Search Results (826)

This paper presents a proof-of-concept real-time safety alerting system for safety-critical environments such as construction sites. Key components of the system include Bluetooth Low Energy (BLE) devices for indoor localization, integrated with a customized Android application using the Framework for Internal Navigation and Discovery (FIND). Administrative control and data management are handled by a server-side component, supported by an interactive website for real-time safety monitoring. The architecture supports safety zoning and employs machine learning algorithms, including k-NN, Random Forest, and SVM, for analyzing localization data. Experimental validation in a laboratory setup demonstrates a localization accuracy of 97%, a response time of 1.2 s, and a maximum spatial error of 1.2 m. These results highlight the system’s reliability and potential for enhancing safety compliance in real-world deployment scenarios. Full article

For tunnels constructed in a single direction, the pipe roof at the tunnel exit portal can be installed either as Outside-to-Inside advanced support arrangements (Out–In ASA) or Inside-to-Outside advanced support arrangements (In–Out ASA). To investigate the pipe roof’s mechanical behavior and deformation characteristics under two excavation methods, this study establishes Pasternak two-parameter elastic foundation beam models for the pipe roof. Corresponding boundary conditions are proposed for each support configuration, and the governing differential equation for pipe roof deflection is derived and solved. The Hanjiashan Tunnel is used as an engineering case study to validate the theoretical results by comparing them with field monitoring data. A comparative analysis and parametric sensitivity study are then conducted for the two construction methods. The results show that theoretical predictions align well with the field measurements, confirming the validity of the proposed model. This study proposed calculation parameters for the Hanjiashan Tunnel. Under this circumstance, the method of Out–In ASA has been proven to offer improved structural performance and safety when the tunnel face is close to the portal. Moreover, the timely installation of the initial support and the strong bearing capacity of the surrounding rock can further reduce pipe roof deformation near the tunnel exit. Therefore, the Out–In ASA method is recommended for single-direction tunnel excavation. If the method of Out–In ASA is not feasible due to site constraints, the method of In–Out ASA can be adopted, while early support and effective grouting should be guaranteed to ensure control of excessive deformation. The findings of this study can provide a theoretical reference for the construction of tunnel portals in single-direction excavation. Full article

The rapid and sensitive detection of regulatory elements within transgenic constructs of genetically modified organisms (GMOs) is essential for effective monitoring and control of their distribution. In this study, we present several innovative electrochemical biosensing platforms for the detection of regulatory sequences in genetically modified (GM) plants, combining the loop-mediated isothermal amplification (LAMP) method with electrodes functionalized by two-dimensional (2D) nanomaterials. The sensor design exploits the high surface area and excellent conductivity of reduced graphene oxide, Ti₃C₂T_x, and molybdenum disulfide (MoS₂) to enhance signal transduction. Furthermore, we used a “green synthesis” method for Ti₃C₂T_x preparation that eliminates the use of hazardous hydrofluoric acid (HF) and hydrochloric acid (HCl), providing a safer and more sustainable approach for nanomaterial production. Within this framework, the performance of various custom-fabricated electrodes, including laser-patterned gold leaf films, physical vapor deposition (PVD)-deposited gold electrodes, and screen-printed gold electrodes, is evaluated and compared with commercial screen-printed gold electrodes. Additionally, gold and carbon electrodes were electrochemically covered by gold nanoparticles (AuNPs), and their properties were compared. Several electrochemical methods were used during the DNA detection, and their importance and differences in excitation signal were highlighted. Electrochemical properties, sensitivity, selectivity, and reproducibility are characterized for each electrode type to assess the influence of fabrication methods and material composition on sensor performance. The developed biosensing systems exhibit high sensitivity, specificity, and rapid response, highlighting their potential as practical tools for on-site GMO screening and regulatory compliance monitoring. This work advances electrochemical nucleic acid detection by integrating environmentally-friendly nanomaterial synthesis with robust biosensing technology. Full article

For an existing bridge constructed with separate spans, the ends of adjacent flanges are disconnected. The problem of separated driving may occur at the bridgehead position after traffic conversion. The idea of integral splicing two separate spans of the existing long-span bridge is proposed. Direct crossing of a vehicle between the two separate spans of the existing long-span bridge can be realized. Firstly, the demand for integral splicing of the existing box girder bridge is analyzed using different methods. Then, an integral splicing composite structure (ISC-Structure) is designed and tested, and the corresponding design method is summarized. Finally, the construction technology for the ISC-Structure is optimized based on the actual field conditions. This research shows that the integral splicing demand of the old bridge can be obtained through on-site monitoring at the splicing position. Furthermore, the proposed random traffic flow simulation method can be applied to expand the data volume and verify the validity of the monitoring data. The proposed ISC-Structure meets the transverse splicing requirements of the Xinfengjiang Bridge. It can effectively connect the two separate spans, enabling them to work compositely and improving longitudinal mechanical properties. A layered and segmented construction scheme is proposed, and the relevant construction technology is optimized for the target integral splicing project. The proposed integral splicing design and construction technology can sever as a reference for similar long-span bridge extension projects. Full article

The long-term safety and operational reliability of zoned earth dams depend on the structural integrity of their internal components, including core, filters, and shell zones. This is particularly relevant for old dams which have been operational for a long period of time. Such existing infrastructure systems are exposed to various loading types over time, including environmental, seepage-related, extreme event, and climate change effects. As a result, even when they look intact externally, changes might affect their internal structure, composition, and possibly functionality. Thus, it is important to delineate a comprehensive and cost-effective strategy to identify potential issues and derive the health status of existing earth dams. This paper outlines a systematic approach for conducting a comprehensive health check of these structures through the implementation of a multi-epoch geotechnical approach based on a variety of standard measured and monitored quantities. The goal is to compare current properties with baseline data obtained during pre-, during-, and post-construction site investigation and laboratory tests. Guidance is provided on how to judge such multi-epoch comparisons, identifying potential outcomes and scenarios. The proposed approach is tested on a well-documented case study in Southern Italy, an area prone to climate change and subjected to very high seismic hazard. The case study demonstrates how the integration of historical and contemporary geotechnical data allows for the identification of critical zones requiring attention, the validation of numerical models, and the proactive formulation of targeted maintenance and rehabilitation strategies. This comprehensive, multi-epoch-based approach provides a robust and reliable assessment of dams’ health, enabling better-informed decision-making workflows and processes for asset management and risk mitigation strategies. Full article

This paper outlines the implementation and core results of a combined archaeological, historical, and ethnographic study of the histories of well construction and water management among Boran, Gabra, and Rendille pastoralists in arid and semi-arid areas of Northern Kenya and Southern Ethiopia. Co-developed with representatives from different local communities from the outset, this project sought to document the spatial distribution of different types of hand-dug wells found across the study areas, their associated oral histories and, if possible, establish through archaeological means their likely date of initial construction. Concurrent with addressing these academic objectives, this project aimed to train a cohort of local heritage stewards in archaeological, historical, and ethnographic data collection and interpretation, equipping them with the necessary skills to monitor sites of heritage value and further record additional elements of the tangible and intangible heritage of the study areas. This paper discusses the archaeological work that the community trainees participated in, the strategies developed with them to create wider awareness of this heritage, and its implications for identifying ways to ”weather” climate change in the future. Full article

The development of unconventional oil and gas resources highly relies on hydraulic fracturing technology, and the fracturing effect directly affects the level of oil and gas recovery. Carrying out fracturing evaluation is the main way to understand the fracturing effect. However, the current fracturing evaluation methods are usually carried out after the completion of fracturing operations, making it difficult to achieve real-time monitoring and dynamic regulation of the fracturing process. In order to solve this problem, an intelligent prediction method for fracture propagation based on the attention mechanism and Long Short-Term Memory (LSTM) neural network was proposed to improve the fracturing effect. Firstly, the GOHFER software was used to simulate the fracturing process to generate 12,000 groups of fracture geometric parameters. Then, through parameter sensitivity analysis, the key factors affecting fracture geometric parameters are identified. Next, the time-series data generated during the fracturing process were collected. Missing values were filled using the K-nearest neighbor algorithm. Outliers were identified by applying the 3-sigma method. Features were combined through the binomial feature transformation method. The wavelet transform method was adopted to extract the time-series features of the data. Subsequently, an LSTM model integrated with an attention mechanism was constructed, and it was trained using the fracture geometric parameters generated by GOHFER software, forming a surrogate model for fracture propagation. Finally, the surrogate model was applied to an actual fracturing well in Block Ma 2 of the Mabei Oilfield to verify the model performance. The results show that by correlating the pumping process with the fracture propagation process, the model achieves the prediction of changes in fracture geometric parameters and Stimulated Reservoir Volume (SRV) throughout the entire fracturing process. The model’s prediction accuracy exceeds 75%, and its response time is less than 0.1 s, which is more than 1000 times faster than that of GOHFER software. The model can accurately capture the dynamic propagation of fractures during fracturing operations, providing reliable guidance and decision-making basis for on-site fracturing operations. Full article

The environment of the power operation site is complex and changeable, and the accurate identification of the wearing status of workers’ safety helmets is significant to ensure personal safety and the stable operation of the power system. Existing research suffers from high rates of missed detections and limited ability to discriminate fine-grained states, especially the identification of “wrongly wearing” states. Therefore, this paper proposes an intelligent identification method of safety helmet status for power workers based on a dual-path attention network. We embed the convolutional block attention module (CBAM) in the two paths of the backbone and neck layers of YOLOv5 and enhance the feature focusing ability of the key areas of the helmet through the channel-spatial attention coordination, so as to suppress the interference of complex background. In addition, a special dataset covering power scenarios is constructed, including fine-grained state annotation under various lighting, different poses, and occlusion conditions to improve the generalization of the model. Finally, the proposed method is applied to the images of the electric power operation site for experimental verification. The experimental results show that the proposed YOLO-CBAM achieves an outstanding mean average precision of 98.81% for identifying all helmet states, providing reliable technical support for intelligent safety monitoring. Full article

The current research on smart construction sites is mainly from the perspective of the whole life cycle of the project, and often focuses on the identification of factors at the macro level. It lacks in-depth quantitative analysis of the complex interdependence between influencing factors, and it is difficult to accurately identify key driving factors and weight distribution. This paper takes engineering project management as the perspective, constructs a smart site construction model. The advantages of DEMATEL method and ANP method are innovatively combined to construct the DEMATEL-ANP evaluation model, which overcomes the limitations of single method in weight determination and relationship analysis, and provides a more detailed and scientific analysis framework for the evaluation of smart site construction, and, taking the Urumqi region as an example, its smart construction is evaluated and analyzed. The results of the study show that the correlation between the indicators affecting the construction of smart construction sites is strong, in which the comprehensive influence of personnel safety management, construction quality management, and construction safety management play a greater role, with the comprehensive weights of 0.0917, 0.0817 and 0.0767, respectively; the total score of smart construction site construction of Urumqi region is 63.959, which is in the primary construction stage. Among them, the construction and application of meteorological monitoring are the best, scoring 70.26; the construction and application of most indicators, such as personnel safety management, cost comparison decision-making, dust monitoring, and noise monitoring, are the second best; the construction progress control and wastewater monitoring construction are poor, scoring 55.21 and 57.741. The results of this study can provide direct value to key audiences such as construction enterprise managers, government regulators, and smart site solution providers. This paper considers regions with unique climate types to provide a reference for the construction of intelligent construction sites in the same type of regions. Full article

The structural safety monitoring of industrial heritage is of great significance for global urban renewal and the preservation of cultural heritage. However, traditional tilt monitoring methods suffer from limited accuracy, low efficiency, poor global perception, and a lack of intelligence, making them inadequate for meeting the tilt monitoring requirements of super-high-rise industrial heritage chimneys. To address these issues, this study proposes a tilt monitoring method for super-high-rise industrial heritage chimneys based on LiDAR point clouds. Firstly, LiDAR point cloud data were acquired using a ground-based LiDAR measurement system. This system captures high-density point clouds and precise spatial attitude data, synchronizes multi-source timestamps, and transmits data remotely in real time via 5G, where a data preprocessing program generates valid high-precision point cloud data. Secondly, multiple cross-section slicing segmentation strategies are designed, and an automated tilt monitoring algorithm framework with adaptive slicing and collaborative optimization is constructed. This algorithm framework can adaptively extract slice contours and fit the central axes. By integrating adaptive slicing, residual feedback adjustment, and dynamic weight updating mechanisms, the intelligent extraction of the unit direction vector of the central axis is enabled. Finally, the unit direction vector is operated with the x- and z-axes through vector calculations to obtain the tilt-azimuth, tilt-angle, verticality, and verticality deviation of the central axis, followed by an accuracy evaluation. On-site experimental validation was conducted on a super-high-rise industrial heritage chimney. The results show that, compared with the results from the traditional method, the relative errors of the tilt angle, verticality, and verticality deviation of the industrial heritage chimney obtained by the proposed method are only 9.45%, while the relative error of the corresponding tilt-azimuth is only 0.004%. The proposed method enables high-precision, non-contact, and globally perceptive tilt monitoring of super-high-rise industrial heritage chimneys, providing a feasible technical approach for structural safety assessment and preservation. Full article

The active pile underpinning technology when a tunnel passes under a bridge involves complex force conditions, making construction monitoring and control extremely challenging. However, there is a lack of research on the laws governing the stress and deformation responses of bridges during the construction process. This paper takes an active pile underpinning project of a metro line passing under a bridge as a case study. Design and construction plans are taken as the basis, and on-site monitoring data are incorporated. A three-dimensional finite element simulation model is established. This model is used to analyze the distribution and variation laws of stress and settlement during the pile underpinning process. The results show that: considering the traffic conditions of the bridge and the requirements for additional stress, it is reasonable to suggest that the actual settlement of the bridge deck should be 2–3 mm; the determination of the jacking force should generally be greater than the load transmitted from the pier column to the underpinning beam and less than 75% of the maximum bearing capacity, which is more reasonable. Full article

With the increasing demand for urban rail transit capacity, shield tunneling has become the predominant method for constructing underground metro systems in densely populated cities. However, the spatial interaction between shield tunnels and adjacent retaining structures poses significant engineering challenges, potentially leading to excessive ground settlement, structural deformation, and even stability failure. This study systematically investigates the deformation behavior and associated risks of retaining systems during adjacent shield tunnel construction. An orthogonal multi-factor analysis was conducted to evaluate the effects of grouting pressure, grout stiffness, and overlying soil properties on maximum surface settlement. Results show that soil cohesion and grouting pressure are the most influential parameters, jointly accounting for over 72% of the variance in settlement response. Based on the numerical findings, a Bayesian network model was developed to assess construction risk, integrating expert judgment and field monitoring data to quantify the conditional probability of deformation-induced failure. The model identifies key risk sources such as geological variability, groundwater instability, shield steering correction, segmental lining quality, and site construction management. Furthermore, the effectiveness and cost-efficiency of various grouting reinforcement strategies were evaluated. The results show that top grouting increases the reinforcement efficiency to 34.7%, offering the best performance in terms of both settlement control and economic benefit. Sidewall grouting yields an efficiency of approximately 30.2%, while invert grouting shows limited effectiveness, with an efficiency of only 11.6%, making it the least favorable option in terms of both technical and economic considerations. This research provides both practical guidance and theoretical insight for risk-informed shield tunneling design and management in complex urban environments. Full article

Microbially induced carbonate precipitation (MICP), as an eco-friendly biomineralization technology, has opened up an innovative path for the green and low-carbon development of the mining industry. Unlike conventional methods, its in situ solidification minimizes environmental disturbances and reduces carbon emissions during construction. This article reviews the research on MICP technology in various scenarios within the mining industry, summarizes the key factors influencing the application of MICP, and proposes a future research direction to fill the gap of the lack of systematic guidance for the application of MICP in this field. Specifically, it elaborates on the solidification mechanism of MICP and its current application in the solidification and storage of tailings, heavy metal immobilization, waste resource utilization, carbon sequestration, and field-scale deployment, establishing a technical foundation for broader implementation in the mining sector. Key influencing factors that affect the solidification effect of MICP are discussed, along with critical engineering challenges such as the attenuation of microbial activity and the low uniformity of calcium carbonate precipitation under extreme conditions. Proposed solutions include environmentally responsive self-healing technologies (the stimulus-responsive properties of the carriers extend the survival window of microorganisms), a one-phase low-pH injection method (when the pH = 5, the delay time for CaCO₃ to appear is 1.5 h), and the incorporation of auxiliary additives (the auxiliary additives provided more adsorption sites for microorganisms). Future research should focus on in situ real-time monitoring of systems integrated with deep learning, systematic mineralization evaluation standard system, and urea-free mineralization pathways under special conditions. Through interdisciplinary collaboration, MICP offers significant potential for integrated scientific and engineering solutions in mine waste solidification and sustainable resource utilization. Full article

This study employs Geographic Information Systems (GIS) combined with multivariate statistical techniques to evaluate soil contamination at two landfill sites in Al-Kharj, Saudi Arabia. A total of 32 soil samples were collected and analyzed for heavy metals and metalloids (HMs) using a range of contamination indices and established soil quality standards. GIS mapping revealed that the Al-Kharj landfill 1 (Kj1) experienced a steady area expansion from 2014 through 2025, while landfill Kj2 expanded from 2014 until 2022, after which its area contracted following the construction of additional facilities. The average values of HMs observed were as follows: Fe (9909 mg/kg), Al (6709 mg/kg), Mn (155.9 mg/kg), Zn (36.4 mg/kg), Cr (24.1 mg/kg), V (22.2 mg/kg), Ni (19.5 mg/kg), Cu (8.20 mg/kg), Pb (7.91 mg/kg), Co (4.32 mg/kg), and As (2.29 mg/kg). Notably, Kj2 exhibited overall higher HM concentrations than Kj1, with particularly elevated levels of Cr, Ni, and Pb. Although most HMs remained within internationally accepted safety limits, only three samples (9.4% of the total) exceeded the WHO threshold for Pb (>30 mg/kg). An analysis using contamination and enrichment factors pointed to increased concentrations of Pb, Zn, and Cr, suggesting localized anthropogenic contributions. Additionally, all samples recorded an ecological risk index (Eri) below 40, and the levels of As, Cr, and Pb consistently stayed under their respective effects range-low (ERL) thresholds, indicating minimal contamination risks. The variations in HM contamination between the sites are likely attributable to differences in the sources of metal inputs and removal processes. These findings highlight the need for continuous monitoring and localized remediation strategies to ensure environmental safety and sustainable landfill management. Full article

There is currently no mature calculation theory to accurately predict the settlement of high-fill subgrade. This paper developed an intelligent monitoring system to accurately predict the settlement of high-fill subgrade based on on-site experiments, and the back-propagation (BP) neural network model was used to predict the settlement of high-fill subgrade. The results show that multiple data preprocessing methods built into intelligent systems can automatically generate multi-point and correlation curves, and the system can identify and distinguish various influencing factors to improve the accuracy and reliability of monitoring data. There will be a certain initial settlement of subgrade in the initial stage after filling construction is completed, and the settlement rate at this stage is relatively fast. Afterwards, the soil enters a rapid consolidation stage, and the settlement rate of subgrade gradually slows down. Finally, the filling soil consolidation becomes stable, and the rate of subgrade settlement enters a relatively stable stage. In addition, the BP neural network model is a good method for predicting the settlement of high-fill subgrade. The research findings can provide inspiration for developing an intelligent monitoring system to accurately predict the settlement of high-fill subgrade. Full article