H. Bui, T. Sakurahara, S. Reihani, E. Kee, Z. Mohaghegh
{"title":"Probabilistic Validation: Theoretical Foundation and Methodological Platform","authors":"H. Bui, T. Sakurahara, S. Reihani, E. Kee, Z. Mohaghegh","doi":"10.1115/1.4056883","DOIUrl":null,"url":null,"abstract":"\n Addressing safety concerns in commercial Nuclear Power Plants (NPPs) often requires the use of advanced modeling and simulation (M&S) in association with the Probabilistic Risk Assessment (PRA). Advanced M&S are also needed to accelerate the analysis, design, licensing, and operationalization of advanced nuclear reactors. However, before a simulation model can be used for PRA, its validity must be adequately established. The objective of this research is to develop a systematic and scientifically justifiable validation methodology, namely, Probabilistic Validation (PV), to facilitate the validity evaluation (especially when validation data are not sufficiently available) of advanced simulation models that are used for PRA in support of risk-informed decision-making and regulation. This paper is the first in a series of two papers related to the PV that provides the theoretical foundation and methodological platform. The second paper applies the PV methodological platform for a case study of Fire PRA of NPPs. Although the PV methodology is explained in the context of PRA of the nuclear industry, it is grounded on a cross-disciplinary review of literature and so applicable to validation of simulation models, in general, not necessarily associated with PRA or nuclear applications.","PeriodicalId":44694,"journal":{"name":"ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems Part B-Mechanical Engineering","volume":"7 1","pages":""},"PeriodicalIF":1.8000,"publicationDate":"2023-02-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems Part B-Mechanical Engineering","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1115/1.4056883","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"ENGINEERING, MULTIDISCIPLINARY","Score":null,"Total":0}
引用次数: 0
Abstract
Addressing safety concerns in commercial Nuclear Power Plants (NPPs) often requires the use of advanced modeling and simulation (M&S) in association with the Probabilistic Risk Assessment (PRA). Advanced M&S are also needed to accelerate the analysis, design, licensing, and operationalization of advanced nuclear reactors. However, before a simulation model can be used for PRA, its validity must be adequately established. The objective of this research is to develop a systematic and scientifically justifiable validation methodology, namely, Probabilistic Validation (PV), to facilitate the validity evaluation (especially when validation data are not sufficiently available) of advanced simulation models that are used for PRA in support of risk-informed decision-making and regulation. This paper is the first in a series of two papers related to the PV that provides the theoretical foundation and methodological platform. The second paper applies the PV methodological platform for a case study of Fire PRA of NPPs. Although the PV methodology is explained in the context of PRA of the nuclear industry, it is grounded on a cross-disciplinary review of literature and so applicable to validation of simulation models, in general, not necessarily associated with PRA or nuclear applications.