Quantitative moisture measurement of road pavements using 3D noise-modulated GPR

Within Queensland, Australia around 90% of state controlled roads are constructed from unbound granular materials with thin bituminous surfacings. These pavements are significantly influenced by moisture. However currently there is no rapid, quantitative method of assessing in-place pavement moisture suitable for use at large scales. This makes it difficult for road engineers to diagnose and treat moisture ingress mechanisms in failing pavements and to properly assess and protect flood weakened roads from heavy vehicle damage. This research focuses on quantitative moisture measurement of unbound granular road pavements using rapid 3D multi-offset ground penetrating radar (GPR) techniques. The work will use an update of an existing 3D noise-modulated GPR (NM-GPR) system to collect multiple wide angle reflection and refraction (WARR) profiles across the road lane, while moving along the road at highway speeds. The intention is to use geophysical methods on this data to determine pavement layer permittivity values and from this estimate in-place pavement moisture. While the NM-GPR update is being finalised, preliminary research has commenced. Synthetic data have been produced to model the expected multi-offset data from the new system. This data have been used to test methods of identifying and tracking subsurface layers and the application of geophysical methods to determine pavement layer permittivity values. Preliminary laboratory investigations of moist pavement materials have also commenced using a vector network analyser (VNA) and a phase-shift measurement technique. This has been done in order to develop the necessary moisture-permittivity relations to calibrate the moisture predictions from the GPR permittivity measurements. This paper describes the current state of research, preliminary simulations and laboratory testing undertaken toward the goal of developing a robust, high-speed method of quantifying in-place road pavement moisture.