Double-arch tunnels, as one of the popular forms of tunnels, might be exposed to boiling liquid expanding vapour explosions (BLEVEs) associated with transported liquified petroleum gas (LPG), which could cause damage to the tunnel and even catastrophic collapse of the tunnel in extreme cases. However, very limited study has investigated the performance of double-arch tunnels when exposed to internal BLEVEs and in most analyses of tunnel responses to accidental explosions. The TNT-equivalence method was used to approximate the explosion load, which may lead to inaccurate tunnel response predictions. This study numerically investigates the response of typical double-arch tunnels to an internal BLEVE resulting from the instantaneous rupture of a 20 m³ LPG tank. Effects of various factors, including in-situ stresses, BLEVE locations, and lining configurations on tunnel responses are examined. The results show that the double-arch tunnels at their early-operation ages are more vulnerable to severe damage when exposed to the BLEVE due to the low action of in-situ stress of rock mass on the response of early-age tunnels. It is also found that directing the LPG tank to different driving lanes inside tunnels can affect the BLEVE-induced tunnel response more significantly than varying the configurations of tunnel lining. Moreover, installing section-steel arches in the mid-wall can effectively improve the blast resistance of the double-arch tunnels against the internal BLEVE. In addition, the prediction models based on multi-variate nonlinear regressions and machine learning methods are developed to predict the BLEVE-induced damage levels of the double-arch tunnels without and with section-steel arches.

Mechanical softening behaviors of shale in CO₂-water-rock interaction are critical for shale gas exploitation and CO₂ sequestration. This work investigated the cross-scale mechanical softening of shale triggered by CO₂-water-rock interaction. Initially, the mechanical softening of shale following 30 d of exposure to CO₂ and water was assessed at the rock-forming mineral scale using nanoindentation. The mechanical alterations of rock-forming minerals, including quartz, muscovite, chlorite, and kaolinite, were analyzed and compared. Subsequently, an accurate grain-based modeling (AGBM) was proposed to upscale the nanoindentation results. Numerical models were generated based on the real microstructure of shale derived from TESCAN integrated minerals analyzer (TIMA) digital images. Mechanical parameters of shale minerals determined by nanoindentation served as input material properties for AGBMs. Finally, numerical simulations of uniaxial compression tests were conducted to investigate the impact of mineral softening on the macroscopic Young’s modulus and uniaxial compressive strength (UCS) of shale. The results present direct evidence of shale mineral softening during CO₂-water-rock interaction and explore its influence on the upscale mechanical properties of shale. This paper offers a microscopic perspective for comprehending CO₂-water-shale interactions and contributes to the development of a cross-scale mechanical model for shale.

Research on automation and intelligent operation of tunnel boring machine (TBM) is receiving more and more attention, benefiting from the increasing construction data. However, most studies on TBM operations optimization were trained by the labels of human drivers’ decisions, which were subjective and stochastic. As a result, the control parameters suggested by these models could hardly surpass the performance of a human driver, even the possibility of subjective incorrect decisions. Considering that the geomechanical feedback to TBM under drivers’ actions is objective, in this paper, a transformer-based model called the geological response for tunnel boring machine (GRTBM), is proposed to learn the relationship between operation-adjust and TBM monitoring changes. Additionally, with the model-based offline reinforcement learning, this paper provided a novel approach to optimizing the TBM excavation operations. The decision processes, recorded in the Yin-song TBM project for a waterway tunnel in Jilin Province of China, were used for the validation of the model. By adopting an implicit perception of geological conditions in the GRTBM model, the suggested method achieved the desired state within a single action, greatly outperformed the practical adjustments where 500 s were taken, revealing the fact that the proposed model has the potential to surpass the capability of human beings.

In this paper, a seismic and vibration reduction measure of subway station is developed by setting a segmented isolation layer between the sidewall of structure and the diaphragm wall. The segmented isolation layer consists of a rigid layer and a flexible layer. The rigid layer is installed at the joint section between the structural sidewall and slab, and the flexible layer is installed at the remaining sections. A diaphragm wall-segmented isolation layer-subway station structure system is constructed. Seismic and vibration control performance of the diaphragm wall-segmented isolation layer-subway station structure system is evaluated by the detailed numerical analysis. Firstly, a three-dimensional nonlinear time-history analysis is carried out to study the seismic response of the station structure by considering the effect of different earthquake motions and stiffness of segmented isolation layer. Subsequently, the vibration response of site under training loading is also studied by considering the influence of different train velocities and stiffness of the segmented isolation layer. Numerical results demonstrate that the diaphragm wall-segmented isolation layer-subway station structure system can not only effectively reduce the lateral deformation of station structure, but also reduce the tensile damage of the roof slab. On the other hand, the developed reduction measure can also significantly reduce the vertical peak displacements of site under training loading.

Micro-disturbance grouting is a recovery technique to reduce the excessive deformation of operational shield tunnels in urban areas. The grout mass behaves as a fluid in the ground before hardening to form a grout-soil mixture, which highlights the necessity of using fluid-solid coupling method in the simulation of grouting process. Within a discrete element modeling environment, this paper proposes a novel fluid-solid coupling method based on the pore density flow calculation. To demonstrate the effectiveness of this method, it is applied to numerical simulation of micro-disturbance grouting process for treatment of large transverse deformation of a shield tunnel in Shanghai Metro, China. The simulation results reveal the mechanism of recovering tunnel convergence by micro-disturbance grouting in terms of compaction and fracture of soil, energy analysis during grouting, and mechanical response of soil-tunnel interaction system. Furthermore, the influence of the three main grouting parameters (i.e., grouting pressure, grouting distance, and grouting height) on tunnel deformation recovery efficiency is evaluated through parametric analysis. In order to efficiently recover large transverse deformation of shield tunnel in Shanghai Metro, it is suggested that the grouting pressure should be about 0.55 MPa, the grouting height should be in the range of 6.2-7.0 m, and the grouting distance should be in the range of 3.0-3.6 m. The results provide a valuable reference for grouting treatment projects of over-deformed shield tunnel in soft soil areas.

Rockburst is a major challenge to hard rock engineering at great depth. Accurate and timely assessment of rockburst risk can avoid unnecessary casualties and property losses. Despite the existence of various methods for rockburst assessment, there remains an urgent need for a comprehensive and reliable criterion that is easy to both apply and interpret. Developing a new rockburst criterion based on simple parameters can potentially fill this gap. With its advantages, this criterion can facilitate a more effective and efficient prediction of rockburst potential, thereby contributing significantly to enhancing safety measures. In this paper, combined with the internal and external factors of rockburst, four control variables (i.e., integrity index, stress index, brittleness index, and elastic energy index) were selected to be incorporated into a comprehensive rockburstability index (RBSI). Based on 116 sets of rockburst cases, the rockburst potential was accurately quantified and predicted using the categorical boosting (CatBoost) model and the nature-inspired metaheuristic African vultures optimization algorithm (AVOA). In its performance validation, the criterion achieved the highest accuracy of 90.48%, verifying the reliability and effectiveness of the proposed RBSI criterion. Additionally, an interpretive method was applied to analyze the variable influence on the criterion, facilitating the explanation of predictions and the analysis of the formula’s robustness under different conditions. In general, compared with existing criterion methods involving relevant indicators, the newly proposed RBSI criterion enhances the accuracy of rockburst potential prediction, and it can effectively and swiftly evaluate the preliminary risk of rockburst. Lastly, a graphical user interface was developed to provide a clear visualization of the assessment of rockburst potential.

When tunnel boring machines (TBMs) excavate through jointed rock masses, the cutting efficiency is strongly affected by the shear strength of joints, the mechanism of which, however, remains poorly understood. In this study, a series of disc-cutter indentation tests were conducted on granite rock mass specimens with different joint shear strengths. During the indentation, the cracking process was recorded by a digital image correlation (DIC) system. The deformation and strength of specimens, cracking behavior, rock breakage mode and cutting efficiency were quantitatively investigated. In addition, to investigate the combined effects of joint shear strength, orientation and spacing on the rock breakage mechanism, numerical rock mass models were established based on a particle flow code PFC2D. Experimental results reveal that the cracking of primary and secondary cracks changes from the mixed shear-tensile to tensile mode in the initial stage, while the joint shear strength does not affect the cracking mode in the subsequent propagation process. The rock breakage mode is classified to an internal block breakage mode, a cross-joint breakage mode and a cutters-dependent breakage mode. The cross-joint breakage mode is optimal for improving the cutting efficiency. Numerical simulation results reveal that the increase in the joint shear strength changes the internal block breakage mode to cross-joint breakage mode for rock masses of particular ranges of joint orientation and spacing. These findings provide basis for improving the TBM cutting efficiency through jointed rock masses.

The Sichuan-Xizang Railway is a global challenge, surpassing other known railway projects in terms of geological and topographical complexity. This paper presents an approach for rapidly profiling rock mass quality underneath tunnel face for the ongoing construction of the Sichuan-Xizang Railway. It adopts the time-series method and carries out the quantitative analysis of the rock mass quality using the depth-series measurement-while-drilling (MWD) data associated with drilling of blastholes. A tunnel face with 15 blastholes is examined for illustration. The results include identification of the boundary of homogeneous geomaterial by plotting the blasthole depth against the net drilling time, as well as quantification of rock mass quality through the recalculation of the new specific energy. The new specific energy profile is compared and highly consistent with laboratory test, manual logging and tunnel seismic prediction results. This consistency can enhance the blasthole pattern design and facilitate the dynamic determination of charge placement and amount. This paper highlights the importance of digital monitoring during blasthole drilling for rapidly profiling rock mass quality underneath and ahead of tunnel face. It upgrades the MWD technique for rapid profiling rock mass quality in drilling and blasting tunnels.

Rockburst has always been a challenge for the safe construction of deep underground engineering. This study investigated the rockburst characteristics in highly-stressed D-shape tunnels under impact loads from rock blasting and other mining-related dynamics disturbances. The biaxial Hopkinson pressure bar was utilized to apply varying biaxial prestress and the same impact loads to cube specimens with D-shape hole. High-speed camera and digital image correlation (DIC) were used to capture the failure process and strain field of specimen. The test results demonstrate that the D-shape hole specimen experience rockburst under coupled static stress and impact load. Under this circumstance, the rockburst mechanism of the D-shaped hole specimens involves spalling in sidewall induced by impact load, indicating dynamic tensile failure. The high static prestress provides the initial stress field, while the impact load disrupts the stress equilibrium, result in the stress or strain concentration in the sidewall of the D-shape hole, inducing rockburst. Moreover, the rockburst process can be divided into (1) calm stage, (2) crack initiation, propagation, and coalesce stage, (3) spalling stage and (4) rock fragments ejection stage. Impact load triggers rockburst occurrence, while vertical stress further determines the rockburst characteristics. The influence range and magnitude of strain concentration zone and displacement deformation of the tunnel surrounding rock increases with increasing vertical stress, thus inducing more severe rockburst.

Rockburst is a frequently encountered hazard during the production of deep gold mines. Accurate prediction of rockburst is an important measure to prevent rockburst in gold mines. This study considers seven indicators to evaluate rockburst at four deep gold mines. Field research and rock tests were performed at two gold mines in China to collect these seven indicators and rockburst cases. The collected database was oversampled by the synthetic minority oversampling technique (SMOTE) to balance the categories of rockburst datasets. Stacking models combining tree-based models and logistic regression (LR) were established by the balanced database. Rockburst datasets from another two deep gold mines were implemented to verify the applicability of the predictive models. The stacking model combining extremely randomized trees and LR based on SMOTE (SMOTE-ERT-LR) was the best model, and it obtained a training accuracy of 100% and an evaluation accuracy of 100%. Moreover, model evaluation suggested that SMOTE can enhance the prediction performance for weak rockburst, thereby improving the overall performance. Finally, sensitivity analysis was performed for SMOTE-ERT-LR. The results indicated that the SMOTE-ERT-LR model can achieve satisfactory performance when only depth, maximum tangential stress index, and linear elastic energy index were available.

During dislocation, a tunnel crossing the active fault will be damaged to varying degrees due to its permanent stratum displacement. Most previous studies did not consider the influence of the tunnel’s deep burial and the high in-situ stress, so the results were not entirely practical. In this paper, the necessity of solving the anti-dislocation problem of deep-buried tunnels is systemically discussed. Through the model test of tunnels across active faults, the differences in failures between deep-buried tunnels and shallow-buried tunnels were compared, and the dislocation test of deep-buried segmental tunnels was carried out to analyze the external stress change, lining strain, and failure mode of tunnels. The results are as follows. (1) The overall deformation of deep-buried and shallow-buried tunnels is both S-shaped. The failure mode of deep-buried tunnels is primarily characterized by shear and tensile failure, resulting in significant compressive deformation and a larger damaged area. In contrast, shallow-buried tunnels mainly experience shear failure, with the tunnel being sheared apart at the fault crossing, leading to more severe damage. (2) After the segmental structure design of the deep-buried tunnel, the “S” deformation pattern is transformed into a “ladder” pattern, and the strain of the tunnel and the peak stress of the external rock mass are reduced; therefore, damages are significantly mitigated. (3) Through the analysis of the distribution of cracks in the tunnel lining, it is found that the tunnel without a segmental structure design has suffered from penetrating failure and that cracks affect the entire lining. The cracks in a flexible segmental tunnel affect about 66.6% of the entire length of the tunnel, and cracks in a tunnel with a short segmental tunnel only affect about 33.3% of the entire length of the tunnel. Therefore, a deep-buried tunnel with a short segmental tunnel can yield a better anti-dislocation effect. (4) By comparing the shallow-buried segmental tunnel in previous studies, it is concluded that the shallow-buried segmental tunnel will also suffer from deformation outside the fault zone, while the damages to the deep-buried segmental tunnel are concentrated in the fault zone, so the anti-dislocation protection measures of the deep-buried tunnel shall be provided mainly in the fault zone. The results of the above study can provide theoretical reference and technical support for the design and reinforcement measures of the tunnel crossing active fault under high in-situ stress conditions.

The evaluation of urban underground space (UUS) suitability involves multiple indicators. Assigning weight to these indicators is crucial for accurate assessment. This paper presents a method for spatially variable weight assignment of indicators using the order relation analysis method (G₁-method), the entropy weight method, an improved grey relational analysis (GRA) and a set of spatial weight adjustment coefficients. First, the subjective and objective weights of indicators for engineering geological and hydrogeological conditions were determined by the G₁-method and entropy weight method, respectively, and their combined weights were then obtained using the principle of minimum discriminatory information. This study highlighted the impact of surface restrictions, such as buildings, on UUS, and the degree of the influence of these buildings gradually decreased with the increase in depth of the rock and soil mass in UUS, which resulted in changes in weights of indicators with depth. To address this issue, a coefficient was defined as the standardized value of the ratio of additional stress applied by restrictions to the self-weight stress of soil at the same depth to modify the combined weights so that all weights of indicators could vary in space. Finally, an improved GRA was used to determine the suitability level of each evaluation cell using the maximum correlation criterion. This method was applied to the 3D suitability evaluation of UUS in Sanlong Bay, Foshan City, Guangdong Province, China, including 16 evaluation indexes. This study comprehensively considered the influence of multiple factors, thereby providing reference for evaluating the suitability of UUS in big cities.

To solve the problem that current attitude planning methods do not fully consider the interaction and constraints among the shield, segmental tunnel ring, and geology, and cannot adapt to the changes in the actual engineering environment, or provide feasible long-term and short-term attitude planning, this paper proposes autonomous intelligent dynamic trajectory planning (AI-DTP) to provide tunnel ring and centimeter-layer planning targets for a self-driving shield to meet long-term accuracy and short-term rapidity. AI-DTP introduces the Frenet coordinate system to solve the problem of inconsistent spatial representation of tunnel data, segmental tunnel ring location, and surrounding geological conditions, designs the long short-term memory attitude prediction model to accurately predict shield attitude change trend based on shield, tunnel, and geology, and uses a heuristic algorithm for trajectory optimization. AI-DTP provides ring-layer and centimeter-layer planning objectives that meet the needs of long-term accuracy and short-term correction of shield attitude control. In the Hangzhou-Shaoxing Intercity Railroad Tunnel Project in China, the “Zhiyu” shield equipped with the AI-DTP system was faster and more accurate than the manually controlled shield, with a smoother process and better quality of the completed tunnel.

Subways, underground logistics systems and underground parking, as the primary facilities types of underground, contribute significantly to the achievement of carbon-neutral cities by moving surface transportation to underground, thereby releasing surface space for the creation of more urban blue-green space for carbon sink. Therefore, in-depth studies on carbon neutrality strategies as well as reliable layout optimization solutions of these three types of underground facilities are required. This study proposes a spatial layout optimization strategy for carbon neutrality using underground hydrogen storage and geothermal energy for these three types of underground facilities employing a multi-agent system model. First, three spatial layout relationships, competition, coordination, and followership, between five underground facilities that contribute to emission reduction were investigated. Second, the implementation steps for optimizing the spatial layout of underground facilities were determined by defining the behavioral guidelines for spatial environment, underground facility, and synergistic agent. Finally, using the Tianfu New District in Chengdu City, China, as a case study, layouts of underground facilities under three different underground space development scenarios were simulated to verify the model. The findings of this study address the gap in the research on underground spatial facilities and their layout optimization in response to emission reduction. This study provided a significant reference for the study of underground space and underground resources at the planning level to aid in achieving carbon-neutral cities.

Many empirical and analytical methods have been proposed to predict fracturing pressure in cohesive soils. Most of them take into account three to four specific influencing factors and rely on the assumption of a failure mode. In this study, a novel data-mining approach based on the XGBoost algorithm is investigated for predicting fracture initiation in cohesive soils. This has the advantage of handling multiple influencing factors simultaneously, without pre-determining a failure mode. A dataset of 416 samples consisting of 14 distinct features was herein collected from past studies, and used for developing a regressor and a classifier model for fracturing pressure prediction and failure mode classification respectively. The results show that the intrinsic characteristics of the soil govern the failure mode while the fracturing pressure is more sensitive to the stress state. The XGBoost-based model was also tested against conventional approaches, as well as a similar machine learning algorithm namely random forest model. Additionally, several large-scale triaxial fracturing tests and an in-situ case study were carried out to further verify the generalization ability and applicability of the proposed data mining approach, and the results indicate a superior performance of the XGBoost model.

Excessive underground train-induced vibration becomes a serious environmental problem in cities. To investigate the vibration transfer from an underground train to a building nearby, an explicit-integration time-domain, three-dimensional finite element model is developed. The underground train, track, tunnel, soil layers and a typical multi-story building nearby are all fully coupled in this model. The complex geometries involving the track components and the building are all modelled in detail, which makes the simulation of vibration transfer more realistic from the underground train to the building. The model is validated with in-situ tests data and good agreements have been achieved between the numerical results and the experimental results both in time domain and frequency domain. The proposed model is applied to investigate the vibration transfer along the floors in the building and the influences of the soil stiffness on the vibration characteristics of the track-tunnel-soil-building system. It is found that the building vibration induced by an underground train is dominant at the frequency determined by the P2 resonance and influenced by the vibration modes of the building. The vertical vibration in the building decreases in a fluctuant pattern from the foundation to the top floor due to loss of high frequency contents and local modes. The vibration levels in different rooms at a same floor can be different due to the different local stiffness. A room with larger space thus smaller local stiffness usually has higher vibration level. Softer soil layers make the tunnel lining and the building have more low frequency vibration. The influence of the soil stiffness on the amplification scale along the floors of the building is found to be nonlinear and frequency-dependent, which needs to be further investigated.

High mountain valleys are characterized by the development of intricate ground stress fields due to geological processes such as tectonic stress, river erosion, and rock weathering. These processes introduce considerable stability concerns in the surrounding rock formations for underground engineering projects in these regions, highlighting the imperative need for rigorous stability assessments during the design phase to ensure construction safety. This paper introduces an innovative approach for the pre-evaluation of the stability of surrounding rocks in underground caverns situated within high mountain valleys. The methodology comprises several pivotal steps. Initially, we conduct inverse calculations of the ground stress field in complex geological terrains, combining field monitoring and numerical simulations. Subsequently, we ascertain stress-strength ratios of the surrounding rocks using various rock strength criteria. To assess the stability characteristics of the surrounding rocks in the 1^# spillway cave within our project area, we employ numerical simulations to compute stress-strength ratios based on different rock strength criteria. Furthermore, we undertake a comparative analysis, utilizing data from the 5^# Underground Laboratory (Lab 5) of Jinping II Hydropower Station, aligning the chosen rock strength criterion with the damage characteristics of Lab 5′s surrounding rocks. This analysis serves as the cornerstone for evaluating other mechanical responses of the surrounding rocks, thereby validating the pre-evaluation methodology. Our pre-evaluation method takes into account the intricate geological evolution processes specific to high mountain valleys. It also considers the influence of the initial geostress field within the geological range of underground caverns. This comprehensive approach provides a robust foundation for the analysis and assessment of the stability of surrounding rocks, especially in high mountain valley areas, during the design phase of underground engineering projects. The insights derived from this analysis hold substantial practical significance for the effective guidance of such projects.