Analyzing Importance Measure methodologies for integrated Probabilistic Risk Assessment in Nuclear Power Plants

Tatsuya Sakurahara, Seyed Reihani, Mehmet Ertem, Zahra Mohaghegh, Ernie Kee

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Importance Measures (IMs) are used to rank the risk contributing factors in Probabilistic Risk Assessment (PRA). In this paper, existing IM methodologies are analyzed in order to select the most suitable IM for an Integrated PRA (IPRA) of Nuclear Power Plants. In IPRA, the classical PRA of the plant is used, but specific areas of concern (e.g., fire, GSI-191, organizational factors, and seismic) are modeled in a simulation-based module (separate from PRA) and the module is then linked to the classical PRA of the plant. The IPRA, with respect to modeling techniques, bridges the classical PRA and simulation-based/dynamic PRA. This paper compares the local and Global Importance Measure (GIM) methodologies and explains the importance of GIM for IPRA. It also demonstrates the application of GIM methodologies to illustrative examples and, after comparing the results, selects the CDF-based sensitivity indicator (Si (CDF)) as an appropriate moment-independent GIM for IPRA. The results demonstrate that, because of the complexity and nonlinearity of IPRA frameworks, Si(CDF) is the best method to accurately rank the risk contributors. Si(CDF) can capture three key features: (1) distribution of input parameters, (2) interactions among input parameters, and (3) distribution of the model output.

Original languageEnglish (US)
Title of host publicationPSAM 2014 - Probabilistic Safety Assessment and Management
PublisherTechno-Info Comprehensive Solutions (TICS)
StatePublished - 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

Keywords

  • Global Importance Measure
  • Global sensitivity analysis
  • Importance Measure
  • Integrated Probabilistic Risk Assessment (IPRA)
  • Simulation-based PRA

ASJC Scopus subject areas

  • Safety, Risk, Reliability and Quality

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  • Cite this

    Sakurahara, T., Reihani, S., Ertem, M., Mohaghegh, Z., & Kee, E. (2014). Analyzing Importance Measure methodologies for integrated Probabilistic Risk Assessment in Nuclear Power Plants. In PSAM 2014 - Probabilistic Safety Assessment and Management Techno-Info Comprehensive Solutions (TICS).