Modeling of Rutting Depth Using Dynamic Creep Test Results

Pavements are considered as national heritage of every country, and each year a major part of an organizations budget is spent on repairing, upgrading and maintaining them. Providing adequate funding for this purpose is a challenge which managers and decision-makers are facing with. On the other hand, many years are that rutting as one of the most common types of damages created in this type of pavements. These damages are created over time and due to the accumulation of small permanent deformation which is caused by each load. An increase in permanent deformation that leads to an increase in the depth of groove can cause serious problems in the pavement. Thus, estimating the potential of rutting in the asphalt mixtures in laboratory gets a special significance. In this research, by identifying experiences and research methods of the world and after investigating current situation our country, in addition to determining direct influential parameters, a suitable model for estimating the depth of the groove in asphalt will be presented. The proposed model determining the rutting depth of Hot Mix Asphalt by using dynamic creep test results. Model validation is verified by using the Artificial Neural Network (ANN).