The design of electrostatic precipitators

by use of physical models

G. Bacchiega - IRS S.r.l. – www.irsweb.itR. Sala -I. Gallimberti -P. Tronville - F. Zatti

2

Objective of the paper

• To show how modeling tools can be employed to design modern Electrostatic Precipitators (ESP) for industrial applications

• To demonstrate the power of modern CFD tools to tackle turbulent gas flow, electrical field and discharge phenomena, particle charging and transport, particle collection and re-entrainment

• Considerations:– It is necessary a multidisciplinary approach (five authors!)– The presenter's area of expertise in this case is limited to

Computational Fluid Dynamics (CFD)

Design procedure

• Draft design based on: general specification analysis, expected exhaust particle concentration, site specific physical constraints, previous similar projects

• Simulation and optimisation of the gas flow in the ESP body (adoption of smoothing profiles at the inlet and exit)

• Simulation of the particle capture process and verification of the draft design efficiency (to make the necessary modifications and comply with specifications)

• Detailed engineering design and construction drawings, should include as a final result the mechanical specifications, cost evaluation and construction schedule

Modeling approach

• Time-dependent simulation of the main physical phenomena that take place inside the electrostatic precipitator

• Self-consistent physical and mathematical models for each phenomenon

• Modular structure of the models

Data structure

Gas Flow: 3D Fluid-Dynamic

Gas Flow: 2D Fluid-Dynamic

Sect. 1

Laplacian Field

Electric Field

time loop

Back Corona Glow Corona Streamer Corona Breakdown

Electric Field

Sect. 2

Ion Migration

Particle Charging

Particle Migration

Space Charge Distribution

Sect. 3

Particle Collection

Rapping Reentrainment

Process Efficiency

Sect. 4

Fluid-Dynamic simulation

Data structure

Gas Flow: 3D Fluid-Dynamic

Gas Flow: 2D Fluid-Dynamic

Laplacian Field

Electric Field

time loop

Back Corona Glow Corona Streamer Corona Breakdown

Electric Field

Ion Migration

Particle Charging

Particle Migration

Space Charge Distribution

Particle Collection

Rapping Reentrainment

Process Efficiency

Sect. 1

Sect. 2

Sect. 3

Sect. 4

3-D Fluid-DynamicFluid-dynamics

conditions of gas flow: stationary conditions of

3-D gas flow in the precipitator

2-D Fluid-DynamicFluid-dynamics

conditions of gas flow: 2-D gas flow in a single

cell

7

Calculation of flow field• Mass, momentum and energy conservation• Isotropic turbulence by k- model of the first order (kinetic

energy k and rate of turbulent dissipation )

ru

xi

i

0

u

t

u u

xpx x

Si j i

j i

ij

j

ui

k

t

u k

x xkx

Gi

i i

t

k i

t

t

u

x x xckG c

ki

i i

t

i

t

1 2

2

8

FLUE GAS OPERATING CONDITIONS Gas flow (on wet) Nm3/h 124000Operating temperature °C 402Operating Pressure kPa 98.7O2 Concentration % vol 11.25

Relative humidity % vol 8.7INLET PARTICLE CHARACTERISTICS Particle concentration (dry at 8% O2) mg/Nm3 4707

Furnace particles (average diameter 0.25 micron) % in mass 4.2Reaction particles (average diameter 6.0 micron) % in mass 95.8DRAFT ESP CHARACTERISTICSN° of fields 3N° of gas passages (d = 400 mm) 19N° of plates per field (h = 13.35 m, l = 0.5 m) 8N° of emitting electrodes per plate (RDE type) 1

Operating parameters - characteristics

9

3-D mesh of the ESP

10

Calculated velocity contours (central section)

11

Smoothing velocity profile

See white lines and dashes (perforated plates)

12

Fluid dynamic optimization

Perforated plates with variable permeability

Electric field section

Data structure

Gas Flow: 3D Fluid-Dynamic

Gas Flow: 2D Fluid-Dynamic

Laplacian Field

Electric Field

time loop

Back Corona Glow Corona Streamer Corona Breakdown

Electric Field

Ion Migration

Particle Charging

Particle Migration

Space Charge Distribution

Particle Collection

Rapping Reentrainment

Process Efficiency

Sect. 1

Sect. 2

Sect. 3

Sect. 4

Laplacian Fieldelectrostatic conditions defined by geometry

Electric Field

Time dependent electrostatic conditions defined by charge in the

space

14

Modeling the electrostatic fieldDefines characteristics of electric

dischargesDefines forces over the particles

Electrostatic field

Poisson equations

2

0

V

E V

Orthogonal embedded grid

Calculation domain

Calculation methodPotential and field: iterative FDM algorithm (Finite Differences Method) with convergence verification

15

Laplace potential and electric field

Characteristics:

• Refined mesh near high voltage-high divergence electrodes

• Electric field distribution proportional to a reference one

• The solution over the domain is calculated only once

0

0.5

1

1.5

2

2.5

3

0 5 10 15l [cm]

V(l

)/V

0

V(l)/V0

V(l)

70

35

0

V(l

) [k

V]

16

Potential and electric field

• Lower intensity comparing with laplacian field (~20%)

• Mesh with low refinement

0.0 kV

7.5 kV

6.0 kV

4.5 kV

9.0 kV

4.5 kV7.0 kV7.5 kV

3.0 kV

1.5 kV

0.0 kV

0

10

20

30

40

50

60

70

0 5 10 15l [cm]

V [

kV]

V=Vlapl

V=Vcar

17

Electric field contour in a collection cell

18

Voltage-Current characteristic

0

0,1

0,2

0,3

0,4

0,5

0,6

0,7

0,8

0,9

1

0 20 40 60 80Voltage (kV)

Curr

ent density

(m

A/m

2)

T= 20°C (Meas.)

T= 20°C (Sim.)

T= 400°C (Sim.)

Discharging characterization

Data structure

Gas Flow: 3D Fluid-Dynamic

Gas Flow: 2D Fluid-Dynamic

Laplacian Field

Electric Field

time loop

Back Corona Glow Corona Streamer Corona Breakdown

Electric Field

Ion Migration

Particle Charging

Particle Migration

Space Charge Distribution

Particle Collection

Rapping Reentrainment

Process Efficiency

Sect. 1

Sect. 2

Sect. 3

Sect. 4

Glow coronaStationary corona

discharge

Back coronaMicro-discharge in the dust

layer at the plates

20

Model of Glow Corona

Ionisationregion

Transportregion

V= 0

Vdc= V

Electrons emission by positive ions collisions

ne R ve R in R v R

Molecular ionization and attachment

neve neve

Ions drift by electric field force

ion ionE

iont ion

vion

Ddiff ion

0

21

Glow Corona: calculation procedure

Electric field distribution

Ions current injection

Space charge distribution

Time dependent solution of transport equation

Ions transport

22

Back Corona: physical description

Micro-discharge in the dust layer at the plates

• Global electric conditions (electric field in the dust)• Characteristics of the dust (particle size distribution, resistivity,

dielectric constant)

equiflux equiflux

0 1 plate

j

equipotentials

Charging section

Data structure

Gas Flow: 3D Fluid-Dynamic

Gas Flow: 2D Fluid-Dynamic

Laplacian Field

Electric Field

time loop

Back Corona Glow Corona Streamer Corona Breakdown

Electric Field

Ion Migration

Particle Charging

Particle Migration

Space Charge Distribution

Particle Collection

Rapping Reentrainment

Process Efficiency

Sect. 1

Sect. 2

Sect. 3

Sect. 4

Particle charging Mechanism of particle

charging

24

Model of particle chargingBy means of the field:

The particle modifies locally the electric field

E ERr

qrtot

r

r

0

3

30

2112 4

cos

Ions drift and attach to the particles

dqdt

eq

qq

ionion s

s

4

10

2

The process ends when the electric field created by the particle is greater then the ambient field

0

1220

20q R Es

r

r

25

By diffusion:

dqdt

a e v TqeRk T

qqion

b s

2

041exp

Thermal agitation of ions produce collisions with the particles

Model of particle charging

Particle migration section

Ionic migrationIonic migration process

Particle migrationParticle migration

process

Space charge distribution

Time dependent variation of ionic and particles distribution

Data structure

Gas Flow: 3D Fluid-Dynamic

Gas Flow: 2D Fluid-Dynamic

Laplacian Field

Electric Field

time loop

Back Corona Glow Corona Streamer Corona Breakdown

Electric Field

Ion Migration

Particle Charging

Particle Migration

Space Charge Distribution

Particle Collection

Rapping Reentrainment

Process Efficiency

Sect. 1

Sect. 2

Sect. 3

Sect. 4

27

Particles migration section

Fluid transport: particles are dragged by the gas in the duct

Velocity vp depends not only on forces, but also on inertia

Electric transport: charged particles are drifted by electric field to the plates

F qE

F R v vv f p 6

v vqmE v v

qmE ef f

t

0

Global instantaneous velocity

28

Efficiency %

0.00%

10.00%

20.00%

30.00%

40.00%

50.00%

60.00%

70.00%

80.00%

90.00%

100.00%

0 5 10 15 20 25 30

Plates

%

Cl.1

Cl.2

Cl.3

Cl.4

Cl.5

Cl.6

Cl.7

Cl.8

Cl.9

Tot

Rend.tot. 98.95%

Particles collection section

Data structure

Gas Flow: 3D Fluid-Dynamic

Gas Flow: 2D Fluid-Dynamic

Laplacian Field

Electric Field

time loop

Back Corona Glow Corona Streamer Corona Breakdown

Electric Field

Ion Migration

Particle Charging

Particle Migration

Space Charge Distribution

Particle Collection

Rapping Reentrainment

Process Efficiency

Sect. 1

Sect. 2

Sect. 3

Sect. 4

Rapping-Reentrainment

Conditions of particles collection:

stationary simulation of dust over the plates

Collection and re-entrainment

Time-dependent evaluation of particles layer at plates

Objectives:

• Evaluation of particles re-entering in the main stream (re-entrainment)

• Evaluation of electric behavior (back-corona)• Definition of mechanical behavior (rapping,

collecting efficiency)

Collection and re-entrainment

Min

Mout-ree

Mout-

hop

Mass balance of re-entrained, collected and

fallen particles

32

Inlet particle size distribution

Percentage by mass

33

Particle size distribution (inlet and exit)

Mechanical layout

Conclusions

• It is possible to optimize the ESP characteristics by using engineering calculations and thus avoiding empirical correlations

• The balance between cost and performance can be carefully evaluated during the design phase

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