Abstract :
Road pavement performances are of great importance for driving comfort and safety. Monitoring and rehabilitation activities are always extremely strategic and crucial. The points of strength of advanced non-destructive techniques for road pavement monitoring essentially are: (1) reliability, (2) significance in the space domain, (3) efficiency and (4) quickness. One of the most relevant and widely used technologies is the Ground Penetrating Radar. In the field of pavement analysis its most frequent applications are the evaluation of layers thickness and voids detection. Recent experimental results put also in light the capability of Radar to identify the causes of road damages. Empirical relationships between physical and mechanical characteristics of the materials and electromagnetic parameters have been seen, established and analytical functions were proposed. Most promising and interesting evidences regard the prediction of water content. It is crucially important because water intrusion in sub-grade is one of the most important causes of loss of mechanical properties. The empirical relationships have shown a conservative and comparable trend for different materials, status conditions and radar frequencies, but variable amplitudes. General mathematical laws could be very useful to analyze the Radar scans correctly and in a more comprehensive framework A stochastically based correction of semi-empirical approach is here proposed to correlate the geophysical characteristics of the pavement?????????s materials (sub-grade) to the par:rmeters of the empirical model. Average dimension of grains, grading, specific surface area of grains (that is related to the hygroscopic potential) and dielectric characteristics of the dry material are primarily taken into consideration. The impact of this geophysical and stochastical model on non-destructive measurements and on the pavement management is high and it is here discussed.
