Week 8 - Simulating Cyclone separator with Discrete Phase Modelling

AIM:

• To perform analysis on Cyclone Separator and calculate separation efficiency for given cases

1. Case I - Size of particle = 5 um, Velocity = 1 to 5 m/s
2. Case II - Velocity = 3m/s, size of particles = 1 to 5 um

• Explain different models used to determine the efficiency of cyclone separator in brief

THEORY:

Cyclone Separator:

Cyclone separators or simply cyclones are separation devices (dry scrubbers) that use the principle of inertia to remove particulate matter from flue gases. Cyclone separators is one of many air pollution control devices known as precleaners 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.

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. 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.

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.

Four empirical models used to calculate the cyclone separator efficiency:

Iozia and Leith Model:

Iozia and Leith logistic model is a modified version of 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 ηi of particle diameter dpi can be calculated from

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

Li and Wang Model:

The Li and Wang model includes particle bounce or reentrainment 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 reentrainment 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 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 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: 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 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 [1] to calculate a 50% cut diameter, dpc, is

where Ne is the number of revolutions

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

PROCEDURE

the following procedure is followed in performing the simulation and extracting the results

Step 1 - Geometry setup:

• Import the given geometry in SpaceClaim

• Suppress the given geometry for physics.

 Step 2 - Mesh:

create a baseline mesh
Baseline mesh

STEP 3: SET UP & SOLUTION

• Solver type: pressure based
• Time state: Steady
• Enable gravity with -9.81m/s on y-axis
• Viscous Model :K-epsilon – RNG – Swirl dominated flow
• Methodology : Simulation is done using DPM(Discrete phase modelling)

Boundary Conditions:-

• Inlet velocity : parameter (varying , constant)
• Inlet and wall:- Reflect
• Outlet(Top):- Escape
• Outlet(Bottom/dustbin) – Trap

Run simulation for 600 iterations

case1: 1μm 3m/sec

Result:

case1: 3μm 3m/sec

case1: 5μm 3m/sec

If the velocity of the particle is kept constant and increase the particle size, the seperation efficiency increases but the pressure almost constant with the same velocity.

case2: 5μm 1m/sec

case2: 5μm 3m/sec

case2: 5μm 5m/sec

If the particle size is kept constant and increase the velocity, the seperation efficiency and pressure drop increases.

CONCLUSION

Based on the results discussed in the previous section, we can make the following conclusion

• The efficiency of cyclone separators of the same size and configuration decreases as the particle size decreases.
• The efficiency of the cyclone separator s directly proportional to the flow velocity of the particulate. I.e. high-velocity yields higher efficiency
• Pressure drop only depends on the velocity of the particulate. As the velocity increases the pressure difference between inlet and outlet pressure increases.

As the size of the particle decreases and the velocity of the flow decreases, the time is taken for convergence also increases. So to overcome this, the maximum no of steps in tracking parameters are increased