Performance of Distributed Optical Fiber Sensors (DOFS) and Digital Image Correlation (DIC) in the monitoring of RC structures

Distributed Optical Fiber Sensors (DOFS) are strain measuring tools whose potential had been discovered in the latest years only, in particular related to the civil engineering field. A unique utility lies in the possibility of bonding these extremely thin sensors (125µm of diameter) to steel reinforcement bars which will later be embedded in Reinforced Concrete (RC) elements in order to monitor its mechanical strains. These measurements encircle the features of reliability, accuracy, completely dist8ributed nature and desired frequency. The present paper presents the results of an experimental campaign developed at UPC´s Structure Technology Laboratory that saw the tensing of two RC tensile members (ties) with DOFSinstrumented steel rebars providing strain readings every 7.5mm. The first of the two members was designed not to crack while the second one yes, giving insight on the steel rebar’s strain profile when surrounded by cracking concrete. The described results are novel in their essence as measurements as accurate, completely-distributed, experimentally extracted, both before and after concrete cracking, have been, up until now, impossible. The internal strain measurements are additionally integrated with an external Digital Image Correlation (DIC) monitoring which provides data on the displacements and strains of the members’ surfaces in order to check the feasibility, reliability and accuracy of both monitoring techniques. The present research represents the beginning of an in-depth experimental campaign aimed at providing reinforcement strain data for multiple loaded RC ties that encompass different geometrical features (concrete cover, reinforcement ratio, bar diameter and more). This is fundamental for an improved understanding of phenomenon that rely on the knowledge of steel strains (such as steel-concrete bond and tension stiffening) which have always resorted to theoretical, empirical or numerical solutions.

Postprint (published version)