Week 8 - Simulating Cyclone separator with Discrete Phase Modelling

Objective:

• The objective of this project is to perform analysis on cyclone separator and calculate the separation efficiency and pressure drop.
• To perform velocity versus particle size study from 1 m/s to 5m/s and for particle size from 1 micrometer to 5 micrometer. Tabulate the results and compare for efficiency.

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 are 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.

Empirical models for Cyclone Separator Efficiency:

1: Iozia and Leith Model.

Iozia and Leith 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 flow resistance W.

• Li and Wang Model:

The Li and Wang model include 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,

3: Koch and Licht Model,

Koch and Licht 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.

4: Lapple Model,

Lapple 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 to calculate a 50% cut diameter, dpc , is

Solving and Modeling approach:

We shall solve for 5 cases as discussed in Aim. We will be using ANSYS Fluent solver to create the fluid volume in geometry and perform structured cartesian CFD mesh with boundary definitions, setup the physics of fluid flow and run the iterations to get solutions, using post processing to interpret the data in form of plots, contours, vectors, streamlines etc.,

we shall study for 5 cases as follows.

Case	Inlet velocity (m/s)	Particle size (micrometer)
1	1	5
2	3	5
3	5	5
4	3	1
5	3	3

For this type of problem, we will be using discrete phase option that allows user to visualize suspended particle in a fluid medium. So, we shall study for efficiency and the pressure drop at escape outlet.

We shall keep in mind we are using a student version of ASNYS, so we are limited with the number of elements to play with. Then, we tabulate the case study results and compare it with the open literature or book data results to validate the simulation.

Modelling Procedure:

1: Pre-Processing.

• Open Ansys Workbench→under Analysis system select Fluid flow(fluent) drag and drop it in Project schematic → Geometry → New spaceclaim geometry.
• File select the appropriate file and then Open the file.
• This project is an internal flow simulation project, so we have to extract the fluid volume by using Volume extract with edge selection option in spaceclaim.

Cyclone Separator:

Fluid Volume:

2: Meshing.

In this project we are going to use cartesian mesh, to use this mesh Mesh `rarr` Methods `rarr` Cartesian and element size as 5mm. After creating the mesh we have to name the inlet and top outlet as outlet escape, outlet bottom as outlet trap.

3: Simulation.

• Setting up for Physics. Choose pressure-based solver and steady state condition with gravity enabled in Y axis as –9.81 m/s^2.

• The turbulence model we are using is K-epsilon turbulence model with RNG and Swirl dominating flow.

• Under material we are selecting air as our default material.
• In the Discrete phase deck, select Injections > Create > Injection type surface and select the inlet surface. And input X velocity as 3 m/s (as per case) and the material are anthracite by default. The particle size can be input as 0.000005 m (as per case).

• In the Boundary conditions, select the inlet as velocity inlet and in DPM as Inlet. Let the fluid volume be wall with DPM as reflect, Outlet escape as escape, outlet trap as trap.

Inlet:

We can change the inlet velocity according to our requirement,

Output Trap:

Output Reflect:

• In Method, for the swirl dominating flows change the turbulent kinetic energy to second order upwind, and coupled method. Let us use Standard initialization compute from inlet.

• Now, it's time to start the simulation. For Run Calculation, we shall run for 350 iterations initially if required we shall extend based on the number of incomplete particles.
• We need to export the particle data for us to analyse in post processing, for that go to File > Export > Particle history data and select the required directory and click write.
• In the Outline view under Simulation Reports, clicking on the Report Outline > Generate should generate a Ansys Fluent Simulation Report which is automatically generated with all the information of the simulation in it. This can be exported as a PDF also. We are done with setup, we can close the setup.

Results:

Case 1:

Inlet velocity=1m/s,

Particle size: 5 micrometers.

Scaled Residual:

Velocity Contour:

Pressure Contour:

Anthracite Time:

Case 2:

Inlet velocity=3m/s,

Particle size: 5 micrometers.

Scaled Residual:

Velocity Contour:

Pressure Contour:

Anthracite Time:

Case 3:

Inlet velocity=5m/s,

Particle size: 5 micrometers.

Scaled Residual:

Velocity Contour:

Pressure Contour:

Anthracite Time:

Case 4:

Inlet velocity=3m/s,

Particle size: 1 micrometers.

Scaled Residual:

Velocity Contour:

Pressure Contour:

Anthracite Time:

Case 5:

Inlet velocity=3m/s,

Particle size: 3 micrometers.

Scaled Residual:

Velocity Contour:

Pressure Contour:

Anthracite Time:

CONCLUSION:

The 5 case comparison shows us various data on pressure and velocity contour and the animation of the particle data shows us the formation of double vortices one leading the heavy suspended particles downward and the inner vortex leading the lighter fluid to escape outlet.

The efficiency of the cyclone separator is the ratio of the number of particles trapped to the number of particle tracked. The number of particles tracked is the number of mesh elements in the inlet face, so if we need to study more quantity of particles try reducing the mesh size.

In our case the number of particles tracked is 378. Also the pressure difference (Pressure drop) between the inlet and the escape outlet is also studied and tabulated as follows,

case	inlet velocity (m/s)	particle size (micrometer)	particle Tracked	Particle Trapped	Particle Escaped	Particle Incomplete	Efficiency (%)	Pressure Difference(Pa)
1	1	5	378	307	71	-	81.22	2.27
2	3	5	378	223	152	3	58.99	27.08
3	5	5	378	315	63	-	83.33	83.1
4	3	1	378	310	68	-	82.01	25.36
5	3	3	378	312	66	-	82.54	27.05

INFERENCES:

Here, with reference from the literatures we come to know that the efficiency is better close to 99% when the particle size is more than 10 micrometer. The same is inferred in our study too, we could see that the efficiency is around 80% for all cases except for the 3 m/s and 5 micrometer particle.

Velocity increases around the inlet due to the centrifugal action, and the animation of particle data shows that some particles loose its velocity as it moves down swirling. In real time, this occurs due to the friction between the wall and the particle velocity. So, the cyclone separator is prone to internal wear. Otherwise if the particle size is very small with a optimized velocity for efficiency, cyclone separators are economic and efficient devices for separating suspended particles from the fluid medium, be it air or liquid. Also, the cyclone separator vortex formation greatly depends on the dimensions of the geometry as well.