Analysis and Optimization of Spray Tower in WFGD - … and Optimization of Spray Tower in WFGD F. Li, ... Wet Sulfuric Acid process Spray-dry ... balance of effective pollutant removal

Analysis and Optimization of Spray Tower in WFGD

F. Li, K. J. Brown, W. Kalata, R. J. Schick

Spraying Systems Company

May 23rd, 2014

Ansys Convergence 2014 Regional Conference of Chicago

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Introduction

Nature Human • Sulfur dioxide (SO2) is one of the major

pollutants in the atmosphere.

• Beginning of 1980s, emission of SO2

caused by human activities achieved 65 Mt/year (~22% from US distribution).

• SO2 impact on human: smog and soot, etc.

• Acid rain is well known for its health hazards, which resulted from SO2 dissolving with precipitation droplets.

• FGD is consist of several technologies to remove SO2 from exhaust flue gases or other emitting processes.

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Flue Gas Desulfurization (FGD)

Wet Scrubbing

Wet Sulfuric Acid process

Spray-dry Scrubbing

Dry Sorbent Injection System

SNOx FGD

FGD is a set of technologies used to remove sulfur dioxide from exhaust flue gases.

• Lime/limestone

• Dual Alkali/MgO

• Mitsubishi/Bischoff

• Limestone Forced Oxidation

• Trona

• Sodium

(Bi)carbonate

• Hydrated Lime

• Lime

• Trona

• Sodium

Carbonate

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Spray Tower Evaluation

• Maximum reduction and minimal scaling – Control of droplet

• System implementation cost and pollutant reduction – Nozzle characteristics and placement

• Common: hydraulic injectors – Full cone and hollow cone

• Nozzles produce a range of drops, which sizes varies with:

– Liquid properties – Nozzle type – Capacity – Pressure – Spray angle

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• World Leader in Spray Technology – Privately owned (Est. 1937) – Headquarters in Wheaton, IL

• Products

– Spray nozzles, related systems and accessories – Over 120,000 standard and 180,000 non-standard engineered products

• Access to Market

– Global/Regional engineering and manufacturing – 85 local sales engineering offices around the world

• Value added

– Recognized global brand for spray technologies – Quality, service, support, engineered solutions – Serve 50 major industrial markets

Spraying Systems Co.

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Spray Characterization Technology

• Phase Doppler Interferometry (PDI)

- Artium 2D-MD

• Flux Measurement Device

- drop size & velocity

• 4.0 – 1638 µm

• PDI/PDPA

• LSI

- flow rate, drop size, spray angle, spray coverage and various quality control tests

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Technology Combination

• Computational Fluid Dynamics (CFD) is the science of predicting

– Fluid flow

– Heat transfer

– Mass transfer

– Chemical reactions

– And related phenomena

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Spraying Systems Co. Nozzles

• WFGD requires:

Extensive and precise performance, trouble-free operation and long service life.

• Customers satisfication:

-WhirlJet® nozzles (hollow cone pattern)

-FullJet® nozzles (full cone pattern)

-SpiralJet® nozzles

Nozzle Qt. Pressure Flow Rate Spray Angle Exit Velocity Dv0.50

ID # psi gpm ° m/s μm

1-1/2CX-25 10 12.2 33 74 7.2 1188

1-1/4CRC20-45 10 19.1 33 47 8.2 1155

1-1/4CRC20-45 12 13.2 27.5 47 6.8 1218

1-1/2CX-16 16 11.6 20.625 75 7.1 1150

1-1/4CX-12 20 13.2 16.5 70 7.5 1122 8

CFD Set-up • Major mechanism - discrete phase model - volumetric chemistry - chemical reaction model

• Absorber - Inlet gas flow ~5,200,000 lb/hr - Inlet SO2 ~35, 000lb/hr - Whole spray levels designed by Spraying Systems Co.

• Physical design - Babcock & Wilcox Company

- Standard industrial size limestone spray scrubber

- Limestone forced oxidation (LSFO) system

Mist eliminator

Flow straightener

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© 2014 ANSYS, Inc.

Reaction Mechanisms Core Mechanism: wet combusting particle surface reaction chemistry model

In this case: particle species j (s) + gas phase species n products

CaCO3 + SO2 + 0.5O2 = CaSO4 + CO2

The particle reaction rate, R (kg/m2·s), can be expressed as

R = D0 (Cg - Cs) = Rc (Cs)N

where,

D0 =bulk diffusion coefficient (m/s)

Cg =mean reacting gas species concentration

in the bulk (kg/m3)

Cs =mean reacting gas species concentration

at the particle surface (kg/m3)

Rc =chemical reaction rate coefficient

N =apparent reaction order (dimensionless)

Rate of reaction is given as

,

where,

=rate of particle surface species depletion (kg/s)

Ap =particle surface area (m2)

Yj =mass fraction of surface species j in the particle

ƞr =effectiveness factor (dimensionless)

=rate of particle surface species reaction per unit area

(kg/m2·s)

Pn =bulk partial pressure of the gas phase species (Pa)

D0,r = diffusion rate coefficient for reaction r

= kinetic rate of reaction r

Nr = apparent order of reaction r 10

© 2014 ANSYS, Inc.

CFD Results

• Part I Nozzle Selection • Part II Optimization

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10CRC @ L1 10CX @ L1 10CX @ L2 10CRC @ L2

Nozzle Qty. – 10 Spray Tower

Lowest Removal Highest Removal

SO2 mass fraction

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10CRC @ L1 10CX @ L1 10CX @ L2 10CRC @ L2

Droplet Diameter (μm)

Droplet Diameter (μm)

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Nozzle Qty. – 10 Particle Tracking

12CRC @ L3 12CRC @ L4

slightly higher

Displayed maximum reaction rate was 5×10-5 kgmol/(m3•s).

12CRC @ L3 12CRC @ L4

SO2 mass fraction

Velocity (m/s)

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Nozzle Qty. – 12 Gas

12CRC @ L3 12CRC @ L4 12CRC @ L3 12CRC @ L4

Droplet Diameter (μm)

Spray Concentration (kg/m3)

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Nozzle Qty. – 12 Injection

16CX @ L5 16CX @ L6

16CX @ L5 16CX @ L6

Higher

Spray Concentration (kg/m3)

SO2 mass fraction

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Nozzle Qty. – 16 Spray Tower

Gas path lines colored by its temperature displayed on the contour of particle diameter (refer to left) at the middle plane.

16CX @ L5 16CX @ L6

16CX @ L5 16CX @ L6

Droplet Diameter (μm)

Temperature (K)

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Nozzle Qty. – 16 Drop/Gas Tracking

• Target: -Select the better performance nozzle and location for multiple nozzles

• Evaluation of designs: -SO2 reduction capability -wall contact amount -slurry consumption

• CRC series nozzle -bigger passage-exits design -narrow spray angle -capacity limitation for desired

• 10/12-nozzle performance trends differ than 16-nozzle

Part I - Conclusion

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© 2014 ANSYS, Inc.

CFD Results

• Part I Nozzle Selection • Part II Optimization

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© 2014 ANSYS, Inc.

Drop Size Distribution

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Rosin-Rammler Distribution Function

• Widely accepted function to model the distribution of droplet sized in spray atomizers.

MMD (DV0.50): drop diameter such that 50% of total volume is in drops of smaller diameter (obtained

experimentally)

D: diameter

Q: fraction of volume contained in drops of diameter less than D

X: constant (generally computed from known value of MMD)

q (N): constant, spread parameter (based on spray type.)

Dmin - DV0.01: drop diameter such that 1% of total volume is in drops of smaller diameter

Dmax - DV0.99: drop diameter such that 99% of total volume is in drops of smaller diameter

q

X

D

eQ

1q

MMDX

/1)693.0(

q=2.5

q=3.0

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Optimization Test – Gas Profile

Velocity (m/s)

10n 12n 16n 20n

SO2 mass fraction

10n – 91.1% 12n – 90.3% 16n – 94.9% 20n – 95.1% 22

Optimization Test – SO2 Removal

10n – 89.9% 12n – 88.7% 16n – 94.5% 20n – 94.8%

Optimization Test (q=2.5) – Injection

10n 12n 16n 20n

Spray Concentration (kg/m3)

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Droplet Diameter (μm)

Optimization Test (q=2.5) – Droplets

10n 12n 16n 20n

Spray Concentration (kg/m3)

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Optimization Test (q=3.0) – Injection

10n 12n 16n 20n

26 10n 12n 16n 20n

Droplet Diameter (μm)

Optimization Test (q=3.0) – Droplets

Animation of Injection

16cx q=2.5

16cx q=3.0

20cx q=2.5

20cx q=3.0 27

Conclusion

Results matched with previous work: • Greater efficacy of pollutant removal and reduced wall contact:

– Smaller droplet distribution – More uniform droplet distribution. – Location of injections relative to gas flow.

Further results learned from this work: • Velocity behavior exhibits less oscillation and recirculation than pilot-plant

study • Effective limestone usage was confirmed in the simulation, also matched

with industrial measurements. • Optimal setup with 16-nozzle.

– Smaller flow per nozzle = smaller drop size – More nozzles = more uniform distribution – Diminishing returns beyond 16 nozzles

• Increase in the RR spread parameter resulted in better SO2 reduction.

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Summary

• This work demonstrates the capability of CFD simulation on the applications of WFGD spray tower.

• The results indicate similar trends to previous work.

• The key of this spray system optimization is finding the balance of effective pollutant removal and slurry supply, through control of spray characteristics.

• Spray behavior and its interaction with gas is critical to solve this pollution issue.

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Discussion and Suggestions Discussion

• Simplified layout was applied in the simulation to save simulation time, instead of using the original design of flow straightener and mist collector.

• This work is produced only for the specific absorber introduced above in the beginning. Same result will not be guaranteed for other absorbers even same nozzles were applied.

Suggestion

• Contact Spraying Systems Co. for exact spraying injector selections based on your system conditions. Applications will be evaluated by spray experts with our spray characterization knowledge and technology.

• We can help to get the optimal spraying system for individual needs.

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