Identifying zones of rockburst-collapse compound hazards in deep tunnels
Abstract
In settings of substantial geological variability, geological formations, and high-stress environments, rockburst-collapse compound hazards typically arise during subterranean excavation activities. The presence of these hazards has emerged as a challenge in execution of deep underground projects, with the intensity more complex than that of individual hazards, such as rockbursts or collapses. The present work provides an indicator to identify segmental potential compound hazard zones to address the issue. This system employs seismic P-wave velocity ( C p ) acquired via the tunnel seismic prediction (TSP) method to determine the rock mass quality index (BQ) and geological strength index (GSI) at the working face. Through integration of the rock mass quality index with strength-stress ratio of the rock mass, we assess the likelihood of shallow rock collapse and deep rock fracturing, facilitating precise identification of potential compound hazard zones in the tunnel ahead. This paper theoretically modifies the stress state within intact rock, addressing the local stress concentration at the interface between fractured and intact rock, which is basis to the rockburst-collapse compound hazards. The proposed indicator was then validated through two instances of rockburst-collapse compound hazards that occurred during construction. The analyses of error propagation and parametric sensitivity indicate that the GSI derived from P-wave velocity exhibits a controlled uncertainty when C p < 6.0 km/s, demonstrating that the indicator is stable and reliable for practical use. The findings present an applicable analytical framework for identifying potential compound hazard areas in deep tunnels.
Fields of Study & Subjects
Rock Mechanics and Modeling
Geotechnical Engineering and Underground Structures
Geotechnical Engineering and Analysis
Publication details
- Journal / source
- Journal of Rock Mechanics and Geotechnical Engineering
- Publisher
- Elsevier BV
- Publication date
- 1 April 2026
- Language
- EN