Distributed Sensing (DOFS) in Reinforced Concrete members for reinforcement strain monitoring, crack detection and bond-slip calculation

Distributed Optical Fiber Sensors (DOFS) are novel and increasingly popular strain monitoring tools recently applied to the Structural Health Monitoring (SHM) of Reinforced Concrete (RC) structures. Up to now, most applications have seen the instrumenting of the latter’s external surfaces yet, in few circumstances, this technique has also been adopted with the scope of measuring the strains present on the embedded reinforcement bars (rebars). Before the advent of DOFS, due to the lack of tools able to perform such investigation in an accurate, completely-distributed and un-intrusive fashion, structural analyses that rely on the knowledge of the rebars’ strains (such as tension stiffening) have always resorted to theoretical, empirical or numerical solutions. Yet, with the potential provided by DOFS, such insight is finally acquirable and represents the start of a new way of understanding the composite behavior of RC structures. The experimental campaign, topic of the present article, intends on taking full advantage of such potential to study the bond stress and slip present on the surface between concrete and steel rebars in differently sized cracking and non-cracking RC tensile members. These are key parameters for the development of any stress transfer approach-based RC structures’ serviceability analysis, thus the importance of using DOFS for this novel application. The DOFS extracted bond/slip laws are further compared with the Model Code 2010’s predictions and seems to provide consistently higher bond stresses per similar slip than the latter.

The study was performed within project No. 09.3.3-LMT-K-712-01-0145 that has received funding from European Social Fund under grant agreement with the Research Council of Lithuania (LMTLT). Furthermore, the authors acknowledge the help of COTCA Asistencia Técnica, Patología y Control de Calidad for the contribution provided in lending the OBR ODiSI-A machine.

Peer Reviewed

Postprint (author's final draft)