Abstract
The volumetric discontinuity intensity (\(P_{32}\)) is defined as the total discontinuity area by rock mass volume. \(P_{32}\) has been considered the most suitable parameter to quantify discontinuities within rock masses because it takes into account density and size and does not depend on orientation. Currently, determining the \(P_{32}\) from discontinuity mapping of rock exposures requires a series of discrete fracture network (DFN) simulations. This method is time-consuming and requires advanced software; thus, it is generally not used in practical rock engineering applications. This paper proposes a new method to obtain the \(P_{32}\) of rock masses from 2D rock exposures, based on well-known weighted joint density (\({\text{wJd}}\)) and mean trace length (\(\mu_{\text{l}}\)) estimates. The method was developed and validated using DFN modeling and compared with \(P_{32}\) estimates obtained by computational simulations in a real case study (Monte Seco tunnel). Finally, the synthetic rock mass (SRM) modeling technique was used to investigate the effects of \(P_{32}\) on the mechanical behavior of a hypothetical rock mass, highlighting the individual contributions of \({\text{wJd}}\) and \(\mu_{\text{l}}\). The results demonstrate that the proposed method is reliable and can estimate the \(P_{32}\) of rock masses without requiring computation simulations. Moreover, the SRM analysis showed that discontinuity density and size have a similar impact on the mechanical behavior of rock masses with non-persistent discontinuity sets.
Highlights
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A new method for obtaining the volumetric intensity of rock masses from discontinuity mapping of 2D rock exposures.
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The method was developed and validated using parametric discrete fracture network analysis and applied in a tunneling case study.
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A synthetic rock mass case demonstrated the volumetric intensity and discontinuity size's contributions to the mechanical behavior of rock masses.
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Abbreviations
- \(P_{32}\) :
-
Volumetric discontinuity intensity (m−1)
- \(P_{32}^{{{\text{max}}}}\) :
-
Maximum volumetric discontinuity intensity (m−1)
- \(P_{20}\) :
-
Areal discontinuity density (m−2)
- \(P_{10}\) :
-
Linear discontinuity intensity (m−1)
- \({\text{wJd}}\) :
-
Weighted joint density (m−1)
- \({\text{wJd}}^{{\text{u}}}\) :
-
Unbiased weighted joint density (m−1)
- \(\delta_{\text{i}}\) :
-
Acute angle between the discontinuity dip and the mean rock face (°)
- \(A\) :
-
Area of the square-shape sampling window (m2)
- \(L\) :
-
Length of the square-shape sampling window’s edge (m)
- \(r\) :
-
Radius of the circular window (m)
- \(m\) :
-
Number of trace endpoints in the window
- \(n\) :
-
Number of trace endpoints cut by the window boundary
- \(f_{\text{i}}\) :
-
Correction factors for \(\delta_{\text{i}}\)
- \(\mu_{{\text{l}}}\) :
-
Unbiased mean trace length (m)
- \(\sigma_{{\text{l}}}\) :
-
Unbiased standard deviation of trace lengths (m)
- \(\mu_{{\text{D}}}\) :
-
Mean discontinuity diameter (m)
- \(\sigma_{{\text{D}}}\) :
-
Standard deviation of discontinuity diameter (m)
- \({\text{CoV}}\) :
-
Coefficient of variation of discontinuity diameters
- \(C_{31}\) :
-
Constant factors for \(P_{10}\)
- \(C_{32}\) :
-
Constant factors for \(P_{20}\) (m)
- \(S_{{\text{f}}}\) :
-
Biased size factor
- \(S_{{\text{f}}}^{{\text{u}}}\) :
-
Unbiased size factor
- \(V_{{\text{f}}}\) :
-
Size variation factor
- \({\text{UCS}}_{{\text{i}}}\) :
-
Uniaxial compressive strength of the intact rock (MPa)
- \({\text{UCS}}_{{\text{m}}}\) :
-
Uniaxial compressive strength of the synthetic rock mass (MPa)
References
Baecher G, Lanney NA, Einstein HH (1977) Statistical description of rock properties and sampling. In: Proceedings of the 18th U.S. symposium on rock mechanics (USRMS). Colorado School of Mines Press, pp 5C1_1–5C1_8
Cacciari PP, Futai MM (2016a) Integrating terrestrial laser scanning and discrete fracture networks approaches for tunnel modelling in fractured rock masses. In: Anais do VII Simpósio Brasileiro de Mecânica das Rochas. https://doi.org/10.20906/cps/sbmr-06-0030
Cacciari PP, Futai MM (2016b) Mapping and characterization of rock discontinuities in a tunnel using 3D terrestrial laser scanning. Bull Eng Geol Environ 75:223–237. https://doi.org/10.1007/s10064-015-0748-3
Cacciari PP, Futai MM (2017) Modeling a shallow rock tunnel using terrestrial laser scanning and discrete fracture networks. Rock Mech Rock Eng 50:1217–1242. https://doi.org/10.1007/s00603-017-1166-6
Cacciari PP, Futai MM (2021) The influence of fresh and weathered rock foliation on the stability of the monte seco tunnel. Rock Mech Rock Eng 54:537–558. https://doi.org/10.1007/s00603-020-02292-z
Cacciari PP, Morikawa DS, Futai MM (2015) Modelling a railway rock tunnel using terrestrial laser scanning and the distinct element method. In: ISRM regional symposium—8th South American Congress on Rock Mechanics, SACRM 2015 2015-Novem:101–108. https://doi.org/10.3233/978-1-61499-605-7-101
Chilès JP, Wackernagel H, Beucher H, Lantuéjoul C, Elion P (2008) Estimating fracture density from a linear or aerial survey. In: Proceedings of the eighth international geostatistics congress. Gecamin Ltda, Santiago, pp 535–544
Dershowitz WS, Herda HH (1992) Interpretation of fracture spacing and intensity. In: 33th U.S. symposium on rock mechanics (USRMS). Santa Fe, pp 757–766
Elmo D, Donati D, Stead D (2018) Challenges in the characterisation of intact rock bridges in rock slopes. Eng Geol 245:81–96. https://doi.org/10.1016/j.enggeo.2018.06.014
Elmo D, Stead D, Yang B et al (2021) A new approach to characterise the impact of rock bridges in stability analysis. Rock Mech Rock Eng. https://doi.org/10.1007/s00603-021-02488-x
Fekete S, Diederichs M, Lato M (2010) Geotechnical and operational applications for 3-dimensional laser scanning in drill and blast tunnels. Tunn Undergr Sp Technol 25:614–628. https://doi.org/10.1016/j.tust.2010.04.008
Han X, Chen J, Wang Q et al (2016) A 3D fracture network model for the undisturbed rock mass at the Songta Dam site based on small samples. Rock Mech Rock Eng 49:611–619. https://doi.org/10.1007/s00603-015-0747-5
Havaej M, Coggan J, Stead D, Elmo D (2016) A combined remote sensing–numerical modelling approach to the stability analysis of delabole slate quarry, Cornwall, UK. Rock Mech Rock Eng 49:1227–1245. https://doi.org/10.1007/s00603-015-0805-z
Hekmatnejad A, Emery X, Brzovic A et al (2017) Investigating the impact of the estimation error of fracture intensity (P32) on the evaluation of in-situ rock fragmentation and potential of blocks forming around tunnels. Tunn Undergr Sp Technol. https://doi.org/10.1016/j.tust.2020.103596
Hekmatnejad A, Crespin B, Opazo A et al (2020) Spatial modeling of discontinuity intensity from borehole observations at El Teniente mine, Chile. Eng Geol 228:97–106. https://doi.org/10.1016/j.enggeo.2017.07.012
Kulatilake PHSW, Wu TH (1984a) Estimation of mean trace length of discontinuities. Rock Mech Rock Eng 17:215–232. https://doi.org/10.1007/BF01032335
Kulatilake PHSW, Wu TH (1984b) The density of discontinuity traces in sampling windows. Int J Rock Mech Min Sci Geomech Abstr 21:345–347. https://doi.org/10.1016/0148-9062(84)90367-X
Lato M, Kemeny J, Harrap RM, Bevan G (2013) Rock bench: Establishing a common repository and standards for assessing rockmass characteristics using LiDAR and photogrammetry. Comput Geosci 50:106–114. https://doi.org/10.1016/j.cageo.2012.06.014
Mah J, Samson C, McKinnon SD (2011) 3D laser imaging for joint orientation analysis. Int J Rock Mech Min Sci 48:932–941. https://doi.org/10.1016/j.ijrmms.2011.04.010
Mas Ivars D, Pierce ME, Darcel C et al (2011) The synthetic rock mass approach for jointed rock mass modelling. Int J Rock Mech Min Sci 48:219–244. https://doi.org/10.1016/j.ijrmms.2010.11.014
Mauldon M (1998) Estimating mean fracture trace length and density from observations in convex windows. Rock Mech Rock Eng 31:201–216. https://doi.org/10.1007/s006030050021
Mauldon M, Dunne WM, Jr MBR (2001) Circular scanlines and circular windows: new tools for characterizing the geometry of fracture traces. 23:247–258
Palmstrom A (2005) Measurements of and correlations between block size and rock quality designation (RQD). Tunn Undergr Sp Technol 20:362–377. https://doi.org/10.1016/j.tust.2005.01.005
Priest SD (1993) Discontinuity analysis for rock engineering. Springer, London
Rasmussen LL, Cacciari PP, Futai MM et al (2019) Efficient 3D probabilistic stability analysis of rock tunnels using a Lattice Model and cloud computing. Tunn Undergr Sp Technol 85:282–293. https://doi.org/10.1016/j.tust.2018.12.022
Rogers S, Elmo D, Webb G, Catalan A (2014) Volumetric fracture intensity measurement for improved rock mass characterisation and fragmentation assessment in block caving operations. Rock Mech Rock Eng 48:633–649. https://doi.org/10.1007/s00603-014-0592-y
Schlotfeldt P, Carter TG (2018) A new and unified approach to improved scalability and volumetric fracture intensity quantification for GSI and rockmass strength and deformability estimation. Int J Rock Mech Min Sci 110:48–67. https://doi.org/10.1016/j.ijrmms.2018.06.021
Shang J, West LJ, Hencher SR, Zhao Z (2018) Geological discontinuity persistence: implications and quantification. Eng Geol 241:41–54. https://doi.org/10.1016/j.enggeo.2018.05.010
Sturzenegger M, Stead D (2009) Close-range terrestrial digital photogrammetry and terrestrial laser scanning for discontinuity characterization on rock cuts. Eng Geol 106:163–182. https://doi.org/10.1016/j.enggeo.2009.03.004
Sturzenegger M, Stead D, Elmo D (2011) Terrestrial remote sensing-based estimation of mean trace length, trace intensity and block size/shape. Eng Geol 119:96–111. https://doi.org/10.1016/j.enggeo.2011.02.005
Terzaghi RD (1965) Sources of error in joint surveys. Géotechnique 15:287–304. https://doi.org/10.1680/geot.1965.15.3.287
Wu Q, Kulatilake PHSW, Tang H (2011) Comparison of rock discontinuity mean trace length and density estimation methods using discontinuity data from an outcrop in Wenchuan area, China. Comput Geotech 38:258–268. https://doi.org/10.1016/j.compgeo.2010.12.003
Zhang L, Einstein HH (1998) Estimating the mean trace length of rock discontinuities. Rock Mech Rock Eng 31:217–235. https://doi.org/10.1007/s006030050022
Zhang L, Einstein HH (2000) Estimating the intensity of rock discontinuities. Int J Rock Mech Min Sci 37:819–837. https://doi.org/10.1016/S1365-1609(00)00022-8
Zhang L, Einstein HH (2010) The planar shape of rock joints. Rock Mech Rock Eng 43:55–68. https://doi.org/10.1007/s00603-009-0054-0
Zhang L, Einstein HH, Dershowitz WS (2002) Stereological relationship between trace length and size distribution of elliptical discontinuities. Géotechnique 52:419–433. https://doi.org/10.1680/geot.2002.52.6.419
Zhang Q, Wang Q, Chen J et al (2016) Estimation of mean trace length by setting scanlines in rectangular sampling window. Int J Rock Mech Min Sci 84:74–79. https://doi.org/10.1016/j.ijrmms.2016.02.002
Acknowledgements
The authors would like to thank the Brazilian National Council for Scientific and Technological Development (CNPq) logistical and financial support.
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Cacciari, P.P., Futai, M.M. A Practical Method for Estimating the Volumetric Intensity of Non-persistent Discontinuities on Rock Exposures. Rock Mech Rock Eng 55, 6063–6078 (2022). https://doi.org/10.1007/s00603-022-02966-w
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DOI: https://doi.org/10.1007/s00603-022-02966-w