Monitoring Corrosion of Steel Bars in Reinforced Concrete based on Helix Strains Measured from a Distributed Fiber Optic Sensor


Corrosion of steel bars compromises the safety and service life of reinforced concrete structures. This study develops an in-situ corrosion monitoring method for reinforced concrete with a distributed fiber optic sensor through experimentation. Reinforced concrete beams instrumented with distributed fiber optic sensors were prepared. A constant current was impressed to the beams immersed in a NaCl solution for accelerated corrosion. The distributed fiber optic sensor was deployed in a helix pattern on the steel bar to measure expansive strains generated by corrosion of the steel bar. The corrosion process of the steel bar was assessed in an electrochemical test. The strain measured from the sensor was utilized to evaluate the volume of the corrosion products surrounding the steel bars and predict the cracking of the concrete cover. To investigate the deterioration process of reinforced concrete, different levels of concrete cover thickness (28 mm, 35 mm, and 43 mm) and water-to-cement ratio (0.4, 0.5, and 0.6) were studied. The relationship between the mass loss of steel bars and the volume of corrosion products is established to provide a method for evaluating the effects of steel corrosion on the deterioration of reinforced concrete.


Civil, Architectural and Environmental Engineering

Research Center/Lab(s)

INSPIRE - University Transportation Center


This study was partially funded by the U.S. National Science Foundation [Grant No. CMMI-1235202 ], the U.S. Department of Transportation [Grant No. 693JK31950008CAAP ], and Stevens Institute of Technology through the BRIDGING and SPRINT Awards of the School of Engineering and Science.

Keywords and Phrases

Corrosion; Crack; Distributed fiber optic sensors; In-situ condition assessment; Interactive defects; Mass loss; Reinforced concrete; Steel–concrete interface; Structural health monitoring

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Document Type

Article - Journal

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© 2020 Elsevier Ltd, All rights reserved.

Publication Date

01 Feb 2020