Assessment of Fatigue Life for Corroded Prestressed Concrete Beams Subjected to High-Cycle Fatigue Loading
Publication: Journal of Structural Engineering
Volume 149, Issue 2
Abstract
Millions of in-service concrete bridges around the world are exceeding their design life. Corrosion may lead to a sudden fracture of prestressing steels, and understanding the fatigue behavior of corroded prestressed concrete (PC) bridges is essential. Accordingly, an effective fatigue analytical model for corroded PC beams is needed. In this study, an experimental investigation of the fatigue behavior of corroded PC beams, was carried out. Thirteen PC beams had experienced acceleration corrosion before high-cycle fatigue testing. All beams failed due to fatigue fracture of the corroded tensile steel bars, and three-dimensional laser scanning results indicated that the fracture occurred at the minimum cross sections with a severe corrosion pit. A segmented linear analytical model to evaluate fatigue response and predict fatigue life was developed which considers fatigue irrecoverable plastic strain of concrete, stress concentration, and longitudinal variation in the cross-sectional areas of corroded steel bars. There is an acceptable agreement between the numerical and experimental results of corroded PC beams. The proposed model can reasonably predict the evolution of strains in concrete, corroded prestressing steel, and rebars in PC beams under high-cycle fatigue loading, thereby allowing fatigue life prediction. Further analysis studied the influence of degree of corrosion in prestressing wires/rebars, stress concentration and longitudinal variation in cross-sectional areas of corroded steel bars, load ranges, and partial prestressing ratios (PPRs). It was found that, to reasonably estimate the fatigue life of corroded PC beams, the influence of stress concentration must be considered with the proposed impact factor. A higher corrosion degree, load range, or PPR shortens the fatigue life of corroded PC beams.
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Data Availability Statement
Some or all data, models, or code that support the findings of this study are available from the corresponding author upon reasonable request.
Acknowledgments
This research project was financially supported by the National Natural Science Foundation of China (Grant Nos. 51878486 and 52178163) and the Key R&D Program of Shaanxi Province (Grant No. 2022SF-403).
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Received: May 16, 2022
Accepted: Oct 17, 2022
Published online: Dec 1, 2022
Published in print: Feb 1, 2023
Discussion open until: May 1, 2023
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