Rock spalling is a common phenomenon of local rock mass failure in large underground cavern projects under high geostress, which seriously threatens the stability of engineering and construction safety. Relying on the underground powerhouse projects on both the left and right banks of the Baihetan Hydropower Station in Southwest China, a numerical evaluation method for the depth of rock spalling based on case back analysis is proposed through the use of numerical simulation, parameter inversion, field testing, and case investigation. Firstly, by collecting and organizing field data, the typical distribution pattern of spalling during the excavation of the roof arch and sidewalls of the Baihetan left and right bank powerhouses is statistically analyzed. Secondly, by taking rock displacement and loosening zone depth as target variables, key rock mechanics parameters in different rock spalling segmentations are obtained through the combination of a large number of field test results and the genetic-neural network algorithm (GA-ANN). Thirdly, the numerical simulation and the evaluation index of rock fracture damage (RFD) are used to analyze the range and depth of the brittle failure zone of the surrounding rock after excavation based on the hard rock degradation model (RDM) applicable to deep rock engineering, and the results are compared with the observed rock spalling damage on-site. The results show that more than 91% of the rock spalling depths correspond to RFD thresholds ranging from 1.35 to 1.50. Finally, the threshold was used to analyze the excavation of the layer Ⅲ of the underground powerhouses on the left and right banks of the Baihetan Hydropower Station. The results showed that the predicted accuracy of the rock spalling failure depth reached over 88%, proving the good applicability of the model in practical engineering, indicating that the RFD can be used to effectively predict the depth of rock spalling failure. This study can provide important support for predicting the depth of rock mass failure in deep underground engineering.

There are many studies on the spatial variability of mechanical parameters of jointed rock masses and the reliability of slopes with potential slip surface, but the research on the spatial variability of mechanical parameters of rock slopes and the uncertainty analysis of excavation unloading response (deformation and plastic zone) is limited. A probabilistic evaluation method for excavation unloading response of rock slopes considering the uncertainty of mechanical parameters is proposed. Based on laboratory rock mechanical tests and geological survey mapping data, the probabilistic statistical models of rock mass mechanical parameters of slopes are constructed by using Hoek-Brown empirical criterion and Monte Carlo analysis method, in which the uniaxial compressive strength (UCS) of rocks, the geological strength index (GSI) and the parameters of rock mass joints are input, and these probabilistic models are checked by the chi-square test. Based on the point estimation principle, the combination scheme of rock mass mechanical parameters is constructed, and the simulation analysis of slope excavation process is carried out by the numerical method to obtain the probability distributions of the slope safety factor as well as the displacement and plastic zone of rock masses after excavation. This method is used to analyze the rock mass mechanical parameters and excavation unloading response of a cutting slope along the Beijing-Qinhuangdao expressway under construction. The values and uncertainty distributions of rock strength, elastic modulus, cohesion and internal friction angle are obtained. By using the point estimation and FLAC^3D simulation method, the distributions of the slope safety factor as well as the displacement and plastic zone distributions of typical observation points are obtained. The comparison between the simulation results and the measured values shows the applicability of the proposed method. This study provides an effective way for the mechanical parameter estimation and stability evaluation of the rock cutting slope, and can provide a valuable reference for the decision-making process in practical engineering construction.