DOI https://doi.org/10.36487/ACG_repo/2625_48
Cite As:
Malovichko, D, Rigby, A & Mroczek, S 2026, 'Operational assessment of dynamic demand imposed on ground support
during large seismic events', in D Cumming-Potvin & J Wesseloo (eds),
Ground Support 2026: Proceedings of the 11th International Conference on Ground Support in Mining, Australian Centre for Geomechanics, Perth, pp. 1-12,
https://doi.org/10.36487/ACG_repo/2625_48
Abstract:
Large seismic events recorded in mines often exhibit complex waveforms, indicating that rock mass failure and the associated deformation of excavations evolve dynamically in space and time. It is of practical importance to infer the characteristics of this evolution from the recorded waveforms, as this enables the quantification of the dynamic demand imposed on ground support (e.g. in terms of tunnel surface displacement or kinetic energy). Detailed reconstruction of spatio-temporal characteristics of seismic sources is possible (Malovichko et al. 2025); however, it requires significant effort and is not feasible in an operational context (e.g. within a few hours after an event).
For seismic events associated with sudden slip along a planar surface or shear failure in a confined environment, the strongest near-source peak ground velocity can be estimated using the relatively simple method proposed by McGarr (1991). By combining this estimate with conservative assumptions about source spatial distribution, maps of peak ground velocity for the tunnels can be constructed. However, this method cannot be applied to events involving episodes of excavation convergence and the paper proposes an approach to address this limitation. The rapid evaluation of strainburst demand parameters (e.g. strainburst depth, bulking velocity) is possible assuming that the strongest far-field displacement pulses are associated with the most severe episode of dynamic stress fracturing at the tunnel/s perimeter. The subsequent mapping of the demand parameters is then presented.
The proposed approach is demonstrated using real data from two mines. Its application to operational rockburst damage forecasting is illustrated.
Keywords: rockburst, seismicity, seismic source
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