Optimizing Flexible Pavement Density during Construction with Closed-Loop GPR Monitoring

Ground-penetrating radar (GPR) has been proven capable of accurately predicting asphalt concrete (AC) thickness and density. These properties are vital for pavement structural integrity. The objective of this study was to monitor AC compaction during construction. Several challenges have been addressed: 1) A GPR system was retrofitted to a roller compactor; 2) An aggregate dielectric constant database was used, in lieu of back-calculating it from extracted cores; 3) An algorithm to overcome GPR’s limited resolution was used to correct for thin layers; and 4) the effects of surface moisture, from compaction drum, are isolated from GPR signal. Three different stone matrix asphalt (SMA) sections were monitored using GPR and their data were analysed. The predicted thicknesses and densities by GPR were compared to ground-truth extracted cores at specific locations. The mean absolute errors for density and SMA thickness prediction are 0.7% and 4mm, respectively.

Authors

Publication Details

Journal
e-Journal of Nondestructive Testing
Published
2025-09-18
DOI
https://doi.org/10.58286/31695
Citations
1
Primary Topic
Geophysical Methods and Applications
Type
article
Field-Weighted Citation Impact
1.15
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article

Optimizing Flexible Pavement Density during Construction with Closed-Loop GPR Monitoring

Imad L. Al‐Qadi, Lama Abufares, Yihan Chen
1 citations
e-Journal of Nondestructive Testing
Geophysical Methods and Applications
1.15
article

Optimizing Flexible Pavement Density during Construction with Closed-Loop GPR Monitoring

Imad L. Al‐Qadi, Lama Abufares, Yihan Chen
article en
1 citations

Abstract

Ground-penetrating radar (GPR) has been proven capable of accurately predicting asphalt concrete (AC) thickness and density. These properties are vital for pavement structural integrity. The objective of this study was to monitor AC compaction during construction. Several challenges have been addressed: 1) A GPR system was retrofitted to a roller compactor; 2) An aggregate dielectric constant database was used, in lieu of back-calculating it from extracted cores; 3) An algorithm to overcome GPR’s limited resolution was used to correct for thin layers; and 4) the effects of surface moisture, from compaction drum, are isolated from GPR signal. Three different stone matrix asphalt (SMA) sections were monitored using GPR and their data were analysed. The predicted thicknesses and densities by GPR were compared to ground-truth extracted cores at specific locations. The mean absolute errors for density and SMA thickness prediction are 0.7% and 4mm, respectively.

e-Journal of Nondestructive TestingVol. 30(10)
Openalex Percentile: Top 19%
Geophysical Methods and Applications
1.15
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