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A petri net methodology for modeling the resilience of nuclear power plants

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conference contribution
posted on 2021-10-05, 10:44 authored by Rundong (Derek) Yan, Sarah DunnettSarah Dunnett, Silvia Tolo, John Andrews
In the paper, a novel Petri Net (PN) method for assessing the resilience of nuclear reactors is presented. The PN model constructed aims to simulate the failure of the subsystems in a reactor caused by either natural degradation or external disruptive events such as tsunamis and earthquakes, the resultant accidents due to the failure of different reactor subsystems, the responses of the reactor to different accidents, and the recovery and maintenance of the reactor after the accident. The simulation results are analyzed to identify the key characteristics of the resilience of the nuclear reactor. To demonstrate the feasibility and the capability of the proposed approach, the failure of four heat transport pumps in the primary cooling system of an experimental reactor is chosen as a case study. The research shows that PN modeling is an effective tool for evaluating the resilience of nuclear power plants.

Funding

A Resilience Modelling Framework for Improved Nuclear Safety (NuRes)

Engineering and Physical Sciences Research Council

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History

School

  • Aeronautical, Automotive, Chemical and Materials Engineering

Department

  • Aeronautical and Automotive Engineering

Published in

Proceedings of the 31st European Safety and Reliability Conference (ESREL 2021)

Pages

2426-2432

Source

31st European Safety and Reliability Conference (ESREL 2021)

Publisher

Research Publishing Services

Version

  • VoR (Version of Record)

Rights holder

© European Safety and Reliability Association

Publisher statement

Reproduced with permission of the author

Publication date

2021-09-30

Copyright date

2021

ISBN

9789811820168

Language

  • en

Editor(s)

Bruno Castanier; Marko Cepin; David Bigaud; Christophe Berenguer

Location

Angers, France

Event dates

19th September 2021 - 23rd September 2021

Depositor

Dr Derek Yan . Deposit date: 5 October 2021

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