UC Pavement Research Center
Available online at: https://doi.org/10.1177%2F0361198119849901
Elkashef, Mohamed, Shawn S. Hung, David Jones, John T. Harvey (2019) Using Predictive Models to Estimate the Properties of Binders in Reclaimed Asphalt Pavement Mixes using Fine Aggregate Matrix Mix Testing. Transportation Research Record 2673 (6), 501 - 511
A number of predictive models, such as the Hirsch and Al-Khateeb models, have been proposed to determine the properties of asphalt binders from asphalt concrete mix testing results. Fine aggregate matrix (FAM) mix testing can also provide useful insights into the likely performance of asphalt concrete mixes. Consequently, FAM mix testing can be an appropriate means of assessing the predictive power of these models. In this study, FAM mixes prepared with two virgin binders, PG58-28 and PG64-16, and then with different percentages of reclaimed asphalt pavement (RAP) were tested to determine their stiffness and phase angle using temperature-frequency sweeps in a dynamic shear rheometer. The data from the control mixes with no RAP were used along with the rheological properties of the virgin binders to fit the Hirsch and Al-Khateeb models. The fitted models were then used to estimate the properties of the binders in the 15% and 25% RAP FAM mixes. A comparison of the estimated binder properties with the measured binder properties clearly indicated that the fitting parameters are binder dependent. Moreover, the estimated binder moduli deviate from the measured moduli, particularly at high temperatures. The estimated complex shear moduli from the model were found to be consistently higher than the measured shear moduli values of the chemically extracted binders. It was thus concluded that the predictive models studied, in their current form, fail to provide a reliable estimate of the binder properties in mixes containing RAP.
Key words: models, asphalt, asphalt concrete, binders, binder content