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    Probabilistic Validation: Theoretical Foundation and Methodological Platform

    Source: ASCE-ASME J Risk and Uncert in Engrg Sys Part B Mech Engrg:;2023:;volume( 009 ):;issue: 002::page 21204-1
    Author:
    Bui, Ha
    ,
    Sakurahara, Tatsuya
    ,
    Reihani, Seyed
    ,
    Kee, Ernie
    ,
    Mohaghegh, Zahra
    DOI: 10.1115/1.4056883
    Publisher: The American Society of Mechanical Engineers (ASME)
    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 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.
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      Probabilistic Validation: Theoretical Foundation and Methodological Platform

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    contributor authorBui, Ha
    contributor authorSakurahara, Tatsuya
    contributor authorReihani, Seyed
    contributor authorKee, Ernie
    contributor authorMohaghegh, Zahra
    date accessioned2023-08-16T18:49:41Z
    date available2023-08-16T18:49:41Z
    date copyright3/7/2023 12:00:00 AM
    date issued2023
    identifier issn2332-9017
    identifier otherrisk_009_02_021204.pdf
    identifier urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4292552
    description abstractAddressing 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 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.
    publisherThe American Society of Mechanical Engineers (ASME)
    titleProbabilistic Validation: Theoretical Foundation and Methodological Platform
    typeJournal Paper
    journal volume9
    journal issue2
    journal titleASCE-ASME J Risk and Uncert in Engrg Sys Part B Mech Engrg
    identifier doi10.1115/1.4056883
    journal fristpage21204-1
    journal lastpage21204-27
    page27
    treeASCE-ASME J Risk and Uncert in Engrg Sys Part B Mech Engrg:;2023:;volume( 009 ):;issue: 002
    contenttypeFulltext
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