Explore the vast range of titles available.

Structural health monitoring (SHM) systems have been developed to evaluate structural responses to extreme events such as natural and man-made hazards. Additionally, the increasing volume of users and vehicle sizes can lead to the sudden damage and collapse of bridge structures. Hence, structural monitoring and dynamic characteristic analyses of bridge structures are critical and fundamental requirements for bridge safety. SHM can overcome the weaknesses of visual inspection practices, such as lack of resolution. However, because of computational limitations and the lack of data analysis methods, substantial quantities of SHM data have been poorly interpreted. In this paper, the SHM of bridges based on dynamic characteristics is used to assess the \"health state\" of bridge structures. A comprehensive SHM system using vibration-based techniques and modal identification for bridge structures are well defined. Some advanced concepts and applications regarding bridge safety evaluation methods, including damage detection and load-carrying capacity, are reviewed. For the first time, the pros and cons of each vibration technique are comprehensively evaluated, providing an advantage to the authority or structural owner when developing a bridge management database. This information can then be used for continuous structural monitoring to access and predict the bridge structure condition.

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

Recent earthquakes have demonstrated a significant contribution of the masonry infill walls in the structural response of the reinforced concrete (RC) buildings. Field observations after the 25th April’s earthquake in Nepal reinforce the conclusion regarding the influence of the infill walls increasing significantly the structural stiffness, which has a direct impact on the natural frequencies of the structure and of structural elements. Firstly the manuscript focuses on the performance of the infilled RC structures, describing common Nepalese architectural configurations and the major damages observed in infilled RC buildings. Secondly, it shows results from data collected on ambient vibration tests performed in seven infill panels with different characteristics, such as geometric dimensions, openings and levels of damage. These results are used to study the influence of each parameter in the out-of-plane frequency of the wall panels. The present studies along the manuscript are followed by a presentation of the study cases (buildings and the walls), test setups, main results and conclusions.

This study introduces a method for processing various types of random real-world signals from bridges in both experimental models and real-world scenarios using a wireless sensor system. By analyzing and processing signals collected during actual traffic on bridges, the study identifies and provides parameters that meet current quality inspection requirements to ensure the safety of bridge users. The parameters investigated in this study include deformation, natural frequency, amplitude, impact factor, and damping coefficient. Research has determined and highlighted key parameters to assess the quality of bridge spans to meet quality inspection standards. Using actual traffic vibration signals provides accurate and useful information that supports the government in conducting regular inspections. Furthermore, this study reduces inspection costs for regulatory agencies by significantly reducing costs compared to traditional methods, offering economic benefits. In general, this research not only introduces a new approach to vibration signal processing, but also brings practical benefits to bridge infrastructure management and inspection.

The Olla bridge, built in the second half of the nineteenth century, is an arch bridge consisting of five brick masonry arches with stone masonry piers. The bridge crosses the Stura river along the State Route SS 21, connecting the French border with the South-West part of the Piedmont region, and still represents a crucial node for the local commercial traffic. The paper summarises selected results of the extensive research programme carried out to assess the structural conditions of the historic bridge, which exhibited local damage of the arches and diffused surface decay. After a discussion on the common issues arising in the structural assessment of historical infrastructures, the Olla bridge is described and full details are given on the different steps of the investigation: (a) historical research, geomatic survey, on-site visual inspection and limited local tests on materials; (b) operational modal testing and analysis; (c) development of a FE model based on architectural research and selected modelling assumptions; (d) choice of the uncertain structural parameters and identification of the optimal parameters based on the experimentally obtained data.

The output-only modal analysis is ubiquitously used for structural health monitoring of civil engineering systems. The measurements for such applications require the use of multiple data acquisition systems (DAS) to avoid complicated meshes of cables in high-rise buildings, avoid traffic constriction on a bridge during measurements, or to avoid having limited channels in a single DAS. Nevertheless, such requirements introduce time synchronization problems which potentially lead to erroneous structural dynamic characterization and hence misleading or inconclusive structural health monitoring results. This research aims at proposing a system-identification-based time synchronization algorithm for output-only modal analysis using multiple DAS. A new procedure based on the compensation of the phase angle shifts is proposed to identify and address the time synchronization issue in ambient vibration data measured through multiple DAS. To increase the robustness of the proposed algorithm to the inherent inconsistencies in these datasets, the kernel density function is applied to rank multiple time-shift estimates that are sometimes detected by the algorithm when inaccuracies exist in the data arising from low signal-to-noise ratio and/or presence of colored noise in the ambient excitations. First, the synchronized ambient vibration dataset of a full-scale bridge is artificially de-synchronized and used to present a proof of concept for the proposed algorithm. Next, the algorithm is applied to ambient vibration data of a 30-story, reinforced concrete building, where the synchronization of the data could not be achieved using two DAS despite best efforts. The application of the proposed time synchronization algorithm is shown to both detect and correct the time synchronization discrepancies in the output-only modal analysis.

In-service prestressed concrete box girder bridges have received increasing attention in recent years due to a large number of bridges reaching decades in service. Therefore, the ageing of infrastructure demands the development of robust condition assessment methodologies based on affordable technology such as vehicle-induced vibration tests (VITs) in contrast with more expensive existing technologies such as tests using hammers or shakers. Ambient vibration tests (AVTs) have been widely used worldwide, taking advantage of freely available ambient excitation sources. However, the literature has commonly reported insufficient input energy to excite the structure to obtain satisfactory modal identification results, especially in long-span concrete bridges. On the other hand, the use of forced vibration tests (FVTs) requires more economic resources. This paper presents the results of field measurements at optimally selected locations in VITs consisting of a 32-ton truck and a springboard with a height of 50 mm. AVTs using optimal sensor placement (OSP) provide similar results to VITs without considering OSP locations. Additionally, the VIT/AVT cost ratio is reduced to 2 since a shorter data collection time is achieved within a one-day (8 h) test framework, which minimizes temperature effects, thus leading to improvements in AVT identification results, especially in vertical modes.

The Guadalquivir bridge is a large-scale twin steel truss bridge located in Spain that opened to traffic in 1929. Since the bridge has come into operation for a long time, structural health monitoring (SHM) is strictly necessary to guarantee safety and avoid serious incidents. This paper proposes a novel approach to model updating for the Guadalquivir bridge based on the vibration measurements combined with a hybrid metaheuristic search algorithm. Cuckoo Search (CS) is an evolutionary algorithm derived from global search techniques to look for the best solution. Nevertheless, CS contains some fundamental defects that may reduce its effectiveness in dealing with optimization issues. A main drawback of CS arises in the low convergence level because CS applies fixed values for parameters when looking for the optimal solution. In addition, CS relies a lot on the quality of original populations and does not have the capability to enhance the quality of the next generations. If the position of the original particles is far from the optimal places, it may be challenging to look for the best solution. To remedy the shortcomings of CS, we propose a hybrid metaheuristic algorithm (HGAICS) employing the advantages of both Genetic Algorithm (GA) and Improved Cuckoo Search (ICS) to solve optimization problems. HGAICS contains two outstanding characteristics as follows: (1) GA is employed to create original particles with the best quality based on the capacity of crossover and mutation operators and (2) those particles are then applied to look for the global best derived from the flexible and global search ability of ICS. This paper also presents the application of wireless triaxial sensors (WTSs) taking the place of classical wired systems (CWSs) to the measurements. The use of WTSs increases dramatically the freedom in setting up experimental measurements. The results show that the performance of the proposed hybrid algorithm not only determines uncertain parameters of the Guadalquivir bridge properly, but also is more accurate than GA, CS, and improved CS (ICS). A MATLAB package of the proposed method (HGAICS) is available via GitHub: https://github.com/HoatranCH/HGAICS.

Bridges are fundamental components of transportation infrastructure, facilitating the efficient movement of people and goods. However, the conservation of heritage bridges introduces additional challenges, encompassing environmental, social, cultural, and economic dimensions of sustainability. This study investigates risk mitigation strategies for a heritage-listed, 120-year-old reinforced concrete bridge in Australia—one of the nation’s earliest examples of reinforced concrete construction, which remains operational today. The structure faces multiple risks, including passage of overweight vehicles, environmental degradation, progressive crack development due to traffic loading, and potential foundation scouring from an adjacent stream. Due to the heritage status and associated legal constraints, only non-invasive testing methods were employed. Ambient vibration testing was conducted to identify the bridge’s dynamic characteristics under normal traffic conditions, complemented by non-contact displacement monitoring using laser distance sensors. A digital twin structural model was subsequently developed and validated against field data. This model enabled the execution of various “what-if” simulations, including passage of overweight vehicles and loss of foundation due to scouring, providing quantitative assessments of potential risk scenarios. Drawing on insights gained from the case study, the article proposes a six-phase Incident Response Framework tailored for heritage bridge management. This comprehensive framework incorporates remote sensing technologies for incident detection, digital twin-based structural assessment, damage containment and mitigation protocols, recovery planning, and documentation to prevent recurrence—thus supporting the long-term preservation and functionality of heritage bridge assets.

The paper investigates the dynamic characterisation, the numerical model tuning and the seismic risk assessment of two monumental masonry towers located in Italy: the Capua Cathedral bell tower and the Aversa Cathedral bell tower. Full-scale ambient vibration tests under environmental loads are performed. The modal identification is carried out using techniques of modal extraction in the frequency domain. The refined 3D finite element model (FEM) is calibrated using the in situ investigation survey. The FEM tuning is carried out by varying the mechanical parameters and accounting for the restraint offered by the neighbouring buildings and the role of soil–structure interaction. The assessment of the seismic performance of the bell towers is carried out through a nonlinear static procedure based on the multi-modal pushover analysis and the capacity spectrum method. Through the discussion of the case studies, the paper shows that the modal identification is a reliable technique that can be used in situ for assessing the dynamic behaviour of monumental buildings. By utilising the tuned FEM of the towers, the theoretical fundamental frequencies are determined, which coincide with the previously determined experimental frequencies. The results from seismic performance assessment through a pushover analysis confirm that the masonry towers in this study are particularly vulnerable to strong damage even when subjected to seismic events of moderate intensity.