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Get Free AccessCorrosion is one of the most frequently occurring problems in reinforced concrete (RC) structures. The formation of rust products results in deterioration processes that decrease the durability and structural capacity. Therefore, frequent inspection and monitoring of corrosion damage play a vital role in establishing reliable asset management of civil structures. Vibration-based monitoring (VBM) is particularly useful in studying the global response of a deteriorated structure, since a change in modal characteristics may indicate damage. Although VBM has already been studied thoroughly, a systematic understanding of how corrosion contributes to the changes in modal characteristics is still lacking. In this study, an overview and assessment of the existing literature for dynamic tests on corroded RC beams is provided, aiming to give a critical review of the current knowledge, possibilities and challenges related to this topic. Moreover, this study presents additional data from two test programmes, which enable to point out the challenges in VBM of corroding RC beams. The experimental test programmes include two locally corroded beams and three uniformly corroded beams, as well as non-corroding reference beams. For high corrosion levels, the natural frequencies of beams reported in the literature, as well as the beams of the test programmes, decreased. However, comparison with a non-corroding reference beam proved to be essential to eliminate the influence of other non-negligible factors such as creep and shrinkage. Other modal characteristics, such as the damping ratio and mode shapes, are found to be less sensitive to monitor uniform or local corrosion in RC beams.
Eline Vandecruys, Eline Vereecken, Dimitrios Anastasopoulos, Els Verstrynge, Robby Caspeele, Edwin Reynders, Geert Lombaert (2023). Challenges in assessing corrosion damage in reinforced concrete beams by vibration-based monitoring: literature analysis and experimental study. Structural Health Monitoring, 22(6), pp. 4233-4251, DOI: 10.1177/14759217231159321.
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Type
Article
Year
2023
Authors
7
Datasets
0
Total Files
0
Language
English
Journal
Structural Health Monitoring
DOI
10.1177/14759217231159321
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