modelling uncertainties and the use of
TRANSCRIPT
Modelling uncertainties and the use of
“uncertain” model results in nuclear
emergency preparedness
Nordic Nuclear and Radiation Risk Estimates -
Advances and Uncertainties - Joint NKS-R and
NKS-B Seminar, Finlandshuset,
Stockholm, 15-16 January 2019
Steen Hoe DEMA ([email protected])
Introductory remarks, Topics
Uncertainties from
● Meteorological models
● Atmospheric Models
● Source Terms Models
How to mix and use model result with uncertainties in
Nuclear Emergency Management
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Introductory remarks, acknowledgements
Material and help to this presentation from:
● Dr Jens Havskov Sørensen , Danish Meteorological Institute (DMI),
● Jan Pehrsson, PDC-ARGOS, Denmark
● SSM
● Elisabeth Tengborn, Anders Riber Marklund Lloyd’s Register, Sweden
● IRSN website
Projects and software:
● NKS (AVESOME), EU-FASTNET, ARGOS- and RASTEP- software
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Uncertainty – dispersion models
● Selection of dispersion models (ex DERMA, MATCH, SNAP, RIMPUFF and
URD)
● Numerical Weather Prediction models (HARMONIE, HIRLAM, ECMWF,…)
● Danish Operational setup in
● Danish Meteorological Institute - DMI
● Danish Emergency Management- DEMA
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Thyroid dose (5y)Large postulated release from Ringhals NPP
● RIMPUFF (based on HIRLAM data)
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Slide 5
Thyroid dose (5y)
● DERMA (based on HARMONIE)
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Slide 6
Thyroid dose (5y)
Slide 7
● DERMA (based on HIRLAM T )
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Uncertainty – Meteorological (Harmonie Model)
● Danish Operational setup in
● Danish Meteorological Institute - DMI
● Danish Emergency Management- DEMA
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Thyroid “dose” (5y)
Slide 9
● DERMA ensemble result “where most
models agrees”
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Thyroid “dose” (5y)
Slide 10
● DERMA ensemble result with areas for
“potential high values”- not physical
correct
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Coping with uncertainty in ARGOS
Slide 11
● Iso Curves are stored as
Hazard areas in ARGOS
● Population data can be
calculated for Hazard areas
in DEMA’s ARGOS-
installation
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Ensemble 10th percentile
Slide 12
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10th percentile+RIMPUFF
Slide 13
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10th percentile+RIMPUFF+DERMA
Slide 14
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10th
percentile+RIMPUFF+DERMA+90t
h percentile
Slide 15
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Solution: 2 areas for decision makers
Slide 16
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Total early Dose – recalculated
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DID you remember?
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Source Terms?
● Advanced Source Term models and severe accidents codes
● MELCOR, MAAP and ASTEC - not very usefully in the emergency phase
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https://www.irsn.fr/EN/Research/Scientific-tools/Computer-codes/Pages/The-ASTEC-Software-Package-2949.aspx
The EU FASTNET project
“Tool for the fast and reliable prediction of severe accident progression and
anticipation of the source term of a nuclear accident”
● WP1: Developing a sever accident scenario database with generic source
terms
● WP2 and WP3: Developing generic models for existing NPPs in Europe both
using a deterministic approach (3D/3P and PERSAN) and a probabilistic
method (RASTEP)
● WP4: Exercises using the source term tools developed in WP2 and WP3
together with decision support systems
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RASTEP (Developed by Lloyds Register Consulting for SSM)
● By answering questions about e.g. system availability and containment
pressure etc. RASTEP gives the probability for different source terms.
The source terms in RASTEP are pre-calculated using a severe accident
code.
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NKS AVESOME project lessons
from a Emergency management
View:
● Start with only a few source
terms
● Only compare source term of
similar size.
● One forecast, one source term
are still relevant!
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How to mix uncertainties from a model
chain in Nuclear Emergency Management
1,00E+08
1,00E+09
1,00E+10
1,00E+11
1,00E+12
1,00E+13
1,00E+14
1,00E+15
1,00E+16
1,00E+17
1,00E+18
0 360 720108014401800216025202880
Acc
um
ula
ted
rel
ease
(B
q)
Time (min)
Accumulated release of Cs-137GAP
OTL-
OLL-
OTI-
L--X
F-E-
OTES
OLES
Implementation in ARGOS
Operational only for Meteorological
Ensemble modelling in Denmark
Technical operational before spring
2019.
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Conclusions and hopes
Meteorological Ensemble Modelling is operational and provides dispersion
outputs (In Denmark) but with limited forecast time, but we need more
research in handling the uncertainty of source terms and monitoring data.
The Emergency management system can have problem with digesting the
amount of data/prognosis coming from the models.
We need more technical cooperation between neighbouring countries and a
more open approach for exchanging potential source term.
If we shall maintain a trustworthy Nuclear Emergency handling, we need
technical expertise on all levels in the Emergency Organisations.
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Danish Emergency Management Agency
Datavej 16
Phone: +45 4590 6000
E-mail: [email protected]
www.brs.dk
3460 Birkerød
Thank you
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