 Framework to model severe accident management guidelines into Level 2 probabilistic safety assessment of a nuclear power plantJaehyun Cho, Sang Hun Lee, Jaewhan Kim and Seong Kyu Park Reliability Engineering and System Safety, 2022, vol. 217, issue C Abstract: Severe accident management guidelines (SAMG) play a significant role in mitigating severe accidents in nuclear power plants (NPPs), and thus the modeling of SAMG into Level 2 probabilistic safety assessment (PSA) has become essential to more realistically quantify the safety of NPPs and the effectiveness of SAMG. This study developed a systematic framework to model SAMG into Level 2 PSA, in which SAMG event trees and fault trees are modeled to formulate SAMG in a probabilistic manner. Application results to the internal events of a real plant, the OPR-1000, showed that the inclusion of SAMG in the Level 2 PSA model led to not only a significant increase in the conditional containment intact probability, from 37 to 70%, but also a considerable decrease in NPP risk, namely by 44% compared to the case without SAMG. The method can be used for the estimation of the effectiveness of each mitigation strategy, as well as for the identification of the risk-significant factors regarding SAMG. Keywords: Level 2 PSA; SAMG; NPP risk; Cs-137; Severe accident; Event tree; Fault tree (search for similar items in EconPapers) Downloads: (external link) Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:eee:reensy:v:217:y:2022:i:c:s0951832021005743 DOI: 10.1016/j.ress.2021.108076 Access Statistics for this article Reliability Engineering and System Safety is currently edited by Carlos Guedes Soares More articles in Reliability Engineering and System Safety from Elsevier |
Is your work missing from RePEc? Here is how to contribute.
Questions or problems? Check the EconPapers FAQ or send mail to .
EconPapers is hosted by the
School of Business at Örebro University.