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Scour is a significant cause of bridge failure, and resulting bridge closures are likely to generate significant disruption to infrastructure networks. The management of scour-susceptible bridges is a significant challenge for improving transport resilience, but tends to be heuristic and qualitative. Such assessments often suffer from insufficient knowledge of key factors and require assumptions, which may increase their estimation and relative uncertainty. Analysis of publicly available technical documents reveals that various definitions of “risk” are adopted, as well as multiple approaches are applied. This paper has three objectives: (i) to illustrate the concept of risk in bridge scour management; (ii) to propose a simple scoring system to analyse existing risk-based approaches to manage bridge scour; and (iii) to analyse and compare such approaches on the basis of the obtained scores. A sample of nine documents containing bridge scour risk assessment practices or approaches was analysed using the developed rating system.

This paper compares the application of two recently published guidance documents for risk-based assessment of hydraulic actions on bridges, namely the UK Design Manual for Roads and Bridges and the Italian Ministry of Infrastructure and Transport’s Guidelines, to two case study bridges (Staverton Bridge, UK; Borgoforte Bridge, Italy). This work is one of the first to illustrate how to apply these guidelines. Both documents present risk-based methods for the assessment of hydraulic actions, while exhibiting fundamental differences. For example, the UK method prescribes calculations for local and constriction scour, water depth, and velocity at several cross-sections; by comparison, the Italian method does not prescribe calculations to assess the risk level. For the case studies in this paper, the hydraulic risk obtained for Staverton Bridge resulted as ‘High’ using both methods. The scour score for the Borgoforte Bridge resulted higher using the Italian method (Medium-High), as compared to the UK approach (Medium). This difference is due to how the guidelines assess the vulnerability associated with the minimum clearance. The comparison of these two risk-based approaches and the resulting discussion may serve as a useful resource for those wishing to develop new risk-based methods for assessing hydraulic actions on bridges.

Bridge scour is a leading cause of failure for bridges over waterways and is notoriously difficult to detect with accuracy. Dynamic Structural Health Monitoring (SHM) of bridges for scour has gained traction in recent years as monitoring systems have improved and the reliability of measurements increased. Due to the large number of bridges on typical networks and the limited financial resources within asset management agencies, decision-makers must prioritize certain structures when it comes to management in the event of flooding. The decision to install a dynamic SHM system on a bridge must be balanced by the financial benefit of doing so, as limited resources often need to be carefully rationed. In this paper, a methodology is proposed to evaluate such benefit based on the Value of Information (VoI) from Bayesian decision analysis. A case study is presented whereby a dynamic SHM system is considered to be installed on a typical bridge with the aim to support emergency management operations during flooding. The proposed methodology allows computation of the financial benefit of installing a dynamic SHM system over a certain reference period, thus accounting for multiple flood events and scenarios. The various elements of the procedure are discussed in detail.

One of the most interesting applications of Structural Health Monitoring (SHM) is the possibility of providing real-time information on the conditions of civil infrastructures during and following disastrous events, thus supporting decision-makers in prompt emergency operations. The Bayesian decision theory provides a rigorous framework to quantify the benefit of SHM through the Value of Information (VoI) accounting for different sources of uncertainties. This decision theory is based on utility considerations, or, in other words, it is based on risk. Instead, decision-making in emergency management is often based on engineering judgment and heuristic approaches. The goal of this paper is to investigate the impact of different decision scenarios on the VoI. To this aim, a general framework to quantify the benefit of SHM information in emergency management is applied to different decision scenarios concerning bridges under scour and seismic hazards. Results indicate that the considered decision scenario might tremendously affect the results of a VoI analysis. Specifically, the benefit of SHM information could be underestimated when considering non-realistic scenarios, e.g., those based on risk-based decision-making, which are not adopted in practice. Besides, SHM information is particularly valuable when it prevents the selection of suboptimal emergency management actions.

Aging structural components, together with the increasing transportation needs and limited budgets, are challenging aspects that typically concern decision-makers and infrastructure owners. Although Structural Health Monitoring (SHM) has been a powerful tool to optimize maintenance-related activities and post-disaster emergency management, the sensor readout and, therefore, the outcome of the monitoring system is susceptible to errors due to malfunctioning. For years, the Value of Information (VoI) has been studied to quantify the long- term benefit of SHM systems against the initial investment in sensing instrumentation without considering the eventuality of faulty sensing nodes. However, these are very common in field applications. This paper proposes a new framework to calculate the benefit of using Sensor Validation Tools (SVTs) before calculating the damage-sensitive features that drive the SHM process. The novel approach extends the traditional Vol to consider multiple “health” states of the SHM system, associate the outcome of the SHM system with the state of both the structure and the SHM system, and quantify the additional value obtained from SVTs.

This paper is focused on the description and application of an extended version of the Interpolation Method for the damage localization where a statistical characterization of the indicator is prop...

In the aftermath of a seismic event, decision-makers have to decide quickly among alternative management actions with limited knowledge on the actual health condition of buildings. Each choice entails different direct and indirect consequences. For example, if a building sustains low damage in the mainshock but people are not evacuated, casualties may occur if aftershocks lead the structure to fail. On the other hand, the evacuation of a structurally sound building could lead to unnecessary financial losses due to business and occupancy interruption. A monitoring system can provide information about the condition of the building after an earthquake that can support the choice between several competing alternatives, targeting the minimization of consequences. This paper proposes a framework for quantifying the benefit of installing a permanent seismic structural health monitoring (S2HM) system to support building evacuation operations after a seismic event. Decision-makers can use this procedure to preventively evaluate the benefit of an SHM system and decide about the worthiness of its installation.

Structural Health Monitoring (SHM) allows tracking the structural behavior in time and support decisions regarding, for instance, the need for maintenance and repair activities. Most traditional SHM systems require sensors that are directly applied to the structure to get insights into the structural performance. Satellite technologies can provide an appealing alternative to traditional SHM. They allow to measure displacements at a large scale and to follow their evolution without the need of directly accessing the structure. Further to this, the possibility to monitor large areas opens new avenues for the development of automatic alert systems able to issue an alarm and early-flag damaged structures. However, displacements of civil structures might also be induced by sources other than damage such as thermal or periodic hydrogeological variations. These can hinder the onset and development of damage or lead to false alarms if such displacements are erroneously interpreted as damages. This paper aims to present a new method for damage detection based on DInSAR measurements, that tackles both aspects providing reliable information about the onset of damage under environmentally changing conditions in a period corresponding to about twice the revisit time of the satellite. A case study is presented to demonstrate the applicability of the proposed method, namely the Palatino bridge in Rome, Italy. The satellite data are acquired by COSMO-SkyMed of the Italian Space Agency and consist of displacements of the observed structure recorded during a period spanning between 2011 and 2019.

Resilient and sustainable traffic infrastructure systems such as bridges play a crucial role in societal economic growth. During the last decades, substantial research has been undertaken for the optimal management of risks associated with extreme events, and the concept of resilience was introduced. The knowledge on the system characteristics affecting resilience is increasing and so is the capability to model and analyze systems. The first step in systems modelling and analysis is to define the system which has not been addressed methodically in the literature. In this contribution, we provide a framework for systems identification in the context of resilience informed management of historic bridges. The proposed approach rests on the indicator-based systems modelling framework of the Joint Committee on Structural Safety (JCSS). With this basis we identify ten resilience indicators which provide information concerning the resilience performances of historic bridges. Finally, we apply the suggested approach through an example.

Structural Performance Monitoring is usually carried out using indicators to assess the current (diagnosis) or future (prognosis) structural performance concerning specified limit states. The assessment requires the definition of threshold values of the indicators that correspond to the considered limit states. Traditionally, the identification of indicators of the structural condition through continuous and autonomous measurements is addressed as Structural Health Monitoring (SHM). In this paper, a critical review of the existing documents on structural monitoring standardization is carried out, and open research issues and practical hurdles related to the standardization are discussed. The review shows that most of the SHM guidelines and technical codes published in several countries worldwide before 2010 only tackle the diagnostic process. More recent documents explicitly include also the decision-making for integrity management. This evolution in the monitoring purpose reflects a change in integrity management objectives, increasingly driven by the optimization of resources allocation rather than by safety requirements. Further to this, digitalization, and the availability of large volumes of monitoring information, open research avenues related to their use as decision support tools for asset integrity management.

In this paper, the effectiveness of vibration-based tests for the detection of damages for prestressed concrete beams is investigated. Despite large research efforts, discrepant and sometimes contradicting conclusions have been drawn regarding the efficacy and reliability of vibration-based monitoring for prestressed structures. Herein, a contribution to this discussion is provided by tackling the problem from a different perspective. Specifically, the question that this paper intends to answer is: “Do vibration-based tests support decision-makers in integrity management operations for prestressed elements?” The discussion is carried out by comparing the performance of prestressed and ordinary reinforced concrete beams with similar capacities. Both analytical and numerical case studies are considered. Results show that, for prestressed beams, in contrast to reinforced concrete beams, modal parameters can provide information regarding damage only when the structure is close to its ultimate conditions. This makes this information hardly useful for integrity management purposes and the effectiveness of vibration-based tests questionable for this type of structural element.

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.

Recent developments in the field of smart sensing systems enable performing simple onboard operations which are increasingly used for the decentralization of complex procedures in the context of vibration-based structural health monitoring (SHM). Vibration data collected by multiple sensors are traditionally used to identify damage-sensitive features (DSFs) in a centralized topology. However, dealing with large infrastructures and wireless systems may be challenging due to their limited transmission range and to the energy consumption that increases with the complexity of the sensing network. Local DSFs based on data collected in the vicinity of inspection locations are the key to overcome geometric limits and easily design scalable wireless sensing systems. Furthermore, the onboard pre-processing of the raw data is necessary to reduce the transmission rate and improve the overall efficiency of the network. In this study, an effective method for real-time modal identification is used together with a local approximation of a damage feature, the interpolation error, to detect and localize damage due to a loss of stiffness. The DSF is evaluated using the responses recorded at small groups of sensors organized in a decentralized topology. This enables the onboard damage identification in real time thereby reducing computational effort and memory allocation requirements. Experimental tests conducted using real data confirm the robustness of the proposed method and the potential of its implementation onboard decentralized sensor networks.

Recent research in Indirect Structural Health Monitoring (ISHM) uses the dynamic response of instrumented vehicles to carry out “drive-by” monitoring of bridges. These vehicles are generally cars or trucks instrumented with different types of sensors. However, some urban bridges are inaccessible to regular vehicles. Also, cars and trucks have non-negligible weight and suspension systems that may affect the collected vibration data. Stiff, light, and standardized shared micromobility vehicles, such as bicycles and electric kick scooters, have never been explored for ISHM purposes. This paper proposes an innovative and automatic ISHM strategy based on the data collected by smartphones temporarily installed on shared micromobility vehicles. An identification procedure suitable for cloud computing is proposed to extract the dynamic parameters of bridges without needing any sensor deployment, becoming particularly appealing for monitoring a densely built environment at a territorial scale. The methodology is applied to a real footbridge in Bologna (Italy).

Deterioration of bridges due to ageing and higher demands, induced by increased traffic load, require the development of effective maintenance policies and intervention strategies. Such concern should be aimed at ensuring the required levels of safety, while optimally managing the limited economic resources. This approach requires a transversal advance; from the element level, through the system level, all the way to the network level. At the same time intervention prioritisation based on the importance of the system (bridge) inside the network (e.g. highway), or of the single structural element inside the bridge is dependent. The first step in bridge condition assessment is the verification of safety and reliability requirements that is carried out using the traditional prescriptive (deterministic) approach or the current performance- based (probabilistic) approach. A critical issue for efficient management of infrastructures lies in the available knowledge on condition and performance of bridge asset. This information is obtained using a collection of significant Performance Parameters at one or more of the three levels (element, system, and network). Traditional techniques for estimation of Performance Parameters rely on already established visual inspection. However, a more reliable description of the system performance is obtained through Non-Destructive Testing and Structural Health Monitoring. Condition assessment essentially pertains to the check of compliance with Performance Goals and requires the definition and computation of Performance Indicators. They are calculated directly from Performance Parameters or from physical models calibrated using the Performance Parameters collected on the structure. Paper overviews the steps to bridge condition assessment regarding safety and reliability., The Baltic Journal of Road and Bridge Engineering, 13 (4), ISSN:1822-427X

Management of aging engineering systems is a growing concern. Decisions such as service limitation or interruption might have to be taken in order to keep an appropriate level of safety following a disastrous event. Information about the infrastructure can be collected by inspections and/or by Structural Health Monitoring (SHM) devices. The Value of Information (VoI) from Bayesian decision analysis can be used to quantify the benefit of using a certain data-acquisition strategy and to select the most appropriate one. This paper takes advantage of the correlation among the state of the components of an infrastructure due, for example, to their similar design and exposure conditions. The collection of data about an appropriately selected sample of components is used to infer the state of other components. As an example, the proposed formulation is used to quantify the VoI considering a system of bridges subject to gradual degradation processes and seismic hazards.

Seismic structural health monitoring (S2HM) has advanced significantly in the last three decades. However, currently there is no consensus on the need for real-time processing of data acquired during an earthquake. Numerous applications exist whereby S2HM-equipped systems record valuable seismic response data. A delayed use of the seismic data prohibits timely discovery of hidden damages in a structure which, in turn, possibly increases its vulnerability during events to follow – with increased risk to occupants. Such risks are of particular concern when, for example, there are long-distance/long period effects e.g. for tall buildings and long-span bridges that are significantly affected by events that originate at far distances. These phenomena necessitate near real-time monitored data to make timely data-based informed decisions on the health or performance of the affected structure. The paper discusses criteria for functionality and occupiability thresholds in actual applications.

All over Europe, the management of bridge integrity is carried out primarily through inspections that allow collecting information about the condition of bridges and support decisions about...

In the last 20 years, SAR sensors installed on satellites have been increasingly used to monitor large scale phenomena such as subsidence, uplifting, or landslides. Recently several research groups started to investigate the use of remote sensing for damage detection in civil infrastructures. This technique presents in principle several advantages, not least the possibility to monitor a network of structures using the same sensor. However, its implementation for civil engineering projects is still at its infancy and a limited number of applications can be found in literature. The goal of this paper is to investigate the feasibility of using InSAR data for structural health monitoring of bridges with reference to a number of case studies. Data measured by radar satellites with different spatial and temporal resolutions and different frequency bands are processed to extract bridge displacement data and analyzed to identify possible structural damages. The SqueeSAR technique is used to extract displacement time histories from SAR images acquired by radar sensors with different spatial and temporal resolution (TerraSAR-X and RADARSAT 1–2). Displacements are then processed to identify anomalies possibly related to damage. Results show that high-resolution radar data enable the detection of very small structural displacements due to environmental changes, such as temperature variation.

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 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.

This article aims at contributing to the seismic performance assessment of a historic brick masonry building by finding a strength reduction coefficient through the use of linear and nonlin...

Decision makers face several challenges in the aftermath of a disastrous event. Emergency operations such as traffic restrictions, bridge closures and immediate repairs might have to be scheduled in order to keep an appropriate level of safety. The state of the infrastructure after the occurrence of the seismic event can be predicted based on the a priori knowledge about the system, and decisions may be taken based on this knowledge. This is generally done by minimizing the expected cost of the different plans of action, considering both direct (e.g. failure of a component) and indirect costs (e.g. costs coming from diverted traffic after a bridge closure). However, inspections of selected critical components can provide insight into the actual state of the system and consequently change the chosen plan of action for the decision makers. Different methods of inspections come at different costs, information and uncertainties. It is important to decide whether or not inspections should be done and if so select the most appropriate inspection method so that the associated costs do not overcome the benefits that would be obtained by performing it. Moreover, advanced monitoring techniques that are able to investigate the state of the system over time (such as sensor monitoring) can provide additional information about the way the system is evolving. This information can in turn be used to update the knowledge about the state of the system before the occurrence of a disastrous event, further reducing the chance of taking the wrong managing decision. Before installation, decision makers must properly evaluate the costs associated to these monitoring techniques, to decide whether the additional information overcomes their cost. In this work, we propose a general framework to evaluate the Value of Information of selected inspection procedures considering the possible information from structural health monitoring (SHM) of system. The proposed framework will be applied to a case study of a two-span reinforced concrete bridge. 1

This paper compiles and describes the national initiatives and projects on Seismic Structural Health Monitoring (S 2 HM) active in a number of European countries. Sensors networks and typical layouts, data processing techniques and policies adopted for the management of alerts are described for the different national programs. The different policies adopted for the access to data are also described. Applications to buildings, bridges or cultural heritage constructions are used to describe in detail the seismic SHM systems installed in Italy, France, Greece and Portugal.

Several methods proposed in literature for the localization of stiffness losses rely on the detection of irregularities in the deflected shape of the structure. This requires accurate description of the deflected shape achievable through a high spatial resolution of sensors, high quality or measures and accounting for the approximations introduced by signal processing. In the first part of this paper a survey of vibration-based damage localization algorithms based on the detection of (changes of) irregularities in the deflected structural shape is reported. Most of these methods rely on damage parameters defined in terms of the local variations of curvature due to the direct relationship of this parameter with the variations of stiffness. Due to some drawbacks related to the estimation of curvature from noisy recorded responses, other methods have been proposed to detect local variations of the deformed shape without directly computing the curvature. Also, many of the methods proposed in literature have been validated only on numerical models, due to the scarce availability of experimental data recorded on damaged structures. Recently data recorded on benchmark structures have become available giving the opportunity to verify the capability of these methods for damage localization in real-world conditions. In the last part of the paper, a method for damage localization based on the detection of localized changes in the structural deformed shapes, the Interpolation Method, is applied to two benchmark structures. The first is the UCLA Factor Building whose response to several non-destructive earthquakes has been recorded by a dense network of sensors. The second is the 7th storey portion of building tested to collapse, using base inputs of increasing severities, on the USDS shaking table.

Transportation infrastructures play an essential role for sustainable and resilient societal developments. In case of an infrastructure failure, such as a partial of full collapse of a bridge, the failure event may cause further cascading failures in the transportation network and lead to severe disruptions of societal functionality. The identification of optimal strategies for the management of critical infrastructure systems through inspections, monitoring, maintenance, repairs, strengthening and renewals, comprises a common but non-trivial challenge for asset owners and operators. To support assets integrity managers in this process the JCSS (2008) has issued a guideline on risk informed decision making for engineered facilities and systems with a focus on the main components of the system identification pertaining to decision analysis. With this basis, the present paper identifies and proposes a novel and generic framework for system identification in the context of resilience management of bridges with a special focus on heritage structures subject to disturbance events such as natural hazards, excessive degradation, failure and accidents and human and organizational errors. The framework addresses the decision situations before, during and after disturbance events with special emphasis directed on the system characteristics of relevance for resilience management and how information about these characteristics may be represented in terms of resilience indicators. In addition, the suggested framework directs emphasis on the role of management of information utilized in support of decision making. Transportation infrastructures play an essential role for sustainable and resilient societal developments. In case of an infrastructure failure, such as a partial of full collapse of a bridge, the failure event may cause further cascading failures in the transportation network and lead to severe disruptions of societal functionality. The identification of optimal strategies for the management of critical infrastructure systems through inspections, monitoring, maintenance, repairs, strengthening and renewals, comprises a common but non-trivial challenge for asset owners and operators. To support assets integrity managers in this process the JCSS (2008) has issued a guideline on risk informed decision making for engineered facilities and systems with a focus on the main components of the system identification pertaining to decision analysis. With this basis, the present paper identifies and proposes a novel and generic framework for system identification in the context of resilience management of bridges with a special focus on heritage structures subject to disturbance events such as natural hazards, excessive degradation, failure and accidents and human and organizational errors. The framework addresses the decision situations before, during and after disturbance events with special emphasis directed on the system characteristics of relevance for resilience management and how information about these characteristics may be represented in terms of resilience indicators. In addition, the suggested framework directs emphasis on the role of management of information utilized in support of decision making.