The blast-induced vibration during excavation by drilling and blasting method has an important impact on the surrounding structures. In particular, with the development of tunnel engineering, the impact of blasting vibration on tunnel construction has attracted extensive attention. In this paper, the propagation attenuation characteristics of blast-induced vibration (PPV, peak particle velocity) on different tunnel structures were systematically studied based on the field monitoring data. Initially, the attenuation characteristics of blasting vibration PPV on the lower bench surface, the side wall of the excavated tunnel and the closely spaced adjacent tunnel were investigated. Subsequently, the capacity of several widely utilized empirical prediction equations to estimate the PPV on tunnel structures was examined, along with a comparative analysis of their prediction accuracy. The research findings indicate that it is feasible to predict the PPV on the tunnel structures using empirical equations. The attenuation characteristics of blasting vibration PPV are different in different structures and directions. The prediction accuracy of the empirical equations varies, while the discrepancies are minimal. The principal variation among these equations lies in the site-specific coefficients k, β, λ, highlighting the differential impact of structural and directional considerations on the predictive efficacy. Based on the empirical equation and safe PPV provided by the blasting vibration safe standards on tunnels of China (GB6722-2014), and considering the influence of all structures and directions, it is determined that the safe distance of blasting vibration in the tested tunnel project should be larger than 20.28-18.31 m, 18.31-16.16 m, and 16.16-13.75 m for blasting vibration frequency located in ≤10 Hz, 10-50 Hz, and >50 Hz.

This study investigated the fault nucleation and rupture processes driven by stress and fluid pressure in fine-grained granite by monitoring acoustic emissions (AEs). Through detailed analysis of the spatiotemporal distribution of the AE hypocenter, P-wave velocity, stress-strain, and other experimental observation data under different confining pressures for stress-driven fractures and under different water injection conditions for fluid-driven fractures, it was found that fluid has the following effects: 1) complicating the fault nucleation process, 2) exhibiting episodic AE activity corresponding to fault branching and the formation of multiple faults, 3) extending the spatiotemporal scale of nucleation processes and pre-slip, and 4) reducing the dynamic rupture velocity and stress drop. The experiments also show that 1) during the fault nucleation process, the b- value for AEs changes from 1 to 1.3 to 0.5 before dynamic rupture, and then rapidly recovers to around 1-1.2 during aftershock activity and 2) the hydraulic diffusivity gradually increases from an initial pre-rupture order of 0.1 m²/s to 10-100 m²/ s after dynamic rupture. These results provide a reasonable fault pre-slip model, indicating that hydraulic fracturing promotes shear slip before dynamic rupture, as well as laboratory-scale insights into ensuring the safety and effectiveness of hydraulic fracturing operations related to activities such as geothermal development, evaluating the seismic risk induced by water injection, and further researching the precursory preparation process for deep fluid-driven or fluid-involved natural earthquakes. The publicly available dataset is expected to be used for various purposes, including 1) as training data for artificial intelligence related to microseismic data processing and analysis, 2) predicting the remaining time before rock fractures, and 3) establishing models and assessment methods for the relationship between microseismic characteristics and rock hydraulic properties, which will deepen our understanding of the interaction mechanisms between fluid migration and rock deformation and fracture.

In order to solve the problem of gas overlimit in corner corners of coal and gas prominent mines, through the combination of air leakage mechanism in the goaf, near-field fissure expansion and rich area division, blocking material development and optimization, performance measurement of blocking materials and on-site test, we started to study the causes of gas concentration in corner corners, analysis of roof collapse and transparency in corners and performance test of blocking materials, and optimized the blocking materials by combining laboratory test and engineering test. Considering the thickness of the sealing film, the attenuation ratio of the sealing film thickness, the gelation time, and the gelation viscosity under different ratios, we designed a multi factor orthogonal experiment to optimize the optimal ratio suitable for the engineering site. Factors affecting blocking effectiveness, such as gel water retention and gel flame resistance, were also tested. The sealing scheme was implemented in the 2109 working face of a coal and gas outburst mine in Gansu, China. Through on-site monitoring of the changes in temperature, gas concentration, and air leakage at each monitoring point before and after the use of sealing materials, the analysis of the detection results shows that the temperature changes at each monitoring point after the use of sealing materials do not exceed 0.2°C; The change in oxygen concentration is less than 0.27 %; The gas concentration has decreased by more than 60 %, with a decrease of 71.32 % in the gas concentration in the upper corner. The air leakage has decreased by more than 53 %, and the proportion of decrease in air leakage at the upper corner is as high as 56.83 %. This air leakage control technology has remarkable blocking effect, meets the requirements of corner near-field fissure blocking material, and is easy to prepare, inexpensive, non-toxic, tasteless and green, providing a successful experience for the treatment of similar coal and gas outburst mines that can be referenced.

The instability of retaining wall is a key factor for many geo-hazards, such as landslides. To estimate the stability of retaining wall, the distribution of earth pressure is necessary. The results of in-situ observations and indoor experiments demonstrate that the distribution of earth pressure behind the retaining wall exhibits remarkable nonlinearity. When the results are analyzed in details, the oscillation and quasi-periodicity of the distribution of earth pressure are observed, which has not been given widely concerns and cannot be described by the existing analytical models. Based on the internal variable gradient theory and operator averaging method, a gradient-enhanced softening constitutive model is proposed in this paper to describe the oscillation and quasi-periodicity of the distribution of earth pressure acting on the retaining wall, by introducing the high-order gradient terms of the hydrostatic pressure into Mohr-Coulomb yield condition. In order to check the applicability of the proposed formulation, the predictions from the formulations are compared with the full-scale and laboratory-scale test results as well as the existing formulations. It is noted from the comparisons between predicted and measured values that the results of gradient-dependent softening constitutive model provides the comparable approximations for active earth pressure and describes the oscillation and quasi-periodicity very well. This model may enhance the comprehension of soil mechanics and provide a novel view for the design of the retaining wall.

Engineering disasters, such as rockburst and collapse, are closely related to structural instability caused by insufficient bearing capacity of geological materials. Uniaxial compressive strength (UCS) holds considerable significance in rock engineering projects. Consequently, this study endeavors to devise efficient models for the expeditious and economical estimation of UCS. Using a dataset of 729 samples, including the Schmidt hammer rebound number, P-wave velocity, and point load index data, we evaluated six algorithms, namely Adaptive Boosting (AdaBoost), Gradient Boosting Decision Tree (GBDT), Extreme Gradient Boosting (XGBoost), Light Gradient Boosting Machine (LightGBM), Random Forest (RF), and Extra Trees (ET) and utilized Bayesian Optimization (BO) to optimize the aforementioned algorithms. Moreover, we applied model evaluation metrics such as Root Mean Square Error (RMSE), Mean Absolute Error (MAE), Variance Accounted For (VAF), Nash-Sutcliffe Efficiency (NSE), Weighted Mean Absolute Percentage Error (WMAPE), Coefficient of Correlation (R), and Coefficient of Determination (R²). Among the six models, BO-ET emerged as the most optimal performer during training (RMSE = 4.5042, MAE = 3.2328, VAF = 0.9898, NSE = 0.9898, WMAPE = 0.0538, R = 0.9955, R² = 0.9898) and testing (RMSE = 4.8234, MAE = 3.9737, VAF = 0.9881, NSE = 0.9875, WMAPE = 0.2515, R = 0.9940, R² = 0.9875) phases. Additionally, we conducted a systematic comparison between ensemble and traditional single machine learning models such as decision tree, support vector machine, and K-Nearest Neighbors, thus highlighting the advantages of ensemble learning. Furthermore, the enhancement effect of BO on generalization performance was assessed. Finally, a BO-ET-based Graphical User Interface (GUI) system was developed and validated in a Tunnel Boring Machine-excavated tunnel.

Effective monitoring techniques and equipment are essential for the prevention and control of coal and rock dynamic disasters such as rockburst. Based on the fact that there is charge generation during deformation and rupture of coal rock body and the charge signals contain a large amount of information about the mechanical process of deformation and rupture of coal rock, the rockburst charge sensing monitoring technology has been formed. In order to improve the charge sensing technology for monitoring and early warning of rockburst disasters, this paper develops a new generation of portable coal rock charge monitoring instrument on the basis of the original instrument and carries out laboratory and underground field application. The primary advancement involves enhancing the external structure of the sensor and increasing the charge sensing area, which can more comprehensively capture the charge signals from the loaded rupture of the coal rock body. The overall structure of the data acquisition instrument has been improved, the monitoring channels have been increased, and the function of displaying the monitoring data curve has been added, so that the coal and rock body force status can be grasped in time. The results of the experimental study show that the abnormal charge signals can be monitored during the rupture process of rock samples under loading, and the monitored charge signals are in good agreement with the sudden change of stress in the rock samples and the formation of crack extension. There is a precursor charge signal before the stress mutation, and the larger the loading rate is, the earlier the precursor charge signal appears. The charge monitoring instrument can monitor the charge signal of the coal seam roadway under strong mining pressure. In the zone of elevated overburden pressure, the amount of induced charge is large, and anomalously high value charge signals can be monitored when a coal shot occurs. The change trend of the charge at different measuring points of strike and inclination has a good consistency with the distribution of overrunning support pressure and lateral support pressure, which can reflect the stress distribution and the degree of stress concentration of the coal body through the size and location of the charge, foster early warning and analysis of rockburst, and provide target guidance for the prevention and control of rockburst.