Search Results (1,242)

To mitigate safety risks such as tunnel collapse and water inrush induced by fault fracture zones during urban shield tunneling, this study investigates the application mechanisms and identification characteristics of the surface transient electromagnetic (TEM) method for ahead-of-face geological prediction, using a shallow metro tunnel (30–50 m burial depth) in Qingdao as a case study. Departing from conventional empirical threshold approaches, a three-dimensional geological model incorporating a fault fracture zone is constructed. Guided by electromagnetic diffusion theory, the transient field response evolution is numerically simulated to obtain time-domain electromagnetic decay curves at various observation points. By integrating these simulations with field measurements, quantitative criteria for fault identification are extracted. The results demonstrate that the electric field response attenuation rate at measurement points directly overlying the fault fracture zone is significantly faster than that in the intact host rock. This accelerated decay behavior is jointly governed by the fault scale, degree of water saturation in the fracture zone, and source–receiver offset, serving as a primary indicator for fault identification. In the apparent resistivity profiles, the fault-intersecting zones exhibit distinct abrupt transitions between low and high resistivity. The water-saturated fracture zone manifests as a well-defined low-resistivity anomaly, generating a pronounced electrical contrast with the high-resistivity host rock. Field validation confirms that the identified low-resistivity anomaly aligns closely with the actual location of the water-bearing fault, which was subsequently verified during tunnel excavation. This study elucidates the physical mechanism of electromagnetic diffusion distortion induced by faults under shallow urban conditions. The proposed integrated criterion, combining the response attenuation rate with abrupt apparent resistivity boundaries, effectively mitigates the non-uniqueness inherent in single-parameter geophysical interpretations. These findings provide theoretical support and a reproducible engineering criterion for ahead-of-face fault prediction in metro tunnels. Future research should further incorporate the effects of geological anisotropy and dynamic groundwater seepage on the electromagnetic diffusion process. Full article

Background: Carpal tunnel syndrome (CTS) is the most prevalent peripheral nerve entrapment neuropathy, with rising incidence in aging populations. Uncertainty persists regarding the efficacy and safety of carpal tunnel release (CTR) in patients aged ≥ 70 years. Objectives: To systematically evaluate the indications, clinical outcomes, and utility of CTR in elderly patients (≥70 years), with comparison to younger cohorts. Methods: Following PRISMA 2020 guidelines, PubMed/MEDLINE, Scopus, CENTRAL, Embase, Web of Science, and grey literature sources were searched from inception through September 2025. Two independent reviewers extracted data; inter-rater agreement was strong (κ = 0.81–0.86). The primary outcome was the Boston Carpal Tunnel Questionnaire (BCTQ). Weighted mean differences (WMDs) with 95% confidence intervals (CIs) were calculated using DerSimonian–Laird random-effects models. Certainty of evidence was assessed using the GRADE framework. Results: A total of 20 studies encompassing 3841 operated hands, including 1139 hands in elderly patients and 2702 hands in younger comparators across comparative studies, were analyzed. Mean SS-BCTQ improvement was 1.8 points (95%CI: 1.6–2.0; exceeding the established MCID of 1.04–1.05 points). FS-BCTQ improvement was 1.1 points (95%CI: 0.9–1.3; marginally below the pooled MCID of 1.13 points). Elderly patients demonstrated SS-BCTQ improvement of 1.7 points and satisfaction rates of 72–94%, comparable to younger cohorts (75–95%; p = 0.38). Grip strength improved 15–25% in younger patients but remained unchanged in elderly patients (p < 0.001). Sensory recovery reached 42% in elderly versus 58% in younger patients (p < 0.01). Complication rates were low and age-independent (3.1%; RR 1.08; 95%CI: 0.86–1.35; p = 0.52). GRADE certainty was as follows: low for symptom and functional improvement; very low for surgery versus conservative management. Conclusions: CTR is associated with significant symptomatic benefit in elderly patients when conservative treatment fails, with complication rates comparable to younger populations. Age alone should not constitute a surgical contraindication. Preoperative counseling must establish realistic expectations regarding grip strength and functional recovery. High-quality randomized trials in elderly populations remain an urgent research priority. Full article

Fluctuating pressure generated during ship operation is closely related to propeller vibration, noise, and structural safety, and its frequency spectrum is a key design indicator in the propeller design stage. However, water tunnel experiments to measure fluctuating pressure generated by high-speed propellers require high-pressure facilities and involve complex procedures, high costs, and long lead times when experimental conditions are modified or new propellers are tested. To overcome these limitations, this study proposes a deep learning-based network, referred to as MSPFS-Net (Model-Test Ship Pressure Frequency Spectra Network), to estimate the frequency spectrum of fluctuating pressure from model test data. The proposed method uses propeller CAD data, principal design parameters, wake data, and water tunnel test conditions as inputs, and is trained in a supervised learning framework using frequency-domain data obtained by transforming experimentally measured fluctuating pressure signals. The trained network can predict the fluctuating pressure frequency spectrum without direct sensor measurements, even under conditions not present in the training dataset. The results of this study demonstrate the potential to reduce dependence on water tunnel experiments and to efficiently evaluate fluctuating pressure characteristics in the early design stage, indicating that the proposed approach can serve as a practical design support tool in terms of both cost and time efficiency. Full article

Purpose: The aim of this study is to describe a slit-modified 23-gauge infusion trocar designed to enable early postoperative hypotony-free sclerotomy closure by allowing scleral suturing prior to complete trocar removal, and to report initial clinical outcomes in eyes with proliferative diabetic retinopathy with or without vitreous hemorrhage (PDR + H and PDR). Methods: A standard 23-gauge metallic (titanium) trocar was modified by creating a longitudinal slit that permitted passage of a suture needle while the trocar remained partially engaged within the scleral tunnel. At the end of pars plana vitrectomy, a transscleral suture was placed through the slit with the knot prepared prior to trocar removal, followed by simultaneous trocar extraction and suture tightening. Eighteen consecutive patients undergoing vitrectomy for PDR (fourteen with vitreous hemorrhage [PDR + H]; four without) were included. Intraocular pressure (IOP) was recorded preoperatively, immediately after sclerotomy closure (postoperative baseline), and at 8 and 24 h postoperatively. The study was designed as an exploratory pilot feasibility and safety evaluation of a slit-modified infusion trocar in 23-gauge vitrectomy. The primary outcomes were postoperative IOP stability and wound leakage. Secondary outcomes included early hypotony, postoperative hemorrhage, choroidal effusion, and the need for additional suturing. Results: All procedures were completed without intraoperative complications. The mean IOP was 14.83 ± 2.50 mmHg preoperatively, 13.33 ± 1.53 mmHg immediately after closure, 14.17 ± 3.01 mmHg at 8 h, and 15.17 ± 1.79 mmHg at 24 h. No cases of wound leakage or early postoperative hypotony were observed in either subgroup. One eye exhibited a transient IOP increase at 8 h; no choroidal effusion, postoperative hemorrhage, or need for secondary suturing occurred. Endotamponade consisted of balanced salt solution (BSS) in eight eyes, SF6 in seven eyes, silicone oil in two eyes, and air in one eye. Conclusions: The slit-modified infusion trocar enables secure, hypotony-free closure of the infusion sclerotomy by eliminating the open-wound interval during trocar removal. This simple biomedical device modification provides stable early postoperative IOP across different tamponade agents and appears safe and feasible in high-risk eyes with PDR. Full article

High-speed train aerodynamics have mainly been improved by passive design methods, such as streamlined noses, local fairings, and surface smoothing. These methods have achieved clear benefits, but several important aerodynamic problems remain difficult to solve by geometry optimization alone. Open-air drag is still affected by tail flow separation, base-pressure recovery, and disturbances around bogies and the underbody; crosswind safety is influenced by unsteady leeward-side separation and wake asymmetry; slipstream behavior depends on wake vortices, boundary-layer development, and complex near-ground underbody flow; and tunnel-related pressure transients arise from compression-wave generation, propagation, and reflection. These coupled effects mean that one fixed train shape cannot perform optimally in all operating conditions. For this reason, this review proposes that active flow control (AFC) should not be regarded only as a drag-reduction or stability-improvement technique for high-speed trains. Instead, it should be understood as a mission-adaptive aerodynamic control framework, in which different control actions are used for different operating scenarios. This paper first clarifies that passive optimization is increasingly subject to diminishing returns under multi-objective and engineering constraints. It then reviews AFC studies on drag reduction, base-pressure recovery, wake and slipstream control, underbody flow conditioning, crosswind mitigation, and tunnel pressure-wave suppression. Related AFC studies on bluff bodies, road vehicles, and other separated flows are included only when their physical relevance to trains is clear. The review further distinguishes gross aerodynamic improvement from net energy gain and identifies actuator power, durability, maintainability, acoustic impact, validation level, and full-scale transferability as decisive feasibility factors. Current research is still dominated by open-loop numerical studies with simplified actuation. Future work should therefore move toward multi-objective, closed-loop, energy-aware, sensor–actuator-integrated, and explainable machine-learning-assisted AFC. The main message is that the next step in train aerodynamics is not simply a better fixed shape, but a control-enabled train that can selectively redistribute aerodynamic authority across its mission profile. Full article

The mechanical sensitivity of energetic materials is closely linked to the stability of their microstructures; however, in situ observation of their dynamic response under external mechanical stimuli at the atomic scale remains challenging. Here, we propose a deep-learning-based intelligent analysis method for scanning tunneling microscopy (STM) images of a next-generation insensitive energetic material 3-nitro-1,2,4-triazol-5-one (NTO). We design SpecMol, a lightweight segmentation network with frequency-domain awareness, which achieves high-precision segmentation and orientation recognition of individual NTO molecules in adsorption images. Building upon this, we apply localized external forces to one-dimensional NTO nanochains via in situ STM tip manipulation and quantitatively analyze the geometric evolution of their fundamental building blocks—dimers. Experimental results reveal that, following mechanical perturbation, the relative orientation angle within the dimer (averaging approximately 14.55°) remains highly stable (CCC = 0.834), confirming the remarkable structural rigidity of NTO dimers. This study provides, for the first time, direct microscopic evidence at real-space atomic resolution for the low mechanical sensitivity of NTO, elucidating that its exceptional local structural stability originates from rigid dimeric units stabilized by an extensive hydrogen-bonding network. Our findings not only deepen the fundamental understanding of the safety performance of energetic materials but also demonstrate the powerful potential of integrating artificial intelligence with advanced characterization techniques for molecular-scale functional materials research. Full article

Tunnel construction requires accurate and timely classification of surrounding rock masses to ensure safety and guide excavation. This research addresses the limitations of conventional methods and unimodal intelligent approaches by proposing a novel hybrid deep model, Random-Mamba, that integrates drilling parameters and digital images for enhanced classification performance. A dataset of 3361 synchronized samples was constructed, containing six drilling parameters, digital face images, and expert-classified rock mass grades. The model employs a dual-branch architecture: a Random Forest processes the drilling parameters, and a MambaVision network extracts visual features, with a multilayer perceptron performing the fusion. The proposed model achieved an overall accuracy of 92.12% and a macro-F1 score of 91.66%, outperforming the most comparable hybrid model by 2.61% in accuracy. It demonstrated particularly high precision in identifying Class III rock with an F_1-score of 93.2%. Ablation and comparative experiments confirmed its superiority over both single-modality models, such as SVM and ResNet, and other hybrid architectures, like Random-Swin. SHAP-based sensitivity analysis further revealed that feed speed was the most influential drilling parameter for classification. The effective fusion of complementary mechanical and visual data provides a robust and practical solution for real-time rock mass assessment in tunneling engineering. Full article

Large-span stadium roofs in coastal regions are highly vulnerable to typhoon-induced wind damage, and their post-event performance depends on both structural safety and functionality recovery. This study proposes a probabilistic framework to assess typhoon-induced damage, functionality degradation, recovery, and resilience of a large-span stadium roof system in Shenzhen, China. Progressive damage to the roof cover and the roof-supporting structure is evaluated by combining wind tunnel pressure data and structural analysis. The results show that the roof cover shows greater vulnerability than the supporting structure, with slight damage emerging at around 30 m/s, whereas structural damage requires higher wind speeds. A functionality-based recovery model is further developed by considering repair preparation, repair duration, and repair sequence constraints. The building generally exhibits a high resilience level, with a mean resilience index of 0.9550 and a median of 0.9589. The initial overall building functionality loss increases from about 7% under TY conditions to 20% under STY and 60% under Super TY, while the recovery duration increases by about 2–3 times and 5–6 times relative to the TY case, respectively. The proposed framework provides a practical basis for resilience-oriented performance assessment of large-span roof structures under typhoon hazards. Full article

With the rapid development of urban rail transportation, environmental vibrations caused by subways operating are becoming more serious. They have affected people’s living comfort, the stability of precision scientific instruments, and the safety of buildings. In order to make a good and real prediction of metro-induced vibration, this paper constructs a kind of analytical–numerical hybrid method to evaluate the dynamic response of the whole vehicle–track–tunnel–soil system. First, an analytical metro vehicle–track coupled dynamic model is established according to the Zhai method, and then the wheel–rail force acting on trains can be acquired. And then we use a 3D numeric model which incorporates the track, tunnel and ground with a finite element method. At last, the wheel–rail force is used as an excitatory load, and then the train–track–tunnel–ground coupling system dynamic response analytic–numeric model can be created. Based on this, the influence of track quality level, train speed and tunnel burial depth on the characteristics of ground surface vibration is studied in sequence. From the results, we can see that given the same track quality condition, increasing train speed greatly increases the response amplitude on the ground surface; improving track quality is very effective to reduce response amplitude; and with the tunnel buried deeper, the vibration level would be obviously reduced, local peak response would be suppressed and deep tunnels would have better vibration suppression under higher-speed operation conditions. Full article

Robotic systems are increasingly being deployed in mining operations to support tasks such as inspection, navigation, environmental monitoring, and safety supervision. However, mining environments present significant challenges for robotic perception due to dynamic terrain conditions, poor illumination, airborne dust, and frequent disturbances caused by excavation and heavy machinery. Conventional frame-based vision systems often struggle under these conditions due to motion blur, latency, and limited dynamic range. This study proposes a system-level conceptual framework for integrating event-based sensing into robotic mining systems in order to support perception in highly dynamic and safety-critical environments, with the aim of improving responsiveness and robustness under such conditions. Event-based cameras, inspired by biological vision, asynchronously detect brightness changes at the pixel level and provide microsecond temporal resolution with high dynamic range and low latency. The proposed framework combines event cameras with complementary sensing modalities including LiDAR, inertial measurement units, and RGB cameras to form a multi-sensor perception architecture. The framework is structured into multiple functional layers encompassing environmental sensing, event-driven perception, sensor fusion and AI processing, digital twin integration, and autonomous decision-making. Potential application scenarios including robotic tunnel inspection, autonomous navigation of mining robots, hazard detection, multi-agent cooperation in mining sites, and real-time digital twin updating are also discussed. The proposed framework provides a unified system-level reference architecture intended to guide future implementation and validation. Full article

Drill pipe threads are susceptible to fatigue cracking under complex downhole loads, posing significant risks to drilling safety. Although metal magnetic memory (MMM) testing enables efficient nondestructive evaluation, its practical utility is often compromised by interference from material magnetization and lift-off distance. To overcome this limitation, we introduce a novel damage assessment method based on the area peak-to-mean ratio (APMR) of magnetic signals. This feature is specifically designed to suppress external disturbances while retaining sensitivity to stress-induced magnetic anomalies. Finite element analysis was performed to elucidate the magneto-mechanical coupling behavior at defective thread roots. Subsequently, MMM signals were acquired from drill pipe threads under varying inspection conditions using a custom-built scanning system equipped with 16 tunneling magnetoresistance (TMR) sensors. Multiple features, including APMR, were extracted and evaluated across various machine learning classifiers. The gradient boosting machine (GBM) achieved superior performance, yielding an accuracy of 0.9861 and a recall of 1.0000 on the test set—outperforming all other models. This work presents an effective automated approach for drill pipe thread damage evaluation, contributing to enhanced reliability and safety in drilling operations. Full article

To investigate the multifactor coupling mechanisms in roadway tunnel fire accidents, this study develops a quantitative risk analysis framework integrating the N-K model and a dynamic Bayesian network (DBN). Historical accident statistics are analyzed to identify coupling patterns among human, tunnel, vehicle, and management subsystems. The N-K model quantifies coupling strength and interaction mechanisms, while the integrated N-K–DBN model enables dynamic probabilistic assessment, diagnostic evaluation, and sensitivity analysis. Using empirical data reduces reliance on expert-based assessments and may improve the transparency and consistency of the evaluation within the adopted coding and modeling assumptions. The findings indicate that human–vehicle and human–tunnel–vehicle couplings exhibit the highest probabilities and are, within the present modeling framework, most strongly associated with traffic accidents, vehicle categories, and emergency management proficiency. Sensitivity analysis provides model-based insights for formulating operation and maintenance strategies under the adopted assumptions. During early operation, the results suggest that strengthening traffic control and improving emergency response capability may help reduce accident likelihood. In later stages, maintaining the stable operation of tunnel systems may help limit coupling risks. Overall, this study provides a model-based quantitative reference for understanding dynamic coupling paths and for supporting fire-safety-related decision making in roadway tunnel systems. Full article

Geometric deviations are inevitably generated during tunnel lining construction. These deviations result from construction inaccuracies. They pose potential risks to long-term structural safety and engineering quality. Traditional numerical simulations are based on idealized design cross-sections. This approach is limited in reflecting actual mechanical behavior. In this study, a refined modeling and safety assessment method is developed. Construction-induced geometric deviations are incorporated into the analysis. Optimized geometric fitting and mesh reconstruction algorithms are employed. Large-scale irregular point cloud data are efficiently processed. A full-scale solid finite element model is constructed. Actual construction deviations are represented in this model. The results are systematically compared with those from the conventional design model. It is revealed that construction-induced geometric deviations alter internal force transmission paths. Asymmetric deformation is induced. Localized stress concentrations are observed. The ideal stress state is predicted by the design model. In contrast, stiffness degradation is observed in the as-built model. This degradation is significant in vulnerable regions such as the haunch on the heavily loaded side. A considerable reduction in the local safety factor is also observed. The overestimation of safety redundancy is quantified when geometric variations are neglected. The results indicate that incorporating field-measured point cloud data into structural simulations can improve the geometric realism of tunnel-lining assessment and assist in identifying potential high-risk zones. Full article

Mine disasters require urgent lifeline setup in confined tunnels, but manual rescue in unstable accident zones carries huge safety risks. Coal mine rescue robots (CMRRs) have become key equipment to replace manual rescue. However, traditional remote-controlled CMRRs suffer from low autonomy and weak environmental perception capability, which have become critical bottlenecks for field application. As an emerging technology in the mining field, digital twin enables high-precision virtual-real mapping and on-site operation guidance, providing a novel solution to the above problems. To realize autonomous navigation and digital twin visualization of the CMRR, this paper first carries out targeted hardware retrofits on the CMRR platform, upgrades environmental perception, communication transmission and motion control modules, and lays a solid hardware foundation for subsequent algorithm design and system implementation. Aiming at the complex post-disaster underground environment, a digital twin-integrated CMRR system is constructed. For intelligent autonomous navigation, this study investigates a 3D point cloud–based autonomous navigation framework and proposes a slope-fitting method as well as a maximum arrival probability obstacle avoidance method based on Bézier curve trajectories. For environmental visualization, a digital twin interactive interface is built to monitor gas and other environmental parameters in real time, and accurately reconstruct underground roadway structures based on point cloud data. This design not only ensures the robot’s autonomous obstacle avoidance but also helps rescuers grasp underground conditions in advance. Field tests in a simulated post-disaster mine with complex terrain show that the system can stably complete autonomous navigation tasks, maintain stable motion control under dynamic interference, and provide accurate and reliable environmental data for rescue decisions, verifying its feasibility and effectiveness in harsh mine rescue scenarios. Full article

The impact of short-distance lateral shield tunneling threatens the safety of operational high-speed railways (HSRs). To address the engineering challenge of “how to select isolation pile density under fixed cost constraints,” this study focuses on the Xi’an Metro shield tunnel section passing laterally adjacent to the Daxi and Zhengxi Passenger Dedicated Lines. Under the constraint of identical total economic costs, two isolation pile schemes—low-density and high-density—were established to investigate the control patterns of different densities on HSR bridge piles and surrounding ground surface deformation. A three-dimensional (3D) numerical model was developed for the lateral shield tunneling process. Combined with field-measured data, numerical simulations were conducted for corresponding construction stages to analyze the disturbance effects of shield tunneling on HSR piers and the surrounding ground, as well as the deformation restraint performance of isolation piles. The results indicate that the high-density isolation pile scheme (pile spacing: 2.0 m; pile length: 22 m) provides superior control compared to the low-density scheme (pile spacing: 4 m; pile length: 28 m). Following single- and double-track excavation, the vertical displacement of HSR piers was reduced by 0.6 mm and 1.1 mm, respectively—a reduction of 40–74%. Furthermore, the pier displacement along the depth direction shifted from non-uniform to relatively uniform. The difference in surface settlement between the two schemes was only 0.2 mm, suggesting that isolation pile density has a marginal impact on ground deformation. The horizontal displacement of high-density isolation piles stabilized at 1.7–1.9 mm, with vertical heave ranging from 1.2 to 1.4 mm. The lateral displacement profile exhibited a regular “double-C outward expansion” shape, which is better suited to the characteristics of water-rich sand layers. Initial excavation causes significant disturbance to the original strata, necessitating enhanced stress field protection measures. The high-density scheme is recommended for engineering applications, as it achieves optimal control of bridge pile deformation under cost constraints and meets regulatory specifications. Full article