Analysis of hot mix asphalt compaction data by means of fuzzy clustering techniques

The analytical control of the compaction of an hot mix asphalt is difficult because of the complex relationship among uncertain features but it is fundamental to achieve the target established in the design respecting the estimated cost. For this reason it is necessary to use instruments that report the surveyed data in real time not only of the compaction but also of other parameters relative to the considered scenario, through evolved analytical procedures in order to extract useful information. The aim of this paper is the proposal of an expeditious procedure to be used during the execution of an asphalt layer that, based on a fuzzy clustering technique and starting from the knowledge of the information recorded by ordinary measuring instruments, predicts whether the material under certain conditions can reach the desired value of density. This result can be deduced with great rapidity during the paving operations on site without waiting for extraction time of cores and subsequent laboratory analysis. In this way it is possible to identify more precisely what aspects of the environmental context have to be corrected for performing the best compaction.