Development of Aggregate Dielectric Constant Database Protocol for Asphalt Concrete Density Prediction

Abstract

Contractors are paid incentives/disincentives based on achieved in situ asphalt concrete (AC) density. Ground-penetrating radar (GPR) has been proven feasible for predicting in situ density of AC pavements using various empirical and fundamental approaches. However, to use fundamental equations for density prediction, aggregate dielectric constant must be known beforehand. Destructive cores are usually extracted from the pavement to back-calculate the aggregate dielectric constant. This cancels out the non-destructive benefit of the GPR technology. In this study, GPR is used to quantify the dielectric constant of 10 different aggregates commonly used in AC mixes in Illinois, U.S. The sampled aggregates included limestone, dolomite, trap rock, granite, and crushed gravel. The purpose was to initiate an aggregate dielectric constant database that would help predict AC density nondestructively and accurately. By using the aggregate database, GPR would help contractors estimate achieved density in real-time without prior calibration. This technology would save energy, time, and cost. Simulations using gprMax and a sensitivity analysis are presented to illustrate the effect of aggregate dielectric constant on AC bulk dielectric constant and, consequently, on AC density predicted by the Al-Qadi Lahouar Leng model. A new procedure to determine the aggregate dielectric constant using the electromagnetic mixing theory is detailed. Advanced chemical tests confirmed that the aggregate dielectric constant is a function of its elemental/mineral compositions. Finally, laboratory and field data were used to validate AC density prediction using the aggregate database. The establishment of an aggregate dielectric constant database would improve the accuracy of GPR in nondestructive AC density prediction.