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dc.contributor.authorHou, Yue
dc.contributor.authorHuang, Yucheng
dc.contributor.authorSun, Fengyan
dc.contributor.authorGuo, Meng
dc.identifier.citationYue Hou, Yucheng Huang, Fengyan Sun, and Meng Guo, “Fractal Analysis on Asphalt Mixture Using a Two-Dimensional Imaging Technique,” Advances in Materials Science and Engineering, vol. 2016, Article ID 8931295, 7 pages, 2016. doi:10.1155/2016/8931295
dc.description.abstractFractal is a mathematical set that has a fractal dimension which usually exceeds its topological dimension and may be nonintegral. Since the asphalt pavement texture has limitations of randomness and self-similarity, fractal theory has been explored to quantify the asphalt pavement texture and employs good applicability in processing and analyzing the complex details of research object. In this paper, the 2D digital image of the pavement surface is measured in terms of area fractal dimension and contour fractal dimension, which are used to correlate with aggregate gradation and British Pendulum Number (BPN) value, respectively. It turns out the area fractal dimension of aggregate provides a simple way to acquire the continuous gradation of asphalt concrete sample and the contour fractal dimension is an available parameter to characterize roughness and friction of pavement surface texture.
dc.rightsCreative Commons Attribution 4.0 International
dc.titleFractal Analysis on Asphalt Mixture Using a Two-Dimensional Imaging Techniqueen_US
dc.typeArticle - Refereed
dc.description.versionPeer Reviewed
dc.rights.holderCopyright © 2016 Yue Hou et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
dc.title.serialAdvances in Materials Science and Engineeringen_US

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Creative Commons Attribution 4.0 International
License: Creative Commons Attribution 4.0 International