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

Siqi Wang, Shan Zhao, Imad L Al-Qadi

Research output: Contribution to journalReview article

Abstract

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.

Original languageEnglish (US)
JournalSurveys in Geophysics
DOIs
StatePublished - Jan 1 2019

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Pavement overlays
asphalt
pavements
Asphalt concrete
Asphalt pavements
ground penetrating radar
radar data
pavement
compaction
Radar
Compaction
moisture
Moisture
Radar reflection
prediction
predictions
radar
radar echoes
Concrete pavements
electrical property

Keywords

  • Density and thickness prediction
  • Finite-difference time-domain
  • Ground penetrating radar
  • Nonlinear optimization
  • Thin asphalt concrete overlay

ASJC Scopus subject areas

  • Geophysics
  • Geochemistry and Petrology

Cite this

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title = "Real-Time Density and Thickness Estimation of Thin Asphalt Pavement Overlay During Compaction Using Ground Penetrating Radar Data",
abstract = "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.",
keywords = "Density and thickness prediction, Finite-difference time-domain, Ground penetrating radar, Nonlinear optimization, Thin asphalt concrete overlay",
author = "Siqi Wang and Shan Zhao and Al-Qadi, {Imad L}",
year = "2019",
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language = "English (US)",
journal = "Surveys in Geophysics",
issn = "0169-3298",
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AU - Wang, Siqi

AU - Zhao, Shan

AU - Al-Qadi, Imad L

PY - 2019/1/1

Y1 - 2019/1/1

N2 - 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.

AB - 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.

KW - Density and thickness prediction

KW - Finite-difference time-domain

KW - Ground penetrating radar

KW - Nonlinear optimization

KW - Thin asphalt concrete overlay

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