Investigation of factors affecting dynamic modulus and phase angle of various asphalt concrete mixtures

This study investigated the dynamic response of various asphalt concrete (AC) mixtures subjected to sinusoidal loading. Eight AC mixtures (four wearing and four base course) were selected including (but not limited to): superpave, asphalt institute manual series, and dense bituminous macadam. The uniaxial dynamic modulus (|E*|) test at various temperatures (4.4–54.4\ua0°C) and frequencies (0.1–25\ua0Hz) was conducted using asphalt mixture performance tester. Statistical analysis of two-level factorial was employed to regulate the factors affecting the AC mixtures. The results revealed that an increase in temperature (from 21.1 to 37.8\ua0°C), translated into 45 and 43\ua0% drop in |E*| values on average while 80 and 67\ua0% decrease in |E*| values was attributed to the sweep of frequency (from 25 to 0.1\ua0Hz) for wearing and base course mixes, respectively. Non-linear regression model was developed to express the dynamic modulus as a function of test temperature, loading frequency and mixture volumetric parameter. Furthermore, Witczak model of dynamic modulus prediction was evaluated and the results indicated a close fit with an average under prediction error of 0.20. The study characterized and ranked the representative AC mixtures that could help in selecting the material/gradation for mechanistic-empirical pavement design approach

Modelling and characterising the fatigue behaviour of asphaltic concrete mixtures

This paper investigates the fatigue behaviour of asphaltic concrete mixtures subjected to Indirect Tensile Fatigue Test (ITFT) under a stress-controlled mode. The conventional stress/strain based approach is used to determine the number of cycles to failure and initial strain value under specified repeated load levels. The fatigue test results indicate that the MS-2 mix (containing 60% and 40% of coarser and finer particles, respectively) prepared with the 40/50 penetration grade binder accumulates less initial strain, and has a relatively better resistance to fatigue than the other tested mixtures. Furthermore, this fatigue behaviour is modelled using a power, intrinsically linear, and non-linear functional specifications. Among these, a non-linear model formulation is found to be the best suited, expressing the number of cycles to fatigue failure as a function of the initial strain, the viscosity, the optimum bitumen content, and the resilient modulus. The fatigue model captures high variability in the data (R2 = 0.86) with a reasonable prediction error (of 15%) as compared to other models. The findings of this study can serve as the basis for selection of asphaltic concrete mixtures based upon the fatigue life criterion; the models proposed in this study can be used as a precursor to determining the fatigue behaviour without performing laborious laboratory testing.</p