2013 - NZ - Modelling the Flushing Mechanism of Thin Flexible Surface Pavements

The research presented in this thesis investigated the occurrence of flushing of chip seal pavements. The research aimed to determine the effects of volumetric properties of chip seal surfaces on flushing, focusing on the relationship between air voids and flushing initiation. Additionally, the research aimed to develop a pavement deterioration model to predict the initiation and progression of flushing on chip seal pavements. Mechanical testing was conducted on cores obtained from in-service, flushed chip seal pavements from Auckland, Waikato, Christchurch and Dunedin regions of New Zealand. The tests that were performed on the cores included wheel tracking, air voids measurement, bitumen extractions and sieve analyses to determine aggregate grading profiles. Measurements were made of the depth and pattern of deformation that had developed on the cores during wheel tracking. Samples extracted from tested cores were scanned using a computed tomography scanner and the scan images were analysed using image analysis techniques to calculate the volume of air voids within the samples. The reduction in air void volume during wheel tracking was compared to the flushing that had occurred on the samples to establish the relationship between flushing and air voids. Furthermore, data analysis was performed on pavement condition data gathered from New Zealand’s long-term pavement performance database to identify the combination of factors that provided the best prediction of flushing, and regression analysis was performed to develop a model to predict the initiation and progression of flushing. The laboratory testing described above revealed that the thickness of a chip seal surface has a direct correlation to flushing, where thicker surfaces tend to have more severe flushing. Moreover, the reduction in air void volume that occurred in a chip seal structure due to loading was directly related to the amount of flushing likely to occur on that surface. The pattern of deformation of a chip seal structure provided an indication of its state of stability, which in turn indicated the best method of treatment for flushing. From the data analysis it was identified that the combination of factors that provided the best indication of flushing were surface thickness, surface age, rutdepth and grade of aggregates. The flushing initiation model had an accuracy of 76% and the flushing progression model was also statistically strong at predicting the quantity of flushing. Using these research outcomes, a pavement condition assessment guideline was developed to aid with managing flushed pavements. Overall, this research has significantly increased the understanding of the mechanisms that lead to flushing and established ways to better identify and manage flushing.