Reliability analysis of digital systems in a probabilistic risk analysis for nuclear power plants

Stefan Authén, Jan-Erik Holmberg

Research output: Contribution to journalArticle

39 Citations (Scopus)

Abstract

To assess the risk of nuclear power plant operation and to determine the risk impact of digital systems, there is a need to quantitatively assess the reliability of the digital systems in a justifiable manner. The Probabilistic Risk Analysis (PRA) is a tool which can reveal shortcomings of the NPP design in general and PRA analysts have not had sufficient guiding principles in modelling particular digital components malfunctions. Currently digital I&C systems are mostly analyzed simply and conventionally in PRA, based on failure mode and effects analysis and fault tree modelling. More dynamic approaches are still in the trial stage and can be difficult to apply in full scale PRA-models. As basic events CPU failures, application software failures and common cause failures (CCF) between identical components are modelled.The primary goal is to model dependencies. However, it is not clear which failure modes or system parts CCF:s should be postulated for. A clear distinction can be made between the treatment of protection and control systems. There is a general consensus that protection systems shall be included in PRA, while control systems can be treated in a limited manner. OECD/NEA CSNI Working Group on Risk Assessment (WGRisk) has set up a task group, called DIGREL, to develop taxonomy of failure modes of digital components for the purposes of PRA. The taxonomy is aimed to be the basis of future modelling and quantification efforts. It will also help to define a structure for data collection and to review PRA studies.
Original languageEnglish
Pages (from-to)471-482
JournalNuclear Engineering and Technology
Volume44
Issue number5
DOIs
Publication statusPublished - 2012
MoE publication typeA1 Journal article-refereed

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Keywords

  • Nuclear I&C
  • digital I&C
  • software
  • Probabilistic Risk Analysis
  • Probabilistic Safety Assessment
  • reliability
  • PRA
  • PSA

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