Non-Destructive Corrosion Inspection of Reinforced Concrete Using Ground-Penetrating Radar: A Review
Abstract
:1. Introduction
2. Methodology
3. Corrosion Monitoring Using Ground-Penetrating Radar
3.1. Laboratory Simulated Corrosion Inspection
3.1.1. Long-Term Corrosion Monitoring
Initiation Phase
Formation of Cracks
Spalling
3.1.2. Conclusions from Laboratory Simulated Corrosion Inspection
3.2. On-Site Corrosion Inspection
3.2.1. Numerical Analysis of GPR Attributes
3.2.2. Visual-Based or Combined Analysis of GPR Attributes
3.2.3. Condition Assessment by Combination of Multiple NDT
3.2.4. Conclusions from the On-Site Corrosion Inspection
4. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
References
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Study | Year | Technique for Accelerated Corrosion Test | Method of Acquiring GPR Attributes | Current Density, i (µA/cm2) | Dimension of Specimens (m) | GPR (GHz) 1 |
---|---|---|---|---|---|---|
Hubbard et al. [16] | 2003 | Impressed current technique | Before and after corrosion acceleration | - | 1.25 × 1 × 0.25 | 1.2 |
Raju et al. [53] | 2018 | - | 0.76 × 0.38 × 0.203 | 2.6 | ||
Zaki et al. [54] | 2018 | - | 1 × 0.5 × 0.2 | 2 | ||
Lai et al. [56] | 2010 | Monitoring during corrosion acceleration | - | 1.5 × 0.5 × 0.5 | 1.5 and 2.6 | |
Zhan et al. [57] | 2011 | 165,000 | 0.45 × 0.14 × 0.135 | 1 | ||
Lai et al. [58] | 2011 | 340 | - | 1.5 and 2.6 | ||
Lai et al. [17] | 2013 | 260 and 760 | 1.5 × 0.5 × 0.5 | 1.5 and 2.6 | ||
Hong et al. [18] | 2014 | 424 | 1.5 × 1.5 × 0.3 | 2.6 | ||
Hong et al. [19] | 2015 | 125 | 0.8 × 0.8 × 0.24 | 2.6 | ||
Wong et al. [20] | 2019 | 650 2 | 0.548 × 0.4 × 0.15 | 2 | ||
Hasan et al. [55] | 2016 | Corroded rebars immersed in emulsion | Before and after corrosion acceleration | - | Water oil emulsions | 2.6 |
Sossa et al. [52] | 2019 | Corroded rebars cast in concrete | - | 0.3 × 0.08 × 0.08 | 1.6 | |
Curing chamber | - | 0.3 × 0.2 × 0.07 |
Study | Year | Other Techniques | GPR (GHz) | Main Findings | |
---|---|---|---|---|---|
Air-Coupled | Ground-Coupled | ||||
Comparison with other NDT | |||||
Barnes et al. [24] | 2000 | HCP, CD | 1 | - | Agreement on spatial distribution of deteriorated areas; 65.1% and 66.2% correctly predicted deteriorated areas compared to HCP and CD, respectively. |
Scott et al. [97] | 2003 | IE, CD | 2.4 | 1.5 | GPR systems could not detect whole delaminated areas. |
Barnes et al. [69] | 2004 | HCP, CD | 1 | - | GPR was effective in predicting damaged areas when the degree of deterioration is between 10% and 50%. |
Rhazi et al. [73] | 2007 | HCP | - | 1.5 | The values for the degree of attenuation were proposed based on the correlation with HCP. |
Barnes et al. [21] | 2008 | HCP, CD | - | 1.5 | The correlation between GPR and HCP and CD was improved after the depth correction. |
Maser et al. [74] | 2012 | HCP, IE, HS | 1 and 2 | 1.5 and 2.6 | The agreement between GPR and HCP was 90.2%, and between GPR and IE was 79.3%. |
Simi et al. [98] | 2012 | IE, CD | - | 2 | Moisture and corrosion maps produced with commercial software showed good spatial agreement with IE and CD. |
Gucunski et al. [91] | 2013 | ER | - | 1.5 | The good agreement between GPR and ER; 95% of the locations where ER ≤ 40 kꭥcm agreed with the location where GPR amplitude was <15 dB. |
Pailes et al. [93] | 2015 | ER, HCP, IE, CD, HS | - | 1.5 | The best spatial agreement compared to different NDT was between GPR and ER, and GPR and sounding techniques (CD and HS). |
Dinh et al. [81] | 2017 | ER, HCP, IE | - | 1.5 | Correlation between GPR and other NDT was determined by a traditional numerical analysis and a method based on comparison with a simulated waveform; better agreement was found using ER and HCP than IE. |
Sun et al. [94] | 2018 | AE, CD | - | 1.5 | GPR showed a larger deteriorated area than AE. GPR detected deteriorated areas near joints, while AE did not. |
Sultan et al. [95] | 2018 | HS, IRT | - | 1.6 | Compared to the IRT, GPR was less accurate in detecting delamination. |
Dinh et al. [92] | 2019 | ER, HCP | - | 1.5 | GPR maps produced by the method based on SAFT showed good correlation with HCP and ER. In one case, the correlation with ER was better than with HCP. |
Combination with other NDT | |||||
Maser [99] | 2009 | GPR, IRT | - | - | The combination of GPR and IRT was effective in condition assessment. The GPR assisted the IRT in detecting deeper delamination. |
Gucunski et al. [23] | 2010 | GPR, ER, HCP, IE, USW | - | 1.5 | This combination of NDT can characterize different levels of deterioration. GPR brought effectiveness in the speed of inspection as the fastest technology from these five. |
Gucunski et al. [100] | 2013 | GPR, ER, IE, USW | - | 2 | GPR deterioration maps were effectively implemented in a robotic system for bridge deck evaluation. |
Alani et al. [101] | 2014 | GPR, deflection and vibration system | - | 2 | GPR results were combined with the deflection and vibration system to create a FEM model; GPR was used to locate rebar and detect cracks and potential moisture areas. |
Kim et al. [102] | 2016 | GPR, ER, IE | - | 2 | GPR results were combined with ER and IE to calculate the condition index for estimation of service life. |
Abu Dabous [103] | 2017 | GPR, IRT | - | 1.6 | Maps obtained with GPR and IRT were overlapped to form areas of possible delamination; the detected area was used to determine the condition rating. |
Omar et al. [104] | 2018 | GPR, IRT | 1 | 1.6 | A method based on the integrated results obtained with GPR and IRT was proposed. |
Ahmed et al. [105] | 2018 | GPR, ER, HCP, IE | - | - | Data fusion model from GPR, ER, HCP and IE maps was developed; fusion was on pixel and feature level. |
Solla et al. [106] | 2019 | GPR, IRT | - | 2.3 | The paper proposes a procedure for anomaly detection based on joint observation of GPR signal and IRT temperature. |
Kilic et al. [107] | 2020 | GPR, IRT, laser distance sensor, camera | - | 2 | The effectiveness of the integrated techniques was demonstrated on a bridge; GPR was used to detect water leakage, large cracks and corrosion. |
Rashidi et al. [108] | 2020 | GPR, ER, HCP, IE, USW | - | 1.5 | The results from NDT were used to determine condition indices calculated using divergence from the ideal distribution using the Jensen–Shannon method. |
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Tešić, K.; Baričević, A.; Serdar, M. Non-Destructive Corrosion Inspection of Reinforced Concrete Using Ground-Penetrating Radar: A Review. Materials 2021, 14, 975. https://doi.org/10.3390/ma14040975
Tešić K, Baričević A, Serdar M. Non-Destructive Corrosion Inspection of Reinforced Concrete Using Ground-Penetrating Radar: A Review. Materials. 2021; 14(4):975. https://doi.org/10.3390/ma14040975
Chicago/Turabian StyleTešić, Ksenija, Ana Baričević, and Marijana Serdar. 2021. "Non-Destructive Corrosion Inspection of Reinforced Concrete Using Ground-Penetrating Radar: A Review" Materials 14, no. 4: 975. https://doi.org/10.3390/ma14040975
APA StyleTešić, K., Baričević, A., & Serdar, M. (2021). Non-Destructive Corrosion Inspection of Reinforced Concrete Using Ground-Penetrating Radar: A Review. Materials, 14(4), 975. https://doi.org/10.3390/ma14040975