Developing a Model for Estimating the Asphalt Mixture Flow Number Using Gyratory Compactor Shear Stress Curve and Compaction Slope

Network of roads is a part of assets of each country that can be progressive in different fields and aspects. So, maintenance and repair of this property, is significant. Accordingly, pavement has a very specific effect due to its high costs. The More correct maintenance, lower costs appeared. Asphalt rutting is one of the flexible pavement deteriorations. Rutting has caused high maintenance and repairs costs and several problems for road users for years, so researches are concentrated on this problem. Investigations showed rutting has various origins, although, the most important factor is permanent deformation production due to lack of asphalt shear strength. Predicting asphalt pavement strength against permanent deformation while preparing laboratory mix design can prevent producing asphalt with high rutting potential. However, not only laboratory instruments for this purpose are expensive, but an experienced labor should be used for a considerable time to work with them. These factors made the researchers look for lower cost and time procedures for assessment of rutting in laboratory step. Although the most popular method of determining rutting potential, is loading wheel, but in lots of researches, dynamic creep test is used. Previous studies showed flow number of dynamic creep test is related to rutting potential inversely. In this research which covers a wide variety of aggregates, gradation, bitumen and filler used in Iran a simple model for predicting flow number is developed. Then it was appeared that gyratory shear stress curve which is the one of six output curves of gyratory compactor, can be represented as a logarithmic model. After modeling this curve for all specimens and determining the slope of density for them, a simple model was presented to estimate the flow number by SPSS software. The independent variables of this model were determined from output curves of gyratory compactors. This model was validated by using neural network and genetic algorithm. And its accuracy was confirmed by an appropriate percent of confidence. Flow number can be predicted while asphalt specimens are prepared in order to determine the 9 Developing a Model for Estimating … / Ziari, Divandari, Shafabakhsh and Fakhri optimal bitumen in laboratory by this model. So not only there is no need for expensive equipments to perform rutting and dynamic creep test, but also a reduction in mix design procedure time is achievable and producing of asphalt with high potential of rutting is prevented.