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The 46th STIG Policy Platform Seminar: Bayesian and Non-Bayesian methods for the assessment of the risks of major nuclear accidents

June 7, 2016

Details

Type Lecture
Intended for General public / Enrolled students / International students / Alumni / Companies / University students
Date(s) June 10, 2016 10:00 — 11:30
Location Hongo Area Campus
Venue Seminar room 2, Economics Research Annex (Kojima Hall)
Capacity 50 people
Entrance Fee No charge
Registration Method Advance registration required
https://ppforum.jp/?action_entry=true&forum_id=342
Contact Science, Technology, and Innovation Governance (STIG), The University of Tokyo
STIG@pp.u-tokyo.ac.jp

Abstract:
How do past observations inform us of the future risks of major nuclear accidents? How did the catastrophe at the Fukushima Dai-ichi nuclear power plant change the expected frequency for such events? There has been little consensus in answering these questions. While opponents of nuclear power claim that the probability of a serious accident is very high, the industry ensures that it is negligible. Furthermore, when facing such ambiguity, or multiple sources of information, how should policy-makers behave regarding these rare but catastrophic risks? The aim of the presentation is to present two methods developed in CERNA-Mines ParisTech that try to shed light on these questions. We will first present a Bayesian method which tries to determine the effect of the Fukushima Dai-ichi accident on the probability of witnessing future major nuclear accidents. Second, we will present a non-Bayesian method which tries to account for the ambiguity that characterizes the risks of nuclear power accidents.

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