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Nowadays, with many available numerical methods developed in rock mechanics, researchers have always focused on the parameter calibration of the numerical model but ignored the predictive capability of these methods. A comparative study of nine commonly used numerical methods was performed for predicting rock failure through international cooperation organized by the Discontinuous Deformation Analysis (DDA) commission of the International Society for Rock Mechanics (ISRM). Two steps of numerical modelling were conducted including a calibration procedure from given experimental results and a numerical prediction for benchmark tests with these calibrated parameters for three types of rocks. Through the comparison between different numerical and experimental results, the inherent weaknesses and strengths of different numerical methods in terms of predicting rock failure were identified and analysed. The influence of human intervention in terms of parameter selection is even more significant than the choice of different numerical methods. Some potential factors (i.e., different boundary conditions, heterogeneity of rock material, strength parameters, particle packing, and failure criteria) that may occur in numerical and physical tests were further discussed. Through the comparison of different failure criteria, we found the selection of rock failure criterion might be the major factor that affected the predictive capability of numerical methods, and the nonlinear failure model (the Hoek–Brown criterion) showed the superiority in the prediction of rock fracturing subjected to complex stress conditions. This comparative work also enlightens the significance of a high-quality calibration process and the future advancement of rock failure criteria. © 2023 Elsevier Ltd
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International Journal of Rock Mechanics and Mining Sciences
ISSN: 1365-1609
Year: 2023
Volume: 166
7 . 2 0 0
JCR@2022
ESI Discipline: GEOSCIENCES;
ESI HC Threshold:14
Cited Count:
WoS CC Cited Count: 0
SCOPUS Cited Count: 16
ESI Highly Cited Papers on the List: 0 Unfold All
WanFang Cited Count:
Chinese Cited Count:
30 Days PV: 9
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