Week 8 - Simulating Cyclone separator with Discrete Phase Modelling
Aim:-> To perform CFD analysis on cyclone separator.
Theory:-
Cyclone separator:- It is the separation devices which works on principle of inertia to remove particulate matter from flue gases. Cyclone separators is one of many air pollution control devices, known as pre-cleaners 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.
Cyclone separators are generally able to remove somewhere between 50-99% of all particulate matter in flue gas. How well the cyclone separators are actually able to remove this matter depends largely on particle size. If there is a large amount of lighter particulate matter, less of these par0ticles are able to be separated out. Because of this, cyclone separators work best on flue gases that contain large amounts of big particulate matter.
All cyclone separators have an associated pressure drop. The pressure drop can be thought of as the amount of energy required to move the gas through the separator, alternatively, it can be thought of as the amount of resistance the cyclone separator adds to the system flow. The pressure drop is a product of the gas flow rate, gas density and cyclone geometry.
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Gas containing entrained particles (dirty air) enters at high velocity through the tangential inlet at the top of the cyclone. The gas flows into the cyclone body/barrel at a tangent and begins to flow in a circular downward spiral towards the lower reject port; this downward flowing spiral is referred to as a spiral vortex. Particles with more inertia will impact with the side of the cyclone whilst particles with lower inertia will remain within the gas stream. The cone diameter gradually decreases which causes the gas velocity to increase. The outer vortex creates an additional inner vortex closer to the center of the separator body and this inner vortex flows spirally upwards towards the accept port.
Particles with greater inertia will be less affected by the vortex and will continue travelling in a straight line. This straight-line trajectory causes the high inertia particles to move out of the gas stream and impact with the cyclone separator body. These particles then fall to the base of the cyclone separator and out of the reject port. In this way, entrained particles of a certain size can be separated from the gas stream.
Empirical efficiency models:-
1. Iozia and Leith model:
Iozia and Leith model is modified version of Barth model. This model is developed based upon force balance. The model assumes that a particle carried by the vortex endures the influence of two forces i.e. centrifugal force and flow resistance.
Collection efficiency of a particles with diameter dpi">dpi
can be calculated as-
ηi=11+(dpcdpi)β">ηi=11+(dpcdpi)β
Where,
β=Expression for slope parameter">β=Expression for slope parameter
β=0.62-0.87ln(dpc100)+5.21ln(abD2)+1.05ln(abD)2">β=0.62−0.87ln(dpc100)+5.21ln(abD2)+1.05ln(abD)2
dpc=50% cut size">dpc=50% cut size
dpc=[9μQπρpzcvtmax2]0.5">dpc=[9μQπρpzcv2tmax]0.5
2. Li and Wang model:
Li and Wang (1989) model includes particle bounce or re-entrainment and turbulent diffusion at cyclone wall. A two dimensional analytical expression of particle distribution in cyclone is obtained.
This model based on following assumption-
-> 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 re-entrainment on the cyclone wall are:
c=c0 at θ=0">c=c0 at θ=0
Dr∂c∂r=(1-α)ωc at r=D2">Dr∂c∂r=(1−α)ωc at r=D2
-> The tangential velocity is related to the radius of cyclone by:
uRn=constant">uRn=constant
The collection efficiency can be formulate as-
ηi=1-exp{-λθ1}">ηi=1−exp{−λθ1}
where,
θ1=2πS+La">θ1=2πS+La
λ=(1-α)kωwDrrwn">λ=(1−α)kωwDrrnw
3. 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">uRn=constant
The efficiency can be calculated as-
Here G is factor related to configuration of cyclone and n related to vortex.
4. 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 to calculate a 50% cut diameter, dpc, is
dpc=[9μb2πNevi(ρp-ρg)]0.5">dpc=[9μb2πNevi(ρp−ρg)]0.5
Where,
Ne=Number of revolution">Ne=Number of revolution
Ne=1a[H+h2]">Ne=1a[H+h2]
And efficiency can be given as-
ηi=11+(dpcdpi)2">ηi=11+(dpcdpi)2
Pre processing:-
It includes geometry preperation and mesh generation.
Geometry:
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Fig: Geometry |
Above figure shows geometry of cyclone separator.
The 3D model of cyclone separator provided by course instructor in form of STEP file is imported in ANSYS space-claim. Then by using edge selector from volume extraction option choose inlet and outlet edges carefully to extract volume. Then extract volume by clicking on correct option. Hence we got our extracted volume. Then hide the cyclone separator body and suppressed it for physics also.
In above figure red color shows extracted volume and blue color shows cyclone separator body.
Material:
The fluid is considered as air here and the dirt particals are concider as anthracites.
PROCEDURE
the following procedure is followed in performing the simulation and extracting the results
Step 1 - Geometry setup:
- Import the given geometry in SpaceClaim
- Extract the fluid volume from the geometry. Prepare -> extract volume -> select edges
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- Suppress the given geometry for physics.
Step 2 - Mesh:
- Here cut cell approach is tried to mesh the domain to obtain better accuracy and mesh quality
- Named selections are assigned to identify the inlets and outlets of the domain.
Step 3 - Setting up Physics:
- Pressure based, steady-state solver. Gravity = 9.81 m/s2
- Model: K-Epsilon -> RNG, Swirl Dominated Flow
- Model: Discrete Phase model -> Interaction with continuous phase, update DPM sources every flow iteration, Max no of steps -> Create Injections
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- Boundary Conditions: Inlet -> velocity, DPM = reflect, Outlet top -> DPM = escape, Outlet bottom -> DPM = trap, walls -> DPM = reflect
Step 4 - Method:
Step 5 - Initialization: Standard initialization
Step 6 - Run the simulation: enter no of iterations, run the simulation
Step 7 - Extract the results: Check convergence from residuals, particle tracking, pressure contours.
RESULT
CASE 1
- v=3 m/s, d=1e-6 m
Residual
Particle Resident Time & Separation Efficiency
Separation Efficiency = 215/465 = 46.23 %
Pressure contour & Pressure drop
Max Pressure = 11.65 pa, Min Pressure = -2.396 Pa
Pressure Difference = 14.046 Pa - v=3 m/s, d=2e-6 m
Residual
Particle Resident Time & Separation Efficiency
Seperation Efficiencey = (Trapped/Tracked)*100 = 50.75%
Pressure contour & Pressure drop
Max Pressure = 11.65 pa, Min Pressure = -2.396 Pa
Pressure Difference = 14.046 Pa - v=3 m/s, d=3e-6 m
Residual
Particle Resident Time & Separation Efficiency
Seperation Efficiencey = (Trapped/Tracked)*100 = 55.48%
Pressure contour & Pressure drop
Max Pressure = 12.54 pa, Min Pressure = -2.991 Pa
Pressure Difference = 15.531 Pa - v=3 m/s, d=4e-6 m
Residual
Particle Resident Time & Separation Efficiency
Seperation Efficiencey = (Trapped/Tracked)*100 = 61.5%
Pressure contour & Pressure drop
Max Pressure = 11.65 pa, Min Pressure = -2.398 Pa
Pressure difference = 14.048 Pa - v=3 m/s, d=5e-6 m
Residual
Particle Resident Time & Separation Efficiency
Seperation Efficiencey = (Trapped/Tracked)*100 = 70.32 %
Pressure contour & Pressure drop
Max Pressure = 11.65 pa, Min Pressure = -2.397 Pa
Pressure difference = 14.047 Pa
Case 1 Size of Particles (m) Velocity of particles (m/s No of the particles tracked No of the particles escaped No of the particle trapped No of the particles incomplete separation efficiency (%) Pressure difference (Pa) 1 1e5 3 465 239 215 11 46.23 14.046 2 2e5 3 465 229 236 0 50.75 14.046 3 3e5 3 465 207 258 0 55.48 14.046 4 4e5 3 465 179 286 0 61.5 14.048 5 5e5 3 465 138 327 0 70.32 14.047
CASE 2
- v=1 m/s, d=5e-6 m
Residual
Particle Resident Time & Separation Efficiency
Seperation Efficiencey = (Trapped/Tracked)*100 = 24.086 %
Pressure contour & Pressure drop
Max Pressure = 1.032 pa, Min Pressure = -1.844 Pa
Pressure difference = 2.876 Pa - v=2 m/s, d=5e-6 m
Residual
Particle Resident Time & Separation Efficiency
Seperation Efficiencey = (Trapped/Tracked)*100 = 62.79 %
Pressure contour & Pressure drop
Max Pressure = 5.396 pa, Min Pressure = -1.366 Pa
Pressure difference = 6.762 Pa - v=3 m/s, d=5e-6 m
Residual
Particle Resident Time & Separation Efficiency
Seperation Efficiencey = (Trapped/Tracked)*100 = 70.32 %
Pressure contour & Pressure drop
Max Pressure = 11.65 pa, Min Pressure = -2.397 Pa
Pressure difference = 14.047 Pa - v=4 m/s, d=5e-6 m
Residual
Particle Resident Time & Separation Efficiency
Seperation Efficiencey = (Trapped/Tracked)*100 = 78.70 %
Pressure contour & Pressure drop
Max Pressure = 21.44 pa, Min Pressure = -4.371 Pa
Pressure difference = 25.811 Pa - v=5 m/s, d=5e-6 m
Residual
Particle Resident Time & Separation Efficiency
Seperation Efficiencey = (Trapped/Tracked)*100 = 84.73 %
Pressure contour & Pressure drop
Max Pressure = 34.3 pa, Min Pressure = -7.055 Pa
Pressure difference = 41.355 Pa
Case 1 Size of Particles (m) Velocity of particles (m/s) No of the particles tracked No of the particles escaped No of the particle trapped No of the particles incomplete Separation efficiency (%) Pressure difference (Pa) 1 5e5 1 465 248 112 115 24.086 2.876 2 5e5 2 465 173 292 0 62.79 6.762 3 5e5 3 465 138 327 0 70.32 14.047 4 5e5 4 465 99 366 0 78.7 25.811 5 5e5 5 465 71 394 0 84.73 41.355
Note: Ideally the cyclone separator simulation requires zero incomplete particles. But due to the limitation in computation, few cases discussed above have few incomplete particles. This can be optimized with an increase by increasing the maximum no of steps in tracking parameters.
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.