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Pre-Accidental Situations Highlighted by RECUPERARE Method and Data (PSAM-0029)

Excerpt

RECUPERARE method (presented in previous PSAM) has been developed for operating feedback analysis and built on the French Human Reliability Analysis (HRA) principles. It is used to study the causes of human errors or technical failures occurred in French PWRs and the recovery process of events. Based on an event classification (6 categories) model according to the nature of the link between failure and recovery, the identified and recorded data are:

• the causes of the defects (technical, human, organizational) and the context in which they appear;

• the factors of the recovery performance (depending on technical and organizational aspects);

• a chronological analysis, designed to collect delays between failures and their detection/recovery for each event.

About 3600 events reported in French PWRs (1997–2003) had been reviewed through this model. Initially, the weight of factors and the most important factors, which influenced the detection and recovery delay, are defined. For this purpose, the regression Partial Least Square (PLS) is used. Then, to link RECUPERARE results with pre-accidentals data, conditional probabilities of events linked between them by a cause and effect relationship are calculated. For this, the Bayesian method with the Bayesian network is built with the PLS obtained results and applied. This constitutes a first approach to take into account in HRA the human and organizational factors highlighted by operating feedback.

  • Summary/Abstract
  • Introduction
  • Factors Influencing the Detection and Recovery Delay
  • Link with Pre-Accidentals Data
  • Conclusion
  • References

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