The fatigue life of Asphalt concrete pavement consists of two components, namely the resistance to fracture and crack, and the ability to heal the micro cracks. Both processes changes with temperature and time. Such processes exhibit the sustainability potential of asphalt concrete pavement. Repeated traffic loading and environmental impact causes deterioration in asphalt concrete pavement mixes and exhibit micro cracking and decreases its stiffness. However, due to the crack healing phenomena effect, asphalt mixes can demonstrate strength recovery and prolongs the fatigue life of asphalt mixtures. Many studies have been conducted to characterize the asphalt healing and its mechanisms. The approach to study this potential requires implementation of proper additives to the asphalt cement which can improve the self healing property of asphalt concrete and reserve the quality of the pavement. The aim of this work is to thoroughly understand the cracking and healing mechanisms and to define appropriate laboratory tests and type of additives which can increase the healing potential and can be used for a reliable performance-related selection and characterization of the asphalt binders, and the suitable asphalt concrete mixture based on the traffic loading and the environment issues. It was felt that it is essential to evaluate whether it is possible to achieve accelerated healing in asphalt mixtures within laboratory conditions, which could represent the actual behavior in the field. It was concluded that the process of healing is a sustainable measure and can be used to balance the damage process. The influence of several additives on the microcrack healing concept was discussed. The amount and rate of healing of asphalt cement which depend on several properties such as; its healing potential, stiffness, and surface free energy was also analized.
Study on a Prediction Model of the Tensile Strain Related to the Fatigue Cracking Performance of Asphalt Concrete Pavements Through Design of Experiments and Harmony Search Algorithm
