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Surface cracks are alluded to as one of the early signs of potential damage to infrastructures. In the same vein, their detection is an imperative task to preserve the structural health and safety of bridges. Human-based visual inspection is acknowledged as the most prevalent means of assessing infrastructures' performance conditions. Nonetheless, it is unreliable, tedious, hazardous, and labor-intensive. This state of affairs calls for the development of a novel YOLOv8-AFPN-MPD-IoU model for instance segmentation and quantification of bridge surface cracks. Firstly, YOLOv8s-Seg is selected as the backbone network to carry out instance segmentation. In addition, an asymptotic feature pyramid network (AFPN) is incorporated to ameliorate feature fusion and overall performance. Thirdly, the minimum point distance (MPD) is introduced as a loss function as a way to better explore the geometric features of surface cracks. Finally, the middle aisle transformation is amalgamated with Euclidean distance to compute the length and width of segmented cracks. Analytical comparisons reveal that this developed deep learning network surpasses several contemporary models, including YOLOv8n, YOLOv8s, YOLOv8m, YOLOv8l, and Mask-RCNN. The YOLOv8s + AFPN + MPDIoU model attains a precision rate of 90.7%, a recall of 70.4%, an F1-score of 79.27%, mAP50 of 75.3%, and mAP75 of 74.80%. In contrast to alternative models, our proposed approach exhibits enhancements across performance metrics, with the F1-score, mAP50, and mAP75 increasing by a minimum of 0.46%, 1.3%, and 1.4%, respectively. The margin of error in the measurement model calculations is maintained at or below 5%. Therefore, the developed model can serve as a useful tool for the accurate characterization and quantification of different types of bridge surface cracks. [ABSTRACT FROM AUTHOR]

Presently, the prevailing approaches to assessing hinge joint damage predominantly rely on predefined damage indicators or updating finite element models (FEMs). However, these methods possess certain limitations. The damage indicator method requires high-quality monitoring data and demonstrates variable sensitivities of distinct indicators to damage. On the other hand, the FEM approach mandates a convoluted FEM update procedure. Hinge joint damage represents a major kind of defect in prefabricated assembled multi-girder bridges (AMGBs). Therefore, effective damage detection methods are imperative to identify the damage state of hinge joints. To this end, a stiffness-based method for the performance evaluation of hinge joints of AMGBs is proposed in this paper. The proposed method estimates hinge joint stiffness by solving the characteristic equations of the multi-beam system. In addition, this study introduces a method for determining baseline joint stiffness using design data and FEM. Subsequently, a comprehensive evaluation framework for hinge joints is formulated, coupling a finite element model with the baseline stiffness, thereby introducing a damage indicator rooted in stiffness ratios. To verify the effectiveness of the proposed method, strain and displacement correlations are analyzed using actual bridge monitoring data, and articulation joint stiffness is identified. The results underscore the capability of the proposed method to accurately pinpoint the location and extent of hinge joint damage. [ABSTRACT FROM AUTHOR]

Explicit sampling of and connecting to light sources is often essential for reducing variance in Monte Carlo rendering. In dense, forward‐scattering participating media, its benefit declines, as significant transport happens over longer multiple‐scattering paths around the straight connection to the light. Sampling these paths is challenging, as their contribution is shaped by the product of reciprocal squared distance terms and the phase functions. Previous work demonstrates that sampling several of these terms jointly is crucial. However, these methods are tied to low‐order scattering or struggle with highly‐peaked phase functions. We present a method for sampling a bridge: a subpath of arbitrary vertex count connecting two vertices. Its probability density is proportional to all phase functions at inner vertices and reciprocal squared distance terms. To achieve this, we importance sample the phase functions first, and subsequently all distances at once. For the latter, we sample an independent, preliminary distance for each edge of the bridge, and afterwards scale the bridge such that it matches the connection distance. The scale factor can be marginalized out analytically to obtain the probability density of the bridge. This approach leads to a simple algorithm and can construct bridges of any vertex count. For the case of one or two inserted vertices, we also show an alternative without scaling or marginalization. For practical path sampling, we present a method to sample the number of bridge vertices whose distribution depends on the connection distance, the phase function, and the collision coefficient. While our importance sampling treats media as homogeneous we demonstrate its effectiveness on heterogeneous media. [ABSTRACT FROM AUTHOR]

The study designed a risk assessment scheme to reduce the risk of highway bridge construction in highland mountainous areas, and optimised the existing hierarchical analysis method used for risk weight calculation, using entropy weight and fuzzy numbers for improvement, and designed an optimised fuzzy hierarchical entropy weight comprehensive risk assessment model. The results found that the maximum affiliation degree of site safety management risk is 0.39, which is a low-level risk; the maximum affiliation degree of personnel safety and operation quality category is 0.42, which is an intermediate risk; the maximum affiliation degree of machinery and equipment is 0.40, which is a high-level risk; the maximum affiliation degree of construction materials is 0.69, which is a low-level risk; and the maximum affiliation degree of environment category is 0.51, which is an intermediate risk. The maximum affiliation of the overall construction risk is 0.369, which indicates that the fuzzy comprehensive evaluation of the project is an intermediate risk. The results of the study show that the proposed construction risk assessment scheme for highway bridges in highland mountainous areas can provide certain reference for the construction of highland mountainous areas and avoid the corresponding safety risks. [ABSTRACT FROM AUTHOR]

Background: Auto‐segmentation of organs‐at‐risk (OARs) in the head and neck (HN) on computed tomography (CT) images is a time‐consuming component of the radiation therapy pipeline that suffers from inter‐observer variability. Deep learning (DL) has shown state‐of‐the‐art results in CT auto‐segmentation, with larger and more diverse datasets showing better segmentation performance. Institutional CT auto‐segmentation datasets have been small historically (n < 50) due to the time required for manual curation of images and anatomical labels. Recently, large public CT auto‐segmentation datasets (n > 1000 aggregated) have become available through online repositories such as The Cancer Imaging Archive. Transfer learning is a technique applied when training samples are scarce, but a large dataset from a closely related domain is available. Purpose: The purpose of this study was to investigate whether a large public dataset could be used in place of an institutional dataset (n > 500), or to augment performance via transfer learning, when building HN OAR auto‐segmentation models for institutional use. Methods: Auto‐segmentation models were trained on a large public dataset (public models) and a smaller institutional dataset (institutional models). The public models were fine‐tuned on the institutional dataset using transfer learning (transfer models). We assessed both public model generalizability and transfer model performance by comparison with institutional models. Additionally, the effect of institutional dataset size on both transfer and institutional models was investigated. All DL models used a high‐resolution, two‐stage architecture based on the popular 3D U‐Net. Model performance was evaluated using five geometric measures: the dice similarity coefficient (DSC), surface DSC, 95th percentile Hausdorff distance, mean surface distance (MSD), and added path length. Results: For a small subset of OARs (left/right optic nerve, spinal cord, left submandibular), the public models performed significantly better (p < 0.05) than, or showed no significant difference to, the institutional models under most of the metrics examined. For the remaining OARs, the public models were inferior to the institutional models, although performance differences were small (DSC ≤ 0.03, MSD < 0.5 mm) for seven OARs (brainstem, left/right lens, left/right parotid, mandible, right submandibular). The transfer models performed significantly better than the institutional models for seven OARs (brainstem, right lens, left/right optic nerve, left/right parotid, spinal cord) with a small margin of improvement (DSC ≤ 0.02, MSD < 0.4 mm). When numbers of institutional training samples were limited, public and transfer models outperformed the institutional models for most OARs (brainstem, left/right lens, left/right optic nerve, left/right parotid, spinal cord, and left/right submandibular). Conclusion: Training auto‐segmentation models with public data alone was suitable for a small number of OARs. Using only public data incurred a small performance deficit for most other OARs, when compared with institutional data alone, but may be preferable over time‐consuming curation of a large institutional dataset. When a large institutional dataset was available, transfer learning with models pretrained on a large public dataset provided a modest performance improvement for several OARs. When numbers of institutional samples were limited, using the public dataset alone, or as a pretrained model, was beneficial for most OARs. [ABSTRACT FROM AUTHOR]

In April 2021 Stavå bridge, a main bridge on E6 in Norway, was abruptly closed for traffic. A structural defect had seriously compromised the bridge's structural integrity. The Norwegian Public Roads Administration (NPRA) closed it, made a temporary solution and reopened with severe traffic restrictions. The incident was alerted through what constitutes the bridge's Digital Twin processing data from Internet of Things sensors. The solution was crucial in online and offline diagnostics, the case demonstrating the value of technologies to tackle emerging dangerous situations as well as acting preventively. A critical and rapidly developing damage was detected in time to stop the development, but not in time to avoid the incident altogether. The paper puts risk in a broader perspective for an organization responsible for highway infrastructure. It positions online monitoring and Digital Twins in the context of Risk- and Condition-Based Maintenance. The situation that arose at Stavå bridge, and how it was detected, analysed, and diagnosed during virtual inspection, is described. The case demonstrates how combining physics-based methods with Machine Learning can facilitate damage detection and diagnostics. A summary of lessons learnt, both from technical and organisational perspectives, as well as plans of future work, is presented. [ABSTRACT FROM AUTHOR]

As the world's transport infrastructure ages, the importance of bridge condition monitoring is becoming increasingly acknowledged. Large-scale deployment of existing inspection and monitoring techniques is infeasible due to cost and logistical challenges. The concept of using sensors located within vehicles for low cost 'drive-by' monitoring has become the focus of much attention in recent years. This paper presents a new data-driven approach for drive-by bridge monitoring. Machine learning techniques are leveraged to allow the influence of vehicle speed to be considered and the Operating Deflection Shape Ratio (ODSR) is presented as an alternative damage-sensitive feature to the commonly used frequency spectrum. Extensive laboratory experiments demonstrate that the method is capable of detecting midspan cracking and seized bearings. A statistical classification approach is adopted to classify damage indicators as either 'damaged' or 'healthy'. Classification accuracy is seen to vary between 65-96% and is similar whether using the frequency spectrum or ODSR. Based on the results of the laboratory testing, it is expected that this approach could be implemented on a large scale to act as an early warning tool for infrastructure owners to identify bridges presenting signs of distress or deterioration. [ABSTRACT FROM AUTHOR]

The First Egongyan Bridge in Chongqing, China was opened to traffic on December 27, 2000. It carries six-lanes of city traffic and two pedestrian paths, one on each side. It is a 600 m span suspension bridge. It was planned that the two pedestrian paths might eventually be converted to transit tracks in the future. However, with the rapid increase in urban traffic, the deck was transformed into an 8-lane bridge instead. Therefore, a new bridge parallel and adjacent to the old bridge was built for the rail transit. For aesthetic reasons, the city decided that the new bridge should also be a suspension bridge, with the same span length and tower height as the first bridge. The First Egongyan Bridge was a true suspension bridge with main cables anchored to ground anchors. However, the new bridge bridge's proximity to the first bridge necessitated the construction of a self-anchored suspension bridge that did away with a second set of ground anchors. This 600 m span happened to be the world's longest span for a self-anchored suspension bridge. [ABSTRACT FROM AUTHOR]

In the evaluation of existing bridges and viaducts, relying solely on a desk study is often inadequate for determining their structural reliability. Performing a proof load test provides valuable field data that offers detailed information about the structural integrity. However, the relation between the magnitude of the load and the structural reliability is not immediately clear. This study addresses the challenges associated with determining the target load and highlights the uncertainties that play a key role. A case study is presented that shows the time-dependent character of the structural reliability and the influence of an informative and a weakly informative prior distribution in a Bayesian context. It is shown how both past traffic loads and a proof load test may contribute to the proven strength of a structure. The described method provides a starting point towards a flexible approach for proof load testing in which structure-specific knowledge levels and requirements are considered. [ABSTRACT FROM AUTHOR]

Many recent collapses concerned old bridges, but also modern ones, often having the same age, the same types of materials, and the same technologies. Therefore, it is crucial to analyse the errors and vulnerabilities highlighted by these failures and understand their causes to improve design, construction technologies, inspection, and maintenance criteria and avoid malfunctions and collapses in the future. Among the collapses of recent history, that of the viaduct over the Polcevera River in Genoa has been one of the most severe in terms of the number of victims, the relevance of the bridge, and economic repercussions. General information about the bridge is summarised, and the activities of forensic engineering carried out after the collapse are shortly reported. The paper concludes by presenting initiatives undertaken by the Italian Government to thoroughly control and verify existing bridges and plan the renewal of the national infrastructural network. [ABSTRACT FROM AUTHOR]

This article proposes an innovative concept of an intelligent bridge system that integrates sensors, a processing unit, and an actuator to maintain bridge safety and performance even in the face of unexpected environmental changes and disturbances. Although technically challenging, this system is an exciting prospect for young engineers who aspire to contribute to cutting-edge technological advancements. As a practical example, this article presents an ICT-based bridge remote monitoring system called the "Intelligent Bridge," which allows real-time monitoring and control during extreme events such as earthquakes and typhoons. The Intelligent Bridge comprises a stand-alone monitoring system and a web-based internet monitoring system for bridge maintenance, which is introduced as an intelligent structure integrated into the intelligent bridge system. To verify the validity of the proposed system, it is investigated the ability to adjust cable forces on a 2-span continuous cable-stayed bridge model to control its structural performance. The development of an intelligent bridge system represents a significant advancement in bridge engineering and has the potential to improve the safety and longevity of bridges, particularly in areas prone to extreme environmental events. The system proposed in this article has practical applications that can benefit both engineers and the general public. [ABSTRACT FROM AUTHOR]

To estimate the connectivity of a road network, it is crucial to evaluate the correlation of hazard intensities among individual bridge locations since the probability of multiple bridges being damaged simultaneously depends on the degree of this correlation. However, research on connectivity assessment of bridge networks considering spatial correlations associated with flood intensities is scarce in the literature. When quantifying the spatial correlation of flood intensities, modeling based on the stream distance rather than the Euclidean distance is required, taking into account that river flow is restricted only within the stream network. To achieve this purpose, a novel methodology is proposed to evaluate the spatial correlation of a stream network based on a geostatistical linear model and stream network covariance models. In addition, this study considers the spatial correlation of seismic hazard intensity. With the proposed method, it is possible to identify which bridges play an important role in ensuring the connectivity of the road network under multiple hazards, i.e. flood and seismic. As an illustrative example, the proposed method is applied to a hypothetical bridge network in Kumamoto Prefecture, Japan. The results demonstrate that improved network connectivity can be achieved by implementing a relevant retrofitting strategy for important bridges. [ABSTRACT FROM AUTHOR]

This article reports the process that allowed to check the condition of a steel railway bridge having a strategic position within the network. The framework representing the actions needed for the service life extension of the bridge is first described, then the conducted inspections are illustrated, together with the developed numerical analyses and the conception of specific tests on site. The conclusion, downstream of all these analyses and with the comparison of the real-life experiments, was to allow a limited extension of the useful life of the bridge, even with some reductions in the safety factor, respecting a reduction in the speed of railway trains and prescribing continuous monitoring of the bridge. In this context, all the test evaluations, combined with the surveillance/monitoring, and joined with an important numerical modelling activity, lead to the concept of "structural augmentation" of the bridge for service life extension purposes. The specific case of the examined bridge is supposed to be an example of good practice useful for infrastructure authorities. [ABSTRACT FROM AUTHOR]

This article presents a case study with various developments of digital twinning of a sample of load tests performed on several railways bridges. The case study is located in Extremadura, South Western Spain and its aim is the generation of a validated, multi-layered information construct in the form of a digital twin as the result of a load test. This result is conceived, not only to verify the assumptions of the design of the bridge but also, to optimize future maintenance plans of the network. This particular case study is framed within a vaster European effort on digitization of the construction sector. Research and Innovation Actions within this demo case are aimed at integrating routine requirements and procedures of load tests with cutting edge digital technologies for the generation of validated virtual replica of these physical bridges. The generated twins during these load tests behaviourally match the obtained response during loading and as such, represent an ideal model for future simulations and behavioural predictions. Different data-gathering techniques and numerical models are integrated within a Common Data Environment (CDE). All efforts related to measurement, simulation, 3D modelling, assessment and validation can be wrapped up systematically for further use during regular operation of the asset. [ABSTRACT FROM AUTHOR]

As the existing bridge stock is aging, the task of assessing these bridges becomes increasingly important. One of the assessment methods for existing bridges is load testing. Improvements in the field of diagnostic load testing are related to the use of numerical models. Improvements in the field of proof load testing focus on the safety of the execution of the test as well as the required load in the test. What is still lacking is a reflection of these recent advances in the codes and guidelines used for load testing of bridges. Two approaches are proposed to address this lack. The first approach attempts to answer fundamental questions with regard to bridge load testing through research. The second approach is to coordinate efforts and facilitate collaboration and exchange of ideas internationally through the IABMAS Technical Committee on Bridge Load Testing. In conclusion, it is expected that these efforts will form the basis of improved recommendations for the assessment of concrete bridges by load testing to be included in codes and guidelines and to serve the community of engineers faced with the task of assessing ageing infrastructure. [ABSTRACT FROM AUTHOR]

Standards for the design of bridges, buildings and other infrastructure specify design loads for climatic hazards such as temperature, snow, wind, and floods based on return periods presented in maps or tables that account for regional differences. These design loads were developed from statistical analyses of historical hazard data under the assumption that the past is representative of the future. Climate change may affect the frequencies and intensities of environmental hazards which, depending on regional variations, raises questions as to whether structures designed to current specifications will meet minimum safety standards over their future service lives. This paper critically appraises issues related to using historical hazard data for future designs. It reviews basic principles of uniform reliability, that modern design codes use as the basis for ensuring minimum levels of safety, describing the relationship between hazard return periods, structural reliability, risk and the maximum loads expected within a structure's service life. Simple examples involving wind effects on structures demonstrate how to calibrate structural design hazard maps for climate-related extreme events to meet the minimum standards of safety implied in current specifications. The paper also introduces a possible practical approach to account for climate change when designing new structures and assessing the safety of existing facilities. [ABSTRACT FROM AUTHOR]

Thanks to the capabilities of distributed fibre optic sensors (DFOS), a significant increase in their applications within civil and geotechnical engineering has been observed during the last few years. In contrast to conventional spot gauges, the main advantage of this technology is direct damage detection, as the information is gained over the entire measurement path. This diagnostic solution is especially suitable for safety-critical infrastructure, including bridges. However, to utilise the benefits of the DFOS approach, appropriate interrogators, sensors, and installation methods must be adopted. The article briefly discusses possible solutions available on the market, indicating their specific advantages and limitations. Then, several practical case studies related to bridge monitoring in Poland are presented. The review shows various possible applications, from long measurement sections over entire spans to small-size structural components. Some are truly new and pioneer solutions, solving different technical problems in bridge engineering. Presented applications supported by in situ data proved the possible high-quality performance of DFOS-based systems for measurements of concrete, steel and composite bridges in actual operating conditions. [ABSTRACT FROM AUTHOR]

Bridge network maintenance and rehabilitation activities are crucial to prevent bridge failure from human-made and natural hazards such as deterioration, overload, collision, fire, flooding, and earthquake. Under a limited budget, understanding the bridge closure cost to social-economic-environmental aspects can help prioritizing bridge network maintenance and rehabilitation in a cost-benefit justifiable manner. In this study, the costing method is applied to calculate social-economic-environmental costs incurred due to detour routes with additional travel time and distance. In addition to the commonly used cost factors of time value cost and vehicle running cost, this study also uses probability theory to calculate the expected consequence costs of delayed rescue services of ambulance, police, and fire-fighting caused by bridge closure. A case study with a bridge network is used to demonstrate the methodology adopted and outcome benefits from study. The results of case study show that the time value cost of vehicle passengers, vehicle running cost, and ambulance delay cost are the major cost contributors. The bridge importance ranking and consequence cost of bridge closure can be used to provide prioritized inspection and repair program for bridge components that have a high ranking under limited budget and provide benefit estimations. Practical Applications: In the real asset management of bridge networks, information on consequences of bridge closure is essential to bridge maintenance and rehabilitation (M&R) planning. For example, if the daily cost of bridge closure can be estimated particularly as a monetary value, the funding application for bridge M&R can be easily approved because it can show the M&R cost is lower than the benefit, which is to avoid the consequence cost of bridge closure. Furthermore, under a limited budget, bridges with a higher consequence cost of bridge closure in the bridge network can be prioritized for M&R planning. Understanding the consequence cost of bridge closure can also help in developing consequence-mitigated planning during actual bridge closures for planned repair. This study developed a costing methodology to estimate the daily consequence cost of bridge closure as a monetary value in terms of social-economic-environmental impacts. The results show that the time value cost of vehicle passengers and vehicle running cost are the most important contributors to the total consequence cost for bridges with available detour routes for crossing. For bridges with no alternative crossing routes, ambulance delay cost is the major contributor, followed by delay cost of police and fire-fighting services. [ABSTRACT FROM AUTHOR]

Background: The CRC‐VTE trial conducted in China revealed a significant occurrence of venous thromboembolism (VTE) in patients following colorectal cancer (CRC) surgery, raising concerns about implementing thromboprophylaxis measures. The present study aimed to identify and analyze inappropriate aspects of current thromboprophylaxis practices. Methods: This study performed an analysis of the CRC‐VTE trial, a prospective multicenter study that enrolled 1836 patients who underwent CRC surgery. The primary objective was to identify independent risk factors for VTE after CRC surgery using multivariate logistic regression analysis. Furthermore, among the cases in which VTE occurred, the appropriateness of thromboprophylaxis was assessed based on several factors, including pharmacologic prophylaxis, time to initiate prophylaxis, drug selection, drug dosage, and duration of pharmacologic prophylaxis. Based on the analysis of the current state of thromboprophylaxis and relevant clinical guidelines, a modified Delphi method was used to develop a clinical pathway for VTE prophylaxis after CRC surgery. Results: In this analysis of 1836 patients, 205 (11.2%) were diagnosed with VTE during follow‐up. The multifactorial analysis identified several independent risk factors for VTE, including age (≥70 years), female sex, varicose veins in the lower extremities, intraoperative blood transfusion, and the duration of immobilization exceeding 24 h. None of the patients diagnosed with VTE in the CRC trial received adequate thromboprophylaxis. The main reasons for this inappropriate practice were the omission of thromboprophylaxis, delayed initiation, and insufficient duration of thromboprophylaxis. We developed a specialized clinical pathway for thromboprophylaxis after CRC surgery to address these issues. Conclusions: This study offers a comprehensive nationwide evaluation of existing thromboprophylaxis practices in patients after CRC surgery in China. A specialized clinical pathway was developed to address the identified gaps and improve the quality of care. This clinical pathway incorporates explicit, tailored, detailed recommendations for thromboprophylaxis after CRC surgery. [ABSTRACT FROM AUTHOR]

• This manuscript firstly establishes a half vehicle-pavement-continuous beam bridge (VPCB) coupled system analytical model. • It is innovatively that the bridge and vehicle initial conditions are considered into analytical model. • The pavement road surface local deterioration is simulated by increasing the local roughness level of the road surface. At present, the highway bridge field is in a period of vigorous development, and the application of continuous beam bridges is becoming more extensive, so the related safety research is particularly important. However, there are few studies on the vehicle-bridge coupled interaction of continuous beam bridges, and the influence of pavement is not considered. In order to ensure that the theoretical research can better serve the engineering practice, it is urgent to establish a more refined and more complex vehicle-bridge coupled model. In this paper, a vehicle-pavement-continuous beam bridge (VPCB) coupled system model is established. A half-vehicle model is adopted, the pavement is simulated by a continuous and uniform spring damper, and the bridge is a three-span continuous beam bridge. The motion equation of VPCB system is established and deduced using D 'Alembert principle and modal superposition method. The dynamic responses of VPCB system are calculated by Newmark- β method. Here, the continuous beam bridge mode functions are fitted based on the modal vector of the continuous beam calculated by the finite element model. The correctness of the method is verified by existing literatures. The effects of bridge pavement, vehicle speed, bridge second span length, the pavement equivalent spring stiffness coefficient k p and damping coefficient c p , road roughness on VPCB system are studied. The results show that the pavement can reduce the bridge dynamic amplification factor (DAF) and the vehicle acceleration to improve the ride comfort. The dynamic responses of the vehicle and the bridge contain each other's natural frequencies. The responses of VPCB system increase with the vehicle velocity, the vehicle responses are more affected than the bridge responses. The pavement equivalent stiffness and damping coefficient has little effect on the system. The responses of vehicle and bridge increase with the increase of the bridge second span length. When the vehicle travels each span of the three-span continuous beam bridge, the time history curve of the pavement deformation under the tire resembles a sine wave. When the local roughness level of the road surface increases, the system responses at the deteriorated position suddenly increases, and the responses of the subsequent position will also be affected. The larger the roughness grade, the more obvious the responses increase. The effect on the system responses of the whole pavement damage is more significant than the local pavement damage. [ABSTRACT FROM AUTHOR]

The rapid and accurate postearthquake traffic capacity or functionality loss assessment for highway bridges after a strong earthquake is crucial to the decision-making for postearthquake emergency rescue and recovery, as well as seismic resilience analysis. The postearthquake traffic capacity of a simply supported highway girder bridge designed based on the capacity design philosophy is generally dominated by the loss of postearthquake vertical load-carrying capacity of the damaged bridge column, which, however, cannot be rapidly and quantitatively evaluated by previous studies. This study develops a postearthquake vertical load-carrying capacity loss model for flexure-dominated circular RC bridge columns using multiple linear regression, which is a function of column-related structural parameters and a selected damage indicator (i.e., residual drift ratio). The database of the postearthquake vertical load-carrying capacity loss for the damaged but before collapsed RC columns is generated through numerical simulations using a loading scheme consisting of nonlinear time-history analysis followed by pushdown analysis. In order to generate a sufficient database of the vertical capacity loss of RC columns, an incremental dynamic analysis (IDA) approach is adopted to produce different damage levels on the column. The significance of the loss regression model and the significance of each corresponding regression coefficient are checked by statistical tests. In addition, the generalization ability of the loss model is also tested by 10-fold cross-validation. After that, a probabilistic postearthquake vertical load-carrying capacity loss model is developed in this study. Based on this probabilistic model, a traffic capacity fragility curve conditioned on the residual drift ratio of a given column is proposed in this study for the first time to assess the remaining functionality of a given RC column. This proposed traffic capacity fragility curve is further validated by two example columns with and without considering the uncertainty, respectively. The traffic fragility curve can be quickly generated for the target circular RC bridge column and facilitate the postearthquake decision-making for the damaged but before-collapsed column, thus forwarding to the introduced rapid postearthquake assessment for simply supported highway girder bridges. [ABSTRACT FROM AUTHOR]

In this paper, we present an unscented Kalman filter (UKF) for fusion of information from an accelerometer, global navigation satellite system (GNSS) instrumentation, and rotational sensor recordings of structural motion. Seismic and structural motions do not only include translations, but further incorporate torsion and twisting of the ground and/or structural components. Accelerometer and GNSS positions are known to be prone to errors introduced by rotation, such as (1) gravitational leakage, (2) misorientation, and (3) antenna pole tilt. In alleviating such effects, we propose fusion of information from six component (6C) data—3C translation and 3C rotation—and demonstrate its applicability for motion tracking on a flexible pedestrian bridge. To simulate a variety of load effects, the bridge was subjected to various sources of excitation such as hammer impulses, jumping, twisting, and running, as well as a combination thereof named the "artificial coupled forcing." The rotation errors of both the accelerometer and GNSS-estimated positions are corrected via a UKF-based fusion. We further identify the modal properties of the monitored bridge, excited by the different excitation sources, using a covariance driven stochastic subspace identification. The twisting of the bridge is shown to be a primary source of rotation errors. These errors ought to be corrected because their order of magnitude can be as large as the actual signal in the case of GNSS positions and up to 10% for accelerometer sensors. We compare the proposed UKF-based fusion for 6C motion tracking against a simplified linear Kalman filter and demonstrate the potential of the former for real-time, broadband, rotation-free displacement, velocity, and rotations tracking. [ABSTRACT FROM AUTHOR]

The bidirectional ductile end diaphragm concept uses energy-dissipating buckling restrained braces (BRB) as fuses located at the end of a bridge superstructure's floating spans. This system using BRBs can provide seismic resilient and damage-free bridges fully operational immediately after an earthquake. A shake-table testing program was conducted to subject a 1/2.5-scale specimen to series of ground motions. The specimen tested represents one span of a five-span bridge having BRBs connected to the abutment and the pier next to it. The purpose of these tests was to experimentally validate proposed connection details when subjected to the three-dimensional (3D) displacement histories (compared with the axis of the BRBs) that resulted from bidirectional ground motions and the fact that the connections must accommodate inclined BRB layouts. The test protocol included earthquake displacement histories that represent design demands, cycles of thermal excitations, and (to eventually make the BRBs fail) extreme motions. The testing program validated the effectiveness of the proposed concept and the ability of BRBs to sustain multiple ground motions before failure. [ABSTRACT FROM AUTHOR]

Bridges are important physical structures in a cityscape. With spaces in urban areas, becoming increasingly precious and important, even the bridges and their columns have gained a significant role in voicing city stories. Art on bridges are cultural expressions of urban narratives. The presence of artwork on the bridges also reduces the chances of these sheltered places from becoming hubs for antisocial activities. The study analyses the role of art on three important bridges in Chennai expounding on the communicative city theory. Coming up after infrastructural developments in the city, the artwork on these bridges serves as representatives of urban narratives. They include stories of social equity, environmental awareness and city activities, thereby promoting a positive city identity. The study also denotes the importance of increased community engagement to advance individual and community based participation in creating sustainable cities and diverse city communities. [ABSTRACT FROM AUTHOR]

Objective: Numerous studies have reported that metformin can reduce the risk of tumor development. However, some of the results of these studies are conflicting, necessitating a more reliable evaluation. Methods: We conducted a Mendelian randomization phenome-wide association study (MR-PheWAS) of tumors to explore the causal relationship between metformin and tumors. Two cohorts of patients taking metformin were obtained from the UK Biobank. Complete phenotype data of the tumors were obtained from FinnGen_R10. We elucidated the causal relationship using a two-sample Mendelian randomization (MR) analysis. More importantly, we conducted a meta-analysis to ensure relatively unbiased results. In the MR analysis, we used the inverse-variance weighted (IVW) method as the main outcome indicator. Subsequently, two cohorts were integrated for the meta-analysis. Finally, we investigated the mechanisms through mediational MR analysis. Results: MR analysis revealed that metformin might have a causal relationship with 13 tumor-associated phenotypes in the training cohort. Four phenotypes were validated in the testing cohort. In the training and testing cohorts, metformin exhibited a protective effect against brain meningiomas and malignant neoplasms of the breast (HER-positive), oral cavity, tonsils, and the base of the tongue. Intriguingly, after integrating the results of the two cohorts for the meta-analysis, 12 results were statistically significant. Mediational MR analysis suggested that the effects of metformin on brain meningiomas may be weakened by the presence of the family Oxalobacteraceae. Conclusion: Metformin exhibits potential preventive and therapeutic effects on four types of tumors: brain meningioma, malignant neoplasms of the breast (HER-positive), oral cavity and tonsils, and the base of the tongue. Large randomized controlled trials are required to confirm these findings. [ABSTRACT FROM AUTHOR]

Bridges are metal or concrete structures, which make road connections across rivers when installed over river paths. When flooding or scouring occurs, several issues including bridge destruction and interruption of road connections arise. There are a variety of methods of protecting such structures, one of which is application submerged vanes. This research shows how two vanes with different submergence ratio affected decrease in local scour surrounding one pier and groups of piers installed in a 180-degree bend. The scour around pier groups either in a transverse position to the flow or with a longitudinal direction was analyzed. This finding suggested that applying vanes decreased the deepest scour around the piers in all the tests, and its maximum effect occurred in triad longitudinal pier groups. By raising the submergence ratio, bed scour depth at the outer bank reached its minimum size in longitudinal pier groups. In transverse pier groups, the first scour hole near the outer bank increased in depth in the presence of vanes. By using the vanes, the slope of the scour hole towards the inner bank grew larger than that towards the other bank. The maximum slope of the outer bank happened in the triad transverse pier group at an approximate value of 0.63. The most significant impact of submerged vanes on reducing the upstream slope was observed in a single pier with 75% submerged vanes and triad longitudinal piers with 25% submerged vanes, resulting in reductions of about 50 and 74% respectively compared to piers without vanes. [ABSTRACT FROM AUTHOR]

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The seismic resilience of bridges has become an important concept in civil engineering since these systems need to remain operative during and after earthquakes. In this regard, the definition of recovery needs to consider the delay time (named as the time between an event and the beginning of the recovery process). The original concept of seismic resilience has been expanded herein in order to account for the delay time of bridge configurations. Its role in the quantification of seismic resilience has been investigated by performing a case study of a Californian highway bridge subjected to an ensemble of 100 input motions. The results demonstrate that the delay time may significantly reduce the seismic resilience of bridges. [ABSTRACT FROM AUTHOR]

The Special Issue "4D Printing: State-of-the-art, Recent Trends, and Applications" highlights the significant impact of scientific advancements on practical and innovative applications. It focuses on the interdisciplinary challenges of multi-material printability on a voxel basis and optimizing the actuation performance of composite structures with various stimuli. Key considerations, such as mechanical strength and potential adverse effects, shape the design methods suited to specific quantitative data limitations. Four-dimensional printing calls for creativity, interdisciplinary collaboration, and practical applications. While recognizing experience-based approaches in research, this review paper emphasizes integrating science and technology through alternative strategies; innovative approaches; and the exploration of engineering, design, and artificial intelligence. [ABSTRACT FROM AUTHOR]

Rodent infestation has always been one of the most severe threats to humans, which to solve consumes massive manpower and resources. People usually use traps or poisons to treat rat infestation. Such passive countermeasures are inefficient. Damage often occurs when the rats are finally trapped or killed, not to mention the potential risk to injure humans or cause pollution. In this article, we propose a WiFi-based active small object tracking system named TomFi. The core components of TomFi include several deep learning techniques that bridge rat locations/motions and WiFi signal variations (represented by the channel state information). TomFi first employs a detection model to detect the appearance of the rat and then localize it based on a two-branch localization model. Through the design of the two-branch localization model, to our best knowledge, we are the first to solve the information loss and distortion problem. We conducted extensive experiments in both the laboratory environment and real-world kitchen scenarios. The results show that TomFi can achieve a detection success rate of 99%+ and a centimeter-level localization accuracy in real time. [ABSTRACT FROM AUTHOR]

The Edmund Pettus Bridge, Selma, Alabama, a symbol of the American Civil Rights Movement and an exemplar of early 20th-century engineering, stands as a testament to the progress and challenges of its era. The bridge, recognized for its pivotal role in the 1965 "Bloody Sunday" conflict and the following Selma to Montgomery marches for voting rights, also represents significant engineering achievements with its distinctive design and construction methodology. In this study, the research team presents a comprehensive framework for documenting heritage bridges by utilizing Terrestrial Laser Scanning (TLS) technology, supplemented by other Reality Capture (RC) techniques, including Structure from Motion (SfM), 360-degree photography, and Unmanned Aerial Vehicle (UAV), and integrating the data within a Building Information Modeling (BIM) environment. The focus on the Edmund Pettus Bridge case study demonstrates how this novel approach can capture the intricate details of its structural and architectural features while preserving its historical narratives. The documentation outcomes, including a detailed BIM model and a set of Historic American Engineering Record (HAER) drawings, highlight the effectiveness of combining TLS and BIM in conserving unconventional heritage structures like bridges. This paper also discusses the technological challenges encountered, such as dealing with heavy traffic and environmental constraints during data acquisition and developing the BIM model and drawings. It outlines the strategies implemented to address these issues. This research contributes to preserving a severely under-represented American National Historic Landmark (NHL). It sets a precedent for documenting other non-building heritage structures, balancing technological advancements with historical integrity. [ABSTRACT FROM AUTHOR]

Emotion causes constitute a pivotal component in the comprehension of emotional conversations. Recently, a new task named Causal Emotion Entailment (CEE) has been proposed to identify the causal utterances for the target emotional utterance in a conversation. Although researchers have achieved some progress in solving this problem, they failed to adequately incorporate speaker characteristics and overlooked the effects of temporal relations in conversation structures. To fill such a research gap to some extent, we propose a novel causal emotion entailment framework, namely MPEG (Multi-Perspective Enhanced Graph attention network). The training of MPEG consists of three stages. First, we utilize a speaker-aware pre-trained model and two attention mechanisms to obtain the utterance representations that incorporate local contexts as well as the speaker and emotional information. Then, these representations are fed into a graph attention network to model the conversation structures and emotional dynamics from both local and global perspectives. Finally, a fully-connected network is implemented to predict the relationships between emotional utterances and causal utterances. Experimental results show that MPEG achieves state-of-the-art performance. [ABSTRACT FROM AUTHOR]

The development of energy recovery systems in vehicles is a form of synergy between energy efficiency and renewable energy to overcome the energy crisis and global warming problems. This paper addresses such challenges by introducing a novel design of a piezoelectric energy harvester (PEH) for a vehicle suspension system. The PEH is designed to capture the linear vibration of the suspension system subjected to road surface roughness and move on uniform bridges. The vibration is amplified by a pressurized liquid cylinder-piston mechanism which deforms the piezoelectric bar to produce electric power. An additional novel mechanism in the form of a piezoelectric protector is also proposed to avoid physical damage due to excessive unidirectional compressive force as a result of an unpredictable uneven road. Given the key design parameters, the electric power can be harvested up to 67.5 W for a PEH with a span of 150 m of the bridge, a velocity of 40 m/s, and a vehicle mass of 2,691.6 kg. [ABSTRACT FROM AUTHOR]

Cascaded H-bridge inverters, which belong to strongly nonlinear time-varying system with complex dynamics, have been widely used in high-voltage and high-power engineering fields. In this paper, a carrier phase-shifted sinusoidal pulse-width modulation cascaded H-bridge inverter is taken as an example with piecewise analysis to establish the discrete iterative mathematical model. Furthermore, the nonlinear dynamic behavior of this inverter system is investigated using folding diagrams, spectrum diagrams, bifurcation diagrams, Lyapunov exponents, etc. We find that this inverter can exhibit multiperiod bifurcation, tangential bifurcation and paroxysmal chaos within certain ranges of control coefficients and other circuit parameters, which will influence the system's stability seriously. On the basis of this discovery, the sinusoidal time-delay feedback control method is proposed. The difference between the load current of the controlled object and its own delay is used to form a feedback term, which is then fed into the sine function and proportional link to obtain the control term. Moreover, the Jacobian matrix of this feedback inverter system is derived, and the constraints on the feedback control coefficient are obtained based on the Jury criterion. Simulation results have verified the effectiveness of such a sinusoidal time-delay feedback control method, which can improve the stability and anti-interference of the system. The research can be used to provide some reference and guidance for the circuit design, debugging and control of cascaded H-bridge inverters. [ABSTRACT FROM AUTHOR]

The paper deals with the problem of obtaining a given dynamic behavior of simply supported bridge beams from the impact of rolling stock. Resonant vibrations of beams become a reality at high speeds if the train is formed of identical cars, which is typical for passenger trains. The phenomenon of suppression of beam vibrations by a train, known from publications, is possible only with an exact ratio of the length of the car and the beam. This significantly reduces the possibilities of choosing the necessary spans of beams. Consideration of issues of interaction in the "bridge–track—train" system for security purposes requires the involvement of a rather complex mathematical apparatus and appropriate software. The paper proposes a new method for determining the specified dynamic behavior of bridge beams, suitable for any spans and available to engineers at the stage of pre-design assignment of dynamic parameters of beams. The requirements that are necessary and sufficient conditions for preventing the resonance of bridge beams on the HSR are determined. At the same time, it does not require the involvement of software based on a complex mathematical technique. [ABSTRACT FROM AUTHOR]

The investigation on vehicle–bridge interaction systems (VBIS) plays an important role in evaluating the performance of bridges and/or vehicles. However, due to the limitations of traditional simulation methods and testing methods, the impact of vehicle jumping (VJ) on the VBIS has never been precisely disclosed. In order to accurately and comprehensively reveal the impact of VJ on the dynamic performance of VBIS, one real-time hybrid simulation method (RHSM) for VBIS considering the impact of VJ (VBIS-VJ) is proposed in this paper. In the proposed method, the vehicle system is chosen as the experimental substructure loaded by servo-hydraulic actuator loading system in real-time, whilst the bridge system is chosen as the numerical substructure numerically simulated in one computer. During the vehicle jumping, the vehicle and bridge vibrate freely respectively, otherwise, the experimental substructure and numerical substructure are synchronized at the coupling points in terms of force equilibrium and deformation compatibility in RHSM for VBIS-VJ. Firstly, the principle and numerical models of RHSM for VBIS-VJ are proposed. Furthermore, numerical simulations of RHSM for VBIS-VJ are conducted for verifying the feasibility of the proposed method. Finally, the influence of jumping position, jumping height, and driving speed on the VBIS is disclosed by hybrid simulations. It is shown that compared with the ever-known investigation methods, the proposed method could economically and accurately disclose the dynamic performance of VBIS-VJ. It is shown from the simulation results that compared with the referenced results, the quantitative errors of the proposed method with quarter vehicle model and half vehicle model are less than 2.5152% and 3.5599% respectively, which prove the effectiveness and accuracy of proposed RHSM for VBIS-VJ. The peak displacement of the bridge at a quarter-span and mid-span exceeds the three-quarters span by about 1.9–2.9 mm. The influence of jumping position of a quarter span and midspan of bridge is much huger than that in the three-quarters span. The dynamic response of bridge increases with the increase the jumping height, but the deformation of the bridge is reduced when the jumping height is more than 0.05 m. Meanwhile, the requirements for experimental loading equipment are acquired through the hybrid simulations, which could be used as a reference for selecting the loading system of the RHSM for VBIS-VJ. [ABSTRACT FROM AUTHOR]

In this study, a multidisciplinary approach combining a numerical analysis in three dimensions and a laboratory test is developed to investigate the dynamic coupling effect as induced by vehicle–bridge interaction in the indirect measurement. To unveil such dynamic coupling and its influence on the frequency measurement, a single degree-of-freedom test vehicle is exclusively designed with adjustable frequency, which is a low-cost, easy-to-use, and reliable tool for measuring beam frequencies in the laboratory while providing valuable data for validating numerical models, calibrating sensors, and evaluating bridge performance. From the multidisciplinary analysis, the shifts of frequencies for both vehicle and bridge are consistently demonstrated as a result of vehicle–bridge interaction effect. Moreover, for the identification of higher-order bridge frequencies, the contact-point response works better than the vehicle’s response, even with shifted frequencies being observed in the three-dimensional numerical results. As an extension, a parametric study is conducted numerically to include various practical conditions, including different types and boundary conditions of a bridge as well as pavement irregularity. [ABSTRACT FROM AUTHOR]

In geotechnical engineering, side friction resistance (SFR) is difficult to be measured directly. To further understand distribution law of the SFR, this paper developed a monitoring device that can directly measure the SFR. Further, a theoretical conversion formula for the elastic deformation and the SFR that considers the end effect of sensor sealing was proposed to guide the selection of sensor size and sealing material. Moreover, the monitoring device for the SFR was then calibrated using a largescale direct shear apparatus and analyzed the stability of the sensor. The calibration results revealed that under cyclic loading and unloading conditions, the linear correlation coefficient of the sensor was greater than 0.996, and the sensitivity after sealing could reach 4.836 ^s/kPa, which met requirements of the engineering application. The developed monitoring device characterized by simple testing principle, low cost, and high precision were successfully applied to an open caisson project in Harbin City, which contributes to address the difficult problem of efficiently collecting the SFR in highways, bridges, water conservancy, and other projects. [ABSTRACT FROM AUTHOR]

High-speed railways are “lifeline projects” that shoulder the heavy responsibility of transporting relief supplies and medical forces for the first time after earthquakes. To ensure the train’s safety after earthquakes, it is of great urgency to ascertain a post-earthquake speed threshold. To that end, a target model for seismic irregularity emerges as a key parameter. In this paper, a null phase assumption-based technique for the mutual conversion between evolutionary power spectral density and non-stationary signal was proposed. Taking a high-speed railway track-bridge system as the research object, the target model of seismic irregularities was constructed based on the proposed technique. The rationality of the target model of seismic irregularities was verified, and the construction parameter settings were discussed. Moreover, a simplified frequency-domain fitting method for the target model of seismic irregularities was proposed based on the spectral decomposition theory. According to the research findings, the null phase assumption-based technique is capable of performing interconversion between seismic irregularity and its evolutionary power spectral density with satisfactory accuracy. It is recommended to set the minimum number of seismic irregularities, spatial sampling interval, hop size, and length of window function as 50, 0.25m, 1, and 40 to 100, respectively. [ABSTRACT FROM AUTHOR]

Deep learning shows great promise for medical image analysis but often lacks explainability, hindering its adoption in healthcare. Attribution techniques that explain model reasoning can potentially increase trust in deep learning among clinical stakeholders. In the literature, much of the research on attribution in medical imaging focuses on visual inspection rather than statistical quantitative analysis. In this paper, we proposed an image-based saliency framework to enhance the explainability of deep learning models in medical image analysis. We use adaptive path-based gradient integration, gradient-free techniques, and class activation mapping along with its derivatives to attribute predictions from brain tumor MRI and COVID-19 chest X-ray datasets made by recent deep convolutional neural network models. The proposed framework integrates qualitative and statistical quantitative assessments, employing Accuracy Information Curves (AICs) and Softmax Information Curves (SICs) to measure the effectiveness of saliency methods in retaining critical image information and their correlation with model predictions. Visual inspections indicate that methods such as ScoreCAM, XRAI, GradCAM, and GradCAM++ consistently produce focused and clinically interpretable attribution maps. These methods highlighted possible biomarkers, exposed model biases, and offered insights into the links between input features and predictions, demonstrating their ability to elucidate model reasoning on these datasets. Empirical evaluations reveal that ScoreCAM and XRAI are particularly effective in retaining relevant image regions, as reflected in their higher AUC values. However, SICs highlight variability, with instances of random saliency masks outperforming established methods, emphasizing the need for combining visual and empirical metrics for a comprehensive evaluation. The results underscore the importance of selecting appropriate saliency methods for specific medical imaging tasks and suggest that combining qualitative and quantitative approaches can enhance the transparency, trustworthiness, and clinical adoption of deep learning models in healthcare. This study advances model explainability to increase trust in deep learning among healthcare stakeholders by revealing the rationale behind predictions. Future research should refine empirical metrics for stability and reliability, include more diverse imaging modalities, and focus on improving model explainability to support clinical decision-making. [ABSTRACT FROM AUTHOR]

This paper mainly introduces the emergency repair process for small- and medium-span bridges. The causes of deterioration were analysed by investigating old bridges. After comparison and selection of schemes, the scheme of beam replacement was confirmed using a lightweight steel ultra-high performance concrete (UHPC) composite beam as the superstructure. The main components of the calculations and the design are introduced in detail. Finally, through the load test of the bridge, it was shown that the lightweight steel-UHPC composite beam had good performance and met the requirements of Highway Level I bearing capacity. The lightweight steel-UHPC composite beam described in this paper has the characteristics of high strength, light weight, fast construction, excellent working performance, and remarkable social and economic benefits. It can be popularised and applied in the emergency repair of small- and medium-span bridges and new bridges. [ABSTRACT FROM AUTHOR]

Various approaches have been proposed for bridge structural health monitoring. One of the earliest approaches proposed was tracking a bridge's natural frequency over time to look for abnormal shifts in frequency that might indicate a change in stiffness. However, bridge frequencies change naturally as the structure's temperature changes. Data models can be used to overcome this problem by predicting normal changes to a structure's natural frequency and comparing it to the historical normal behaviour of the bridge and, therefore, identifying abnormal behaviour. Most of the proposed data modelling work has been from long-span bridges where you generally have large datasets to work with. A more limited body of research has been conducted where there is a sparse amount of data, but even this has only been demonstrated on single bridges. Therefore, the novelty of this work is that it expands on previous work using sparse instrumentation across a network of bridges. The data collected from four in-operation bridges were used to validate data models and test the capabilities of the data models across a range of bridge types/sizes. The MID approach was found to be able to detect an average frequency shift of 0.021 Hz across all of the data models. The significance of this demonstration across different bridge types is the practical utility of these data models to be used across entire bridge networks, enabling accurate and informed decision making in bridge maintenance and management. [ABSTRACT FROM AUTHOR]

The accuracy of bridge performance monitoring and evaluation is easily affected by unfavorable factors such as vehicle coupling and test noise. In order to accurately evaluate the dynamic response and health monitoring threshold of the bridge under different operating conditions, a time-varying dynamic vehicle group model including the main uniform mass and the coupling mass was established, and the influence of road roughness was considered in the coupling equation. A bridge monitoring strategy considering signal noise ratio and vehicle–bridge interaction was proposed, and the effectiveness of the monitoring strategy was verified by taking a simple supported beam as an example. The results showed that the proposed time-varying dynamic vehicle group model could accurately consider the influence of road roughness and estimate the threshold of health monitoring, and the proposed bridge monitoring strategy could filter out a large amount of low signal-to-noise ratio or meaningless data, thus saving computing resources and realizing the lightweight safety monitoring of bridges. [ABSTRACT FROM AUTHOR]

As an important part of the boundary conditions on both sides of the high-speed railway track–bridge system, the seismic response of the subgrade structure is different from that of the bridge structure. This difference has become increasingly significant with the widespread adoption of continuous welded rail technology in bridge construction. Therefore, investigating the seismic response of the bridge system, with a specific focus on the longitudinal constraint effects of the subsequent subgrade track structure, is of paramount importance. Utilizing finite element software, two distinct bridge models are developed: one incorporating the subsequent subgrade track structure and another excluding it. Through nonlinear time history analysis under varying seismic intensities, it is demonstrated that the longitudinal constraint of the subsequent subgrade track structure mitigates the longitudinal displacements and internal forces in critical components of the high-speed railway track–bridge system. Concurrently, acknowledging the heightened complexity and cost associated with post-earthquake repairs of the bridge structure compared to subgrade structure, this study uses a risk transfer connecting beam device. This device can redirect seismic damage from bridge structure to subgrade structure, thereby potentially reducing post-seismic repair expenses for the bridge. [ABSTRACT FROM AUTHOR]

The crack detection of concrete bridges is an important link in the safety evaluation of bridge structures, and the rapid and accurate identification and detection of bridge cracks is a prerequisite for ensuring the safety and long-term stable use of bridges. To solve the incomplete crack detection and segmentation caused by the complex background and small proportion in the actual bridge crack images, this paper proposes a coarse–fine combined bridge crack detection method of "double detection + single segmentation" based on deep learning. To validate the effect and practicality of fine crack detection, images of old civil bridges and viaduct bridges against a complex background and images of a bridge crack against a simple background are used as datasets. You Only Look Once V5(x) (YOLOV5(x)) was preferred as the object detection network model (ODNM) to perform initial and fine detection of bridge cracks, respectively. Using U-Net as the optimal semantic segmentation network model (SSNM), the crack detection results are accurately segmented for fine crack detection. The test results showed that the initial crack detection using YOLOV5(x) was more comprehensive and preserved the original shape of bridge cracks. Second, based on the initial detection, YOLOV5(x) was adopted for fine crack detection, which can determine the location and shape of cracks more carefully and accurately. Finally, the U-Net model was used to segment the accurately detected cracks and achieved a maximum accuracy (AC) value of 98.37%. The experiment verifies the effectiveness and accuracy of this method, which not only provides a faster and more accurate method for fine detection of bridge cracks but also provides technical support for future automated detection and preventive maintenance of bridge structures and has practical value for bridge crack detection engineering. [ABSTRACT FROM AUTHOR]

This paper experimentally assesses the efficacy of the indirect Structural Health Monitoring (iSHM) framework on a full‐scale short‐span bridge of nine meters long, using an instrumented vehicle with non‐negligible mass with respect to the mass of the bridge. Emphasis is given to the dynamic identification of the two mechanical systems through Experimental Modal Analysis (EMA) on both the vehicle and the bridge. The EMA vehicle testing is among the main contributions of this paper, as such data become available in experimental iSHM implementations for the first time in the literature. Thus, new insights are brought on the vehicle's dual role as a roving sensing unit and a vibrating mechanical system. A wireless sensor network is adopted that supports a dual monitoring system, i.e., an indirect system with accelerometers on the vehicle and a conventional system with fixed sensors on the bridge. Under a stationary vehicle's position on the bridge, it is shown that a strong dynamic coupling occurs between the two systems due to their high mass ratio and the vehicle's function as a Spring Mass Damper (SMD). In vehicle's moving state, it is demonstrated that transfer of energy occurs between the vehicle and the bridge, which both oscillate under multiple modes of vibration that change over time. It is identified that four main parameters influence the quality of the extracted bridge natural frequencies from the vehicle‐acquired data, i.e., (i) the filtering properties of the vehicle, (ii) the effective signals length in the presence of road discontinuities, (iii) the speed trade‐offs, and (iv) the level of vehicle‐induced bridge excitation and its transmissibility level. The careful consideration of those parameters determines the effectiveness of iSHM implementations in short‐span bridges. [ABSTRACT FROM AUTHOR]

The simultaneous presence of different electrophores provides an interesting playground for responsive materials. Herein, we present the incorporation of a twice-reversibly oxidizable tetrathiafulvalene (TTF) unit into a binucleating ligand, bridging two metal centers in a fully conjugated plane. A two-step synthesis scheme gave the D2h symmetric Schiff base-like ligand H4L in moderate yields from which the corresponding copper(II) [Cu2L], nickel(II) [Ni2L], [Ni2L(py)4] and iron(II) complexes [Fe2L(py)4], [Fe2L (dmap)4] and [Fe2L(bpee)2]·1 Tol could be obtained. Characterization was performed through 1H-NMR, IR, UV-vis and 57Fe-Mössbauer spectroscopy, SQUID magnetometry and cyclic voltammetry, supported by density functional theory (DFT) calculations. Single crystal X-ray analysis of [Ni2L(py)4] revealed sixcoordinate paramagnetic centers, whereas [Ni2L] underwent gradual coordination induced spin state switching (CISSS) in solution. The magnetic independence of both metal centers is echoed by close-toideal Curie-plots of the [Cu2L] system and the gradual spin crossover of all iron(II) compounds. By contrast, cyclic voltammetry measurements in solution indicated oxidation-dependent TTF-metal interactions, as well as metal-metal interactions. The reversible TTF-borne events in H4L and [Ni2L] are overlaid with metal-borne events in the case of [Fe2L(py)4], as is corroborated by an analysis of the frontier orbital landscapes and through diagnostic spectral features upon chemical oxidation. [ABSTRACT FROM AUTHOR]

In the actual structural health monitoring system of suspension bridges, only part of suspenders tension can be monitored, but not all the suspenders tension can be obtained. To solve this problem, a method for suspenders tension identification of bridges based on the spatio‐temporal correlation between the girder strain and suspenders tension is proposed. By using actual monitoring data of vehicle loads, a spatio‐temporal correlation model of the girder strain and tension forces of all suspenders is constructed based on the combined application of stacked denoising autoencoder and convolutional neural networks‐long short‐term memory model, so as to realize the preliminary identification of suspenders tension. On this basis, by using the actual monitoring data of suspenders tension and the strain monitoring data obtained through the distributed optical fiber sensors, the delicate identification of tension forces of all suspenders is realized based on the error interpolation of preliminary identification results. The results of the example bridge show that the method in this paper can effectively identify tension forces of all suspenders of the suspension bridge, and identification results are more accurate than the method using only the monitoring data of suspenders. [ABSTRACT FROM AUTHOR]

Current traffic simulation approaches analyze vehicle loads and load effects from a statistical perspective; however, they fail to reproduce the spatiotemporal distribution of bridge loads and resultant load effects at every moment, hindering real‐time bridge health management. This paper proposes a two‐step hybrid virtual–real traffic simulation (HvrTS) approach to reproduce the spatiotemporal distribution of bridge loads. Vehicle load sequences are first identified using computer vision based on traffic video from two surveillance cameras installed along the bridge. Next, traffic microsimulation is optimized with the identified vehicle load sequences from the two cameras serving as the known input and validated output. Using a cable‐stayed bridge under free‐flowing traffic, the HvrTS approach achieved a weighted mean square matching error of ≤0.3 m for the vehicle longitudinal location and a matching error of ≤7% for the vehicle lane position, whereas with congested traffic, the matching errors were much higher due to the inherent complexities and challenges associated with reproducing vehicle behavior in heavily congested situations. The traffic load effects calculated via HvrTS presented excellent spatiotemporal matching with those measured by a structural health monitoring system, especially in free‐flow traffic conditions. Applications on a continuous rigid frame girder bridge further validate these findings. Hence, the proposed HvrTS approach can overcome the challenge of spatiotemporal matching between vehicle loads and load effects in field monitoring. [ABSTRACT FROM AUTHOR]

This study stems from the contemporary need to establish a connection between heritage and citizens, a fundamental element in heritage preservation and a safeguard for authenticity and identity values.1 The study bridges the gap between theory and practice by proposing a methodology based on diagnosis and subsequent proposals to bring heritage closer to the local population. The case study used for this purpose has been the city of Seville, Spain, and it primarily focuses on built heritage and the Historic Urban Landscape. The methodology outlined in this article comprises three phases: (1) Survey and Data Collection, involving the design and implementation of a perception-focused survey; (2) Results Analysis and Evaluation, where the obtained data is statistically analysed, subsequently evaluated qualitatively and quantitatively with a proposed a KPI system; (3) Strategic Planning: finally, as a final outcome, the study utilises the previous evaluation to formulate objectives and an action plan to enhance the local community's heritage relationship. It is expected that the proposed methodology for this case study will be applicable to other similar contexts. [ABSTRACT FROM AUTHOR]