Developing a new fire PRA framework by integrating probabilistic risk assessment with a fire simulation module

Tatsuya Sakurahara, Seyed A. Reihani, Zahra Mohaghegh, Mark Brandyberry, Ernie Kee, David Johnson, Shawn Rodgers, Mary Anne Billings

Research output: Contribution to conferencePaper

Abstract

Recently, the fire protection programs at nuclear power plants have been transitioned to a risk-informed approach utilizing Fire Probabilistic Risk Assessment (Fire PRA). One of the main limitations of the current methodology is that it is not capable of adequately accounting for the dynamic behavior and effects of fire due to its reliance on the classical PRA methodology (i.e., Event Trees and Fault Trees). As a solution for this limitation, in this paper we propose an integrated framework for Fire PRA. This method falls midway between a classical and a fully dynamic PRA with respect to the utilization of simulation techniques. In the integrated framework, some of the fire-related Fault Trees are replaced with a Fire Simulation Module (FSM), which is linked to a plant-specific PRA model. The FSM is composed of simulation-based physical models for fire initiation, progression, and post-fire failure. Moreover, FSM includes the uncertainty propagation in the physical models and input parameters. These features will reduce the unnecessary conservativeness in the current Fire PRA methodology by modeling the underlying physical phenomena and by considering the dynamic interactions among them.

Original languageEnglish (US)
StatePublished - Jan 1 2014
Event12th International Probabilistic Safety Assessment and Management Conference, PSAM 2014 - Honolulu, United States
Duration: Jun 22 2014Jun 27 2014

Other

Other12th International Probabilistic Safety Assessment and Management Conference, PSAM 2014
CountryUnited States
CityHonolulu
Period6/22/146/27/14

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Keywords

  • Fire PRA
  • Integrated PRA framework
  • Nuclear power plants

ASJC Scopus subject areas

  • Safety, Risk, Reliability and Quality

Cite this

Sakurahara, T., Reihani, S. A., Mohaghegh, Z., Brandyberry, M., Kee, E., Johnson, D., Rodgers, S., & Billings, M. A. (2014). Developing a new fire PRA framework by integrating probabilistic risk assessment with a fire simulation module. Paper presented at 12th International Probabilistic Safety Assessment and Management Conference, PSAM 2014, Honolulu, United States.