6,142 research outputs found

    Critical Infrastructures: Enhancing Preparedness & Resilience for the Security of Citizens and Services Supply Continuity: Proceedings of the 52nd ESReDA Seminar Hosted by the Lithuanian Energy Institute & Vytautas Magnus University

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    Critical Infrastructures Preparedness and Resilience is a major societal security issue in modern society. Critical Infrastructures (CIs) provide vital services to modern societies. Some CIs’ disruptions may endanger the security of the citizen, the safety of the strategic assets and even the governance continuity. The European Safety, Reliability and Data Association (ESReDA) as one of the most active EU networks in the field has initiated a project group on the “Critical Infrastructure/Modelling, Simulation and Analysis – Data”. The main focus of the project group is to report on the state of progress in MS&A of the CIs preparedness & resilience with a specific focus on the corresponding data availability and relevance. In order to report on the most recent developments in the field of the CIs preparedness & resilience MS&A and the availability of the relevant data, ESReDA held its 52nd Seminar on the following thematic: “Critical Infrastructures: Enhancing Preparedness & Resilience for the security of citizens and services supply continuity”. The 52nd ESReDA Seminar was a very successful event, which attracted about 50 participants from industry, authorities, operators, research centres, academia and consultancy companies.JRC.G.10-Knowledge for Nuclear Security and Safet

    LIFECYCLE MANAGEMENT, MONITORING AND ASSESSMENT FOR SAFE LARGE-SCALE INFRASTRUCTURES: CHALLENGES AND NEEDS

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    Many European infrastructures dating back to ’50 and ’60 of the last century like bridges and viaducts are approaching the end of their design lifetime. In most European countries costs related to maintenance of infrastructures reach a quite high percentage of the construction budget and additional costs in terms of traffic delay are due to downtime related to the inspection and maintenance interventions. In the last 30 years, the rate of deterioration of these infrastructures has increased due to increased traffic loads, climate change related events and man-made hazards. A sustainable approach to infrastructures management over their lifecycle plays a key role in reducing the impact of mobility on safety (over 50 000 fatalities in EU per year) and the impact of greenhouse gases emission related to fossil fuels. The events related to the recent collapse of the Morandi bridge in Italy tragically highlighted the sheer need to improve resilience of aging transport infrastructures, in order to increase the safety for people and goods and to reduce losses of functionality and the related consequences. In this focus Structural Health Monitoring (SHM) is one of the key strategies with a great potential to provide a new approach to performance assessment and maintenance over the life cycle for an efficient, safe, resilient and sustainable management of the infrastructures. In this paper research efforts, needs and challenges in terms of performance monitoring, assessment and standardization are described and discussed.The networking support of COST Action TU1402 on ‘Quantifying the Value of Structural Health Monitoring’ and of COST Action TU1406 on ‘Quality specifications for roadway bridges, standardization at a European level (BridgeSpec)

    Bridges Structural Health Monitoring and Deterioration Detection Synthesis of Knowledge and Technology

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    INE/AUTC 10.0

    Compressive and Coded Change Detection: Theory and Application to Structural Health Monitoring

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    In traditional sparse recovery problems, the goal is to identify the support of compressible signals using a small number of measurements. In contrast, in this thesis the problem of identification of a sparse number of statistical changes in stochastic phenomena is considered when decision makers only have access to compressed measurements, i.e., each measurement is derived by a subset of features. Herein, we propose a new framework that is termed Compressed Change Detection. The main approach relies on integrating ideas from the theory of identifying codes with change point detection in sequential analysis. If the stochastic properties of certain features change, then the changes can be detected by examining the covering set of an identifying code of measurements. In particular, given a large number N of features, the goal is to detect a small set of features that undergoes a statistical change using a small number of measurements. Sufficient conditions are derived for the probability of false alarm and isolation to approach zero in the asymptotic regime where N is large. As an application of compressed change detection, the problem of detection of a sparse number of damages in a structure for Structural Health Monitoring (SHM) is considered. Since only a small number of damage scenarios can occur simultaneously, change detection is applied to responses of pairs of sensors that form an identifying code over a learned damage-sensing graph. Generalizations of the proposed framework with multiple concurrent changes and for arbitrary graph topologies are presented

    Structural health monitoring of in-service tunnels

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    This work presents an overview of some of the most promising technologies for the structural health monitoring (SHM) of in-service tunnels. The common goal of damage or unusual behaviour detection is best pursued by an integrated approach based on the concurrent deployment of multiple technologies. Typically, traditional SHM systems are installed in problematic or special areas of the tunnels, giving information on conditions and helping manage maintenance. However, these methodologies often have the drawbacks of forcing the interruption of traffic for SHM system installation and monitoring only selected portions. Alternative solutions that would make it possible to keep the tunnel in normal operation and/or to analyse the entire infrastructure development through successive and continuous scanning stages, would be beneficial. In this paper, the authors will briefly review some traditional monitoring technologies for tunnels. Furthermore, the work is aimed at identifying alternative solutions, limiting or avoiding traffic interruptions

    Present and future resilience research driven by science and technology

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    Community resilience against major disasters is a multidisciplinary research field that garners an ever-increasing interest worldwide. This paper provides summaries of the discussions held on the subject matter and the research outcomes presented during the Second Resilience Workshop in Nanjing and Shanghai. It, thus, offers a community view of present work and future research directions identified by the workshop participants who hail from Asia – including China, Japan and Korea; Europe and the Americas

    Self-sensing and Self-healing ‘Smart’ Cement-based Materials – A Review of the State of the Art

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    The paper reviews recent research on self-sensing and self-healing cement-based materials as part of Smart Civil Engineering Infrastructures. Incorporated in Structural Health Monitoring systems, these materials are likely to play an important role in making future infrastructure robust, resilient and sustainable. Smart or intelligent cement-based materials have attracted extensive attention in the last decade or so with strong implications for improving structural durability and service life. Additions of carbon fibres, carbon nano-tubes and various nano-powders giving cement-based matrix electrical properties used for self-sensing have been known for over a decade and a half. In addition, the strong capacity of Strain-Hardening Cement-based Composites (SHCC) for autogenous healing is aided by tight crack-width control, and the application of different mineral and bio-additive based materials to accelerate autonomic self-healing of cracks have been noted with great interest. Monitoring of the durability of concrete structures is often neglected in favour of the structural safety against catastrophic failure. The present review summarizes the latest literature with a focus on identifying and documenting key innovations and field applications, and the performance based design approach to tailoring material solutions for long service life, sustainability and resiliency. Smart infrastructures including Smart Buildings and Smart Cities are being constructed at an increasing pace around the world. One of the major driving force is the explosion of low-cost Internet-enabled sensors as part of the new wave of ‘Internet of Things (IoT)’. At a fraction of the cost that is being invested into the latest IoT products for incrementally more comfortable living space, a much more resilient and sustainable infrastructure can be ensured by investing in commercialization of self-sensing and self-healing materials. For this to happen the research community need to identify the gaps between the ‘Industry Pull’ and ‘Technology Push’ first instead of inventing solutions waiting for a problem

    A Systematic Literature Survey of Unmanned Aerial Vehicle Based Structural Health Monitoring

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    Unmanned Aerial Vehicles (UAVs) are being employed in a multitude of civil applications owing to their ease of use, low maintenance, affordability, high-mobility, and ability to hover. UAVs are being utilized for real-time monitoring of road traffic, providing wireless coverage, remote sensing, search and rescue operations, delivery of goods, security and surveillance, precision agriculture, and civil infrastructure inspection. They are the next big revolution in technology and civil infrastructure, and it is expected to dominate more than $45 billion market value. The thesis surveys the UAV assisted Structural Health Monitoring or SHM literature over the last decade and categorize UAVs based on their aerodynamics, payload, design of build, and its applications. Further, the thesis presents the payload product line to facilitate the SHM tasks, details the different applications of UAVs exploited in the last decade to support civil structures, and discusses the critical challenges faced in UASHM applications across various domains. Finally, the thesis presents two artificial neural network-based structural damage detection models and conducts a detailed performance evaluation on multiple platforms like edge computing and cloud computing

    Seismic Evaluation of a Large Network of Bridges by Simplified Automated Procedures and Consequent System Identifications by Dynamic Tests

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    This work presents the seismic evaluation of a large network of infrastructures located in the Veneto Region in the North-East of Italy. A large bridge database was subject to investigation, and simplified automated seismic valuation methods were developed in order to estimate the behavior of different types of structures located in seismic zones. In particular, analyses of infrastructures insistent in seismic zones, including surveys, investigations, seismic evaluation and seismic hazard assessment of the infrastructure in reference to parametric study of the structural vulnerability have been carried out. After estimating the safety factor of each structure based on the most vulnerable structural element, the key infrastructures on which execute system identification and simulate the response through numerical models were distinguished. In fact, the second step of this study is the structural identification of highly damaged bridges where a straightforward procedure has been applied. Static and modal parameters have been estimated for masonry arch bridges, concrete arch and continuous bridges, reticular and box girder steel bridges. The structural identification was used not only for calibration purposes but also for short and long term structural health monitoring (SHM) and damage detection. The SHM systems revealed good efficiency by maintaining the analyzed bridges open to traffic and constantly controlled
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