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©SNERDI 2016. All Rights Reserved. A CFD Model Based Research On Wet Deposition of Large Scale Natural Draft Cooling Tower Shanghai Nuclear Engineering Research & Design Institute www.snerdi.com.cn Wenjie Bao Shanghai Nuclear Engineering Research & Design Institute ShanghaiChina
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©SNERDI 2016. All Rights Reserved.

A CFD Model Based Research On Wet Deposition of Large Scale Natural Draft Cooling Tower

Shanghai Nuclear Engineering Research & Design Institute

www.snerdi.com.cn

Wenjie Bao

Shanghai Nuclear Engineering Research & Design Institute

Shanghai,China

©SNERDI 2016. All Rights Reserved.

1.Background 2.Methodology 3.Model Validation 4.Case Study 5.Conclusion

©SNERDI 2016. All Rights Reserved.

1.Background 2.Methodology 3.Model Validation 4.Case Study 5.Conclusion

©SNERDI 2016. All Rights Reserved.

1. Background

Nuclear power plant construction plan

0 10 20 30 40 50 60 70 80 90 100

UnitedStatesOfAmerica

France

Japan

China

Russia

SouthKorea

Numberofreactors

NuclearPowerPlantStatusinTypicalCountries

UnderConstrucKon OperaKng

©SNERDI 2016. All Rights Reserved.

1. Background

EIA for Inland nuclear power plants

MountainousArea

CoolingTowerImpact

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1. Background

Disadvantages of tradition methods

Methods Disadvantages

Gaussian model Not suggest for mountainous area

Wind tunnel experiments High demand for money and time

SF6 field experiments

CFD model √

©SNERDI 2016. All Rights Reserved.

1.Background 2.Methodology 3.Model Validation 4.Case Study 5.Conclusion

©SNERDI 2016. All Rights Reserved.

2. Methodology

CFD Model (Computational Fluid Dynamics)

Aerodynamic

shape design

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2. Methodology

CFD Model (Computational Fluid Dynamics)

Smoke plume simulation

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2. Methodology

CFD Model (Computational Fluid Dynamics)

Model: Star CCM+

Validation Data: Chalk Point Plant experiment

Case study: Inland NPP sites in China (Planned)

©SNERDI 2016. All Rights Reserved.

2. Methodology

Chalk Point Power Plant

CoolingTower

Plant Overview

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2. Methodology

Chalk Point Power Plant

Sampling Points Distribution

1km

0.5km

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2. Methodology

3D model parameter

Chalk Point 3D model

Domainlength:2000mwidth:1000mheight:500m

Coolingtowerheight:124m

baseradius:40moutsetradius:27.4m

©SNERDI 2016. All Rights Reserved.

2. Methodology

3D model parameter

Inlet wind speed profile 6781.03523.0 zv ⋅=

©SNERDI 2016. All Rights Reserved.

2. Methodology

3D model parameter

Inlet wind speed profile

©SNERDI 2016. All Rights Reserved.

2. Methodology

3D model set up

Chalk Point grid model

PolyhedralmeshGridsizeofcoolingtower:4mGridsizeofotherpart:50~100mTotalnumberofgrid:600,000

©SNERDI 2016. All Rights Reserved.

1.Background 2.Methodology 3.Model Validation 4.Case Study 5.Conclusion

©SNERDI 2016. All Rights Reserved.

3. Model Validation

Cooling tower plume lift

Cooling tower plume diffusion

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3. Model Validation

Cooling tower plume lift

Plume lift height comparison

©SNERDI 2016. All Rights Reserved.

3. Model Validation

Cooling tower wet deposition

Cooling tower wet deposition distribution

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3. Model Validation

Cooling tower wet deposition

Wet deposition data comparison

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1.Background 2.Methodology 3.Model Validation 4.Case Study 5.Conclusion

©SNERDI 2016. All Rights Reserved.

4. Case study

Inland Nuclear Power Plant in China

3D model of NPP site

©SNERDI 2016. All Rights Reserved.

4. Case study

Inland Nuclear Power Plant in China

3D grid of NPP site

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4. Case study

Cooling tower design parameter

Parameters Value

Basediameter 168.66m

Height 215m

Outletdiameter 102.70m

Throatdiameter 99.0m

Twotowersdistance 110m

Eliminatorefficiency 95% DriHvelocity 4.35m/s

DriHtemperature 30.33℃

Plumemassrate 0.455kg/s

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4. Case study

Model boundary conditions

Parameters Value

Windspeedat70m 5.2m/s Surfaceroughness 0.3m

Turbulenceintensity H<100m,0.1;H≥100m,0.05 Airtemperature 16.5℃

pZ

uu ⎟⎟⎠

⎞⎜⎜⎝

⎛×=

0.7070Inlet wind profile expression

©SNERDI 2016. All Rights Reserved.

4. Case study

Calculation result

Downwind centerline wet deposition distribution

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4. Case study

Calculation result

Cooling tower plume diffusion pattern

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1.Background 2.Methodology 3.Model Validation 4.Case Study 5.Conclusion

©SNERDI 2016. All Rights Reserved.

5. Conclusion

l  CFD could simulate the process of cooling tower plum dispersion and

deposition well.

l  When field data is not available, CFD could be a powerful tool in

cooling tower EIA.

l  In case study, this method could reflect the blocking effect of cooling

tower, thus a more reasonable result could be provided.

©SNERDI 2016. All Rights Reserved.

5. Conclusion

l  In further studies, it is necessary to work on boundary conditions

optimization and reasonable meteorological classification, in order

that CFD model could run under multiple meteorological conditions.

l  Plume shadowing of cooling tower drift is decided by season, sun

angel and location, which are not included in CFD model. These

could be important research directions in the future.

©SNERDI 2016. All Rights Reserved.

THANK YOU ! ขอบคุณ!

Shanghai Nuclear Engineering Research & Design Institute

www.snerdi.com.cn

Wenjie Bao Email:[email protected]


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