TY - GEN
T1 - Quantification of Weathered Limestone Surfaces Using Fractal Methods
AU - Harris, Alan
AU - Hudyma, Nick
AU - Brown, Stephanie
AU - Oglesby, Josh
N1 - Publisher Copyright:
© 2018 IEEE.
PY - 2018/10/1
Y1 - 2018/10/1
N2 - 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.
AB - 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.
KW - Fractal
KW - limestone
KW - roughness
UR - http://www.scopus.com/inward/record.url?scp=85056175484&partnerID=8YFLogxK
U2 - 10.1109/SECON.2018.8478894
DO - 10.1109/SECON.2018.8478894
M3 - Conference contribution
AN - SCOPUS:85056175484
T3 - Conference Proceedings - IEEE SOUTHEASTCON
BT - Southeastcon 2018
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2018 IEEE Southeastcon, Southeastcon 2018
Y2 - 19 April 2018 through 22 April 2018
ER -