This presentation describes the RASTEP tool.

1. RASTEP
RApid Source TErm Prediction
Anders Riber Marklund, PhD
The Resilience Shift Workshop
London, 2019-02-05

2. Context
● To make appropriate decisions on emergency response,
there is a need to make predictions of the potential
consequences of an ongoing event.
● Source term = Radioactive release scenario
Lloyd's Register 2
Nuclear Emergency Preparedness and Response

3. RASTEP
● Provides emergency preparedness organisations with decision
support by estimating likelihoods of source term prognoses
(radioactive release scenarios).
● If data is available, the model could be applied to any
prognosis of uncertain scenario development.
● Flooding, climate change, emergency dispatching, releases of
hazardous chemicals, volcanic eruptions etc.
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https://www.lr.org/rastep

4. RASTEP model structure
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RASTEP model
Bayesian Belief
Network
Current
observations
Known scenariosStatistical data
Prognosis

5. Demo case
● The earthquake (11 March 2011, 14:46) lead to scram and containment isolation. Residual heat
removal was initially achieved by the isolation condensers (IC) without problem. The ICs were
however shut off before the tsunami and never restarted.
● A tsunami of ~14 m at 15:36 lead to station blackout and loss of ultimate heat sink. Neither primary
depressurization nor containment spray was achieved.
● The containment venting system was unfiltered.
Lloyd's Register 5
Fukushima Daiichi - Unit 1

6. Lloyd's Register 6

7. Lloyd's Register 7

8. Lloyd's Register 8

10. Lloyd's Register 10
Thank you!
Anders Riber Marklund, PhD
Principal consultant & team lead
Department of nuclear consulting
Deterministic safety analysis & licensing
E: anders.ribermarklund@lr.org
M: +46 (0)70 230 41 14