Abstract
The paper presents an investigation into the durability of functionalized carbon structures (FCS) in a highly alkaline concrete environment. First, the suitability of optical fibers with different coatings—i.e., acrylate, polyimide, or carbon—for the FCS was investigated by subjecting fibers with different coatings to micro/macro bending and a 5% sodium hydroxide (NaOH) (pH 14) solution. Then, the complete FCS was also subjected to a 5% NaOH solution. Finally, the effects of spatial variation of the fiber embedded in the FCS and the bonding strength between the fiber and FCS was evaluated using different configurations —i.e., fiber integrated into FCS in a straight line and/or with offsets. All three coatings passed the micro/macro bending tests and show degradation after alkaline exposure, with the carbon coating showing least degradation. The FCS showed relative stability after exposure to 5% NaOH. The optimum bonding length between the optical fiber and the carbon filament was found to be ≥150 mm for adequate sensitivity.
Highlights
The replacement of conventional techniques used for structural health monitoring (SHM) based on electrical means [1,2] with fiber optic sensors (FOSs) has seen increased popularity over the last decade due to the number of advantages they possess over conventional schemes
The best results were obtained for the two optical glass fibers from OFS (NA = 0.17)
It is assumed that micro defects of the fiber coating of the second fabrication batch caused the degradation of the failure strain
Summary
The replacement of conventional techniques used for structural health monitoring (SHM) based on electrical means (i.e., strain gauges for strain measurement) [1,2] with fiber optic sensors (FOSs) has seen increased popularity over the last decade due to the number of advantages they possess over conventional schemes. The fact that a multitude of sensors can be multiplexed within a single strand of fiber together with the possibility of utilizing a wider bandwidth makes FOSs most suitable for applications that require extraction of data from a vast amount of sensing elements such as those required for SHM of large structures [8,9,10,11,12].
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