NSM CFRP Strips for Shear Strengthening of RC Beams: Tests and Mechanical Model
J. A. O. Barros*, 1, Vincenzo Bianco 2, Giorgio Monti 3
Identifiers and Pagination:Year: 2009
First Page: 12
Last Page: 32
Publisher Id: TOBCTJ-3-12
Article History:Received Date: 28/08/2008
Revision Received Date: 9/10/2008
Acceptance Date: 9/10/2008
Electronic publication date: 9/3/2009
Collection year: 2009
open-access license: This is an open access article licensed under the terms of the Creative Commons Attribution-Non-Commercial 4.0 International Public License (CC BY-NC 4.0) (https://creativecommons.org/licenses/by-nc/4.0/legalcode), which permits unrestricted, non-commercial use, distribution and reproduction in any medium, provided the work is properly cited.
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.