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Proposal of a new method for calculating GSI

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Języki publikacji
EN
Abstrakty
EN
Rock mass classification systems are simple but valuable tools for the qualitative and quantitative classification of rock masses and for the planning of the fortification of mining excavations. Unfortunately, in the prefeasibility phase, not all the information needed for a preliminary project evaluation is always available, and one of the few available information is the RQD, however, although it is very necessary to determine the GSI to analyze the failure criteria, it is difficult to obtain at this stage of the project. Although several correlations between the different classification systems have been identified, the most abundant ones are those relating GSI as a function of RMR and as a function of Barton’s Q. As for GSI relationships as a function of RQD, only three recent relationships are available: Hoek et al. (2013), Santa et al. (2019), and Xia et al. (2022). Therefore, this study presents a correlational analysis of the GSI and RQD classification systems, using robust nonparametric statistics, with the aim of determining an expression to estimate GSI in the field. Among the results, it is highlighted that better GSI prediction results are obtained when 25% < RQD ≤ 87%, with a maximum error of ±14 points, improving the estimation accuracy by 62% with respect to current proposals. Despite the above, the difficulty of interpreting more accurately the specific geological characteristics of each rock mass remains.
Słowa kluczowe
Czasopismo
Rocznik
Tom
Strony
93--105
Opis fizyczny
Bibliogr. 33 poz., rys., tab.
Twórcy
  • Mining Engineering, School of Engineering and Architecture, Universidad Arturo Prat, Iquique, Chile
  • Mining Engineering, School of Engineering and Architecture, Universidad Arturo Prat, Iquique, Chile
Bibliografia
  • ALTMAN D.G., 1990, Practical statistics for medical research, En: s.l.:CRC Press, p. 611.
  • BIENIAWSKI Z.T., 2011, Errores en la aplicación de las clasificaciones geomecánicas y su corrección. Ingeopres, Actualidad técnica de ingeniería civil, minería, geología y medio ambiente, Issue 208, pp. 10–21.
  • CONOVER W., 1999, Practical nonparametric statistical, En: s.l., John Wiley & Sons, p. 578.
  • DEERE D.U., 1963, Technical description of rock cores for engineering purposes, Rock Mechanics and Engineering Geology, 18(1).
  • DEERE D.U., 1989, Rock Quality Designation (RQD) after Twenty Years. DEERE (DON U) CONSULTANT GAINESVILLE FL.
  • FLORES-RUIZ E., MIRANDA-NOVALES M.G., VILLASÍS-KEEVER M.A., 2017, El protocolo de investigación VI: cómo elegir la prueba estadística adecuada, Estadística inferencial. Revista alergia México, Jul., 64(3).
  • GARZÓN-ROCA J., TORRIJO F.J., COBOS G., 2021, Geomechanical characterization and analysis of the Upper Cretaceous flysch materials found in the Basque Arc Alpine region, Bulletin of Engineering Geology and the Environment, 80(10), pp. 7831–7846.
  • GOKCEOGLU C., SONMEZ H., KAYABASI A., 2003, Predicting the deformation moduli of rock masses, International Journal of Rock Mechanics and Mining Sciences, 40(5), pp. 701–710.
  • GONZÁLEZ de VALLEJO L., ORTUÑO-ABAD L., FERRER GUIJÓN M., OTEO MAZO C., 2002, Ingeniería Geológica, s. l, Pearson.
  • HASSANPOUR J., KHOSHKAR A.S., FARASANI M.G., HASHEMNEJAD A., 2022, Investigating the relationships between rock mass classification systems based on data from mechanized tunneling projects in Iran, Bulletin of Engineering Geology and the Environment, 147(8), pp. 1–19.
  • HE M. et al., 2019, An empirical method for determining the mechanical properties of jointed rock mass using drilling energy, International journal of rock mechanics and mining sciences, Vol. 116, pp. 64–74.
  • HERNÁNDEZ SAMPIERI R., 2018, Metodología de la investigación, DF, McGraw-Hill, Interamericana.
  • HESSE C.A., OFOSU J., NORTEY E., 2017, Introduction to nonparametric statistical methods, Akrong Publications, Ltd., Accra.
  • HOEK E., CARTER T.G., DIEDERICHS M.S., 2013, Quantification of the Geological Strength Index Chart. 47th US rock mechanics/geomechanics symposium.
  • 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), pp. 151–160.
  • HUAMAN A., ARDILES R., MENDIETA H., ARÍAS F., SALAS W., NIKAIDO E., CURI N., 2017, Guía de criterios geomecánicos para diseño, construcción, supervisión y cierre de labores subterráneas, Primera ed. Lima: Osinergmin.
  • KAYABASI A., GOKCEOGLU C., 2019, An Assessment on Permeability and Grout Take of Limestone: A Case Study at Mut Dam, Karaman, Turkey, Water, 11(12).
  • LOUREIRO PÉREZ E., 2011, Estadística no paramétrica: un modo de introducción, Buenos Aires, s.n.
  • MARINOS V., MARINOS P., HOEK E., 2005, The geological strength index: applications and limitations, Bull. Eng. Geol. Environ., Issue 65, p. 55–65.
  • MARINOS V., MARINOS P., HOEK E., 2005, The geological strength index: applications and limitations, Bulletin of Engineering Geology and the Environment, 64(1), pp. 55–65.
  • MARTÍNEZ ORTEGA R.M. et al., 2009, El coeficiente de correlación de los rangos de Spearman caracterización, Revista Habanera de Ciencias Médicas, 8(2).
  • PALMSTROM A., 2005, Measurements of and correlations between block size and rock quality designation (RQD), Tunn. Undergr. Sp. Tech., 20(4), pp. 362–377.
  • PRIEST S., HUDSON J., 1976, Discontinuity spacings in rock, International Journal of Rock Mechanics and Mining Sciences and Geomechanics Abstracts, 13(5), pp. 135–148.
  • RAMALLE-GÓMARA E., ANDRÉS de LLANO J., 2003, Use of robust methods in inferential statistics, Atención Primaria, 32(3), pp. 177–182.
  • RESTREPO L., GONZÁLEZ J., 2007, De Pearson a Spearman, Revista Colombiana de Ciencias Pecuarias, 20(2), pp. 183–192.
  • RODRÍGUEZ S.S., VALERO J.D.L., GÓMEZ C.L., 2018, Correlations of geomechanical indices for Andean environments, ISRM European Rock Mechanics Symposium – EUROCK 2018.
  • SACHPAZIS C., 1986, En: Geotechnical Description, Classification and Properties of Carbonate and Calcareous Rock Masses. Their Recording Procedure, s.l, s.n.
  • SANTA C., GONÇALVES L., CHAMINÉ H.I., 2019, A comparative study of GSI chart versions in a heterogeneous rock mass media (Marão tunnel, North Portugal): a reliable index in geotechnical surveys and rock engineering design, Bulletin of Engineering Geology and the Environment, 78(8), pp. 5889–5903.
  • SHEN J., JIMENEZ R., KARAKUS M., XU C., 2014, A Simplified Failure Criterion for Intact Rocks Based on Rock Type and Uniaxial Compressive Strength, Rock Mechanics and Rock Engineering, 47(2), pp. 357–369.
  • TURNER J., 2006, Rock Socketed Shafts for Highway, Transportation Research Board, WA, USA.
  • XIA K. et al., 2022, Quantification of the GSI and D values in the Hoek–Brown criterion using the rock quality designation (RQD) and discontinuity surface condition rating (SCR), Bulletin of Engineering Geology and the Environment, 81(1), pp. 1–21.
  • ZHANG L., 2016, Determination and applications of rock quality designation (RQD), Journal of Rock Mechanics and Geotechnical Engineering, 8(3), pp. 389–397.
  • ZHANG L., EINSTEIN H., 2004, Using RQD to estimate the deformation modulus of rock masses, International Journal of Rock Mechanics and Mining Sciences, Vol. 41, pp. 337–341.
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-07db020d-06d4-44fa-b7d9-73d43dfb39ca
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