Challenge

Cyclone Separator Challenge

AAbhijeet Dhillon3 Aug 2020

Aim:

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

To write a few words about any four empirical models used to calculate the cyclone separator efficiency.
To perform an analysis on a 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 velocity's as 3m/sec.]
To perform an analysis on a given cyclone separator model by varying the particle velocity from 1 m/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]

Solution:

Cyclone Separator :

Cyclone separators or simply cyclones are separation devices (dry scubbers) that use the principle of inertia to remove particulate matter from flue gases . Cyclone separators is one of many air pollution removers 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. In addition, several cyclone separators can operate in parallel, and this system is known as a multicyclone

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 Figure . 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 (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

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:

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:

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 efficiency of a cyclone collector is related to the pressure drop across the collector.
This is an indirect measure of the energy required to move the gas through the system.
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.

Discreate Phase Modelling :

The Lagrangian discrete phase model in ANSYS FLUENT follows the Euler-Lagrange approach. The fluid phase is treated as a continuum by solving the Navier-Stokes equations, while the dispersed phase is solved by tracking a large number of particles, bubbles, or droplets through the calculated flow field. The dispersed phase can exchange momentum, mass, and energy with the fluid phase.

A fundamental assumption made in this model is that the dispersed second phase occupies a low volume fraction(<10%). The particle or droplet trajectories are computed individually at specified intervals during the fluid phase calculation

Coupling between Continuous and Discrete Phase:

One way Coupling-
The fluid phase influences the discrete phase via drag and turbulence.
The discrete phase has no influence on the continuous phase.
Two-way coupling-
The continuous phase influences the discrete phase via drag and turbulence.
The discrete phase influences the continuous phase via source terms of mass, momentum, and energy.
It alternately solves the discrete and continuous phase equations until the solutions in both phases stop changing.

“Interaction with Continuous Phase“ – if this was selected (but do
not select it now) this would mean that that as well as the
continuous (air) region influencing the particles, the particles will also
influence the momentum / energy of the air.

Step Length Factor“ indicates how many steps each particle should make across a grid cell

“Max Number of Steps“ sets a limit for the number of steps. Sometimes particles are trapped in arecircilation region, and this parameter is needed to stop the solver being trapped in a continuous loop.
The solver needs to know what to do with a DPM
particle / droplet when it meets a flow boundary. Note
the additional ‘DPM‘ tab on the Boundary condition
panels for this. The main choices are:
– ‘Escape‘ if particles are free to leave at this boundary
– ‘Reflect‘ if they will bounce off this boundary
– ‘Trap‘ if they will stick to this boundary

Analysis :

Extracting the fluid Volume :

Meshing:

A element size of 5 mm has been given:

Now we will be varying the velocity at the inlet and varying the particle size:

Case1:Varying Velocity :

1.Inlet Velocity = 1m/s

Now the efficiency will be given by :