Steady State Simulation of Cyclone Separator with Discrete Phase Modelling (DPM)

STEADY STATE SIMULATION ON CYCLONE SEPARATOR WITH DISCRETE PHASE MODELLING (DPM) USING ANSYS FLUENT

1. AIM

Our aim is to perform analysis on a cyclone separator with discrete phase modeling (DPM) by varying the particle diameter and its velocity to calculate its separation efficiency and pressure drop using ANSYS FLUENT.

2. THEORY/EQUATIONS/FORMULAE USED

ANSYS FLUENT academic version CFD package is used to carry out the simulation. It is a user friendly interface which provides high productivity and easy-to-use workflows. Workbench contains all workflow needed for solving a problem such as pre-processing, solving and post-processing.

Discrete Phase Modelling (DPM)

Discrete Phase Modelling (DPM) is a technique used when there is a need to represent the solid particles or liquid droplets/ bubbles in gas. It is sub set of multiphase flow. DPM is used when the intention is to investigate the behavior of flow particles from a lagrangian view or discrete perspective.

Lagrangian Approach - Fluid behavior is examined based on particle tracking of a particulate flow where the observer travels along with fluid.

Eulerian Approach - Fluid behavior is considered based on the assumption of a finite volume element in the fluid flow path i.e, observer focuses on specific locations in the space through which the fluid flows as the time passes.

DPM has two phases such as Continuous phase and Discrete Phase.

Continuous phase – It consist of the fluid flowing within the volume which is solved by Navier-Stokes Equation.

Discrete phase – It consist of the smaller particles that interacts with the flowing fluid/ Continuous phase within the volume. It is simulated by tracking the large number of particles/ bubbles/ droplets passing through the continuous phase. Discrete phase can exchange momentum, mass, and energy with the continuous phase.

Assumption - Ignoring the interaction of particles (as well as droplets and bubbles) with each other. Of course, this can happen when the discrete phase, even with a large mass, has a much smaller volume (less than 10%) than the continuous phase. The particle paths (as well as bubbles or droplets) tracking are calculated and determined separately after each iteration of the continuous phase calculations are done.

Application Examples

DPM is useful in various problems such as cyclone separator (particle separation and classification), spray drying, aerosol dispersion, bubble stirring of liquids, liquid fuel combustion, and coal combustion.

Cyclone Separator

Any process has a reaction stage and/or separation stage in which the flow particles are separated and purified. Such separations involve physical principles based on differences in the properties of the constituents in the stream. One of the principle methods for the separation of mixtures is Cyclone separator.

Principle

Cyclone separators or simply cyclones are separation devices that use the principle of inertia to remove particulate matter from flue gases.

It also called a cyclonic dust collector is a widely used air pollution control device that cleanses flue gases of particulate matter before such gases exit into the atmosphere. It's a method of collecting up to 99% of airborne waste in an easy-to-empty container beneath the cyclone.

These devices are primarily labeled as pre-cleaners, as they are instrumental in removing large and abrasive particles from flue gases, which then go through additional filtration processes to remove fine particulate matter. The relevance of cyclone separators lies in the fact that they facilitate the first step of the flue gas filtration process. The objective of these devices is to minimize air pollution and environmental hazards caused by production plant exhaust.

In addition, several cyclone separators can operate in parallel, and this system is known as a multicyclone.

How does it Work?

Cyclone separators works like a centrifuge, but with a continuous feed of dirty air. These 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. 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.

Ranges of Working - 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 flue gas. Effectiveness depends largely on particle size. Cyclone separators work best on flue gases that contain large amounts of big particulate matter than with the large amount of lighter particulate matter

Advantages

1. Cyclone separators are cheap to install and maintain as they have no moving parts. This keeps maintenance and operating costs low.
2. The removed particulate matter is collected when dry, which makes it easier to dispose of.
3. These units take up very little space.

Disadvantage - Standard models are not able to collect particulate matter that is smaller than 10 micrometers effectively and they are unable to handle sticky or tacky materials well.

Empirical Model used to calculate Cyclone Separator Efficiency

1. 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, Z_c, and core diameter, dc, are given as

The addition made by Iozia and Leith on the original Barth (1956) model are the core length Z_c and slope parameter b expression which is derived based on the statistical analysis of experimental data of cyclone with D = 0.25 m. The collection efficiency η_i of particle diameter dpi can be calculated from

2. LI AND WANG MODEL

The Li and Wang (1989) model includes 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:

• The tangential velocity is related to the radius of cyclone by: uRⁿ = constant.

The concentration distribution in a cyclone is given as:

where

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

3. KOCH AND LICHT MODEL

Koch and Licht (1977) 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.

A force balance and an equation on the particles collection yield the grade efficiency η_i,

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

4. LAPPLE MODEL

Lapple (1951) 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 (1951) to calculate a 50% cut diameter, d_pc, is

where N_e is the number of revolutions

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

Problem – Steady State analysis on a Cyclone Separator by DPM

Steady state analysis on a Cyclone Separator using DPM by varying the particle diameter and its velocities to calculate the separation efficiency, pressure drop and discuss the results.

Calculation - Steady State Simulation

Fluid chosen for the problem – Air

Density = 1.225 kg/m3, Cp (Specific Heat) = 1006.43 j/kg-k, Thermal Conductivity = 0.0242 W/m-k

Injection Particle – Anthracite

Separation Efficiency

In general, the efficiency is defined as the number of particle collected at the outlet to the number of particles injected into the cyclone separator.

Separation Efficiency = Number of Particles collected at the outlet

Number of Particles injected at the inlet

The efficiency depends on various factors such as the inlet density, velocity, diameter of the particles, Cyclone separators diameter, length, smoothness of the separator wall, etc. In this problem only the particle dia and the inlet flow and particle velocities are varied.

Pressure Drop

Pressure drop (ΔP) is defined as the difference in the total pressure between the inlet and outlet of across any flow system.

Pressure drop (ΔP) = Total Pressure at the inlet - Total Pressure at the Outlet

Pressure drop is inevitable in any system as there will be losses for sure. The losses are such as frictional losses, kinetic energy losses, etc. In Cyclone separator, the significant losses are due to the swirl motion and energy dissipation. The pressure drop affects the performance of any system so as the cyclone separator. So its monitoring is very important in order to minimize it and improve the performance.

Note - The DPM Boundary conditions for outlet 1 and 2 are escape and trap respectively. So in order to calculate the efficiency and pressure drop the number of particles trapped at the outlet 2 is considered.

3. PROCEDURE

• In the process, firstly the geometry is imported in SpaceClaim and suitable clean up procedures are followed.
• Suitable geometry clean-up for Cyclone Separator model is done such as extracting the volume for flow domain.
• Baseline meshing is done to understand the problem and then to know how much and where the refinement is required in order to study the flow and all the boundaries are named respectively. Also checked the mesh quality is good enough to carry out the simulation.
• Fluid and Injection particle are defined, also solver type, the initial and boundary condition, suitable turbulence model are defined as per the problem.
• In the current problem 10 cases are defined with changes in velocity from 1 to 5 m/s and particle diameter 1 to 5 µm with total flow rate of 1e-20.
• In this case k-epsilon turbulence model is used with RNG as the flow is swirl dominated; the particle tracking data is exported in .xml format and used in CFD post.
• The report definition for the total pressure of inlet and outlet and contours of particle tracking time is initiated in order to validate the essential features.

4. NUMERICAL ANALYSIS (Software used – ANSYS 2018 R1)

• Geometric Model

The 3D geometry of Cyclone Separator is imported in SpaceClaim and the cleanup is done as per the figure given below.

3D Geometry and Extracted Volume – Cyclone Separator

Fig: Geometry Fig: Extracted Flow Domain

• Mesh

Fig: Baseline Mesh Fig: Structural cutcell Mesh

• Boundaries

Fig: Boundaries for the complete domain

• Solver Set-up

1. The mesh file is imported into the FLUENT software for the analysis of the modeled surface.
2. Once the mesh file is loaded and displayed, it is checked for the units, scale, and mesh.
3. There are two types of numerical solver methods pressure –based and density-based solver. The pressure based solver was used rather than the density based solver as the simulation is for lower Mach number. Absolute velocity formulation, steady state was used for the analysis. Gravity is also initiated.

4. k-epsilon turbulence model with RNG as the flow is swirl dominated is used for the analysis.

5. The fluid material chosen is air.

6. Coupled flow is chosen as there is interaction of the injection particle with continuous phase. Also tracking parameters such as max number of steps (Max. time) and step length factor or Length scale (time step) are defined.

Note - Larger the step length factor smaller the time step & smaller the length scale smaller the time step.

7. The chosen Injection particle is Anthracite, is created and the point properties such as velocity, dia and total flow rates are defined. Also the injection type and the release point are set.

8. Convergence and monitor are checked for absolute criteria of 0.00001 for all the residuals.

9. Solution methods – SIMPLE Scheme used for Pressure-Velocity coupling and the methods for Spatial Discretization are as per the below image.

10. Standard initialization is done and computing starts from inlet. Numbers of iterations are set for running the steady simulation.

11. Surface report for Total Pressure is set at inlet and outlet 1 to monitor the variation during run time.

12. Particle Tracking History is exported in .xml format.

13. Quick animation is created to see the flow of injected particle by setting one time repeat and saved it in .mp4 format.

Initial Setup and Boundary Condition

Zone	Type	Boundary Condition	Discrete Phase Modelling BC Type	Additional conditions (if any)
Inlet	Velocity - Inlet	1, 2, 3, 4, 5 m/s	Reflect	Steady State, Pressure Based, Absolute Switched OFF Energy equation Turbulence Model – k-epsilon RNG
Outlet 1 & 2	Pressure - Outlet	0 Pa	Outlet 1 – Escape & Outlet 2 - Trap
Interior-Volume	Interior	Interior	-
Wall	Wall	Stationary wall without slip	Reflect

Fig. Cell Zone Conditions & Boundaries Fig. Inlet Boundary – Velocity Inlet Fig. Discrete Phase Boundary Condition Type for Inlet

5. RESULTS

• Case – 1A

Fig: Convergence Criteria – Residual

Fig: Inlet Pressure Plot Fig: Outlet Pressure Plot

Fig: Pressure Drop

Fig: Particle Time Contour

Fig: Particle Tracking Data

• Case 2A

Fig: Convergence Criteria – Residual

Fig: Inlet Pressure Plot Fig: Outlet Pressure Plot

Fig: Pressure Drop

Fig: Particle Time Contour

Fig: Particle Tracking Data

• Case 3A

Fig: Convergence Criteria – Residual

Fig: Inlet Pressure Plot Fig: Outlet Pressure Plot

Fig: Pressure Drop

Fig: Particle Time Contour

Fig: Particle Tracking Data

• Case 4A

Fig: Convergence Criteria – Residual

Fig: Inlet Pressure Plot Fig: Outlet Pressure Plot

Fig: Pressure Drop

Fig: Particle Time Contour

Fig: Particle Tracking Data

• Case 5A

Fig: Convergence Criteria – Residual

Fig: Inlet Pressure Plot Fig: Outlet Pressure Plot

Fig: Pressure Drop

Fig: Particle Time Contour Fig: Pressure Contour

Fig: Particle Tracking Data

• Case 1B

Fig: Convergence Criteria – Residual

Fig: Inlet Pressure Plot Fig: Outlet Pressure Plot

Fig: Pressure Drop

Fig: Particle Time Contour Fig: Pressure Contour

Fig: Particle Tracking Data

• Case 2B

Fig: Convergence Criteria – Residual

Fig: Inlet Pressure Plot Fig: Outlet Pressure Plot

Fig: Pressure Drop

Fig: Particle Time Contour Fig: Pressure Contour

Fig: Particle Tracking Data

• Case 3B

Fig: Convergence Criteria – Residual

Fig: Inlet Pressure Plot Fig: Outlet Pressure Plot

Fig: Pressure Drop

Fig: Particle Time Contour Fig: Pressure Contour

Fig: Particle Tracking Data

• Case 4B

Fig: Convergence Criteria – Residual

Fig: Inlet Pressure Plot Fig: Outlet Pressure Plot

Fig: Pressure Drop

Fig: Particle Time Contour Fig: Pressure Contour

Fig: Particle Tracking Data

• Case 5B

Fig: Convergence Criteria – Residual

Fig: Inlet Pressure Plot Fig: Outlet Pressure Plot

Fig: Pressure Drop

Fig: Particle Time Contour Fig: Pressure Contour

Fig: Particle Tracking Data

Swirling Strength at different Levels

Absolute Helicity at different Levels

Comparison between all cases based on Separation Efficiency and Pressure Drop

6. CONCLUSION

1. Convergence plot shows that the residual remained more or less constant after 500 iterations and hence can be considered as converged solution in all cases.
2. From Case-A, It can be understood that the pressure drop remain constant for all cases as the velocity remains constant even with varied particle diameter.
3. So, with the change in particle and flow velocity for a particular particle diameter the pressure drop varies can be observed from all Case-B. Also the pressure drop increases with increase in velocity.
4. Pressure contour shows that the pressure is high at the inlet and outer surface of the separator as the particle is being injected from the inlet and then it travels from axial to radial direction which imparts pressure on outer surface.
5. From both Case-A & Case-B, it can be seen that the separation efficiency increase with increase in particle diameter and with increase in particle and flow velocity respectively.
6. The efficiency is calculated based on the data acquired from particle tracking at the inlet and outlet.
7. From the particle time tracking contours, it can be oserved that the particle resident time decreses with increase in velocity and particle diameter.
8. Hence, We can clearly say that Case A4 Cyclone separator is the better choice, with minimum velocity (3 m/s) and particle diameter (4 µm) gives high efficiency with a trade off with considerably less pressure drop among the simulated cases.
9. So it can be concluded that separation efficiency depends on the particle diameter, particle & flow velocity, and less resident time as well. Hence the results are in good agreement and the underlying physics is visible clearly.

7. REFERENCES

1. Jolius Gimbun¹, T.G. Chuah², Thomas S. Y. Choong² and A. Fakhru’l-Razi² , 1Faculty of Chemical and Natural Resources Engineering, University College of Engineering and Technology Malaysia, KUKTEM, Bandar MEC, 25200 Kuantan, Pahang, 2Department of Chemical and Environmental Engineering, Faculty of Engineering, Universiti Putra Malaysia, 43400 UPM, Serdang, Selangor: “EVALUATION ON EMPIRICAL MODELS FOR THE PREDICTION OF CYCLONE EFFICIENCY”, Journal - The Institution of Engineers, Malaysia (Vol. 67, No. 3, September 2006)
2. Wang^a,b, D.L. Xu^b, K.W. Chu^a, A.B. Yu^a,*, a Center for Simulation and Modelling of Particulate Systems and School of Materials Science and Engineering,University of New South Wales, Sydney, NSW 2052, Australia, b Institute of Powder Engineering, School of Materials Science and Engineering, Xi’an University of Architecture and Technology,Xi’an 710055, PR China : “NUMERICAL STUDY OF GAS–SOLID FLOW IN A CYCLONE SEPARATOR”, Applied Mathematical Modelling 30 (2006) 1326–1342
3. https://en.wikipedia.org/wiki/Pressure_drop
4. https://www.mr-cfd.com/services/fluent-modules/discrete-phase-model-dpm/
5. https://nptel.ac.in/content/storage2/courses/103103027/pdf/mod5.pdf
6. https://www.safeopedia.com/definition/5682/cycloneseparator#:~:text=A%20cyclone%20separator%2C%20also%20called,empty%20container%20beneath%20the%20cyclone.
7. https://energyeducation.ca/encyclopedia/Cyclone_separator
8. https://courses.ansys.com/index.php/courses/fluid-kinematics/lessons/simulation-examples-homework-and-quizzes-2/topic/simulation-example-cyclone-separator/
9. https://en.wikipedia.org/wiki/Lagrangian_and_Eulerian_specification_of_the_flow_field