Challenge

Week 8 - Simulating Cyclone separator with Discrete Phase Modelling

NNikhil Kumar14 Feb 2023

Week 8 - Simulating Cyclone separator with Discrete Phase Modelling

Introduction:-

The centrifugal force produced by a spinning gas stream is used by cyclones to separate the particles from the carrier gas. They are perfect for use as pre-cleaners for more expensive final control devices like bag houses or electrostatic precipitators due to their straightforward design, low initial cost, and almost maintenance-free operation. Cyclones excel in high temperature and pressure environments because to their robust construction and flexible component materials.
For particles larger than 5 m, cyclone collection efficiency can exceed 99% and can be used at very high dust loadings.
Large particle removal is done with cyclones for both process usage and reducing air pollution.

The removal of coal dust from a power plant, the usage as a spray drier, or the use as a gasification reactor are examples of applications in harsh environments.
In order to evaluate the design and performance of a cyclone, engineers are often interested in two characteristics. These variables are the pressure drop through the cyclone and particle collecting efficiency. It is crucial to anticipate cyclone efficiency accurately since an inaccurate prediction might lead to an ineffective cyclone separator design. The pressure decrease inside the cyclone as well as the properties of the flow field and particle trajectories may all be accurately predicted using CFD.

This study also examines the cyclone efficiency predictions of four distinct empirical models:

1.Lapple,

2.Koch and Licht,

3.Li and Wang, and

4.Iozia and Leith.

Following that, experimental data from the literature for various inlet flow rates, pressures, and temperatures is compared with the modelling findings.

1. Lapple
Without taking into account flow resistance, the Lapple model was established based on force balance. Lapple made the supposition that a particle entering the cyclone is dispersed uniformly over the inlet hole. In the cyclone, the particle that passes from the half-width entrance to the wall is gathered with a 50% efficiency. Lapple created a semi-empirical relationship to determine a 50% cut diameter, dpc, and it is

2. Koch and Licht
The Koch and Licht collection hypothesis identified the dispersion of gas residence periods inside cyclones and the intrinsically turbulent character of cyclones. Koch and Licht made the following additional assumptions for describing particle motion in the entrance and collecting regions:
• The tangential velocity is linked to the radius of the cy clone by: u Rn = constant.

• 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 grade efficiency is determined by a force balance and an equation for the collection of particles.

G is a factor related to the configuration of the cyclone, n is related to the vortex and τ is the relaxation term.

3. Li and Wang
The Li and Wang model takes into account turbulent diffusion at the cyclone wall as well as particle bounce or re entrainment. It is possible to represent the particle distribution in the cyclone analytically in two dimensions. The following presumptions served as the foundation for the Li and Wang model:
• For uncollected particles inside the cyclone, the radial particle velocity and the radial concentration profile are not constant. • Boundary conditions taking into account the turbulent diffusion coefficient and particle bounce re-entrainment on the cyclone wall are:

• The tangential velocity is related to the radius of cyclone by: u Rn = constant.
The concentration distribution in a cyclone is given as:

4. Iozia and Leith
The Barth Model, which was created based on force balance, was updated by Iozia and Leith.
A particle transported by a vortex is said to be subject to two forces: a centrifugal force, Z, and a flow resistance, W. One may determine the collecting effectiveness I of particle diameter dpi 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

Project description statement:

1. The flow is simulated at an intake with a constant velocity and variable particle diameter. The separation effectiveness is determined.

2. The flow is simulated with variable inlet velocity and constant particle diameter. The cases' separation effectiveness and pressure decrease are determined.

Increasing particle size from 1 micron to 5 microns while maintaining a 3 m/s velocity:

Setup of geometry

1. Select the Fluid flow (fluent) module and begin changing the shape.

2. Open Spaceclaim and import the model's step file.

3. Using the prepare option, fluid volume is derived from the geometry. so that we may analyse the cyclone separator's fluid flow.

4. Since we are only interested in the fluid flow and not the exterior surface, hide the prior geometry and suppress the physics.

Meshing

Mesh stats:

1. Main element size: 5mm

2. Method = Cartesian method

3. No. of elements= 427361

After meshing the model, pick generate mesh to create the basic mesh. However, since mesh refinement affects how many particles enter the inlet, it is preferable to refine the mesh suitably.

b. Offering a named choice:

The tool for picking faces is chosen. Names are given to the inlets, outlet escape, and outlet trap. The intake is where the particles enter; the top allows the smaller impurities to leave, while the bottom traps the larger ones.

Fixing the physics setup

1) General circumstances:

The cyclone separator's orientation is the subject of this investigation. The acceleration owing to gravity must be activated as it is in the x-y plane. The g value is shown as -9.81 on the positive y axis since gravity operates upwards.

It uses a pressure-based solution. The velocity concept used in the steady state analysis is absolute and normal to the boundary.

2. Turbulence modelling:

The K-epsilon(2 equation) model with RNG and swirl-dominated flow is chosen for turbulence modelling. Enhanced wall functions make up the functions.

The Energy is not activated since temperature is unimportant.

Discrete phase modelling is the method chosen.

The continuous phase can be interacted with by the model. DPM level of interval is 10.

The sort of particle is inert for injection. Anthracite is chosen from the fluent database. It is emitted from the intake at a speed of 3 m/s in the x direction. This speed can be changed much further. One micrometres is the particle diameter that was selected for the initial analysis. To determine the separation efficiency, the particle diameter is adjusted from one micrometre to five micrometres.

Boundary conditions: For the three mentioned options, inlet, outlet escape, and outlet trap, the boundary criteria are given.

The velocity requirements for inlet are 3 m/s in the x direction, absolute, and normal to the boundary. The DPM state is evident. This means that the particles cannot escape or become stuck in the intake.

Momentum conditions for the top outlet are essentially pressure conditions whereas DPM conditions are escape. This Boundary allows for the escape of particles.

Additionally a pressure outlet, the bottom outlet's DPM condition is trap.

Solution methods

The COUPLED technique is selected for the pressure velocity coupling. The gradient is based on cells with the least squares. Second order upwind is present for pressure, momentum, turbulent kinetic energy, and turbulent dissipation rate.

Initialization: Flow from inlets is used for standard initialization.

The analysis is done for 500 iterations.

Diameter of the particles = 1 micrometers

The scaled residuals plot :

Inlet Pressure

Outlet Pressure

Track of particles (in Video format)

Link of the video:-

https://youtu.be/dhacvEuu7Yc

Fluent PT For Anthracite

Votex Core Strength region (Swirling Trength)

Numbers of particles trapped and escaped

Pressure Drop

According to the Problem Statement,

Calculation of Separation Efficiency & Pressure Drop In this case are:-

1. Separation efficiency:-

separation efficiency = (Number of particles trapped / Number of particles tracked ) * 100

i.e Here, (312/378)*100 = 82.54%

2. Pressure Drop:-

pressure drop = inlet Pressure - outlet pressure

here, (29.403 - 3.931)Pa = 25.472 Pa

Case - 2

Diameter of Particles = 3micrometer & Velocity = 3m/s

Plots:-

Residuals Plots:-

Inlet Pressure

Outlet pressure

Fluent Pt For Anthracite

Swirling Strength

particles Trapped & Escaped

Pressure Drop

Video Track of Particles

Link of the video

https://youtu.be/Fu6eCup-CvU

Calculation of separation efficiency & Pressure Drop

1. Separation efficiency :-

S.E = (Number of Particles trapped / particles tracked ) * 100

here, (312/378) * 100 = 82.54%

2. Pressure Drop:-

Pressure Drop = Inlet Pressure - Outlet Pressure

here, (29.403-3.931)Pa = 25.472 Pa

Case 3 - Diameter of Particle = 5 micrometer & Velocity = 3m/s

Plots:-

Residuals Plots:-

Inlet pressure

Outlet pressure

Fluent Pt for Anthracite

SWirling Strength

Particles trapped and Tracked

Pressure Drop (inlet - Outlet)

inlet pressure

outlet pressure

Video link of the particles tracked

https://youtu.be/yBuYSTSVBHE

Calculation of Separation efficiency & Pressure Drop

1. Separation efficiency :-

Separation efficiency = (Number of particles trapped / Number of particles tracked ) * 100

here , = (267 / 378) * 100 = 70.63%

2. Pressure Drop

here, (29.403 - 3.931)Pa = 25.472 Pa

Case = 4

Diameter of Particles = 5 micrometer & Velocity = 1 m/s

Plots:-

Residuals Plots:-

Inlet Pressure

Outlet Pressure

Fluent Pt for Anthracite

Swirling Strength

Particles trapped & Tracked

Pressure Drop

Video link of the particles tracked:-

https://youtu.be/X9IYxbSEuVQ

Calculation of Separation efficiency & Pressure Drop

1. Separation Efiiciency :-

Separation efficiency = (Number of particles trapped / Number of particles tracked) * 100

here , S.E = (305/387) * 100 = 80.68%

2. Pressure Drop:-

Pressure Drop = (Inlet Pressure - Outlet Pressure)

here , (2.635-0.320)Pa = 2.315 Pa

Case = 5

Particle diamter = 5 micrometer & velocity = 5m/s

Plots

residuals Plots

Inlet Pressure

Outlet Pressure

Fluent Pt For Anthracite

Swirling Strength

Number of particles trapped and Tracked

Pressure Drop

Video link of the particles tracked

https://youtu.be/pcC6cw81veQ

Calculation of Separation efficiency & Pressure Drop

1. Separation efiiciency

Separation efficiency = (Number of Particles trapped / Number of Particles tracked) * 100

here , S.E = (289/378) * 100 = 76.45%

2. Pressure Drop

Pressure Drop = (Inlet Pressure - Outlet Pressure)

here, (86.125-(-0.0617) Pa = 86.1867 Pa

Final results Tabulation

Cyclone Separator Efficiency

Size of the Particle	Velocity of the particle	No. of Particles Tracked	No. of Particles trapped	No. of particles escaped	cyclone separator efficiency
5 micrometer	1 m/s	378	305	73	80.68%
5 micrometer	3m/s	378	267	111	70.63%
5 micrometer	5m/s	378	289	81	76.45%
3 micrometer	3m/s	378	312	66	82.54%
1 micrometer	3m/s	378	312	66	82.54%

Inference:

We may deduce that the pressure is higher close to the wall section that creates the outer vortex from the pressure velocity charts shown above. The creation of a low-pressure area at the centre of the cyclone separator as a result of greater pressure along the wall causes lighter particles to escape from the top outlet and heavier particles to gather at the bottom outlet.

With air and particle velocities of 3 m/s, simulations are run for particle sizes ranging from 1 m to 5 m. Via the video, it can be seen that smaller particles escape from outlet 1 while larger particles are stuck at the bottom outlet. However, we can also see that lighter particles are trapped at the bottom outlet as a result of interactions between lighter and heavier particles. As a result of these interactions, which result in an exchange of inertial forces and a transfer of kinetic energy from heavier to lighter particles, we can see that some heavier particles also manage to escape through the top outlet.

Week 8 - Simulating Cyclone separator with Discrete Phase Modelling

Ship work like this
in your own course.

Talk to a career counsellor

Ship work like thisin your own course.

Talk to a career counsellor

Ship work like this
in your own course.