CFD analysis of Cyclone Separator using ANSYS FLUENT

ABSTRACT: In this project, I have written about cyclone separator and Empirical model in brief. I have also performed an analysis of the cyclone separator model and applied different boundaries conditions to measure the effects and three different cases were ran to vary the number of particle effect on cyclone separator was observed and recorded.

INTRODUCTION:

• Cyclone separator is a device used to control or remove matter larger than 10micrometer in dia.
• Some high-efficiency cyclone separator can remove matter as small as 2.5micrometer in dia.
• Cyclone separator is not very efficient with larger dia, say 200micrometer. In these cases, gravity settling chamber or momentum separator is a better option.
• Discrete Phase Modelling (DPM) approach was used to simulate the cyclone separator
• The continuous phase is consists of fluid that is flowing with the fluid volume.
• The discrete phase consists of smaller particles that are supposed to be interacting within the continuous phase and can also exchange momentum, mass, and energy with the continuous phase.

Empirical models

1. Lapple model
2. Koch and Licht model
3. Li and Wang model
4. Iozia and Leith model

Lapple model:

Lapple model was developed based on force balance without considering flow resistance. Lapple assumed that a 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 efficiency of the collector of any size of the particle is given by-

Koch and Licht model:

Koch and Licht collection theory recognized the inherent turbulence nature of the cyclone and the distribution of gas residence times within the cyclone.

Koch and Licht described particle motion in the entry and collection regions by the following assumptions:

1. The tangential velocity of the particle is equal to the tangential velocity of the gas flow, i.e. there is no slip between the tangential direction between the particle and the gas.
2. The tangential velocity is related to the radius of the cyclone by u Rn = constant

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

Li and Wang model:

The Li and Wang model include particle bounce or re-entertainment and turbulent diffusion at the cyclone wall. A two-dimensional analytic expression of particle distribution in the cyclone is obtained.

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

Iozia and Leith model:

Iozia and Leith logistic model is based on force balance. The model assumes that the particle carried by the vortex endures the influence of two forces: a centrifugal force and flow resistance. The collection efficiency ηi of particle diameter DPI can be calculated from

β is an expression for scope parameter derived based on the statistical analysis of the experimenatl data of the cyclone.

(Reference: A CFD study on prediction of cyclone collector efficiency, ResearchGate)

PROCEDURE:

Step1) Pre-Processing

1.1) Creation of Geometry- A given geometry of cyclone separator has downloaded and imported to SpaceClaim. Volume extraction is done and the model is saved to do meshing.

1.2) Meshing & Naming- Grid dependency test was performed and different meshing was done. A baseline mesh, a fine mesh, and the finest mesh was used in the simulation. Appropriate naming was done as Inlet, Outlet-1, Outlet-2.

Step-2) Solving

2.1) Setting up physics

• Solver------> Steady-State, Pressure-based, Absolute velocity formulation
• Gravity------> Y-Axis = -9.81m/s2
• Model-------> K-epsilon RNG model with Swirl domination.
• Discrete Phase-------> Discrete phase modeling, set Injection properties.

• Boundary Conditions---> Inlet velocity = 3m/s, Discrete phase B.C=Reflect Outlet-1,2 Gauge Pressure = 0 = 1 ATM, Discrete phase B.C=Escape,reflect,trap or wall-jet (according to requirement).
• Method-------> Second order, for more accuracy.

2.2) Setting up solution

• Standard-Initialization-----> Compute from Inlet
• Initialize the solution
• Run the solution for required no. of iteration to make the solution converge.

Step-3) Post-Processing

• Analyze the result obtained after solving.
• Set and save animation of
• Compute the mass flow rate.

MODEL:

Fig: 3-D Geometry cyclone separator

Fig: Volume extracted body

OUTPUT & RESULTS

Case-1 Providing different boundary conditions at the inlet for DPM such as Trap, Refet, Escape & Wall-jet.

1.1) Inlet boundary condition as Trap

1.2) Inlet boundary condition as Reflect

1.3) Inlet boundary condition as Escape

1.4) Inlet boundary condition as Wall-Jet

Particle History table-:

B.C Type	Particle tracked	Escaped	Aborted	Trapped	Evaporated	Incomplete
Reflect	204	200	0	0	0	4
Trap	204	186	0	0	0	18
Escape	204	186	0	0	0	18
Wall-Jet	204	186	0	0	0	18

Mass flow rate Table-:

Boundary Condition	Mass Flow Rate Kg/s
Type	Inlet	Outlet-1	Outlet-2
Reflect	0.0569625	-0.0112684	-0.0463539
Trap	0.0569625	-0.0112684	-0.0463539
Escape	0.0569625	-0.0112684	-0.0463539
Wall-Jet	0.0569625	-0.0112684	-0.0463539

We can observe that the mass flow rate is constant while changing the discrete phase boundary condition.

Particle fates:

• “Escaped” trajectories are those that terminate at a flow boundary for which the “escape” condition is set.
• “Incomplete” trajectories are those that were terminated when the maximum allowed
  the number of time steps was exceeded.
• “Trapped” trajectories are those that terminate at a flow boundary where the “trap”
  the condition has been set.
• “Evaporated” trajectories include those trajectories along which the particles were
  evaporated within the domain.
• “Aborted” trajectories are those that fail to complete due to numerical/round-off reasons.
  If there are many aborted particles, try to redo the calculation with a modified length
  scale and/or different initial conditions.

Case-2) Varying the number of particles through the inlet and using similar boundary conditions as 'Reflect' for all cases.

As we know, the number of particles can only get varied by using more finer mesh i.e. more finer the mesh more particles will be there. Hence we will be making the mesh finer for three cases and will observe the results.

2.1) Baseline Mesh

2.2) Finer Mesh

2.3) Finest Mesh

Particle History table-:

Mesh Type	Particle tracked	Escaped	Aborted	Trapped	Evaporated	Incomplete
Baseline Mesh	4	4	0	0	0	0
Finer Mesh	204	200	0	0	0	4
Finest Mesh	380	335	0	0	0	45

Mass flow rate Table-:

No. of Particle	Mass Flow Rate (kg/s)
Mesh Type	Inlet	Outlet-1	Outlet-2
Baseline	0.0569625	-0.0135406	-0.0446253
Fine	0.0569625	-0.0141697	-0.0450143
Finest	0.0569625	-0.0121013	-0.0462554

Vortex core region: Fig: Vortex region

Anthracite particles:

Fig: Particle velocity

Fig: Particle Time

We can observe that Anthracite particles are spending less time in the upper part of cyclone separator which is near the upper outlet because of the high-velocity present there, due to the high-velocity, particles are leaving that area quickly. Whereas in the lower area of cyclone separator which is near the lower outlet the particles are spending more time as velocity in that region is low hence particles taking more time there comparatively.

CONCLUSION

1) The number of anthracite particles coming in from the inlet increases as we increase the refinement of the mesh i.e. by decreasing the element size of the mesh.

2) Particles having high velocity in the upper region of cyclone separator as compared to the lower region.

3) Particles spending less time in the upper region of the cyclone separator as compared to the lower region.

4) There is not much difference observed in the Discrete phase boundary condition though we have got the highest no. of particle escaped on "Reflect" type boundary condition and received the same value for all the other boundary conditions.