Epps Martin, Amy2014-12-122017-04-072014-12-122017-04-072012-122012-12-07http://hdl.handle.net/1969.1/148213While the oxidation of binders in hot mix asphalt (HMA) pavements and its subsequent detrimental effects on pavement life have been well recognized in the last few years, many important issues have not yet been investigated. Understanding how best to design mixtures taking this phenomenon into account and achieving maximum durability is an important and complex issue. This study was aimed at characterizing the effects of oxidative aging on durability in terms of mixture fatigue resistance of laboratory mixed-laboratory compacted (LMLC) samples. Direct tension tests were conducted on HMA samples to measure mixture stiffness and a Modified Calibrated Mechanistic with Surface Energy (CMSE*) analysis method was used to predict fatigue life. The effect of various mix design parameters was evaluated to understand their importance with respect to the aging phenomena and mixture fatigue resistance. Analysis of the results showed that aging has a significant negative effect on mixture fatigue resistance. Considerable increase in the stiffness modulus (Eve) of the mixtures was observed with age for all three mixtures analyzed. Air voids (AV) played a substantial role in affecting the fatigue resistance with aging, but a difference of 0.5% in binder content near the optimum level did not statistically change mixture durability in terms of fatigue resistance with aging. For the three mixtures in Texas included in this study, when comparing Eve, one month of artificial aging in the laboratory was equivalent to 10.5 months of natural aging in the field. A good correlation was also found between the Eve of the mixture and the Carbonyl Area (CA) and Dynamic Shear Rheometer (DSR) function of the extracted binder. Thus, a connection exists between the properties of the extracted binder, laboratory mixtures and field mixtures. This relationship will facilitate development of a more mechanistic aging component in pavement performance prediction models.HMAArtificial agingDirect tension testsFatigue resistanceOxidative AgingAsphaltThesis