Reclaimed asphalt pavement (RAP) is a type of material that already suffers long-term aging in the field, so its aging characteristics become prominent since they are closely related to premature distresses and longevity of recycled pavements. While most of investigations of RAP mixtures are carried out in the laboratory, this study focuses on in situ aging of asphalt pavements with RAP overlays. A kinetics-based aging modeling approach is proposed to analyze and quantify long-term field aging of RAP overlays using the Falling Weight Deflectometer (FWD) data and climate data. The kinetics-based approach contains a modulus aging model with kinetic parameters (e.g. aging activation energy) for asphalt mixtures. Eight asphalt overlays are selected with different mixtures (RAP and virgin), thickness (50 mm and 125 mm), and surface preparation (milling and no milling). An asphalt pavement with an overlay has a composite aging process since the aging speeds of different asphalt layers are different. Thus an approach to separate the FWD modulus is developed in order to obtain the actual aging behaviors and properties of the overlay. By applying the kinetics-based modeling to the separated FWD moduli, the aging activation energies of both the overlays and old asphalt layers are determined. It is found that the RAP overlay has the highest aging activation energies and slowest aging rates among the RAP overlay, virgin overlay, and old asphalt layer for the selected pavements. It also reveals through the aging activation energy that the thick overlays age slower than thin ones, and the overlays on milled pavements age slower than those placed without milling. The findings in terms of the aging activation energy can be used to explain the difference in the field performance of overlay pavement sections.
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- Kinetics-based modeling
- Aging activation energy
Luo, X., Gu, F., Zhang, Y., Lytton, R. L., & Birgisson, B. (2018). Kinetics-based aging evaluation of in-service recycled asphalt pavement. Journal of Cleaner Production, 200, 934-944. https://doi.org/10.1016/j.jclepro.2018.07.267