A comprehensive approach for the assessment of HMA compactability using GPR technique

With the focus on quality assurance practices during pavement construction, the present research aims at investigating the compactability of hot mix asphalt using the ground-penetrating radar technique. Thus, density as an indicator of the compactability of hot mix asphalt is predicted using three different electromagnetic-mixing-theory-based density models (namely, the complex refractive index model, Rayleigh model, and Al-Qadi, Lahouar and Leng model), and the prediction performance is also investigated. The investigations are based on experimental data acquired, both in the laboratory and field, from new full-scale asphalt pavement sections with varying asphalt mixture compositions. The laboratory experiment, which involved the compaction of asphalt mixtures using the steel-segmented roller compactor, indicated that compaction mode affects the compactability of hot mix asphalt, whereas the analysis of field ground-penetrating radar experimental data revealed that the estimated electric permittivity eHMA during the compaction process could be considered a measure of the asphalt mix field compactability. The prediction performance of the three density models was evaluated using different methodological approaches with respect to the backcalculation of es of the mix aggregates. The results indicated that, by utilizing the ground-penetrating radar field measured eHMA for the assessment of es, the predicted Gmb values from the implementation of the above density models closely approach the ground-truth field-core bulk densities. Comparative evaluation of the three density models showed that the Al-Qadi, Lahouar, and Leng model exhibits the best prediction performance, which is comparable to nuclear/non-nuclear methods. In light of this, it could be argued that the ground-penetrating radar methodology coupled with novel algorithms can be an effective and efficient tool to improve the asphalt mix compaction process and assessment of in situ density.

[1]  Timo Saarenketo,et al.  Electrical properties of road materials and subgrade soils and the use of ground penetrating radar in traffic infrastructure surveys , 2006 .

[2]  Timo Saarenketo,et al.  Using Ground-Penetrating Radar and Dielectric Probe Measurements in Pavement Density Quality Control , 1997 .

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

[4]  Sesh Commuri,et al.  Neural Network–Based Intelligent Compaction Analyzer for Estimating Compaction Quality of Hot Asphalt Mixes , 2011 .

[5]  Andrea Benedetto,et al.  Water content evaluation in unsaturated soil using GPR signal analysis in the frequency domain , 2010 .

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

[7]  Imad L. Al-Qadi,et al.  In-Place Hot-Mix Asphalt Density Estimation Using Ground-Penetrating Radar , 2010 .

[8]  S. Pensa,et al.  Indirect diagnosis of pavement structural damages using surface GPR reflection techniques , 2007 .

[9]  Bouzid Choubane,et al.  Nuclear Density Readings and Core Densities: A Comparative Study , 1999 .

[10]  Christina Plati,et al.  Use of infrared thermography for assessing HMA paving and compaction , 2014 .

[11]  Christina Plati,et al.  Estimation of in-situ density and moisture content in HMA pavements based on GPR trace reflection amplitude using different frequencies , 2013 .

[12]  Imad L. Al-Qadi,et al.  In situ measurements of hot-mix asphalt dielectric properties , 2001 .

[13]  Brian K Diefenderfer,et al.  Comparison of Nuclear and Nonnuclear Pavement Density Testing Devices , 2008 .

[14]  Mary Stroup-Gardiner,et al.  Using Infrared Thermography to Detect and Measure Segregation in Hot Mix Asphalt Pavements , 2000 .

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