Remya Varma K., Indian
My research work at KTH Royal Institute of Technology, Sweden mainly corresponds to the investigation of self-healing capabilities of asphaltic materials.
Improving the performance and durability of the asphalt pavements is a challenge for pavement engineers throughout the world. Asphalt concrete, a mixture of aggregates and bitumen, is known to exhibit self-healing characteristic. Here, healing is normally defined as the “beneficial internal structural change” and pavement engineers try to use such characteristic to enhance the long-term performance of the pavements. It is yet challenging to quantify what makes bitumen self-heal and the few important parameters are temperature, confinement conditions and the rest periods between loadings in addition to the complex microstructural/ macro molecular nature of bitumen. The ideal scenario is when one can gainfully exploit the self-healing characteristics to tailor-make a binder such that the life of the pavements can be enhanced. One challenge in understanding such healing mechanism is related to the arrangement of the macromolecules of the bitumen. Such arrangement is not unique and it varies depending on the crude source and processing method. In addition to this, bitumen also age during service and such aging is largely influenced by the exposure to oxygen, moisture and ultraviolet rays. The tendency for the material to heal is “slowed” down by the aging process and hence one cannot quantify healing without considering aging.
Investigations have used the Atomic Force Microscopy to observe the different phases of bitumen and the mobility of various phases was measured using neutron scattering. In the proposed research work, the microscopic techniques will be used to measure the mobility parameters of bitumen using neutron imaging. The outcome of this research effort can lead to the development of a macromolecular model for asphalt mixture which could be used to simulate various case scenarios related to self-healing capabilities of the bitumen. A multi-scale modeling approach will be used to predict the results for improving the performance of the asphalt mixture/ pavement.