Cyclone Separator Challenge

Aim:- To perform analysis on cyclone separator and calculate the separation efficiency and pressure drop.

Objective:

1. To study different empirical models used to calculate the cyclone separator efficiency.
2. To perform an analysis on the cyclone separator model and understanding its working.
3. To understand the effects of velocity and particle size (dia 1 μm- 5 μm) on cyclone separator efficiency and pressure drop.

Introduction

Cyclone separators are separation devices (dry scrubbers) that remove particulate matter from flue gases by using the principle of inertia. Cyclone separators are 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.

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 shown 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.

An animated GIF showing how particles move through a cyclonic separator.

Since these larger particles have difficulty following the high-speed spiral motion of the gas and the vortex, the particles hit the inside walls of the container and drop down into a collection hopper. These chambers are shaped like an upside-down cone to promote the collection of these particles at the bottom of the container. The cleaned flue gas escapes out the top of the chamber.

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 par0ticles 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.

Different Empirical models used for cyclone separator efficiency:

4.1. Iozia and Leith Model

Iozia and Leith logistic model is a modified version of the Barth 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 . The collection efficiency `eta_i` of particle diameter `d_(p i)` can be calculated from

`eta_i=frac{1}{1+(d_(pc)/d_(p i))^beta}`

`beta` is the expression for slope parameter derived based on the statistical analysis of experimental data of a cyclone with D = 0.25 m given as

`beta= 0.62-0.87ln (frac{d_(pc)}{100})+5.21 ln (frac{ab}{D^2})+1.05 [ln (frac{ab}{D^2})]^2`

`d_(pc)` is the 50% cut size given by Barth

`d_(pc)=[frac{9muQ}{pi rho_p Z_c (v_(tmax))^2}]^0.5`

where core length `Z_c` and core diameter `d_c` given as

`Z_c = (H-S)-[frac{H-S}{(D/B)-1}][(d_c/B)-1], d_c>B` for

`Z_c=H-S` for `d_c

`d_c=0.47D(frac{ab}{D^2})^(-0.25) (frac{D_e}{D})^1.4`

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 cyclone.

Boundary conditions with the consideration of turbulent diffusion coefficient and particle bounce re-entrainment on the cyclone wall are

`c = c_o, at theta=0`

`D_rfrac{delc}{delr) = (1-alpha)wc, at r=D/2`

The tangential velocity is related to the radius of cyclone by: `muR^n=constant`

`c(r,theta)=frac{c_0(r_w-r_n)exp{-lamda[frac{1}{K(1+n)}r^(1+n)]}}{int_(r_n)^(r_w)exp{frac{1}{K(1+n)}r^(1+n)}dr`

Where

`K= frac{(1-n)(rho_p-rho_g)d^2Q}{18mub(r_w^(1-n)-r_n^(1-n))}`

and

`lamda=frac{(1-alpha)Kw_w}{D_rr_w^n}`

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

`eta_i=1-exp{-lamdatheta_1}`

where

`theta_1=2pi(S+L)/a`

4.3. 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 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: `muR^n`=constant.

A force balance and an equation on the particles collection yields

the grade efficiency ηi

`eta_i=1-exp{-2[frac{Gtau_iQ}{D^3}(n+1)]^(0.5/(n+1)}}`

where

`G=frac{8K_c}{K_a^2K_b^2}`

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

`tau_i=frac{rho_pd_(p i)^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.

4.4. 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 semiempirical relationship developed by Lapple to calculate a 50% cut diameter, `d_(pc)` is

`d_(pc)=[frac{9mub}{2pi N_ev_i(rho_p-rho_g)}]^(1/2)`

where N_e is the number of revolutions

`N_e =frac{1}{a}[h+frac{H-h}{2}]`

The efficiency of the collection of any size of the particle is given by

`eta_i=frac{1}{1+(d_(pc)/d_(p i))^2`

Cyclone Separator Simulation

1) Modeling of Cyclone Separator

2) Meshing

3) Pre-processing

4) Setting up Physics and Solving

5) Post-processing

1) Modeling of Cyclone separator

Prepare the cad model of Cyclone separator using a cad software and then Import into the SpaceClaim.

Extract the volume of the cyclone separator using the Volume extraction command and outer body to be suppressed for physics.

2) Meshing of Cyclone separator

Using the name selection command, provide the name of the boundaries and also provide the mesh size and generate the mesh.

Mesh Size: 06 mm

Number of Nodes: 73014

Number of elements: 370774

3) Setting up physics and solving

Check the mesh first and after that define the solver.

Solver type: Pressure Based

Velocity Formulation: Absolute

Solver: Steady State

Gravity: enabled (-9.81 m/s^2)

Viscous Model: k-epsilon (RNG-Swirl Dominated Flow)

Discrete Phase Model: ON

Select the Interaction with continuous Phase & Update DPM sources every flow iteration. Surface Injection created for inlet and select the Anthracite as a Material. Provide the diameter of the particle and Velocity.

Boundary Conditions

Velocity : 1-5 m/s

Inlet: Reflect

Outlet-1: Escape (Top side)

Outlet-2: Trap (Bottom side)

Method

Momentum: First Order Upwind

Turbulent Kinetic Energy: Second order Upwind

Turbulent Dissipation Rate: Second order Upwind

Initialization

Method: Standard Initialization

Compute From: inlet

Start the Simulation for 500 iterations and get the solution converged.

4) Post-Processing

We perform this simulation we analyze the effect of particle size and effect of Velocity on the cyclone separator.

A) Effect of Particle size

Consider the Velocity as 3 m/s and particle size varied from 1 to 5 `mu m`

Particle Size	1`mu m`	2 `mu m`	3 `mu m`	4 `mu m`	5 `mu m`
Particle Time

Here we are using the velocity of fluid and particle as 3 m/s for all the Particle size so that the change in pressure, velocity, and vortex contour is negligible and gets the nearly same contour.

Pressure, Velocity and Vortex Contour for particle size 5 `mu m`

Animations:

Video animation created for particle time with the velocity 3m/s and different diameters using CFD Post.

Particle Size: 1 `mum`

Particle Size: 3 `mum`

Particle Size: 5 `mum`

Particle Size	Tracked	Escaped	Trapped	Incomplete	Efficiency
1 `mum`	576	266	301	9	0.522
2 `mum`	576	245	329	2	0.571
3 `mum`	576	202	374	-	0.649
4 `mum`	576	189	387	-	0.671
5 `mum`	576	166	410	-	0.712

B) Effect of Particle velocity

Consider the Particle size as 5 `mu m` and varying the particle velocity from 1 to 5 m/s.

Particle Velocity	1 m/s	2 m/s	3 m/s	4 m/s	5 m/s
Particle Time
Pressure
Velocity
Vortex

Animations:

Video animation created for particle time with the velocity 1,3,5 m/s and 5 `mum` diameters using CFD Post.

Particle Size: 1 `mum`

Particle Size: 3 `mum`

Particle Size: 5 `mum`

Particle Velocity	Tracked	Escaped	Trapped	Incomplete	Pressure at Inlet [Pa]	Pressure at Outlet-1	Pressure at Outlet-2	Total Pressure Drop	Efficiency
1 m/s	576	220	240	116	2.36565	0.1901	0.3571	1.87855	0.416667
2 m/s	576	183	385	8	9.89978	0.7815	1.2726	8.62716	0.6684
3 m/s	576	137	439	-	11.9642	1.6573	2.3941	9.5701	0.76215
4 m/s	576	95	481	-	18.6148	3.0441	4.1623	14.4525	0.8351
5 m/s	576	58	518	-	34.0316	4.3134	5.8386	28.193	0.8993

Conclusions

* As we increase the velocity of the cyclone separator, the efficiency of a cyclone separator also increased. while the increase in velocity also increases the pressure which results in high power consumption.

* The cyclone separator efficiency is related to the total pressure drop across the separator. And this is the indirect measure of the energy required to move the gas through the system.

* Below 3 `mum` particle size, cyclone separator is not much effective and it majorly removes the particle size greater than 3 `mum`.

* Pressure and mass flow rate remains constant as velocity constant for different particle sizes and with an increase in particle dia, trapped particles increases, resultant separation efficiency increases.