Intelligent prediction of deep rock strength based on modified three-dimensional Hoek–Brown criterion

Abstract

To study the deep rock strength, this paper proposes a five-parameter deviatoric function to modify the deviatoric function of the Hoek–Brown (HB) criterion, introduces an intelligent optimization algorithm (IOA) to determine the material parameters, thereby constructing a modified three-dimensional (3D) HB criterion, namely MMCHB criterion. The MMCHB criterion avoids the defects of the traditional HB criterion, which neither considers the Intermediate principal stress (IPS) nor meets the smoothness requirement, and overcomes the shortcomings of parameter determination based on conventional methods, which can lead to a single deviatoric plane envelope shape. This modified criterion can be degenerated into the HB criterion under triaxial compression and tension. The proposed criterion is verified using true triaxial test data for six types of intact rock, and the modified 3D HB criteria are selected for comparative study. The results show that the proposed criterion under the IOA has the best prediction error for the six rock types, ranging from 1.6636% to 3.4023%. Overall, the MMCHB criterion outperforms the existing modified 3D HB criteria in prediction. Based on the proposed MMCHB criterion, an intelligent prediction system is developed, which provides a new approach for intelligent prediction of deep rock strength and dynamic construction of rock material parameters.

Keywords

rock strength / Hoek–Brown criterion / Intermediate principal stress / intelligent optimization algorithm / intelligent prediction system

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