Effect of Asphalt Mixture Components on the Uncertainty in Dynamic Modulus Mastercurves

Abstract

Practitioners and researchers in the paving industry have highlighted the importance of the adoption of reliability-based pavement design. The goal of developing reliable pavements with optimum performance over their design life has become a key factor to be considered during both pavement design and construction processes. This requires the adoption of statistical and probabilistic-based analyses for the formulation of the properties and behavior of pavement materials. Thus, many researchers worked on the quantification and modeling of the uncertainty caused by the inherent variability in pavement materials in general and that of asphalt concrete (AC) in particular. The dynamic modulus (|E*|), a fundamental property for mechanistic-empirical and purely mechanistic pavement designs, has been proven to have a significant level of uncertainty that is dependent on climatic and traffic loading conditions. The main objective of this study is to investigate the effect of the AC mixture properties and components on the uncertainty in the |E*| mastercurve. This objective is achieved by conducting an experimental program incorporating four different mixtures having the same material sources but different binder types and gradations. Monte Carlo simulations are used to model the uncertainty of |E*| for each of these mixtures. The paper shows that the uncertainty is dependent on mixture type, as the presence of larger nominal maximum aggregate size, modified binder, or additive can increase the uncertainty in the |E*| mastercurve, especially at high temperatures or slow loading rates. The uncertainty is proven to be material related and not imposed by the testing instrumentation.