Reclassifying historical disasters: From single to multi-hazards

Multi-hazard events, characterized by the simultaneous, cascading, or cumulative occurrence of multiple natural hazards, pose a significant threat to human lives and assets. This is primarily due to the cumulative and cascading effects arising from the interplay of various natural hazards across space and time. However, their identification is challenging, which is attributable to the complex nature of natural hazard interactions and the limited availability of multi-hazard observations. This study presents an approach for identifying multi-hazard events during the past 123 years (1900-2023) using the EM-DAT global disaster database. Leveraging the 'associated hazard' information in EM-DAT, multi-hazard events are detected and assessed in relation to their frequency, impact on human lives and assets, and reporting trends. The interactions between various combinations of natural hazard pairs are explored, reclassifying them into four categories: preconditioned/triggering, multivariate, temporally compounding, and spatially compounding multi-hazard events. The results show, globally, approximately 19 % of the 16,535 disasters recorded in EM-DAT can be classified as multi-hazard events. However, the multi-hazard events recorded in EM-DAT are disproportionately responsible for nearly 59 % of the estimated global economic losses. Conversely, single hazard events resulted in higher fatalities compared to multi-hazard events. The largest proportion of multi-hazard events are associated with floods, storms, and earthquakes. Landslides emerge as the predominant secondary hazards within multi-hazard pairs, primarily triggered by floods, storms, and earthquakes, with the majority of multi-hazard events exhibiting preconditioned/triggering and multivariate characteristics. There is a higher prevalence of multi-hazard events in Asia and North America, whilst temporal overlaps of multiple hazards predominate in Europe. These results can be used to increase the integration of multi-hazard thinking in risk assessments, emergency management response plans and mitigation policies at both national and international levels.

Self-Sensing Rubber for Bridge Bearing Monitoring

Elastomeric bearings are widely used in bridges to support the superstructure, to transfer loads to substructures, and to accommodate movements induced by, for example, temperature changes. Bearing mechanical properties affect the bridge's performance and its response to permanent and variable loadings (e.g., traffic). This paper describes the research carried out at Strathclyde towards the development of smart elastomeric bearings that can be used as a low-cost sensing technology for bridge and/or weigh-in-motion monitoring. An experimental campaign was performed, under laboratory conditions, on various natural rubber (NR) specimens enhanced with different conductive fillers. Each specimen was characterized under loading conditions that replicated in-situ bearings to determine their mechanical and piezoresistive properties. Relatively simple models can be used to describe the relationship between rubber bearing resistivity and deformation changes. Gauge factors (GFs) in the range between 2 and 11 are obtained, depending on the compound and the applied loading. Experiments were also carried out to show that the developed model can be used to predict the state of deformation of the bearings under random loadings of different amplitudes that are characteristic of the passage of traffic over a bridge.

Raspberry Shake-Based Rapid Structural Identification of Existing Buildings Subject to Earthquake Ground Motion: The Case Study of Bucharest

The Internet of things concept empowered by low-cost sensor technologies and headless computers has upscaled the applicability of vibration monitoring systems in recent years. Raspberry Shake devices are among those systems, constituting a crowdsourcing framework and forming a worldwide seismic network of over a thousand nodes. While Raspberry Shake devices have been proven to densify seismograph arrays efficiently, their potential for structural health monitoring (SHM) is still unknown and is open to discovery. This paper presents recent findings from existing buildings located in Bucharest (Romania) equipped with Raspberry Shake 4D (RS4D) devices, whose signal recorded under multiple seismic events has been analyzed using different modal identification algorithms. The obtained results show that RS4D modules can capture the building vibration behavior despite the short-duration and low-amplitude excitation sources. Based on 15 RS4D device readings from five different multistorey buildings, the results do not indicate damage in terms of modal frequency decay. The findings of this research propose a baseline for future seismic events that can track the changes in vibration characteristics as a consequence of future strong earthquakes. In summary, this research presents multi-device, multi-testbed, and multi-algorithm evidence on the feasibility of RS4D modules as SHM instruments, which are yet to be explored in earthquake engineering.

Electromagnetic Sensors for Underwater Scour Monitoring

Scour jeopardises the safety of many civil engineering structures with foundations in riverbeds and it is the leading cause for the collapse of bridges worldwide. Current approaches for bridge scour risk management rely mainly on visual inspections, which provide unreliable estimates of scour and of its effects, also considering the difficulties in visually monitoring the riverbed erosion around submerged foundations. Thus, there is a need to introduce systems capable of continuously monitoring the evolution of scour at bridge foundations, even during extreme flood events. This paper illustrates the development and deployment of a scour monitoring system consisting of smart probes equipped with electromagnetic sensors. This is the first application of this type of sensing probes to a real case-study for continuous scour monitoring. Designed to observe changes in the permittivity of the medium around bridge foundations, the sensors allow for detection of scour depths and the assessment of whether the scour hole has been refilled. The monitoring system was installed on the A76 200 Bridge in New Cumnock (S-W Scotland) and has provided a continuous recording of the scour for nearly two years. The scour data registered after a peak flood event (validated against actual measurements of scour during a bridge inspection) show the potential of the technology in providing continuous scour measures, even during extreme flood events, thus avoiding the deployment of divers for underwater examination.

Resilience assessment framework for critical infrastructure in a multi-hazard environment: Case study on transport assets

The exposure of critical infrastructure to natural and human-induced hazards has severe consequences on world economies and societies. Therefore, resilience assessment of infrastructure assets to extreme events and sequences of diverse hazards is of paramount importance for maintaining their functionality. Yet, the resilience assessment commonly assumes single hazards and ignores alternative approaches and decisions in the restoration strategy. It has now been established that infrastructure owners and operators consider different factors in their restoration strategies depending on the available resources and their priorities, the importance of the asset and the level of damage. Currently, no integrated framework that accounts for the nature and sequence of multiple hazards and their impacts, the different strategies of restoration, and hence the quantification of resilience in that respect exists and this is an acknowledged gap that needs urgently filling. This paper provides, for the first time in the literature, a classification of multiple hazard sequences considering their nature and impacts. Subsequently, a novel framework for the quantitative resilience assessment of critical infrastructure, subjected to multiple hazards is proposed, considering the vulnerability of the assets to hazard actions, and the rapidity of the damage recovery, including the temporal variability of the hazards. The study puts forward a well-informed asset resilience index, which accounts for the full, partial or no restoration of asset damage between the subsequent hazard occurrences. The proposed framework is then applied on a typical highway bridge, which is exposed to realistic multiple hazard scenarios, considering pragmatic restoration strategies. The case study concludes that there is a significant effect of the occurrence time of the second hazard on the resilience index and a considerable error when using simple superimposition of resilience indices from different hazards, even when they are independent in terms of occurrence. This potentially concerns all critical infrastructure assets and, hence, this paper provides useful insights for the resilience-based design and management of infrastructure throughout their lifetime, leading to cost savings and improved services. The paper concludes with a demonstration of the importance of the framework and how this can be utilised to estimate the resilience of networks to provide a quantification of the resilience at a regional and country scale.