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.
Any rock mechanics’ design inherently involves determining the deformation characteristics of the rock material. The purpose of this study is to offer equations for calculating the values of bulk modulus (K), elasticity modulus (E), and rigidity modulus (G) throughout the loading of the sample until failure. Also, the Poisson’s ratio, which is characterized from the stress–strain curve, has a significant effect on the rigidity and bulk moduli. The results of a uniaxial compressive (UCS) test on granitic rocks from the Morágy (Hungary) radioactive waste reservoir site were gathered and examined for this purpose. The fluctuation of E, G, and K has been the subject of new linear and nonlinear connections. The proposed equations are parabolic in all of the scenarios for the Young’s modulus and shear modulus, the study indicates. Furthermore, the suggested equations for the bulk modulus in the secant, average, and tangent instances are also nonlinear. Moreover, we achieved correlations with a high determination factor for E, G, and K in three different scenarios: secant, tangent, and average. It is particularly intriguing to observe that the elastic stiffness parameters exhibit strong correlation in the results.
Rocks deformed at low confining pressure are brittle, which means that after peak stress, the strength declines to a residual value established by sliding friction. The stress drop is the variation between peak and residual values. But no tension reduction takes place at high confining pressure. A proposed definition of the brittle-ductile transition is the transition pressure at which no loss in strength takes place. However, studies that consider information about the brittle-ductile transition, the criterion's range of applicability, how to determine mi, and how confining pressures affect mi's values are scarce. This paper aims to investigate the link between brittle-ductile transition stress, uniaxial compressive strength and Hoek–Brown material constant (mi) for different kinds of rock. It is essential to accurately determine the brittle-ductile transition stress to derive reliable values for mi. To achieve this purpose, a large amount of data from the literature was chosen, regression analysis was carried out, and brittle-ductile transition stress (σTR) was determined based on the combination of Hoek–Brown failure criteria and the recently used brittle-ductile transition stress limit of Mogi. Moreover, new nonlinear correlations were established between uniaxial compressive strength and Hoek–Brown material constant (mi) for different igneous, sedimentary and metamorphic rock types. Regression analyses show that the determination coefficient between σTR and UCS for gneiss is 0.9, sandstone is 0.8, and shale is 0.74. Similarly, the determination coefficient between σTR and mi for gneiss is 0.88. The correlation between Hoek–Brown material constant (mi) and σTR was not notable for sedimentary and metamorphic rocks, probably due to sedimentary rocks' stratification and metamorphic ones' foliation.
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