MEPDG software can predict long term performance of the asphalt mixes based on asphalt input data. When laboratory measured data of an asphalt mix are not available, this software uses the predictive models to estimate the mix properties. AASHTO recommended calibrating these input models based on local materials and mixes. Previous studies showed that local calibration of dynamic modulus (E∗) and creep compliance predictive model improved the reliability of the predictions. The purpose of this paper is to evaluate the impact of local calibration of E∗ and creep compliance models on long term performance of mixes containing reclaimed asphalt pavement (RAP), and to assess the sensitivity of the predicted distresses to RAP content. Three Levels of asphalt input data were considered; Level 1, calibrated Level 3, and Level 3. For calibrated Level 3, the predicted E∗ and creep compliance obtained from calibrated models were used as input data. The results showed that the Level 3 input data tend to overpredict the distress predictions of the asphalt mix compared to calibrated Level 3 or Level 1 asphalt input data. It was found that the calibrated Level 3 asphalt input data can be used for the design and analysis of mixes with comparable accuracy of Level 1 input. As conducting laboratory tests for individual mixes is expensive and time consuming, utilizing reliable calibrated models to predict E∗ and creep compliance can substantially reduce operating and testing expenses. Also, it was found that the predicted distresses are not sensitive to the RAP content.
Esfandiarpour, S., & Shalaby, A. (2018). Effect of local calibration of dynamic modulus and creep compliance models on predicted performance of asphalt mixes containing RAP. International Journal of Pavement Research and Technology, 11(5), 517–529. https://doi.org/10.1016/j.ijprt.2018.04.002