Evaluating and comparing different methods and models for generating relaxation modulus master-curves for asphalt mixes

Based on a master-curve, mixture properties can be predicted or interpolated at different temperatures and loading times of interest from a limited set of laboratory test data. This paper presents a comparative assessment of three methods used for generating the relaxation modulus (E(t)) master-curves of hot-mix asphalt (HMA). These methods were the Arrhenius, the Williams–Landel–Ferry (WLF), and an optimization technique with the sum of square error (SSE) method. Experimental data (E(t) values) for different HMA mixtures were gathered by performing uniaxial loading (strain-controlled) relaxation modulus tests (RMT). The process for evaluating the three methods was based on using the same RMT laboratory data to generate E(t) master-curves and then comparing the best fit functions. Corresponding results suggested that the SSE method generated the best fit functions relative to the measured E(t) data. Unlike the Arrhenius and WLF models, the SSE is independent of external empirical material constants in its application and is universally applicable to any given material or HMA mix type. However, this study also demonstrated that both the Arrhenius and WLF methods can produce satisfactory (and in fact equivalent results) if appropriate constants, that are material or mix type specific, are used. Conclusively, the findings of this paper suggested that satisfactory application of the Arrhenius and WLF methods should be with caution, in particular with respect to the material constants. Otherwise, the SSE method proved to be more accurate and would be preferred.

Research highlights
► The paper compares three methods for generating relaxation modulus (E(t)) master-curves of hot-mix asphalt.
► Compared methods were the Arrhenius, Williams–Landel–Ferry (WLF), and sum of square error (SSE).
► The SSE method generated the best fit functions relative to the measured E(t) data.
► The Arrhenius and WLF methods can produce appropriate results if mix specific constants are used.