Abstract
Aggregate morphology consists of three independent components: form, angularity, and surface texture. As these three components act in different ways in affecting the performance of pavement layer, it is vital to characterize them objectively and accurately. In this study, the coordinates of boundary pixels of aggregate from 2-D images were treated as an equally spaced complex series. The description of the aggregate shape in the frequency domain was obtained by analyzing this complex series with the discrete Fourier transform (DFT). Based on this, the reconstruction of aggregate shape at different frequencies was performed, which validated that the three elements of aggregate shape correspond to different frequencies. In addition, by fitting the relationship between DFT coefficients and form parameters (elongation ratio, sphericity, mean radius, variance of radius), the frequencies contributing to the form properties of aggregate were identified. Moreover, prediction models for the elongation ratio, sphericity, mean, and variance of radius based on the DFT coefficients at the contributing frequencies were developed separately.
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More From: Transportation Research Record: Journal of the Transportation Research Board
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