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    Bayesian Approach for the Seismic Fragility Estimation of a Containment Shell Based on the Formation of Through-Wall Cracks

    Source: ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering:;2016:;Volume ( 002 ):;issue: 003
    Author:
    Nikil N. Pujari
    ,
    Siddhartha Ghosh
    ,
    Sayantani Lala
    DOI: 10.1061/AJRUA6.0000840
    Publisher: American Society of Civil Engineers
    Abstract: The primary containment (PC) in a nuclear power plant provides the last barrier against radiation leakage to the environment. Design specifications fail to assess the performance of a seismically-damaged containment against accidental overpressure. The present work focuses on the seismic fragility estimation of a PC considering formation of through-wall cracks, which may lead to radiation leakage. This is significantly challenging, considering the computation involved in the integration over a multidimensional probability space, detailed numerical modeling of the containment including concrete damage, and nonlinear dynamic analyses of the structure. A Bayesian approach using a Markov chain Monte Carlo (MCMC) integration scheme is adopted, along with more traditional reliability algorithms (point estimate, first-order second moment (FOSM), and response surface), to address the issue of computation while estimating fragility considering both record-to-record variability and structural parameter uncertainty. The fragility based on through-wall cracks is found to be severe with a median acceleration capacity close to the design-basis intensity. The record-to-record variability dominates the total uncertainty. Structural parameter uncertainties can be excluded from fragility calculations to reduce computation.
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      Bayesian Approach for the Seismic Fragility Estimation of a Containment Shell Based on the Formation of Through-Wall Cracks

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    contributor authorNikil N. Pujari
    contributor authorSiddhartha Ghosh
    contributor authorSayantani Lala
    date accessioned2017-05-08T22:27:38Z
    date available2017-05-08T22:27:38Z
    date copyrightSeptember 2016
    date issued2016
    identifier other45766265.pdf
    identifier urihttp://yetl.yabesh.ir/yetl/handle/yetl/80980
    description abstractThe primary containment (PC) in a nuclear power plant provides the last barrier against radiation leakage to the environment. Design specifications fail to assess the performance of a seismically-damaged containment against accidental overpressure. The present work focuses on the seismic fragility estimation of a PC considering formation of through-wall cracks, which may lead to radiation leakage. This is significantly challenging, considering the computation involved in the integration over a multidimensional probability space, detailed numerical modeling of the containment including concrete damage, and nonlinear dynamic analyses of the structure. A Bayesian approach using a Markov chain Monte Carlo (MCMC) integration scheme is adopted, along with more traditional reliability algorithms (point estimate, first-order second moment (FOSM), and response surface), to address the issue of computation while estimating fragility considering both record-to-record variability and structural parameter uncertainty. The fragility based on through-wall cracks is found to be severe with a median acceleration capacity close to the design-basis intensity. The record-to-record variability dominates the total uncertainty. Structural parameter uncertainties can be excluded from fragility calculations to reduce computation.
    publisherAmerican Society of Civil Engineers
    titleBayesian Approach for the Seismic Fragility Estimation of a Containment Shell Based on the Formation of Through-Wall Cracks
    typeJournal Paper
    journal volume2
    journal issue3
    journal titleASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering
    identifier doi10.1061/AJRUA6.0000840
    treeASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering:;2016:;Volume ( 002 ):;issue: 003
    contenttypeFulltext
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