Back analysis of geomechanical parameters in underground works using an evolution strategy algorithm
Autor(a) principal: | |
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Data de Publicação: | 2013 |
Outros Autores: | , , , , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
Texto Completo: | http://hdl.handle.net/1822/22320 |
Resumo: | The purpose of this work is to evaluate the performance of an optimization algorithm from the field of evolutionary computation, namely an Evolution Strategy, in back analysis of geomechanical parameters in underground structures. This analysis was carried out through a parametric study of a synthetic case of a tunnel construction. Different combinations of parameters and measurements were carried out to test the performance of the algorithm. In order to have a comparison base for its performance also three classical optimization algorithms based on the gradient of the error function and a Genetic Algorithm were used. It was concluded that the Evolution Strategy algorithm presents interesting capabilities in terms of robustness and efficiency allowing the mitigation of some of the limitations of the classical algorithms. Moreover a back analysis study of geomechanical parameters using real monitoring data and a 3D numerical model of a hydraulic underground structure being built in the North of Portugal was performed using the Evolution Strategy algorithm, in order to reduce the uncertainties about the parameters evaluated by in situ and laboratory tests. It was verified that the low quantity of monitoring data available hinders the possibility to identify the parameters of interest. The existence of information of only one additional extensometer perpendicular to the existing one would allow this identification to succeed. |
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Back analysis of geomechanical parameters in underground works using an evolution strategy algorithmUnderground structuresGeomechanical parametersEvolution Strategy algorithmScience & TechnologyThe purpose of this work is to evaluate the performance of an optimization algorithm from the field of evolutionary computation, namely an Evolution Strategy, in back analysis of geomechanical parameters in underground structures. This analysis was carried out through a parametric study of a synthetic case of a tunnel construction. Different combinations of parameters and measurements were carried out to test the performance of the algorithm. In order to have a comparison base for its performance also three classical optimization algorithms based on the gradient of the error function and a Genetic Algorithm were used. It was concluded that the Evolution Strategy algorithm presents interesting capabilities in terms of robustness and efficiency allowing the mitigation of some of the limitations of the classical algorithms. Moreover a back analysis study of geomechanical parameters using real monitoring data and a 3D numerical model of a hydraulic underground structure being built in the North of Portugal was performed using the Evolution Strategy algorithm, in order to reduce the uncertainties about the parameters evaluated by in situ and laboratory tests. It was verified that the low quantity of monitoring data available hinders the possibility to identify the parameters of interest. The existence of information of only one additional extensometer perpendicular to the existing one would allow this identification to succeed.Fundação para a Ciência e a Tecnologia (FCT)ElsevierUniversidade do MinhoMoreira, Nuno Ricardo VilaçaMiranda, Tiago F. S.Pinheiro, Marisa MotaFernandes, Pedro Miguel GomesDias, DanielCosta, L.Sena-Cruz, José2013-012013-01-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttp://hdl.handle.net/1822/22320eng0886-779810.1016/j.tust.2012.08.011http://www.sciencedirect.com/science/article/pii/S088677981200154Xinfo:eu-repo/semantics/openAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2023-07-21T12:34:48Zoai:repositorium.sdum.uminho.pt:1822/22320Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-19T19:30:33.507396Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse |
dc.title.none.fl_str_mv |
Back analysis of geomechanical parameters in underground works using an evolution strategy algorithm |
title |
Back analysis of geomechanical parameters in underground works using an evolution strategy algorithm |
spellingShingle |
Back analysis of geomechanical parameters in underground works using an evolution strategy algorithm Moreira, Nuno Ricardo Vilaça Underground structures Geomechanical parameters Evolution Strategy algorithm Science & Technology |
title_short |
Back analysis of geomechanical parameters in underground works using an evolution strategy algorithm |
title_full |
Back analysis of geomechanical parameters in underground works using an evolution strategy algorithm |
title_fullStr |
Back analysis of geomechanical parameters in underground works using an evolution strategy algorithm |
title_full_unstemmed |
Back analysis of geomechanical parameters in underground works using an evolution strategy algorithm |
title_sort |
Back analysis of geomechanical parameters in underground works using an evolution strategy algorithm |
author |
Moreira, Nuno Ricardo Vilaça |
author_facet |
Moreira, Nuno Ricardo Vilaça Miranda, Tiago F. S. Pinheiro, Marisa Mota Fernandes, Pedro Miguel Gomes Dias, Daniel Costa, L. Sena-Cruz, José |
author_role |
author |
author2 |
Miranda, Tiago F. S. Pinheiro, Marisa Mota Fernandes, Pedro Miguel Gomes Dias, Daniel Costa, L. Sena-Cruz, José |
author2_role |
author author author author author author |
dc.contributor.none.fl_str_mv |
Universidade do Minho |
dc.contributor.author.fl_str_mv |
Moreira, Nuno Ricardo Vilaça Miranda, Tiago F. S. Pinheiro, Marisa Mota Fernandes, Pedro Miguel Gomes Dias, Daniel Costa, L. Sena-Cruz, José |
dc.subject.por.fl_str_mv |
Underground structures Geomechanical parameters Evolution Strategy algorithm Science & Technology |
topic |
Underground structures Geomechanical parameters Evolution Strategy algorithm Science & Technology |
description |
The purpose of this work is to evaluate the performance of an optimization algorithm from the field of evolutionary computation, namely an Evolution Strategy, in back analysis of geomechanical parameters in underground structures. This analysis was carried out through a parametric study of a synthetic case of a tunnel construction. Different combinations of parameters and measurements were carried out to test the performance of the algorithm. In order to have a comparison base for its performance also three classical optimization algorithms based on the gradient of the error function and a Genetic Algorithm were used. It was concluded that the Evolution Strategy algorithm presents interesting capabilities in terms of robustness and efficiency allowing the mitigation of some of the limitations of the classical algorithms. Moreover a back analysis study of geomechanical parameters using real monitoring data and a 3D numerical model of a hydraulic underground structure being built in the North of Portugal was performed using the Evolution Strategy algorithm, in order to reduce the uncertainties about the parameters evaluated by in situ and laboratory tests. It was verified that the low quantity of monitoring data available hinders the possibility to identify the parameters of interest. The existence of information of only one additional extensometer perpendicular to the existing one would allow this identification to succeed. |
publishDate |
2013 |
dc.date.none.fl_str_mv |
2013-01 2013-01-01T00:00:00Z |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://hdl.handle.net/1822/22320 |
url |
http://hdl.handle.net/1822/22320 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
0886-7798 10.1016/j.tust.2012.08.011 http://www.sciencedirect.com/science/article/pii/S088677981200154X |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
application/pdf |
dc.publisher.none.fl_str_mv |
Elsevier |
publisher.none.fl_str_mv |
Elsevier |
dc.source.none.fl_str_mv |
reponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação instacron:RCAAP |
instname_str |
Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
instacron_str |
RCAAP |
institution |
RCAAP |
reponame_str |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
collection |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
repository.name.fl_str_mv |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
repository.mail.fl_str_mv |
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1799132809837674496 |