A fractal calculation method was developed to investigate the self-similarity of the time distribution of microseismic events during the evolution of rock bursts. Microseismic data, which were utilized for back-analysis after the rock burst, were collected corresponding to different intensities of immediate rock bursts, occurring in the deeply buried headrace tunnels of Jinping-II Hydropower Station in Sichuan Province, China. The overburden depths of the tunnels are between 1,800 and 2,500 m, where the maximum principal stress reaches 65 MPa in a rock mass mainly comprising Baishan Group marble. The results are as follows: The time distribution of microseismic events during the evolution of immediate rock bursts was found to display fractal properties. If the intensities of rock bursts were lower, the time fractal dimensions were smaller (weak rock bursts < moderate rock bursts < intense rock bursts). The time fractal dimensions can be used as a basis for evaluating rock-burst intensities. Time fractal dimensions correspond to intense rock bursts (>1.6), moderate rock bursts (1.1–1.6), and weak rock bursts (<1.1). The daily time fractal dimensions of microseismic events increased during the process of immediate rock bursts but were significantly reduced before the rock burst occurred. On this basis, the time distribution of microseismic events has the potential to be used as a rock-burst predictor, and the microseismic events time fractal dimension can provide a basis for establishing a warning index and reduce the risk of rock bursts in deep tunnels.

Rockburst disasters in deep tunnels cause serious casualties and economic losses. It is a great challenge to make a warning for rockbursts in geotechnical engineering. In this work, a microseismicity-based rockburst intensity warning method is proposed that is suitable for use in deep tunnels in the initial period of microseismic (MS) monitoring. The method first involves collecting information on a sample of no more than five cases. Then, the event to be analyzed is combined with the sample events and subjected to cluster analysis. Finally, a rockburst intensity warning is generated according to the results of the cluster analysis or after a second cluster analysis. It is a comprehensive, multi-parameter rockburst intensity warning method that only needs a few rockburst cases for input which makes it suitable in the initial period of MS monitoring. The method also incorporates the novel idea of a second cluster analysis. An engineering application based on deep tunnels in the Jinping II hydropower station in Sichuan Province, China, shows that the rockburst intensity warning results based on the proposed method agree well with the actual situations in four tests carried out. The method will enrich the techniques used to warn of rockbursts based on microseismicity.

This study integrates micro-seismic data and data from hundreds of rockbursts of different intensities that occurred in four deep headrace tunnels and one water drainage tunnel at Jinping II hydropower station in Sichuan province, China. The overburden of the studied tunnels is between 1900 m and 2525 m, largely excavated in marble. The tunnels have a total length of 12.4 km. The micro-seismic energy produced during the development of immediate rockbursts excavated with the drill-and-blast method (DBM) and a tunnel boring machine (TBM) were studied. The results indicated that the daily maximum micro-seismic energy can be used as a basis for estimating the rockburst intensity: no rockburst, weak rockbursts, moderate rockbursts, and intense rockbursts, and that the common logarithms of the micro-seismic energy of each level was 4 and 5 and 6, respectively. For the same intensity, rockbursts excavated by TBM and DBM have the same range but different distribution characteristics. The micro-seismic energy can be used as a guide to establish a dynamic warning system based on the evolution of micro-seismic events to reduce the risk of immediate rockbursts during excavation of deep, hard-rock tunnels.

Inherent defects in engineering rock masses inevitably lead to randomness in mechanical parameters and uncertainty in tunnel deformation and failure. To address these challenges, this study proposes a novel coupled analysis method that integrates complex function theory, physical model testing, and Monte Carlo simulation (MCS) for the deformation estimation and failure probability analysis of non-circular tunnels. Theoretically, this method provides a high-speed, high-accuracy analytical framework that overcomes the limitations of purely numerical approaches, particularly in handling continuous–discontinuous failure processes. Practically, it enables a more reliable and efficient stability assessment of tunnel systems under uncertain geological conditions. The proposed method is applied to a traffic tunnel at the Baihetan Hydropower Station. A series of uniaxial compression tests on 40 rock specimens are conducted to obtain statistical distributions of rock deformation parameters. An analytical solution for tunnel displacement is derived using plane elastic complex function theory, and the random displacement field is estimated via MCS. Physical model tests reveal that the elastic stage accounts for 83% of the overload failure process, based on which an elastic limit displacement function is established for tunnel arch settlement and surrounding rock convergence. The failure probability of the tunnel is then calculated, and the effects of the mean, coefficient of variation, and cross-correlation coefficient of rock deformation parameters on failure probability are discussed. The entire computational process is characterized by high speed and precision, offering a new and practical tool for tunnel stability evaluation and reliability-based design.

Rock pillars in deep underground mines are subjected to complex stress environments. The combined effects of in situ stress and cyclic disturbances from mining activities lead to a redistribution of the surrounding rock mass stress field, which readily triggers instability and failure, posing severe threats to mining engineering safety. To investigate the damage mechanism of cyclic loading on rock and its weakening effect on the bearing capacity of mine pillars, this study takes limestone as the research object. A series of uniaxial compression tests were conducted on limestone specimens subjected to triaxial cyclic pre-damage, complemented by numerical simulations to further characterize the energy and deformation evolution of the damaged limestone under cyclic loading conditions. The findings are as follows: (i) Triaxial cyclic tests on limestone show that both the input energy and dissipated energy follow similar trends, decreasing rapidly in the initial stage before stabilizing. The elastic strain energy remains largely constant, with most of the input energy being stored as elastic strain energy. Under constant stress levels and cycle numbers, increases in confining pressure and frequency reduce the rock’s input energy, elastic strain energy, and dissipated energy. (ii) The peak stress of damaged limestone exhibits a positive correlation with the pre-damage confining pressure and cyclic frequency, while it decreases with an increasing number of cycles. Higher confining pressure and frequency raise the input energy, elastic potential energy, and dissipated energy at the peak stress point. (iii) Deformation and failure in damaged limestone originate from the development and propagation of localized deformation zones. Increased lateral displacement within these zones promotes the formation of macroscopic fractures. Due to significant structural heterogeneity inside the localized areas, the evolution of deformation energy is influenced by regional characteristics. (iv) Simulation results indicate that the uniaxial compressive failure of limestone involves the accumulation and propagation of micro-scale tensile cracks, which ultimately coalesce into macro-scale shear fracture surfaces. During uniaxial loading of pre-damaged limestone, newly generated cracks predominantly initiate around pre-existing cracks, with only a limited number distributed randomly. Their peak intensity shows a positive correlation with the pre-damage confining pressure.