Rockburst proneness index of surrounding rock considering rock mass quality and excavation disturbance factor
Fengqiang Gong, Lei Xu, Shuren Wang, Qinghe Zhang, Yong Huang
Abstract
Rockburst is an engineering phenomenon characterized by the release of elastic strain energy due to the dynamic failure of deep surrounding rock. The existing rockburst proneness indexes primarily focus on rock materials, failing to encompass rock mass quality and engineering excavation disturbance. On the basis of the potential elastic strain energy released by rock failure, five kinds of rockburst proneness indexes of surrounding rock are established considering the rock mass quality and excavation disturbance factor. Firstly, the linear relationship between elastic modulus and residual elastic energy of rock materials ( A EF) , the relationships between elastic and deformation moduli, as well as the link with rock mass quality evaluation indexes (i.e., rock mass rating (RMR), basic quality index of rock mass (BQ), and geological strength index (GSI)) and deformation modulus, were used to derive five assessment model of rockburst proneness for surrounding rock. Secondly, the rockburst proneness degree for three grades of surrounding rock (I: excellent rock, II: good rock, and III: fair rock) was assessed utilizing the RMR 89 , BQ, and GSI indices, and the influence of excavation disturbances on the residual elastic energy of surrounding rock ( A EF SR ) was analysed. In general, the higher the quality of rock mass and the lesser the disturbance factor, the greater the rockburst proneness degree of surrounding rock. The accuracy of proposed rockburst proneness indexes was validated by using the field data from 27 rockburst cases. The results demonstrate that the discriminant grade of rockburst index based on GSI is basically consistent with the actual occurrence grade of rockburst cases, with an accuracy of 93%, which can be used as a recommended method for evaluating the rockburst proneness degree of surrounding rock. Finally, the shortcomings of rockburst proneness assessment model are discussed, and the improvement direction is elucidated.