Risk Assessment of Spent Nuclear Fuel Facilities Considering Climate Change

verfasst von

Silvia Tolo, Edoardo Patelli, Michael Beer

Abstract

Natural hazards have the capability to affect technological installations, triggering multiple failures and putting the population and the surrounding environment at risk. Global climate change introduces an additional and not negligible element of uncertainty to the vulnerability quantification, threatening to intensify (both in terms of frequency and severity) the occurrence of extreme climate events. Sea level extremes and extreme coastal high waters are expected to change in the future as a result of both changes in atmospheric storminess and mean sea level rise, as well as extreme precipitation events. These trends clearly suggest a parallel increase in the risks affecting technological installations and the subsequent need for mitigation measures to enhance the reliability of existing systems and to improve the design standards of new facilities. In spite of this situation, the scientific research in this field lacks robust and reliable tools for this kind of assessment, often relying on the adoption of oversimplified models or strong assumptions, which affect the credibility of the results. The main purpose of this study is to provide a novel and general model for the evaluation of the risk of exposure of spent nuclear fuel stored in a facility subject to flood hazard, investigating the potential and limitations of Bayesian networks (BNs) in this field. The network aims to model the interaction between extreme weather conditions and the technological installation, as well as the propagation of failures within the system itself, taking into account the dependencies among the different components and the occurrence of human error. A real-world application concerning the nuclear power station of Sizewell B in East Anglia, in the United Kingdom, is extensively described, together with the models and data set used. Results are presented for three different time scenarios in which climate change projections have been adopted to estimate future risks.

Organisationseinheit(en)

Institut für Risiko und Zuverlässigkeit

Externe Organisation(en)

The University of Liverpool
Tongji University

Typ

Artikel

Journal

ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering

Band

3

Anzahl der Seiten

15

ISSN

2376-7642

Publikationsdatum

06.2017

Publikationsstatus

Veröffentlicht

Peer-reviewed

Ja

ASJC Scopus Sachgebiete

Tief- und Ingenieurbau, Bauwesen, Sicherheit, Risiko, Zuverlässigkeit und Qualität

Ziele für nachhaltige Entwicklung

SDG 13 – Klimaschutzmaßnahmen

Elektronische Version(en)

https://strathprints.strath.ac.uk/70461/1/Tolo_etal_RUES2016_Risk_assessment_spent_nuclear_fuel_facilities_considering_climate_change.pdf (Zugang: Offen)
https://doi.org/10.1061/AJRUA6.0000874 (Zugang: Geschlossen)