Search Results (114)

Small-scale excavations with depths of approximately 1 to 3 m are widely conducted for purposes such as the repair of underground pipelines. In confined construction spaces, earth-retaining systems consisting of lightweight sheet-piles with struts and walers are frequently used. However, comprehensive investigations of the influence of ground conditions on member forces have not yet been conducted. Furthermore, since these temporary structures are generally not designed with seismic considerations, they may suffer damage during earthquakes depending on the soil conditions. Accordingly, this study conducted a comprehensive parametric numerical investigation to evaluate how differences in soil type, such as sandy and cohesive soils, and loading conditions during excavation and earthquake loading affect the internal forces in the supporting members. Excavation analyses using PLAXIS 3D confirmed that as the soil strength parameters (cohesion and internal friction angle) decreased, the demand on the supporting members increased and larger internal forces developed. Dynamic analyses using LIQCA 3D revealed complex behavior in which (i) earth pressure acting on the wall generated compressive forces in the struts, (ii) lateral deformation of the excavation face reduced axial forces in the struts, and (iii) when the ground liquefied, it exhibited a vibration-isolation effect, and the vibration components generated in the structural members became smaller. Full article

Excessive cathodic polarization of underground stainless steel structures results in hydrogen evolution, increasing the risk of hydrogen embrittlement and the disbonding of protective coatings from the structure’s surface. This study was conducted to determine the critical potential and critical cathodic protection current density at which hydrogen evolution occurs on the surfaces of stainless steel grades 1.4301, 1.4401, 1.4125, and 1.4512, and, for comparison, on carbon steel S235. The tests were carried out in an aqueous solution of synthetic (artificial) soil and in a soil filtrate prepared from a soil sample taken in the vicinity of an existing underground gas pipeline connection with stainless steel fittings. The tests showed that the higher the chromium content in the stainless steel was, the lower (more negative) the hydrogen evolution potential was. In an artificial soil environment, the values of this potential ranged from −1105 mV to −1175 mV vs. copper sulphate electrode (CSE) for steels 1.4301, 1.4401, and 1.4125, which contain more than 16% of chromium. For steel 1.4512, containing 12% of chromium, the hydrogen evolution potential was −1050 mV. For comparison, for S235 carbon steel, the hydrogen evolution potential was −1135 mV. The critical cathodic protection current density ranged from 0.30 A/m² to 0.38 A/m² for all tested stainless steels, whilst for S235 steel, this value was higher, equal to 0.65 A/m². The results obtained indicate that applying the commonly accepted potential criterion for cathodic protection for carbon steels (i.e., polarization to a potential in the range from −0.85 V to −1.1 V vs. CSE) poses no risk of causing excessive cathodic polarization of stainless steel. This is important for the design and operation of cathodic protection systems for complex structures containing galvanically connected carbon steel and stainless steel components. Full article

The accurate location of leakage points is a key part of underground gas prevention. To solve the problem of low positioning accuracy for gas extraction pipeline leakage, the gas extraction pipeline leakage experimental system was built, and the multi-source collaborative leakage localization method based on Stacking learning was proposed. The results showed that the Stacking–LSSVM–Elman–DBN (S-L-E-D) model with pressure–flow collaborative input achieved the best localization performance, with an accuracy of 0.932, Root Mean Square Error (RMSE) of 0.053, Mean Absolute Percentage Error (MAPE) of 0.082, Theil Inequality Coefficient (TIC) of 0.056, and a distance error below 1 m. Compared with a single-parameter input, the collaborative pressure–flow input improved the localization accuracy by more than 10%, while the RMSE and MAPE decreased by 39.0% and 37.4%, respectively. Under monitoring point fault conditions, the localization accuracies of monitoring points 1, 4, and 5 were 0.884, 0.891, and 0.881, respectively, while the dual-fault condition of monitoring points 1 and 4 still maintained an accuracy of 0.861. The study provides a feasible multi-source collaborative learning framework for leakage localization in gas extraction pipelines and offers a methodological reference for improving leakage monitoring and early warning. Full article

The article deals with non-destructive methodologies for assessing and preventing corrosion of polymer-coated underground pipelines, advanced corrosion-barrier coating systems based on extruded three-layer high-density polyethylene (3LPE), corrosion control strategies for buried oil, gas, and water transmission infrastructures, and mechanisms and engineering approaches for corrosion prevention and mitigation. The quality assurance of newly polymer-coated underground pipelines, following construction (installation and backfilling), is vital for evaluating the polymer coating quality state and the efficiency of passive anti-corrosion protection, aimed at reducing corrosion risks and prolonging the pipeline’s service life. The evaluation relies on the coating average specific electrical resistance and the presence of coating defects (number, total area, and distribution) of inspected pipeline sections. In this study, based on extensive real data obtained from testing of newly installed underground water and oil/gas pipeline networks (60 projects with a total pipeline length of 260 km) with various technical characteristics, Drainage Test and DCVG (Direct Current Voltage Gradient) complementary non-destructive indirect methods have been investigated to determine the quality level and identify the location and severity of defects in polyolefin (polyethylene) coatings. The novel concepts and criteria were defined: the quantitative criteria for average specific electrical resistance are established; in addition, a new parameter related to the specific coating defects ratio is introduced, which has been shown to correlate with the criteria for the average specific electrical resistance of the polymer coating and consumed electrical current; finally, following DCVG measurements of the 3LPE coating system, a novel degree of relative defect sizes (%IR) for repairs has been suggested. The innovative and comprehensive approach can support the efforts of regulatory quality assurance, design, maintenance, safety, and research communities to ensure the long-term integrity and sustainability of underground polymer-coated steel pipelines. Full article

Recognizing human actions from static images in complex industrial environments remains challenging due to insufficient feature representation and high computational complexity. This issue is particularly critical in power-grid safety monitoring, where improper worker postures (e.g., bending, climbing, falling) can lead to severe accidents and personal injuries, necessitating automated monitoring systems that operate reliably on resource-constrained edge devices. This study proposes a bio-inspired lightweight recognition framework that integrates an improved YOLO-Pose model with a gated recurrent unit (GRU) network. The scientific motivation is grounded in the observation that the human musculoskeletal system achieves highly efficient motion perception through three key mechanisms: hierarchical muscle coordination providing intrinsic rotation invariance, proprioceptive feedback enabling real-time error correction, and selective neural gating reducing redundant information transmission. These biological principles directly inspire our technical contributions: polar-coordinate encoding provides rotation invariance, three-stage filtering mimics proprioceptive feedback, and GRU gating mirrors selective information propagation. Unlike prior approaches that treat pose-based action recognition as a generic computer vision problem, this work explicitly incorporates anatomical structural constraints into the computational pipeline. The framework addresses three research gaps: (1) existing methods lack biomechanically derived invariance properties; (2) GCN-based approaches use fixed topologies that fail to adapt to occlusion patterns; (3) the trade-off between model complexity and accuracy remains unsatisfactory for edge deployment. Experiments on the self-constructed SKPose dataset demonstrate that the proposed method achieves 95.04% accuracy, outperforming ST-GCN by 3.67 percentage points and 2s-AGCN by 1.94 percentage points, with an inference speed of 48 FPS on 8.7 M parameters in underground power-grid environments and provides practical support for biomimetic perception systems and industrial safety monitoring. Full article

The rapid inspection of urban road hazards, such as subsurface voids and pipeline damage, demands high efficiency and precision in detection technology. Conventional Ground Penetrating Radar (GPR) systems often face limitations in urban environments, including slow survey speeds, poor channel scalability, and the trade-off between shallow resolution and deep penetration. The proposed system integrates a dual-band antenna array (200 MHz and 400 MHz) to resolve the classical resolution–penetration trade-off, simultaneously capturing high-resolution shallow data and achieving deep subsurface penetration in a single pass. To overcome the sampling rate bottleneck inherent in low-cost microcontrollers, a custom Time-Division Step Multiplexing (TDSM) protocol extends the equivalent sampling period to 0.38 µs across 24 parallel channels while maintaining a 200 kHz pulse repetition rate—enabling real-time data streaming at vehicle speeds up to 70 km/h with 5 cm trace spacing. This capability directly addresses the critical challenge of traffic disruption on urban arterials caused by conventional slow-speed GPR surveys. Complementing this, a master-slave FPGA-MCU hierarchical architecture provides seamless channel scalability from 24 to 36 channels, adapting to diverse swath width requirements without hardware redesign. Laboratory physics model experiments demonstrate a penetration depth exceeding 3 m after convolutional sparse fusion of the dual-band data, covering the typical burial depth of urban utilities. This study provides a deployable high-resolution underground detection solution for rapid urban infrastructure surveys and emergency disease detection by breaking the traditional constraints of channel number, sampling rate, and detection speed, significantly reducing interference with urban main traffic. Full article

Underground utilities form an essential part of urban infrastructure, yet their importance often becomes apparent only when service disruptions occur. Excavation activities for maintenance, relocation, or new construction carry considerable risks, including utility strikes, project delays, worker injuries, and even fatalities. These risks are largely driven by incomplete or inaccurate information about the location, depth, or material properties of buried utilities. To address this challenge, this study proposes a comprehensive Building Information Modeling (BIM)-based framework for managing underground utilities throughout their lifecycles. The framework is structured into five key stages: data acquisition, data processing, modeling, system application, and data updating. A highway project was used as a case study to validate the proposed approach. The study involved the integrated modeling and visualization of the highway corridor, underground gas pipelines, and overground high-voltage transmission pylons using Autodesk Civil 3D, InfraWorks, and Navisworks. The developed model and workflow were subsequently reviewed with the client department. Application of the framework to a 5 km highway corridor identified five utility-road conflict points (three subsurface gas pipeline intersections and two overground pylon encroachments) that were not detectable from existing 2D records. Expert review by the client department confirmed that the BIM-based visualization and 4D simulation improved construction planning clarity and supported proactive utility relocation decisions. By simplifying information workflows and enabling collaboration among stakeholders, the proposed framework demonstrates strong potential to improve excavation safety, enhance decision-making, and support the wider adoption of BIM for underground utility management. Full article

Mixed steel/polyethylene gas distribution pipelines are increasingly used in congested urban environments where conventional layouts are restricted by existing underground utilities, safety constraints, and site-specific construction conditions. In such systems, buried steel transition sections may become particularly vulnerable to electrical perturbation and corrosion, especially when installed near electrified transport infrastructure. This paper presents a field case study on a recently installed mixed steel/polyethylene gas distribution pipeline located on Lunca Street, Petroșani, Romania, approximately parallel to an electrified railway. Electrical and electrochemical investigations were carried out eight months after installation and included 24 h monitoring of pipe-to-soil potential versus Cu/CuSO₄, 24 h monitoring of alternating current pipe-to-soil voltage, mixed alternating current and direct current signal visualization, and coating insulation resistance measurements. The results showed that alternating current pipe-to-soil voltage was present at all monitored points, with weighted mean values ranging from 0.41 to 1.23 Vrms, while pipe-to-soil potential values ranged from −0.120 to −0.238 V versus Cu/CuSO₄. Although the measured average coating insulation resistance remained relatively high, the combined electrical and electrochemical data indicate that alternating current interference associated with the nearby electrified railway is the most plausible dominant contributing source of the recorded electrical perturbation. Within the analyzed site perimeter, no other nearby electrical infrastructures with comparable interference potential were identified. The highest alternating-current exposure and the least favorable electrochemical values were recorded on the longer metallic segment, showing that metallic length and local configuration strongly influenced the severity of the effect. A mitigation strategy based on polarized electrical decoupling and dedicated grounding is proposed as a practical means of improving electrical safety and reducing corrosion risk in the exposed and buried steel sections. Full article

Urban underground sewage pipelines often suffer from defects such as cracks, irregular joint misalignment, and stratified sedimentation blockages, which may lead to pipeline bursts, sewage overflow, and water pollution. Timely detection of abnormal defects in sewage pipelines is critical to ensuring public health and environmental sustainability. Vision-based sewage pipeline defect detection plays a crucial role in modern urban wastewater treatment systems. However, it still faces challenges such as limited feature extraction capabilities, insufficient multi-scale defect characterization, and poor positioning stability when dealing with low-contrast images and in environments with severe background interference. To address this issue, this study proposes an enhanced SAW-YOLOv8l model that integrates RT-DETR (real-time detection Transformer) with CNN (convolutional neural network) architecture. First, a C2f_SCA module improves the long-distance feature extraction capability and localization precision. Second, an AIFI-PRBN module enhances global feature correlation through attention-mechanism-based intra-scale feature interaction and reduces computational complexity using lightweight techniques. Finally, an adaptive dynamic weighted loss function based on Wise-IoU (weighted intersection over union) further improves training convergence and robustness by balancing the gradient distribution of samples. Experiments on a mixed dataset comprising Sewer-ML and industrial images demonstrate that the SAW-YOLOv8l model achieved mAP@0.5 of 86.2% and precision of 84.4%, which were improvements of 2.4% and 6.6% respectively over the baseline model, significantly enhancing the detection performance of abnormal defects in sewage pipelines. Full article

We propose and experimentally validate an automatic urban water leakage detection architecture that leverages dark fiber links already deployed in telecommunication networks in underground conduits in the vicinity of water pipelines. The sensing stage relies on a differential-phase coherent optical time-domain reflectometry interrogator enhanced with optical pulse compression to improve sensitivity. Building on this vibration acquisition stage, automatic leakage detection algorithms are implemented by searching for leak-induced activity in the frequency domain, which is well suited to revealing leakage-related features. After acquiring a baseline calibration to characterize normal-condition vibrations at each sensing position, leakage candidates are identified by comparing distribution-based metrics computed over multiple measurements against the corresponding baseline statistics. Two automatic leakage detection strategies are developed. First, low-complexity feature-based metrics are implemented, enabling continuous monitoring with minimal computational requirements. Second, an autoencoder-based anomaly detection technique is introduced, which also relies on location-specific normal-condition calibration but reduces the dependence on prior knowledge of the expected leakage vibration signatures. A real-world field trial on an urban network demonstrates reliable detection and localization using controlled leak events generated in the field, with measurements performed over a 17 km sensing fiber and an effective spatial resolution of 2.6 m. Benchmarking against a commercial punctual electro-acoustic leak detector yields consistent trends. Overall, the proposed system could complement existing technologies by enabling automated, continuous city-scale monitoring over already deployed dark fiber infrastructure. Full article

Long-distance coal gangue slurry transportation pipelines are critical components of underground coal mine green backfilling systems, yet blockage failures severely threaten their safe and efficient operation. Existing distributed acoustic sensing (DAS)-based monitoring methods for such pipelines suffer from three key limitations: insufficient fixed-point quantitative accuracy, lack of verified blockage-specific characteristic indicators, and limited quantitative severity assessment capability. To address these gaps, this paper proposes a novel feature-level fusion monitoring method integrating DAS, fiber Bragg grating (FBG), and piezoelectric accelerometers for accurate blockage identification and quantitative evaluation in coal gangue slurry pipelines. A slurry pipeline circulation test platform with gradient blockage simulation (0% to 76.42%) and a synchronous multi-sensor monitoring system were developed. Through multi-domain signal analysis, three blockage-correlated characteristic frequencies were identified and cross-validated by synchronous multi-sensor data: 1.5 Hz (system background vibration), 26 Hz (blockage-induced fluid–structure resonance, verified by the Euler–Bernoulli beam theory with a theoretical value of 25.7 Hz), and 174 Hz (transient flow impact). The DAS phase change rate exhibited a unimodal nonlinear response to blockage degree, with the peak occurring at 40.94% blockage. On this basis, a sine-fitting quantitative inversion model was developed, achieving a high goodness of fit (R² = 0.985), and leave-one-out cross-validation confirmed its excellent robustness with a mean relative prediction error of 3.77%. Finally, a collaborative monitoring framework was built to fully leverage the complementary advantages of each sensor, realizing full-process blockage monitoring covering global blockage localization, precise quantitative severity calibration, and high-frequency transient risk early warning. The proposed method provides a robust experimental and technical foundation for real-time early warning, precise localization, and quantitative diagnosis of long-distance slurry pipeline blockages and holds important engineering application value for the safe and efficient operation of underground coal mine green backfilling systems. Full article

Pipe networks assure the transportation of primary commodities such as water, oil, and natural gas. Quantitative and early detection of defects avoids costly consequences. Due to low cost of water, high-profile accidents, and economic downturns, the research and development of nondestructive evaluation (NDE) and structural health monitoring (SHM) technologies for freshwater mains and urban water networks have received less attention with respect to the gas and oil industries. Moreover, the technical challenges associated with the practical deployment of monitoring systems and the fact that most water pipelines are buried underground demand synergistic interaction across several disciplines, which may limit the transition from laboratory to real structures. This paper reviews the most prominent NDE/SHM technologies for freshwater pipes. The challenges that said infrastructures pose, as well as the methodologies that can be translated into SHM approaches, are highlighted. The scope of this review is to provide a holistic view of the physical principles, the success, and the technological challenges associated with the inspection and monitoring of freshwater pipelines. Full article

With the rapid transition toward modern power systems, ensuring the operational integrity of substation earthing networks has become a critical priority in infrastructure modernisation. This paper investigates the resistive coupling interference between substation earthing grids and adjacent underground metallic pipeline networks within the context of renovation projects. An integrated field–circuit coupling methodology, synergising CDEGS-based electromagnetic field analysis with ETAP-based circuit modelling, is proposed to quantify critical safety performance metrics. Simulation results demonstrate that resistive coupling induces significant fluctuations in key performance parameters, potentially compromising system safety during faults. Based on these findings, a suite of targeted optimisation strategies and protective measures is developed to ensure the stable operation of both the earthing system and the surrounding metallic infrastructure. This study provides a rigorous theoretical framework and practical technical guidance for the design and optimisation of substation earthing systems in complex electromagnetic environments. Full article

Aging underground pipeline infrastructure across the United States, including systems used for potable water supply, wastewater collection, and stormwater conveyance, has exceeded its intended service life, emphasizing the need for replacement or rehabilitation to maintain reliable service to communities. Among available trenchless technologies, cured-in-place pipe (CIPP) is widely applied because it minimizes surface disruption and is well-suited for use in densely populated areas. Despite these advantages, environmental concerns remain regarding the release of total volatile organic compounds (VOCs) during CIPP installation and curing. This study evaluates total VOC emissions from CIPP liners under field conditions. Air samples were collected at six installation sites across the United States before, during, and after installation and curing to quantify key VOC species. Multiple sampling methods were employed, including photoionization detectors (PIDs), Summa canisters, and personal worker sampling. The measured compounds included styrene, cumene, acetophenone, hexane, toluene, and ethanol. Measured concentrations were compared with occupational exposure limits established by the U.S. Environmental Protection Agency (USEPA), the National Institute for Occupational Safety and Health (NIOSH), and the Occupational Safety and Health Administration (OSHA). The results indicate that styrene was the dominant compound within active CIPP work zones, with peak concentrations reaching 25.5 ppm during curing. In contrast, VOC concentrations decreased substantially within five feet downwind of the work zone. Overall, the findings suggest that potential public exposure risks are limited, while workers directly involved in CIPP operations may experience elevated short-term exposures during installation and curing activities. Full article

Underground mining environments pose significant challenges for automated hazard detection due to low illumination, restricted visibility, and the absence of Global Navigation Satellite System (GNSS) coverage. These factors limit situational awareness and delay inspection efforts, particularly after disruptive events when rapid assessment is essential for safety. This study addresses this problem by developing a dual-pipeline framework for 2D–3D detection that uses 360° imaging and LiDAR-based machine learning to identify people, vehicles, and positional changes in underground settings without requiring personnel to re-enter hazardous areas. The objective was to create a system capable of recognizing objects and monitoring spatial changes under real underground mine conditions. The 2D component used a Ricoh Theta Z1 camera to collect panoramic images, and a YOLO (You Only Look Once) v8n model was fine-tuned using datasets representing low light, shadowed underground scenes. The 3D component employed an Ouster OS1-070-64 LiDAR sensor, and point clouds were processed through denoising, ICP alignment, surface reconstruction, manual annotation, and 2D projection. A YOLO-based model was then trained to detect objects and measure displacement between LiDAR scans. Results demonstrated strong performance for both components. The fine-tuned YOLOv8n model reliably detected personnel and vehicles despite challenging lighting and visual clutter, while the 3D pipeline localized objects in the registered LiDAR frame and quantified vehicle displacement between consecutive scans by comparing 3D bounding-box centroids after ICP alignment (displacement vector and magnitude). These findings indicate that the combined 2D–3D system can effectively support automated hazard recognition and environmental monitoring in GNSS-denied underground spaces. Full article