Real-Time Density and Thickness Estimation of Thin Asphalt Pavement Overlay During Compaction Using Ground Penetrating Radar Data

Achieving desired density is crucial for thin asphalt concrete (AC) overlay construction quality control and quality assurance purposes. Ground penetrating radar (GPR) can be implemented for AC pavement layer thickness and density prediction during compaction. However, the overlapping of GPR reflections from surface and bottom of the thin AC overlay, as well as the presence of surface moisture, jeopardizes the prediction accuracy. In this study, a pavement model with thin AC overlay was simulated using gprMax, a finite-difference time-domain-based tool. Surface moisture was simulated as a 2-mm film with mixed electrical properties of water and AC. A nonlinear optimization method was used to address the overlapping and surface moisture issues simultaneously. The error of the thin AC overlay dielectric constant and thickness prediction results was less than 7% and 10%, respectively. Field test during thin overlay compaction was also performed to validate the proposed method. The AC overlay thickness and density estimation accuracies were 91% and 99%, respectively.

[1]  Samuel Labi,et al.  Determining the Service Life of Thin Hot-Mix Asphalt Overlay by Means of Different Performance Indicators , 2009 .

[2]  Alfred M. Bruckstein,et al.  The resolution of overlapping echos , 1985, IEEE Trans. Acoust. Speech Signal Process..

[3]  Pedro Romero,et al.  Evaluation of New Nonnuclear Pavement Density Gauges with Data from Field Projects , 2002 .

[4]  Tom Scullion,et al.  AUTOMATED PAVEMENT SUBSURFACE PROFILING USING RADAR: CASE STUDIES OF FOUR EXPERIMENTAL FIELD SITES , 1992 .

[5]  Imad L. Al-Qadi,et al.  MEASURING LAYER THICKNESSES WITH GPR - THEORY TO PRACTICE , 2005 .

[6]  Imad L. Al-Qadi,et al.  Real-Time Monitoring of Asphalt Concrete Pavement Density during Construction using Ground Penetrating Radar: Theory to Practice , 2019, Transportation Research Record: Journal of the Transportation Research Board.

[7]  W. Muller Self-correcting pavement layer depth estimates using 3D multi-offset ground penetrating radar (GPR) , 2014, Proceedings of the 15th International Conference on Ground Penetrating Radar.

[8]  T. Scullion,et al.  Road evaluation with ground penetrating radar , 2000 .

[9]  F. Navarro,et al.  Ground-penetrating radar , 2009 .

[10]  Imad L. Al-Qadi,et al.  Development and validation for in situ asphalt mixture density prediction models , 2011 .

[11]  D. Daniels Ground Penetrating Radar , 2005 .

[12]  Nectaria Diamanti,et al.  A study of GPR vertical crack responses in pavement using field data and numerical modelling , 2010, Proceedings of the XIII Internarional Conference on Ground Penetrating Radar.

[13]  I. Al-Qadi,et al.  Continuous real-time monitoring of flexible pavement layer density and thickness using ground penetrating radar , 2018, NDT & E International.

[14]  Imad L. Al-Qadi,et al.  Prediction of thin asphalt concrete overlay thickness and density using nonlinear optimization of GPR data , 2018, NDT & E International.

[15]  Tom Scullion,et al.  Application of ground-penetrating radar in measuring the density of asphalt pavements and its relationship to mechanical properties , 2016 .

[16]  Imad L. Al-Qadi,et al.  Pavement drainage pipe condition assessment by GPR image reconstruction using FDTD modeling , 2017 .

[17]  David Mata,et al.  Evaluation of non-destructive density determination for QA/QC acceptance testing : research project capsule. , 2017 .

[18]  David E. Newcomb,et al.  Thin Asphalt Overlays for Pavement Preservation , 2009 .

[19]  Imad L. Al-Qadi,et al.  Application of regularized deconvolution technique for predicting pavement thin layer thicknesses from ground penetrating radar data , 2015 .

[20]  Christina Plati,et al.  Accuracy of pavement thicknesses estimation using different ground penetrating radar analysis approaches , 2007 .

[21]  Shan Zhao,et al.  Development of regularization methods on simulated ground-penetrating radar signals to predict thin asphalt overlay thickness , 2017, Signal Process..

[22]  Motoyuki Sato,et al.  in situ measurement of pavement thickness and dielectric permittivity by GPR using an antenna array , 2014 .

[23]  A. P. Annan 11. Ground-Penetrating Radar , 2005 .

[24]  Imad L. Al-Qadi,et al.  Innovative Approach for Asphalt Pavement Compaction Monitoring with Ground-Penetrating Radar , 2013 .

[25]  Peter Annan,et al.  A review of Ground Penetrating Radar application in civil engineering: A 30-year journey from Locating and Testing to Imaging and Diagnosis , 2017, NDT & E International.

[26]  Imad L. Al-Qadi,et al.  Field Application of Ground-Penetrating Radar for Measurement of Asphalt Mixture Density: Case Study of Illinois Route 72 Overlay , 2012 .

[27]  Imad L. Al-Qadi,et al.  Automatic detection of multiple pavement layers from GPR data , 2008 .

[28]  Donald E Watson,et al.  Thin Asphalt Concrete Overlays , 2014 .

[29]  Craig Warren,et al.  gprMax: Open source software to simulate electromagnetic wave propagation for Ground Penetrating Radar , 2016, Comput. Phys. Commun..

[30]  K. Yee Numerical solution of initial boundary value problems involving maxwell's equations in isotropic media , 1966 .

[31]  Imad L. Al-Qadi,et al.  Algorithm development for the application of ground-penetrating radar on asphalt pavement compaction monitoring , 2016 .