Week 8 - Simulating Cyclone separator with Discrete Phase Modelling

AIM:

To perform an analysis on cyclone separator and calculate the separation efficiency and pressure drop.

OBJECTIVE:

• 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 calculate 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 same as particle velocity]

INTRODUCTION:

CYCLONE SEPARATOR:

Cyclone separators or simply cyclones are separation devices that use the principle of inertia to remove particle 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. For example, several different models of one cyclone type can exist, and the sizes can range from a relatively small 1.2-1.5 meters tall (about 4-5 feet) to around 9 meters (30 feet)—which is about as tall as a three story building!.

WORKING:

Cyclone separators work much like a centrifuge, but with a continuous feed of dirty air. In a cyclone separator, 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 is shown in 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.

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 setting 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.

APPLICATION OF CYCLONE SEPARATOR:

• Sawmills to remove sawdust
• Oil refineries
• Kiln preheaters
• Vacuum cleaners
• Extraction woods
• High-pressure washing devices
• Lubricating fluid
• Industrial water treatment.

EMPRICAL MODELS USED TO CALCULATE THE CYCLONE SEPARATOR EFFICIENCY:

IOZIA AND LEITH MODEL:

Iozia and Leith logistic model is a modified version of 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 a flow resistance, W. Core length, Z_c, and core diameter, d_c.

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. 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:

c=c0,at θ=0

Dr∂c∂r=(1−α)wc,Dr∂c

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. 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:

c=c0at θ=0

Dr(∂c/∂r)=(1-α)wc,at r=D/2

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 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: uR^n=constant

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.

SIMULATION PROCEDURE:

GEOMETRY:

• First the geometry is imported into the Ansys spaceclaim.

• Then the fluid volume is extracted from the model using the volume extraction tool available in spaceclaim.

MESH:

• The named selection such as inlet and two outlets are assigned to the models using the named selection option available in meshing module.

INLET:

OUTLET:

• The mesh is created for the model with a mesh size of 10mm.

• Number of nodes – 22858
• Number of elements – 112026

SETUP:

GENERAL:

• Time – steady state
• Solver type – pressure based
• Velocity formulation – absolute
• Gravity - -9.81 m/s2 [y- direction]

VISCOUS MODEL:

• Swirl dominated RNG k-epsilon with standard wall function.

MATERIAL:

• Fluid - air

BOUNDARY CONDITION:

INLET:

• Velocity – Case 1: 1m/s

Case 2: 3m/s

Case 3: 5m/s

Case 4,5,6: 3m/s

• DPM BC type – reflect

OUTLET1:

• Gauge pressure – zero pa

• DPM BC type - escape

OUTLET2:

• Gauge pressure – zero pa

• DPM BC type – trap

WALL BC:

• Wall motion – stationary
• Shear condition – no slip
• Wall roughness - standard

• DPM BC type - reflect

DISCRETE PHASE MODEL:

Discrete phase modelling is a method in which the flow of the discrete phase with a continuous flow is modelled. DPM is used to track individual particles through the continuum fluid. The lagrangian discrete phase model follows the lagrangian approach. The fluid phase is treated as a continuum by solving the navier-stokes equation, while the dispersed phase is solved by tracking a large number of particle, bubble or droplet through the calculated flow field. The dispersed phase can exchange momentum, mass, energy with the fluid phase.

In this case solid particle size ranging from 1micrometer to 5micrometer is being simulated as a discrete phase.

• Enabled interaction with continuous phase – to enable coupled flow
• Enabled update DPM sources every flow iterations.
• Tracking parameters – maximum no of steps – 50000.

• Injection type - surface
• Particle type – inert
• Diameter distribution - uniform

INITIALIZATION:

Standard initialization

The simulation is runned for 600 iterations.

RESULTS:

1. 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.

CASE1 – VELOCITY : 1M/S AND DIAMETER : 5 MICROMETER:

RESIDUAL:

ANTHRACITE PARTICLE TIME:

VORTEX CORE REGION:

VELOCITY PLOT:

PRESSURE PLOT:

PARTICLE DATA:

Separation efficiency = No. of particle trapped/No. of particle tracked

separation efficiency = (8/120)*100 = 6.67%

PRESSURE DROP:

CASE2 – VELOCITY : 3M/S AND DIAMETER : 5 MICROMETER:

RESIDUAL:

ANTHRACITE PARTICLE TIME:

VORTEX CORE REGION:

VELOCITY PLOT:

PRESSURE PLOT:

PARTICLE DATA:

Separation efficiency = No. of particle trapped/No. of particle tracked

separation efficiency = (119/120)*100 = 99.17%

PRESSURE DROP:

CASE3 – VELOCITY : 5M/S AND DIAMETER : 5 MICROMETER:

RESIDUAL:

ANTHRACITE PARTICLE TIME:

VORTEX CORE REGION:

VELOCITY PLOT:

PRESSURE PLOT:

PARTICLE DATA:

Separation efficiency = No. of particle trapped/No. of particle tracked

separation efficiency = (120/120)*100 = 100%

PRESSURE DROP:

SUMMARY:

CASES	VELOCITY (m/s)	DIAMETER (μmμm)	PRESSURE DROP(pa)	SEPARATION EFFICIENCY(%)
CASE 1	1m/s	5μmμm	0.516 pa	6.67%
CASE 2	3m/s	5μmμm	5.325 pa	99.17%
CASE 3	5m/s	5μmμm	15.35 pa	100%

2. To 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.

CASE1 – VELOCITY : 3M/S AND DIAMETER : 1MICROMETER:

RESIDUAL:

ANTHRACITE PARTICLE TIME:

VORTEX CORE REGION:

VELOCITY PLOT:

PRESSURE PLOT:

PARTICLE DATA:

Separation efficiency = No. of particle trapped/No. of particle tracked

separation efficiency = (34/120)*100 = 28.33%

PRESSURE DROP:

CASE2 – VELOCITY : 3M/S AND DIAMETER : 3MICROMETER:

RESIDUAL:

ANTHRACITE PARTICLE TIME:

VORTEX CORE REGION:

VELOCITY PLOT:

PRESSURE PLOT:

PARTICLE DATA:

Separation efficiency = No. of particle trapped/No. of particle tracked

separation efficiency = (105/120)*100 = 87.5%

PRESSURE DROP:

CASE3 – VELOCITY : 3M/S AND DIAMETER : 5 MICROMETER:

RESIDUAL:

ANTHRACITE PARTICLE TIME:

VORTEX CORE REGION:

VELOCITY PLOT:

PRESSURE PLOT:

PARTICLE DATA:

Separation efficiency = No. of particle trapped/No. of particle tracked

separation efficiency = (119/120)*100 = 99.17%

PRESSURE DROP:

SUMMARY:

CASES	VELOCITY (m/s)	DIAMETER (μmμm)	PRESSURE DROP(pa)	SEPARATION EFFICIENCY(%)
CASE 1	3m/s	1μmμm	5.325 pa	28.33%
CASE 2	3m/s	3μmμm	5.325 pa	87.5%
CASE 3	3m/s	5μmμm	5.325 pa	99.17%

CONCLUSION:

• In this challenge we have analyzed the cyclone separator efficiency by varying the diameter and velocity.
• As we increased the diameter and velocity, the separation efficiency also increases.
• Velocity has a great impact as compared to diameter variation.
• Pressure also depends on velocity change.
• For constant velocity, by varying the diameter size pressure drop remains the same.
• Increases in velocity causes the high pressure drop.