Geological Strength Index Relationships with the Q-System and Q-Slope

Samad Narimani, Seyed Morteza Davarpanah, Neil Bar, Ákos Török and Balázs Vásárhelyi ()
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Samad Narimani: Department Engineering, Geology & Geotechnics, Faculty of Civil Engineering, Budapest University of Technology and Economics, 1111 Budapest, Hungary
Seyed Morteza Davarpanah: Department Engineering, Geology & Geotechnics, Faculty of Civil Engineering, Budapest University of Technology and Economics, 1111 Budapest, Hungary
Neil Bar: Gecko Geotechnics LLC, Kingstown 1471, Saint Vincent and the Grenadines
Ákos Török: Department Engineering, Geology & Geotechnics, Faculty of Civil Engineering, Budapest University of Technology and Economics, 1111 Budapest, Hungary
Balázs Vásárhelyi: Department Engineering, Geology & Geotechnics, Faculty of Civil Engineering, Budapest University of Technology and Economics, 1111 Budapest, Hungary

Sustainability, 2023, vol. 15, issue 14, 1-16

Abstract: The Q-system and Q-slope are empirical methods developed for classifying and assessing rock masses for tunneling, underground mining, and rock slope engineering. Both methods have been used extensively to guide appropriate ground support design for underground excavations and stable angles for rock slopes. Using datasets obtained from igneous, sedimentary, and metamorphic rock slopes from various regions worldwide, this research investigates different relationships between the geological strength index (GSI) and the Q-system and Q-slope. It also presents relationships between chart-derived GSI with GSI estimations from RMR89 and Q’ during drill core logging or traverse mapping. Statistical analysis was used to assess the reliability of the suggested correlations to determine the validity of the produced equations. The research demonstrated that the proposed equations provide appropriate values for the root mean squared error value (RMSE), the mean absolute percentage error (MAPE), the mean absolute error (MAE), and the coefficient of determination (R-squared). These relationships provide appropriate regression coefficients, and it was identified that correlations were stronger when considering metamorphic rocks rather than other rocks. Moreover, considering all rock types together, achieved correlations are remarkable.

Keywords: rock mass classification; Q-system; Q-slope; geological strength index (GSI) (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2023
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