An integrated methodology for spatio-temporal incorporation of underlying failure mechanisms into fire probabilistic risk assessment of nuclear power plants

Tatsuya Sakurahara, Zahra Mohaghegh, Seyed Reihani, Ernie Kee, Mark Brandyberry, Shawn Rodgers

Research output: Contribution to journalArticle

Abstract

In this research, an Integrated probabilistic risk assessment (I-PRA) methodological framework for Fire PRA is developed to provide a unified multi-level probabilistic integration, beginning with spatio-temporal simulation-based models of underlying failure mechanisms (i.e., physical phenomena and human actions), connecting to component-level failures, and then linking to system-level risk scenarios in classical PRA. The simulation-based module, called the fire simulation module (FSM), includes state-of-the-art models of fire initiation, fire progression, post-fire failure damage propagation, fire brigade response, and scenario-based damage. Fire progression is simulated using a CFD code, fire dynamics simulator (FDS), which solves Navier–Stokes equations governing the turbulent flow field. Uncertainty quantification is conducted to address parameter uncertainties. The I-PRA paves the way for reducing excessive conservatisms derived from the modeling of (i) fire progression and damage and (ii) the interactions between fire progression and manual suppression. Global importance measure analysis is used to rank the risk-contributing factors. A case study demonstrates the implementation of I-PRA for a regulatory-documented fire scenario.

Original languageEnglish (US)
Pages (from-to)242-257
Number of pages16
JournalReliability Engineering and System Safety
Volume169
DOIs
StatePublished - Jan 2018

Keywords

  • Common cause failure
  • Fire brigade
  • Fire dynamics simulator (FDS)
  • Fire human reliability analysis (HRA)
  • Fire probabilistic risk assessment (PRA)
  • Global importance measure
  • Integrated probabilistic risk assessment (I-PRA)
  • Simulation-based PRA
  • Uncertainty analysis

ASJC Scopus subject areas

  • Safety, Risk, Reliability and Quality
  • Industrial and Manufacturing Engineering

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