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Correlations between various rock mass classification / characterization systems for the Zagros tunnel-W Iran

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Abstract

This study deals with the comparative investigation on various classification/characterization systems for sedimentary rocks in two parts, 40 km-long of the Zagros tunnel, west of Iran. The results of extensive geotechnical explorations and field measurements were applied to obtain the rock mass classification/characterization systems such as Rock Mass Rating (RMR), Rock Condition Rating (RCR), Q-system (Q), Rock Mass Number (QN), Rock Mass index (RMi), Rock Structure Rating (RSR), and Geological Strength Index (GSI) for a wide range of sedimentary rocks. A set of systems inter-relationship is proposed. Some of these correlation relations such as RMR-Q, RMR-RMi, RMi-Q, RCR, GSI-GSI(Cai) are similar to the one or more relations proposed in the previous studies, however, some of them such as RSR-RMR, RSR-Q, RCR-QN and GSI-RMR are not similar to the previous works. Joint set orientation and joint set number are more important parameters that cause weak correlation coefficients where both side classifications are not similar in considering them in calculating values. So it is proposed to find relations between any pairs of systems that both of them consider or not consider these parameters. The relations are proposed for a wide range of sedimentary rocks and can be applied for similar geological environments

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References

  • Abad J, Celada B, Chacon E, et al. (1983) Application of geomechanical classification to predict the convergence of coal mine galleries and to design their supports. In: 5th ISRM Congress, Melbourne, Australia, pp 1–5.

  • Aksoy CO (2008) Review of rock mass rating classification: historical developments, applications, and restrictions. Journal of Mining Science, 44(1): 51–63. https://doi.org/10.1007/s10913-008-0005-2.

    Google Scholar 

  • Al-Harthi AA (1993) Application of CSIR and NGI classification systems along tunnel no. 3 at Al-Dela descent, Asir Province, Saudi Arabia. In: Cripps JC, Coulthard JM, Culshaw MG, et al. (eds.) The Engineering Geology of Weak Rock. Balkerma, Rotterdam.

    Google Scholar 

  • Alashti MS (2018) New Empirical relations for determination of rock slope safety factor in fully drained conditions on section RS06 of block five in Sungun copper mine. East African Scholars Multidisciplinary Bulletin 4413(3): 61–121.

    Google Scholar 

  • Alavi M (1994) Tectonics of the Zagros orogenic belt of Iran: new data and interpretations. Tectonophysics 229(3–4): 211–238.

    Google Scholar 

  • Alavi M (2004) Regional stratigraphy of the Zagros fold-thrust belt of Iran and its proforeland evolution. American Journal of Science 304(1): 1–20.

    Google Scholar 

  • Ali W, Mohammad N, Tahir M (2014) Rock Mass Characterization for Diversion Tunnels at Diamer Basha Dam, Pakistan-a design perspective. International Journal of Science and Engineering Technologies 3(10): 1292–1296.

    Google Scholar 

  • Andriani GF, Parise M (2017) Applying rock mass classifications to carbonate rocks for engineering purposes with a new approach using the rock engineering system. Journal of Rock Mechanics and Geotechnical Engineering 9(2): 364–369. https://doi.org/10.1016/j.jrmge.2016.12.001

    Google Scholar 

  • Arjmandzadeh R, Sharifi Teshnizi E, Rastegarnia A, Golian M, et al. (2019) GIS Based Landslide Susceptibility Mapping in Qazvin Province of Iran. Iranian Journal of Science and Technology, Transactions of Civil Engineering; https://doi.org/10.1007/s40996-019-00326-3

  • Aydan Ö, Ulusay R, Tokashiki N (2014) A new rock mass quality rating system: Rock Mass Quality Rating (RMQR) and its application to the estimation of geomechanical characteristics of rock masses. Rock Mechanics and Rock Engineering 47(4): 1255–1276. https://doi.org/10.1007/s00603-013-0462-z

    Google Scholar 

  • Babets D V, Sdvyzhkova, Larionov MH, et al (2017) Estimation of rock mass stability based on probability approach and rating systems. Journal of Rock Mechanics and Geotechnical Engineering 9(6): 993–1009. https://doi.org/10.1016/j.jrmge.2017.07.007

    Google Scholar 

  • Bar N, Barton N (2017) The Q-slope method for rock slope engineering. Rock Mechanics and Rock Engineering 50(12): 3307–22. https://doi.org/10.1007/s00603-017-1305-0

    Google Scholar 

  • Barton N (1995) The influence of joint properties in modelling jointed rock masses. In: 8th ISRM Congress, Tokyo, Japan, pp 25–29.

  • Barton N (1999) TBM performance estimation in rock using QTBM. T & T International 31(9): 30–34.

    Google Scholar 

  • Barton N (2002) Some new Q-value correlations to assist in site characterisation and tunnel design. International Journal of Rock Mechanics and Mining Sciences 39(2): 185–216. https://doi.org/10.1016/S1365-1609(02)00011-4.

    Google Scholar 

  • Barton N, Lien R, Lunde J (1974) Engineering classification of rock masses for the design of tunnel support. Rock Mechanics 6(4): 189–236. https://doi.org/10.1007/BF01239496.

    Google Scholar 

  • Basahel H, Mitri H (2017) Application of rock mass classification systems to rock slope stability assessment: A case study. Journal of Rock Mechanics and Geotechnical Engineering 9(6): 993–1009. https://doi.org/10.1016/j.jrmge.2017.07.007

    Google Scholar 

  • Berberian M (1995) Master blind thrust faults hidden under the Zagros folds: active basement tectonics and surface morphotectonics. Tectonophysics 241(3–4): 193–224. https://doi.org/10.1016/0040-1951(94)00185-C

    Google Scholar 

  • Bieniawski ZT (1974) Geomechanics classification of rock masses and its application in tunneling. In: Proceedings of the 3rd Conference of International Society of Rock Mechanics, Denver, USA, pp 27–32.

  • Bieniawski ZT (1976) Rock mass classification in rock engineering applications. In: Proceedings of a Symposium on Exploration for Rock Engineering. Cape Town, Balkema, 97–106.

  • Bieniawski ZT (1979) Engineering rock mass classification-new aid for engineers and geologists. Earth and Mineral Sciences 49(1): 1–5.

    Google Scholar 

  • Bieniawski ZT (1989) Engineering Rock Mass Classifications: A Complete Manual for Engineers and Geologists in Mining, Civil, and petroleum engineering. John Wiley & Sons, p 250.

  • Bieniawski ZT (1993) The RMR system and future trends. Comprehensive rock engineering. In: J. A. Hudson (ed.) Classification of Rock Masses for Engineering 3: 553–573.

    Google Scholar 

  • Brook N, Dharmaratne GR (1985) Simplified rock mass rating system for mine tunnel support. Transactions-Institution of Mining and Metallurgy 94: 148–154.

    Google Scholar 

  • Cai M, Kaiser PK, Uno H, et al. (2004) Estimation of rock mass deformation modulus and strength of jointed hard rock masses using the GSI system. International Journal of Rock Mechanics and Mining Sciences 41(1): 3–19. https://doi.org/10.1016/S1365-1609(03)00025-X

    Google Scholar 

  • Cameron-Clarke IS, Budavari S (1981) Correlation of rock mass classification parameters obtained from borecore and in-situ observations. Engineering Geology 17(1–2): 19–53. https://doi.org/10.1016/0013-7952(81)90019-3

    Google Scholar 

  • Castro Caicedo A de J, Pérez Pérez DM (2013) Correlation Between The RMR and Q Geomechanical Classifications at “LA LÍNEA” Exp; pratory Tunnel, Colombian Centeral Andes. Earth Science Bulletin (34): 42–50.

    Google Scholar 

  • Celada B, TardáguilaCelada, B. et al. (2014) Actualización y Mejora del RMR,” IGP-InGeoPress 234: 18–22.

    Google Scholar 

  • Choquet P, Hadjigogiu J. (1993) Design of support for underground excavations. In Hudson JA (ed.): Comprehensive Rock Engineering: Principles, Practice and Projects. Pergamon Press, Oxford 4: 313–348.

    Google Scholar 

  • Cosar S. (2004) Application of rock mass classification systems for future support design of the Dim tunnel near Alanya, Master of Science thesis in mining engineering, Middle East Technical University, Ankara Turkey. p.217.

    Google Scholar 

  • Csen Z, Sadagah BH (2003) Modified rock mass classification system by continuous rating. Engineering Geology 67(3–4): 269–80. https://doi.org/10.1016/S0013-7952(02)00185-0

    Google Scholar 

  • Deere D (1988) The rock quality designation (RQD) index in practice. In: Rock Classification Systems for Engineering Purposes. ASTM International.

  • Deere DU, Miller RP (1966) Engineering classification and index properties for intact rock. Technical Report No. AFNL-TR-65-116, Air Force Weapon Laboratory, New Mexico.

    Google Scholar 

  • El-Naqa A (1994) Rock mass characterisation of Wadi Mujib dam site, Central Jordan. Engineering Geology 38(1–2):81–93.

    Google Scholar 

  • Franklin JA (1971) Triaxial strength of rock materials. Rock Mechanics, 3(2): 86–98.

    Google Scholar 

  • Goel RK, Jethwa JL, Paithankar AG (1995a) Indian experiences with Q and RMR systems. Tunneling and Underground Space Technology 10(1): 97–109. https://doi.org/10.1016/0886-7798(94)00069-W

    Google Scholar 

  • Goel RK, Jethwa JL, Paithankar AG (1995b) Tunnelling through the young Himalayas, a case history of the Maneri-Uttarkashi power tunnel. Engineering Geology 39(1–2): 31–44. https://doi.org/10.1016/0013-7952(94)00002-J

    Google Scholar 

  • Goel RK, Jethwa JL, Paithakar AG (1996) Correlation between Barton’s Q and Bieniawski’s RMR- A new approach. International Journal of Rock Mechanics and Mining Sciences and Geomechanics Abstracts, 33(7), 307A

    Google Scholar 

  • Hashemi M, Moghaddas S, Ajalloeian R (2010) Application of rock mass characterization for determining the mechanical properties of rock mass: A comparative study. Journal of Rock Mechanics and Geotechnical Engineering 43(3): 305–20. https://doi.org/10.1007/s00603-009-0048-y

    Google Scholar 

  • Hemmati Nourani M, Taheri Moghadder M, Safari M (2017) Classification and assessment of rock mass parameters in Choghart iron mine using P-wave velocity. Journal of Rock Mechanics and Geotechnical Engineering 9(2):318–28. https://doi.org/10.1016/j.jrmge.2016.11.006

    Google Scholar 

  • Hoek E (1994) Strength of rock and rock masses, ISRM News Journal 2(2):4–16.

    Google Scholar 

  • Hoek E (2002) A brief history of the development of the Hoek-Brown failure criterion. Online material, www.rocscience.com, 7 pages.

  • Hoek E, Brown ET, (1997) Practical estimates of rock mass strength International Journal of Rock Mechanics and Mining Sciences: 34(8): 1165–86. https://doi.org/10.1016/S1365-1609(97)80069-X

    Google Scholar 

  • Hoek E, Marinos P, Benissi M (1998) Applicability of the Geological Strength Index (GSI) classification for very weak and sheared rock masses, the case of the Athens Schist formation. Bulletin of Engineering Geology and the Environment 57(2): 151–60. https://doi.org/10.1007/s100640050031

    Google Scholar 

  • Hsiao FY, Wang CL, Chern JC (2009) Numerical simulation of rock deformation for support design in tunnel intersection area. Tunneling and Underground Space Technology 24(1): 14–21. https://doi.org/10.1016/j.tust.2008.01.003

    Google Scholar 

  • Irvani I, Wilopo W, Karnawati D (2013) Determination of Nuclear Power Plant Site in West Bangka Based on Rock Mass Rating and Geological. Journal of Southeast Asian Applied Geology 5(2): 78–86. https://doi.org/10.22146/jag.7210

    Google Scholar 

  • International Society for Rock Mechanics (ISRM) (1978) Rock characterization, Testing and Monitoing, Suggested methods for the quantitative description of discontinuties in rock masses, International Journal of Rock Mechanics and Mining Science 15:319–368.

    Google Scholar 

  • Kaiser TK, Gale AD (1985) Evaluation of cost and emprical support design at BC Rail Tumbler Ridge tunnels. Canadian Tunnelling, Tunnelling Association of Canada. Wiley, New York, pp 77–106.

    Google Scholar 

  • Kendorski FS, Cummings RA, Bieniawski ZT, Skinner EH, et al. (1983) Rock mass classification for block caving mine drift support. In: 5th ISRM Congress, Melbourne, Australia, pp 1–13.

  • Kumar N, Samadhiya NK, Anbalagan R (2004) Application of rock mass classification systems for tunneling in Himalaya, India. International Journal of Rock Mechanics and Mining Sciences 41: 852–857. https://doi.org/10.1016/j.ijrmms.2004.03.147

    Google Scholar 

  • Laderian A, Abaspoor MA (2012) The correlation between RMR and Q systems in parts of Iran. Tunneling and Underground Space Technology 27(1): 149–58. https://doi.org/10.1016/j.tust.2011.06.001

    Google Scholar 

  • Laubscher DH (1977) Geomechanics classification of jointed rock masses-mining applications. Transactions of the Institution of Mining and Metallurgy 86: A1–A8.

    Google Scholar 

  • Lauffer H (1958) Classification for tunnel construction. Geologie und Bauwesens 24(1): 46–51.

    Google Scholar 

  • Li Y, Zhang S, Zhang X (2018) Classification and fractal characteristics of coal rock fragments under uniaxial cyclic loading conditions. Arabian Journal of Geosciences 11(9): 1–12. https://doi.org/10.1007/s12517-018-3534-2

    Google Scholar 

  • Lin F, Luan H, Zeng Y, Zhong Z (2017) Some new correlations of Q-value with rock mechanics parameters in underground oil storage caverns. Civil Engineering Journal, 3(8): 537–46. https://doi.org/10.28991/cej-2017-00000111.

    Google Scholar 

  • Marinos P, Hoek E et al. (2000) GSI: a geologically friendly tool for rock mass strength estimation. In: ISRM International Symposium. Melbourne, Australia, pp 1–19.

  • Marinos V (2014) Tunnel behaviour and support associated with the weak rock masses of flysch. Journal of Rock Mechanics and Geotechnical Engineering 6(3): 227–39. https://doi.org/10.1016/j.jrmge.2014.04.003

    Google Scholar 

  • Marinos VA (2019) A revised, geotechnical classification GSI system for tectonically disturbed heterogeneous rock masses, such as flysch. Bulletin of Engineering Geology and the Environment 78(2): 899–912. https://doi.org/10.1007/s10064-017-1151-z

    Google Scholar 

  • Matula M, Holzer R (1978) Engineering topology of rock masses. In: Proceedings of Felsmekanik Kolloquium, Grundlagen ung Andwendung der Felsmekanik, Karlsruhe, Germany, 107–21.

  • Mohammadi M, Hossaini MF (2017) Modification of rock mass rating system: Interbedding of strong and weak rock layers. Journal of Rock Mechanics and Geotechnical Engineering 9(6): 1165–70. https://doi.org/10.1016/j.jrmge.2017.06.002

    Google Scholar 

  • Morales T, Uribe-Etxebarria G, Uriarte JA, et al. (2004) Geomechanical characterisation of rock masses in Alpine regions: the Basque arc (Basque-Cantabrian basin, northern Spain). Engineering Geology 71(3–4): 343–62. https://doi.org/10.1016/S0013-7952(03)00160-1

    Google Scholar 

  • Moreno TE (1980) Application de las c1assificaciones geomechnicas a los tuneles de parjares. 11st Cursode Sostenimientos Activosen Galeriasy Tunnels. Found Gomez Parto, Madrid, Spain.

    Google Scholar 

  • Osgoui R Ünal E. (2005) Rock reinforcement design for unstable tunnels originally excavated in very poor rock mass. 31st ITAAITES World Tunnel Congress, Istanbul, Turkey, 291–296.

  • Palmström A (1995) RMi-A Rock Mass Characterization System for Rock Engineering Purposes. PhD Thesis, Oslo University, Norway, p 400.

    Google Scholar 

  • Palmström A (2000) On classification systems. In: Proceedings of Workshop on Reliablity of Classification Systems a Part of the International Conference of Geological Engineering. GeoEng2000, Melbourne, Australia, 1–5.

  • Patching TH, Coates DF (1968) A recommended rock classification for rock mechanics purposes. Canadian Mining and Metallurgical Bulletin 61(678): 1195–1197.

    Google Scholar 

  • Piteau DR (1973) Characterizing and extrapolating rock joint properties in engineering practice. In Geomechanik—Fortschritte in der Theorie und deren Auswirkungen auf die Praxis/Geomechanics—Progress in Theory and Its Effects on Practice, Springer, Vienna, p. 5–31.

    Google Scholar 

  • Poorbehzadi K, Yazdi A, Sharifi Teshnizi E, Dabiri R (2019) Investigating of Geotechnical Parameters of Alluvial Foundation in Zaram-Rud Dam Site, North Iran. International Journal of Mining Engineering and Technology 1(1):33–44. https://uniquepubinternational.com/upi-journals/international-journal-mining-engineering-technology-ijmet/

    Google Scholar 

  • Von Preinl ZT, Tamames BC, Fernandez JM, et al. (2006) Rock mass excavability indicator: New way to selecting the optimum tunnel construction method. Tunneling and Underground Space Technology 21(3–4): 237.

    Google Scholar 

  • Rabcewicz LV (1965a) The New Austrian Tunnelling Method, Water Power, Part III-17(1): 19–24.

    Google Scholar 

  • Rabcewicz LV (1965b) The new Austrian Tunnelling Method. Water Power, Part II-16(12): 511–515.

    Google Scholar 

  • Rafiee R (2013) Tunnels stability analysis using binary and multinomial logistic regression (LR). Journal of Geology and Mining Research 5(4): 97–107. https://doi.org/10.5897/jgmr2013.0176

    Google Scholar 

  • Rahimi E, Sharifi Teshnizi E, Rastegarnia A, Motamed Al-Shariati E (2019) Cement take estimation using neural networks and statistical analysis in Bakhtiari and Karun 4 dam sites, in south west of Iran. Bulletin of Engineering Geology and the Environment 78: 2817–2834. https://doi.org/10.1007/s10064-018-1271-0

    Google Scholar 

  • Ramamurthy T, Arora VK (1993) A classification for intact and jointed rocks. In: Anagnostopoulos A, Frank R and Kalteziotis N (eds.) Geotechnical Engineering of Hard Soils-Soft Rocks, Taylor and Francis, Rotterdam, p. 235–242.

    Google Scholar 

  • Ranasooriya J, Nikraz H (2012) Reliability of the linear correlation of rock mass rating (RMR) and tunnelling quality index (Q). Australian Geomechanics, 44(2): 47–54.

    Google Scholar 

  • Rastegarnia A, Sharifi Teshnizi E, Hosseini S, Shamsi H, et al. (2018) Estimation of punch strength index and static properties of sedimentary rocks using neural networks in south west of Iran. Measurement, 128:464–478. https://doi.org/10.1016/j.measurement.2018.05.080

    Google Scholar 

  • Rehman H, Ali W, Naji AM, et al. (2018a) Review of Rock-Mass Rating and Tunneling Quality Index Systems for tunnel design: development, definement, application and limitation. Applied Sciences, 8(8): 1250. https://doi.org/10.3390/app8081250

    Google Scholar 

  • Rehman H, Naji A, Kim J, Yoo H-K (2018b) Empirical evaluation of Rock Mass Rating and Tunneling Quality Index system for Tunnel support design. Applied Sciences 8(5): 782. https://doi.org/10.3390/app8050782

    Google Scholar 

  • Rocscience (2002) Dips User’s Guide. Rocscience Inc, Toronto, Ontario, Canada.

    Google Scholar 

  • Romana M (1985) New adjustment ratings for application of Bieniawski classification to slopes. In: Proceedings of the International Symposium on Role of Rock Mechanics, Zacatecas, Mexico. pp: 49–53.

  • Romana MR. (1993) A geomechanical classification for slopes. In: Hudson JA (ed.) Slope Mass Rating in Comprehensive Rock Engineering, Principles—Practice and PROJECTS. Pergamon Press, New York,USA, chapter 3: 575–600.

    Google Scholar 

  • Rutledge JC, Preston RL (1978) New Zealand experience with engineering classifications of rock for the prediction of tunnel support. In: Proceedings of the International Tunnelling Symposium, Tokyo, Japan, A3.1–A3.7

  • Sadeghi S, Yassaghi A (2016) Spatial evolution of Zagros collision zone in Kurdistan, NW Iran: Constraints on Arabia-Eurasia oblique convergence. Solid Earth. 7(2): 659–72. https://doi.org/10.5194/se-7-659-2016

    Google Scholar 

  • Santos V, da Silva P, Brito M (2018) Estimating RMR values for underground excavations in a rock mass. Minerals 8(3): 78. https://doi.org/10.3390/min8030078

    Google Scholar 

  • Sari D, Pasamehmetoglu AG (2004) Proposed support design, Kaletepe tunnel, Turkey. Engineering Geology 72(3–4): 201–16. https://doi.org/10.1016/j.enggeo.2003.08.003

    Google Scholar 

  • Saroglou C, Qi S, Guo S, Wu F (2019) ARMR, a new classification system for the rating of anisotropic rock masses. Bulletin of Engineering Geology and the Environment 78(5): 3611–26. https://doi.org/10.1007/s10064-018-1369-4

    Google Scholar 

  • Sayeed I, Khanna R. (2015) Empirical correlation between RMR and Q systems of rock mass classification derived from Lesser Himalayan and Central. In: International Conference on “Engineering Geology in New Millennium”. New Delhi, India, 1–12.

  • Senra K. (2016) Correlations between geomechanical properties to amphibolites and schists from south of Minas Gerais state, Brazil. Master of Science Thesis in Civil Engineering, Universidade Federal de Viçosa, Viçosa, Brazil. p.160.

    Google Scholar 

  • Singh B, Goel RK (1999) Rock Mass Classification: A Practical Approach in Civil Engineering. Vol. 46. Elsevier, Netherland. p.265.

    Google Scholar 

  • Singh JL, Tamrakar NK (2013) Rock mass rating and geological strength index of rock masses of Thopal-Malekhu river areas, central Nepal lesser himalaya. Bulletin of the Department of Geology 16: 29–42.

    Google Scholar 

  • Somodi G, Krupa Á, Kovács L, et al. (2018) Comparison of different calculation methods of Geological Strength Index (GSI) in a specific underground construction site. Engineering Geology 243(4): 50–58. https://doi.org/10.1016/j.enggeo.2018.06.010

    Google Scholar 

  • Song Y, Xue H, Ju G (2020) Comparison of different approaches and development of improved formulas for estimating GSI. Bulletin of Engineering Geology and the Environment. https://doi.org/10.1007/s10064-020-01739-5

  • Sonmez H, Ulusay R (1999) Modifications to the geological strength index (GSI) and their applicability to stability of slopes. International Journal of Rock Mechanics and Mining Sciences 36(6): 743–60. https://doi.org/10.1016/S0148-9062(99)00043-1

    Google Scholar 

  • Sonmez H, Ulusay R (2002) A discussion on the Hoek-Brown failure criterion and suggested modifications to the criterion verified by slope stability case studies. Bulletin for Earth Science 26(1): 77–99.

    Google Scholar 

  • Soufi A, Bahi L, Ouadif L, Kissai JE (2018) Correlation between Rock mass rating, Q-system and Rock mass index based on field data. MATEC Web of Conferences, 149: 02030. 1–7. https://doi.org/10.1051/matecconf/201814902030

    Google Scholar 

  • Stille H, Groth T, Fredriksson A (1982) FEM-analysis of rock mechanical problems with JOBFEM. Stiftelsen Bergteknisk Forskning-BeFo, Stockholm 307(1): 82.

    Google Scholar 

  • Stocklin J. (1968) Structural history and tectonics of Iran: a review. American association of Petroleum Geologists Bulletin 52(7): 1229–1258.

    Google Scholar 

  • Terzaghi K. (1946) Rock Defects and Loads on Tunnel Supports. Harvard University, p.95.

  • Tugrul A (1998) The application of rock mass classification systems to underground excavation in weak limestone, Ataturk dam, Turkey. Engineering Geology 50(3–4): 337–345.

    Google Scholar 

  • Unal E (1996) Modified rock mass classification: M-RMR system. Milestones in Rock Engineering, A. A. Balkema

  • de Vallejo LI (1985) Tunnelling evaluation using the Surface Rock Mass Classification System SRC. In: International Sympusium ISRM on role of Rock Mechanics in Excavations for Mining and Civil Works, Zacatecas, Mexico.

  • de Vallejo LI (2003) SRC rock mass classification of tunnels under high tectonic stress excavated in weak rocks. Engineering Geology 69(3–4): 273–285.

    Google Scholar 

  • de Vallejo LI (1983) A new rock classification system for underground assessment using surface data. In: International Symposium on Engineering Geology and Underground Construction. Portugal, p. II-85.

  • Warren SN, Kallu RR, Barnard CK (2016) Correlation of the Rock Mass Rating (RMR) system with the Unified Soil Classification System (USCS): Introduction of the Weak Rock Mass Rating System (W-RMR). Rock mechanics and rock engineering 49(11): 4507–4518. https://doi.org/10.1007/s00603-016-1090-1

    Google Scholar 

  • Wickham GE, Tiedemann Hr, Skinner EH (1972) Support determinations based on geologic predictions. In: Proceedings of the Rapid Excavation Tunnelling Conference, New York, USA. pp: 43–64.

  • Williamson DA (1984) Unified rock classification system. Bulletin of Engineering Geology and the Environment 21(3): 345–54.

    Google Scholar 

  • Yan-jun S, Rui-xin Y, Geng-she Y, Guang-li X, Shan-yong W (2017) Comparisons of Evaluation Factors and Application Effects of the New [BQ] GSI System with International Rock Mass Classification Systems. Geotechnical and Geological Engineering 35(6): 2523–2548. https://doi.org/10.1007/s10706-017-0259-z

    Google Scholar 

  • Zhang Q, Huang X, Zhu H, Li J (2019) Quantitative assessments of the correlations between rock mass rating (RMR) and Geological Strength Index (GSI). Tunneling and Underground Space Technology 83:73–81. https://doi.org/10.1016/j.tust.2018.09.015

    Google Scholar 

  • Zienkiewicz OC, Stagg KG (1969) Rock Mechanics in Engineering Practice. John Wiley & Sons, London, UK. p 442.

    Google Scholar 

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Acknowledgements

The author would like to thank anonymous reviewers for the useful discussions on this manuscript. Thanks are expressed to the Dr. E Mokhtari and Dr. M Fatollahi for their kind help to provide field data.

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  1. Department of Geology, Faculty of science, Imam Khomeini International University, Qazvin, 34149-16818, Iran

    Shahriar Sadeghi

  2. Engineering Geology, Young Researchers and Elite Club, Shahrekord Branch, Islamic Azad University, Shahrekord, 15655-461, Iran

    Ebrahim Sharifi Teshnizi

  3. School of Railway Engineering, Iran University of Science and Technology, Tehran, 16548-73961, Iran

    Benyamin Ghoreishi

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Sadeghi, S., Sharifi Teshnizi, E. & Ghoreishi, B. Correlations between various rock mass classification / characterization systems for the Zagros tunnel-W Iran. J. Mt. Sci. 17, 1790–1806 (2020). https://doi.org/10.1007/s11629-019-5665-7

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