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The predicted Bridge Condition Index (BCI) is a guiding indicator for formulating preventive maintenance strategies for bridges and is hardly available even if using the most advanced neural network prediction model, owing to the few measured BCIs and neural network model defects. In this paper, an improved Back-Propagation Neural Network (BPNN) model named CPSO-BP-MC is proposed to predict BCI, which has a BPNN as its core, combined with the Coordinated Particle Swarm Optimization (CPSO) algorithm aims to faster convergence and avoid local optimal solution even with less training sample, and the Markov Chain (MC) algorithm aims to further revise the fluctuation of CPSO-BP prediction output due to maintenance and reinforcement. A case study is presented to demonstrate the efficiency of CPSO-BP-MC predicting BCI with fewer training samples. Comparing the predicted BCI of CPSO-BP-MC with the measured BCI and other models, the results show that CPSO-BP-MC converges faster than other models, and can predict the BCI more stably and accurately, and the error between prediction and measured BCI is less than 3 %. [ABSTRACT FROM AUTHOR]

The combined use of finite element modeling and structural health monitoring is becoming increasingly relevant in bridge maintenance. A growing number of new and old structures is instrumented with different kinds of sensors driven by dedicated hardware and software, while numerical models are used to simulate the response of the structures under various scenarios. This paper presents the monitoring of the Smithfield Street Bridge, one of the oldest and most iconic bridges in the city of Pittsburgh (Pennsylvania, USA). The bridge was instrumented by an independent party, not involved with the research presented here, with strain, displacement, and rotation wireless sensors. A detailed finite element model of one of the spans of the bridge was developed to calculate the strains induced by standardized trucks under pristine and simulated damage conditions. In addition, the model enabled to determine the sensitivity necessary to detect relevant structural changes in the bridge. The results of the numerical analyses were then compared with the results of a test in which a truck of known weight crossed the bridge multiple times. Finally, the data relative to 3 years of uninterrupted monitoring were processed and analyzed to identify eventual anomalies. [ABSTRACT FROM AUTHOR]

Translation abstract Effects of traffic‐induced vibrations on young concrete: part 2In the COUNT (COncreting UNder Traffic) research project, the effects of traffic vibrations on young concrete were extensively investigated. This issue has recently become more relevant. When bridges are being renewed or extended, traffic bans are often imposed for fear that the vibrations caused by traffic could damage the young (hardening) concrete. COUNT aimed to determine critical vibration values and underlying damage mechanisms on the basis of three systematically designed series of tests. The first two series, in which unreinforced concrete and the concrete‐steel composite were investigated, were reported on in the first part of the article, which has already been published. This second part of the article deals primarily with the third series, in which tests were carried out on a large, realistic scale. Concrete slabs were cast which were in direct contact with a vibrating prefabricated concrete slab. Possible damage was later analysed by means of crack measurements, bending tests and permeability tests. At the end, recommendations for practical application are given, also taking into account the findings of external research work. [ABSTRACT FROM AUTHOR]

Dynamic response analysis of multi-span beams is one of the important topics in the field of highway and railway engineering, which provides valuable guidance for the design, operation and maintenance of multi-span bridges. It is worth considering how to calculate the dynamic characteristics of multi-span beams quickly and conveniently. In this study, an effective analytical method is developed for the dynamic modeling and investigations of multi-span Timoshenko beams under moving loads by employing the assumed mode method (AMM). Based on Hamilton’s principle, the equation of motion of the Timoshenko multi-span beam subjected to moving loads is formulated and the natural frequencies are calculated. A comprehensive investigation is conducted on the dynamic responses of the multi-span Timoshenko beam considering different factors, including the length-to-thickness ratio, disorder degree, arrangement order, number of spans and related parameters of moving loads. In addition, the influence of the interval and velocity of the moving load series on the dynamic responses, including displacement, velocity and acceleration of the multi-span beam, are analyzed in detail. The theoretical calculation results of multi-span Timoshenko beams under moving loads are compared with numerical results obtained from ANSYS software, and the results are in good agreement. This demonstrates that the developed method, which utilizes the AMM to analyze the dynamic characteristics of multi-span beams subjected to moving loads, significantly simplifies the calculations and is well-suited for practical engineering applications. [ABSTRACT FROM AUTHOR]

The prediction of fatigue cracks on orthotropic steel decks is of great significance to the maintenance of bridges. However, fatigue cracks are affected by various uncertainties in reality, which encourages a data‐driven study for the sake of reliability and accuracy of predictions. Based on the crack inspection data from orthotropic steel decks on actual bridges in China, the feature engineering is conducted considering fatigue crack behaviors, and the machine learning models are trained and tested for predicting cracks, including XGBoost, random forest, and multiple decision trees. According to the receiver operating characteristic curves of the three models, the XGBoost model has the best performance, whereas the average AUC is about 0.75, limited by the insufficient data volume of positive samples. With the SHAP values of all features, the interpretation of the machine learning model is presented, indicating that the global effects, that is, the longitudinal position, the loading condition, and the bridge age, are always influential factors for fatigue cracks. The local features concerning the interactions between cracks have an effect on crack behaviors to a certain extent, but less important. Accordingly, the interpretable machine learning model can provide conservative predictions in a rather transparent way on this issue, which can benefit decision‐making in bridge designs, maintenance, and management. Highlights: Interpretable machine learning is applied to predict cracks on orthotropic steel decks.Inspection data analysis is conducted to propose features about crack behaviors.Performance of different machine learning models are compared.The interpretation of crack behaviors is given by SHAP values. [ABSTRACT FROM AUTHOR]

The term “digital twin” is becoming increasingly prevalent in both research and politics with regard to infrastructure structures. Industry is making significant advancements in the fields of automation and autonomy. While numerous definitions are in circulation, some of which are identical, many are similar in nature. This work examines the digital twin from its original industry perspective and considers its relevance to the constructional engineering sector. The objective of this study is to provide an overview of the current approaches in the Industry 4.0 and constructional engineering industry, examining the associated technical opportunities and challenges. The study compares the definitions, requirements and projects executed in this field. The technologies under examination are contrasted on the basis of their position within the data model. The preliminary findings suggest that some solutions for Industry 4.0 have already been developed for the construction engineering sector. However, it must be acknowledged that some solutions have yet to be fully validated. [ABSTRACT FROM AUTHOR]

The degradation of bridge structural performance arises from the combined influence of various factors. Performance assessment and reliable prediction of bridge performance degradation through effective utilizing of detection information updates is a challenging problem. In this paper, the concept of performance indicators is redefined, employing to delineate bridge performance degradation. A bridge performance degradation model (the error ≤8%) is formulated, considering the multiple-variable Bayesian dynamic linear method (MBDLM) and revealing the coupling mechanisms among factors influencing bridge performance degradation. On this basis, the prediction performance of the model is quantitatively evaluated by three metrics: mean squared error, predictive mean squared error and mean absolute percentage error. A methodology is presented for the assessment, prediction, and maintenance reinforcement of in-service bridge structural performance degradation. This approach holds promise for future applications in safety assessments and the decision-making process for preventive maintenance of operational bridges. [ABSTRACT FROM AUTHOR]

This article investigates the challenges of maintaining the Machico Cable-Stayed Bridge in a marine environment, focusing on its implications for urban mobility. The primary problem addressed is the impact of harsh marine conditions on the structural integrity of the bridge, which poses significant challenges for ongoing maintenance and safety. The research highlights unique aspects such as the effects of saltwater exposure on materials and the interplay between infrastructure and urban transit dynamics. By emphasizing these critical issues, this study aims to provide insights into effective maintenance strategies and contribute to the broader discourse on urban mobility in coastal regions. [ABSTRACT FROM AUTHOR]

In order to study the influence law of rockfall on the train running safety of railway bridges, a simply supported box girder bridge on a railway in western mountainous area was taken as the research object. A rockfall impact simulation model and a vehicle-track-bridge coupling dynamic analysis model, which fully considered material nonlinearity and contact nonlinearity, were established. The characteristics of rockfall impact force on bridge piers were clarified, and the train running safety on the bridge under rockfall impact was analyzed. The influence of rockfall impact speed, angle, height, and rockfall diameter on running safety was also revealed. The results showed that: (1) The peak impact force value of rockfall increased with the speed and diameter of the rockfall, while the impact height and angle had little effect on the peak impact force. (2) The increase in rockfall diameter enlarged the damage range of the pier structure, characterized by the appearance of multiple impact force peaks and an extended impact force time history. (3) The faster the rockfall impact speed and the greater the impact energy, the more significant the threat to train running safety on the bridge. The closer the rockfall impact height was to the top of the pier and the larger the diameter of the falling rock, the greater the lateral dynamic response of the train, posing a higher threat to train safety on the bridge. (4) The variation patterns of the time-history curves of each safety evaluation index of the train under different working conditions were similar across different impact angles of rockfall, with minimal changes in their impact on train safety. (5)The wheel load reduction rate was highly sensitive to rockfall diameter and impact height. The wheel load reduction rate exceeded the standard limit when the rockfall diameter reached 2. 5 meters. The research results will provide a reference for the whole life cycle design and safe operation and maintenance of railway bridges in western mountainous area. [ABSTRACT FROM AUTHOR]

The use of UHPC as an overlay and repair material in the bridge industry has been increasing recently. Ensuring sufficient interface shear strength between the substrate and UHPC is necessary for adequate performance and the structural integrity of the composite section. Due to the lack of structural design code for UHPC members, designers often rely on experimental data developed by researchers or on existing conventional concrete design code to predict the interface shear capacity of sections containing UHPC. The various test methods currently used to quantify the interface shear strength oftentimes produce different results. The objectives of this paper are to create a database of the studies on the interface shear strength of UHPC members available in the literature and carry out a statistical assessment. Moreover, a reliability analysis is conducted on the collected experimental database, and the probability of failure is determined for UHPC–concrete, UHPC–UHPC, and monolithic UHPC interfaces. The paper also investigates the dependence of the reliability index on two different test methods used for interface shear capacity prediction. Additionally, a simpler interface shear capacity model with readily determined parameters is proposed for the monolithic UHPC interface, with a better reliability index compared to current design specification. [ABSTRACT FROM AUTHOR]

Clamping force is crucial for resisting slip loads in friction-type high-strength bolted (FHSB) connections, and following corrosion, it diminishes due to sectional reduction of the nuts and/or bolt heads. Evaluating clamping force loss (CFL) in corroded FHSBs is essential for steel bridge inspection and maintenance. The cutting methods currently employed to simulate corrosion encounter challenges including limited shapes, low efficiency, and poor accuracy, leading to significant data dispersion in experiments and diminished reliability of evaluation models. Furthermore, existing evaluation models fail to fully consider the influence of factors such as corrosion shape, size, thread specifications, corrosion location, and initial clamping force (ICF) on clamping force. Hence, this research proposed a novel wire-cutting simulation corrosion method (WCSCM) and conducted experiments on 80 specimens. Based on experimental results, five clamping force evaluation models were systematically established for corrosion shapes including thickness uniform corrosion, height uniform corrosion, height and thickness corrosion, eccentric corrosion, and trapezoid corrosion, and their fitting accuracy was compared and analyzed. Furthermore, the impact of thread specifications, corrosion location, and ICF on clamping force was discussed. Finally, procedures for measuring field corrosion bolt dimensions and methods for approximating corrosion shapes were proposed, followed by validation of the evaluation model's effectiveness through on-site bridge testing. The findings showed that the WCSCM accurately reproduced the corrosion shapes and sizes of the nuts and/or bolt heads, with regression equation coefficients exceeding 0.97, notably higher than those of existing models. The CFL resulting from various corrosion shapes and sizes exhibited variation, indicating the necessity for distinct models tailored to each corrosion damage pattern of the nuts and/or bolt heads. The impact of thickness uniform corrosion on clamping force primarily correlated with ICF, with less influence from thread specification or corrosion location. The proposed models were able to achieve an accuracy level within ±20%, providing a basis for replacing corroded bolts on steel bridges. [ABSTRACT FROM AUTHOR]

The Fenshui River Bridge is a steel–concrete composite girder bridge with a main span of 90 m. Due to the topographical constraints, the steel box girder was constructed without the use of auxiliary piers, employing incremental launching techniques. This article focuses on the construction technology used for the steel box girder of the Fenshui River Bridge. Firstly, using the influence matrix method, the cable force is determined based on the maximum cantilever state of the structure, with the vertical deformation of the front end of the guide beam and the horizontal deformation of the top of the tower as the control objectives. The unstressed cable length is then calculated based on the mechanical relationship between cable deformation and cable force. A calculation method for adaptive cable force is proposed, which is based on the variation of the stress-free cable length within the adaptive structural system. Next, the finite element analysis method was employed to determine the optimal layout position for the tower. The results indicate that during the incremental launching construction of the steel box girder, the calculated cable forces using the method proposed in this paper are in close agreement with the measured cable forces. At the maximum cantilever state of the structure, the calculated and measured values of the cable force resulted in a percentage difference of 3.96%. The calculated values of deformation and stress in key sections showed a percentage difference of 6.4% for deformation and 6.6% for stress. To maximize the effectiveness of the tower and cable, the tower should be positioned above the bridge pier when the guide beam crosses the maximum span. The findings of this paper can serve as a reference for the construction of similar types of bridges. [ABSTRACT FROM AUTHOR]

The girder bottom inspection is becoming an important part of the bridge maintenance process. In this study, a vehicular defect identification system was built to make the inspection process of bridge bottoms more intelligent, efficient and accurate. The system contains three main parts: image acquisition, image stitching and defect recognition. The image acquisition part was responsible for controlling the start and stop of image acquisition, data transmission and image storage. The image sequences collected were processed and stitched into a panoramic image during the image stitching process, and the coordinate systems of images would also be unified. Finally, the defects in the image were recognized and positioned. Combined with the BIM model, multiscale digital display of bridge bottom defect, including defect recognition and positioning results, was obtained. With the multiscale information, the maintenance for bridges will become more convenient. The deep learning model U2-Net was used to detect cracks and realized a defect detection accuracy of millimeter-level. The experimental results proved that the cracks in the images of the bridge bottom could be detected effectively using the proposed method with a high performance of 79.15 % test dataset F1-score and 0.691 MIoU. Additionally, the proposed defect location method had a centimeter-level defect location accuracy. [ABSTRACT FROM AUTHOR]

Bridge maintenance is a highly intricate task that involves considering a wide range of factors in order to achieve optimal decisions that align with multiple objectives, criteria, and the entire lifecycle of the bridge. While physics-informed analysis, such as the finite element method (FEM), can simulate complex and closely coupled scenarios, such as bridge structural analysis, it cannot account for some loosely coupled discrete factors, which could be addressed by ontological reasoning. Therefore, this paper presents a knowledge-driven decision-making framework that combines static knowledge reasoning with dynamic FEM analysis results to support holistic bridge maintenance decisions. One significant contribution of this research is the development of a comprehensive bridge maintenance ontology that incorporates knowledge derived from bridge maintenance standards. Another key contribution is the ability to employ complex runtime rules-based reasoning to tackle intricate bridge maintenance scenarios. To enable automatic knowledge-driven reasoning, an integrated workflow is developed to orchestrate semantic modeling with numerical modeling through a Python-based Web Ontology Language application programming interface (OWL API). This integration facilitates the efficient orchestration of the framework. A case study is presented to demonstrate the potential for the developed framework in assisting with the complex holistic decisions required for bridge maintenance. [ABSTRACT FROM AUTHOR]

Responsible for 70% of the global CO2 emissions, infrastructure has a significant impact on our climate and the related consequences. Bridges are a major keystone of the infrastructure and take a leading position in its decarbonization. In this framework, low‐carbon emission steels play an important role. Low‐carbon emission steels, like ArcelorMittal's XCarb® recycled and renewably produced steels, are already available on the market. Combining scrap and renewable electricity, it offers very low levels of CO2 emissions per ton of finished steel. The present paper describes how different steel solutions can be combined to lower the material input, to simplify the construction process and to reduce the maintenance efforts in bridge construction. The impact of efficient design has been assessed by a Life‐Cycle Assessment (LCA) for bridge solutions with small and medium spans of up to 40 m. The paper concludes with a summary of recently realized bridge projects in Poland. [ABSTRACT FROM AUTHOR]

Segmentally assembled bridges are increasingly finding engineering applications in recent years due to their unique advantages, especially as urban viaducts. Vehicle loads are one of the most important variable loads acting on bridge structures. Accordingly, the influence of overloaded vehicles on existing assembled bridge structures is an urgent concern at present. This paper establishes the finite element model of the segmentally assembled bridge based on ABAQUS software and analyzes the influence of vehicle overload on an assembled girder bridge structure. First, a finite element model corresponding to the target bridge is established based on ABAQUS software, and the load is controlled to simulate vehicle movement in each area of the traveling zone at different times. Second, the key cross-sections of segmental girder bridges are monitored in real time based on the force characteristics of continuous girder bridges, and they are compared with the simulation results. Finally, a material damage ontology model is introduced, and the structural damage caused by different overloading rates is compared and analyzed. Results show that the finite element modeling method is accurate by comparing with on-site measured data, and it is suitable for the numerical simulation of segmental girder bridges; Dynamic sensors installed at 1/4L, 1/2L, and 3/4L of the segmental girder main beams could be used to identify the dynamic response of segmental girder bridges; The bottom plate of the segmental girder bridge is mostly damaged at the position where the length of the precast beam section changes and the midspan position. With the increase in load, damage in the direction of the bridge develops faster than that in the direction of the transverse bridge. The findings of this study can guide maintenance departments in the management and maintenance of bridges and vehicles. [ABSTRACT FROM AUTHOR]

This study proposes a method for assessing the effect of stochastic vibrations resulting from track irregularities which are rarely studied but significant on bridge fatigue. First, the pseudo-excitation method is utilized to determine the power spectrum density of stress. Subsequently, the trigonometric series method is employed to acquire the stress time history set. Then, a traditional fatigue life calculation method is employed for analysis. By utilizing a post-sampling method, the need for costly repetitive solutions of the vehicle-bridge coupling system is eliminated. Numerical simulations are conducted on a steel truss bridge, revealing the non-negligible effect of track irregularity on bridge fatigue performance. The study investigates the underlying mechanism, highlighting the pronounced influence of long-wave track irregularity. Moreover, the research explores the correlation between track smoothness and bridge fatigue performance, demonstrating that a decrease in track smoothness leads to an increase in fatigue loss. These findings emphasize the necessity of considering stochastic vibrations when evaluating bridge fatigue, providing valuable insights for bridge design and maintenance. [ABSTRACT FROM AUTHOR]

The frequent damage and repair of bridge expansion joint anchorage zone has caused a great burden to the bridge maintenance work. The objective of this study is to prepare a steel fiber reinforced polyurethane concrete (SFPUC) with balanced multi-properties of workability, compressive strength, and flexural strength for the application in bridge expansion joint anchorage zone. A four-factor, five-level orthogonal experimental design was carried out to investigate the effects of the binder-aggregate ratio (BA), cement content (C), fine-coarse aggregate ratio (FC), and steel fiber dosing (SF) on the workability, compressive strength, and flexural strength, respectively. The multi-criteria decision-making (MCDM) method was used to transform the multi-response problem in the orthogonal experimental design into a single-response problem. Finally, a real engineering application and a finite element method were used to verify the feasibility of SFPUC for the expansion joint anchorage zone. The results show that the optimum proportion of SFPUC is BA (25%), C (20%), FC (20%), and SF (2.5%). The maximum principal stress in SFPUC anchorage zone is less than that in C50 steel fiber concrete anchorage zone under the same load. SFPUC is a highly promising material for bridge expansion joint anchorage zone repair. [ABSTRACT FROM AUTHOR]

The durability of bridge deck pavement significantly influences the economic gains from bridge maintenance and transportation efficiency. With the increasing application of autonomous trucks (ATs) in highway bridges, there is a growing need to ascertain the adequacy of existing bridge deck pavement designed for human-driven vehicles to withstand the unique driving behaviors of ATs, especially their distinctive lateral driving behaviors, such as centering within lanes, which may affect the lifetime of bridge deck pavement. In this study, we first establish both the mechanical model and continuous variable temperature field model of the bridge deck pavement. Subsequently, a durability evaluation method is proposed for assessing rutting in bridge deck pavement that accounts for the lateral driving behavior of ATs. We examine the impact of varying lateral driving behaviors of ATs within a lane on the durability of bridge deck pavement with a double-layer structure. The findings show that the regulation of the lateral driving behavior of ATs can effectively postpone the onset of bridge deck pavement deterioration akin to rutting in human-driven trucks by up to 3.66 years (as determined by periodic detection year). This results in a notable reduction in rutting of 11% compared to human-driven trucks. Conversely, without the implementation of lateral control, the rutting caused by ATs could increase by 54%. Moreover, we develop and formulate lateral control strategies for ATs based on the theoretical insights obtained. These strategies take into consideration the applicable conditions for effective lateral control. This investigation not only provides essential theoretical support for maintenance and design strategies of bridge deck pavement within the realm of ATs but also offers operational recommendations for ATs on highway bridges. These suggestions encompass traffic speed limits and prescribed driving behaviors within lanes, which are essential considerations from the standpoint of AT operations. [ABSTRACT FROM AUTHOR]

Bridges in areas with high seismic risk are constantly exposed to earthquake threats. Therefore, comprehensive bridge damage assessments are essential for postearthquake retrofitting and safety assurance. However, traditional methods of assessing damage and collecting data are time‐consuming and labor‐intensive. To address this issue, this study proposes a deep generative adversarial network (GAN)‐based approach to predict the surface damage patterns of bridge columns. Using visual patterns from experimental tests, the proposed approach can generate surface damage to the synthetic column, such as cracks and concrete splinters. The study also investigates the effects of different data representation schemes, such as grayscale, black and white, and obstacle‐removed images, and uses the corresponding damage indices as additional constraints to improve network training. The results show that the proposed approach can offer a reliable reference for bridge engineers to evaluate and repair seismic‐induced bridge damage, which can significantly lower the cost of disaster reconnaissance. [ABSTRACT FROM AUTHOR]

Bridges are a crucial component of social infrastructure, playing a vital role in transportation, logistics and transit. Several bridges in South Korea were constructed during the rapid development period of the 1990s and 2000s, with RC slab bridges making up a significant portion of these structures. Over time, many of these bridges have aged considerably. To address this, the "Special Act on the Safety Control and Maintenance of Establishments" was enacted in South Korea to improve bridge maintenance. However, maintenance for aging small- to medium-sized bridges, except for Type 1 bridges, remains inadequate due to budget and personnel shortages. In this study, we developed a damage assessment method to evaluate the deterioration and analyze the current state of small- to medium-sized RC slab bridges. We derived the correlation between the deflection response ratio and the stiffness reduction rate of a bridge through structural analysis. This correlation data were then used to assess the damage to actual in-service bridges. Finally, we analyzed the current state of the target bridge and validated the damage assessment method. [ABSTRACT FROM AUTHOR]

Purpose Methods Results Conclusions Level of Evidence This study aimed to clarify the characteristics of delaminated rotator cuff tears (RCTs) and evaluate the clinical outcomes of a modified arthroscopic en masse suture bridge repair for delaminated RCTs.Patients with full‐thickness RCTs, who underwent arthroscopic suture bridge repair with a minimum 2‐year follow‐up, were retrospectively reviewed. Patients were categorized into two groups based on the presence of delamination. Delaminated RCTs were treated using a modified en masse suture bridge technique, while nondelaminated RCTs received a conventional suture bridge technique. Preoperative and postoperative Constant scores and American Shoulder and Elbow Surgeons (ASES) scores were determined to evaluate clinical outcomes. Postoperative magnetic resonance imaging (MRI) was carried out to identify the integrity and retear of the repaired rotator cuff.A total of 172 patients were included in our study cohort, in which 67 (39%) delaminated RCTs were confirmed intraoperatively. The prevalence of delamination was significantly higher in large tears (53/102, 52%) compared to medium tears (14/70, 20%) (p < 0.001). No significant differences in age (n.s.) or gender (n.s.) were observed between the two groups. Both groups showed significant improvements in Constant and ASES scores postoperatively (both p < 0.001), with no significant differences between the groups (n.s.). The retear rates were 2/67 (3.0%) in the delamination group and 3/105 (2.9%) in the nondelamination group, showing no significant difference (n.s.).The modified arthroscopic en masse suture bridge technique was effective for repairing delaminated RCTs, yielding favourable clinical outcomes comparable to those of nondelaminated tears.Level IV. [ABSTRACT FROM AUTHOR]

One of the key tasks to ensure infrastructure safety is the periodic detection of bridge cracks. Since manual crack detection is subjective and inefficient, it is very important to develop an automatic crack recognition system by using machine vision. Inspired by the pyramid vision transformer (PVT) and the feature pyramid network (FPN) variants, a method combining PVT, residual transformer (REST), holistically nested edge detection (HED), and downstream detection tasks is proposed in this paper, which is named EVPTMFF (efficient visual pyramid transformer and multiple-feature fusion). Based on the PVT, the multiheaded attention module was replaced and the efficient attention module was adopted, which could process the data efficiently and flexibly. To improve the performance of EVPTMFF, the original perceptual field windows were changed. The adjacent windows were partially overlapped, which was more conducive to feature interaction and improves detection performance. To prove the generalization ability of the model, three different data sets related to bridges were collected and formed. We carried out experiments on these three data sets, and EVPTMFF showed good results. Especially for larger data sets, the performance advantage was more significant. Practical Applications: The crack detection model proposed in this paper presents a good detection effect under different illumination and interference. And the detection results, collected data, time, and other information are saved to the bridge crack detection software. This can help engineers quickly and accurately detect cracks on the bridge surface, as well as predict the development trend of cracks and possible safety issues. In practical application, the bridge crack detection system can help engineers find and solve the bridge crack problem in time and avoid the security risks and economic losses caused by cracks. At the same time, the efficiency and accuracy of bridge maintenance can be improved, and the maintenance cost and time can be reduced. The bridge crack detection system can be integrated with other hardware equipment and management systems to form a complete bridge management platform, which contributes to the traffic construction and social and economic development of the city. [ABSTRACT FROM AUTHOR]

The orthotropic steel decks (OSDs) are vulnerable to fatigue fractures, which will inevitably impair the normal service of the steel bridge panels. To determine the impact of the initial cracks on the fatigue life, this study constructed an evaluation model of the OSD rib-to-deck joints crack based on the fracture mechanics principle. And combined it with the multi-scale finite element analysis model, the digital fatigue test model of the whole bridge was established. Research shows: A typical I-II-III composite crack with the supremacy of type I crack can be seen in the OSD rib-to-deck joints. Fatigue cracks developed at the deck weld toe dominate the fatigue failure mode. Further research revealed that as the depth of cracks increased, the stress on the cross-section was redistributed. The intensity factor then displayed a trend of growing and then gradually flattening or even dropping. Based on the relationship between cracks of different depths and the remaining life of the OSDs, recommendations are given for bridge maintenance. The multi-scale digital fatigue test can provide analysis and simulation methods for the fatigue crack propagation in the steel bridge deck of the bridge in operation. [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]

Bridge maintenance activities benefit from digital models, provided in the interoperable IFC format. Such a model, enriched with up-to-date information, is an enabler for a wide range of applications. It opens new perspectives in asset information management. However, the manual creation of a digital replica, representing the actual state of the asset from point cloud data, is time-consuming. Consequently, process automation is of particular interest. This paper proposes a systematic, semi-automatic approach for creating IFC bridge models from point clouds. It introduces new methods for semantic segmentation and 3D shape modeling. A case study demonstrates the feasibility of the process in practice. Compared to other solutions, proposed methods are robust when dealing with incomplete point clouds. [ABSTRACT FROM AUTHOR]

Given the advances in technology and the development of urban development and progress in people's lifestyles, the use of bridges is considered as an important and necessary way of esophageal communication. Bridges are one of the most important tools for connecting roads and different cities, which connect different areas and create connections between people. One of the most important and necessary measures in the bridge industry is related to the repair and maintenance of bridges, which cost less than building a bridge and help to create connections between people. To this end, the present study examines the effects affecting the maintenance and repair of bridges in urban contexts and for this issue an approach under conditions of intuitive fuzzy uncertainty based on analytic network process and comprise solution methods to calculate weights and option ranking offers. However, an integrated group decision making-based soft computing approach is tailored by computing the criteria importance and experts' weights to solve the urban concrete bridge maintenance model selection problem. Finally, to validate the proposed method, a case study is used along with a comparison of the proposed method and existing methods in the literature. The final results indicate the strength and efficiency of the proposed method in calculating weights and ranking options for the project of maintenance and repair of urban bridges in Rasht. [ABSTRACT FROM AUTHOR]

Europe's transportation infrastructure including bridges requires optimised maintenance plans and adequate monitoring throughout its life cycle to ensure safety and serviceability. The deployment of new technologies can help this goal, providing numerous advantages compared to existing and established inspection and monitoring methods. This deployment can be facilitated by adequate policies and focused research and innovation, taking also into account the European ambitions for safe, secure, and future-proof transportation infrastructure. Considering the above, the objective of this study is threefold. First, it provides an overview of recent policy initiatives in Europe that facilitate the adoption of new and emerging technologies in bridge inspection and monitoring, as well as maintenance in general. Second, it identifies and reviews R&I projects relevant to bridges, including the budgetary expenditure, from the Horizon 2020 European Research Framework Programme which was recently concluded. Finally, it systematically reviews technologies and solutions developed by the identified projects, assessing also their technology readiness. What emerges is substantial research, which includes solutions and technologies (e.g., use of air or ground drones, artificial intelligence, digital twins) that have the potential to reshape the bridge inspection and monitoring state of play in Europe and beyond. [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]

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]

This study examines the cyclic shear-slip performance of a novel prefabricated composite shear stud (PCSS) connector designed for accelerated bridge construction (ABC) of composite structures. An in-depth experimental procedure is employed involving the design and fabrication of four push-out specimens with two different stud configurations. The specimens are then tested under both monotonic and cyclic-to-monotonic loading protocols. Upon completion of the testing phase, a meticulous inspection of the fractography is conducted to delineate and qualify the failure mode of the PCSS connectors. Simultaneously, a comprehensive shear-slip curve is derived from the measured data, enabling a detailed analysis over the mechanical performance. Furthermore, the study calculates a series of deformation-associated indicators from the shear-slip curve, effectively quantifying the ductility, recoverability, and capacity of the PCSS. The test results accentuate a well-deformed and ductile failure mode of the tested PCSS specimens, marked by the stud fracture and crushing of surrounding concrete. This could be attributed to the constraint of vertical plates of the PCSS on the concrete, which improves the capacity and recoverability of the PCSS. Whereas, the performance of the PCSS is also notably influenced by the group nail effect, for which the ductility and per-stud capacity degrade with the increase in the number of studs. Especially, the PCSS specimen exhibits full elastic-to-plastic hysteresis loops under cyclic loads, together with the satisfied ductility, implying an excellent potential of the PCSS to dissipate energy under impact loads. In addition, the PCSS displays a robust stiffness across different cyclic loading blocks. Hence, satisfactory post-damage ductility has still been observed in the PCSS under the monotonic loading after the cyclic loading. In conclusion, this work elucidates the superiority of the PCSS in terms of capacity, ductility, and recoverability, providing a promising basis for their application in the accelerated construction of composite bridges. [ABSTRACT FROM AUTHOR]

An accurate prediction of the future service state of long-span bridges is crucial for the structural reliability evaluation, maintenance planning, and further life-cycle cost analysis. By extending the average conditional exceedance rate (ACER) statistical model and applying input–output data collected through a structural health monitoring (SHM) system, this paper proposes a novel methodology for predicting the future service state of long-span bridges. The advantages lie in the consideration of the main excitation load as the structural input and the strain response of the bridge as the output. Therefore, a mapping relationship between the extreme excitation load and extreme strain could be established, and the future service state of long-span bridges could be predicted. The proposed method comprises three steps: (1) extraction of the ambient temperature-induced strain and vehicle-induced strain from the measured strain series through the SHM system using the baseline estimation and denoising with sparsity (BEADS) method, (2) establishing statistical models of the extreme values of different excitations (input) and structural strains (output) using a cascade of conditioning approximations and the ACER to obtain the tail trend of the data and extrapolating it, and (3) establishing a functional relationship between the input and output extreme values based on the same conditions of the regression period at the target prediction level, after which the future service state of long-span bridges can be predicted. The proposed method is applied to a case study of the Jinchao Bridge in Guangdong Province, China, and the results are expected to provide a scientific reference for the design of new bridges and in the maintenance of existing ones in service. [ABSTRACT FROM AUTHOR]

With the rapid development of China's transportation network, the demand for bridge construction is increasing, the traffic volume is increasing yearly, and the average vehicle speed and the frequency of overloaded vehicles crossing bridges are soaring. When a vehicle passes over a highway bridge, it can easily form a coupling vibration between the vehicle and bridge due to the excitation of the expansion joint, the unevenness of the bridge deck, and the existing coating-hole. The impact effect is significant, which seriously affects the operation safety of both the vehicle and bridge, seriously damaging the service life of the bridge. Due to the influence of construction technology, it is common for the vibration to meet transverse and longitudinal expansion joints of a prefabricated girder bridge, where an aging bridge deck frequently results in bulges and potholes in asphalt pavement. The bridge vibration amplification effect under the dynamic load of heavy, high-speed vehicles is significant, and research about the large impact coefficient of bridges with local pavement deterioration is urgently needed. This study used SIMULINK simulation software and involved conducting several bridge model tests. Dynamic simulation analyses and running vehicle tests on scaled and real bridge models were carried out to study the coupling vibration response of bridge decks in the presence of different pothole sizes. The results show that the impact effect of low-speed vehicles passing through a larger-sized pothole is relatively significant, and the impact coefficient can be amplified to 214% of the original value under good road surfaces in extreme cases. The vehicle–bridge coupling impact effect of potholes is similar to bulges. This relevant work could provide suggestions for the operational performance evaluation and maintenance of bridges with local pavement deterioration. [ABSTRACT FROM AUTHOR]

The accurate measurement of cable force plays an important role in the structural form, structural behavior, and safety evaluation of large-span cable-stayed bridges. A fast cable-force estimation method is proposed based on the alignment recognition method and smartphone-captured video. This method can realize real-time, non-contact, and non-destructive force measurements. Videos of bridge cables were collected using a portable smartphone, and an alignment recognition method was employed to obtain the lateral displacement along the cable, followed by numerical differentiation of the lateral displacement of the cable to acquire the acceleration time history. Based on the fundamental dynamic equation of beam elements, a unified explicit formula for cable-force calculation considering service characteristics was established in the frequency method. Finally, the method was applied to the cable-force measurement during the operation and maintenance stage of the Gengcun Dou Bridge. The measured cable forces were compared with the values obtained from the on-site monitoring system. The results show that the proposed method can accurately identify the acceleration time history at different positions of the cable, and the corresponding frequency components are essentially consistent. The average relative deviation of the measured cable forces from the reference method is within 3%. The proposed cable-force measurement method is simple as regards equipment, convenient for operation, and high in efficiency, providing a new method for the measurement of cable forces in large-span cable-stayed bridges, which can offer reliable measured cable-force data for structural analysis during bridge operation and the maintenance stage. [ABSTRACT FROM AUTHOR]

Steel bearings have been commonly used to counteract induced loading from thermal and traffic conditions in numerous bridges. However, their effectiveness has been compromised due to aging and maintenance limitations, potentially impacting the overall bridge system performance. Existing monitoring techniques for detecting malfunctioning steel bearings lack automation and precision, making them inadequate for long-term and real-time bridge dynamics assessment. This study proposes a response-based approach to identify bearing malfunction by analyzing the traffic-induced response in the bearing vicinity. To implement this approach, laser displacement sensors and wireless acceleration sensors were employed to monitor both malfunctioning and well-functioning steel bridge bearings. Significant differences in bearing performance were observed through response analysis and comparison. Laser sensor measurements revealed larger vertical deflections in the girder at malfunctioned bearing under traffic loading. Moreover, the investigation of the acceleration response in the bearing locality indicated that bearing malfunction could alter the vibrational characteristics of the vicinity, significantly affecting Cross Power Spectral Density (CPSD) and cross-correlation. To quantitatively evaluate the performance of steel bearings, a Condition Score (CS) was introduced. The CS exhibited a strong correlation with bearing damage, providing valuable insights for maintenance and decision-making processes in bridge asset management. This study offers a comprehensive and automated method for identifying steel bridge bearing malfunction by utilizing advanced monitoring techniques and introducing the CS for assessment. The results obtained from this approach can enhance bridge maintenance strategies and contribute to effective bridge asset management. [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]

With the high-quality development of transportation in China, highway bridges, as the core part of transportation infrastructure, have received widespread attention for their safety and operation management. Especially in the field of super large bridges, due to their importance in transportation and enormous social benefits, safety and operation management are particularly crucial. This research focused on the operation and maintenance management of super large bridges, especially how to improve the efficiency and effectiveness of bridge operation and maintenance management through BIM (Building Information Modeling) technology. This technology deepened the understanding of bridge structure and performance by establishing a detailed BIM model. By standardizing model data and establishing coding systems, data interoperability and management efficiency were improved, providing decision support for the daily management and maintenance of bridges. According to experimental data, it can be concluded that the accuracy of basic information judgment, temperature and humidity accuracy, bridge status judgment accuracy, and operation and maintenance information accuracy of BIM dynamic temperature recognition and maintenance technology for bridges were among four sets of data. The accuracy rates of all four data items were between 91.20% and 94.27%, indicating a high accuracy rate. The comprehensive application of these technologies aims to improve the operation and maintenance management level of super large bridges, ensure their long-term stability and safety, and contribute to the sustainable development of transportation systems. [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]

Uncoated weathering steel (UWS) is used for bridges to minimize maintenance costs incurred due to possible steel corrosion. State highway departments often use weathering steel for bridges with the expectation that the weathering steel structure will not corrode. Weathering steel has improved corrosion-resistant behavior over conventional steel; however, weathering steel is not maintenance free and will corrode if not used in correct ambient conditions and properly maintained. Consequently, weathering steel retards corrosion but may require future restoration through cleaning and/or applying surface coatings. The Arkansas Department of Transportation (ARDOT) bridge inspection inventory includes 859 UWS bridges. Approximately 11% of these bridges have some level of oxide film degradation, AASHTO defect code 3430. These bridges are located throughout the state. Other states have also experienced this condition, resulting in state highway departments facing the dilemma of how to restore weathering steel sections that have experienced corrosion. This article reviews the extensiveness and severity of oxide film degradation at UWS bridges in Arkansas, the prevalence of UWS oxide film corrosion in other states, how oxide film corrosion progresses as a function of time, and remediation measures. [ABSTRACT FROM AUTHOR]

Bridges deteriorate due to different causes such as ageing and climatic conditions. As a consequence, repair actions are considered more expensive than maintenance. Therefore, the prediction of maintenance at the bridge network level is particularly complex due to the considerable level of heterogeneity spanning various bridge types and functions. Consequently, in this article an analytical deterioration model called 'two-step cluster analysis' is presented and applied to predict the results of a homogeneous data set. This model had been used in different fields including civil engineering but not for superstructure deterioration forecasting. Variables that interfere with the performance of the structure were considered, such as geometry, volume of traffic, among others. The results show that deterioration drop rapidly if repair treatments were not performed. Variations of up to 20.9% at 50 years between the degradation of the database and the analysis of groups, demonstrates the importance of grouping within the analysis of the database, since the late maintenance can affect the life of the bridge. Preventive actions could significantly mitigate the deterioration process. The applied methodology benefits from current bridge inspection practice and produces a probabilistic rating that is consistent with the Markov approach for model deterioration and grouping variables. [ABSTRACT FROM AUTHOR]

Modern bridge construction towards a higher degree of low carbonization and assembly has been the general trend, while developing and broadening the low-carbon and assembled-oriented Accelerated Bridge Construction (ABC) technology can better realize the trade-offs between construction quality, efficiency, cost and sustainability. In the current mainstream ABC technologies such as precast-assembled concrete bridge and assembled steel bridge schemes, it is difficult to achieve an excellent balance between the above multicriterion trade-offs. To this end, this paper proposes a novel low-carbon and assembled composite bridge scheme as an innovative case of ABC technology based on a 26.7 km-length urban viaduct project in China with urgent environmental protection and assembly demands. Construction sustainability, the comprehensive economy and low-carbon performance are well balanced by the collaborative application of new steel–concrete composite structures, the rapid assembly interface design and low-carbon material technologies. The proposed scheme has been applied to a completed real-scale bridge, and the whole construction process only experienced 105 days of effective time, accompanied with slight environmental interference and construction noise and a small amount of labor and equipment input. In addition, the safety of the bridge, the rationality of the design concept and the calculation method have been verified by the static and dynamic loading tests of the real-scale bridge. [ABSTRACT FROM AUTHOR]

One of the primary challenges in cable-stayed bridges is to assess the service performance of stay cables in response to applied loads and ensure that they meet safety requirements. This paper proposes a new strategy to analyze the time-varying reliability of the ultimate load-carrying capacity of stay cables under resistance and stress uncertainty conditions. Initially, we employ the frequency-squeezing processing (FSP) technique within the vibration frequency method (VFM) to enhance the accuracy and effectiveness of cable force identification through field measurement. Subsequently, we thoroughly discuss and establish the statistical characteristics and probabilistic models of stress, including both slow-varying trend and fast-varying trend components, as well as resistance considering the strengthening deterioration effect. The slow-varying trends of the cable forces are extracted using the moving average method (MAM), and both the extracted slow variation and the fast-varying trend components are analyzed in detail. Finally, we introduce a Gaussian process-based surrogate model to assess the time-varying structural reliability by analyzing the associated limit-state function for the ultimate load capacity of the stay cables. In this study, the proposed strategy is applied to quantify the ultimate load-carrying reliability of a stay cable under the uncertainty of the coupled action of corrosion and fatigue. Compared with conventional reliability analysis, the failure probability interval estimation shows the uncertainty boundaries and provides specific years of reliability failure, which can serve as an important reference for bridge maintenance and strengthening. [ABSTRACT FROM AUTHOR]

This paper addresses the need for accurate and objective safety assessments of bridges in Brazil taking into account the increase in traffic load and limited funding for infrastructure. In Brazil, the usual method of ensuring bridge safety involves strengthening based on design codes using deterministic analysis and partial safety factors. This method leads to an increase in the maintenance cost of the bridges. Structural reliability assessment, a higher-tier assessment method, is recommended globally for assessing the safety of existing bridges beyond current deterministic methods. This paper presents a study that evaluates the structural safety of existing road bridges in Brazil using the semi-probabilistic method defined in Brazilian standards and the full probabilistic method. The study selected six case studies of existing reinforced and prestressed concrete bridges to evaluate their structural safety concerning current normative loads. The results suggest that the partial safety factors defined in the Brazilian standards are consistent with international standards. The reliability analysis can guarantee the bridges' safety, even with increased traffic loads, without additional costs for structural strengthening. Therefore, the paper highlights the importance of promoting reliability analysis in Brazil to ensure the safety of existing bridges and promote cost-effective and objective safety assessments. [ABSTRACT FROM AUTHOR]

To reduce risk incidents in large bridge construction, it is necessary to study the interaction mechanisms and dynamic changes among various risk factors during the construction of large bridges. First, the evolution mechanism of construction risks for large bridges is analyzed, and a risk factor structure system is established. Then, based on system dynamics theory, a causal loop diagram and flow–stock diagram are constructed, and system dynamics equations for each variable in the flow diagram are established to build a system dynamics model. Finally, taking a large bridge construction project as an example, the variable equations are assigned actual values, and the construction risk level is simulated and analyzed. The results show that, ➀ continuous investment in safety funds can effectively reduce the overall risk level of the system, ➁ changes in the management risk subsystem have a significant impact on the overall risk level of large bridge construction, and ➂ increasing the safety investment ratio in both the personnel risk subsystem and the management risk subsystem can effectively reduce the total risk level of the system. [ABSTRACT FROM AUTHOR]