Development of Monitoring, Analysis and Maintenance Technics of Infrastructures

In this paper, a novel Multi-Objective Hypergraph Particle Swarm Optimization (MOHGPSO) algorithm for structural health monitoring (SHM) systems is considered. This algorithm autonomously identifies the most relevant sensor placements in a combined fitness function without artificial intervention. The approach utilizes six established Optimal Sensor Placement (OSP) methods to generate a Pareto front, which is systematically analyzed and archived through Grey Relational Analysis (GRA) and Fuzzy Decision Making (FDM). This comprehensive analysis demonstrates the proposed approach’s superior performance in determining sensor placements, showcasing its adaptability to structural changes, enhancement of durability, and effective management of the life cycle of structures. Overall, this paper makes a significant contribution to engineering by leveraging advancements in sensor and information technologies to ensure essential infrastructure safety through SHM systems. Full article

In recent years, bridge collapses resulting from vehicle overloading have underscored the crucial necessity for real-time monitoring of traffic conditions on bridges, making pavement-based weigh-in-motion systems indispensable for large bridges. However, these systems usually have poor durability and will cause traffic interruptions during their installation and maintenance processes. This paper addresses the challenge of recognizing vehicle loads by proposing a vehicle load identification method based on machine vision and displacement influence lines. The technology consists of three essential steps. Firstly, machine vision technology is utilized to identify vehicle trajectories. Following this, the displacement response, monitored by millimeter-wave radar, is integrated to calculate the influence lines of the structure’s displacement. Lastly, an overall least squares method incorporating a regularization term is applied to calculate axle weights. The efficacy of the proposed method is validated within the monitoring system of a specific continuous beam. Importantly, the calibration of vehicles and the validation dataset rely on information monitored by the pavement-based weigh-in-motion system of adjacent arch bridges, serving as ground truth. Results indicate that the identification errors for gross vehicle weight do not exceed 25%. This technology holds significant importance for identifying vehicle weights on small to medium-span bridges. Due to its cost-effectiveness, easy installation, and maintenance, it possesses a high potential for widespread adoption. Full article

Effective facility asset management requires specific skills and tools to optimize the use of limited resources, making a decision support system essential. This research introduces a comprehensive decision support system, which is a framework organized into three models: the criticality model, the rehabilitation model, and the optimum criticality model to manage the rehabilitation of facility assets. The criticality model utilizes the Analytical Hierarchy Process (AHP) to assess the group of assets. Emphasizing criticality as a central management factor, this model lays the foundation for subsequent decision-making. The rehabilitation model employs an Artificial Neural Network (ANN), integrating Customer Level of Service (CLoS), Technical Level of Service (TLoS), and asset criticality to determine appropriate rehabilitation actions. NeuralTools 7.5 is leveraged for precise predictions of rehabilitation strategies tailored to specific assets. The third model, optimum criticality, focuses on prioritizing rehabilitation activities within the constraints of limited budgets. Lingo 20.0 is utilized to optimize rehabilitation activities, considering budget limitations and other constraints, offering a strategic approach to maximize the impact of available resources. This integrated framework provides decision-makers with a systematic and data-driven approach to facility management, enhancing the efficiency and effectiveness of rehabilitation actions. An academic building was chosen as a hypothetical example to implement the three models and suggest the essential considerations for managing both the academic building itself and other infrastructure assets. The results obtained demonstrate that the principles and methodologies encapsulated in this project can be extrapolated and scaled up for application to large-scale infrastructure assets, ensuring the sustenance of the requisite level of service and the management of acceptable risk on a broader scale. Full article

In this paper, we propose a data classification and analysis method to estimate fire risk using facility data of thermal power plants. To estimate fire risk based on facility data, we divided facilities into three states—Steady, Transient, and Anomaly—categorized by their purposes and operational conditions. This method is designed to satisfy three requirements of fire protection systems for thermal power plants. For example, areas with fire risk must be identified, and fire risks should be classified and integrated into existing systems. We classified thermal power plants into turbine, boiler, and indoor coal shed zones. Each zone was subdivided into small pieces of equipment. The turbine, generator, oil-related equipment, hydrogen (H2), and boiler feed pump (BFP) were selected for the turbine zone, while the pulverizer and ignition oil were chosen for the boiler zone. We selected fire-related tags from Supervisory Control and Data Acquisition (SCADA) data and acquired sample data during a specific period for two thermal power plants based on inspection of fire and explosion scenarios in thermal power plants over many years. We focused on crucial fire cases such as pool fires, 3D fires, and jet fires and organized three fire hazard levels for each zone. Experimental analysis was conducted with these data set by the proposed method for 500 MW and 100 MW thermal power plants. The data classification and analysis methods presented in this paper can provide indirect experience for data analysts who do not have domain knowledge about power plant fires and can also offer good inspiration for data analysts who need to understand power plant facilities. Full article

Slope failures pose significant threats to human safety and vital infrastructure. The urgent need for the accurate prediction of these geotechnical events is driven by two main goals: advancing our understanding of the underlying geophysical mechanisms and establishing efficient evacuation protocols. Although traditional physics-based models offer in-depth insights, their reliance on numerous assumptions and parameters limits their practical usability. In our study, we constructed an experimental artificial slope and monitored it until failure, generating an in-depth displacement dataset. Leveraging this dataset, we developed and compared prediction models rooted in both statistical and machine learning paradigms. Furthermore, to bridge the gap between generic evaluation metrics and the specific needs of slope failure prediction, we introduced a bespoke performance. Our results indicate that while the statistical approach did not effectively provide early warnings, the machine learning models, when assessed with our bespoke performance metric, showed significant promise as reliable early warning systems. These findings hold potential to fortify disaster prevention measures and prioritize human safety. Full article

This paper introduces an innovative model for heavy-haul train–track–bridge interaction, utilizing a coupling matrix representation based on the virtual work principle. This model establishes the relationship between the wheel–rail contact surface and the bridge–rail interface concerning internal forces and geometric constraints. In this coupled system’s motion equation, the degrees of freedom (DOFs) of the wheelsets in a heavy-haul train lacking primary suspension are interdependent. Additionally, the vertical and nodding DOFs of the bogie frame are linked with the rail element. A practical application, a Yellow River Bridge with a heavy-haul railway line, is used to examine the accuracy of the proposed model with regard to discrepancy between the simulated and measured displacement ranging from 1% to 11%. A comprehensive parametric analysis is conducted, exploring the impacts of track irregularities of varying wavelengths, axle load lifting, and the degradation of bridge stiffness and damping on the dynamic responses of the coupled system. The results reveal that the bridge’s dynamic responses are particularly sensitive to track irregularities within the wavelength range of 1 to 20 m, especially those within 1 to 10 m. The vertical displacement of the bridge demonstrates a nearly linear increase with heavier axle loads of the heavy-haul trains and the reduction in bridge stiffness. However, there is no significant rise in vertical acceleration under these conditions. Full article

Among the construction processes of Portland cement concrete pavement (PCCP), the curing compound spraying process is one of the most important processes. If the curing compound spraying amount does not meet the standard or if the curing compound is not applied evenly, distresses occur at the early age of construction, ultimately causing deterioration in concrete pavement performance. The purpose of this study is to develop a real-time monitoring system for a curing compound spraying process based on the Internet of Things (IoT) and sensing technologies to improve the construction quality of concrete pavement. To achieve the goal of this research, we conducted various laboratory and field experiments. The curing compound spraying amount and sprayed status were measured and analyzed using flowmeters, image acquisition sensors, and an image processing program, and the data were provided to workers in real time and simultaneously transmitted to the IoT cloud to form a database. From this study, it is confirmed that the IoT-technology-based curing compound spraying amount and sprayed status monitoring systems can be successfully established to manage construction quality related to the curing of concrete pavement. Full article

This paper presents a numerical investigation on the residual stresses and co-existent equivalent plastic strains in cold-formed high-strength steel (CFHSS) circular hollow sections (CHS) by using an advanced finite element (FE)-based method. In this method, the entire manufacturing process of the CFHSS CHS was modeled numerically. The accuracy of the numerical predictions of equivalent plastic strains and residual stresses in the CFHSS CHS was verified by comparing the predictions with the existing test results of both the residual stress measurement and load-end shortening response of the stub column. By using the FE-based method, the effects of high-frequency electric resistance welding on the residual stresses and the stub column response were investigated. The through-thickness variations of both the equivalent plastic strains and residual stresses in CFHSS CHS, which are difficult to measure in the laboratory, were explored numerically. Finally, the effect of cold work (which is quantified by the equivalent plastic strains and residual stresses) on the stub column response of CFHSS CHS tubes was evaluated. It can be found that the equivalent plastic strains and longitudinal residual stresses are generally uniform around the cross-section of CFHSS CHS. The transverse and longitudinal residual stresses are generally uniform across each half-thickness, with the inner half-thickness under compression and the outer half-thickness under tension. The results also demonstrate that both the plastic strains and residual stresses may significantly affect the cross-section capacities of CFHSS CHS. Full article

Strain measurements have a significant role in evaluating the condition of various structural types and have become an essential component in the area of structural health monitoring. However, there are some limitations in the current means of strain measurement, and this study aims to improve these methods. We have designed a novel strain measurement method based on template matching algorithms and microscopic vision techniques, developed a new sliding strain sensor, and paired it with a new microscope to realize strain measurement. The method has the function of remote wireless acquisition with a cell phone, which is more widely applicable. In the laboratory performance testing, the zero drift of the sensor is mainly concentrated in the fluctuation range of ±2 με, and the effective range reaches nearly 40,000 με. In the comparison experiments with the linear variable differential transformer, the maximum error of the static loading is only 5 με, and the maximum error rate of the dynamic loading is less than 1%, which proves that it has a relatively high accuracy. Finally, the short-term real-time monitoring of the local structure of the footbridge was accomplished, and the strain changes on the surface of the structure were captured instantly, stably, and efficiently in the actual measurements. The proposed strain measurement system has the advantages of high accuracy, a low cost, convenient measurement, and wide applicability, and it provides a novel alternative means for strain measurement in the field of structural health monitoring. Full article

The stay cable is one of the most critical structural components of a cable dome structure. However, during its service life, it may lose its stiffness due to environmental factors and metal fatigue, thus making the structure a safety hazard. As the most important mechanical physical parameter of the cable, it is necessary to create a health-monitoring method to ensure the safety of the structure. In this study, a smart cable with a fiber optic Bragg grating (FBG) sensor is proposed. The sensor is embedded in the Z-shaped cable of the stay cable to ensure the simultaneous deformation of the sensor and cable. The monitoring of the cable force can be achieved after obtaining the relationship coefficient between the sensor and the cable force. In the rest of the paper, the sensing principle and fabrication procedure are described. A series of tests are conducted to verify the sensing performance of the smart cable. Finally, the dynamic monitoring and long-term monitoring of the cable force in the cable-supported grid system of Dalian Suoyuwan Football Stadium are carried out by using the smart cable, and the stability and safety of the structure are evaluated by the monitoring results. Full article

The lithological characterization of the seafloor is key information for offshore engineering, especially when it comes to pier and platform design. Undetected shallow gas pockets may cause the collapse of heavy platforms for hydrocarbon production. Unconsolidated sediments are not ideal for the basement of wind farms for electric power production. Drilling and coring can be used for local sampling, but continuous profiles or even areal coverage are far more preferable. High-resolution seismic profiles are successfully used when ports are not too busy, but otherwise, single-channel systems must be used. We show in this paper that even these simpler systems can be used to estimate parameters such as the acoustic impedance of shallow sediments directly beneath the seafloor. We exploit the amplitude decay of the multiple reflections between the seafloor and the surface, which does not depend on the source energy. If the offset between source and receiver is not too small, we can estimate the shallow P velocity and, via acoustic impedance, also the rock density. Full article

The subject of the research is the investigation of the behavior of railway tracks in places with a significant change in the stiffness of the track. These parts can be designed from various structural elements and their materials, and this mainly results in a height change of the track level during its operation. These transition zones are monitored and expertly examined to detect undesirable deformations of the geometrical position of the track caused by the trains running. The transition zones are at the points where the fixed track transitions to the classic track bed, in our case it is their combination with bridge structures, especially at their supports. In Slovakia, under the conditions of the Railways of the Slovak Republic, the issue is topical within the framework of the modernization of trans-European railway corridors. The results of experimental measurements and their analysis will provide relevant data for subsequent research solutions for their new numerical modelling, which will ensure a smooth passage through these points of change without height fluctuations, vibrations, and shocks from the wheels of train sets. Full article

Retrofitted super-span old T-shaped concrete beams (RS-OCT beams) are commonly used in highway bridges in coastal cities and offshore zones in China. The realization of a practical ultimate state for this beam under a bending load is still lacking. In this study, a flexural experiment on an original RS-OCT beam subjected to a long-term vehicle cyclical load was conducted in a laboratory. Several interesting phenomena were discovered. Notably, a butt-weld joint typically exists on longitudinal reinforced bars, which may be vulnerable to bending. The RS-OCT beam simultaneously suffered from the double function of atmospheric environment and fatigue during service. Based on the time-dependent and fatigue theories of materials, finite element analysis was performed using the ABAQUS software. The flexural behavior of the RS-OCT beam at various time periods was simulated. Subsequently, the flexural bearing capacities of the beams were calculated. The safety reservation of the RS-OCT beam at various time stages was related to the change in material properties and upgrading of the loading level. The latter plays a dominant role in the service state. Full article

Subjected to the relentless impacts of typhoons and rough seas, offshore wind turbines’ structures, particularly the tower, foundation, and blade, are at constant risk of damage. Full-field strain monitoring helps to discover potential structural defects, thereby reducing disasters caused by overall structural failure. This study introduces a novel method for assessing strain and temperature fields on these kinds of 3D surfaces of cylindrical structures. The method harnesses the capabilities of a high spatial resolution (0.65 mm) Optical Frequency Domain Reflectometer (OFDR)-based Distributed Optical Fiber Sensor (DOFS) in conjunction with a unique helical wiring layout. The core process begins with mapping the fiber optic path onto a plane corresponding to the unfolded cylinder. Fiber optic signals are then differentiated on this plane, deriving a two-dimensional strain distribution. The plane strain field is subsequently projected onto the 3D side of the cylinder. An experiment was carried out in which a 3.5 m long optical fiber was helically wound with a 10 mm pitch on the surface of a cantilever beam of a cylinder shell with a diameter of 36 mm and a length of 300 mm. The experiment collected about 5400 measurement points on the cylindrical surface of 340 cm², approximately 15.9 measurement points per square centimeter. The reconstructed results successfully reveal the strain field of the pipe cantilever beam under bending and torsional loads, as well as the palm-shaped temperature field. This experimental validation of the method’s efficacy lays the theoretical groundwork for its application to real wind turbines. Full article

Bedding-controlled landslides are a common geological hazard for open-pit metal mines and occur on layered rock slopes. It can spread spatially over the final boundary of the dip slope and persist throughout the entire life cycle of the mine, substantially compromising the safety of mining operations. Identifying potential landslide areas and determining the landslide mechanism is crucial for the safety production and slope management of mines. This study proposes a combination of satellite radar interferometry measurement and numerical simulation to determine the landslide mechanism of the bedding-controlled slope in open-pit mines. First, the multidimensional small baseline subset (MSBAS) technique of interferometric synthetic aperture radar (InSAR) is used to capture deformation information in the vertical and east–west directions of the slope, locate large-scale and long-term movements, and preliminarily determine the trend of landslides. Then, a layered slope damage constitutive model is established, and a three-dimensional stability calculation of the layered slope is performed using COMSOL Multiphysics 5.3 software based on the strength reduction method to study the development and evolution process of landslides. The effectiveness of the method is validated by a large-scale bedding-controlled slope failure in the Nanfen open-pit mine in Liaoning, China, revealing the failure mechanism of the slope under excavation conditions. The study shows that the eastern slope bedding-controlled landslide in the Nanfen open-pit mine is a multizone composite-mode landslide caused by excavation, which belongs to the shear–slip–tension deformation failure mechanism as a whole. This study provides a new method for analyzing the mechanism of layered rock slope landslides under mining activities in open-pit mines, which can be used to assess and predict similar landslides. Full article

The qualit12y of shafting alignment is related to the reliability and safety of a ship’s operation, and bearing displacement adjustment (BDA) plays a key role in shafting alignment. To solve the problems encountered in ship shafting alignment in the actual construction, this study focused on the investigation of the shafting load measurement system based on the strain gauge method (SGM), used the optimization method based on quadratic programming (QP) to calculate the BDA and adopted algorithms based on the bearing load influence coefficients (BICs) to forecast the load after the adjustment. The experimental work, as well as the measurement, calculation and analysis of several real ships, indicated that the measurement, optimization and forecasting methods of the bearing load of the propulsion shafting of large ships in this study would be significant for guiding the actual construction work of ship shafting alignment. Full article

Recent advancements in vehicle automation and driver-assistance systems that detect pavement markings has increased the importance of the detectability of pavement markings through various sensor modalities across weather and road conditions. Among the sensing techniques, light detection and ranging (LiDAR) sensors have become popular for vehicle-automation applications. This study used low-cost mobile multi-beam LiDAR to assess the performance of several types of pavement marking materials installed on a limited-access highway in various conditions, and quantified the degradation in detection performance over three years. Four marking materials, HPS-8, polyurea, cold plastic, and sprayable thermoplastic, were analyzed in the current study. LiDAR reflectivity data extracted from a total of 210 passes through the test sections were analyzed. A new detectability score based on LiDAR intensity data was proposed to quantify the marking detectability. The results showed that the pavement marking detectability varied across the material types over the years. The results provide guidance for selecting materials and developing maintenance schedules when marking detectability by LiDAR is a concern. Full article

This paper presents a method for dynamically maintaining a regional elevation datum using CORS stations as core nodes. By utilizing CORS station data and surface mass loading data (including land water storage, sea level, and atmospheric pressure), the normal height changes of each station can be determined and dynamically maintained. The validity of this method is verified using multiple leveling survey results from five CORS stations in Beijing’s subsidence area between January 2012 and June 2021. Results show that it is necessary to derive and correct the height anomaly variation of CORS stations caused by surface mass loading using the remove-calculate-restore method and the Green’s function integration method, with the influence of surface mass changes reaching a subcentimeter level. CORS stations exhibiting great observation quality achieve a mean accuracy of 2.7 mm in determining normal height changes. Such accuracy surpasses the requirements of second-class leveling surveys covering route lengths exceeding 1.35 km, as well as conforming/closed loop routes with distances greater than 0.46 km. By strategically selecting CORS stations with long-term continuous observations and high-quality data as core nodes within the elevation control network, dynamic maintenance of the regional elevation datum can be achieved based on CORS station data. Full article

Telemetry data are the most important basis for ground operators to assess the status of satellites in orbit, and telemetry data-based anomaly detection has become a key tool to improve the reliability and safety of spacecrafts. Recent research on anomaly detection focuses on constructing a normal profile of telemetry data using deep learning methods. However, these methods cannot effectively capture the complex correlations between the various dimensions of telemetry data, and thus cannot accurately model the normal profile of telemetry data, resulting in poor anomaly detection performance. This paper presents CLPNM-AD, contrastive learning with prototype-based negative mixing for correlation anomaly detection. The CLPNM-AD framework first employs an augmentation process with random feature corruption to generate augmented samples. Following that, a consistency strategy is employed to capture the prototype of samples, and then prototype-based negative mixing contrastive learning is used to build a normal profile. Finally, a prototype-based anomaly score function is proposed for anomaly decision-making. Experimental results on public datasets and datasets from the actual scientific satellite mission show that CLPNM-AD outperforms the baseline methods, achieves up to 11.5% improvement based on the standard $F_1$ score and is more robust against noise. Full article

Sustainable management is a challenging task for large building infrastructures due to the uncertainties associated with daily events as well as the vast yet isolated functionalities. To improve the situation, a sustainable digital twin (DT) model of operation and maintenance for building infrastructures, termed SDTOM-BI, is proposed in this paper. The proposed approach is able to identify critical factors during the in-service phase and achieve sustainable operation and maintenance for building infrastructures: (1) by expanding the traditional ‘factor-energy consumption’ to three parts of ‘factor-event-energy consumption’, which enables the model to backtrack the energy consumption-related factors based on the relevance of the impact of random events; (2) by combining with the Bayesian network (BN) and random forest (RF) in order to make the correlation between factors and results more clear and forecasts more accurate. Finally, the application is illustrated and verified by the application in a real-world gymnasium. Full article

Measuring fast neutron emission around accelerators is important for purposes of environmental monitoring and radiation safety. It is necessary to detect two types of neutrons: thermal and fast. Fast neutron spectroscopy is commonly employed using a hydrogen-recoil proportional-counter; however, its threshold is 2 MeV. The aim of this study was to expand PGNA converters based on KCl to fulfil the need to detect neutron energies ranging from 0.02 MeV to 3 MeV. In our previous research, we established a counting system comprised of a large converter of KCl with a NaI(Tl) gamma radiation spectrometer. The KCl converter is efficient for fast neutron prompt gamma emission. The potassium naturally includes a radioisotope that emits 1.460 MeV gamma rays. The presence of the constant level of 1.460 MeV gamma ray counts offers an advantage, providing a stable background for the detector. The study was carried out using MCNP simulations of the counting system with a variety of PGNA converters based on KCl. We concluded that KCl mixtures combined with other elements, such as PGNA converters, demonstrated improved detection performance for fast neutron emissions. Furthermore, an explication of how to add materials to KCl to provide a proper converter for fast neutrons was introduced. Full article

Inspection data can be used to comprehend and plan effective maintenance of bridges. In particular, the year of initial construction is one of the most important criteria for formulating maintenance plans, making budget allocations, and estimating soundness. In an initial survey of bridges in Cambodia, it was concluded that the year of construction of only 54% of 2439 bridges surveyed is known, with the remaining 46% remaining unknown. In this research, Landsat satellite data is used to estimate the year of construction of these bridges. Landsat provides spatial spectral reflectance information covering more than 30 years, and for longer bridges this can be used to estimate the year of construction by visual judgement. However, limited image resolution means this is not possible for shorter bridges. Instead, a method using the Landsat Normalized Difference Water Index (NDWI) is used to estimate the year of construction. Three pixels are selected from Landsat image data in such a way that one lies on the current location of a bridge and two other reference pixels are placed on similar terrain at a certain distance perpendicular to the bridge axis. NDWI values are plotted over time for the three pixels and the difference in value between the bridge pixel and the two reference pixels is then compared. Before the bridge is constructed, all three pixels should have similar NDWI values, but after construction the value of the target bridge pixel should differ from the other two because the NDWI value of a bridge surface is different from that of the surrounding vegetation. By looking for this change, the year of construction of a bridge can be estimated. All the bridges in the Cambodian database are classified into three categories based on length (which affects their visibility in Landsat images) and year of construction is estimated. The results show that estimated year of construction has the same accuracy in all three categories. Full article

In this study, three-dimensional finite element models of high-mast light poles without and with spiral helical strakes were built using ANSYS software to investigate their vibration characteristics in a wind environment. Based on a two-way, fluid–structure interaction simulation method, the dynamic responses of the high-mast light poles under different windspeeds were analyzed. The results indicate that the high-mast light pole structure without spiral helical strakes may suffer from evident vortex-induced vibration, which is dominated by the third vibration mode in the windspeed range of 5~8 m/s, whereas the light pole with spiral helical strakes had no obvious vortex-induced vibration. The external helical strakes can amplify the along-wind response of the light pole to a certain extent, while significantly decreasing its crosswind vortex-induced response. The vibration suppression effect is better when the value of pitch P is small. Practically, if P = 7.5 D (D is the diameter of the dominant vibration mode), the vibration suppression effect is best. On the other hand, if the value of pitch P remains constant, the vibration suppression effect increases with the height H of the outer helical strakes. However, excessively high outer helical strakes may also increase the along-wind response of the structure. In general, when spiral helical strakes are used in design, the recommended values of P and H are P = 7.5 D and H = 0.20 D. Full article

The inspection and maintenance of track ballast are fundamental tasks for the preservation of the condition of railway networks. This work presents an application based on a low-cost solid-state LiDAR system, which allows the user to accurately measure the ballast geometry from a mobile inspection trolley or draisine. The solid-state LiDAR system, the LiVOX Avia, was validated on a test track through comparison with a traditional static LiDAR system, the Faro Focus 3D. The results show a standard deviation of around 6 mm for the solid-state LiDAR system. The LiVOX system also provides the capability to measure the ballast digital elevation model and profiles. The LiVOX results are in agreement with those obtained from the Faro Focus. The results demonstrate that the LiVOX system can sufficiently measure even the displacement of a single layer of ballast stones typically between 2.5 cm and 5 cm. The data provided can be easily digitalized using image processing tools and integrated into geographic information systems for infrastructure management. Full article

Urban railway track infrastructures often suffer from damage that affects their service performance due to a variety of factors. In this study, an unsupervised feature selection and damage identification method based on globally sparse probabilistic principal component analysis (PCA) is proposed for urban railway tracks using the monitoring data of train-induced dynamic responses. A Bayesian framework is proposed for generating principal components on a basis of vectors (original variables) with a global sparseness pattern instead of separate patterns in a traditional sparse PCA. In this framework, a variational expectation-maximization algorithm is employed to obtain the tractable calculation of the marginal likelihood function for learning all uncertain parameters of the Bayesian model. The obtained principal components are linear combinations of the very same set of important variables, making our method better interpretable than the traditional sparse PCA. We can clearly understand which original variables are most relevant for describing the data. The track damage is identified simply by discriminating the corresponding measured dynamic responses using the binary elements of the latent vector inferred from the Bayesian globally sparse PCA algorithm. The usefulness is demonstrated by successfully identifying the track bed plate crack damage through the actual train-induced dynamic responses collected from the structural health monitoring system of an urban railway track infrastructure, where the method is able to achieve $F_1$ scores of 90% or higher for various scenarios. Full article

In recent decades, many cities have become densely populated due to increased urbanization, and the transportation infrastructure system has been heavily used. The downtime of important parts of the infrastructure, such as tunnels and bridges, seriously affects the transportation system’s efficiency. For this reason, a safe and reliable infrastructure network is necessary for the economic growth and functionality of cities. At the same time, the infrastructure is ageing in many countries, and continuous inspection and maintenance are necessary. Nowadays, detailed inspections of large infrastructure are almost exclusively performed by inspectors on site, which is both time-consuming and subject to human errors. However, the recent technological advancements in computer vision, artificial intelligence (AI), and robotics have opened up the possibilities of automated inspections. Today, semiautomatic systems such as drones and other mobile mapping systems are available to collect data and reconstruct 3D digital models of infrastructure. This significantly decreases the downtime of the infrastructure, but both damage detection and assessments of the structural condition are still manually performed, with a high impact on the efficiency and accuracy of the procedure. Ongoing research has shown that deep-learning methods, especially convolutional neural networks (CNNs) combined with other image processing techniques, can automatically detect cracks on concrete surfaces and measure their metrics (e.g., length and width). However, these techniques are still under investigation. Additionally, to use these data for automatically assessing the structure, a clear link between the metrics of the cracks and the structural condition must be established. This paper presents a review of the damage of tunnel concrete lining that is detectable with optical instruments. Thereafter, state-of-the-art autonomous tunnel inspection methods are presented with a focus on innovative mobile mapping systems for optimizing data collection. Finally, the paper presents an in-depth review of how the risk associated with cracks is assessed today in concrete tunnel lining. Full article

Sensing performance is crucial for real-world applications of the embedded piezoelectric lead zirconate titanate (PZT) sensors in concrete structures. Based on the electromechanical impedances (EMIs) obtained numerically and experimentally from the embedded PZT sensors, effects of installation orientation and interfacial roughness were investigated on their sensitivity and reliability for quantitative concrete stress monitoring. The numerical results suggest a better sensitivity in the embedded 90° PZT sensors, with planar normal perpendicular to the loading direction, where the conductance amplitude variation is 6.5 times of that of the 0° PZT sensors, with normal parallel to load direction. Further, the improved reliability of the PZT sensors with rough interfaces is observed experimentally, which makes them robust for concrete stress monitoring over a wider sensing range from 0 to 20 MPa. Based on the static analyses, it is noted that the sensing performance of the embedded sensor is significantly affected by the interfacial stiffness degradation induced by the enhanced strain surrounding the sensor. These findings suggest that delaying the interfacial stiffness degradation, i.e., with proper installation orientation and interfacial treatment, could improve the sensing performance of the embedded sensors for quantitative concrete stress monitoring. Full article

With the refinement of the urban transportation network, more and more passengers choose the combined mode. To provide better inter-trip services, it is necessary to integrate and forecast the passenger flow of multi-level rail transit network to improve the connectivity of different transport modes. The difficulty of multi-level rail transit passenger flow prediction lies in the complexity of the spatiotemporal characteristics of the data, the different characteristics of passenger flow composition, and the difficulty of research. At present, most of the research focuses on one mode of transportation or the passenger flow within the city, while the comprehensive analysis of passenger flow under various modes of transportation is less. This study takes the key nodes of the multi-level rail transit railway hub as the research object, establishes a multi-task learning model, and forecasts the short-term passenger flow of rail transit by combining the trunk railway, intercity rail transit and subway. Different from the existing research, the model introduces convolution layer and multi-head attention mechanism to improve and optimize the Transformer multi-task learning framework, trains and processes the data of trunk railway, intercity railway, and subway as different tasks, and considers the correlation of passenger flow of trunk railway, intercity railway, and subway in the prediction. At the same time, a new residual network structure is introduced to solve the problems of over-fitting, gradient disappearance, and gradient explosion in the training process. Taking the large comprehensive transportation hub in Guangzhou metropolitan area as an example, the proposed multi-task learning model is evaluated. The improved Transformer has the highest prediction accuracy (Average prediction accuracy of passenger flow of three traffic modes) 88.569%, and others methods HA, FC-LSTM and STGCN are 81.579%, 82.230% and 81.761%, respectively. The results show that the proposed multi-task learning model has better prediction performance than the existing models. Full article

Many transportation infrastructures all around the world are facing new challenges in terms of ageing and loss of performance. The infrastructural asset managers are required to perform scrupulous control of the health condition of the infrastructures over time and to execute the required maintenance works. In this context, digital twin models of the infrastructures should have a key role to simplify and speed up the procedures for proper maintenance. This paper discusses the advantages of developing digital twin models for the management of infrastructures, with a focus on bridges. In particular, the role of dynamic tests performed on bridges for the development of digital twin models is addressed, paying attention to test procedures and requirements. Issues such as the quality of instrumentation, the numerosity, and layout of sensors, and the acquisition and post-processing procedures are addressed through applications to two real bridge case studies. Both infrastructures are multi-span pre-stressed RC bridges that were dynamically tested after the restoration and seismic upgrading works. Results of ambient vibration tests and operational modal analyses are described, providing an idea of dynamic test requirements, as well as their use within the framework of the digital twin model creation. Full article

Existing railways can no longer meet transportation requirements, and it is an urgent need to expand old tunnels. However, the existence of ventilations shaft makes expansions face greater risks. This study analyzed the tangential stress change trend during the expansion process through field monitoring, and numerical simulation was used to analyze the changes in stress and displacement under different shaft depths and width–span ratios. The results show that as one approaches the tunnel face, the tangential stress in the arch foot and side wall of the J-2 and J-3 sections gradually increased, and the tangential stress in the arch foot and side wall of the J-1 section gradually decreased. The distance of the tunnel expansion’s influence on tangential stress is about 0.91 to 1.45 times the tunnel span. The largest value of vertical displacement had a linear relationship with shaft depth, and the largest value of horizontal displacement had a quadratic relationship with shaft depth. Changes in the width–span ratio only had a greater impact on the ventilation shaft section. These results can provide a reference for similar in situ expansion projects. Full article

The public transportation priority strategy is a significant way to alleviate urban traffic congestion, and the urban public transport mode share (UPTMS) is a crucial indicator to measure the performance of public transportation priority strategies. To explore the influence factors of UPTMS, this study hypothesized that UPTMS is influenced by factors such as population, economy, road operation performance, public transport infrastructure, and private transport facilities, and tested the hypotheses using structural equation modeling (SEM) and Bayesian structural equation modeling (BSEM) based on urban macro economic and transport data in Guangzhou and Beijing, China. The results showed that, in the case of a small sample, BSEM is more adept at examining the correlation between the UPTMS and its influencing factors than SEM; in the Guangzhou and Beijing models, public transport infrastructure has the greatest positive and most significant impact on the UPTMS, and road operation performance has the greatest negative and most significant impact. Moreover, road operation performance is significantly improved by public transport infrastructure, while private transport facilities have a significant negative influence on road operation performance. Full article

The stress release ratio of the surrounding rock in tunnel excavation is one of the most important indicators that affect the stress distribution and displacement of the surrounding rock. To determine the variation law of the stress release ratio of the surrounding rock during excavation in silty clay stratum, the stress release law is determined based on the convergence–confinement method (CCM) and field test data. The stress release law of the surrounding rock under support is determined based on the displacement back analysis method. The permitted displacement safety factor of silty clay under different subgrade conditions and the optimal supporting time of the initial supporting structure are determined by comparing the stress release ratio with surrounding rock displacement. The results indicated that the stress release ratio of surrounding rock in the silty clay stratum is approximately 78–90% when the coordinate displacement of the supporting structure and surrounding rock is stable under the current excavation and support conditions. For the surrounding rock of subgrade V in the silty clay stratum, the safety factor of the permitted displacement in the tunnel vault is approximately 2.91, and the initial support should be carried out within 1 m behind the face advancing. For the surrounding rock of subgrade VI1, the safety factor of the permitted displacement is 1.40, and the initial support must be carried out 1 m ahead of the tunnel face. For the surrounding rock of grade VI2, the initial support must be carried out 4 m ahead of the tunnel face. Full article

Image-based inspection technologies involving various sensors and unmanned aerial vehicles are widely used for facility inspections. The level of data analysis technology required to process the acquired data algorithmically (e.g., image processing and machine learning) is also increasing. However, compared with their development rate, the applicability of new inspection technologies to actual bridges is low. In addition, only individual technologies (for inspecting specific deteriorations) are being developed; integrated inspection systems have been neglected. In this study, the bottom-up method (which systematizes the applications of a specific technology) is avoided; instead, several technologies are summarized and a system of preliminary frameworks is established using a top-down method, and the applicability of each technology is verified in a testbed. To this end, the utility of the initially constructed technical system was assessed for two bridges; then, a strong utility technology was selected and applied to an offshore bridge under extreme conditions. The data obtained from the inspection were accumulated in a database, and a 3D-type external inspection map was produced and applied in the subsequent inspection via virtual and augmented reality equipment. Through the system, it was possible to obtain cost-effective and objective bridge inspection images in extreme environments, and the applicability of various technologies was verified. Full article

Accurately recognizing the influence of excavation disturbance on the traversing cross-type deep foundation pit of the subway, determining the active range of the disturbance, and reasonably arranging the structure within its range can effectively ensure the safety of the project and save resources to achieve the goal of sustainable development. A three-dimensional model was established using the soil small strain hardening model to examine the subway deep foundation pit project in the CBD (central business district) core area of Fuzhou Coastal New City, where the soil is mainly soft soil with high natural water content, high compressibility, and weak permeability. The model was verified against the theoretical solution of Melan, and the deformation characteristics of the cross-asymmetric foundation pit excavation were analyzed. The results show that, due to repeated disturbance from excavation and unloading between the foundation pits, the soil arching effect, and changes in the boundary conditions, the structure at the intersection and the surrounding soil interact. The horizontal displacement of the retaining structure and the surrounding surface settlement are quite different from those observed from a single foundation pit excavation. For instance, the maximum horizontal displacement of profile 1-3 in Zone I decreases by 26.1%, while the maximum horizontal displacement of profile 1-1 in Zone II increases by 20.4%, and the maximum surface settlement around the profiles also has similar characteristics. The disturbance on the retaining structure and soil in different areas at the intersection can be divided into positive and negative effects. The active range of the “disturbance influence zone” is determined: the foundation pit of Metro Line 6 is 3.5 He and the foundation pit of Metro Line F1 is 3.0 He. Finally, the influence of changes in the groundwater level on the active range of the “disturbance influence zone” is discussed. Full article

Intense electromagnetic pulses are electromagnetic waves with sharp rise time, high field strength and short duration. They have attracted more and more attention in recent years because they can cause destructions or malfunctions of some key national core infrastructures, such as power grids, communication and financial networks, etc. Hence, it is important to harden these facilities to ensure that they can survive in the face of electromagnetic pulse attacks. A direct way to investigate the vulnerabilities of these facilities is placing them in the electromagnetic environments generated by EMP simulators. However, the scale of facilities under test are limited by the working volumes of simulators. With the increase in working volumes and field strength, the price and technical difficulty of simulators are increased. Therefore, low cost and sustainable test methods to investigate vulnerabilities of large-scale systems against EMP are proposed in this study. The study takes advantage of continuous wave immersion (CWI) test and pulse current injection (PCI) test methods, which are low cost and sustainable to predict the pulse responses and assess the nonlinear effect of large-scale facilities under EMP attacks. In a CWI test, the magnitude of the transfer function of large-scale systems or facilities can be measured, and the corresponding phase information of the transfer function can be reconstructed by minimum phase algorithm (MPA) if the systems meet the minimum phase condition. After acquiring the entire information of the transfer function, we can predict the responses of a system under threat-level EMP attacks. However, these responses are obtained under the assumption that the system does not have nonlinear effects. Because the CWI is a low-level test, it cannot simulate the threat-level EMP attacks. In the PCI test proposed here, a bulky pulse current is coupled into the system to stimulate enough current intensity, just as the system was attacked by threat-level EMPs. In this situation, the system would be destroyed, or any other nonlinear effect would occur in the system. After that, the problem is to determine the quantities of the injected current, and a few kinds of norms are introduced in this paper to define the quantities. The method proposed here innovatively takes the experimental results of CWI as reference inputs of PCI tests. In this paper, the accuracy of the response prediction is validated by means of simulations and experiments. Results show that as a low-level test method in the frequency domain, the CWI test method can not only analyze couplings of external electromagnetic energy from frequency domain but also predict responses of the facilities under high amplitude electromagnetic pulses. The nonlinear effect of large-scale facilities can be assessed by applying the PCI test method with the results from CWI prediction. Therefore, if infrastructures or facilities are too large to be tested under EMP simulators, an alternative approach is to carry out the CWI and PCI experiments. Full article

For the safe and efficient operation of dams, frequent monitoring and maintenance are required. These are usually expensive, time consuming, and cumbersome. To alleviate these issues, we propose applying a wave-based scheme for the location and quantification of damages in dams. To obtain high-resolution “interpretable” images of the damaged regions, we drew inspiration from non-linear full-multigrid methods for inverse problems and applied a new cyclic multi-stage full-waveform inversion (FWI) scheme. Our approach is less susceptible to the stability issues faced by the standard FWI scheme when dealing with ill-posed problems. In this paper, we first selected an optimal acquisition setup and then applied synthetic data to demonstrate the capability of our approach in identifying a series of anomalies in dams by a mixture of reflection and transmission tomography. The results had sufficient robustness, showing the prospects of application in the field of non-destructive testing of dams. Full article

With the gradual maturity of the terrestrial laser scanners (TLS) technology, it is widely used in the field of deformation monitoring due to its fast, automated, and non-contact data acquisition capabilities. The TLS technology has changed the traditional deformation monitoring mode which relies on single-point monitoring. This paper analyzes the application of TLS in deformation monitoring, especially in the field of ground surface, dam, tunnel, and tall constructions. We divide the methods for obtaining ground surface deformation into two categories: the method based on point cloud distance and the method based on displacement field. The advantages and disadvantages of the four methods (M2M, C2C, C2M, M3C2) based on point cloud distance are analyzed and summarized. The deformation monitoring methods and precisions based on TLS for dams, tunnels, and tall constructions are summarized, as well as the various focuses of different monitoring objects. Additionally, their limitations and development directions in the corresponding fields are analyzed. The error sources of TLS point cloud data and error correction models are discussed. Finally, the limitations and future research directions of TLS in the field of deformation monitoring are presented in detail. Full article

The traditional method of designing freeway geometric characteristics may not well consider traffic safety and evaluation problems associated with vehicle, driver, road, and environmental features. This paper looks into accident-prone compound curves and puts forward a traffic safety evaluation method that can comprehensively assess various influencing factors. This method integrates driving simulation and Virtual Reality (VR) technology. Methodically, this paper first used three-dimensional (3D) design software to build the digital model and spatial scene model of the compound curves from the aspects of geometric structure, spatial characteristics, terrain information, and so on. Next, drivers were invited to conduct a series of driving simulation experiments upon the human–computer interaction safety experience platform, and driver physiological data and vehicle driving information collected. Last but not least, the mean values of heart rate changes, steering wheel angle changes, and driving trajectory changes were derived to synthesise the comprehensive traffic safety evaluation framework. Based on the analysis of the results of the orthogonal test, select the road plane design indicators that have a significant impact on the traffic safety evaluation, and carry out regression analysis. The research shows that the novel traffic safety evaluation method integrating with VR technology can comprehensively consider various influencing factors, and designers can dynamically adjust the design metrics according to the traffic safety level. Full article

Ocean platforms that are under complex sea conditions and loads for long periods are prone to fatigue cracks. These cracks may lead to large deformations, even displacement, of the platform, and should be monitored to ensure engineering safety. Cracks are not easily detected in the micro stage and small levels of strain measurement are required to ensure high accuracy. Furthermore, cracks are prone to suddenly developing into large deformations, especially in structural connections in practical engineering. This study developed a novel adaptive range strain sensor for structural crack monitoring that can monitor the whole structural crack propagation process in ocean platforms. The strain sensor is used for micro deformation monitoring through its fiber Bragg grating (FBG) sensor with high sensitivity. The sensor can automatically adapt to crack fractures and provide warnings through an STM32 single-chip microcomputer (SCM) system when the structure suddenly cracks, causing large deformation. The experimental results demonstrate that the device has high precision in micro measurement with the ability to capture structural fractures. The field application shows the high strain sensitivity of the sensor in crack monitoring, which indicates that the adaptive range strain sensor is suitable for the structural crack monitoring of ocean platforms. Full article

Hollow slab bridges are the most widely used form of small- and medium-span bridges. The existing research on the dynamic characteristics of hollow slab bridges is mostly based on numerical models, but there is a lack of theoretical analyses of their dynamic characteristics. In this paper, the relationship between the dynamic characteristic parameters and structural parameters of a hollow slab bridge is explored theoretically. Firstly, the solid model of a hollow slab bridge was established, and a modal analysis was carried out on it as a reference. Then, an orthotropic plate was used as an equivalent dynamic analysis model, and the analytical form of the transverse modal shape was deduced based on Kirchhoff thin plate theory. Furthermore, one hinge joint was considered as being equivalent to the elastic support boundary, and the local structure and the equivalent elastic support boundary were used to reflect the transverse modal shape of the original structure. The analysis shows that the influence of hinge joints on the transverse modal shape is mainly reflected in the transmission of bending deformation. Through comparison and verification, the results show that the analytical expression of the transverse modal shape can well describe the low-order transverse modal shape of a hollow slab bridge. Full article

Safety risk identification is the premise and foundation of safety risk management for railway construction. However, due to some characteristics of railway projects, which include large volumes of work, complex construction environments, and long construction cycles, etc., the risk factors of railway projects are often hidden in all stages of engineering construction. It results in the comprehensive identification of safety risks of railway projects being usually difficult, and this problem is more serious when the railway is constructed in complex and dangerous areas. Therefore, to identify the safety risks comprehensively, this paper constructs a safety risk identification method applicable to railway construction in complex and dangerous areas. This method studies the spatial and temporal distribution of risks and their relationship with subprojects by using a work breakdown structure (WBS), a risk breakdown structure (RBS), grid-based management, and forming a safety risk identification matrix, which can help researchers analyze the characteristics of risks. In order to verify the effectiveness of the method, the A Railway, which is located in the western of China, was selected as a case study, and risk identification for its civil engineering was carried out. The research results show that in the construction process of the A Railway, the main types of safety risks suffered by various branch projects were different. In addition, some risk factors only appeared at specific times in space, and there is a strong interaction between these risk factors. Based on this method, safety risk identification can intuitively discover the spatial and temporal distribution of risk factors and analyze the interaction between risk factors, which can provide help for the formulation of targeted risk control measures. Full article

The penetration characteristics of the slurry and the support pressure transfer mechanisms are critical to the tunnel face stability control during a mechanized excavation. In this paper, numerical calculations coupling computational fluid dynamics (CFD) with the discrete element method (DEM) are carried out to simulate sand column penetration tests considering different particle size ratios. The reasonableness of the numerical model is verified by comparing the variation patterns of the soil permeability coefficients monitored in the numerical tests with the results of existing laboratory tests. The mesoscopic transport characteristics of the slurry particles in the sand soil pores are considered based on numerical tests, while the slurry support effects corresponding to different penetration types are evaluated. Three main basic types of slurry infiltration are observed due to the different ratios of slurry particle size over soil pore size. For the first penetration type, the slurry particles are accumulated and able to form a supporting filter cake. The slurry support is effective because of the significant pressure drop generated on both sides of the filter cake. For the second penetration type, both a filter cake and an infiltration zone are present. A dense filling network is formed between the filter cake and the penetration zone. The third type corresponds to a purely penetration zone. An effective impermeable filling network cannot be formed, and the slurry support effect is not obvious. The development of slurry penetration distance shows an obvious time effect; the farther the penetration distance, the larger the slurry filtration loss, and the worse the transformation effect of slurry support pressure. Full article

The article proposes the use of a semi-rigid energy-dissipation connection combined with a U-shaped metal damper to avoid brittle failure of rigid steel beam–column connections under seismic loading. The U-shaped metal damper connects the H-section column and the H-section beam to form a new energy-dissipation connection as an energy-dissipation member. Compared with the existing research, this connection has a stable energy-dissipation performance and great ductility. To clarify the mechanism of energy dissipation, mechanical models under two U-shaped damping deformation modes are established. The calculation formulas for the yield load and stiffness are derived for the corresponding deformation mode using the unit load method. Taking the T-shaped beam–column connection and the application of U-shaped steel damper in the beam–column connection as an example, the mechanical model of the connection is established and the calculation formulas for the yield load and stiffness are derived. At the same time, the connection is subjected to a quasi-static test under cyclic loading. The results show that the hysteretic curve of the test is complete and that the skeleton curve is accurate compared to the theory. The error range of the initial stiffness and yield load obtained by the test and the theoretical formula is kept within 20%, indicating that the theoretical formula is reasonable and feasible. In addition, the correctness of the finite element model is verified by establishing a finite element model and comparing it with the test. The mechanical responses of purely rigid connections and rigid semi-rigid composite connections are compared and analyzed using a multi-story and multi-span plane frame as an example. The results show that the model with semi-rigid connections, compared to the model with rigid connections, avoids the gradual loss of bearing capacity caused by the failure of the connection area of the second floor of the main structure and improves the seismic performance of the main structure. Full article

Road maintenance is a key aspect of road safety and resilience. Traffic signs are an important asset of the road network, providing information that enhances safety and driver awareness. This paper presents a method for the recognition and geolocation of vertical traffic signs based on artificial intelligence and the use of a low-cost mobile mapping system. The approach developed includes three steps: First, traffic signals are detected and recognized from imagery using a deep learning architecture with YOLOV3 and ResNet-152. Next, LiDAR point clouds are used to provide metric capabilities and cartographic coordinates. Finally, a WebGIS viewer was developed based on Potree architecture to visualize the results. The experimental results were validated on a regional road in Avila (Spain) demonstrating that the proposed method obtains promising, accurate and reliable results. Full article