Energy considerations are essential for the evaluation of violent failures which are commonly encountered as mining goes deeper. To address the relationships among different energy components, a series of numerical models were conducted by using 3DEC and a script was developed for energy visualization. The theoretical and numerical results of the ratio between the released kinetic energy and the excavated strain energy were compared under elastic and plastic models. The distribution of stored elastic strain energy and dissipated plastic strain energy in the vicinities of openings with different shapes were also investigated. Furthermore, the efficiency of a latest destressing method as a proactive measure for seismic management was evaluated based on the energy redistribution patterns. This research can improve the understanding of the energy evolution near excavations and contribute to the evaluation of burst-proneness of excavations as well as effectiveness of rockburst mitigation measures.
When underground mining continues to reach deep deposits, significant energy changes take place in rock mass and cause excavation instabilities such as rock bursts (e.g., Cook et al. 1966 and Zhou et al. 2018). The involved brittle failures cannot be represented accurately by the traditional failure indictors such as deformation and stress. The acquisition of the energy variations is essential to describe these violent failure process (Wang et al. 2021).
In view of the importance of energy considerations, more and more studies have been conducted through theoretical analysis, numerical simulation, and laboratory experiments in the past years. Salamon (1984) conducted theoretical analysis on the relationships among energy components during mining by using an elastic model. Different criteria for rockburst proneness of rock mass are proposed based on the strain-stress curves, especially the post-failure behavior obtained from laboratory experiments such as strain energy storage index (Kidybinski 1981 and Gong et al. 2019), potential energy of elastic strain (Wang & Park 2001 and Tajdus et al. 2014), brittleness index (Keneti & Sainsbury 2018) and so on. Meanwhile, several energy indices are introduced in the analysis of numerical simulation results including strain energy density (SED) (Xu et al. 2003 and Weng et al. 2017), energy release rate (ERR) (Cook 1966), local energy release rate (LERR) (Jiang et al. 2010) and excess energy (Khademian & Ozbay 2019).
