EGU25-10960, updated on 15 Mar 2025
https://doi.org/10.5194/egusphere-egu25-10960
EGU General Assembly 2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
Oral | Wednesday, 30 Apr, 09:20–09:30 (CEST)
 
Room -2.15
Challenges in Detecting Thin Asphalt Layers Using GPR
Andreas Loizos1, Christina Plati2, and Alexandros Mouzakis3
Andreas Loizos et al.
  • 1Department of Transportation Planning and Engineering, National Technical University of Athens (NTUA), Athens, Greece (aloizos@central.ntua.gr)
  • 2Laboratory of Pavement Engineering, National Technical University of Athens (NTUA), Athens, Greece (cplati@central.ntua.gr)
  • 3Laboratory of Pavement Engineering, National Technical University of Athens (NTUA), Athens, Greece (amouzakis@mail.ntua.gr)

Ground Penetrating Radar (GPR) is a valuable tool in transportation infrastructure surveys that has evolved alongside the advancements in global technology. As a Non-Destructive Testing (NDT) technique, GPR is mainly utilized for pavement investigations and has been successfully used to assess the thickness in pavement engineering. However, despite its many years of use and improvements, there is still one major issue: how effectively can GPR detect thin asphalt layers? This challenge, commonly referred to as the "thin layer problem" according to the international literature, arises from the fact that it is difficult to detect reflections from thin layers. The main issue is the possible overlap of bottom and surface reflections, which makes accurate detection difficult.

The present research study addresses the accuracy requirements associated with using high frequency GPR antennas to identify and measure the thickness of thin asphalt layers. A key feature of this research is the proposed methodology, which provides a simple and effective approach to processing GPR data from thin asphalt layers to accurately detect their thickness. The methodology was validated using field data based on a highway section where rehabilitation works were carried out in conjunction with a newly constructed asphalt surface course. The estimated thickness of the thin layer showed an acceptable margin of error compared to the core sample measurements.

Overall, the results demonstrate the robustness and adaptability of GPR for quality assurance and quality control purposes, even in complex environments. In summary, GPR is a powerful tool that paves the way for more efficient pavement infrastructure management.

How to cite: Loizos, A., Plati, C., and Mouzakis, A.: Challenges in Detecting Thin Asphalt Layers Using GPR, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-10960, https://doi.org/10.5194/egusphere-egu25-10960, 2025.