Cyclone Separator Challenge

Title: CFD analysis on a Cyclone Separator using ANSYS Fluent.

Objective:

1. To perform CFD analysis on a given Cyclone Separator model.
2. First case. To vary boundary conditions i.e. Reflect, Trap, Escape and Wall jet.
3. Second case. To perform a study to analyse the model with different particle size for Reflect DPM condition.

Theory:

Cyclone Separator:

Cyclones are devices that employ a centrifugal force generated by a spinning gas stream to separate particles from the carrier gas. Their simple design, low maintenance costs, and adaptability to a wide range of operating conditions such as sizes and flow rates make cyclones one of the most widely used particle removal devices. By using suitable materials and methods of construction, cyclones may be adapted for use in extreme operating conditions: high temperature, high pressure, and corrosive gases. Cyclones are important particle removal devices in both engineering and process operations. An inaccuracy in cyclone efficiency prediction may result in an inefficient design of cyclone separators. Models to predict the behaviour of cyclones are usually empirical. It remains largely a process of trial and error, since empirical cyclones models are only applicable to specific cyclone geometries. This study reviews the prediction four different cyclone efficiency empirical models, namely Lapple, Koch and Licht, Li and Wang, and Iozia and Leith.

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

The addition made by Iozia and Leith on the original Barth (1956) model are the core length zc and slope parameter β expression which is derived based on the statistical analysis of experimental data of cyclone with D = 0.25 m. The collection efficiency ηi of particle diameter dpi can be calculated from

Li and Wang model:

The Li and Wang (1989) model includes particle bounce or re-entrainment and turbulent diffusion at the cyclone wall. A two-dimensional analytical expression of particle distribution in the cyclone is obtained. Li and Wang model was developed based on the following assumptions:

• The radial particle velocity and the radial concentration profile are not constant, for uncollected particles within the cyclones.
• Boundary conditions with the consideration of turbulent diffusion coefficient and particle bounce re-entrainment on the cyclone wall are:

• The tangential velocity is related to the radius of cyclone by: uRn = constant. The concentration distribution in a cyclone is given as:

Koch and Licht:

Koch and Licht (1977) collection theory recognized the inherently turbulent nature of cyclones and the distribution of gas residence times within the cyclone. Koch and Licht describe particle motion in the entry and collection regions with the additional 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 cyclone by: uRn = constant. A force balance and an equation on the particles collection yields the grade efficiency ηi.

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

Lapple model:

Lapple (1951) model was developed based on force balance without considering the 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 semi empirical relationship developed by Lapple (1951) to calculate a 50% cut diameter, dpc, is

Procedure:

Step 1: Geometry:

The geometry used to run the simulation is:

Extracting the required fluid volume, we get:

Step 2: Meshing:

This problem has to be solved in two cases

Case 1: mesh size: 10mm. {For different DPM conditions.}.

Case 2: Mesh size: 10mm, Face sizing :5mm. {Reflect DPM condition.

Step 3: Setup & Solution:

Case 1:

1. Pressure based solver was used.
2. Steady Time.
3. Absolute velocity.
4. Viscous model: k-epsilon model, Standard wall treatment, and swirl dominate flow were enabled.
5. Continuous DPM enabled.
6. Inlet boundary conditions: velocity: 5m/s. DPM: Reflect, Trap, Escape and Wall jet.

Case 2:

1. Pressure based solver was used.
2. Steady Time.
3. Absolute velocity.
4. Viscous model: k-epsilon model, Standard wall treatment, and swirl dominate flow were enabled.
5. Continuous DPM enabled.

Inlet boundary conditions: velocity: 5m/s. DPM: Reflect.

Step 4: Results:

Case 1:

Reflect DPM condition:

Residual plot:

Anthracite particle time contour:

Animation video:

Details of DPM iteration:

Trap DPM condition:

Residual plot:

Anthracite particle time contour:

Animation video:

Details of DPM iteration:

Escape DPM condition:

Residual plot:

Anthracite particle time contour:

Animation video:

Details of DPM iteration:

Wall jet DPM condition:

Residual plot:

Anthracite particle time contour:

Animation video:

Details of DPM iteration:

From the obtained results, the following information as tabulated.

Type	Tracked	Escaped	Incomplete	Trapped	Aborted	Evaporated
Reflect	124	124	0	0	0	0
Trap	124	124	0	0	0	0
Escape	124	124	0	0	0	0
Wall jet	124	124	0	0	0	0

Case 2:

Particle size: 5 μm.

Residual plot:

Anthracite particle time contour:

Animation video:

Details of DPM iteration:

Particle size: 6 μm.

Residual plot:

Anthracite particle time contour:

Animation video:

Details of DPM iteration:

Particle size: 7 μm.

Residual plot:

Anthracite particle time contour:

Animation video:

Details of DPM iteration:

From the obtained results, the following information as tabulated.

Size	Tracked	Escaped	Incomplete	Trapped	Aborted	Evaporated
5 μm	402	401	1	0	0	0
6 μm	402	401	1	0	0	0
7 μm	402	401	1	0	0	0

Conclusion:

1. Finer the mesh, more accurate the results obtained turns out to be.
2. There is no difference in different DPM type simulations, mostly due to low mass flow rate of the Cyclone Separator.

(reference: http://dspace.unimap.edu.my/xmlui/bitstream/handle/123456789/13571/054-058_empirical%20models.pdf?sequence=1&isAllowed=y).