star global conference areva - dispersion – march 17-19th...

STAR Global conference AREVA - dispersion – March 17-19th 2014 - p.1RESTRICTED AREVA

The information in this document is AREVA property and is intended solely for the addressees.Reproduction and distribution are prohibited. Thank you

Engineering & Projects Organization

RESTRICTED AREVAThe information in this document is AREVA property and is intended solely for the addressees.

Reproduction and distribution are prohibited. Thank you

B. Farges, P. Brocheny, C. Thelier, N. GoreaudAREVA NP

CFD for atmospheric dispersion prediction in close range



Outline of the presentation

1. Context

2. Methodology setup and validation

2a. Hydraulics

2b. Dispersion

3. Industrial application

4. Conclusion and outlook



1. Context (1/2)

Some accidental or incidental scenarios can lead an i ndustrial site to release gases or particules in the atmosphere

Depending on the concentration, of the weather condit ions and of the quantity, it will form a plume of a give n size / concentration

Utilities must demonstrate that these scenarios are p roperly handled and that the consequences are acceptable� For the public outside the facility fences => long range

� More and more : for the workers on site => close ra nge

Some tools exist on the market dedicated to these is sues, but� No or very limited capacity for detailed representa tion of a given

industrial site (buildings, complex obstacles…)



1. Context (2/2)

AREVA has a long history in using CFD

� Variety of problems� Trained engineers� Computation power available� Validation file on numerous

applications� CFD used as a support to safety

analyses

For this reason : choice to use CFD for the modelling of near-field atmospheric dispersion

� Detailed representation of site geometry (buildings…)

� Recirculations, turbulence, buoyancy,… taken into account



2. Methodology setup Approach

Step by step : growing complexity

a. Hydraulics only :• On an empty domain• With a single building• Benchmark against litterature

b. Addition of dispersion :• On an empty domain first• Validation against the Prairie Grass experiment

c. Addition of reacting flows (not part of presentation t oday) :• Possibilities to account for chemical reactions / power decay during dispersion

Illustration on the sizing of protection on an AREVA facility



2.a. Methodology setup Hydraulics on empty domain

Assumptions� Surface boundary layer� Perfect gas� Stationnary wind profile : Assumtion that meteo variation are slow compared to

dispersion transient

Computation assumptions� In accordance with best practicesIdentified through a litterature survey� Large domain dimensions in order to prevent side effects .� Turbulence model : standard (was found to be the best compromise)

� Dispersion in neutral conditions (classical

choice : Richards & Hoxey, Hargreaves, Vendel)B.Blocken et al, 2007

ε−k

Equations of velocity , temperature and turbulent qua ntities profile relative to a neutral atmosphere prescribe at inlet.



Profiles prescribed at domain inlet (from similitude theory from Monin-Obukhov)

Acceptable situation on empty domain

2.a. Methodology setup Hydraulics on empty domain

Turbulent kinetic energy

Turbulent dissipation

Velocity

Temperature

Atmosphéric profiles

)(

*

0

3

zz

u

+=

κε

µC

uk

²*=

)ln(*

0

0

z

zzuu

+=

κ

( ) zTzT ⋅−= 0098,00

Profiles maintained

Local anomalytypical for standard CFD codes



Behaviour of flow around an obstacle (square building)� Presence of turbulent structures

� Classical k-epsilon limitations (consistent with litt erature) :

Results are consistent with the state of the art and judged acceptable

Slightsurestimation of turbulent kinetic

energy upstream

Slightunderestimation of recirculation zone

Slightsurestimation of the recirculation zone downstream

2.a. Methodology setup Hydraulics with a single building

10 m



Reference experiment : Projet Prairie Grass (1956)� SO2 release in an open plain

� 68 tests about 10 of them in neutral conditions• Three configurations chosen to validate the methodology

Two means to calibrate the results :� Calibration of a parameter : S ct => fast, provides order of magnitudes at the plume

centerline

� Statistical correction => more complex, more reliabl e

2.b. Methodology setup Dispersion

Vervecken et al. 2013



Simulation of the Prairie Grass experiment� Calibrating Sct enables to get the right concentration in the axis of the

plume

But the shape of the plume is incorrect : overestimation in the axis of the plume and underestimation of its width . (Known phenomenon : Vervecken, Riddle )

Acceptable for an order of magnitude determination.

2.b. Methodology setup Dispersion



Simulation of the Prairie Grass experiment� Accounting of wind oscillations (litterature : Verveck en)

• Statistical fluctuations around the average wind direction : a statistical fluctuation with standard deviation σ

αhas been measured :

• Turbulence modelling already accounts for some deviation σm� definition of an additive deviation σe to reach σ

α

• Performance of several computations for several angles• Gaussian ponderation of the results

2.b. Mise en place de la mod élisation Dispersion

Fluctuations de la direction du vent (essai n°57)

0

0,02

0,04

0,06

58 90 122Angle en degré

Den

sité

de

prob

abili

té



Simulation of Prairie Grass experiment� Results with second method

• Shape of the plume and concentration of the plume are better predicted• Drawback : several computations are necessary

Correction statistique sur les capteurs à 50 m

0

100

200

300

400

500

600

60 70 80 90 100 110 120

Angle en degré

conc

entr

atio

n de

SO

2 en

mg/

m3

Mesures test 57

Simulation 57 -Sct0,7

Simulation 57 -Sct 0,7 - correctionstatistique

2.b. Mise en place de la mod élisation Dispersion




Milling facility

Industrial problem� Ammonia stored on site under

pressure

� If a leakage happens, need to ensureacceptable doses are not overcome

First step� CAD repair inside STAR-CCM+ from

site data

� Large domain generation

� Meshing• Less than 5 million cells for the total

volume• Enabling a fast and smooth transient run




Results� Instantaneous velocity profiles on

site for a given wind direction• First indication of zones of potential

hazard

� Instantaneous concentration profiles everywhere on the plant

• Information that enables to quantify the dilution of the release and the size of the plume

� Derived into the quantification of the zones where reglementary thresholdcan be overcome

• Used for demonstration to regulators and design optimisation



4. Conclusion and outlook

AREVA has developped a method to assess the consequences of atmospheric dispersion in close range� Based on its expertise on CFD

� For its own purpose

This method is operational and proved to provide usefulresults on an industrial case

Beyond safety demonstration, this method has a lot of potential :� Site layout verification / optimisation

� Strong wind sizing

� Wind power generation

� …

star global conference areva - dispersion – march 17-19th...

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