Abstract
The drilling rate index (DRI) is a measure, commonly used in predicting drillability in tunneling and drilling in quarry projects; this requires a particular set of laboratory test equipment. Determining drillability from the physical and mechanical properties of rocks is essential for the selection of proper machine drilling and predicting the cost and time a project requires. The special physical and mechanical rock properties that affect drillability include the point load index (IS50), uniaxial compressive strength (UCS), Young’s modulus (E), mineral composition of rock, hardness, abrasiveness, and brittleness. This research has tried to estimate the Sievers’ J miniature drill test (SJ), brittleness test (S20), and DRI values using the mineralogical, physical, and mechanical properties of rocks. Accordingly, 16 various granitic samples were collected from the Gelas water conveyor project (Naghadeh city, Iran). Pearson’s correlations and simple and multiple linear and non-linear regression analyses were performed. It was concluded that SJ, S20, and DRI have an indirect correlation with density (D), UCS, IS50, E, abrasivity index (ABI), CERCHAR abrasivity index (CAI), and Rock Abrasivity Index (RAI), and seemingly no correlation with porosity (n). The outcomes showed that the UCS, ABI, CAI, and D were inversely proportional with DRI and n was positively correlated with it. Multiple linear and non-linear models showed that the fitted model could successfully predict SJ, S20, and DRI through ABI, UCS, IS50, and density. The validation of results revealed that the multiple linear and non-linear models with two independent variables (density and ABI) showed a better performance than the models with three independent variables (density, IS50, and UCS).
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The authors were funded by the Vice-Chancellery for Research and Technology Affairs of Bu-Ali Sina University, Hamedan, Iran.
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Karrari, S.S., Heidari, M., Hamidi, J.K. et al. Estimation of drilling rate index values of granitic rocks with their mineralogical properties using different estimation models. Arab J Geosci 15, 856 (2022). https://doi.org/10.1007/s12517-022-10120-7
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DOI: https://doi.org/10.1007/s12517-022-10120-7