Uncertainty analysis for the dynamic modulus of recycled asphalt mixtures using unclassified fractionated RAP materials

Abstract

The use of unclassified reclaimed asphalt pavement (RAP) is limited due to concerns about raw material variability, impacting RAP mixture performance consistency. Space constraints lead to aggregating recycled materials from various projects into "unclassified RAP," hindering its potential benefits. The evaluation of uncertainties, particularly in dynamic modulus |E*|, is crucial for assessing performance and reliability in asphalt mixtures containing unclassified RAP. In this research, A systematic approach for calculating the coarse and fine RAP ratios based on unclassified RAP content, along with regulated processing and fractionation meeting standards was implemented. Then, a probabilistic model was established, utilizing the sigmoidal function, to analyze the uncertainty in |E*| as a function of the reduced frequency for asphalt mixtures with varying unclassified RAP contents (0%, 15%, 25%, and 45%). The findings revealed that |E*| uncertainty was minimal at low temperatures, reasonable at service temperatures, and critical (COV > 30%) at high temperatures for standard and RAP mixtures. Importantly, increasing unclassified RAP content doesn't worsen |E*| uncertainty. Mixes with high unclassified RAP content showed similar or lower COV values across analyzed frequencies. The proposed approach can reduce COV values in high unclassified RAP content mixes, offering a practical solution to leverage these materials' benefits.