Search Results (88)

Urban rail transit projects situated in Quaternary deposits are progressively influenced by ultra-shallow gas. During the investigation and construction phases, this gas may instigate gas outbursts, combustion, explosions, stratum disturbances, and secondary ground deformations. To transparently and applicably identify the most crucial disaster-inducing factors in engineering practice, this research constructs a hierarchical risk factor evaluation framework for shallow gas hazards during the investigation stage of rail transit engineering. Initially, candidate indicators were screened via a literature review of shallow gas hazard studies and metro engineering reports. Subsequently, by employing the AHP, four first-level indicators and fifteen second-level indicators were compared and weighted. The findings indicate that shallow gas pressure, methane content per ton of soil, and the occurrence form of shallow gas are the three most influential factors, with comprehensive weights of 0.2735, 0.2319, and 0.1113 respectively. A metro tunnel case in Guangdong Province was then utilized to illustrate how the ranked indicators can guide the verification of suspected zones, section-based hazard discrimination, and the planning of controlled gas release. In comparison with existing studies that concentrate on descriptive disaster phenomena or single-factor analyses, the contributions of this study are threefold. Firstly, it offers a structured indicator system specifically tailored to Quaternary shallow gas in rail transit engineering. Secondly, it makes the expert-based weighting process explicit. Thirdly, it links the ranking results to practical investigation and prevention decisions. This framework is intended as a preliminary engineering decision support tool rather than a substitute for detailed predictive modeling or large-sample statistical validation. Full article

In hot and humid regions, urban underground utility tunnels are susceptible to high temperature and humidity due to moist inlet air, cable heat dissipation, and limited ventilation jointly affecting the internal environment. To address this issue, an alternating ventilation strategy, in which fan operation is periodically reversed to switch between air supply and exhaust, is proposed. Compared to conventional mechanical ventilation, this strategy overcomes the constraints of unidirectional airflow and mitigates thermal and humidity stratification, with low retrofit requirements and good adaptability. Ventilation performance was evaluated using non-guarantee rates for temperature and relative humidity, i.e., the ratio of the number of measurement points where the temperature/relative humidity exceeds 40 °C/65% to the total number of measurement points in the utility tunnel (TNGR and RHNGR), non-uniformity coefficients (K_T and K_RH), and mean temperature (T_m). The alternating mode outperformed the conventional mode, reducing TNGR by 6.0% and Tm by 0.3 °C while improving temperature and humidity distributions and lowering cable temperatures. Although the reduction in T_m appears modest, it is practically meaningful because it helps weaken thermal stratification and local overheating, improves cable operating conditions, and may reduce the need for high-airflow operation when tunnel temperatures approach the permissible limit. Response surface methodology was further used to optimize the alternating ventilation parameters, indicating that the recommended fan commutation frequency is 2 under different inlet air temperatures. CFD validation confirmed the effectiveness of the optimized scheme. At an inlet air temperature of 35 °C, KRH decreased from 11.9% to 11.0% and Tm decreased from 37.5 °C to 36.9 °C. Full article

This study provides a comparative performance evaluation of commercial Precise Point Positioning Real-Time Kinematic (PPP-RTK) and public Network RTK (NRTK) services for vehicle-based positioning in urban and suburban environments. Using low-cost u-blox ZED-F9 receivers, the research assesses the accuracy, availability, and robustness of the u-blox PointPerfect service against a regional NRTK network across diverse real-world scenarios, including high-speed highway conditions and signal-challenging urban corridors. The experimental framework utilizes a rigid-bar setup for high-precision ground-truth validation and incorporates an independent vertical accuracy assessment against a LiDAR-derived digital elevation model (DEM). The results demonstrate that all tested configurations achieve decimeter-level accuracy. Notably, the integration of PPP-RTK with an inertial measurement unit (IMU) delivers performance nearly equivalent to NRTK, effectively mitigating vertical biases and ensuring positioning continuity in GNSS-denied areas such as tunnels. These results confirm that low-cost GNSS solutions, when paired with modern augmentation services and IMU integration, can meet the stringent demands of mass-market applications like Cooperative Intelligent Transport Systems (C-ITS) and autonomous mobility. Full article

With the increasing density of urban underground space development, the soil disturbance induced by large-section rectangular pipe jacking poses a significant threat to the safety of underlying subway tunnels. Taking the Lihe Road utility tunnel project in Wuhan, which crosses over Metro Line 4, as the engineering background, a three-dimensional finite element (FE) model was established using Midas GTS NX to simulate the entire pipe jacking process. Field monitoring data from caisson excavation, ground improvement, pipe jacking, and backfill grouting were introduced for validation, enabling a systematic investigation of the influence mechanism of pipe jacking on existing tunnels. In the numerical simulation, the modified Mohr–Coulomb constitutive model was adopted for the soil, and a “portal-type” reinforcement system was introduced. The pipe jacking process was simulated equivalently with a 1.2 m advance per cycle. The results indicate that the ground settlement induced by pipe jacking exhibits a stage-wise accumulation pattern and eventually develops into a stable settlement trough. The vertical settlement of the tunnel follows an evolutionary law of “early occurrence in the near field, delayed response in the far field, and final convergence,” with peak settlements of 2.44 mm and 2.53 mm for the left and right lines, respectively. Ground improvement significantly mitigates soil deformation, reducing the maximum surface settlement from 45.5 mm to 11.1 mm, decreasing the tunnel’s peak vertical settlement by 37%, and reducing horizontal displacement by 64%, thereby effectively suppressing lateral soil extrusion. The proposed closed-loop analysis method of “numerical simulation–monitoring validation–measure evaluation” reveals the spatiotemporal evolution law of soil–tunnel interaction during pipe jacking construction and provides valuable reference for risk control in similar engineering projects. Full article

Underground utility tunnels face corrosion, cracks, and leakage after long-term use, endangering urban safety. Traditional methods have strong subjectivity, high miss rates, and poor real-time performance, failing refined management needs. This paper proposes an attention-enhanced YOLOv11 rather than YOLOv10 because its C3k2 backbone and dynamic anchor head already surpass YOLOv10 by 1.8% mAP for pipeline defect detection in utility tunnels. It uses homomorphic filtering to improve low-light image quality; replaces the last two C3k2 modules of the original YOLOv11 with a Multi-Scale Feature Aggregation Module to capture micro-cracks via expanded receptive fields; introduces a bidirectional weighted feature pyramid network in the neck (with C2PSA/BRA attention) for cross-scale feature fusion and background suppression, which yields both fine-grained micro-crack sensitivity and global false-target suppression; and adopts DIoU loss in the detection head to reduce slender defect localization errors. Experiments on 5000 utility tunnel defect images show the improved algorithm achieves 93.2% precision, 92.4% recall, and 92.6% mAP—outperforming the original YOLOv11, Faster R-CNN, and YOLOv5. Ablation experiments confirm module effectiveness, cutting relative error by 75% compared with the baseline. This algorithm can accurately identify multiple types of defects in complex utility tunnel environments, providing technical support for the safe and efficient operation and maintenance of urban infrastructure. Full article

To improve the accuracy of cable temperature anomaly prediction and ensure the reliability of urban distribution networks, this paper proposes a multi-scale spatiotemporal model called MSST-Net (MSST-Net) for medium-voltage power cables in underground utility tunnels. The model addresses the multi-scale temporal dynamics and spatial correlations inherent in cable thermal behavior. Based on the monthly periodicity of cable temperature data, we preprocessed monitoring data from the KN1 and KN2 sections (medium-voltage power cable segments) of Guangzhou’s underground utility tunnel from 2023 to 2024, using the Isolation Forest algorithm to remove outliers, applying Min-Max normalization to eliminate dimensional differences, and selecting five key features including current load, voltage, and ambient temperature using Spearman’s correlation coefficient. Subsequently, we designed a multi-scale dilated causal convolutional module (DC-CNN) to capture local features, combined with a spatiotemporal dual-path Transformer to model long-range dependencies, and introduced relative position encoding to enhance temporal perception. The Sparrow Search Algorithm (SSA) was employed for global optimization of hyperparameters. Compared with five other mainstream algorithms, MSST-Net demonstrated higher accuracy in cable temperature prediction for power cables in the KN1 and KN2 sections of Guangzhou’s underground utility tunnel, achieving a coefficient of determination (R²), mean absolute error (MAE), and root mean square error (RMSE) of 0.942, 0.442 °C, and 0.596 °C, respectively. Compared to the basic Transformer model, the root mean square error of cable temperature was reduced by 0.425 °C. This model exhibits high accuracy in time series prediction and provides a reference for accurate short- and medium-term temperature forecasting of medium-voltage power cables in urban underground utility tunnels. Full article

Driven by the advancement of the global blue economy strategy and the rapid expansion of urbanization into deep underground spaces, the scale of critical infrastructure, ranging from cross-sea bridges and undersea tunnels to offshore wind farms and deep-buried utility tunnels, has reached unprecedented levels [...] Full article

Tunnels have significantly expanded human activity spaces and alleviated urban congestion and environmental pollution on the surface. However, fires and associated smoke propagation in tunnels pose common and critical challenges in underground space utilization. Previous studies have primarily focused on smoke control under standard atmospheric conditions, emphasizing isolated parameters such as jet velocity or heat release rate (HRR), while overlooking key factors like environmental pressure and fire source proximity that influence smoke buoyancy and containment efficacy. One of the key problems remains unsolved: the comprehensive mechanisms governing transverse air curtain performance in variable-pressure and proximity scenarios. This study utilized Fire Dynamics Simulator (FDS6.7.1) software to conduct numerical simulations, aiming to elucidate the underlying incentives and explore the phenomena of smoke–thermal interactions. The analysis systematically evaluates the influence of four critical parameters: HRR (1–15 MW), fire-to-curtain distance (5–95 m), air curtain jet velocity (6–16 m/s), and ambient pressure (40–140 kPa). Results show that (1) jet velocity emerges as the dominant factor, with exponential enhancement in thermal containment efficiency at velocities above 10 m/s due to intensified shear forces; (2) escalating HRR weakens isolation, leading to disproportionate downstream temperature rises and diminished efficacy; (3) fire proximity within 10 m disrupts curtain integrity via high-momentum smoke impingement, amplifying thermal gradients; and (4) elevated ambient pressure dampens smoke buoyancy while augmenting air curtain momentum, yielding improved containment efficiency and reduced temperatures. This paper is helpful for the design and operation of thermal applications in underground infrastructures, providing predictive models for optimized smoke control systems. The contour maps reveal the field-distribution trends and highlight the significant influence of the air curtain and key governing parameters on the thermal field and smoke control performance. This work delivers pivotal theoretical and practical insights into the advanced design and optimization of aerodynamic smoke control systems in tunnel safety engineering Full article

Urban air mobility operations, such as flying Uncrewed Aerial Vehicles (UAVs) and small passenger aircraft in and around cities, will be inherently susceptible to the turbulent wind conditions in urban environments. Therefore, understanding UAM aircraft performance under microscale wind disturbances is critical. Gaining such insight is non-trivial due to the lack of sufficient UAM aircraft operational data and the complexities involved in flight testing UAM aircraft. A viable solution to overcome this hindrance is through simulation-based flight testing, data collection, and performance assessment. To support this effort, the present paper establishes a custom Stochastic microscale Wind Model (SWM) capable of efficiently generating high-resolution, spatio-temporally varying urban wind fields. The SWM is validated against wind tunnel test data, and subsequently, the findings are employed to guide targeted refinements of urban wake simulation. Furthermore, to incorporate realistic atmospheric conditions and demonstrate the ability to generate location-specific wind fields, the SWM is coupled with the mesoscale Weather Research and Forecasting (WRF) model. This integrated approach is demonstrated through a case study focused on a potential vertiport site in Milan, Italy, illustrating its utility for assessing operational area-specific UAM aircraft performance and vertiport emplacement. Full article

With the rise of the low-altitude economy, there is growing demand for performance and safety evaluation of logistics drones and urban aircraft operating in complex turbulent environments. Conventional wind tunnels, however, face challenges in simulating the non-uniform wind fields characteristic of urban low-altitude conditions, such as building wake flows, street canyon winds, and tornadoes. To address this gap, this study proposes a novel simulation device for low-altitude complex wind fields, which utilizes multi-fan coordinated control technology integrated with jet fan arrays, pressure-stabilizing chambers, and swirl fan systems to dynamically replicate horizontal flows, vertical flows, and specialized wind patterns. Numerical simulations using Ansys Icepak validate the effectiveness of the design: the optimized horizontal flow field achieves a wind speed of 83 m/s with a turbulence intensity ranging from 5% to 20%; the gust mode attains rapid response within 3 s; and high-fidelity simulations are achieved for wind shear, tornadoes (with a maximum tangential wind speed of 50 m/s), and downbursts (with a central vertical jet velocity of 40 m/s). Furthermore, for typical urban wind environments such as alley winds and intersection flows, the study elucidates the characteristics of abrupt wind speed variations and vortex dynamics induced by building obstructions. This research provides a new perspective and a potential technical pathway for testing low-altitude aircraft, assessing urban wind environments, and supporting related studies, thereby contributing to the advancement of complex wind field simulation technologies. Full article

Timing and time synchronization are critical capabilities of Global Navigation Satellite Systems (GNSSs), but their performance deteriorates significantly in challenging environments like urban canyons and tunnels. To address this issue, this paper proposes the Distributed Sensor Time Synchronization architecture (DSTS), a novel architecture integrating Bayesian filtering with deep reinforcement learning. DSTS utilizes Bayesian filtering to fuse Time-of-Flight (ToF) measurements with Channel Impulse Response features for real-time compensation of non-linear errors and accurate path state prediction. Concurrently, the Deep Deterministic Policy Gradient (DDPG) algorithm trains each node into an intelligent agent that dynamically learns optimal synchronization weights based on local information like neighbor clock stability and link quality. This allows the architecture to adaptively amplify reliable nodes while mitigating the negative effects of unstable peers and adverse channels, ensuring high accuracy and availability. Simulation experiments based on a real-world UWB dataset demonstrate the architecture’s exceptional performance. The Bayesian filtering module effectively mitigates non-linear errors, reducing the standard deviation of ToF measurements in NLOS scenarios by up to 51.6% (over 41.2% consistently) while achieving high path state prediction accuracy (>85% static, >95% simulated dynamic). In simulated dynamic and heterogeneous networks, the DDPG algorithm achieves a synchronization accuracy better than traditional average-consensus algorithms, ultimately reaching a frequency and phase precision of $4\times {10}^{-10}$ and $5\times {10}^{-10}$ s, respectively. Full article

Small-diameter tunnels play a crucial role in urban infrastructure, managing functions such as sewage, rainwater, and electrical systems. However, the safety assessment of small-diameter tunnel shield construction faces difficulties due to unclear physical relationships and the limitations of traditional physical information models in predicting complex risks. To address this issue, the integration of physical information with data-driven analysis methods offers a promising approach. Combining these advantages, a hybrid model was proposed to establish a robust construction safety risk evaluation framework for small-diameter tunnels under geological conditions. The presently proposed method mainly consists of a clustering of risk factors, physical information stratification, and risk early warning. Specifically, the K-means clustering method optimized by the Harris Hawks algorithm was used for risk identification, the Analytic Hierarchy Process was used for risk analysis, and the physical information output from the risk analysis was used for risk warning. A case study was produced, utilizing the proposed hybrid model for the Wuhan East Lake Deep Tunnel project. The results show the risk transfer path through inadequate personnel safety awareness and protection, mechanical system failures and installation deviations, substandard material quality and improper stacking, outdated or immature construction technology, and environmental risks. Full article

Utility tunnels concentrate various important urban engineering pipelines within a shared underground space, which poses significant fire risks, particularly from cable fires. In this study, a full-scale fire experiment was conducted to investigate the temperature distribution characteristics of cable fires in utility tunnels, along with the effects of spray intensity, cable fullness, and longitudinal ventilation on the extinguishing efficiency of a high-pressure water mist fire extinguishing system (HWMFES). The results show that the maximum heating area of a cable fire in a utility tunnel is localized to the three cable trays nearest to and directly above the fire source, with a peak temperature of 825 °C, while the impact on other areas is negligible. Increasing the spray intensity from 0.7 to 1.0 L/(min·m²) reduced the time required to lower temperatures to 50 °C by 40.8%, while reducing cable fullness from 12 to 6 cables per tray shortened extinguishing time by 22.5%. Additionally, applying a ventilation speed of 2 m/s enhanced cooling efficiency, reducing the time to reach 50 °C by 67.5% compared to still air conditions. These findings provide practical insights and data support for optimizing the design and application of HWMFES in enhancing fire safety in utility tunnels. Full article

To ensure the safe and reliable operation of hydrogen-blended natural gas (HBNG) pipelines in urban utility tunnels, this study conducted a comprehensive CFD simulation of the leakage and diffusion characteristics of HBNG in confined underground environments. Utilizing ANSYS CFD software (2024R1), a three-dimensional physical model of a utility tunnel was developed to investigate the influence of key parameters, such as leak sizes (4 mm, 6 mm, and 8 mm)—selected based on common small-orifice defects in utility tunnel pipelines (e.g., corrosion-induced pinholes and minor mechanical damage) and hydrogen blending ratios (HBR) ranging from 0% to 20%—a range aligned with current global HBNG demonstration projects (e.g., China’s “Medium-Term and Long-Term Plan for Hydrogen Energy Industry Development”) and ISO standards prioritizing 20% as a technically feasible upper limit for existing infrastructure, on HBNG diffusion behavior. The study also evaluated the adequacy of current accident ventilation standards. The findings show that as leak orifice size increases, the diffusion range of HBNG expands significantly, with a 31.5% increase in diffusion distance and an 18.5% reduction in alarm time as the orifice diameter grows from 4 mm to 8 mm. Furthermore, hydrogen blending accelerates gas diffusion, with each 5% increase in HBR shortening the alarm time by approximately 1.6 s and increasing equilibrium concentrations by 0.4% vol. The current ventilation standard (12 h⁻¹) was found to be insufficient to suppress concentrations below the 1% safety threshold when the HBR exceeds 5% or the orifice diameter exceeds 4 mm—thresholds derived from simulations showing that, under 12 h⁻¹ ventilation, equilibrium concentrations exceed the 1% safety threshold under these conditions. To address these gaps, this study proposes an adaptive ventilation strategy that uses variable-frequency drives to adjust ventilation rates in real time based on sensor feedback of gas concentrations, ensuring alignment with leakage conditions, thereby ensuring enhanced safety. These results provide crucial theoretical insights for the safe design of HBNG pipelines and ventilation optimization in utility tunnels. Full article

Circular deep excavations, characterized by their symmetrical geometry, are commonly employed in constructing foundations for large-span suspension bridges and as launching shafts for shield tunneling. However, the mechanical behavior of such excavations under asymmetric surface surcharge remains inadequately understood due to a paucity of relevant investigations. This study addresses this knowledge gap by establishing a three-dimensional finite element model (3D-FEA) based on the anchor deep excavation project of a specific bridge. The model is utilized to investigate the influence of asymmetric surcharge on the forces and deformations within the supporting structure. The results show that both the internal force and displacement cloud diagrams of the support structure exhibit asymmetric characteristics. The distribution of displacement and internal forces has spatial effects, and the maximum values all occur in the areas where asymmetric loads are applied. The maximum values of the displacement, axial force, and shear force of underground continuous walls increase with the increase in the excavation depth. The total displacement curves all show the feature of a “bulging belly”. The maximum displacement is 13.3 mm. The axial force is mainly compression, with a maximum value of −9514 kN/m. The maximum positive and negative values of the shear force are 333 kN/m and −705 kN/m, respectively. The bending moment diagram of different monitoring points shows the characteristics of “bow knot”. The maximum values of the positive bending moment and negative bending moment are 1509.4 kN·m/m and −2394.3 kN·m/m, respectively. The axial force of the ring beam is mainly compression, with a maximum value of −5360 kN, which occurs in ring beams 3, 4, and 5. The displacement cloud diagram of the support structure under symmetrical loads shows symmetrical characteristics. Under different load conditions, the displacement curve of the diaphragm wall shows the characteristics of “bulge belly”. The forms of loads with displacements from largest to smallest at the same position are as follows: asymmetric loads, symmetrical loads, and no loads. These findings provide valuable insights for optimizing the structural design of similar deep excavation projects and contribute to promoting sustainable urban underground development. Full article