Week 8 - Simulating Cyclone separator with Discrete Phase Modelling

AIM

To perform simulation on the cyclone separator using discrete phase modelling, and calculate the separator efficiency and pressure drop

OBJECTIVES

1. Describe any four empirical models used to calculate the cyclone separator efficiency. 
2. Perform an analysis on the 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 velocities as 3 m/sec].
3. Perform an analysis on the given cyclone separator model by varying the particle velocity from 1m/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].

INTRODUCTION

The main objective of this simulation is to find the efficiency of the cyclone seperator for the same particle velocity of 3 m/s for the various particle size such as 1e-6m, 3e-6m and 5e-6m and compare the results. Then, by keeping the particle size of 5e-6m as constant, vary the velocity of the particle and fluid as 1,3 and 5m/s and compare the results. Here, we are using discrete phase modelling for tracking the particles in the separator and since the particle size is so small, the particle interaction with the continuous flow fluid (air) option is enabled.

 

THEORY

 

Cyclone Separator: 

Cyclone separators are separation devices that use the principle of inertia to remove particulate matter from flue gases. Cyclone separator is one of many air pollution control devices known as pre-cleaners 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 multi-cyclone.

It is important to note that cyclones can vary drastically in their size. The size of the cyclone depends largely on how much flue gas must be filtered, thus larger operations tend to need larger cyclones. For example, several different models of one cyclone type can exist, and the sizes can range from a relatively small 1.2-1.5 meters tall (about 4-5 feet) to around 9 meters (30 feet)—which is about as tall as a three-story building.

 Working

            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 the Figure below. 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.

Most cyclones are built to control and remove particulate matter that is larger than 10 micrometers in diameter. However, there do exist high-efficiency cyclones that are designed to be effective on particles as small as 2.5 micrometers. As well, these separators are not effective on extremely large particulate matter. For particulates around 200 micrometers in size, gravity settling chambers or momentum separators are a better option.

                        Out of all of the particulate-control devices, cyclone separators are among the least expensive. They are often used as a pre-treatment before the flue gas enters more effective pollution control devices. Therefore, cyclone separators can be seen as "rough separators" before the flue gas reaches the fine filtration stages.

   

Effectiveness

                        Cyclone separators are generally able to remove somewhere between 50-99% of all particulate matter in the flue gas. How well the cyclone separators are actually able to remove this matter depends largely on particle size. If there is a large amount of lighter particulate matter, less of these particles are able to be separated out. Because of this, cyclone separators work best on flue gases that contain large amounts of big particulate matter.

                        There are several advantages and disadvantages of using cyclone separators. First, cyclone separators are beneficial because they are not expensive to install or maintain, and they have no moving parts. This keeps maintenance and operating costs low. Second, the removed particulate matter is collected when dry, which makes it easier to dispose of. Finally, these units take up very little space. Although effective, there are also disadvantages in using cyclone separators. Mainly because the standard models are not able to collect particulate matter that is smaller than 10 micrometers effectively and the machines are unable to handle sticky or tacky materials well

`"Separator efficiency",η=("Number of particles trapped at the bottom outlet")/("Total number of particles tracked" )`

 

Gas Cyclone Separator

            Gas cyclone separators are grouped into two main categories, Reverse flow and Axial flow. Reverse flow cyclone separators are cone-shaped, gas enters at the top of the separator body, flows downwards then flows back upwards, and is discharged. For Axial flow cyclone separators, gas enters at one end and is discharged at the opposite end. The axial flow design is not as common as the reverse flow design. 

            The project will focus on the reverse flow gas cyclone separator because this type of separator is the most commonly used today. 

Components and Design

            A Reverse flow cyclone separator is an industrial assembly with no moving parts and a simple design. The main cylindrical part of the cyclone separator is known as the body or barrel, the gradually narrowing conical section is known as the cone. Untreated gas enters tangentially through the inlet at the side of the separator. Entrained particles within the gas stream are separated from the gas stream and discharged through the reject port of the base of the separator. Clean gas exits through the accept port at the top of the separator. 

Factors affecting the Efficiency

            There are several factors that can affect the cyclone separator efficiency. These include particle density, particle size, volumetric flow rate, pressure drop, cone length, body length, the ratio of accepting port to body diameter, and even the smoothness of the cyclone's internal surfaces.

We will now discuss the most important design aspects:

Particle Density

                        Particle density is one of the most deciding factors, affecting the cyclone's ability to remove entrained particles. Dense particles such as various oxides can be separated with a 99% or greater efficiency, irrespective of particle size. Dense particles are easily separated. When the particle density decreases, the efficiency decreases. 

Particle Size

                        Particle size is a large design consideration affecting the separator's efficiency. Larger particles can be more easily separated than smaller particles. Particles smaller than five microns are difficult to separate without using very small separators. Particles exceeding 200 microns can often be separated using other means, such as gravity settling chambers. A reduction in particles size will give a corresponding reduction in efficiency. 

Geometry

                        A separator's geometry greatly impacts the efficiency of the unit. A large diameter cyclone separator will not be able to separate particles as efficiently as a smaller diameter separator. The efficiency of the separator increases as the cone diameter decreases. Thus reducing the cone diameter, enables the removal of finer and finer particles. A small diameter cone will extract much finer particles from a gas stream than the larger diameter cone.

Pressure Drop

                        All cyclone separators have an associated pressure drop. The pressure drop can be thought of as the amount of energy required to move the gas through the separator. Alternatively, it can be thought of as the amount of resistance the cyclone separator adds to the system flow. 

Separator body to accept port diameter ratio 

                        Finally, another way to increase a separator's efficiency is to reduce accept port diameter. This changes to separator body to accept port diameter ratio and has the effect of only allowing finer particles to leave the separator through the accept port.  

Large or Small separator

                        Small cyclone separators have a higher efficiency rating but the associated pressure drop is high and the volumetric flow rate is low. Gas velocity through a small separator is also very high and this will lead to a higher level of erosion if the gas stream contains abrasive particles. 

            Large cyclone separators have a lower efficiency rating but the associated pressure drop is low and the volumetric flow rate high. A large cyclone separator is not suitable for removing fine particles from a gas stream. 

Advantages and Disadvantages

There are many advantages associated with cyclone separators some of these include cheap to purchase, low maintenance, suitable for high temperatures, suitable for liquid mist and vapors, do not requiring much space.

Some disadvantages are associated with cyclone separators but these disadvantages can be reduced in severity if the correct separator is selected for the correct application. Disadvantages may include high operating costs, associated with the pressure drop across the separator, inefficient when handling smaller fine particles, and not being suitable for sticky substances. 

 

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 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.

 

Discrete Phase Modelling

The discrete phase modelling is a sub section of Muliphase flows. A DPM is used when the aim is to investigate the behaviour of the particles from a Lagrangian view and a discrete  perspective. The difference between the Lagrangian and Eulerian view is that fluid behaviour in the Lagragian view is examined based in particle tracking of a particulate flow, whereas fluid behaviour is considered in the Eulerian view based on the assumption of a finite volume element in the fluid flow path.

In DPM, the continuous phase is solved using Navier-Stokes equations. At the same time, the discrete phase is simulated by tracking a large number of particles, bubbles or droplets passing through the calculated continuous flow field. It should be noted that the discrete phase can exchange momentum, mass and energy with the continuous phase. This method can be made much simpler by ignoring the interaction of particles with each other. Of course, this can happen when the discrete phase, even with a large mass, has a much smaller volume (less than 10%) than the continuous phase calculations, the particle paths are calculated and determined separately.

The RNG K-Epsilon model is a convenient model for simulating jet impingement, swirling flows, secondary flows and separation flows. yet the isotropic eddy viscosity assumption holds a disadvantage at times.

There are two different phases in DPM:

1. Continues Phase: Continues phase consists of the fluid that is flowing within the fluid volume

1. Discrete Phase:

• Consists of smaller particles interacting with the continuous phase
• Can change momentum, mass, the energy within the fluid phase or continuous phase in our case

Two ways of carrying out DPM

Coupled flow

In coupled flow, the discrete phase will influence the flow of the continues phase.

Uncoupled flow

The discrete phase will not have any interaction with the continues phase.

But since the size of the particles injected into the cyclone separator is very small, usage of both the type of flow should not matter much.

The calculation process followed in the DPM:

 

Coupling between continuous and Discrete phase:

• One-way coupling
• Two-way coupling

Tracking Parameters:

• Maximum number of steps
• Length scale
• Step length factor

 

Boundary condition types

Reflect

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

"Reflect'' Boundary Condition for the Discrete Phase

 

Trap

The trajectory calculations are terminated and the fate of the particle is recorded as "trapped''. In the case of evaporating droplets, their entire mass instantaneously passes into the vapour phase and enters the cell adjacent to the boundary. In the case of combusting particles, the remaining volatile mass is passed into the vapour phase.

          "Trap'' Boundary Condition for the Discrete Phase

 

Escape

The particle is reported as having "escaped'' when it encounters the boundary in question. Trajectory calculations are terminated.

         "Escape'' Boundary Condition for the Discrete Phase

 

Wall-jet

The wall-jet type boundary condition is appropriate for high-temperature walls where no significant liquid film is formed, and in high-Weber-number impacts where the spray acts as a jet. The model is not appropriate for regimes where the film is important (e.g., port fuel injection in SI engines, rainwater runoff, etc.).

Wall-film

This boundary condition consists of four regimes: stick, rebound, spread, and splash, which are based on the impact of energy and wall temperature.

Interior

This boundary condition means that the particles will pass through the internal boundary. This option is available only for internal boundary zones, such as a radiator or a porous jump.

It is also possible to use a user-defined function to compute the behaviour of the particles at a physical boundary.

 

SOLVING AND MODELLING APPROACH

The simulations are performed for various cases which are shown below,

• For this simulation, we generate structured mesh by inserting the cartesian method. This gives the best results for the simulation. Also, the number of mesh cells in the inlet of the separator gives the total number of particles to be tracked.
• Here, since the swirl flow dominates because of the geometry of the separator, we choose the k-epsilon RNG turbulence model with swirl dominated flow option enabled. This provide more accurate simulation results compared to others.   
• The material of the discrete particle is taken as anthracite which is a hard variety of coal.  

 

PRE PROCESSING AND SOLVER SETTING

            In our challenge we will create a flow simulation of a cyclone seperator. In general I will be explaining only one case and posting the screenshots of the other cases.

 

Case 1

                                    Particle Size                            - 1e-6m

Velocity                                  - 3m/s

• Import the given cyclone separator model into spaceclaim and extract its fluid volume using Volume Extract option under Prepare menu.

 

• Hide and suppress the outer solid volume of the cyclone separator in order to perform the simulation only on the fluid volume. Then, close the spaceclaim.

• Now, open the mesh window from the Ansys standalone workflow and give names for the required regions of the cyclone separator fluid volume.

• Insert a new mesh method and choose the method as cartesian for the body. This will generate the structured hexahedral mesh. 

• Give the element size as 5mm and generate the mesh.

 

• Since it is the structured mesh, the element quality is high for almost every mesh elements.

• The number of particles entering the inlet of the cyclone separator can be tracked by finding the number of mesh cells at inlet.

 

• Cross sectional view,

 

Cells	Faces	Nodes
427871	1312260	456604

 

• Here, the gravity is enabled since the particles are to be trapped at the bottom of the cyclone separator. The gravitational acceleration is towards the negative y-axis direction of the cyclone separator. So, the gravity acceleration is given on the required axis direction.  

• Here, the k-epsilon RNG turbulence model is chosen as the viscous model with swirl dominated flow option enabled. Since the simulation is performed mainly to track the discrete particles which are flowing along with fluid(air) having the high swirling effect, the k-epsilon RNG turbulence model will be the correct choice for this model. 

• Enable the discrete phase model. Create the injection of particles by selecting the injection type as surface from inlet and the particles material as anthracite. Then, give the particle diameter as 1*e-6 m and velocity in the normal direction of the inlet surface as 3 m/s .   

• Give the inlet velocity of the fluid(air) as 3 m/s and under DPM, select the discrete phase BC type as reflect. 

• Give the boundary conditions for the top outlet as pressure outlet with atmospheric pressure and give the discrete phase BC type as escape.  

• Give the boundary conditions for the bottom outlet as pressure outlet with atmospheric pressure and give the discrete phase BC type as trap since the particles are to be trapped here.  

• For the wall, check if the DPM is a given as reflect.

• In order to track the discrete particles more accurately, select the second order upwind for both turbulent kinetic energy and dissipation rate under spatial discretization. Here, select the scheme as coupled for the pressure velocity coupling.

• Initialize the simulation using standard initialization and select compute from inlet option.

• Run the simulation for 350 iterations.

 

RESULT

Case 1

                                    Particle Size                            - 1e-6m

                                    Velocity                                  - 3m/s

                                                                       Residual

 

                                                             Velocity Contour

 

                                                                   Pressure Contour

 

                                                                 Anthracite Particles Time

 

 

Case 2

                                    Particle Size                            - 3e-6m

                                    Velocity                                  - 3m/s

                                                                      Residual

 

                                                           Velocity Contour

 

                                                               Pressure Contour

 

                                                           Anthracite Particles Time

 

Case 3

                                    Particle Size                            - 5e-6m

                                    Velocity                                  - 3m/s

 

                                                                       Residual

 

                                                             Velocity Contour

 

                                                                   Pressure Contour

 

                                                                   Anthracite Particles Time

 

Case 4

                                    Particle Size                            - 5e-6m

                                    Velocity                                  - 1m/s

                                                                           Residual

 

                                                              Velocity Contour

 

                                                                   Pressure Contour

 

                                                              Anthracite Particles Time

 

Case 5

                                    Particle Size                            - 5e-6m

                                    Velocity                                  - 5m/s

                                                                    Residual

 

                                                         Velocity Contour

 

                                                                Pressure Contour

 

                                                         Anthracite Particles Time

 

                                                                       Animation

 

 

 

CONCLUSION

1. From the above table, we can observe that for the same particle size of 5e-6m, as the velocity increases the efficiency of the separator decreases. This is due to the increase in swirling effect as the velocity increase and hence the number of particles escaped also increases. Also, we can see that, for the same inlet velocity of 3 m/s, as the particle size increases the efficiency also increases (except for case 3). This is because the inertial force on the particles increases as the particles size increases causing the particles to get trapped at the bottom.
2. Now, if we observe the pressure drop column in the above table, we can see that, as the velocity of the fluid(air) and particles increases at inlet the pressure drop also increases which causes the some particles to escape through the top outlet.   
3. From the results obtained from the first case study, wherein the particle size has been varied. We can observe that for a constant inlet velocity, as the particle size increases, the outlet or separation efficiency of the cyclone separator also increases. This is due to the fact that, if the particle size is too small, they tend to get carried upwards due to the low pressure vortex created in the middle and they escape out, along with the flue gases as they are less denser. On the contrary, if the particle sizes are larger, the re-circulating vortex tends to not have that great of an effect on these particles and they settle down and collect into the bottom outlet or dustbin.
4. Therefore, the particle size is directly proportional to the separation efficiency and greater the particle size, higher the separation efficiency. The variation of particle size has no significant impact on the pressure drop of the system.