Probability Analysis of Embankment on Soft Soil

Detalhes bibliográficos
Autor(a) principal: Falcão, Patrícia Rodrigues
Data de Publicação: 2021
Outros Autores: Fagundes, Diego de Freitas, Alves, Antônio Marcos de Lima
Tipo de documento: Artigo
Idioma: por
Título da fonte: Vetor (Online)
Texto Completo: https://periodicos.furg.br/vetor/article/view/12905
Resumo: No model correctly predicts a given system's reality, so that the engineering calculations have uncertainties, which may cause several kinds of errors. The constructions on soft clay deposits present a high difficulty due to such soil's high compressibility and low resistance. The geotechnical designs of embankments on soft soils are traditionally analyzed using a global safety factor obtained through deterministic methods, not incorporating the calculation's inherent uncertainties. On the other hand, the probabilistic approach makes it possible to quantify the uncertainties arising from the parameters' variability and the more comprehensive assessment of the expected safety level for the work through the probability of failure. In this way, it is possible to untie the idea that high safety factor values always guarantee safer projects. In this context, this study aims to compare the solutions obtained by the Probabilistic Methods of Rosenblueth, Monte Carlo, Latin Hypercube, and First Order Second Moment (FOSM), in addition to evaluating the results by means of a deterministic approach using the methods of Bishop Simplified, Janbu Simplified, Spencer and Morgenstern & Price. Stability analyses were performed using the Slide v.6 computational tool. The analyses show the importance of introducing the coefficient of variation in the parameters since the uncertainty directly affects the level of performance expected for the work.
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spelling Probability Analysis of Embankment on Soft SoilAnálise Probabilística de Aterro sobre Solos MolesSolos molesMétodos DeterminísticosMétodos ProbabilísticosProbabilidade de FalhaSoft soilDeterministic MethodsProbabilistic MethodsFailure ProbabilityNo model correctly predicts a given system's reality, so that the engineering calculations have uncertainties, which may cause several kinds of errors. The constructions on soft clay deposits present a high difficulty due to such soil's high compressibility and low resistance. The geotechnical designs of embankments on soft soils are traditionally analyzed using a global safety factor obtained through deterministic methods, not incorporating the calculation's inherent uncertainties. On the other hand, the probabilistic approach makes it possible to quantify the uncertainties arising from the parameters' variability and the more comprehensive assessment of the expected safety level for the work through the probability of failure. In this way, it is possible to untie the idea that high safety factor values always guarantee safer projects. In this context, this study aims to compare the solutions obtained by the Probabilistic Methods of Rosenblueth, Monte Carlo, Latin Hypercube, and First Order Second Moment (FOSM), in addition to evaluating the results by means of a deterministic approach using the methods of Bishop Simplified, Janbu Simplified, Spencer and Morgenstern & Price. Stability analyses were performed using the Slide v.6 computational tool. The analyses show the importance of introducing the coefficient of variation in the parameters since the uncertainty directly affects the level of performance expected for the work.Nenhum modelo prevê perfeitamente a realidade de um determinado sistema; consequentemente, os cálculos em engenharia têm incertezas, que, por conseguinte vão repercutir diretamente em erros de diversos tipos. Em especial, as obras sobre depósitos de argilas moles apresentam uma alta dificuldade devido ao comportamento caracterizado por elevada compressibilidade e baixa resistência desse solo. Os projetos geotécnicos de aterros sobre solos moles são tradicionalmente analisados por intermédio de um fator de segurança global obtido por meio de métodos determinísticos, não incorporando as incertezas inerentes no cálculo. Já a abordagem probabilística possibilita a quantificação das incertezas oriundas da variabilidade dos parâmetros, bem como a avaliação mais abrangente do nível de segurança esperado para a obra através da probabilidade de falha. Desse modo, é possível desvincular a ideia que altos valores de fator de segurança sempre garantem projetos mais seguros. Neste contexto, o presente estudo tem como objetivo comparar as soluções obtidas pelos Métodos Probabilísticos de Rosenblueth, Monte Carlo, Hipercubo Latino e First Order Second Moment (FOSM), além de avaliar os resultados pela abordagem determinística pelos métodos de Bishop Simplificado, Janbu Simplificado, Spencer e Morgenstern & Price. As análises referentes a estabilidade foram realizadas com o auxílio da ferramenta computacional Slide v.6. Os resultados oriundos das análises evidenciam a importância da inserção do coeficiente de variação nos parâmetros, já que a incerteza repercute diretamente no nível de desempenho esperado para a obra.Universidade Federal do Rio Grande2021-04-22info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdfhttps://periodicos.furg.br/vetor/article/view/1290510.14295/vetor.v30i1.12905VETOR - Journal of Exact Sciences and Engineering; Vol. 30 No. 1 (2020); 38-48VETOR - Revista de Ciências Exatas e Engenharias; v. 30 n. 1 (2020); 38-482358-34520102-7352reponame:Vetor (Online)instname:Universidade Federal do Rio Grande (FURG)instacron:FURGporhttps://periodicos.furg.br/vetor/article/view/12905/8678Copyright (c) 2021 VETOR - Revista de Ciências Exatas e Engenhariasinfo:eu-repo/semantics/openAccessFalcão, Patrícia Rodrigues Fagundes, Diego de Freitas Alves, Antônio Marcos de Lima2021-08-05T21:46:16Zoai:periodicos.furg.br:article/12905Revistahttps://periodicos.furg.br/vetorPUBhttps://periodicos.furg.br/vetor/oaigmplatt@furg.br2358-34520102-7352opendoar:2021-08-05T21:46:16Vetor (Online) - Universidade Federal do Rio Grande (FURG)false
dc.title.none.fl_str_mv Probability Analysis of Embankment on Soft Soil
Análise Probabilística de Aterro sobre Solos Moles
title Probability Analysis of Embankment on Soft Soil
spellingShingle Probability Analysis of Embankment on Soft Soil
Falcão, Patrícia Rodrigues
Solos moles
Métodos Determinísticos
Métodos Probabilísticos
Probabilidade de Falha
Soft soil
Deterministic Methods
Probabilistic Methods
Failure Probability
title_short Probability Analysis of Embankment on Soft Soil
title_full Probability Analysis of Embankment on Soft Soil
title_fullStr Probability Analysis of Embankment on Soft Soil
title_full_unstemmed Probability Analysis of Embankment on Soft Soil
title_sort Probability Analysis of Embankment on Soft Soil
author Falcão, Patrícia Rodrigues
author_facet Falcão, Patrícia Rodrigues
Fagundes, Diego de Freitas
Alves, Antônio Marcos de Lima
author_role author
author2 Fagundes, Diego de Freitas
Alves, Antônio Marcos de Lima
author2_role author
author
dc.contributor.author.fl_str_mv Falcão, Patrícia Rodrigues
Fagundes, Diego de Freitas
Alves, Antônio Marcos de Lima
dc.subject.por.fl_str_mv Solos moles
Métodos Determinísticos
Métodos Probabilísticos
Probabilidade de Falha
Soft soil
Deterministic Methods
Probabilistic Methods
Failure Probability
topic Solos moles
Métodos Determinísticos
Métodos Probabilísticos
Probabilidade de Falha
Soft soil
Deterministic Methods
Probabilistic Methods
Failure Probability
description No model correctly predicts a given system's reality, so that the engineering calculations have uncertainties, which may cause several kinds of errors. The constructions on soft clay deposits present a high difficulty due to such soil's high compressibility and low resistance. The geotechnical designs of embankments on soft soils are traditionally analyzed using a global safety factor obtained through deterministic methods, not incorporating the calculation's inherent uncertainties. On the other hand, the probabilistic approach makes it possible to quantify the uncertainties arising from the parameters' variability and the more comprehensive assessment of the expected safety level for the work through the probability of failure. In this way, it is possible to untie the idea that high safety factor values always guarantee safer projects. In this context, this study aims to compare the solutions obtained by the Probabilistic Methods of Rosenblueth, Monte Carlo, Latin Hypercube, and First Order Second Moment (FOSM), in addition to evaluating the results by means of a deterministic approach using the methods of Bishop Simplified, Janbu Simplified, Spencer and Morgenstern & Price. Stability analyses were performed using the Slide v.6 computational tool. The analyses show the importance of introducing the coefficient of variation in the parameters since the uncertainty directly affects the level of performance expected for the work.
publishDate 2021
dc.date.none.fl_str_mv 2021-04-22
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/12905
10.14295/vetor.v30i1.12905
url https://periodicos.furg.br/vetor/article/view/12905
identifier_str_mv 10.14295/vetor.v30i1.12905
dc.language.iso.fl_str_mv por
language por
dc.relation.none.fl_str_mv https://periodicos.furg.br/vetor/article/view/12905/8678
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. 1 (2020); 38-48
VETOR - Revista de Ciências Exatas e Engenharias; v. 30 n. 1 (2020); 38-48
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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