APPLICATION OF BAYESIAN METHODOLOGY FOR THE ANALYSIS OF THE FOUNDATIONS OF THE MODERNIZED PIER OF PORTO NOVO (RIO GRANDE, BRAZIL)
Autor(a) principal: | |
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Data de Publicação: | 2016 |
Outros Autores: | , |
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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Vetor (Online) |
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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 |
_version_ |
1797041761231568896 |