APPLICATION OF BAYESIAN METHODOLOGY FOR THE ANALYSIS OF THE FOUNDATIONS OF THE MODERNIZED PIER OF PORTO NOVO (RIO GRANDE, BRAZIL)

Detalhes bibliográficos
Autor(a) principal: Magalhães, Felipe Costa
Data de Publicação: 2016
Outros Autores: Alves, Antônio Marcos de Lima, Dias, Cláudio Renato Rodrigues
Tipo de documento: Artigo
Idioma: por
Título da fonte: Vetor (Online)
Texto Completo: https://periodicos.furg.br/vetor/article/view/2247
Resumo: The aim of this work is to present the application of a procedure for updating the predictions of the bearing capacity of the piles, by using the driving data measured during the execution process. The updating is obtained through the application of the concepts of the Bayesian analysis. The uncertainty of the parameters is modeled by an "a priori" and an “a posteriori" probability distribution. The "a priori" distribution is obtained through semi-empirical methods for predicting the bearing capacity of piles based on Standard Penetration Test results. The construction of the “a posteriori" distribution is made by the updating of the “a priori” distribution, using a function of maximum likelihood based on data from driving registries. The procedure has been applied on a pile job, part of the project of a new pier at Porto Novo, in Rio Grande (RS).
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spelling APPLICATION OF BAYESIAN METHODOLOGY FOR THE ANALYSIS OF THE FOUNDATIONS OF THE MODERNIZED PIER OF PORTO NOVO (RIO GRANDE, BRAZIL)Aplicação de metodologia bayesiana na análise das fundações do cais modernizado do porto novo de Rio Grande (RS)Engenhariaestacasteorema de bayesThe aim of this work is to present the application of a procedure for updating the predictions of the bearing capacity of the piles, by using the driving data measured during the execution process. The updating is obtained through the application of the concepts of the Bayesian analysis. The uncertainty of the parameters is modeled by an "a priori" and an “a posteriori" probability distribution. The "a priori" distribution is obtained through semi-empirical methods for predicting the bearing capacity of piles based on Standard Penetration Test results. The construction of the “a posteriori" distribution is made by the updating of the “a priori” distribution, using a function of maximum likelihood based on data from driving registries. The procedure has been applied on a pile job, part of the project of a new pier at Porto Novo, in Rio Grande (RS).O objetivo deste trabalho é apresentar a aplicação de um procedimento de atualização da previsão da capacidade de carga de estacas, tomando como base os registros documentados durante a execução dos trabalhos. Esta atualização é obtida através da aplicação dos conceitos da análise Bayesiana. A incerteza dos parâmetros é modelada por distribuições de probabilidade “a priori” e “a posteriori”. Para obtenção da distribuição “a priori” foram utilizados métodos semi-empíricos de previsão da capacidade de carga das estacas baseados em resultados de ensaios SPT (Standard Penetration Test). A distribuição “a posteriori” é obtida através da atualização da distribuição “a priori”, utilizando uma função de máxima verossimilhança baseada em dados registrados durante a cravação das estacas. O procedimento foi aplicado em um estaqueamento da obra de remodelação do cais do Porto Novo, em Rio Grande (RS).Universidade Federal do Rio Grande2016-09-22info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdfhttps://periodicos.furg.br/vetor/article/view/2247VETOR - Journal of Exact Sciences and Engineering; Vol. 24 No. 1 (2014); 66-81VETOR - Revista de Ciências Exatas e Engenharias; v. 24 n. 1 (2014); 66-812358-34520102-7352reponame:Vetor (Online)instname:Universidade Federal do Rio Grande (FURG)instacron:FURGporhttps://periodicos.furg.br/vetor/article/view/2247/3804Copyright (c) 2016 VETOR - Revista de Ciências Exatas e Engenhariasinfo:eu-repo/semantics/openAccessMagalhães, Felipe CostaAlves, Antônio Marcos de LimaDias, Cláudio Renato Rodrigues2016-09-23T01:53:21Zoai:periodicos.furg.br:article/2247Revistahttps://periodicos.furg.br/vetorPUBhttps://periodicos.furg.br/vetor/oaigmplatt@furg.br2358-34520102-7352opendoar:2016-09-23T01:53:21Vetor (Online) - Universidade Federal do Rio Grande (FURG)false
dc.title.none.fl_str_mv APPLICATION OF BAYESIAN METHODOLOGY FOR THE ANALYSIS OF THE FOUNDATIONS OF THE MODERNIZED PIER OF PORTO NOVO (RIO GRANDE, BRAZIL)
Aplicação de metodologia bayesiana na análise das fundações do cais modernizado do porto novo de Rio Grande (RS)
title APPLICATION OF BAYESIAN METHODOLOGY FOR THE ANALYSIS OF THE FOUNDATIONS OF THE MODERNIZED PIER OF PORTO NOVO (RIO GRANDE, BRAZIL)
spellingShingle APPLICATION OF BAYESIAN METHODOLOGY FOR THE ANALYSIS OF THE FOUNDATIONS OF THE MODERNIZED PIER OF PORTO NOVO (RIO GRANDE, BRAZIL)
Magalhães, Felipe Costa
Engenharia
estacas
teorema de bayes
title_short APPLICATION OF BAYESIAN METHODOLOGY FOR THE ANALYSIS OF THE FOUNDATIONS OF THE MODERNIZED PIER OF PORTO NOVO (RIO GRANDE, BRAZIL)
title_full APPLICATION OF BAYESIAN METHODOLOGY FOR THE ANALYSIS OF THE FOUNDATIONS OF THE MODERNIZED PIER OF PORTO NOVO (RIO GRANDE, BRAZIL)
title_fullStr APPLICATION OF BAYESIAN METHODOLOGY FOR THE ANALYSIS OF THE FOUNDATIONS OF THE MODERNIZED PIER OF PORTO NOVO (RIO GRANDE, BRAZIL)
title_full_unstemmed APPLICATION OF BAYESIAN METHODOLOGY FOR THE ANALYSIS OF THE FOUNDATIONS OF THE MODERNIZED PIER OF PORTO NOVO (RIO GRANDE, BRAZIL)
title_sort APPLICATION OF BAYESIAN METHODOLOGY FOR THE ANALYSIS OF THE FOUNDATIONS OF THE MODERNIZED PIER OF PORTO NOVO (RIO GRANDE, BRAZIL)
author Magalhães, Felipe Costa
author_facet Magalhães, Felipe Costa
Alves, Antônio Marcos de Lima
Dias, Cláudio Renato Rodrigues
author_role author
author2 Alves, Antônio Marcos de Lima
Dias, Cláudio Renato Rodrigues
author2_role author
author
dc.contributor.author.fl_str_mv Magalhães, Felipe Costa
Alves, Antônio Marcos de Lima
Dias, Cláudio Renato Rodrigues
dc.subject.por.fl_str_mv Engenharia
estacas
teorema de bayes
topic Engenharia
estacas
teorema de bayes
description The aim of this work is to present the application of a procedure for updating the predictions of the bearing capacity of the piles, by using the driving data measured during the execution process. The updating is obtained through the application of the concepts of the Bayesian analysis. The uncertainty of the parameters is modeled by an "a priori" and an “a posteriori" probability distribution. The "a priori" distribution is obtained through semi-empirical methods for predicting the bearing capacity of piles based on Standard Penetration Test results. The construction of the “a posteriori" distribution is made by the updating of the “a priori” distribution, using a function of maximum likelihood based on data from driving registries. The procedure has been applied on a pile job, part of the project of a new pier at Porto Novo, in Rio Grande (RS).
publishDate 2016
dc.date.none.fl_str_mv 2016-09-22
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/2247
url https://periodicos.furg.br/vetor/article/view/2247
dc.language.iso.fl_str_mv por
language por
dc.relation.none.fl_str_mv https://periodicos.furg.br/vetor/article/view/2247/3804
dc.rights.driver.fl_str_mv Copyright (c) 2016 VETOR - Revista de Ciências Exatas e Engenharias
info:eu-repo/semantics/openAccess
rights_invalid_str_mv Copyright (c) 2016 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. 24 No. 1 (2014); 66-81
VETOR - Revista de Ciências Exatas e Engenharias; v. 24 n. 1 (2014); 66-81
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
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