International case study comparing PSA modeling approaches for nuclear digital I&C – OECD/NEA task DIGMAP
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| Názov: | International case study comparing PSA modeling approaches for nuclear digital I&C – OECD/NEA task DIGMAP |
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| Autori: | Porthin, Markus, Shin, Sung Min, Quatrain, Richard, Tyrväinen, Tero, Sedlak, Jiri, Brinkman, Hans, Müller, Christian, Picca, Paolo, Jaros, Milan, Natarajan, Venkat, Piljugin, Ewgenij, Demgné, Jeanne |
| Zdroj: | Nuclear Engineering and Technology, Vol 55, Iss 12, Pp 4367-4381 (2023) |
| Informácie o vydavateľovi: | Elsevier BV, 2023. |
| Rok vydania: | 2023 |
| Predmety: | Benchmarking, TK9001-9401, Case study, Digital I&C, Nuclear engineering. Atomic power, Probabilistic safety assessment, ta216, Reliability, 7. Clean energy, Nuclear power plant |
| Popis: | 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. |
| Druh dokumentu: | Article |
| Jazyk: | English |
| ISSN: | 1738-5733 |
| DOI: | 10.1016/j.net.2023.08.012 |
| Prístupová URL adresa: | http://juuli.fi/Record/0678308523 https://doi.org/10.1016/j.net.2023.08.012 https://cris.vtt.fi/en/publications/a68606ce-0e8c-4ce9-bcdb-0a2b83572e4a https://doi.org/10.1016/j.net.2023.08.012 https://doaj.org/article/d9b8f72c7ac1491ba001b614bec27113 |
| Rights: | CC BY |
| Prístupové číslo: | edsair.doi.dedup.....e3496dae2e32b4826fbd2b1b436550a7 |
| Databáza: | OpenAIRE |
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Nájsť tento článok vo Web of Science | Abstrakt: | 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. |
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| ISSN: | 17385733 |
| DOI: | 10.1016/j.net.2023.08.012 |