Probabilistic risk model of digital reactor protection system for benchmarking

Research output: Book/ReportReport

Abstract

This report presents a probabilistic risk assessment (PRA) model of a nuclear power plant focusing on digital I&C in the reactor protection system (RPS). The model is prepared for an international benchmark study of OECD/NEA/CSNI/WGRISK project DIGMAP. The model contains one event tree representing loss of main feed-water accident in a fictive boiling water reactor plant. In the simplified model only the RPS is modelled in detailed. This is the main focus area of the benchmark study. The selected modelling approach utilises simple and small fault trees as building blocks that are linked. Effects of fault-tolerant techniques are taken into account in the computation of failure probabilities, but they are not included explicitly in the main PRA model to avoid too much complexity. The models developed by the benchmark participants are different and produce different results. Some models include almost all possible details, whereas some models are even more simplified than the VTT’s model. The more simplified the PRA model is made, the more background calculations are needed. Common cause failure assumptions cause large differences in the results, and therefore, the next step in the study is to harmonize the assumptions to enable effective comparison of the models created by the benchmark participants. The example model is created mainly for the comparison of modelling techniques in the benchmark, and it may be too simple to draw conclusions about the actual risks related to real RPSs. Modelling and computation techniques used in this study should however be quite well applicable to real systems.
Original languageEnglish
PublisherVTT Technical Research Centre of Finland
Number of pages25
Publication statusPublished - 9 Jan 2020
MoE publication typeD4 Published development or research report or study

Publication series

SeriesVTT Research Report
NumberVTT-R-01028-19

Keywords

  • probabilistic risk assessment
  • digital I&C
  • software reliability

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