Shear expression derivation and parameter evaluation of Hoek-Brown criterion

Hoek-Brown criterion is one of the most widely used strength criteria in the field of rock engineering, which can reflect the nonlinear empirical relationship between the ultimate principal stresses in rock failure, while the determination of Hoek-Brown parameters is still controversial. The evaluation of Hoek-Brown parameters according to geological strength index (GSI) classification of rock mass involves engineering experiences and subjectivity, and the fitting method of Hoek-Brown parameters based on laboratory triaxial experimental results of multiple fractured rocks is also not going to be easy. Besides, the majority of previous studies were still carried out through the triaxial tests of intact rocks. In this study, the shear expression of Hoek-Brown criterion was derived, and an approximate method for determining Hoek-Brown parameters basedon shear tests was established. Primarily, Hoek-Brown criterion was briefly reviewed and the variations of Hoek-Brown parameters with the change of GSI was analyzed. When GSI decreases from 100 to 50, the reduction of a is only 0.006.While s shows almost no change and approximates to 0 when GSI decreases from 50 to 0. On this basis, the existing shear expression of Hoek-Brown criterion for intact rock (GSI = 100) was extended to the fractured rock mass with 50 < GSI < 100. In addition, the approximate shear expression of Hoek-Brown criterion for fractured rock mass in the range of 0 < GSI < 50 was deduced by assuming s = 0. Then, Hoek-Brown parameters can be calculated through shear tests and MATLAB programing. Finally, based on the structural plane occurrence information of Tangdan copper mine, a random fracture network was generated by Monte Carlo method to prepare random fractured rock mass samples for compression-shear experiments, which were employed to verify the proposed method.

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Opracowanie rekordu ze środków MEiN, umowa nr SONP/SP/546092/2022 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2022-2023)