It is generally accepted that climate-change is leading to increased frequency of extreme weather events worldwide, and this is placing heavier demands on an already aging infrastructure-network. Bridges are particularly vulnerable infrastructure assets that are prone to damage or failure from climate-related actions. In particular, bridges over waterways can be adversely affected by flooding, specifically the washing away of foundation soils, a mechanism known as scour erosion. Scour is the leading cause of failure for bridges with foundations in water as it can rapidly compromise foundation stiffness often resulting in unacceptable movements or even collapse. There is growing interest among asset managers in applying health monitoring approaches to assess the real-time performance of bridges under damaging actions, including scour. Sensor-based approaches involve the acquisition of data such as dynamic measurements, which can be used to infer the existence of scour or other damage without the Published in Journal of Civil Structural Health Monitoring 10 (3) 2020 pp.485-496 laborious requirements of undertaking visual inspections. In this paper, a framework is proposed to assess the benefit obtained from health monitoring systems as compared to the scenario where no monitoring system is employed on a bridge, to ascertain how useful these systems are at assisting decision-making. Decisions typically relate to the implementation of traffic restrictions or even partial or complete bridge closure in the event of damage being detected, which has associated consequences for a network. A case study is presented to demonstrate the approach postulated in this paper. IntroductionExtreme weather events are becoming more frequent as a result of climate-change and this is putting increasing pressure on built infrastructure. In tandem with this, infrastructure networks worldwide are aging, and many are approaching the end of their original design lives. These two phenomena together mean it is now more important than ever to direct attention to the maintenance and management of the aging asset stock to ensure safe, reliable transport infrastructure exists for generations to come.Bridges are one of the main infrastructure assets at significant risk from climate-induced loading.Bridges with foundations in water are susceptible to scour erosion [1], whereby adverse hydraulic actions remove soil from around and under foundations compromising stability and increasing the risk of failure [2]. The occurrence of scour can cause a reduction in the stiffness and capacity of a bridge foundation [3][4][5] and lead to sudden failure.Scour is most commonly monitored by means of visual inspections, whereby divers inspect a given bridge's foundations periodically (typically at times when flooding is not occurring). Susceptible bridges are usually rated using a scale related to the perceived severity of the scour problem affecting their foundations. The main issues with this type of approach are the subjective nature of the rating schemes adop...

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This paper is integral part of the Special Issue on “Existing Concrete Structures: Structural Health Monitoring and Testing for condition assessment.” It deals with vibration‐based methods (VBMs) for damage localization that approach the problem of structural integrity management through the analysis of the dynamic response of the structure under ambient or forced vibrations. In the last years, these methods received a widespread interest in the structural health monitoring (SHM) community due to the possibility to use them for continuous SHM and real time damage identification. The performance of these methods is commonly verified on numerical models or laboratory specimens that, by their nature, cannot reproduce all the sources of uncertainties found in practice. The availability of data recorded on a real benchmark, the S101 bridge in Austria, enabled the comparison of three well known vibration‐based time‐invariant methods for damage localization, namely, the curvature method, the interpolation error method, and the strain energy method. The bridge, built in the early 1960, is a typical example of a European highway bridge. Responses to ambient vibrations were recorded both in the undamaged and in several different damage scenarios artificially inflicted to the bridge. This paper reports the results of the application of the three mentioned methods of damage localization to this case study.

One of the most discussed aspects of vibration-based structural health monitoring (SHM) is how to link identified parameters with structural health conditions. To this aim, several damage indexes have been proposed in the relevant literature based on typical assumptions of the operational modal analysis (OMA), such as stationary excitation and unlimited vibration record. Wireless smart sensor networks based on low-power electronic components are becoming increasingly popular among SHM specialists. However, such solutions are not able to deal with long data series due to energy and computational constraints. The decentralization of processing tasks has been shown to mitigate these issues. Nevertheless, traditional damage indicators might not be suitable for onboard computations. In this paper, a robust damage index is proposed based on a damage sensitive feature computed in a decentralized fashion, suitable for smart wireless sensing solutions. The proposed method is tested on a numerical benchmark and on a real case study, namely the S101 bridge in Austria, a prestressed concrete bridge that has been artificially damaged for research purposes. The results obtained show the potential of the proposed method to monitor the conditions of civil infrastructures.

This paper addresses the structural health monitoring (SHM) of the bell tower of the Basilica of San Pietro in Perugia, Italy, which is located in a seismic area. Known as one of the landmarks of the Umbrian capital, the tower belongs to a monumental complex of exceptional historical and cultural value. Therefore, its protection with respect to earthquakes is an important issue. To this purpose, a vibration-based SHM system able to detect anomalies in the structural behaviour by means of statistical process control tools has been installed in the tower and is under continuous operation since December 2014. The effects of the 2016-2017 Central Italy seismic sequence were clearly detected by this system, even if earthquakes took place at relatively large distance from the bell tower. The large amount of SHM data collected over four years allowed to assess the modifications in the structural behaviour of the bell tower in post-earthquake conditions.