Investigation of natural rock joint roughness

Yunfeng Ge, Pinnaduwa H.S.W. Kulatilake, Huiming Tang, Chengren Xiong

Research output: Contribution to journalArticle

57 Scopus citations

Abstract

The paper provides a comprehensive review on rock joint roughness measurement and quantification procedures. Superiority of fractal based methods over JRC, statistical parameters and statistical functions in quantifying roughness is discussed in the paper. Two of the best fractal based methodologies available in the literature, the modified 2-D divider and variogram methods, are used to quantify natural rock joint roughness in 3-D and 2-D, respectively. The capability of these two methods in accurate quantification of natural rock joint roughness is shown in the paper by applying the procedures to four natural rock joints. A good comparison has been obtained from the values obtained through the two methods. Both these methodologies have two parameters to capture the stationary roughness. The fractal dimension captures the spatial auto correlation of roughness; the other parameter captures the amplitude of roughness. Anisotropic roughness has been studied by applying two other methodologies: (a) a triangular plate methodology and (b) a light source methodology to the same four natural rock joints. A reasonably good comparison has been obtained through the results of these two methodologies. All four roughness quantification methodologies can be applied to any size of sample covering from laboratory to field scales. The results of the triangular plate and light source methodologies provided possible sliding direction values (under the gravitational loading) close to that reported in the literature for the rough discontinuity planes used in the study.

Original languageEnglish (US)
Pages (from-to)290-305
Number of pages16
JournalComputers and Geotechnics
Volume55
DOIs
StatePublished - Jan 1 2014

Keywords

  • Fractals
  • Measurement
  • Quantification
  • Rock joints
  • Roughness

ASJC Scopus subject areas

  • Geotechnical Engineering and Engineering Geology
  • Computer Science Applications

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