Evaluating the Effects of Using Recycled Asphalt Pavements on Fatigue Properties of Warm Mix Asphalt

This paper presented an experimental study to characterize thestiffness modulus and fatigue life of warm mix asphalt mixturecontaining recycled asphalt pavements (RAP) with and withouta rejuvenating agent. For this purpose, warm mix asphaltswere produced using Sasobit and Asphamin as two of the mostcommon additive materials. The following five mixes were preparedand tested: a mix with 30% RAP, two mixes with 30%RAP plus warm mix asphalt additives, and two mixes with 30%RAP plus warm mix asphalt additives and a rejuvenating agent.The results indicated no significant difference in the stiffnessmodulus of warm mix asphalt mixtures containing RAP andconventional mixtures including recycled asphalt pavement.However, the indirect tensile fatigue test results showed thatthe addition of the warm mix asphalt additives and rejuvenatingagent improved the fatigue life of the mixtures at differenttemperatures

Providing Laboratory Rutting Models for Modified Asphalt Mixes with Different Waste Materials

Due to the complex behavior of asphalt pavement materials under various loading conditions, pavement structure, and environmental conditions, accurately predicting the permanent deformation of asphalt pavement is difficult. This study discusses the application of artificial neural network (ANN) and the multiple linear regression (MLR) in predicting permanent deformation of asphalt concrete mixtures modified by waste materials (waste plastic bottles and waste high-density polyethylene). The use of waste materials in the pavement industry can prevent the accumulation of waste material and environmental pollution and can reduce primary production costs. The results of a laboratory study evaluating the rutting properties of Hot-Mix Asphalt (HMA) mixtures using dynamic creep tests were investigated. The results indicate ANN techniques are more effective in predicting the rutting of the modified mixtures tested in this study than the traditional statistical-based prediction models. On the other hand, results show that an increase in percentage of waste materials is very effective in reducing the final strain of asphalt mixtures. However, an increase in percentage of additives over 7% does not help to reduce permanent deformation under dynamic loading in the asphalt mixtures