Source term uncertainty analysis: probabilistic approaches and applications to a BWR severe accident

A suite of methods has been established to quantitatively estimate uncertainties existed in source term analysis during a nuclear reactor severe accident. The accident sequence occurred at Unit 2 of the Fukushima Daiichi nuclear power plant (NPP) is taken as an example in which it is numerically mod...

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Autores principales:	Xiaoyu ZHENG, Hiroto ITOH, Hitoshi TAMAKI, Yu MARUYAMA
Formato:	article
Lenguaje:	EN
Publicado:	The Japan Society of Mechanical Engineers 2015
Materias:	fukushima daiichi npp accident source term uncertainty analysis latin hypercube sampling bayesian nonparametric density estimation kullback-leibler divergence Mechanical engineering and machinery TJ1-1570
Acceso en línea:	https://doaj.org/article/e079d6a94fc5498aac0233ea2e8a48a4
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spelling	oai:doaj.org-article:e079d6a94fc5498aac0233ea2e8a48a42021-11-26T06:30:10ZSource term uncertainty analysis: probabilistic approaches and applications to a BWR severe accident2187-974510.1299/mej.15-00032https://doaj.org/article/e079d6a94fc5498aac0233ea2e8a48a42015-09-01T00:00:00Zhttps://www.jstage.jst.go.jp/article/mej/2/5/2_15-00032/_pdf/-char/enhttps://doaj.org/toc/2187-9745A suite of methods has been established to quantitatively estimate uncertainties existed in source term analysis during a nuclear reactor severe accident. The accident sequence occurred at Unit 2 of the Fukushima Daiichi nuclear power plant (NPP) is taken as an example in which it is numerically modeled via the integrated severe accident code MELCOR 1.8.5. This standardized approach mainly consists of four steps: screening analysis, random sampling, numerical computation and verification of uncertainty distributions. First, by using an individually randomized one-factor-at-a-time screening method, a group of variables are preliminarily determined as important uncertain variables. Second, appropriate probability distributions are assigned to all selected variables. Multiple sets of random samples are generated using Latin Hypercube sampling combined with the consideration of rank correlation among input variables. Third, random samples of all selected variables are inputted into MELCOR 1.8.5. Numerical simulation with multiple code runs is implemented. Finally, uncertainty distributions for representative source terms (barium cesium, cesium iodide and tellurium) are obtained and verified. The technique of Bayesian nonparametric density estimation is applied to obtain probability density functions of interested source terms. In order to obtain a reasonable uncertainty distribution, several rounds of Latin Hypercube sampling and computation are conducted. As an alternative method to Wilks sampling criteria, the difference of probability density functions is evaluated through the comparison based on the Kullback-Leibler (KL) divergence. With the subjective judgment of small enough KL divergence, after a certain number of numerical computations, the uncertainty distributions of representative source terms are considered as stable enough as reliable results.Xiaoyu ZHENGHiroto ITOHHitoshi TAMAKIYu MARUYAMAThe Japan Society of Mechanical Engineersarticlefukushima daiichi npp accidentsource termuncertainty analysislatin hypercube samplingbayesian nonparametric density estimationkullback-leibler divergenceMechanical engineering and machineryTJ1-1570ENMechanical Engineering Journal, Vol 2, Iss 5, Pp 15-00032-15-00032 (2015)
institution	DOAJ
collection	DOAJ
language	EN
topic	fukushima daiichi npp accident source term uncertainty analysis latin hypercube sampling bayesian nonparametric density estimation kullback-leibler divergence Mechanical engineering and machinery TJ1-1570
spellingShingle	fukushima daiichi npp accident source term uncertainty analysis latin hypercube sampling bayesian nonparametric density estimation kullback-leibler divergence Mechanical engineering and machinery TJ1-1570 Xiaoyu ZHENG Hiroto ITOH Hitoshi TAMAKI Yu MARUYAMA Source term uncertainty analysis: probabilistic approaches and applications to a BWR severe accident
description	A suite of methods has been established to quantitatively estimate uncertainties existed in source term analysis during a nuclear reactor severe accident. The accident sequence occurred at Unit 2 of the Fukushima Daiichi nuclear power plant (NPP) is taken as an example in which it is numerically modeled via the integrated severe accident code MELCOR 1.8.5. This standardized approach mainly consists of four steps: screening analysis, random sampling, numerical computation and verification of uncertainty distributions. First, by using an individually randomized one-factor-at-a-time screening method, a group of variables are preliminarily determined as important uncertain variables. Second, appropriate probability distributions are assigned to all selected variables. Multiple sets of random samples are generated using Latin Hypercube sampling combined with the consideration of rank correlation among input variables. Third, random samples of all selected variables are inputted into MELCOR 1.8.5. Numerical simulation with multiple code runs is implemented. Finally, uncertainty distributions for representative source terms (barium cesium, cesium iodide and tellurium) are obtained and verified. The technique of Bayesian nonparametric density estimation is applied to obtain probability density functions of interested source terms. In order to obtain a reasonable uncertainty distribution, several rounds of Latin Hypercube sampling and computation are conducted. As an alternative method to Wilks sampling criteria, the difference of probability density functions is evaluated through the comparison based on the Kullback-Leibler (KL) divergence. With the subjective judgment of small enough KL divergence, after a certain number of numerical computations, the uncertainty distributions of representative source terms are considered as stable enough as reliable results.
format	article
author	Xiaoyu ZHENG Hiroto ITOH Hitoshi TAMAKI Yu MARUYAMA
author_facet	Xiaoyu ZHENG Hiroto ITOH Hitoshi TAMAKI Yu MARUYAMA
author_sort	Xiaoyu ZHENG
title	Source term uncertainty analysis: probabilistic approaches and applications to a BWR severe accident
title_short	Source term uncertainty analysis: probabilistic approaches and applications to a BWR severe accident
title_full	Source term uncertainty analysis: probabilistic approaches and applications to a BWR severe accident
title_fullStr	Source term uncertainty analysis: probabilistic approaches and applications to a BWR severe accident
title_full_unstemmed	Source term uncertainty analysis: probabilistic approaches and applications to a BWR severe accident
title_sort	source term uncertainty analysis: probabilistic approaches and applications to a bwr severe accident
publisher	The Japan Society of Mechanical Engineers
publishDate	2015
url	https://doaj.org/article/e079d6a94fc5498aac0233ea2e8a48a4
work_keys_str_mv	AT xiaoyuzheng sourcetermuncertaintyanalysisprobabilisticapproachesandapplicationstoabwrsevereaccident AT hirotoitoh sourcetermuncertaintyanalysisprobabilisticapproachesandapplicationstoabwrsevereaccident AT hitoshitamaki sourcetermuncertaintyanalysisprobabilisticapproachesandapplicationstoabwrsevereaccident AT yumaruyama sourcetermuncertaintyanalysisprobabilisticapproachesandapplicationstoabwrsevereaccident
_version_	1718409813322366976

Source term uncertainty analysis: probabilistic approaches and applications to a BWR severe accident

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