Introduction: The stability evaluation and deformation prediction in geotechnical engineering depend on accurate rock mass mechanical parameters (RMMPs). The selection of these parameters directly influences the reliability of analysis. The conventional techniques used to assess the RMMPs face considerable challenges in real-world applications, which necessitates the need to investigate novel approaches.Methods: This paper proposes a displacement back-analysis (DBA) approach that utilizes support vector regression (SVR) optimized by differential evolution grey wolf algorithm (DE-GWO) to invert the RMMPs, which improves global optimization capability and inversion accuracy. Firstly, the uniform test design method is employed to outline the RMMPs for inversion, anddisplacement calculations are performed using FLAC^3D to generate learning and testing samples. Secondly, the DE-GWO, particle swarm optimization (PSO), genetic algorithm (GA), and SVR are integrated to identify the optimal superparameters, while the nonlinear mapping relationship between inversion parameters and displacements is established. Finally, the mechanical parameters to be measured are inversed based on field-measured displacements. This model is utilized to invert the RMMPs for a mining site located in Yunnan Province, and the inversed RMMPs are utilized for forward analysis. The results demonstrate that the DE-GWO-SVR method achieves the best results but requires the shortest inversion time.Results: The inversed RMMPs fall within acceptable ranges, while the error between the forward and monitored displacements is less than 10%, with a maximum deviation of 9.52%. This research introduces an innovative approach for assessing the RMMPs.

Different from the goaf formed by normal mining, the goaf formed by the continuous caving of the lower illegal goafs is extremely irregular and unstable, which leads to the difference in the goaf caving characteristics. Taking the complex irregular goaf of the Shirengou Iron Mine in China as the research object, the 3D laser scanning technology is used to detect the goaf shape and analyze the cause of the formation. Then, the caving characteristics of the goaf are analyzed by the methods of the numerical simulation, the monitoring of the crash of the caving rock, and the monitoring of the deformation of the arch foot. The simulation results show that the transverse expansion of the irregular goaf boundary is mainly along the perpendicular to the direction of the ore body strike when the goaf caves upward in the initial stage. Additionally, the monitoring results show that the caving characteristics can be divided into two stages: the paroxysmal caving stage and the periodicity caving stage. The paroxysmal caving characteristics are intense and irregular, while the periodicity caving characteristics have obvious periodicity, which is mainly reflected in the periodic alternation between the mass caving and the temporary stability. The interval period of the goaf mass caving is about 15–30 days and is changed by the progress of filling treatment. The conclusions in this work reveal the particularity of the caving characteristics in the complex irregular goaf and contribute to the improvement of the caving characteristics and the prediction of mass caving.

Introduction: High ground stress in deep mining operations results in rocks exhibiting mechanical properties that differ from those at shallow depths. This study conducted conventional triaxial compression (CTC) tests to elucidate themechanical behaviors of deep marble under CTC conditions.Methods: Initially, it analyzed energy evolution of deep marble under CTC conditions and developed a damage variable (D) expression. Subsequently, we examined impacts of confining pressure (σ₃) and D on dissipated energy (W_d) and Poisson’s ratio (μ′) and proposed an expression for damage energy dissipation rate (U). Finally, based on the first law of thermodynamics, we established a differential equation for energy balance that facilitated the development of a damage constitutive model (DCM) for marble under CTC conditions. This model effectively couples the internal energy and damage within the rock.Results: The results indicated that: (1) the maximum W_d increased with increasing σ₃, and the W_d experienced stages of stability, slow growth, steady growth, and slowdown. (2) At a constant σ₃, the μ′ under loading conditions increased with increasing damage level. However, as rock damage intensified in the residual stage, the growth rate of μ′ slowed and subsequently stabilized. (3) The proposed model effectively captures the nonlinear characteristics of stress-strain (SS) curves for deep marble under CTC conditions during the elastic, plastic yield, instability failure, and residual stages.Discussion: This research offers theoretical insights for stability analysis in deep mining activities.

Introduction: In order to reduce the impact of secondary disasters caused by the instability of rock and soil mass (RSM) during engineering construction on the environment, and to achieve safe and efficient engineering construction. Therefore, investigating the mechanical properties (M.P.), energy evolution laws, and damage characteristics of limestone with different water saturation (w) under cyclic loading-unloading (CLU) conditions is of significant engineering significance.Methods: This study conducted uniaxial compression (UC) and cyclic loading-unloading tests on limestone samples with different w values (i.e., 0%, 25%, 50%, 75%, 100%) to elucidate their mechanical properties and energy dissipation. The influence of w on the degradation of limestone was examined based on damage variables.Results: The results indicated that (1) as w increases, both the compressive strength (f_c) and elastic modulus (E) of the samples gradually decrease, while the peak axial strain gradually increases. When the w exceeded 0.4%, the failure characteristics transitioned from brittleness to ductility. (2) For limestone samples with the same w, the f_c and E under CLU conditions were greater than those under uniaxial compression conditions, while the peak axial strain was smaller than that under UC conditions. Analysis using the DRA method confirmed that w did not significantly affect the deformation memory effect of limestone. (3) As the axial strain and number of cycles (N) increased, both the input energy and dissipated energy gradually increased, while the elastic energy initially increased before rapidly declining. The proportion of elastic energy first increased and then decreased, while the proportion of dissipated energy first increased, then decreased, and finally suddenly increased. Compared with UC, CLU significantly enhanced the rock’s capacity to store elastic energy. (4) For the same N, limestone with higher w exhibited greater damage than that with lower w. Moreover, samples with high w always failed earlier than those with low w under both the UC and CLU conditions.Discussion: The research results provide a theoretical basis for understanding the dynamic response behavior and stability analysis of limestone slopes under disturbance and rainfall effects.

At present, rockburst disasters cannot be predicted accurately, and the prevention and control of deep underground engineering disasters are significantly challenging. To explore the evolution law of precursory information of rockburst instability, the rockburst test of diorite was conducted with high confining pressure and different unloading rates (0.1 MPa/s, 0.3 MPa/s, 0.5 MPa/s, 0.7 MPa/s, and 0.9 MPa/s). Multidimensional analysis is carried out by evaluating deformation features, fast Fourier transform (FFT), energy entropy, singular spectrum entropy, and power spectrum entropy. The results show that Poisson’s ratio is hook-shaped before rockburst, the elastic modulus is in the shape of a step, ringing count and energy surge after a quiet period, three-dimensional law of stress location space shows a large red ball distribution along the shear plane, value fluctuates in the low-value range, and low-frequency high amplitude and high-frequency low amplitude fluctuate in a large range after 300 s, with frequent abnormal fluctuations of the energy spectrum entropy, the singular spectrum entropy, and the power spectrum entropy curve. The above research results can be considered the evolution law of rockburst precursor information, which enriches the theoretical method of explosion disaster prediction.