Defect Recognition: Applying Time-Lapse GPR Measurements and Numerical Approaches
Roads are critical components of infrastructure, and assessing their quality is essential to ensure the safe transport of people and goods, which in turn supports economic prosperity. Various factors, such as subsurface conditions, moisture content, and temperature, influence road performance and ca...
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MDPI AG
2025-01-01
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| author | Enas Abdelsamei Diaa Sheishah Mohamed Aldeep Csaba Tóth György Sipos |
| author_facet | Enas Abdelsamei Diaa Sheishah Mohamed Aldeep Csaba Tóth György Sipos |
| author_sort | Enas Abdelsamei |
| collection | DOAJ |
| description | Roads are critical components of infrastructure, and assessing their quality is essential to ensure the safe transport of people and goods, which in turn supports economic prosperity. Various factors, such as subsurface conditions, moisture content, and temperature, influence road performance and can degrade their efficiency as transportation networks. While surface road defects can often be identified through visual inspection, information about subsurface extensions, their impact on structural integrity, and potential risks remain concealed. This study aimed to perform a comparative analysis of dielectric permittivity (ε) using time-lapse Ground Penetrating Radar (GPR) measurements on pre- and post-renovated road sections. This study also sought to evaluate the effectiveness of this approach for road assessment and to employ forward modeling for a deeper understanding of road defects and their associated hazards. Results revealed that the pre-renovated road section exhibited significant fluctuations in dielectric values, ranging from 3.13 to 15.9. In contrast, the post-renovated section showed consistent values within a narrow range of 5 to 6.6. Different crack types were classified, and the mean ε for each visually identified crack type was calculated. Despite the higher frequency of transverse cracks compared to other defects, longitudinal cracks exhibited the highest mean dielectric value (~10.3), while alligator cracks had the lowest (~8.33). Numerical simulations facilitated accurate interpretation of the defects identified in the road section, providing insights into their nature and associated risks. The methodology used for crack classification and numerical simulation can be applied to other road sections globally, offering a standardized approach to road assessment and maintenance planning. |
| format | Article |
| id | doaj-art-a020f9da80254c6d87d2ddcdac42b2e4 |
| institution | Kabale University |
| issn | 2673-4117 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | MDPI AG |
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| series | Eng |
| spelling | doaj-art-a020f9da80254c6d87d2ddcdac42b2e42025-01-24T13:31:33ZengMDPI AGEng2673-41172025-01-0161510.3390/eng6010005Defect Recognition: Applying Time-Lapse GPR Measurements and Numerical ApproachesEnas Abdelsamei0Diaa Sheishah1Mohamed Aldeep2Csaba Tóth3György Sipos4Department of Geoinformatics, Physical and Environmental Geography, University of Szeged, Egyetem u. 2-6, 6722 Szeged, HungaryDepartment of Geoinformatics, Physical and Environmental Geography, University of Szeged, Egyetem u. 2-6, 6722 Szeged, HungaryNational Research Institute of Astronomy and Geophysics, El Marsad St., Helwan, Cairo 11421, EgyptDepartment of Highway and Railway Engineering, Budapest University of Technology and Economics, Műegyetem Rakpart 3, 1111 Budapest, HungaryDepartment of Geoinformatics, Physical and Environmental Geography, University of Szeged, Egyetem u. 2-6, 6722 Szeged, HungaryRoads are critical components of infrastructure, and assessing their quality is essential to ensure the safe transport of people and goods, which in turn supports economic prosperity. Various factors, such as subsurface conditions, moisture content, and temperature, influence road performance and can degrade their efficiency as transportation networks. While surface road defects can often be identified through visual inspection, information about subsurface extensions, their impact on structural integrity, and potential risks remain concealed. This study aimed to perform a comparative analysis of dielectric permittivity (ε) using time-lapse Ground Penetrating Radar (GPR) measurements on pre- and post-renovated road sections. This study also sought to evaluate the effectiveness of this approach for road assessment and to employ forward modeling for a deeper understanding of road defects and their associated hazards. Results revealed that the pre-renovated road section exhibited significant fluctuations in dielectric values, ranging from 3.13 to 15.9. In contrast, the post-renovated section showed consistent values within a narrow range of 5 to 6.6. Different crack types were classified, and the mean ε for each visually identified crack type was calculated. Despite the higher frequency of transverse cracks compared to other defects, longitudinal cracks exhibited the highest mean dielectric value (~10.3), while alligator cracks had the lowest (~8.33). Numerical simulations facilitated accurate interpretation of the defects identified in the road section, providing insights into their nature and associated risks. The methodology used for crack classification and numerical simulation can be applied to other road sections globally, offering a standardized approach to road assessment and maintenance planning.https://www.mdpi.com/2673-4117/6/1/5dielectric constantground penetrating radarsurface reflectionforward modelingpotential risk |
| spellingShingle | Enas Abdelsamei Diaa Sheishah Mohamed Aldeep Csaba Tóth György Sipos Defect Recognition: Applying Time-Lapse GPR Measurements and Numerical Approaches Eng dielectric constant ground penetrating radar surface reflection forward modeling potential risk |
| title | Defect Recognition: Applying Time-Lapse GPR Measurements and Numerical Approaches |
| title_full | Defect Recognition: Applying Time-Lapse GPR Measurements and Numerical Approaches |
| title_fullStr | Defect Recognition: Applying Time-Lapse GPR Measurements and Numerical Approaches |
| title_full_unstemmed | Defect Recognition: Applying Time-Lapse GPR Measurements and Numerical Approaches |
| title_short | Defect Recognition: Applying Time-Lapse GPR Measurements and Numerical Approaches |
| title_sort | defect recognition applying time lapse gpr measurements and numerical approaches |
| topic | dielectric constant ground penetrating radar surface reflection forward modeling potential risk |
| url | https://www.mdpi.com/2673-4117/6/1/5 |
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