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contributor authorNikil N. Pujari
contributor authorSiddhartha Ghosh
contributor authorSayantani Lala
date accessioned2017-12-30T13:04:39Z
date available2017-12-30T13:04:39Z
date issued2016
identifier otherAJRUA6.0000840.pdf
identifier urihttp://138.201.223.254:8080/yetl1/handle/yetl/4245358
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
pageB4015004
treeASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering:;2016:;Volume ( 002 ):;issue: 003
contenttypeFulltext


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