Correlate aggregate angularity characteristics to the skid resistance of asphalt pavement based on image analysis technology
Department of Civil, Environmental, and Geospatial Engineering
The impact of aggregate morphological characteristics plays a key role in the skid resistance of road surface due to driving safety and cost benefits. The 2nd generation of the Aggregate Imaging Measurement System (AIMS II) and X-ray Computed Tomography (CT) were utilized to evaluate the shape of particles and capture the change in their morphological characteristics. The Los Angeles Abrasion (LAA) Test was also conducted in this paper to investigate the influence of variations in aggregate angularity on the resistant performance of asphalt mixtures. Before and after 100, 300, 500, and 1000 rotations of LAA polishing process, 48 particles from each different size were adopted and measured using AIMS II and XCT to obtain the value of their morphological properties. The parameter gradient angularity (GA) with AIMS II and three-dimensional angularity (3DA) with XCT of aggregate surface area were proposed from these tests. Analysis of Variance (ANOVA) was employed to compare these two image analysis systems. Conventional experiments including the sand patch test and British pendulum test, were applied using the prepared aggregates to establish a correlation between the morphological properties of grains and the parameters related to the skid resistance of asphalt mixtures. It was found that the resistance performance of asphalt mixtures can be well described with a function using the value of morphological properties through regression analysis. The efficacy of the X-ray CT analyzing system was verified to evaluate the performance of asphalt mixture pavement precisely. The changes in morphological characteristics of particles are the main causes for degradation in the skid resistance of asphalt pavement.
Construction and Building Materials
Correlate aggregate angularity characteristics to the skid resistance of asphalt pavement based on image analysis technology.
Construction and Building Materials,
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