Residents living near drill-and-blast tunnels often experience disturbances from blasting operations. This motivates us to investigate the characteristics of airblasts and resulting noise through on-site monitoring at three tunnels. The research focuses on both the temporal evolution and spatial propagation of air-blasts. Temporal analysis, including peak overpressure (POp), positive duration (PD), and Fourier main frequency (MF), emphasizes the relationship between airblast characteristics, blasting delays, and rock grade. It shows that airblast bandwidths are typically in the range of 3e20 0 Hz, with noise levels exceeding 130 dB, which is comparable to jet engines and rocket launch. Spatial propagation analysis reveals the impact of tunnel space on airblast propagation. Although POp and PD typically decrease with distance inside the tunnel, wave superposition can cause increased overpressure and prolonged durations at far-field distances (above 60 m kg-1/3). Outside the tunnel, sound radiation was influenced by azimuth and was basically determined by sound power d an often-overlooked factor. To address the anisotropic propagation of airblasts, a predictive model was proposed for external noise levels, considering variables like distance, azimuth angle, initial sound power, and wave expansion. Validated by tests, this model successfully unifies data from three studies, helping to explain and predict airblast disturbances near tunnels. (c) 2026 Institute of Rock and Soil Mechanics, Chinese Academy of Sciences. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/ 4.0/).

The construction of deep excavation inevitably impacts the surrounding strata, posing risk to the safety of adjacent buildings. Therefore, accurately evaluating strata settlement during the construction is essential. This study considers Shenzhen Metro Chegongmiao Station as a case study, offering a comprehensive analysis of the mechanical behavior throughout the entire deep excavation process. A predictive method is proposed, incorporating the Mindlin solution and the Source-Sink Imaging method. This method includes simplified representations of the unloading effects from diaphragm wall construction and soil excavation. Additionally, nonlinear fitting is employed to derive the dewatering curve, addressing the challenge of predicting the groundwater level outside the excavation zone. The influence of the dewatering is thus quantified through calculating the seepage volumetric forces. The results demonstrate that in water-rich strata, the unloading effect due to diaphragm wall construction- a factor frequently underestimated in conventional analysis- exerts a profound influence on the surrounding strata. Quantitative evidence from the case study reveals that this phase alone contributed 12 mm to the surface settlement, accounting for a significant 44% of the cumulative displacement (27 mm). The settlement curves exhibit variations across different construction stages. Notably, the location of the maximum surface settlement during the diaphragm wall trenching occurs at the point farthest from the excavation. Furthermore, an analysis of the factors influencing settlement shows that slurry density has the most substantial effect. With the same relative change, slurry density exerts an influence on settlement that is up to 30 times larger than the effects of other variables. These findings provide a scientific foundation for the design, construction, and safety assessment of deep excavations in water-rich strata.

Drill-and-blast tunneling generates large volumes of rock spoil, and efficient and accurate characterization of block size distribution is critical for enhancing resource utilization. However, traditional manual measurement methods are time-consuming and limited in spatial coverage. To address these limitations, a UAV-based image acquisition approach combined with deep learning was employed to automatically extract rock block contours. The block size distribution and resource utilization potential of tunnel spoil were investigated using a case study from Dangshun Tunnel spoil yard in Qinghai Province, China. The results show that the median block diameter is approximately 300 mm, with maximum sizes exceeding 1 500 mm. Both the size and morphology of rock blocks exhibit systematic spatial variation along the slope, with particle size gradually increasing from fine to coarse from the slope crest to the slope toe, while block shape transitioning progressively from subrounded to angular. In recently dumped areas, rock blocks largely preserve their original blast-induced fragmentation features, with a relatively high proportion of large fragments exceeding 1 000 mm in size. This suggests that optimization of charging structure and blasthole spacing is necessary. Based on gravity-induced sorting characteristics, a zoned resource utilization strategy is proposed in which medium- and fine-grained materials at the crest and slope face zones can be directly used as fill or road construction materials, whereas coarse blocks accumulated at the slope toe should be crushed for recycling. The findings provide a technical basis for efficient resource utilization of tunnel spoil and optimization of blasting design in tunnel engineering.

Irradiating hard rocks by a high-power laser can reduce localized hardness in the rocks; however, continuous lasers produce a large amount of melt that inhibits further heat absorption. Pulsed lasers allow rocks to absorb and dissipate energy and avoid melt formation. In this study, 200 W nanosecond pulsed laser was used to irradiate granite. The effects of laser parameters on the thermal cracking morphology, temperature field, warming pattern, and Leeb hardness of the granite surface were analyzed. The optimal laser parameters for softening granite were determined by performing objective optimization in MATLAB using granite’s melting point as the reference. Nanoindentation techniques were employed to assess the softening characteristics of the granite surface along the longitudinal direction. The results showed that three main forms of thermal damage occurred on the granite surface: oxidative decomposition, spalling, and melting. The damage state was affected by the average laser power, with the pulse width and repetition frequency affecting surface damage differently. Appropriate laser parameters effectively controlled the melt damage on the granite surface, and irradiation with nanosecond pulsed lasers effectively reduced surface hardness. However, excessive power can generate large amounts of hard melts and weaken the softening effect.

Rapid growth of projects on high-fill sites under red clay and deep soft clayey foundations in Southwest China has exposed the limitations of conventional dynamic compaction in effective improvement depth and energy utilization. Punching and Squeezing Dynamic Compaction (PSDC) forms red clay–gravel composite piers through successive punching, backfilling and squeezing, offering potential advantages in deep densification; However, the mechanism of energy transmission and structural evolution remain unclear, constraining optimization of construction parameters and design. To address this gap, an integrated “Discrete element simulation–laboratory model testing–μCT 3D reconstruction” framework is established. Based on PFC3D with a Hertz contact model, impact-induced dynamic response and energy distribution were elucidated, and macro–meso consistency was verified against model tests and μCT-3D reconstructed piers, enabling systematic analysis of energy transfer, dissipation and skeleton reorganization under PSDC. Results show pronounced three-dimensional directional attenuation of impact energy: vertical transmission is the most efficient, the 45° oblique direction exhibits intermediate decay, and the horizontal direction attenuates rapidly with distance. Gravel content decisively governs energy pathways and skeletal architecture: a 60% gravel content produces continuous force chains, increases wave impedance, and concentrates energy at depth, promoting more effective compressive deformation and deep densification; in contrast, 50% gravel yields a more discrete skeleton, enhancing shallow random sliding, increasing sliding work, and promoting near-field dissipation. A directional attenuation model derived from a three-dimensional wavefront effectively fits the exponential decay of peak particle velocity with distance in the three directions and, for two representative gravel contents (50% and 60%), indicates a consistent chain linking gravel-skeleton connectivity, energy partitioning, and densification efficiency. These insights, obtained for 50%–60% gravel contents in high-fill red clay, illustrate how skeleton continuity regulates directional attenuation and densification, and they provide a basis for further extensions to broader mixture ratios and field scales.

This study presents an innovative maintenance strategy for in-service tunnels, integrating high-fidelity 3D digital reconstruction with physics-based simulation to enable predictive maintenance. First, a digitalisation workflow is developed to integrate geological conditions, tunnel structures, and defect data using 3D point-matching, semantic extraction, and Kriging interpolation. Statistical analysis then unveils correlations between structural defects and geological conditions. Furthermore, a novel bottom-up automatic mesh-processing workflow is presented to automate mesh partitioning, quality assessment, and topology optimisation in digital models, enabling seamless transitions from digital models to numerical simulation. A case study of the Yutang Liangzi Tunnel in China is conducted to verify the proposed strategy. The developed digital model discovers significant correlations between tunnel defects and geological conditions. Finite element analysis reveals stress patterns in tunnel structures under various boundary and load conditions. The proposed strategy shows potential to advance next-generation maintenance practices for operational tunnels.

Primary support deformation encroachment into secondary lining space is a critical problem in tunnels under unfavorable geological conditions. Conventional demolition and reconstruction of failed supports causes severe re-disturbance to stabilized rock masses, posing high collapse risks and increasing costs. To tackle this critical challenge, this paper presents a slim-strengthened steel arch-shotcrete lining with interlocking longitudinal connecting bars (SS-ILCB lining) as a substitute for the cast-in-place reinforced concrete lining (CIP-RC lining). Full-scale loading tests and numerical simulations systematically investigate its mechanical properties, failure mechanisms, and performance compared with the CIP-RC lining. Results demonstrate that: the SS-ILCB lining experiences the elastic stage, the elasto-plastic stage and the failure stage, exhibiting a small eccentric compression state under approximately 1.5-dimensional constraint state. The shotcrete exhibits a typical shear failure mode instead of bending failure. The concentration of multiple steel arch joints on the same longitudinal horizontal line within a limited range will significantly reduce the local stiffness of the lining, making this region the most vulnerable part that fails first during the loading process. The connection nodes between the longitudinal connecting bars and the steel arch should be strategically placed away from the steel arch joints. The technical strategy of implementing a slim-strengthened secondary lining design and optimizing the construction process can notably enhance construction efficiency while maintaining acceptable structural safety margins. The research findings provide valuable technical support and reference for similar underground engineering projects.

Rapid extraction of excavation contours from tunnel face images and quantitative assessment of overbreak/underbreak areas are essential for quality control in drill-and-blast tunneling. This study proposes an automated framework that integrates prompt-guided YOLO-SAM2 joint segmentation with scale calibration based on a laser rangefinder to delineate tunnel face contours and quantify overbreak/underbreak. First, YOLO11-seg is fine-tuned on tunnel face image datasets to generate bounding boxes and initial masks as prompts, and a fine-tuned SAM2 refines the boundary segmentation. Second, a pixel-to-physical mapping is established via laser ranging and triangulation to convert segmented areas into physical length. Finally, Monte Carlo Dropout is adopted for uncertainty quantification to assess the reliability of the segmentation results. Experiments show that: (1) the proposed method achieves efficient contour extraction and quantification, enabling rapid per-image analysis for practical engineering applications; (2) compared with ft-YOLO11-seg, the YOLO-SAM2 framework increases the mean F1score and pixel accuracy (PA) by 7.42% and 7.16%, respectively; and (3) the relative combined standard uncertainty of the area measurement after scale calibration is approximately 0.38%. Bland-Altman analysis between the two measurement methods showed a mean percentage bias of approximately 2.03%, with 95% limits of agreement of [-1.89%, 5.95%]. The proposed method offers a rapid quantitative approach for detecting tunnel-face overbreak and underbreak.

This study systematically investigates the post-construction settlement behavior of high-fill red clay embankments, focusing on the influences of three key factors (water content, degree of compaction, and lift thickness) and the effectiveness of geogrid-based reinforcement measures. A three-dimensional finite-element model based on the Mohr–Coulomb constitutive theory was established using MIDAS GTS NX 2022 R1 to simulate staged construction processes and long-term settlement under self-weight loading. The results indicate that settlement is predominantly concentrated in the upper fill zone adjacent to the slope surface, with displacement contours sagging inward toward the fill interior, while the underlying foundation undergoes negligible deformation. An elevated water content and reduced degree of compaction significantly enhance the compressibility of red clay, leading to increased settlement magnitudes and prolonged stabilization periods. Excessively thick lifts result in inadequate deep compaction, thereby inducing larger final settlements. Two reinforcement schemes (geogrid combined with anti-slide piles and geogrid combined with a gravity retaining wall) were verified to effectively mitigate post-construction settlement, with the former achieving a more pronounced improvement in the embankment stability coefficient. Based on the comprehensive analysis, optimal construction control parameters for high-fill red clay embankments are proposed: precise regulation of water content, maximization of compaction degree, and adoption of a lift thickness of approximately 30 cm. The findings of this study provide quantitative technical support and design references for the settlement control of similar high-fill red clay embankment projects in southern China’s mountainous and hilly regions.

Time-series machine learning (ML) models are commonly employed to forecast the tunneling performance of tunnel boring machines (TBMs) by learning from historical data. However, these models often generate delayed predictions, reducing their effectiveness for real-time decision-making. In this study, a temporal convolutional network (TCN) is developed to predict TBM penetration rates using actual tunnel project datasets. The underlying causes of prediction delays are identified by decomposing the input sequence, and two novel decomposition-reconstruction-based model train strategies are proposed to address this challenge. The results indicate that standard ML models trained on raw TBM time series data produce delayed predictions, primarily due to high first-order partial autocorrelation of residual components in the input sequences. These delays can be eliminated by incorporating prior knowledge to predict residuals or fully decomposing the residual components. The proposed method significantly improves the reliability of time series prediction models, enhances prediction performance, and provides generalizable frameworks for mitigating prediction delays in geotechnical time series modeling.

Floor heave is a common defect in mountainous tunnels.It is critical but challenging to predict the risk of floor heave,as traditional methods often fail to characterize this phenomenon effectively.This study proposes a data-driven approach utilizing a support vector machine(SVM)optimized by the sparrow search algorithm(SSA)to address the issue.The model was developed and validated using a dataset collected from 100 tunnels.Shapley value analysis was conducted to identify the key features influ-encing floor heave defects.Moreover,a committee-based uncertainty quantification method is pre-sented to evaluate the reliability of each prediction.The results show that:(1)Data feature engineering and SSA play pivotal roles in expediting the convergence of the SVM model.(2)Groundwater and high in situ stress are key factors contributing to tunnel floor heave.(3)In comparison to backpropagation(BP)neural networks,the SSA-SVM demonstrates superior robustness in handling imperfect and limited data.(4)The committee-based uncertainty quantification method is proven effective to evaluate the trustworthiness of each prediction.This data-driven surrogate model offers an effective strategy for understanding the factors that impact tunnel floor defects and accurately predicting tunnel floor heave deformation.

Failures caused by groundwater on tunnel floors, such as floor heave, leakage, and cracking, have presented significant challenges for the safe operation of high‐speed railway (HSR) tunnels. One major but overlooked cause of these water‐related problems is concealed damage in the concrete construction joints of tunnel floors. This study conducts a refined numerical investigation based on a case of water‐related failures in an HSR tunnel floor. The study's innovation lies in its comprehensive consideration of the cracking and seepage process of the construction joints using the cohesive zone model and the fracture flow model specially developed to address this issue. The obtained results predict that the tunnel's original drainage system is ineffective in reducing the high external water pressure at the bottom of the tunnel, leading to floor heave. The damage at the construction joint interface primarily occurs as a result of floor heave and is mainly distributed at the invert arch‐invert fill interface and the invert fill‐leveling layer interface. This damage weakens the stiffness of the tunnel floor, making it easier for the track deformation to reach the operation warning value compared to the model that does not consider the interface effect. Pressurized groundwater can seep into the construction joints through areas with poor waterproofing, resulting in interlayer water pressure that uplifts the track structure before damage occurs at the entire invert arch–arch fill interface. Lastly, a new drainage system that combines an external bottom channel and interlayer drainage pipe was proposed according to the characteristics of the water‐induced failures, which can effectively prevent floor heave and joint leakage.

Due to space constraints in mountainous areas, twin tunnels are sometimes constructed very close to each other or even overlap. This proximity challenges the structural stability of tunnels built with the drill-and-blast method, as the short propagation distance amplifies blasting vibrations. A case of blasting damage is reported in this paper, where concrete cracks crossed construction joints in the twin-arch lining. To identify the causes of these cracks and develop effective vibration mitigation measures, field monitoring and numerical analysis were conducted. Specifically, a restart method was used to simulate the second peak particle velocity (PPV) of MS3 delays occurring 50 ms after the MS1 delays. The study found that the dynamic tensile stress in the tunnel induced by the blast wave has a linear relationship with the of the product of the concrete wave impedance and the PPV. A blast vibration velocity exceeding 23.3 cm/s resulted in tensile stress in the lining surpassing the ultimate tensile strength of C30 concrete, leading to tensile cracking on the blast-facing arch of the constructed tunnel. To control excessive vibration velocity, a mitigation trench was implemented to reduce blast wave impact. The trench, approximately 15 m in length, 50 cm in width, and 450 cm in height, effectively lowered vibration velocities, achieving an average reduction rate of 52% according to numerical analysis. A key innovation of this study is the on-site implementation and validation of the trench's effectiveness in mitigating vibrations. A feasible trench construction configuration was proposed to overcome the limitations of a single trench in fully controlling vibrations. To further enhance protection, zoned blasting and an auxiliary rock pillar, 80 cm in width, were incorporated to reinforce the mid-wall. This study introduces novel strategies for vibration protection in tunnel blasting, offering innovative solutions to address blasting-induced vibrations and effectively minimize their impact, thereby enhancing safety and structural stability.

A case study delving into the damage of tunnel structures subject to bottom voids is presented in this paper. The study is carried out through the comparison between the field and numerical investigations, confirming that the damage behavior in the tunnel structure can be numerically analyzed by considering the field-investigated continuous bottom void in the numerical simulation. Moreover, the numerical model without a bottom void is also simulated to clarify the damage in the bottom structure influenced by the field-investigated continuous bottom void. The numerical analysis demonstrates that the existence of a bottom void has significantly changed the deformation characteristics of the tunnel structure, in which the damages in the tunnel structure are probably caused by the investigated continuous bottom void in the field. This study can provide guidance for repairing damaged tunnel structures subject to bottom voids.

Geological hazards, particularly water inrush, pose frequent challenges in tunnel constructions within karst regions. Drawing from the engineering experiences in addressing multiple large-scale water inrush hazards in the Dejiang tunnel, a combined method of field investigation and theoretical analysis was employed for qualitative and quantitative analyses of water inrush mechanisms. The regional geological investigation highlighted the formation of strong and weak aquifers due to alternating weak limestone and mudstone in the synclinal strata, creating favorable conditions for large-scale karst conduit. Atmospheric precipitation water connects karst cavities through groundwater-eroded karst conduit, establishing a recharge system for water inrush hazards. Three empirical formulas are adopted to investigate the influence of rainfall on the tunnel’s actual water inflow. Importantly, it was found that considering only the influence of rainfall or surface water cannot reasonably predict the inflow in this area. The disaster’s primary causes are attributed to the heavy rainfall, karst conduit, underground river, and weak strata, which have contributed to the persistent nature of water inrush events. The principle of “drainage and blockage” was used to address the issue of water inrush. Proposed remediation strategies during construction, including the innovative membrane bag high-pressure grouting, have proved to be effective in addressing the connected karst conduits. The drainage and blockage effects were achieved by installing drainage pipes during the grouting reinforcement process. Finally, the water pressure-resistant structure was employed to enhance the stiffness of the lining. As validated by monitoring data, the measures serve as crucial methods to guarantee the safety of tunnel structures, effectively prevent water inrush and amplify the ecological benefits of water-rich areas.

Maoxian Tunnel is located in a high -stress region and has undergone over 1.0 m of horizontal deformation, which has caused concrete cracking in the initial support and the failure of fulllength grouted rock bolts owing to extrusion. Investigations revealed that higher water -cement (w/c) ratios lead to higher grout volume shrinkage (Vs), consistency, and inadequate borehole filling. Combined with the lower compressive strength of grouting, this results in weak rock -bolt bonding. The wet contact interface further reduces the ultimate bearing capacity of the interface. Therefore, the rock bolts are squeezed out and fail. Reducing Vs by adopting a smaller w/c ratio and optimizing the w/c agents can enhance the grout's compressive strength. Additionally, the strength of the rock-bolt interface is improved in soft rock. The varying bolt length significantly influences the rock deformation control, but the tunnel stress relaxation in areas with high geostress extends beyond 8.0 m. Strengthening support structures and expediting installation are both crucial measures for resisting structural forces in such environments.

Traditional tunnel management methods are labor-intensive and costly. This study introduces a digital model that integrates tunnel structures, operational defects, and geological conditions for efficient tunnel management. The method automates 3D reconstruction using 2D CAD drawings, textual defect reports, and geological data, incorporating statistical analysis to provide insights into structural health in complex geological settings. Additionally, the developed digital model can be seamlessly integrated into computational models for evaluating tunnel mechanical state and improving maintenance decisions. Both digital and numerical replicas can be continuously updated when new information becomes available. Application to the Yutang Liangzi Tunnel in China reveals a high correlation between tunnel defects and geological conditions. Furthermore, static and dynamic numerical simulations are performed to assess the structural stability of the tunnel. The developed method shows great potential for advancing digital twins in tunnel engineering.

Airblast and blasting noise have long been major environmental nuisances associated with blasting works, often leading to complaints from nearby residents. Therefore, comprehending the propagation characteristics of airblast waves is crucial. This study collected the air overpressure (AOp) signals of airblast during tunnel construction. These signals originated from blasting in different rock conditions, excavation methods, and blasting locations. The analyzed signal parameters include the overpressure peak (pmax), overpressure duration (t+), positive impulse (I+), and Fourier main frequency. The study found that the time-domain AOp signal is composed of multiple sub-signals, each originating from the each delay of the millisecond blasting. The explosive equivalent is the most significant factor influencing AOp, rather than tunnel excavation methods and rock conditions. Harder rock conditions involve more explosives, resulting in larger pmax, longer t+, and more I+. Among these, the explosive quantity in the cutting holes of MS1 provides the most accurate prediction for pmax. However, as the airblast waves propagate inside the tunnel, their pmax, t+, I+, and Fourier main frequency exhibit fluctuating changes with distance. This fluctuation stems from the AOp surge caused by wave chasing, and is more pronounced in smaller cross-sections owing to wall constraints. The airblast waves rapidly attenuate after propagating out of the tunnel entrance, interestingly, the degree of AOp attenuation and the distribution of the main frequency are related to the azimuth angle. As the angle from the tunnel axis increases, the AOp attenuation becomes more pronounced and the main frequency increases. The study also observed that the main frequency distribution of the airblast waves ranges from 0 to 140 Hz, with a broad distribution within the audible range (>20 Hz). This can lead to intense noise, which disrupts the daily life of residents. Moreover, the airblast waves transmitted outside the tunnel contain infrasound, which may cause windows to squeak in the distance.

Objective Many defects related to the lining of high -speed rail tunnels gradually become prominent with the increase of the high-speed rail construction completion years. The waterproof board cutting lining concrete is one of these serious defects. In order to reduce the structural disturbance and the above defects impact on line operation, new technologies need to be used to rectify the waterproof board cutting lining defects in the arch of high-speed rail tunnel. Method Based on a dual-line high-speed railway tunnel with a design speed of 200 km/h in southwest China, two adoptable treatment schemes (cast-in-place arch and lattice technology) after its arch waterproof board cutting the lining concrete are analyzed in detail. A comparative assessment of the safety and economy of the structure is also carried out. The construction organization, process flow, protective measures and construction effects of the defect rectification scheme using lattice technology are emphatically discussed. Result & Conclusion Compared with other schemes, the lattice technology rectification scheme makes full use of the existing structure bearing capacity, repairs the tunnel only in a local area with little impact on both the existing lining structures and the high-speed railway line operation. This scheme can significantly reduce the main stress and displacement of the structure, and make the bearing capacity of the defective lining meet the design requirements.