prediction of cleaning efficiency of an electrostatic precipitator

8/12/2019 Prediction of Cleaning Efficiency of an Electrostatic Precipitator

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Created by-Gourab Patra

Mechanical Engineering DepartmentSeptember,2012

Bengal engineering & science university, shibpur


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Why use ESP? One of the major air pollution problems is due to the particulate

emissions from many large industrial units.

The concentration of solid air pollutants in the vicinity of the

industrial areas constitutes a constant offence to all inhabitants andthe environment.

These pollutants composed mainly ofAlO3, SiO2, CaO and Fe2O3.The major part of this quantity is composed of particles with

diameters less than10 m which can be inhaled with air.

Electrostatic precipitators are widely used to control the particulate

emissions.

Cleaning efficiency of an ESP may vary between 90% and 99%

MECHANICAL ENGG. DEPT. 2


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The optimisation of the cleaning efficiency of ESPs isimportant in a wide range of industrial applications.

Present paper describes the development andassessment of a complete design and optimisationmethod.



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In this paper the numerical method and the associatedmodels are analysed first; then detailed results are

presented and discussed and the final conclusions are

drawn thereupon.



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Structure of The Procedure:

1.1. Flow field modelling.

1.2. Electric fieldmodelling.

1.3. Particle dynamics.

1.4. Particlereentrainment.

1. Thenumerical

method



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2.1. Original operatingconditions.

2.2. Optimisation study-insertion of smoothing grids.

2. Results

anddiscussion.

3.Conclusions.



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8/41MECHANICAL ENGG. DEPT. 8


9/41MECHANICAL ENGG. DEPT. 9


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The continuity and momentum equations are


Where,is the density,uiandXiare the Cartesian velocity components and coordinatedirections, respectively.

Pis the pressure .denotes the dynamic viscosity.


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At this point, the complete three dimensional flow field issolved iteratively, assuming that it is influenced neither by

the particulate phase nor the electric field.



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2.2. Electric field modelling


The electric field of an electrostatic precipitator is defined by

the following equations:

where is the density of the electric current, the charge

density, the air dielectric constant, bthe ion mobility, theelectric field and the electric potential.

E0

cJ


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These equations are reduced to:

Boundary conditions for solving this set of equations:1. The electric potential on the electrode surface is constant and equal

to the corona onset value.

2. At the grounded collecting plates, potential value is zero.

3. The third condition is related to the first derivative of the electric

potential on the electrode surface and its mathematical form is givenby,2/1)/( rBAEon

(9)


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whereEonis the ion current threshold value for an electrode of

radius r and is the relative density of air (with respect to the

normal conditions). A and B are constants with valuesA=30.1105 v/m

B=9.06104 v/m1/2

for an electrode-plate set-up.

Under the above conditions, the system of the electric-field equations is solved using the grid presented in thefigure on the next slide.



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1.3. Particle dynamicsIn this step a Langrangian approach is adopted, in which aparticle trajectory is calculated and monitored until collection

or escape in the atmosphere occurs.

The Langrangian representation of the solid phase gives an

accurate prediction of the electrostatic precipitator-collection

efficiency, provided that a large number of particle trajectories

is monitored.

For the present study, the order of magnitude of the monitoredtrajectories is 106.



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The electric charge of the particles is analytically calculated by thecharging equation


Where, qp=Instant particle charge.

qs=Saturation charge.e =Electron charge.

vm=Average thermal ion velocity.

rp=Particle radius.

c=Charge density.

k is the Boltzmann constant, T the gas temperature and K the

dielectric constant of the particle material.


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The saturation charge, the average thermal ion velocity and the ion

mobility are given by the following relations:

bs=Ion mobility in normal T0 andP0conditions.

The integration of Eq. (14) is done with a fourth order Runge-Kutta

method, along with the integration of the motion Eqs.(10) and (11).


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1.4. Particle reentrainment

Most significant factor for reducing collecting efficiency.

The dust collected on the plate surface is subject to the reentrainment

mechanism.

Occurs due to;

rapping action on the collecting plates.

erosion by particles and the fluid flow.

the weight of the particle agglomerations.

above mechanisms produce a dust detachment off the plates that

drifts a significant amount of particle mass back into the flow.

Usually, the size of the reentrained particles ranges from the

submicron to the 10 m scale.



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The reentrainment modelling is based on the following relation:

Pris the mass fraction of a detached dust agglomeration that will be

reentrained into the flow.

L is the length of the distance, which the agglomerationhas travelled after its detachment.

A, B are constants. For the ESP under experiment, A =0.003 and

B =2.

This model is reliable only when the monitored particle trajectories

are at least of the order of 500000.


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2. Results & discussions

Findings from the numerical analysis :1. Effect of particle reentrainment mostly governs the collecting

efficiency of an ESP.

2. This effect can be minimized by an aerodynamic optimisation of

the velocity profile.

3. Most of reentrainment occurs at the upper section of the collector

plate, velocity of the particles is to be minimised here.

4. This is done by employing a skewed velocity profile with a

skewness factor less than 1.



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Skewness factor:


The skewness factor represents the ratio of the flow velocity at the topsection over the velocity at the bottom section of the filter.


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2.1. Original operating conditions.


The typical operating conditions of the industrial ESP are as follows:The inlet flue gases velocity = 18.43 m/s.

Inlet temperature 191.31o

C.Density =0.67 kg/m3.

Table 1 presents a detailed view of the particle size distribution at the inlet,


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The velocity profile at the collecting section inlet is highly non-

uniform and skewed in the adverse direction than the desired

one.(next fig.).

It is expected that reentrainment will be enhanced, causing a

degradation at the filters collecting efficiency.

The reason for the poor aerodynamic quality of the flow at the

central section is the sudden expansion in geometrical configuration.



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Velocity Profile observed from the x-y plane:


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3.2. Optimisation study-insertionof smoothing grids

The optimisation is carried out by insertion of smoothing grids.

These grids can be easily constructed and implemented into the unitat very low cost.

The grids have a cell structure, with variable cell density, which

corresponds to a resistance coefficient.

The insertion of five smoothing grids at the positions x = 15:0; 17.9,18.2, 35.3 and 36:6m, gave a quasi-uniform velocity profile, which

corresponds to substantially improved aerodynamic characteristics.



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It is observed that the collecting areas are wider and smoother, with

an important section of them extended to the lower parts of the

collecting plates. The mass balance of this section gave an efficiency value of 98.8%,

which corresponds to a 44% emissions reduction in comparison with

the original operating conditions.

This result proves that with the insertion of cost-effective smoothinggrids, the cleaning efficiency of a unit can be significantly improved.



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3.conclusions:

The methodology presented in the Sections 12 constitutes a

modular approach to the modelling of electrostatic precipitators.

The advanced tools and models implemented therein are based on

physical considerations and contain very few empirical parameters.

It can be used to simulate precipitation mechanisms in any kind of

industrial process.

The agreement with the available experimental data is considered

satisfactory and therefore, the present methodology has been used in

order to optimise aerodynamically the cleaning efficiency of the

precipitator. Over all, it may be concluded that the methodology presented in this

paper can be successfully used for the design and optimisation of

industrial electrostatic precipitators.



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Future work in this field will comprise the introduction of the ionic

wind effects on the gas phase, as well as the interaction of theparticle charges with the electric field properties.



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acknowledgements: This presentation is fully adapted from the research work ofAgamemnon A.Varonos, John S.Anagnostopoulos, George

C.Bergeles on PREDICTION OF CLEANING EFFICIENCY OF

AN ELECTROSTATIC PRECIPITATOR published in Journal of

Electrostatics vol.55 (2002) 111133 .

I downloaded it from www.sciencedirect.com .



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prediction of cleaning efficiency of an electrostatic precipitator

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