NSM CFRP laminates for shear strengthening of RC beams : tests and mechanical model

The application of Carbon Fiber Reinforced Polymer (CFRP) strips according to the Near Surface Mounted (NSM) technique has proven to be a promising shear strengthening strategy for RC beams, in terms of effectiveness and executability. Nevertheless, several aspects concerning the underlying resistin...

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Detalhes bibliográficos
Autor principal: Barros, Joaquim A. O. (author)
Outros Autores: Bianco, V. (author), Monti, G. (author)
Formato: article
Idioma:eng
Publicado em: 2009
Assuntos:
Texto completo:http://hdl.handle.net/1822/13510
País:Portugal
Oai:oai:repositorium.sdum.uminho.pt:1822/13510
Descrição
Resumo:The application of Carbon Fiber Reinforced Polymer (CFRP) strips according to the Near Surface Mounted (NSM) technique has proven to be a promising shear strengthening strategy for RC beams, in terms of effectiveness and executability. Nevertheless, several aspects concerning the underlying resisting mechanisms and their mechanical interpretation still need to be clarified and organized in a comprehensive model. By a critical overview of the relevant research findings available to date in the analytical modeling domain, it emerges that most of the efforts carried out are mainly devoted to quantify parameters related to the NSM debonding failure mechanism, on the basis of test set-ups whose geometry often greatly differs from the actual conditions met in a common T-cross section beam. To give some contribution for the discussion of these subjects, an experimental program was carried out, on T-beams of quasi-real scale and with a given ratio of existing steel stirrups. The main results are presented and analyzed in the present work. In the second part of this work, a new analytical predictive model is proposed. It assumes as possible failure mechanisms: debonding, tensile rupture of the strip and the concrete tensile fracture and allows the interaction between strips to be accounted for. The comparison between the results determined by the application of the proposed model and those obtained from experimental research reveals the high predictive accuracy of this model.