Excavation-induced fracturing mechanisms in deep hard rock: A hierarchical block model

Abstract

The fracture characteristics of the excavation damage zones (EDZs) of deeply buried tunnels are closely related to energy evolution, and they are highly valuable for support design. Advanced numerical simulation techniques have shown the potential for evaluating the EDZ properties. On the basis of the finite-discrete element method (FDEM) and Poisson’s random block generation technique, the virtual block model (VBM) is proposed to characterize the intact rock masses surrounding tunnels. Moreover, a virtual block upscale principle is proposed to determine the geometric and meso-mechanical parameters. The Canadian Underground Research Laboratory and China Jinping Underground Laboratory Phase II (CJPL-II) project excavations are simulated, and the excavation-induced fracture characteristics of the surrounding rock masses are analyzed in detail. The VBM captures the tensile, shear, and mixed fracture properties under excavation-induced confining pressure evolution. Then, the thicknesses of the spalling rock slabs in Lab #7 of the CJPL-II project are evaluated via the Otsu method. Combined with onsite monitoring data, the validity and advancement of the VBM are verified. This study expands the applicability of the FDEM and provides a new method for assessing the EDZs of surrounding rocks.

Keywords

Strain bursting / Deep tunnel / FDEM / Hard rock / Brittle fracture mechanism

Data availability

The data that support the findings of this study are available from the corresponding author upon reasonable request.

CRediT authorship contribution statement

Shili Qiu: Writing - review & editing, Supervision, Software, Project administration, Funding acquisition. Shirui Zhang: Writing - original draft, Visualization, Validation, Software, Methodology, Investigation, Formal analysis, Data curation, Conceptualization. Quan Jiang: Writing - review & editing, Supervision, Project administration, Funding acquisition. Yuheng Fang: Investigation. Ping Li: Investigation. Shaojun Li: Project administration. Yaxun Xiao: Data curation. Dingping Xu: Data curation.

Declaration of competing interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Acknowledgement

The authors acknowledge the financial support received from the National Natural Science Foundation of China (Grant Nos. 52325905 and 42377172).

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