A Bayesian updating of crack distributions in steam generator tubes

Detalhes bibliográficos
Autor(a) principal: Francisco, Alexandre Santos
Data de Publicação: 2021
Outros Autores: Simões, Tiago
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Vetor (Online)
Texto Completo: https://periodicos.furg.br/vetor/article/view/13067
Resumo: The structural failure of steam generator tubes is a common problem that can a ect the availability and safety of nuclear power plants. To minimize the probability of occurrence of failure, it is needed to implement maintenance strategies such as periodic nondestructive inspections of tubes. Thus, a tube is repaired or plugged whenever it has detected a crack which a threshold size is overtaken. In general, uncertainties and errors in crack sizes are associated with the nondestructive inspections. These uncertainties and errors should be appropriately characterized to estimate the actual crack distribution. This work proposes a Bayesian approach for updating crack distributions, which in turn allows computing the failure probability of steam generator tubes at current and future times. The failure criterion is based on plastic collapse phenomenon, and the failure probability is computed by using the Monte-Carlo simulation. The failure probability at current and future times is in good agreement with the ones presented in the literature.
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spelling A Bayesian updating of crack distributions in steam generator tubesAtualização Bayesiana da distribuição de trincas em tubos de gerador de vaporSteam generator tubesCrack distributionBayesian updatingTubos do gerador de vaporDistribuição de trincasAtualização BayesianaThe structural failure of steam generator tubes is a common problem that can a ect the availability and safety of nuclear power plants. To minimize the probability of occurrence of failure, it is needed to implement maintenance strategies such as periodic nondestructive inspections of tubes. Thus, a tube is repaired or plugged whenever it has detected a crack which a threshold size is overtaken. In general, uncertainties and errors in crack sizes are associated with the nondestructive inspections. These uncertainties and errors should be appropriately characterized to estimate the actual crack distribution. This work proposes a Bayesian approach for updating crack distributions, which in turn allows computing the failure probability of steam generator tubes at current and future times. The failure criterion is based on plastic collapse phenomenon, and the failure probability is computed by using the Monte-Carlo simulation. The failure probability at current and future times is in good agreement with the ones presented in the literature.A ruptura de um dos tubos do gerador de vapor é um problema que pode afetar a disponibilidade e segurança das usinas nucleares. Para reduzir ao mínimo a probabilidade da ocorrência desse problema, deve-se implementar uma estratégia de manutenção com inspeções periódicas dos tubos do gerador de vapor, por meio de técnicas não-destrutivas. Com isso, um tubo é reparado ou tamponado sempre quando o tamanho da trinca detectada ultrapassa um valor crítico. Em geral, incertezas na detecção e erros de medição estão associados às técnicas não-destrutivas. Essas incertezas e erros devem ser caracterizados propriamente para se estimar acuradamente a distribuição dos tamanhos de trincas. Neste trabalho, propõe-se aplicar uma abordagem probabilística Bayesiana para atualizar a distribuição dos tamanhos de trinca, e a partir da distribuição obter a probabilidade de falha dos tubos do gerador de vapor em momentos presente e futuro. O critério de falha é baseado no fenômeno do colapso plástico, e a probabilidade de falha é computada através da simulação de Monte-Carlo. Os resultados de probabilidade de falha em momentos presente e futuro estão em boa concordância com valores encontrados na literatura.Universidade Federal do Rio Grande2021-07-21info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdfhttps://periodicos.furg.br/vetor/article/view/1306710.14295/vetor.v30i2.13067VETOR - Journal of Exact Sciences and Engineering; Vol. 30 No. 2 (2020); 33-44VETOR - Revista de Ciências Exatas e Engenharias; v. 30 n. 2 (2020); 33-442358-34520102-7352reponame:Vetor (Online)instname:Universidade Federal do Rio Grande (FURG)instacron:FURGenghttps://periodicos.furg.br/vetor/article/view/13067/8888Copyright (c) 2021 VETOR - Revista de Ciências Exatas e Engenhariasinfo:eu-repo/semantics/openAccessFrancisco, Alexandre SantosSimões, Tiago2021-08-05T21:47:31Zoai:periodicos.furg.br:article/13067Revistahttps://periodicos.furg.br/vetorPUBhttps://periodicos.furg.br/vetor/oaigmplatt@furg.br2358-34520102-7352opendoar:2021-08-05T21:47:31Vetor (Online) - Universidade Federal do Rio Grande (FURG)false
dc.title.none.fl_str_mv A Bayesian updating of crack distributions in steam generator tubes
Atualização Bayesiana da distribuição de trincas em tubos de gerador de vapor
title A Bayesian updating of crack distributions in steam generator tubes
spellingShingle A Bayesian updating of crack distributions in steam generator tubes
Francisco, Alexandre Santos
Steam generator tubes
Crack distribution
Bayesian updating
Tubos do gerador de vapor
Distribuição de trincas
Atualização Bayesiana
title_short A Bayesian updating of crack distributions in steam generator tubes
title_full A Bayesian updating of crack distributions in steam generator tubes
title_fullStr A Bayesian updating of crack distributions in steam generator tubes
title_full_unstemmed A Bayesian updating of crack distributions in steam generator tubes
title_sort A Bayesian updating of crack distributions in steam generator tubes
author Francisco, Alexandre Santos
author_facet Francisco, Alexandre Santos
Simões, Tiago
author_role author
author2 Simões, Tiago
author2_role author
dc.contributor.author.fl_str_mv Francisco, Alexandre Santos
Simões, Tiago
dc.subject.por.fl_str_mv Steam generator tubes
Crack distribution
Bayesian updating
Tubos do gerador de vapor
Distribuição de trincas
Atualização Bayesiana
topic Steam generator tubes
Crack distribution
Bayesian updating
Tubos do gerador de vapor
Distribuição de trincas
Atualização Bayesiana
description The structural failure of steam generator tubes is a common problem that can a ect the availability and safety of nuclear power plants. To minimize the probability of occurrence of failure, it is needed to implement maintenance strategies such as periodic nondestructive inspections of tubes. Thus, a tube is repaired or plugged whenever it has detected a crack which a threshold size is overtaken. In general, uncertainties and errors in crack sizes are associated with the nondestructive inspections. These uncertainties and errors should be appropriately characterized to estimate the actual crack distribution. This work proposes a Bayesian approach for updating crack distributions, which in turn allows computing the failure probability of steam generator tubes at current and future times. The failure criterion is based on plastic collapse phenomenon, and the failure probability is computed by using the Monte-Carlo simulation. The failure probability at current and future times is in good agreement with the ones presented in the literature.
publishDate 2021
dc.date.none.fl_str_mv 2021-07-21
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv https://periodicos.furg.br/vetor/article/view/13067
10.14295/vetor.v30i2.13067
url https://periodicos.furg.br/vetor/article/view/13067
identifier_str_mv 10.14295/vetor.v30i2.13067
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv https://periodicos.furg.br/vetor/article/view/13067/8888
dc.rights.driver.fl_str_mv Copyright (c) 2021 VETOR - Revista de Ciências Exatas e Engenharias
info:eu-repo/semantics/openAccess
rights_invalid_str_mv Copyright (c) 2021 VETOR - Revista de Ciências Exatas e Engenharias
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Universidade Federal do Rio Grande
publisher.none.fl_str_mv Universidade Federal do Rio Grande
dc.source.none.fl_str_mv VETOR - Journal of Exact Sciences and Engineering; Vol. 30 No. 2 (2020); 33-44
VETOR - Revista de Ciências Exatas e Engenharias; v. 30 n. 2 (2020); 33-44
2358-3452
0102-7352
reponame:Vetor (Online)
instname:Universidade Federal do Rio Grande (FURG)
instacron:FURG
instname_str Universidade Federal do Rio Grande (FURG)
instacron_str FURG
institution FURG
reponame_str Vetor (Online)
collection Vetor (Online)
repository.name.fl_str_mv Vetor (Online) - Universidade Federal do Rio Grande (FURG)
repository.mail.fl_str_mv gmplatt@furg.br
_version_ 1797041761787314176

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