Abstract
Nuclear power plants are increasingly being equipped with digital I&C systems. Although some probabilistic safety assessment (PSA) models for the digital I&C of nuclear power plants have been constructed, there is currently no specific internationally agreed guidance for their modeling. This paper presents an initiative by the OECD Nuclear Energy Agency called “Digital I&C PSA – Comparative application of DIGital I&C Modelling Approaches for PSA (DIGMAP)”, which aimed to advance the field towards practical and defendable modeling principles. The task, carried out in 2017–2021, used a simplified description of a plant focusing on the digital I&C systems important to safety, for which the participating organizations independently developed their own PSA models. Through comparison of the PSA models, sensitivity analyses as well as observations throughout the whole activity, both qualitative and quantitative lessons were learned. These include insights on failure behavior of digital I&C systems, experience from models with different levels of abstraction, benefits from benchmarking as well as major contributors to the core damage frequency and those with minor effect. The study also highlighted the challenges with modeling of large common cause component groups and the difficulties associated with estimation of key software and common cause failure parameters.
Original language | English |
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Pages (from-to) | 4367-4381 |
Journal | Nuclear Engineering and Technology |
Volume | 55 |
Issue number | 12 |
DOIs | |
Publication status | Published - Dec 2023 |
MoE publication type | A1 Journal article-refereed |
Funding
The work presented in this paper is part of the WGRISK programme of work supported by the OECD/NEA. EDF thanks IRSN for its invitation to participate in this work. National participations were particularly supported by The Finnish Research Programme on Nuclear Power Plant Safety 2015–2018 ( SAFIR2018 ) and 2019–2022 ( SAFIR2022 ), the National Research Foundation of South Korea Grant funded by the Korean Government (MSIT) ( RS-2022-00144175 ), the Dutch research programme on nuclear energy and technology funded by the Ministry of Economic Affairs and Climate , the German Federal Ministry for the Environment, Nature Conservation and Nuclear Safety ( Bundesministerium für Umweltschutz und Reaktorsicherheit, BMU ), and the Technology Agency of the Czech Republic through the Competence Centre CANUT (Centre for Advanced Nuclear Technologies).
Keywords
- Benchmarking
- Case study
- Digital I&C
- Nuclear power plant
- Probabilistic safety assessment
- Reliability