Ecole Centrale de Lyon. Laboratoire de Mécanique des Fluides et d'acoustique

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Erica Conley
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through an obstacle array: numerical modelling

1 Ecole Centrale de Lyon Laboratoire de Mécanique des Fluides et d'acoustique Pollutant dispersion through an obstacle array: numerical modelling and experimental investigation Soulhac L., Rios I., Garbero V., Farges B., Salizzoni P., Scaccianoce L., Perkins R., F.-X. Cierco Work funded by CEA/DAM

1. Introduction Dispersion of hazardous material in urban area Context of

industrial facilities Transport of toxic materials Need of model tools in order

release Predict the dispersion for emergency response Evaluate precisely the

2 1. Introduction Dispersion of hazardous material in urban area Context of prevention from short accidental releases Accidental releases due to urban industrial facilities Transport of toxic materials Need of model tools in order to Simulate different scenarios in preparation and training for an eventual release Predict the dispersion for emergency response Evaluate precisely the impact of a release in postaccident analysis LMFA/ECL Harmo 11 - Cambridge - 04/07/2007 2

1. Introduction Some orders of magnitude 110 million km inhbts 10000 1 km inhbts 100 m inhbts Street scale High concentrations Few people No time to react District scale Still high concentrations

3 1. Introduction Some orders of magnitude 110 million km inhbts km inhbts 100 m inhbts Street scale High concentrations Few people No time to react District scale Still high concentrations Already many people concerned Agglomeration scale Low concentrations Very large number of people concerned Enough time for emergency services to react 100 s ~ 1 min s ~ 15 min s ~ 3h Instantaneous 100 m 1 km 10 km release million inhbts inhbts inhbts Concerned area (U ~ 1m/s) Population affected (density ~ inhbts/km²) Concentration values Capacity of reaction LMFA/ECL Harmo 11 - Cambridge - 04/07/ Time Focus on district scale

4 1. Introduction Some modelling issues at district scale Which processes/parameters control dispersion at district scale? How to model a district of thousands street segments? How to predict one or two days of dispersion in a few minutes on a PC? Find an alternative to CFD codes (Fluent, Mercure, ) Need to develop simplified models for operational applications Some approaches exist : MicroSwiftSpray, UDM, We will develop an alternative approach for very fast emergency response LMFA/ECL Harmo 11 - Cambridge - 04/07/2007 4

5 1. Introduction Plan of the presentation 1. Introduction 2. Wind tunnel experiments on urban district 3. SIRANERISK dispersion model 4. Preliminary comparison SIRANERISK / measurements 5. Conclusions and perspectives LMFA/ECL Harmo 11 - Cambridge - 04/07/2007 5

6 2. Wind tunnel experiments on urban district Experimental setting Study of turbulent dispersion from a continuous point source in an urban district Influence of wind direction Atmospheric wind tunnel of the Ecole Centrale de Lyon Dimensions of the test section: 14m x 2.5 m x 3.7m LMFA/ECL Harmo 11 - Cambridge - 04/07/2007 6

H Reality : H = 20 m L x = L y = 100 m S x = S y = 20 m Establishment of the urban

7 2. Wind tunnel experiments on urban district Experimental setting Ly Model : H = 50 mm L x = L y = 5H S x = S y = H Building geometry y z x x Lx Sx Model scale 1:400 Sy H Reality : H = 20 m L x = L y = 100 m S x = S y = 20 m Establishment of the urban boundary layer District studied 7 m LMFA/ECL Harmo 11 - Cambridge - 04/07/2007 7

2. Wind tunnel experiments on urban district Experimental setting Continuous release Point source located in an intersection 0 15 30 45 Concentration measurements with Flame

8 2. Wind tunnel experiments on urban district Experimental setting Continuous release Point source located in an intersection Concentration measurements with Flame Ionisation Detector: y Lateral profiles (y-direction) at different distance from the source Variation of the wind direction x X X LMFA/ECL Harmo 11 - Cambridge - 04/07/2007 8

2. Wind tunnel experiments on urban district Experimental results K 0 4 8 0 2 4 0 1 2 0 0.

9 2. Wind tunnel experiments on urban district Experimental results K Wind direction = 0 Wind tunnel concentration profiles (z = 0) y/h x/h RANS CFD calculations The plume is channelled by the main street Small transverse dispersion in perpendicular streets LMFA/ECL Harmo 11 - Cambridge - 04/07/2007 9

2. Wind tunnel experiments on urban district Experimental results K 0 0 6 4 0 1 0 0.

10 2. Wind tunnel experiments on urban district Experimental results K Wind direction = 15 Wind tunnel concentration profiles (z = 0) y/h x/h Wind direction Plume centreline The plume spreads more rapidly than in the 0 case The plume centreline is shifted due to a channelling mechanism Analogy with plume behaviour in this CFD simulation of the MUST experiment (Carissimo, 2001) LMFA/ECL Harmo 11 - Cambridge - 04/07/

11 2. Wind tunnel experiments on urban district Experimental results K Wind direction = 30 Wind tunnel concentration profiles (z = 0) y/h Wind direction 0 Plume centreline x/h The plume spreads even more rapidly The steps in the concentration profiles correspond to the presence of the streets The concentration is almost homogeneous in each street LMFA/ECL Harmo 11 - Cambridge - 04/07/

12 y/h K 2. Wind tunnel experiments on urban district Experimental results Wind direction = 45 Wind tunnel concentration profiles (z = 0) x/h The plume centreline deflection disappears in the symmetric case The concentration is almost constant in each street but varies from one street to the other LMFA/ECL Harmo 11 - Cambridge - 04/07/

13 y/h K 2. Wind tunnel experiments on urban district Experimental results Wind direction = 45 Wind tunnel concentration profiles (z = 0) x/h RANS CFD calculations Importance of the exchange mechanism at the intersections LMFA/ECL Harmo 11 - Cambridge - 04/07/

control the dispersion in a district : 1. Exchanges at each intersection 2.

14 2. Wind tunnel experiments on urban district Experimental results Wind direction = 45 Importance of the transport over the roof level RANS CFD calculations (roof level z = H) Two mechanisms control the dispersion in a district : 1. Exchanges at each intersection 2. Exchange with the external flow and dispersion over the roof level LMFA/ECL Harmo 11 - Cambridge - 04/07/

SIRANE is a steady state model SIRANERISK is an unsteady model SIRANE model Agglomeration of

15 3. SIRANERISK dispersion model Introduction SIRANERISK is an evolution of the SIRANE model, used for air quality modelling in urban area (application on Lyon, Paris, Grenoble, Torino, Milano, ) SIRANE is a steady state model SIRANERISK is an unsteady model SIRANE model Agglomeration of Lyon 2003 Example of hourly NO X concentrations LMFA/ECL Harmo 11 - Cambridge - 04/07/

3. SIRANERISK dispersion model Geometrical description of a district Urban

model Scale of the detail on buildings Scale of the relief Taken into

Scale of buildings Resolved explicitly by a street network approach Taken

16 3. SIRANERISK dispersion model Geometrical description of a district Urban geometry is complex at different scales need to simplify in an operational model Scale of the detail on buildings Scale of the relief Taken into account by a user-provided external wind field coupled with a puff model Scale of buildings Resolved explicitly by a street network approach Taken into account by a Roughness length LMFA/ECL Harmo 11 - Cambridge - 04/07/

Pollutant budget in each street Exchange

17 3. SIRANERISK dispersion model Geometrical description of a district Representation of urban canopy Simplification of building geometry Pollutant budget in each street Exchange at intersections LMFA/ECL Harmo 11 - Cambridge - 04/07/

18 3. SIRANERISK dispersion model Concentration model in each street Analytical model for the average velocity in each street (Soulhac et al., 2007, submitted to Boundary Layer Meteorology) Budget of pollutant mass in the street ( ) dhwl.c street dt Turbulent exchange at the interface σ WL Q = C C 2π ( ) w H,turb street street,ext Emission of a new rectangular puff over the street = QS + QI,in + Qpart,H QH,turb + QI,out + Qpart,ground + Qwet depos In fluxes Q wet depos. Q part,ground Q I,in Q part,h Out fluxes Q H,turb Q S Q I,out LMFA/ECL Harmo 11 - Cambridge - 04/07/

3. SIRANERISK dispersion model Exchange model for an intersection 15 30 45 RANS CFD calculations Calculation of exchange fluxes as a function of wind direction : P i,j (θ) Averaging

19 3. SIRANERISK dispersion model Exchange model for an intersection RANS CFD calculations Calculation of exchange fluxes as a function of wind direction : P i,j (θ) Averaging fluxes over wind direction fluctuations : with f ( ) ( ) ( ) P θ = f θ θ P θ dθ i,j 0 0 i,j ( ) θ θ exp σ π 0 θ θ 0 = 2 2 θ σθ LMFA/ECL Harmo 11 - Cambridge - 04/07/

20 3. SIRANERISK dispersion model Puff dispersion model over the roof level Each vertical flux of pollutant is modelled by a source of puffs Each puff is advected by the wind field Each puff spreads to model turbulent dispersion LMFA/ECL Harmo 11 - Cambridge - 04/07/

level The model seams to represent the main features of the concentration field Need

21 4. Preliminary comparison SIRANERISK / measur. Wind direction = 30 Ground level Concentration profiles Wind tunnel SIRANERISK Roof level The model seams to represent the main features of the concentration field Need to parameterize the different exchange coefficients to compare more precisely LMFA/ECL Harmo 11 - Cambridge - 04/07/

22 4. Preliminary comparison SIRANERISK / measur. Wind direction = 15 Ground level Concentration profiles Wind tunnel SIRANERISK Roof level LMFA/ECL Harmo 11 - Cambridge - 04/07/

SIRANERISK Roof level Difficulty to describe the lateral diffusion in

23 4. Preliminary comparison SIRANERISK / measur. Wind direction = 0 Ground level Concentration profiles Wind tunnel SIRANERISK Roof level Difficulty to describe the lateral diffusion in this case Pietro Salizzoni's presentation LMFA/ECL Harmo 11 - Cambridge - 04/07/

24 5. Conclusions and perspectives Wind tunnel experimental study Identification of main dispersion mechanisms Development of an unsteady puff-canopy dispersion model, SIRANERISK, for operational purposes Need to validate SIRANERISK model A preliminary comparison between model and experiments shows that SIRANERISK describes the main characteristics of the plume Perspectives Need to parameterize the different exchange coefficients Validation on unsteady dispersion cases LMFA/ECL Harmo 11 - Cambridge - 04/07/

5.39 AN EVALUATION OF THE URBAN DISPERSION MODELS SIRANE AND ADMS URBAN, USING FIELD DATA FROM LYON.

5.39 AN EVALUATION OF THE URBAN DISPERSION MODELS SIRANE AND ADMS URBAN, USING FIELD DATA FROM LYON. Soulhac, L. 1., Pradelle, F. 2 & Perkins, R.J. 1 1 Laboratoire de Mécanique des Fluides et d Acoustique,