Please use this identifier to cite or link to this item: http://hdl.handle.net/1822/42348

TitleProbabilistic-based assessment of composite steel-concrete structures through an innovative framework
Author(s)Matos, José C.
Valente, Isabel B.
Cruz, Paulo J. S.
Moreira, Vicente Novo
KeywordsProbabilistic-based assessment
Uncertainty sources
Model identification
Reliability assessment
Bayesian inference
Composite steel-concrete structures
Issue date2016
PublisherTechno Press
JournalSteel and Composite Structures
Abstract(s)This paper presents the probabilistic-based assessment of composite steel-concrete structures through an innovative framework. This framework combines model identification and reliability assessment procedures. The paper starts by describing current structural assessment algorithms and the most relevant uncertainty sources. The developed model identification algorithm is then presented. During this procedure, the model parameters are automatically adjusted, so that the numerical results best fit the experimental data. Modelling and measurement errors are respectively incorporated in this algorithm. The reliability assessment procedure aims to assess the structure performance, considering randomness in model parameters. Since monitoring and characterization tests are common measures to control and acquire information about those parameters, a Bayesian inference procedure is incorporated to update the reliability assessment. The framework is then tested with a set of composite steel-concrete beams, which behavior is complex. The experimental tests, as well as the developed numerical model and the obtained results from the proposed framework, are respectively present.
TypeArticle
URIhttp://hdl.handle.net/1822/42348
DOI10.12989/scs.2016.20.6.1345
ISSN1229-9367
e-ISSN1598-6233
Peer-Reviewedyes
AccessRestricted access (UMinho)
Appears in Collections:EA - Artigos
ISISE - Artigos em Revistas Internacionais
Lab2PT - Artigos
Lab2PT - Artigos

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