Article Article
Thickness and Density Prediction of Thin Asphalt Concrete Overlay Using GPR

Prediction of thin asphalt overlay thickness and density is challenging due to the ground-penetrating radar (GPR) signal resolution limitation. In this study, a nonlinear optimization approach was developed to analyze GPR signals collected from thin AC overlays to estimate their thickness and density. A finite difference time domain (FDTD) simulation study was conducted to validate the proposed algorithm. The results showed that the accuracy of dielectric constant estimation increased after the nonlinear method was applied. This resulted in a thickness estimation error of less than 1 mm. This study demonstrates that the nonlinear algorithm is an effective approach for estimating thin AC overlay thickness and density from GPR data.

DOI: https://doi.org/10.32548/RS.2018.028

References

 

  • Acott, M.. Thin Hot Mix Asphalt Surfacings (No. IS-110). 1991.
  • Al-Qadi, I. L., & Lahouar, S.. Measuring layer thicknesses with GPR–Theory to practice. Construction and building materials, 19(10), 763-772. 2005.
  • Al-Qadi, I.L., Lahouar, S., & Loulizi, A. Successful application of ground-penetrating radar for quality assurance-quality control of new pavements. Transportation Research Record: Journal of the Transportation Research Board, (1861), 86-97. 2003.
  • Zhao, S., & Al-Qadi, I. L. Development of an analytic approach utilizing the extended common midpoint method to estimate asphalt pavement thickness with 3-D ground-penetrating radar. NDT & E International, 78, 29-36. 2016.
  • Zhao, S., Shangguan, P., & Al-Qadi, I. L. Application of regularized deconvolution technique for predicting pavement thin layer thicknesses from ground penetrating radar data. NDT & E International, 73, 1-7. 2015.
  • Zhao, S., & Al-Qadi, I. L. Development of regularization methods on simulated ground-penetrating radar signals to predict thin asphalt overlay thickness. Signal Processing, 132, 261-271. 2017.
  • Lahouar, S. and Al-Qadi, I.L. Automatic detection of multiple pavement layers from GPR data. NDT & E International, 41(2), 69-81. 2008.
  • Leng, Z., Al-Qadi, I., Shangguan, P., & Son, S. Field Application of Ground-Penetrating Radar for Measurement of Asphalt Mixture Density: Case Study of Illinois Route 72 Overlay. Transportation Research Record: Journal of the Transportation Research Board, (2304), 133-141. 2012.
  • Leng, Z., Al-Qadi, I.L., and Lahouar, S. "Development and validation for in situ asphalt mixture density prediction models." NDT & E International 44(4), 369-375. 2011.
  • Saarenketo, T. Using ground-penetrating radar and dielectric probe measurements in pavement density quality control. Transportation Research Record: Journal of the Transportation Research Board, (1575), 34-41. 1997.
  • Lahouar, S., Al-Qadi, I., Loulizi, A., Clark, T., & Lee, D. Approach to determining in situ dielectric constant of pavements: development and implementation at interstate 81 in Virginia. Transportation Research Record: Journal of the Transportation Research Board, (1806), 81-87. 2002.
  • Al-Qadi, I., Leng, Z., Lahouar, S., & Baek, J. In-place hot-mix asphalt density estimation using ground- penetrating radar. Transportation Research Record: Journal of the Transportation Research Board, (2152), 19- 27. 2010.
  • Warren, C., Giannopoulos, A., & Giannakis, I. gprMax: Open source software to simulate electromagnetic wave propagation for ground penetrating radar. Computer Physics Communications, 209, 163-170. 2016.
Metrics
Usage Shares
Total Views
60 Page Views
Total Shares
0 Tweets
60
0 PDF Downloads
0
0 Facebook Shares
Total Usage
60