Challenge

Simulating Cyclone separator with Discrete Phase Modelling

Simulation Procedure :

Geometry

  1. Import the geometry.
  2. Extract the fluid volume & check for any extra edges so the fluid volume don't get obstruct.
  3. Suppress the outer geometry.
  4. This completes the geometry section.

Mesh

  • Open the mesh section
  • Name the faces like inlet, outlet-1,outlet-2.

  • Then generate the mesh(in our case we have used 0.0055 m mesh element size).

Setup :

  1. Perform mesh check
  2. Set up gravity
  3. Turn on the Turbulence model, In our case we are using K-epsilon RNG model as it is good for swirl domination flows.
  4. Set up the DPM and DPM iteration interval.
  5. Then add injections to inlet surface and set up point properties like particle velocity, Diameter and flow rate.
  6. Set the boundary conditions.
  7. Set up the solution method and relaxation factors.
  8. Finally initialize and run the setup.
  9. Export the particle history.

Result :

  1. Make the fluid volume visible.
  2. Import the particle data.
  3. Set the particle tracks and color them with required variables.
  4. Set up quick animation and observe the particle flow.

Mesh Input :

1] Element size = 0.0055 m/5.5 mm

2] Total elements = 459278

Setup Inputs :-

1] Solver - Pressure Based Steady

2] Viscous Model - K-epsilon RNG(Swirl Domination Flow)

3] Particles - Anthracite

4] Fluid - air

5] DPM Boundaries - Inlet = Reflect

Outlet 1 = Escape

Outlet 2 = Trap

6] Solution method - SIMPLE(first order)

7] No. of DPM tracking steps - 50000

Outputs

########################## { CASE I : Simulation on Varrying particle Diameter } ##########################

In this case we are going to vary particle diameter from 1μm - 5μm and keep the particle and flow velocity as 3m/s and calculate the separation efficiency for each case.

<<<<<<<<<<<<<<< [ For Particle Dia. = 1 μm] >>>>>>>>>>>>>>>

  • Residual

  • Particle time

  • Particle animation

https://youtu.be/fGPJNZRxvdA

Particle Info. :

Tracked Escaped Trapped Incomplete
350 159 189 2

<<<<<<<<<<<<<<< [ For Particle Dia. = 2 μm] >>>>>>>>>>>>>>>

  • Residual

  • Particle time

  • Particle Animation

https://youtu.be/maw202oOAXk

Particle Info. :

Tracked Escaped Trapped Incomplete
350 141 207 2

<<<<<<<<<<<<<<< [ For Particle Dia. = 3 μm] >>>>>>>>>>>>>>>

  • Particle time

  • Particle animation

https://youtu.be/ALPlNeP5bzU

Particle Info. :

Tracked Escaped Trapped Incomplete
350 124 225 1

<<<<<<<<<<<<<<< [ For Particle Dia. = 4 μm] >>>>>>>>>>>>>>>

  • Residual

  • Particle Time

  • Particle Animation

https://youtu.be/U9IU5L541gY

Particle Info. :

Tracked Escaped Trapped Incomplete
350 102 245 3

<<<<<<<<<<<<<<< [ For Particle Dia. = 5 μm] >>>>>>>>>>>>>>>

  • Residual

  • Particle animation

https://youtu.be/h7lBcweCXxA

Particle Info. :

Tracked Escaped Trapped Incomplete
350 68 278 2

Seperation Efficiency = (Particles Trapped/Particles Tracked) * 100

Particle Dia. Trapped Tracked Efficiency
1μm 189 350 54%
2μm 207 350 59.14%
3μm 225 350 64.28%
4μm 245 350 70%
5μm 278 350 79.42%

########################## { CASE II : Simulation on Varrying particle and flow Velocities } ##########################

In this case we are going to vary particle and flow velocity from 1m/s - 5m/s and keep the particle diameter as 5μm and calculate the separation efficiency & pressure drop for each case.

<<<<<<<<<<<<<<< [ For Velocity : 1m/s ] >>>>>>>>>>>>>>>

  • Specifically for this case only with velo. 1m/s, we are going to use different mesh settings and higher number of DPM tracking steps(500000), as the velocity is too low and also the Max. elements restrictions, it is difficult to capture particles which ultimately results in higher incomplete particles, as the no. of mesh elements(0.5 million) aren't enough with this case with lower velocity.
  • Also we need to relax the pressure & momentum equation to get better results.

mesh element size - 0.00531 m/5.31 mm

total elements - 495457

DPM setting-

Under -relaxation factor -

Outputs -

  • Residual

  • Pressure

  • Particle animation

https://youtu.be/9Gxiggn3Slo

Particle Info. :

Tracked Escaped Trapped Incomplete
360 199 156 5

<<<<<<<<<<<<<<< [ For Velocity : 2m/s ] >>>>>>>>>>>>>>>

  • Residual

  • Pressure

  • Particle time

  • Particle Animation

https://youtu.be/q8sDZhRMDpQ

Particle Info. :

Tracked Escaped Trapped Incomplete
350 116 230 4

<<<<<<<<<<<<<<< [ For Velocity : 3m/s ] >>>>>>>>>>>>>>>

  • Residual

  • Pressure

  • Particle time

  • Particle animation

https://youtu.be/444YmTABEKc

Particle Info. :

Tracked Escaped Trapped Incomplete
350 68 278 2

<<<<<<<<<<<<<<< [ For Velocity : 4m/s ] >>>>>>>>>>>>>>>

  • Residual

  • Pressure

  • Particle time

  • Particle Animation

https://youtu.be/s9mDyy55M9I

Particle Info. :

Tracked Escaped Trapped Incomplete
350 38 311 1

<<<<<<<<<<<<<<< [ For Velocity : 5m/s ] >>>>>>>>>>>>>>>

  • Residual

  • Pressure

  • Particle time

  • Particle Animation

https://youtu.be/vHqnZaP40ZM

Particle Info. :

Tracked Escaped Trapped Incomplete
350 31 319 0

Seperation Efficiency = (Particles Trapped/Particles Tracked) * 100

Particle velocity Trapped Tracked Efficiency Pressure drop (Pa)
1m/s 156 360 43.33 0.9184
2m/s 230 350 65.71% 4.7434
3m/s 278 350 79.42% 11.9853
4m/s 311 350 88.85% 22.625
5m/s 319 350 91.14% 35.381

########################## { Observations } ##########################

  • Finer mesh gives more no. of tracked particles, so finer the mesh more will be the accuracy of simulation as it tracks more particles.
  • It can be seen that in CASE I as the particle diameter increases, no. of trapped particles increases too and so does the seperation efficiency.
  • Also there is no difference in pressure drop in all sub cases of CASE I as the velocity is same for all sub cases.
  • It can also be seen that, in CASE II as the velocity increases, so does the seperation efficiency and pressure drop.
  • More no. of tracking steps results in more accurate and stable results, ultimately resulting in less no. of incomplete particle in critical cases.
  • Also the floww seems to be converged as the residual repeats the same pattern after considerable amount of iterations.

Empirical models :-

1] Iozia & Leith model

This model assumes that the particle carried by vortex, experiences 2 forces mainly centrifugal force and flow resistance. The collection efficiency for the same can be calculated by

where dpi = particle diameter

dpc is the 50% cut size of Barth version.

2] Li and Wang model :-

This model has partcile bounce and turbulent diffusion at cyclone walls. This model is based on 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 turbulent diffusion coefficient and particle bounce re-entrainment on the cyclone wall are c=c0 at theta=0

  • The tangential velocity is related to the radius of cy-clone by:`uR^n=constant`

The collection efficiency for particle of any size can be calculated as follows :

3] Koch and licht model:-
This model 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: u R^n= constant.

The efficiency can be calculated as follows :

4] Lappel 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.

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