Determination of joint roughness coefficient using a cost-effective photogrammetry technique
Author:
Funder
Science and Engineering Research Board
Publisher
Springer Science and Business Media LLC
Subject
Geology,Geotechnical Engineering and Engineering Geology
Link
https://link.springer.com/content/pdf/10.1007/s10064-023-03135-1.pdf
Reference66 articles.
1. An P, Fang K, Jiang Q, Zhang H, Zhang Y (2021) Measurement of rock joint surfaces by using smartphone structure from motion (SFM) photogrammetry. Sensors 21(3):922. https://doi.org/10.3390/s21030922
2. Andrade PS, Saraiva AA (2008) Estimating the joint roughness coefficient of discontinuities found in metamorphic rocks. Bull Eng Geol Environ 67:425–434. https://doi.org/10.1007/s10064-008-0151-4
3. Babanouri N, Nasab SK, Sarafrazi S (2013) A hybrid particle swarm optimization and multi-layer perceptron algorithm for bivariate fractal analysis of rock fractures roughness. Int J Rock Mech Min Sci 60:66–74. https://doi.org/10.1016/j.ijrmms.2012.12.028
4. Bae D, Kim K, Koh Y, Kim J (2011) Characterization of joint roughness in granite by applying the scan circle technique to images from a borehole televiewer. Rock Mech Rock Eng 44:497–504. https://doi.org/10.1007/s00603-011-0134-9
5. Bandis S, Lumsden AC, Barton N (1981) Experimental studies of scale effects on the shear behaviour of rock joints. Int J Rock Mech Min Sci Geomech Abstr 18:1–21. https://doi.org/10.1016/0148-9062(81)91009-3
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3. New 2D joint roughness profiles based on pattern recognition technique;Bulletin of Engineering Geology and the Environment;2023-12-05
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