Week 8 - Simulating Cyclone separator with Discrete Phase Modelling
AIM:- The project aim is to perform an analysis of the cyclone separator and calculate the separation efficiency and pressure drop.
OBJECTIVE:- The project objectives are-
- 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 calculating 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 the same as particle velocity]
INTRODUCTION:- Cyclones are devices that employ a centrifugal force generated by spinning gas steam to separate particles from the carrier gas. A gas cyclone separator is widely used in industries to separate dust from gas or for product recovery because of its geometrical simplicity, the relative economy in power, and flexibility.
This figure shows how we separate smaller particle from bigger particle.
Cyclones are particularly well suited for high temperature and pressure conditions because of their rugged design and flexible component materials and they can be operated at very high dust loading. Cyclone separators are used for the removal of large particles for both air pollution control and process use. Application in extreme conditions includes the removal of coal dust in a power plant and the use as a spray dryer or gasification reactor.
Fig: Industrial Cyclone Separator
Engineers are generally interested in two parameters to assess the design and performance of a cyclone. These parameters are the cyclone efficiency of particles and pressure drop through the cyclone. An accurate prediction of cyclone efficiency is very important because inaccuracy in the efficiency prediction may result in an inefficient design of the cyclone separator. CFD has a great potential to predict the flow field characteristics and particle trajectories inside the cyclone. The complicated swirling turbulent flow in a cyclone places great demands on the numerical techniques and the turbulence models employed in the CFD codes when modeling the cyclone pressure drop.
This study presents an application of CFD, in the prediction of cyclone efficiency. This study also reviews the four empirical models for cyclone efficiency. Additionally, we can analyze simulation results. Our simulation can be done in Ansys Fluent.
PROJECT DESCRIPTION:- Before going to our simulation, let's discuss four empirical models to calculate cyclone separator efficiency-
- 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 flow resistance, W. The collection efficiency `eta_i` of particle diameter `d_"pi"`can be calculated from
`beta` is an expression for slope parameter derived based on the statistical analysis of experimental data of a cyclone with D = 0.25 m gives as
And dpc is the 50% cut size given by Bath
Where core length, zc, and core diameter, dc, are given as
-
Li and Wang Model:- The Li and Wang model includes particle bounce or re-entrainment and turbulent diffusion at the cyclone wall. A two-dimensional analytical expression of practical distribution in the cyclone is obtained. Li and Wang's model was developed based on the following assumptions:
- The radial particle velocity and the radial concentration profile are not constant for uncontrolled 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 the cyclone by uRn = constant.
The concentration distribution in a cyclone is given as:
And
The resultant expression of the collection efficiency for a particle of any size is given as
Where
-
Koch and Licht Model:- Koch and Licht's 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, there is no slip in the tangential direction between the particle and the gas.
- The tangential velocity is related to the radius of the cyclone by uRn = constant.
A force balance and an equation on the particles collection yield the grade efficiency `eta_i`
Where
G is a factor related to the configuration of the cyclone, n is the related to the vortex and `tau` is the relaxation term.
-
Lapple Model:- Lapple model was developed based on the force balance with our considering the flow resistance. Lapple assumed that a particle entering the cyclone is evenly distributed across the inlet opening. The particle that travels from the inlet half width to the wall in the cyclone is collected with 50% efficiency. The semi-empirical relationship developed by Lapple to calculate a 50% cut diameter, dpc, is
Where is the number of revolutions
The efficiency of collection of any size of a particle is given by
Geometry and Meshing:- This is our geometry -
To extract the fluid volume from the geometry we use the Volume Extract tool in the Analysis group on the Prepare tab and select the edges to enclose the region.
Now we created the fluid volume
After creating fluid volume, we hide our geometry. Since it can effect the analysis, we select the geometry and click on suppress for physics option.
Meshing:- Here we use Body fitted cartesian meshing for more accurate result.
Mesh details:-
Solver Settings:-
- Pressure-based solvers and absolute velocity are used.
- It is a 3D simulation.
- Steady-state simulation is performed.
- The gravity is enabled in the -ve Y-axis.
- The RNG K-epsilon turbulence model is taken as a viscous model. Because the RNG model is better for swirling flow.
- Here we use Discrete phase modeling. Discrete phase models are used in simulating dilute particle flows. In these methods, point masses that are representing parcels of particles are traced through the computational domain by evaluating local force balances.
- Here we take inert particle as Anthracite. We inject Anthracite through inlet face and we keep both the velocity same.
- In pressure-velocity coupling, a SIMPLE scheme is used. For the momentum, a second order upwind scheme is used and for pressure, the second order is selected. In the case of Turbulent Kinetic Energy and Turbulent Dissipation Rate, a second-order scheme is chosen.
Report:- This is one of the simulation full report
Fluent
Version: 3d, dp, pbns, rngke (3d, double precision, pressure-based, RNG k-epsilon)
Release: 22.1.0
Title:
Models
------
Model Settings
-----------------------------------------------------------------
Space 3D
Time Steady
Viscous RNG k-epsilon turbulence model
Wall Treatment Standard Wall Functions
RNG Differential Viscosity Model Disabled
RNG Swirl Dominated Flow Option Enabled
Heat Transfer Disabled
Solidification and Melting Disabled
Species Disabled
Coupled Dispersed Phase Enabled
NOx Pollutants Disabled
SOx Pollutants Disabled
Soot Disabled
Mercury Pollutants Disabled
Structure Disabled
Acoustics Disabled
Eulerian Wall Film Disabled
Potential/Li-ion Battery Disabled
Multiphase Disabled
Material Properties
-------------------
Material: anthracite (inert-particle)
Property Units Method Value(s)
---------------------------------------------------
Density kg/m^3 constant 1550
Cp (Specific Heat) J/(kg K) constant 1680
Material: air (fluid)
Property Units Method Value(s)
----------------------------------------------------------------
Density kg/m^3 constant 1.225
Cp (Specific Heat) J/(kg K) constant 1006.43
Thermal Conductivity W/(m K) constant 0.0242
Viscosity kg/(m s) constant 1.7894e-05
Molecular Weight kg/kmol constant 28.966
Thermal Expansion Coefficient K^-1 constant 0
Speed of Sound m/s none #f
Material: aluminum (solid)
Property Units Method Value(s)
-----------------------------------------------------
Density kg/m^3 constant 2719
Cp (Specific Heat) J/(kg K) constant 871
Thermal Conductivity W/(m K) constant 202.4
Cell Zone Conditions
--------------------
Zones
name id type
--------------------------
volume_volume 3 fluid
Setup Conditions
volume_volume
Condition Value
---------------------
Frame Motion? no
Boundary Conditions
-------------------
Zones
name id type
-----------------------------------------
wall-volume_volume 1 wall
inlet 6 velocity-inlet
outlet1 7 pressure-outlet
outlet2 8 pressure-outlet
Setup Conditions
wall-volume_volume
Condition Value
------------------------------------------
Wall Motion Stationary Wall
Shear Boundary Condition No Slip
inlet
Condition Value
----------------------------------
Velocity Magnitude [m/s] 3
Discrete Phase BC Type reflect
outlet1
Condition Value
-----------------
outlet2
Condition Value
------------------------------
Discrete Phase BC Type trap
Solver Settings
---------------
Equations
Equation Solved
-------------------
Flow yes
Turbulence yes
Numerics
Numeric Enabled
---------------------------------------
Absolute Velocity Formulation yes
Under-Relaxation Factors
Variable Relaxation Factor
----------------------------------------------
Pressure 0.3
Density 1
Body Forces 1
Momentum 0.7
Turbulent Kinetic Energy 0.8
Turbulent Dissipation Rate 0.8
Turbulent Viscosity 1
Discrete Phase Sources 0.5
Linear Solver
Variable Solver Type Termination Criterion Residual Reduction Tolerance
-----------------------------------------------------------------------------------------------
Pressure V-Cycle 0.1
X-Momentum Flexible 0.1 0.7
Y-Momentum Flexible 0.1 0.7
Z-Momentum Flexible 0.1 0.7
Turbulent Kinetic Energy Flexible 0.1 0.7
Turbulent Dissipation Rate Flexible 0.1 0.7
Pressure-Velocity Coupling
Parameter Value
------------------
Type SIMPLE
Discretization Scheme
Variable Scheme
------------------------------------------------
Pressure Second Order
Momentum Second Order Upwind
Turbulent Kinetic Energy Second Order Upwind
Turbulent Dissipation Rate Second Order Upwind
Solution Limits
Quantity Limit
---------------------------------------
Minimum Absolute Pressure 1
Maximum Absolute Pressure 5e+10
Minimum Temperature 1
Maximum Temperature 5000
Minimum Turb. Kinetic Energy 1e-14
Minimum Turb. Dissipation Rate 1e-20
Maximum Turb. Viscosity Ratio 100000 CASE_1:- In case 1, we 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. And we also discuss the results. Here we use both the velocity's as 3m/sec for all five simulations.
Results for 1μm:-
Residual:-
Anthracite Particle Time Plot:-
Vortex Core Region:-
Results for 2μm:-
Residual:-
Anthracite Particle Time Plot:-
Vortex Core Region:-
Results for 3μm:-
Residual:-
Anthracite Particle Time Plot:-
Vortex Core Region:-
Results for 4μm:-
Residual:-
Anthracite Particle Time Plot:-
Vortex Core Region:-
Results for 5μm:-
Residual:-
Anthracite Particle Time Plot:-
Vortex Core Region:-
Data Table for the results for various particle diameter:-
Cyclone Separator efficiency vs Particle Diameter Plot:-
CASE_2:- In case 2, we 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.. And we also discuss the results. Here we use particle diameter size as 5 μm for all five simulations.
Results for 1m/s:-
Residual:-
Anthracite Particle Time Plot:-
Vortex Core Region:-
Inlet Pressure:-
Results for 2m/s:-
Residual:-
Anthracite Particle Time Plot:-
Vortex Core Region:-
Inlet Pressure:-
Results for 3m/s:-
Residual:-
Anthracite Particle Time Plot:-
Vortex Core Region:-
Inlet Pressure:-
Results for 4m/s:-
Residual:-
Anthracite Particle Time Plot:-
Vortex Core Region:-
Inlet Pressure:-
Results for 5m/s:-
Residual:-
Anthracite Particle Time Plot:-
Vortex Core Region:-
Inlet Pressure:-
Data Table for the results for various velocity:-
Cyclone Separator efficiency vs Particle Velocity Plot:-
Pressure Difference vs Particle Velocity Plot:-
CONCLUSION:- After seeing all the result we conclude that -
- With the increase of particle diameter, the efficiency will decrease.
- With the increase of particle velocity, the efficiency will decrease.
- With the increase of particle velocity, the Pressure will increase.