TY - GEN
T1 - Detection of Geogrids in Road Pavements Using Ground-Penetrating Radar (GPR)
T2 - 10th International Conference on Maintenance and Rehabilitation of Pavements, MAIREPAV10 2024
AU - Neto, Grigório Ribeiro Soares
AU - Solla, Mercedes
AU - Fernandes, Francisco
AU - Fontul, Simona
AU - Pais, Jorge
N1 - info:eu-repo/grantAgreement/FCT//2023.01948.BD/PT#
Funding Information:
It also received financial support from the STRADAR project (TED2021-130183B-I00) funded by MCIN/AEI/https://doi.org/10.13039/501100011033 and by the \u201CEuropean Union NextGenerationEU/PRTR\u201D. M. Solla gratefully acknowledges grant RYC2019\u2013026604\u2013I funded by MCIN/AEI/https://doi.org/10.13039/501100011033 and \u201CESF Investing in your future\u201D.
Publisher Copyright:
© The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.
PY - 2024
Y1 - 2024
N2 - This study explores the efficient identification of geogrids in road pavements through ground-penetrating radar (GPR) and comprehensive laboratory experiments. Geogrids are crucial in enhancing pavement strength and durability, making their effective detection vital for maintenance and longevity. GPR, based on electromagnetic principles, offers a non-destructive and insightful method for evaluating pavement infrastructure. The literature review underscores the gap in studies specifically addressing geogrid detection using GPR in road pavements, motivating the current research. To fill this void, laboratory experiments were conducted, incorporating fiberglass geogrid into asphalt mixtures. The detailed methodology outlines the preparation, execution, and data acquisition using GPR, emphasizing careful consideration of antenna polarities. Results highlight the visual identification of geogrids using specific treatments on radargrams, demonstrating the effectiveness of GPR in detecting nuances not readily discernible in untreated images. Graphical representations bridge real-world geogrid depictions with radargram simulations, enhancing interpretability. The discussion interprets results, emphasizing the influence of geogrid type and GPR antenna position on detection accuracy. Fiberglass geogrid interference prompts considerations for dielectric properties, crucial for optimizing GPR configurations. Practical implications suggest advantages in detecting specific geogrid types. In conclusion, this study contributes nuanced insights to geogrid detection methodologies, guiding advancements in non-destructive testing for road pavements. The knowledge gained catalyzes innovation in geogrid applications and detection techniques, fostering improved infrastructure management practices.
AB - This study explores the efficient identification of geogrids in road pavements through ground-penetrating radar (GPR) and comprehensive laboratory experiments. Geogrids are crucial in enhancing pavement strength and durability, making their effective detection vital for maintenance and longevity. GPR, based on electromagnetic principles, offers a non-destructive and insightful method for evaluating pavement infrastructure. The literature review underscores the gap in studies specifically addressing geogrid detection using GPR in road pavements, motivating the current research. To fill this void, laboratory experiments were conducted, incorporating fiberglass geogrid into asphalt mixtures. The detailed methodology outlines the preparation, execution, and data acquisition using GPR, emphasizing careful consideration of antenna polarities. Results highlight the visual identification of geogrids using specific treatments on radargrams, demonstrating the effectiveness of GPR in detecting nuances not readily discernible in untreated images. Graphical representations bridge real-world geogrid depictions with radargram simulations, enhancing interpretability. The discussion interprets results, emphasizing the influence of geogrid type and GPR antenna position on detection accuracy. Fiberglass geogrid interference prompts considerations for dielectric properties, crucial for optimizing GPR configurations. Practical implications suggest advantages in detecting specific geogrid types. In conclusion, this study contributes nuanced insights to geogrid detection methodologies, guiding advancements in non-destructive testing for road pavements. The knowledge gained catalyzes innovation in geogrid applications and detection techniques, fostering improved infrastructure management practices.
KW - Geogrid Detection
KW - Ground-Penetrating Radar (GPR)
KW - Image Analysis
KW - Infrastructure Maintenance
KW - Non-Destructive Testing
KW - Road Pavements
UR - http://www.scopus.com/inward/record.url?scp=85200493392&partnerID=8YFLogxK
U2 - 10.1007/978-3-031-63584-7_22
DO - 10.1007/978-3-031-63584-7_22
M3 - Conference contribution
AN - SCOPUS:85200493392
SN - 9783031635830
T3 - Lecture Notes in Civil Engineering
SP - 214
EP - 222
BT - Proceedings of the 10th International Conference on Maintenance and Rehabilitation of Pavements - MAIREPAV10 - Volume 2
A2 - Pereira, Paulo
A2 - Pais, Jorge
PB - Springer Science and Business Media Deutschland GmbH
Y2 - 24 July 2024 through 26 July 2024
ER -