Bridge Owners Research Articles

State-of-art review of resilience of bridges and bridge networks

In recent years, many attempts have been made to incorporate resilience frameworks into decision making, establish the best use of available resources and reduce the impact of hazards on bridges and bridge networks. However, scholarly research in this area is still in its early phases, with minimal exploration of research gaps and future prospects. A state-of-the-art review of bridge and bridge network resilience studies using a science mapping approach is presented here. Research on the topic was obtained from the Scopus literature database. The literature database was then analysed using VOSviewer and Nvivo tools to display the domain-specific body of knowledge. The study then focused on the most prolific researchers and disaster types, bridge resilience assessment approaches, current research trends, future directions and theoretical and practical implications. The research paradigm on the resilience of bridges and bridge networks is changing toward the usage of digital tools and technologies. In this context, a framework id proposed by integrating building information modelling/geographic information systems and digital twin models. The proposed framework can aid bridge owners in accumulating iterative data, creating multi-hazard disaster preparedness policies and designing and enhancing life-cycle management and maintenance tasks of bridges and bridge networks.

Application of Deep Convolutional Generative Adversarial Network to Identification of Bridge Structural Damage

In recent years, the increase in the number of vehicles on the road has impacted the service life of bridges, and thus, their performance. In China, bridge inspections must be performed and documented at least once per year using labor-intensive and subjective approaches. In this study, a computationally efficient damage identification methodology for bridges was developed based on a deep convolutional generative adversarial network (DCGAN). To predict the damage to bridges, the vibration data of the structural damage are extracted from sensor measurements on the bridges and applied to the DCGAN model. The proposed damage identification method was validated on a simple supported beam bridge and a continuous girder bridge. The effects of sample size and noise on the identification accuracy were also evaluated. The performance of the DCGAN in the damage identification process is robust and reliable. This method for structural health monitoring offers a more objective evaluation of the overall performance and condition of a bridge, thus enabling bridge owners to efficiently allocate finite maintenance resources.

Bridging the Gap: commodifying infrastructure spatial dynamics with crowdsourced smartphone data

Structural information deficits about aging bridges have led to several avoidable catastrophes in recent years. Data-driven methods for bridge vibration monitoring enable frequent, accurate structural assessments; however, the high costs of widespread deployments of these systems make important condition information a luxury for bridge owners. Smartphone-based monitoring is inexpensive and has produced structural information, i.e., modal frequencies, in crowdsensing applications. Even so, current methods cannot extract spatial vibration characteristics with uncontrolled datasets that are needed for damage identification. Here we present an extensive real-world study with crowdsourced smartphone-vehicle trips within motor vehicles in which we estimate absolute value mode shapes and simulate damage detection capabilities. Our method analyzes over 800 trips across four road bridges with main spans ranging from 30 to 1300 m in length, representing about one-quarter of bridges in the United States. We demonstrate a bridge health monitoring platform compatible with ride-sourcing data streams that check conditions daily. The result has the potential to commodify data-driven structural assessments globally.

Structural Health Monitoring for Dębica Railway Steel Arch Bridge in Poland

The study presents the vibration-based SHM system for the Dębica railway bridge located in Poland. The railway bridge owner was concerned about the excessive and self-excited vibrations of the hangers, the vibration measurement of 8 hangers per span in a total of two spans being monitored. The dynamic responses in both the transverse and longitudinal directions for each hanger under different load events over a nine-month period were recorded and introduced in this paper. The tension force and stress on each hanger are estimated through the natural frequency of the experimental vibration analysis. The proposed approaches could be used to develop a smart alarm system integrated into a vibration-based data-driven SHM system for heavy railway bridges.

Framework for rational decision-making in bridge maintenance

Bridges are deteriorating, and their safety must be continuously assessed. Efficient management of bridges is essentially about making decisions on maintenance activities in line with the decision maker’s preferences. In other words, structural safety should be ensured while optimally allocating resources. In theory, methods are available for solving this complex task; however, they have not yet been implemented by bridge owners. In this study, the implementation into practice is facilitated by presenting a consistent framework for rational decision-making. It is argued that structural assessment is a decision problem that infrastructure owners are obliged to take responsibility for. Bayesian decision theory is presented as the theoretically ideal decision-making framework. The main components of the framework—representations of structural reliability and failure consequences—are discussed in detail, and human safety constraints are integrated. For demonstration purposes, the decision-making framework is applied to two case studies. In addition, it is parameterised by the relative cost of the intervention to failure and the current failure probability to be applicable for any assessment situation. In that way, this study contributes to more efficient maintenance of single bridges and the development of generally applicable structural codes for assessing existing structures.

Improved bridge modal identification from vibration measurements using a hybrid empirical Fourier decomposition

Bridge health monitoring has been a prominent focus within the global engineering community. Bridge owners, stakeholders, and engineers face the formidable tasks of ensuring efficient monitoring, conducting reliable data analysis, interpreting data logically, and making timely decisions. With the increasing global infrastructure deficit, there is an ever-increasing need to develop reliable and economical bridge monitoring solutions. In this paper, a bridge condition assessment technique is proposed that can utilize the vibration data collected from the instrumented sensors and provide reliable system identification results. The proposed method develops a hybrid approach by integrating the Natural Excitation Technique (NExT) and Empirical Fourier Decomposition (EFD) to analyze ambient bridge vibration data and determine the modal parameters of the bridge. First, NExT is formulated to determine the cross-correlation functions of the bridge measurements, and then EFD is explored to decompose the signals into their monocomponents to identify the bridge modal parameters. The proposed methodology can overcome mode mixing and perform modal identification of a system with closely spaced frequencies and low energy modes. The estimated modal parameters such as bridge frequencies, mode shapes, and damping ratio are used for condition assessment of numerical, experimental and full-scale structures, including a short-span steel bridge located in Ontario, Canada. The results demonstrate that the proposed methodology can provide accurate and robust estimates of bridge modal parameters. Future research is reserved for real-time implementation of the proposed methodology for a wide range of civil structures.

Corrosion-induced fragility of existing prestressed concrete girder bridges under traffic loads

Italian and European transportation networks include a significant number of existing bridges, built since the early ‘60s, characterised by simply supported prestressed concrete (PC) girders with post-tensioned steel tendons. Corrosion of tendons, which may lead to significant loss of structural capacity, cannot be detected by simple visual inspections and requires advanced and expensive testing by bridge owners. Therefore, procedures aimed at risk-informed prioritisation of advanced inspections and possibly retrofit are needed. The paper presents a study on the fragility of existing PC girder bridges considering traffic loads, accounting for corrosion-induced effects. An automated framework is proposed, aiming at the efficient probabilistic structural assessment of the investigated bridge typology accounting for different critical corrosion scenarios and the influence of knowledge-based uncertainty related to geometric and mechanical properties. To simulate corrosion effects, prestressing steel tendon geometric and mechanical characteristics are modified through a specific algorithm able to estimate variations in flexural and shear bearing capacity of critical cross-sections. To simulate the traffic loads, a simplified analysis is performed by using code-based traffic load models. In the paper, the framework is tested with reference to a dataset of case-study superstructures. The obtained fragility curves are deeply discussed, highlighting the effects of the number of girders and span length on the corrosion-induced increase in fragility. Although the proposed methodology presents some simplifications, it could improve the current practices of risk prioritisation, by supporting transportation authorities in ensuring the safety of the existing bridge stock.

Smart Bridge Damage Assessment through Integrated Multi-Sensor Fusion Vehicle Monitoring

Abstract. This study explores the efficacy of vehicle-assisted monitoring for bridge damage assessment, emphasizing the integration of diverse sensor data sources. A novel method utilizing a deep neural network is proposed, enabling the fusion of fixed sensors on bridges and onboard vehicle sensors for damage assessment. The network offers scalability, robustness, and implementability, accommodating various measurement types while handling noise and dynamic loading conditions. The main novel aspect of our work is its ability to extract damage-sensitive features without signal preprocessing for future bridge health monitoring systems. Through numerical evaluations, considering realistic operational conditions, the proposed method demonstrates the capability to detect subtle damage under varying traffic conditions. Findings underscore the importance of integrating vehicle and bridge sensor data for reliable damage assessment, recommending strategies for optimal monitoring implementation by road authorities and bridge owners.

A framework for decarbonisation for bridge owners, engineers and designers

The Net Zero Bridges Group brings together bridge specialists concerned to lower the carbon dioxide footprint of their work, and to understand collectively how best to do so. Achieving net zero carbon dioxide by 2050 is the best way to mitigate the severity of the climate emergency. In addition to social consequences, failure will make ensuring the climate resilience of transport infrastructure increasingly difficult. Bridge engineers must rapidly develop new knowledge and skills, and commit to gradual but steady decarbonisation compatible with agreed climate pathways and timelines. Prioritising decarbonisation requires making different decisions to those traditionally made. The carbon dioxide reduction hierarchy asks that measures be prioritised to ‘avoid, switch and improve’. Applying these to bridge engineering requires bold choices, while managing risk effectively. The project life cycle must be rethought to allocate sufficient time at the right time. Above all, the challenge requires collaborative, collective action, to share data and best practice, rather than working in isolation. This paper sets the above in an overriding framework for action, and provides an overview of current thinking for decarbonising bridge construction and maintenance. It identifies priorities for the industry to tackle within the next few years.

Analysis of the information flux model among all the actors involved in the use of a Bridge Management System according to Italian Guidelines: the BMS as a collaborative workplace

Bridges are critical elements in an infrastructural system for the resilience of the transportation network. It is important to guarantee proper maintenance of these structures since they are strategic for the economic and social welfare and support access to emergency services.The adoption of Italian Guidelines for the classification, risk management, safety and monitoring of existing bridges primarily introduces common instructions in periodic bridge inspections. At the same time, they suggest the use of digital instruments to collect data derived by the application of the guidelines.Bridge Management Systems (BMS) can absolve to this requirement and represent an additional value compared to a mere digital archive. From one hand, they are a tool for bridge owners to manage information to guarantee a proper maintenance while complying with budget and founding limitations defined by the Ministry. On the other hand, technicians can exploit them for data collection during bridge inspections and in-depth structural assessment.Thus, the creation of a collaborative workplace is one of the main requirements in the construction of a valid BMS. However, the information fluxes among the subjects can be complex inside a BMS from a management point of view. For instance, BMS must be a place where technicians can insert and receive information accordingly to their task and expertise. For this reason, it is important to ensure the possibility to differentiate data access levels and associate data property and responsibility.After briefly discussing the roles of each actor - technicians, bridge owners, Ministry - involved in the use of a BMS, this paper describes the interaction among all these figures and provides the flux model that has been implemented in INBEE, a new BMS that applies the latest version of the Italian Guidelines.

Application of the Italian Guidelines for Risk Classification and Management of Bridges on a Large Sample Owned by Local Municipalities

In recent years the creation of bridge inventory databases in Italy has become one of the main tasks for bridge owners, in appliance of the Italian Guidelines for the classification, risk management, safety evaluation and monitoring of existing bridges and the early published Operating Instructions. Following the new guidelines, it is finally possible to know the characteristics and the state of conservation of bridges of a complex infrastructural system such as the Italian. The present work provides a statistical analysis on the application of the guidelines over a large sample of bridges owned by local municipalities. In general, these bridges differentiate from bridges owned by highway and country road bodies for dimensions, structural characteristics, and levels of exposure. Therefore, this analysis allows to provide more insights on the bridge characteristics and state of conservations of the Italian infrastructures.

Evaluation of non-destructive techniques for inspection of post- tensioned concrete bridges

Reinforced concrete bridges with post-tensioned (PT) cables are particularly critical structures, as the degradation of the tendons is not fully detectable through conventional investigation methods and/or through visual inspections, due to the intrinsic nature of the structural typology. In fact, PT cables are encased in plastic or metal ducts which aim at protecting them from corrosion, but at the same time hide them making it impossible to evaluate their condition by visual inspection alone. Deterioration conditions of PT systems are broadly categorized into strand defects and grout defects. The deteriorated conditions of PT systems usually lead to a loss of prestressing force, with impacts on the bridge management in the form of reduced load capacity and structural safety, need for expensive rehabilitation interventions, and traffic disruption.Modern inspection guidelines have identified non-destructive (ND) methods suitable for evaluating the conditions of the tendons and the grout. Moreover, ND technologies used in other industries may have potential for PT bridge assessments. The present contribution aims at presenting a simple procedure to rank the non-destructive (ND) methods, that are currently used for investigating the deterioration of tendons and grout, through a series of metrics formulated to evaluate the various technologies under four different aspects, namely accuracy of measurement, ease of use, cost, and impact on the operation of the bridge. The goal is to provide the bridge owners with a decision tool that can assist them in the selection of the optimal ND technology for the evaluation of a particular strand or grout defect.

In-service performance assessment of fire-corrosion damaged cables of bridges

Cable-supported bridges are prone to fire hazards, and the corrosion within further compromises their structural integrity. The present study provides a novel framework for assessing fire-corrosion damage of steel wires currently in use. The relations and failure modes of steel wires under coupled effects of fire-corrosion are established by conducting the tensile test utilizing the replaced steel wires after the fire. Experimental studies found that the deterioration tendency of in-service steel wires after the fire is consistent with that of intact ones, while the corrosion level and position of steel wire have a significant impact on its ultimate strain. To predict the residual mechanical properties of cables after the fire-corrosion coupled damage, a comprehensive database of steel wires properties after the fire is established, and then a data-driven surrogate model is proposed. Finally, four grades are suggested to evaluate various damage degrees of in-service cables under corrosion and fire. The findings can provide bridge owners with guidance on how to replace or repair the damaged components after accidents or natural disaster, thereby increasing the reliability and lifespan of bridges and decreasing the costs associated with maintenance, reconstruction, and replacement.

Portable automatic detection system with infrared imaging for measuring steel wires corrosion damage

Accurate, cost-efficient and lightweight quantitative detection of steel wire corrosion in cable is an unsolvable issue that puzzles researchers and bridge owners. This paper proposed a portable automatic detection system for quantitative corrosion detection of replaced steel wires. The developed system consists of three parts (an automatic detection device, high-precision infrared imager, and corrosion evaluation algorithm). The proposed method is derived on the basis of Joule's law and the formula for calculating heat release. Then, the corroded specimens with different corrosion degrees and corresponding mass loss ratio were obtained by pre-corroded test to simulate industrial air corrosion and pickling test. The prior knowledge acquisition test utilizing presented automatic detection equipment was conducted to acquire the surface temperature of steel wires with various corrosion ratios by infrared camera after electric heating. Subsequently, the optimal quantitative corrosion prediction model after electric excitation is selected after infrared image processing, outlier filtering, theoretical method comparison, and model modification. Finally, the damaged steel wires from an in-service cable-stayed bridge are chosen to validate the proposed model's generalization ability and predictive accuracy. Furthermore, based on the discovery of characteristics on surface temperature of corroded steel wires after heating, the automatic detection device can be upgraded to realize the quantitative detection of in-situ corrosion of bridge cable.

Decision support and structural assessment of a corroding reinforced concrete bridge considering new information

Periodic visual inspections are the primary assessment method to ensure structural safety of existing bridges in practice. The influence of the collected inspection data on the structural reliability and consequential mitigation actions is usually only considered qualitatively. Advanced methods are available for consistent decision-making based on structural reliability analysis informed by inspection data. To demonstrate the practical implementation of advanced methods, the concepts are applied in a case study. Corrosion initiation by chlorides and corrosion propagation are modelled and updated with measurement data using Bayesian networks, resulting in a distribution of reinforcement cross-section loss. This loss is incorporated into the shear failure limit state, on which basis the probability of failure is estimated. In this modelling chain, the information from the chloride measurements directly influences the reliability assessment. The framework is also applicable to other deterioration phenomena and inspection data. This work provides bridge owners with methods to rationalise maintenance activities and ensure safe bridges on a limited budget.

Development of BrIM-Based Bridge Maintenance System for Existing Bridges

Globally, bridges are rapidly aging, and traditional maintenance approaches face significant challenges in terms of efficiency and cost. To overcome these challenges, considerable research has been conducted to introduce enhanced bridge management systems (BMSs) based on bridge information modeling (BrIM) from various perspectives. However, most studies have highlighted the advantages of BrIM, while neglecting the practical issues that potential users may encounter on existing bridges. The primary problem is digitizing existing bridges that have not yet adopted BrIM. The universal applicability of BrIM should be carefully considered from the perspective of national maintenance authorities managing thousands of bridges, because modeling based on commercial software is expected to be time-consuming and costly. Therefore, in this study, information and functional requirements were derived from interviews with stakeholders, including bridge owners, managers, and site inspectors. Based on this understanding, a data-driven modeling approach using basic bridge information was implemented, and an inventory code system was integrated to efficiently manage and utilize the data. Moreover, mapping and deep learning-based vectorization were considered for managing inspection information, and features for bridge assessment, dashboards, and reporting were incorporated to support decision-making. The developed BrIM demonstrated the potential for enhancing maintenance efficiency through a case study. Particularly, significant improvements were observed in mandatory documentation tasks, along with their investigation and analysis, as required by regulations. Additionally, efficient modeling and data management were achieved for the existing bridge.

How to make Monitoring more attractive to Bridge Owners

AbstractThere is a wide gap between bridge owners needs and scientist's desire. Monitoring based assessment of bridges has therefore not really arrived in bridge managers processes. We have to do the necessary only, work out clear objectives, present plausible explanations, offer interfaces to LCE and BIM, create standard applications with plenty of references and submit results that fit into the owners’ work process. How to do this will be explained presenting actual cases from the world longest suspension bridge (Canakkale Bridge 2023m span), several bridge cases in India and China as well as Offshore Applications.

Assessment of bridge Post‐Tensioning systems using non‐destructive (ND) inspection methods

AbstractReinforced concrete bridges with post‐tensioned cables are particularly critical structures, as the degradation of the tendons is not fully detectable through conventional investigation methods and/or through visual inspections, due to the intrinsic nature of the structural typology. After shortly reviewing the main applications of current non‐destructive (ND) methods available for investigating the deterioration of tendons and grout, the paper presents a simple procedure to rank these methods through a series of metrics formulated to evaluate the various technologies under four different aspects: accuracy of measurement, ease of use, cost, impact on the operation of the bridge. The procedure has the aim of providing bridge owners with a decision tool which can assist in the selection of the optimal ND technology available to detect a particular strand or grout defect.

Measurements, Simulation, Analysis and Geolocation in a Digital Twin tool for bridge management

AbstractThis paper presents a digital‐twin based tool that can be used for bridge management. The tool offers various capabilities that include embedding BIM geometries, simulations, measurements, GIS location, and performance analysis. These features enable efficient and effective management of bridges by providing detailed information and analysis of the bridge's performance, which can help in identifying potential issues and implementing appropriate solutions. The methodology represents one of the outcomes of Ashvin, an H2020 project aimed to providing assistant solution for design, construction and management of infrastructure systems. The hitherto obtained findings include this digital tool which can be of practical and beneficial use for bridge owners and operators, as it can help them to organize and centralize the bridge data in a way it helps making informed decisions regarding the maintenance, repair, and replacement of bridges. Overall, this paper highlights the importance of embracing technology in the management of critical infrastructure such as bridges, which can significantly improve their performance and extend their lifespan.

A temperature-driven approach for quantitative assessment of strengthening effect of continuous bridges using structural health monitoring data

The stiffness degeneration of small to medium span bridges has been increasingly observed in recent years, and it has become a major concern of government and bridge owners. A quantitative evaluation method for the bridge performance with strengthening measures is highly desired. Due to the advantages of uninterrupted traffic and long-term tracking capability, a temperature-driven approach for characterization of the correlation pattern between bridge temperature-induced strains and bridge status was proposed in the present study by using structural health monitoring data. First, a theoretical solution of the simplified bridge model was derived to establish the correlation between the stress and deterioration extent under temperature gradient load. After a numerical simulation that combines the thermal–structural interaction analysis and the vehicle–bridge interaction analysis, the strain range was proposed as an assessment index to ensure the stability and effectiveness of the evaluation results. Next, the Generalized Extreme Studentized Deviate method was used for detecting the outliers. The statistical results of the assessment index for different strengthening methods were compared to evaluate the associated strengthening efficiency, and the associated equivalent section height was calculated for visualizing the bridge condition after strengthening measures were taken. The results demonstrated that the proposed temperature-driven method was able to quantitatively evaluate the bridge strengthening effects with a high efficiency.