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Highlights The use of waste cooking oil as a recycling agent opens the possibility for the routine design of 60-to-nearly-100% recycled content asphalt paving mixtures. Aging susceptibility of recycled binders with waste cooking oil is higher than virgin binder. Oil has a greater effect on reducing the stiffness of RAP binder than increasing its m-value. Waste cooking oil tended to improve mixture workability and low temperature performance while reducing moisture and rutting resistance. Selecting the optimum oil content as equal to the average oil content based on satisfying the LT and HT PG can assure short-term and long-term performance. AbstractThe environmental and economic benefits of recycling asphalt pavements have received much attention in recent years. Because of the increase in the cost of raw materials and energy carriers, the reuse of large portions of reclaimed asphalt pavement (RAP) is critical in reducing both the cost and environmental footprint of asphalt pavements. High-RAP mixtures are more prone to low temperature cracking and poor mixture workability because of the higher stiffness of RAP binder. Recycling agents are one of the additives which are used to improve these deficiencies. However, there is some ambiguity about the optimum content of recycling agent to assure proper performance of recycled asphalt pavement during its service life. The current study used 60% and 100% fractionated RAP with waste cooking oil as a recycling agent and crumb rubber to alleviate the aforementioned problems.Laboratory evaluation showed that increasing the amount of recycling agent in the high-RAP mixtures improved their workability and low temperature performance while decreasing moisture damage and rutting resistance. The long-term susceptibility to aging of recycled binder with the organically-based recycling agent was also investigated. A procedure to obtain the optimum percentage of recycling agent was devised to strike a balance between the performance characteristics of mixtures with a high-RAP content.

Crumb rubber modification (CRM) is an effective means of improving neat asphalt performance. Numerous studies have investigated the effects of CRM using the current Superpave® laboratory tests. Recent studies have shown that the assumption of linear viscoelastic behavior or employing insufficient stress or strain levels makes current tests inadequate for properly assessing the performance of binders, especially when modified. This problem has resulted in the development of improved test methods such as the time sweep binder fatigue test and the multiple stress creep and recovery (MSCR) test for permanent deformation. The present study assesses the performance of binders modified with a wide range of crumb rubber content using these newly developed test methods. Additional binder and mixture performance tests were used to compare and validate the results. The results showed that the new tests performed well in predicting performance. Current Superpave criteria also showed good conformance with mixture test results for CRM binders. Tests results suggest that the MSCR can complement current rutting prediction testing. Also, the time sweep test produces results similar in accuracy to current Superpave tests, but it requires longer testing time and is thus not recommended for performance grading.

Pavement performance models are key components of any pavement management system (PMS). These models are used in a network-level PMS to predict future performance of a pavement section and identify the maintenance and rehabilitation needs. They are also used to estimate the network conditions after the application of various maintenance and rehabilitation alternatives and to determine the relative cost effectiveness of each maintenance and rehabilitation alternative. Change in pavement surface roughness over time is one of the most important performance indicators in this regard. A model for changes in the international roughness index (IRI) over time was developed through artificial neural networks (ANNs) pattern recognition, using information from the Specific Pavement Study (SPS)-5 asphalt concrete rehabilitation experiment extracted from FHWA's Long-Term Pavement Performance database. This model can be used to predict and compare pavement roughness variation trends after various rehabilitation alternatives. An example illustrates the implementation of the roughness model along with life-cycle cost analysis in making future pavement rehabilitation recommendations. Model testing results indicate prediction of IRI with minimal errors, and predicted future roughness trends match perfectly with the past performance. These findings indicate that the ANN model performs successfully in predicting IRI trends following each kind of treatment in the SPS-5 experiment. The ANN model was developed for the SPS-5 flexible pavement rehabilitation sections in a wet–freeze climate and may be applied for similar conditions. The example also shows that the detailed model development and implementation framework provided in this study can assist in network-level PMS decision making.

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