Hybrid non-destructive evaluation methods for characterizing chloride-induced corrosion in concrete
This paper aims to describe a GPR-based phase characterization model for characterizing various phases of invisible chloride contamination, active corrosion and cracks/delamination in reinforced concrete (RC) structures. The works are divided into two parts: (1) fieldworks of two 30+ year old RC sla...
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Published in | NDT & E international : independent nondestructive testing and evaluation Vol. 107; p. 102123 |
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Main Authors | , , , |
Format | Journal Article |
Language | English |
Published |
Elsevier Ltd
01.10.2019
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Online Access | Get full text |
ISSN | 0963-8695 1879-1174 |
DOI | 10.1016/j.ndteint.2019.05.008 |
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Summary: | This paper aims to describe a GPR-based phase characterization model for characterizing various phases of invisible chloride contamination, active corrosion and cracks/delamination in reinforced concrete (RC) structures. The works are divided into two parts: (1) fieldworks of two 30+ year old RC slab exposed to abrasive tidal seawater, and (2) laboratory specimens of 4 exposure conditions subject to accelerated corrosion in 94 days. The very different spatial amplitude distribution of the former is verified by the temporal and continuous measurement of the latter. Results show that abnormally low or high amplitude of radar signals are indications of chloride contamination or delamination phase of a corrosion model, respectively. The analysis proves that RC deterioration can be imaged and modelled via GPR by identifying the highest (cracks/delamination) and lowest amplitude (chloride contamination) through certain thresholds established in this paper. The thresholds in both field works and lab’s RC specimens were further collectively used to convert the amplitude values to health indicators of the RC structure in the fieldwork. The methodology, analysis and the corrosion phase characterization will pave the way for large-scale, completely noninvasive, and efficient imaging and diagnosis of RC structures. |
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ISSN: | 0963-8695 1879-1174 |
DOI: | 10.1016/j.ndteint.2019.05.008 |