Catrinel Turcanu, Johan Camps & Benny Carlé cturcanu@sckcen.be
/ jcamps@sckcen.be
Society and Policy Support
Institute Environment, Health and Safety
Belgian Nuclear Research Centre
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Workshop “All models are wrong…”, Groningen, 14-16/03/2011

Outline
 Context
 Nuclear emergency model uncertainties
 Conclusions
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Model for evaluation of nuclear emergencies for the Doel NPP site

Nuclear emergencies & models
Use of models for the protection of people in emergency situations
& preparedness phase:
 Atmospheric transport and dispersion models
(concentrations, deposition)
 Dose models (dose adults, children, thyroid, .)
 Food models (concentrations, dose)
 …
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The modelling problem:
Height-dependent wind velocity
Inversion layer
Atmospheric turbulence
Dry deposition
Wash-out rain
Irradiation
Inhalation
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Ingestion
Irradiation shielding

How are decisions taken?
Legislation
 Reference band of dose values – calculated based on model predictions (or measurements or both)
 Action levels on specific actions (Belgian levels)
Action
General evacuation
Indicative ranges for intervention
(dose – mSv)
General sheltering
(up to 24h)
5-15 (effective dose)
Stable iodine prophylaxis
10-50 (thyroid equivalent dose)
50-150 (effective dose integrated 1 week)
 New recommendations: 20-100 mSv/y, all pathways
 Range ≠ uncertainty !
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Uncertainties
 Modelling assumptions
 Simplifications of reality
 Parameter uncertainty
 Calibration of model parameters
 Input data
 Meteorology
 Source term
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Average plume
Meandering plume
Fluctuating plume
Source models:
Torben Mikkelsen, Risø
Uncertainties from modelling assumptions simple
Conservative calculation
Best estimate complex
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Model intercomparison
Standard conditions
Experimentally validated: factor 2-3 within experiments
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Model intercomparison
Very specific conditions
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Scenario 4
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8
10
7
10
6
10
5
10
4
0 5
9
10
Distance (km)
15
SCK•CEN_A
SCK•CEN_B
HOTSPOT
RODOS (Atstep)
ARGOS (Rimpuff)
Rimpuff (Ismode=1)
NPKPuff4
20 25

Noodplan Doel
JRODOS
Rimpuff (ARGOS)
TIC [Bq s/m 3 ] same color scale
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Model intercomparison realistic scenario

Potential problems related to the resolution of the calculation grid
Inner grid cell: 1 km
 no sheltering
For the same scenario:
Inner grid cell: 100m
 sheltering
>1km
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Parameter uncertainty:
Cs-137 in milk
1000
100
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1
0,1
0
Messungen
Modell-Vorhersage
400 600 800 1000 1200
Source: Florian Gering

Model uncertainties in radiological assessments
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Malcolm Crick, IAEA
Source: Malcolm Crick

Uncertainties in input data (1): meteorology
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Source: Marc de Cort

Uncertainties in the input data (2) with on-site single rain gauge data with multiple rain gauge data
With rain-radar data
Example: Input data precipitation
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10
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Scenario 2
Effect of conservative approach for treatment of rain
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10
8
10
7
10
6
10
5
0
SCK•CEN_A
SCK•CEN_B (depletion off)
SCK•CEN_B (depletion on)
HOTSPOT
RODOS (Atstep)
RODOS (Rimpuff)
ARGOS (Rimpuff)
NPKPuff4
10
16
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Distance (km)
30 40 50

Example: conservative approach
Tihange, core melt, rupture primary circuit
Standard weather conditions
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Example: conservative approach
Tihange, partial core melt, rupture primary circuit
Standard weather conditions
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Example: conservative approach
Tihange, core melt, rupture primary circuit unstable weather conditions
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Conclusions
 Complex problem
 Often models extended beyond validated range
 Difficult to obtain realistic uncertainties on calculations
 Even more difficult to communicate these uncertainties to decision-makers
 Best estimate often replaced by conservative approach
 But … conservative estimates may lead to unfeasible countermeasures
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