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Challenge

Cyclone Separator Challenge

AAnurag Bharadwaj1 Aug 2020

AIM

The aim of this project is to simulate the Discrete Phase Model on the Cyclone separator

OBJECTIVES

  • Cyclone separator efficiency study
  • Simulate the cyclone separator by varying the particle diameter
  • Simulate the cyclone separator by varying the particle velocity

CYCLONE SEPERATOR

Cyclone separators or simply cyclones are separation devices that use the principle of inertia to remove particulate matter from flue gases. Cyclone separators is one of many air pollution control devices known as precleaners 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. In addition, several cyclone separators can operate in parallel, and this system is known as a multicyclone.It is important to note that cyclones can vary drastically in their size. The size of the cyclone depends largely on how much flue gas must be filtered, thus larger operations tend to need larger cyclones.

CYCLONE SPERATOR EFFICIENCY MODELS

Iozia and Leth Model

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 . The collection efficiency η of particle diameter `d_p`can be calculated from

`eta=frac[1][1+[d_(pc)+d_(p)]^beta`

where, `beta`is the slope parameter which is given by

`beta=0.62-0.87ln(frac[d_(pc)][100])+5.21ln(frac[ab][D^2))+1.05ln(frac[ab][D))^2`

`d_(pc)`is the 50% cut size given by

`d_(pc)=[frac[9muQ][pirhopz_cv_t^2]]^0.5`

The core length `z_c`and the core diameter `d_c`are given by

`z_c=(H − S) − frac[H − S][(D/B)-1) (d_c/B)-1`

`d_c=0.47D(frac[ab][D^2])^(−0.25)(frac[De][D])^1.4`

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 particle distribution in the cyclone is obtained.
The concentration distribution in a cyclone is given as
`c=frac[c_0(rw− rn) exp[-lambdafrac[1][K(1+n)]r^(1+n)]][int_(rn)^(rw)exp[frac[1][K(1+n)]r^(1+n)]`
where
`K=frac[(1 − n)(ρp− ρg)d^2Q][18 µb[r_w^(1-n)-r_n^(1-n)]`
`lambda=frac[(1 − α)K w_w][D_rr_w^n`
The resultant expression of the collection efficiency for particle of any size is given as
`η_i= 1 − exp{−λθ1}`
`θ1= [2π (S + L)]/a`
Koch and Licht Model
Koch and Licht collection theory recognized the inher- ently turbulent nature of cyclones and the distribution of gas residence times within the cyclone.
A force balance and an equation on the particles collection yields the grade efficiency η_i
`η_i= 1 − exp{−2frac[GτiQ][D^3](n + 1)]^(0.5/(n+1)}`
`G =frac[8K_c][K_a^2K_b^2]`
`n = 1 −{1 −frac[12D^0.14][2.5]}{frac{T+460][530}}^0.3`
`τ_i=frac[ρpd_p^2][18µ]`
G is a factor related to the configuration of the cyclone, n is related to the vortex and τ is the relaxation term.
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, `d_(pc)`is
`d_(pc)=[frac[9 µb][2π N_ev_i(ρ_p− ρ_g)]]^0.5`
where N_e is the number of revolutions
`Ne=1/a[h +frac[H − h][2]]`
The efficiency of collection of any size of particle is given by
`η_i=frac[1][1 + (d_(pc)/d_p)^2`
CYCLONE SEPERATOR SIMULATION (1 micro meter diameter)
The simulation for the cyclone separator involves the following stages
  1. Geometry
  2. Mesh
  3. Setup
  4. Solution
  5. Result

Geometry

In the geometry stage, when we import the geometry into spaceclaim the fluid volume is to be extracted from the solid model.

Once the fluid volume is extracted we have to supress the solid volume for physics from supress for physics option from the graphics window.

Mesh

In the meshing module in order to get the best results for the simulation of discrete phase modelling we use the cut cell mesh option for a structured mesh. This takes the element count to 73235.
Setup
The setup for the simulation is as follows
  1. Solver - pressure solver
  2. Solver state - Steady state
  3. gravity - Gravity = -9.81 m/s^2 in the Y-direction
  4. Turbulence Model - K_epsilon RNG swirl dominated
  5. Discrete phase - Inlet velocity of anthracite particles = 3 m/s
  6. Particle size - Particle diameter = 1e-6 m
  7. Boundary Condition
  8. Inlet velocity of air = 3m/s
  9. Inlet - Reflect BC
  10. Outlet 1 - escape BC
  11. Outlet 2 - trapped BC

The solution has run for 1000 iterations and the solution has converged after 700 iterations.

CYCLONE SEPERATOR EFFICIENCY

The formula is given by

Efficiency = number of particles tracked / number of particles tracked

`eta =54/120xx100`

`eta=45%`

Results

Velocity Contour of particles

Pressure

Animation

CYCLONE SEPERATOR SIMULATION (3 micro meter diameter)
The simulation for the cyclone sepeartor involves the following stages
  1. Geometry
  2. Mesh
  3. Setup
  4. Solution
  5. Result

Geometry

In the geometry stage, when we import the geometry into spaceclaim the fluid volume is to be extracted from the solid model.

Once the fluid volume is extracted we have to supress the solid volume for physics from supress for physics option from the graphics window.

Mesh

In the meshing module in order to get the best results for the simulation of discrete phase modelling we use the cut cell mesh option for a structured mesh. This takes the element count to 73235.
Setup
The setup for the simulation is as follows
  1. Solver - pressure solver
  2. Solver state - Steady state
  3. gravity - Gravity = -9.81 m/s^2 in the Y-direction
  4. Turbulence Model - K_epsilon RNG swirl dominated
  5. Discrete phase - Inlet velocity of anthracite particles = 3 m/s
  6. Particle size - Particle diameter = 3e-6 m
  7. Boundary Condition
  8. Inlet velocity of air = 3m/s
  9. Inlet - Reflect BC
  10. Outlet 1 - escape BC
  11. Outlet 2 - trapped BC

The solution has run for 1000 iterations and the solution has converged after 700 iterations.

CYCLONE SEPERATOR EFFICIENCY

The formula is given by

Efficiency = number of particles tracked / number of particles tracked

`eta =88/120xx100`

`eta=73.33%`

Results

Velocity Contour of particles

Pressure Contour

Animation

CYCLONE SEPERATOR SIMULATION (5 micro meter diameter)
The simulation for the cyclone separator involves the following stages
  1. Geometry
  2. Mesh
  3. Setup
  4. Solution
  5. Result

Geometry

In the geometry stage, when we import the geometry into spaceclaim the fluid volume is to be extracted from the solid model.

Once the fluid volume is extracted we have to supress the solid volume for physics from supress for physics option from the graphics window.

Mesh

In the meshing module in order to get the best results for the simulation of discrete phase modelling we use the cut cell mesh option for a structured mesh. This takes the element count to 73235.
Setup
The setup for the simulation is as follows
  1. Solver - pressure solver
  2. Solver state - Steady state
  3. gravity - Gravity = -9.81 m/s^2 in the Y-direction
  4. Turbulence Model - K_epsilon RNG swirl dominated
  5. Discrete phase - Inlet velocity of anthracite particles = 3 m/s
  6. Particle size - Particle diameter = 5e-6 m
  7. Boundary Condition
  8. Inlet velocity of air = 3m/s
  9. Inlet - Reflect BC
  10. Outlet 1 - escape BC
  11. Outlet 2 - trapped BC

The solution has run for 1000 iterations and the solution has converged after 700 iterations.

CYCLONE SEPERATOR EFFICIENCY

The formula is given by

Efficiency = number of particles tracked / number of particles tracked

`eta =116/120xx100`

`eta=96.67%`

Results

Velocity Contour of particles

Pressure Contour

Animation

CYCLONE SEPERATOR SIMULATION (1 m/s Velocity )
The simulation for the cyclone separator involves the following stages
  1. Geometry
  2. Mesh
  3. Setup
  4. Solution
  5. Result

Geometry

In the geometry stage, when we import the geometry into spaceclaim the fluid volume is to be extracted from the solid model.

Once the fluid volume is extracted we have to supress the solid volume for physics from supress for physics option from the graphics window.

Mesh

In the meshing module in order to get the best results for the simulation of discrete phase modelling we use the cut cell mesh option for a structured mesh. This takes the element count to 73235.
Setup
The setup for the simulation is as follows
  1. Solver - pressure solver
  2. Solver state - Steady state
  3. gravity - Gravity = -9.81 m/s^2 in the Y-direction
  4. Turbulence Model - K_epsilon RNG swirl dominated
  5. Discrete phase - Inlet velocity of anthracite particles = 1 m/s
  6. Particle size - Particle diameter = 5e-6 m
  7. Boundary Condition
  8. Inlet velocity of air = 1 m/s
  9. Inlet - Reflect BC
  10. Outlet 1 - escape BC
  11. Outlet 2 - trapped BC

The solution has run for 1000 iterations and the solution has converged after 700 iterations.

CYCLONE SEPERATOR EFFICIENCY

The formula is given by

Efficiency = number of particles tracked / number of particles tracked

`eta =31/120xx100`

`eta=25.83%`

Results

Velocity Contour of particles

Pressure Contour

Animation

CYCLONE SEPERATOR SIMULATION (3 m/s velocity)
The simulation for the cyclone separator involves the following stages
  1. Geometry
  2. Mesh
  3. Setup
  4. Solution
  5. Result

Geometry

In the geometry stage, when we import the geometry into spaceclaim the fluid volume is to be extracted from the solid model.

Once the fluid volume is extracted we have to supress the solid volume for physics from supress for physics option from the graphics window.

Mesh

In the meshing module in order to get the best results for the simulation of discrete phase modelling we use the cut cell mesh option for a structured mesh. This takes the element count to 73235.
Setup
The setup for the simulation is as follows
  1. Solver - pressure solver
  2. Solver state - Steady state
  3. gravity - Gravity = -9.81 m/s^2 in the Y-direction
  4. Turbulence Model - K_epsilon RNG swirl dominated
  5. Discrete phase - Inlet velocity of anthracite particles = 3 m/s
  6. Particle size - Particle diameter = 5e-6 m
  7. Boundary Condition
  8. Inlet velocity of air = 3m/s
  9. Inlet - Reflect BC
  10. Outlet 1 - escape BC
  11. Outlet 2 - trapped BC

The solution has run for 1000 iterations and the solution has converged after 700 iterations.

CYCLONE SEPERATOR EFFICIENCY

The formula is given by

Efficiency = number of particles tracked / number of particles tracked

`eta =117/120xx100`

`eta=97.5%`

Results

Velocity Contour of particles

Pressure Contour

Animation

CYCLONE SEPERATOR SIMULATION (5 m/s velocity )
The simulation for the cyclone separator involves the following stages
  1. Geometry
  2. Mesh
  3. Setup
  4. Solution
  5. Result

Geometry

In the geometry stage, when we import the geometry into spaceclaim the fluid volume is to be extracted from the solid model.

Once the fluid volume is extracted we have to supress the solid volume for physics from supress for physics option from the graphics window.

Mesh

In the meshing module in order to get the best results for the simulation of discrete phase modelling we use the cut cell mesh option for a structured mesh. This takes the element count to 73235.
Setup
The setup for the simulation is as follows
  1. Solver - pressure solver
  2. Solver state - Steady state
  3. gravity - Gravity = -9.81 m/s^2 in the Y-direction
  4. Turbulence Model - K_epsilon RNG swirl dominated
  5. Discrete phase - Inlet velocity of anthracite particles = 5 m/s
  6. Particle size - Particle diameter = 5e-6 m
  7. Boundary Condition
  8. Inlet velocity of air = 5 m/s
  9. Inlet - Reflect BC
  10. Outlet 1 - escape BC
  11. Outlet 2 - trapped BC

The solution has run for 1000 iterations and the solution has converged after 700 iterations.

CYCLONE SEPERATOR EFFICIENCY

The formula is given by

Efficiency = number of particles tracked / number of particles tracked

`eta =117/120xx100`

`eta=97.5%`

Results

Velocity Contour of particles

Pressure Contour

Animation

CONCLUSION
  1. As the particle size increases the efficiency of the cyclone separator increases.
  2. After a particular size of particle there is no huge effect of particle size on efficiency of cyclone separator
  3. The discrete phase model is captured in the simulations
  4. The velocity of the particles also plays an important role in cyclone separator efficiency
  5. The pressure drop can be visualised from the pressure contours plots.
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