Quantification of Weathered Limestone Surfaces Using Fractal Methods
Alan Harris, Nick Hudyma, Stephanie Willen Brown, J. Oglesby
Abstract
Alan Harris, Nick Hudyma, Stephanie Willen Brown, J. Oglesby
Abstract
Weathering of rock produces rough surfaces. Profiles from twenty-two weathered limestone specimens were obtained using a high-resolution laser profilometer. Profiles were quantified using five different fractal methods: Modified Divider, Box Counting, Spectral, Semi-Variance, and Roughness Length. The fractal methods provided both fractal dimension and fractal intercept for each of the profiles. The five methods yielded different ranges of fractal dimensions and fractal intercepts. Results of fractal quantification, with the exception of Roughness Length dimension, compared favorably with visual roughness classifications. Since weathering typically affects higher order asperities, the fractal dimension is the most appropriate fractal parameter to assess roughness from weathering. Of the five fractal methods, it was determined that the Spectral or Semi-Variance methods were best to assess weathering roughness. These methods consistently provided fractal dimensions between 1 and 2, compared favorably with visual classification of smooth and rough specimens, and provided a wide range of fractal dimension values.
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Weathering of rock produces rough surfaces. Profiles from twenty-two weathered limestone specimens were obtained using a high-resolution laser profilometer. Profiles were quantified using five different fractal methods: Modified Divider, Box Counting, Spectral, Semi-Variance, and Roughness Length. The fractal methods provided both fractal dimension and fractal intercept for each of the profiles. The five methods yielded different ranges of fractal dimensions and fractal intercepts. Results of fractal quantification, with the exception of Roughness Length dimension, compared favorably with visual roughness classifications. Since weathering typically affects higher order asperities, the fractal dimension is the most appropriate fractal parameter to assess roughness from weathering. Of the five fractal methods, it was determined that the Spectral or Semi-Variance methods were best to assess weathering roughness. These methods consistently provided fractal dimensions between 1 and 2, compared favorably with visual classification of smooth and rough specimens, and provided a wide range of fractal dimension values.
Key concepts: Fractal dimension, Fractal, Fractal analysis, Surface finish, Multifractal system, Box counting, Surface roughness, Materials science