Please use this identifier to cite or link to this item: http://hdl.handle.net/1822/39548

TitleAn innovative framework for probabilistic-based structural assessment with an application to existing reinforced concrete structures
Author(s)Matos, José C.
Cruz, Paulo J. S.
Valente, Isabel B.
Neves, Luís C.
Moreira, Vicente Novo
KeywordsStructural assessment
Uncertainty sources
Model identification
Optimization algorithm
Reliability assessment
Bayesian inference
Reinforced concrete structures
Issue date2016
PublisherElsevier
JournalEngineering Structures
Abstract(s)A novel framework for probabilistic-based structural assessment of existing structures, which combines model identification and reliability assessment procedures, considering in an objective way different sources of uncertainty, is presented in this paper. A short description of structural assessment applications, provided in literature, is initially given. Then, the developed model identification procedure, supported in a robust optimization algorithm, is presented. Special attention is given to both experimental and numerical errors, to be considered in this algorithm convergence criterion. An updated numerical model is obtained from this process. The reliability assessment procedure, which considers a probabilistic model for the structure in analysis, is then introduced, incorporating the results of the model identification procedure. The developed model is then updated, as new data is acquired, through a Bayesian inference algorithm, explicitly addressing statistical uncertainty. Finally, the developed framework is validated with a set of reinforced concrete beams, which were loaded up to failure in laboratory.
TypeArticle
URIhttp://hdl.handle.net/1822/39548
DOI10.1016/j.engstruct.2015.12.040
ISSN0141-0296
Peer-Reviewedyes
AccessRestricted access (UMinho)
Appears in Collections:EA - Artigos
ISISE - Artigos em Revistas Internacionais
Lab2PT - Artigos
Lab2PT - Artigos

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