_(p))^2)`

Particle tracking animation of particle size of 1µm: