The vast amount of data generated during tunnel construction is crucial for project plan execution, quality control, and safety management. This study aims to enhance information transmission efficiency and security through the application of blockchain technology and to establish a tunnel construction quality control model using Bayesian networks. The results indicate that when the quality state distribution is abnormal, the probability of quality assessment values for reinforcement quality inspection, reinforcement joint welding, and construction personnel skill qualifications each exceed 40

Although extensive research has been conducted on CO2-enhanced coalbed methane (CO2-ECBM) recovery, most prior studies have focused on the impact of gas adsorption-induced swelling on coal permeability under equilibrium conditions. This paper presents a comprehensive thermo-hydro-mechanical-chemical (THMC) model that integrates thermal expansion and heat conduction (T), gas diffusion in the matrix and gas-water two-phase flow in the fractures (H), matrix and fracture deformation due to poroelasticity (M), and non-equilibrium binary gas adsorption-induced matrix swelling (C) during CO2-ECBM recovery. The accuracy of the proposed model was verified through experimental data, and the model was simulated using finite element method (FEM) software. Simulation results indicate that the permeability evolution can be categorized into three stages. Ignoring the impact of water on gas adsorption properties would lead to an overestimation of the influence of adsorption-induced swelling, while disregarding non-equilibrium adsorption underestimates it. An examination of five designed cases identified critical factors influencing permeability. Parametric analysis shows that increases in the injection pressure, the injection temperature, and the initial permeability promote the competitive adsorption-induced swelling between CH4 and CO2, leading to increased CH4 production and CO2 storage. Conversely, an increase in initial water saturation reduces available gas flow space, decreasing both CH4 production and CO2 storage. Higher irreducible water saturation favors early gas recovery, while lower irreducible water saturation is more advantageous for long-term recovery.

Large deformations in deep soft rock roadways primarily stem from low rock strength under high in situ stress and intense mining disturbance. This renders stability control a critical challenge in tunneling support engineering. Utilizing Xinhe Coal Mine’s deep soft rock tunnel as a representative case, this study integrates field monitoring, laboratory experimentation, and numerical simulation to investigate how excavation and grouted rock bolting influence surrounding rock stability. Building upon field-observed deformation mechanisms and support failure patterns, constitutive models for FLAC3D’s embedded cable and beam elements were modified to achieve high-fidelity simulation of grouted support systems. Numerical models simulating diverse support schemes were established to analyze roadway displacement fields, plastic failure development, and structural behavior of support components, ultimately identifying the optimal rehabilitation solution. The research results indicate that the numerical simulation outcomes of the original support scheme exhibit good agreement with field observations in terms of roadway deformation patterns, deformation magnitudes, and occurrences of bolt/cable fractures. This demonstrates that the adopted refined numerical simulation methodology and parameters are reasonable and exhibit high reliability. Considering both surrounding rock stability and cost control, Roadway Rehabilitation Scheme S1 was identified as the optimal support solution. Its specific parameters are pre-grouting + full-section rock bolts (diameter 22 mm, length 2.4 m, spacing 0.8 m, row spacing 1.6 m) + full-section grouted cables (diameter 22 mm, length 6.2 m, spacing 1.0 m, row spacing 1.6 m).

Rational determination of surrounding rock grades is critically important for accurately predicting tunnel instability mechanisms and designing support structures scientifically. However, the traditional Q-system classification method exhibits considerable subjectivity in determining key parameters, especially those pertaining to rock mass integrity, which remains a persistent challenge in engineering geology practice. This study proposes a quantitative modification to the Q-system by integrating the response relationship between joint geometric parameters and block stability. High-definition tunnel face images were processed to extract joint spacing and the number of joint sets. Based on numerical simulations of 115 working conditions, a quantitative relationship was established between these joint parameters and block response. Using the entropy weight method, multiple instability indicators-including displacement, number of unstable blocks, volume, and stress-were comprehensively integrated to derive a modified, continuous parameter that simultaneously captures joint set frequency and spacing. Additionally, the two-dimensional rock block index (RBI2D) was introduced to refine the rock quality designation (RQD), enabling a more accurate characterization of rock mass integrity. Engineering applications demonstrated that the modified Q ' value provides a more reliable assessment of rock mass quality, particularly in joint-intensive zones or near faulted sections. The proposed approach effectively reduces the subjectivity inherent in conventional assessments and offers a technically robust basis for balancing safety and economy in tunnel construction.

The shear behavior and failure mechanisms of non-persistent joints are key to the stability of jointed rock masses, whose shear responses are jointly governed by geometric parameters such as joint aperture and joint persistence. In this study, direct shear tests were performed on specimens containing coplanar non-persistent joints, and the shear-failure process was simulated using the finite element method-cohesive zone model (FEM-CZM) method. The combined effects of joint aperture and joint persistence on shear behavior were investigated from both macroscopic and mesoscopic perspectives, and an improved Jennings shear strength criterion incorporating the weakening effect of joint aperture was derived. The tests revealed two typical post-peak failure patterns: a "sudden drop followed by arcuate recovery" and a "stepwise decline". Increases in both the joint aperture and joint persistence reduce the peak shear strength, with joint persistence exerting a more pronounced influence. Larger joint apertures increase the degrees of rock bridge fracture surface undulation and specimen surface spalling, whereas higher joint persistence flattens the fracture surface and mitigates surface spalling. Simulations indicate that stress initially concentrates at the rock bridge ends and extends towards the middle during shearing. The number of cracks increases sharply at the peak shear stress, with tensile cracks consistently dominating. Larger joint apertures intensify the stress concentration at the rock bridge ends, leading to earlier crack initiation, a more vigorous crack propagation trend, and more dispersed crack paths, whereas higher joint persistence narrows the stress concentration zone and accelerates crack coalescence across the rock bridge. Finally, based on the test and simulation results, an improved Jennings shear strength criterion is proposed by introducing a cohesion reduction coefficient eta(d) that decays exponentially with joint aperture. The validation results demonstrate that the predicted peak shear strengths agree well with the measured values and external data.

During the construction of underground engineering, the natural stress state of rock mass is destroyed under excavation disturbance. It affects the stability of surrounding rock mass and the construction progress of the project in mild cases, and triggers collapse accidents causing huge losses in severe cases. In this study, a special shallow-buried section of the Daling Tunnel is selected. Based on the refined statistics of joints at the tunnel face, the dominant joint groups that mainly control the stability of surrounding rock in this section are obtained. Through Discontinuous Deformation Analysis for Rock Failure (DDARF) numerical simulation, the whole process of crack propagation and coalescence around the tunnel is obtained. By arranging monitoring at key positions, the displacement variations of the arch crown, shoulder, haunch and floor under excavation disturbance are acquired. A series of tests on the process of crack initiation, propagation and coalescence in rock mass of underground engineering provide a reference for revealing the failure mechanism of rock mass and ensuring the safe construction of underground engineering.

Rock mass classification is a fundamental prerequisite for tunnel design, construction safety, and the optimisation of support schemes. The traditional Q-system relies heavily on engineers’ subjective interpretation of parameters such as the joint roughness coefficient and joint alteration coefficient, which often leads to classification uncertainty and errors. To improve the accuracy and objectivity of rock mass classification, a coupled evaluation method integrating fuzzy reasoning and support vector machines (SVM) is proposed. First, subjective parameters are optimised through fuzzy reasoning to reduce empirical interpretation bias. Subsequently, SVM is employed to capture the nonlinear relationships between the optimised features and rock mass classes, thereby enhancing classification performance. Finally, a standardised model training and validation framework is established to systematically verify the effectiveness of the proposed coupled model. The results indicate that the proposed method accuracy of 90

Earthen sites are widely distributed and highly diverse, making the stability analysis of these sites and other geotechnical engineering projects of significant scientific value. In this study, the wall of an earthen site in the south of China is taken as the research object, and the seepage model is established on the basis of analyzing its basic geological conditions. Using ABAQUS software, the infiltration patterns and stability of the north wall under rainfall-induced seepage were investigated. The simulation results show that under low-intensity rainfall of long duration, the wall is prone to deep damage due to the accumulation of stress, whereas under high-intensity rainfall, rapid water infiltration causes the wall to become saturated. As a result, the shear strength of the soil mass decreases rapidly, leading to shallow slips and collapses within a short time. The simulation results are generally consistent with the observed damage to the northern city wall in the field. This study provides a reference for stability analysis of similar geotechnical and hydraulic engineering projects subjected to rainfall and seepage.

Permeability is a critical parameter in coalbed methane (CBM) recovery and received increasing attention in recent years. The slip effect and effective stress exert competing influences on permeability, with coal exhibiting varying sensitivities to effective stress depending on their pore structures. The presence of water further complicates these interactions, affecting both the slip effect and permeability. This study investigates the pore structure and permeability characteristics of four coal cores at varying water contents using low-field nuclear magnetic resonance (NMR) and pulse pressure decay (PPD) methods. An enhanced apparent permeability model was developed by incorporating water content, effective stress, and the slip effect. The dynamic variations of compressibility coefficient, slip coefficient, and intrinsic permeability for Cores C-F were theoretically examined based on the refined model, and the critical pore pressures at which the slip effect becomes significant were identified. The results indicate that cores with larger average pore sizes exhibit more pronounced changes in fracture compressibility coefficients as water content increases. Additionally, the slip coefficient decreases with increasing pore pressure and is notably lower at reduced water contents. Intrinsic permeability increases more significantly with pore pressure at higher water content, with cores having larger average pore diameters showing greater sensitivity to these changes. The critical pore pressure, where the slip effect becomes significant, increases with water content and is higher in cores with smaller average pore sizes. Finally, various coefficients are proposed to quantitatively assess changes in fracture compressibility, slip coefficients, intrinsic permeability, and critical pore pressures under varying water content conditions, enabling more accurate analysis of permeability behavior.

During the construction of engineering projects, it is inevitable to cross fault and fractured zones, which are key geological factors that affect the stability of surrounding rock in tunnels. To study the distribution pattern of instability in surrounding rock and the optimization of synergetic support systems in fault-crossing tunnels, a comprehensive identification method integrating multi-source geological information was proposed, fully considering the geometric shape and distribution characteristics of rock fractures. The location of faults in actual projects was determined using this method, and a detailed three-dimensional numerical model was established accordingly. By simulating tunnel excavation, the spatial distribution pattern and grading characteristics of unstable blocks in surrounding rock were analyzed. Meanwhile, based on the original support methods, the effectiveness of synergetic support in stabilizing surrounding rock in tunnels was revealed, and initial support measures tailored to the characteristics of fault-crossing tunnels were proposed. The research results can provide reliable references for disaster prediction, prevention, and control in fault-crossing tunnels and underground engineering.

The slip effect can significantly enhance the permeability of fractured rock, and understanding its influence is crucial for comprehending gas flow dynamics within reservoirs. Most existing theoretical models treat intrinsic permeability and slip coefficient as constants and lack a method to define the critical pore pressure where the slip effect becomes significant. Thus, a dynamic apparent permeability model was developed based on equivalent fracture and rock bridge models, considering slip coefficient and intrinsic permeability as functions of effective stress and adsorption swelling. Using the established dynamic apparent permeability model, we analyzed variations in intrinsic permeability and slip coefficient under different confining stresses and permeable media. Additionally, we introduced the concept of the slip effect contribution rate to identify the critical pore pressure where the slip effect becomes significant. The results indicate that: 1) Intrinsic permeability increases with rising pore pressure, while slip coefficients decrease; 2) For different permeable media, the increase in intrinsic permeability with pore pressure is linked to gas adsorption properties, and slip coefficient variation is more complex; 3) A power function relationship exists between the slip effect contribution rate and pore pressure, with the critical pore pressure order being N-2

The inherent spatial heterogeneity of complex geological formations results in large differences in the ultimate bearing capacity of individual piles, and it is difficult to reliably quantify and assess the bearing capacity of individual piles. In this paper, based on the results of on-site static load test and sensitivity analysis method, eight sensitive factors are screened out, and the extreme gradient boosting algorithm (XGBoost) is used to predict the ultimate load carrying capacity of individual piles, however, the computed coefficient of determination is less than 0.9, and the prediction effect needs to be strengthened. On this basis, three kinds of swarm intelligent optimization algorithms are introduced to adaptively match the XGBoost hyper-parameters, and the results show that the HGS-XGBoost hybrid prediction model can more accurately calculate the ultimate bearing capacity of a single pile under the composite strata, and the prediction effect can satisfy the engineering requirements when using the HGS-XGBoost prediction model for the actual project.

As rock tunnel construction gradually progresses into the complex engineering stages characterized by long, large, deep, and challenging projects, evaluating the quality of surrounding rock and ensuring excavation safety become formidable tasks due to the intricate and variable geological conditions encountered during tunnel excavation. Precisely extracting the characteristics of rock structures and scientifically assessing tunnel stability have emerged as critical issues requiring urgent solutions. This study integrates computer aided engineering (CAE) with tunnel seismic tomography (TST) advanced geological prediction techniques to dynamically assess the quality of surrounding rock during tunnel construction. Additionally, it employs the discrete element method (3DEC) to dynamically simulate the excavation of various support methods in environments with fracture development. Research findings indicate that CAE technology can precisely reveal the dynamic changes in the rock integrity coefficient during tunnel excavation. TST technology provides advanced geological predictions for complex structures like weak interlayers and fracture zones within the rock mass to be excavated, thereby reducing the risk of failure in the surrounding rock caused by unfavorable geological formations. The numerical simulations based on 3DEC offer a scientific foundation for the safe and rapid construction of fractured rock tunnels and allow optimization of subsequent support proposals. This study suggests a viable construction approach addressing the potential risks in tunnel construction. This approach enables continuous monitoring of changes in the surrounding rock and provides a basis for adjusting excavation methods and optimizing support methods. The findings have significant practical implications for the construction of similar underground projects. A novel approach integrating CAE and TST technologies is proposed to dynamically evaluate the quality of complex fractured rock masses during tunnel construction and optimize support schemes. Numerical simulations confirm that the improved support design significantly enhances construction stability, reduces deformation risks, and minimizes support stress. This study presents a construction concept suitable for complex geological conditions, offering practical guidance for safe execution and cost control in similar projects.

To investigate the mechanism through which irregular undulating joint planes in engineering rock masses are damaged more accurately and reveal their fracture evolution and anchoring mechanism, in this study, discontinuous jointed rock masses with irregular undulating joint planes are designed, samples are produced, a numerical damage constitutive model (based on experimental data, more accurately than ever before) is derived, and discrete element research is performed. The shear test process for discontinuous jointed rock masses without and with anchors is reproduced to compensate for the microscopic fracture mechanism not obtained in the test and to more directly show the crack initiation and propagation process, as well as the changes in mechanical parameters such as stress and displacement in the rock mass fracture process. This study provides an important basis for revealing the mechanism through which rock masses with irregular undulating joint planes are fractured.

This study comprehensively accounts for the randomness in the geometric distribution and mechanical parameters of block bounding discontinuities by incorporating a probabilistic model into block theory. Blocks are classified according to a critical edge length, and Monte Carlo simulation is employed to calculate the formation probability and failure probability of blocks of different sizes. By computing the geometric formation probability and mechanical failure probability of blocks within each class, a total failure probability model for block stability is established and applied to evaluate the stability and reliability of key blocks. Furthermore, using a random block analysis and unfolding procedure for tunnels, the overall distribution pattern of potential sliding blocks in the rock mass surrounding the tunnel excavation face is investigated. This enables a more precise quantitative assessment of block stability and reliability and provides a basis for transforming key blocks and potentially unstable blocks into stable ones.

The rock mass rating (RMR) system is one of the most commonly used methods for classifying rock masses in underground engineering. Uncertainty of RMR values can significantly affect the safety of underground projects. In this regard, we proposed a reliable rating approach for classifying rock masses based on the reliability theory. This theory was incorporated into the RMR system to establish the functions of rock masses of different classifications. By analyzing the probability distribution patterns of various parameters used in the RMR system and using the Monte Carlo method to calculate the reliability probability of surrounding rock belonging to each classification, reliable RMR values for the rock mass to be excavated can be obtained. The results demonstrate that it is feasible to adopt the reliability theory in classification tasks considering the randomness characteristics of rock and soil. As verified through a case study of the Lushan Tunnel project, the proposed approach can be used to obtain the probability of the uncertainty of the calculated RMR values of underground engineering rock masses, and the calculation results are consistent with reality. The proposed approach can serve as a reference for studies in other fields and also applies to other rock mass classification methods.

To quickly determine the blasting block degree and conduct an accurate and objective analysis of the tunnel blasting effect, this study has enhanced and improved upon the traditional genetic algorithm and Otsu algorithm. It has combined it with the marking watershed method and utilized ground digital acquisition to capture images of blasting debris. These images are then used in our custom-developed blasting analysis software to calculate the blasting block degree distribution and provide a quantitative analysis of blasting block degree. The research results show that the optimized image segmentation algorithm effectively improves the traditional threshold segmentation method on the poor effect of segmentation of the edge of the adherent block or the direct application of the watershed segmentation of the over-segmentation problem, to improve the segmentation accuracy based on the new segmentation technology is close to the traditional technology in terms of time. Through the self-developed software, the construction personnel in the project site to quickly obtain the blasting block degree histogram, block degree cumulative curve and other important indicators of the evaluation of the effect of blasting block degree, to provide data support for on-site construction, to assist in the modification of the blasting program, and to improve the efficiency of construction. This study realizes the rapid detection and block identification of blasting blocks, provides data support for the optimization of blasting parameters, and has good application and promotion value.