The study of asphalt chemo-mechanics requires a basic understanding of the physical properties and chemical composition of asphalt and how these properties are linked to changes in performance induced by chemical modifications. This work uniquely implements the framework of chemo-mechanics by investigating two types of chemical modification processes, natural (oxidative aging) and synthetic (chemical doping) as they relate not only to macro-scale properties of asphalt binder but also to the asphalt microstructure and nanorheology. Furthermore, this study demonstrates the application of atomic force microscopy (AFM) imaging and the extraction of nano-scale engineering properties, i.e. elastic modulus, relaxation modulus, and surface energy, as a method to predict performance related to the fatigue characteristics of asphalt binders by modeling intrinsic material flaws present amongst phase interfaces.
It was revealed that oxidative aging induces substantial microstructural changes in asphalt, including variations in phase structure, phase properties, and phase distribution. It has also been shown that certain asphalt chemical parameters have a consistent and measureable effect on the asphalt microstructure that is observed with AFM. In fact, particular phases that emerged via chemical doping revealed a surprising correlation between oxidative aging and the saturates chemical parameter of asphalt in terms of how they explicitly impact durability and performance of asphalt.
By implementing a crack initiation model – which requires measureable microstructural characteristics as an input parameter – it was found that microstructural flaws (depending on the extremity) can have a more profound impact on asphalt performance than the properties of the material located between the flaws. It was also discovered by comparing the findings to performance data in the Strategic Highway Research Program’s (SHRP’s) Materials Reference Library (MRL), that the crack initiation model predicts very similar performance as the SHRP’s distress resistance indicators. Overall, this body of work yields improved input values for asphalt prediction models and serves as the basis for ongoing studies in the areas of asphalt chemical mapping, modeling of nano-damage, and nano-modification using AFM.
| Identifer | oai:union.ndltd.org:tamu.edu/oai:repository.tamu.edu:1969.1/149372 |
| Date | 03 October 2013 |
| Creators | Allen, Robert Grover |
| Contributors | Little, Dallas N., Lytton, Robert L., Epps-Martin, Amy, Glover, Charles J. |
| Source Sets | Texas A and M University |
| Language | English |
| Detected Language | English |
| Type | Thesis, text |
| Format | application/pdf |
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