Resilience analysis of large scale networks using the D-spectrum method

Infrastructure systems are crucial for the development of communities because they provide essential services to the habitants. Here we focus on the transportation network, which is designed to provide a continuous service to the community. Due to its decisive role in the economy, governments and policy makers have been investing in developing strategies to increase the resilience of this kind of infrastructure against disruptive events. In the literature, several methods to evaluate networks’ reliability and resilience can be found. The applicability of these methods is limited to small networks due to the computational complexities. In this paper, the case of city-scale road transportation networks is tackled. The case study considered in this work is the transportation network of a virtual, city called ‘Ideal City’. First, the road map of the city is transformed into an undirected graph with 15012 nodes and 19614 edges. A non-random gradual removal of the edges has been applied until the network’s failure point is reached. The edge removal process is related to the failure probabilities of the edges when the network is exposed to a certain hazard. In fact, the effect of hazards on the transportation network is not direct. The hazard exposes the building structures on the road sides to a failure risk. These structures if collapsed would cause the adjacent roads to be blocked and thus lose functionality due to the debris falling from the structures. For this purpose, a building infrastructure is modeled and the relationship between the level of damage of building and the amount of debris falling on the adjacent roads is developed. A Monte Carlo approach is used to generate failure permutations of edges considering their failure probabilities. The network reliability is then calculated using the Destruction Spectrum (D-spectrum) approach. In addition, the network’s edges have been ranked from the most to the least important by applying the Birnbaum Importance Measure (BIM). Due to the large size of the network, a number of computational problems have arisen. Therefore, several coding algorithms have been developed to allow evaluating both the reliability and the BIM indexes while avoiding computational errors. The results obtained in this study are used to identify the vulnerable components of the network. The vulnerable components are the ones that should be focused on to improve the overall resilience of the infrastructure. The analysis concept adopted in this study is applicable to all network-based infrastructure systems such as water, gas, transportation, etc. Future work will be oriented towards applying the methodology to other network-based infrastructure systems

Indoor tracking using unmanned aerial vehicles

Search and rescue operations during emergencies are complex missions that put at risk the life of first responders. The main challenge is to detect the trapped and injured people inside buildings damaged by different hazards. With a tool showing on a map the number, location and health status of victims, first responders would be able to significantly reduce the evacuation time and save more lives. In this paper, an innovative real-time indoor localization system using Unmanned Aerial Vehicles (UAVs) is proposed. The system includes anchor nodes (antennas) that are mounted on three UAVs flying outside the building and can track the position of people wearing a smart bracelet (tags). The system allows measuring both the absolute and relative location between groups of nodes in 3D without relying on any fixed communication infrastructure that could fail because of the disruptive event. In addition, vital parameters such as heart rate and body temperature can be monitored for each victim and rescuer wearing the bracelet. Each UAV collects, processes, and transfers the data to a portable gateway. A software application with a graphical user interface was developed to display the real-time position of the UAVs and tags with a color-coded indication of the accuracy. Preliminary results of the on-field tests of the systems are presented and discussed

Modelling infrastructure interdependencies and cascading effects using temporal networks

Lifelines are critical infrastructure systems characterized by a high level of interdependency that can lead to cascading failures after any disaster. Many approaches can be used to analyze infrastructural interdependencies, but they are usually not able to describe the sequence of events during emergencies. Therefore, interdependencies need to be modeled also taking into account the time effects. The methodology proposed in this paper is based on a modified version of the Input-output Inoperability Model and returns the probabilities of failure for each node of the system. Lifelines are modeled using graph theory, while perturbations, representing a natural or man-made disaster, are applied to the elements of the network following predetermined rules. The cascading effects among interdependent networks have been simulated using a spatial multilayer approach, while the use of an adjacency tensor allows to consider the temporal dimension and its effects. The method has been tested on a case study based on the 2011 Fukushima Dai-ichi nuclear disaster. Different configurations of the system have been analyzed and their probability of occurrence evaluated. Two models of the nuclear power plant have been developed to evaluate how different spatial scales and levels of detail affect the results

Resilience and safety of civil engineering systems and communities: A bibliometric analysis for mapping the state-of-the-art

The interest in the concept of resilience has been growing consistently over the past few years to study the functionality and behavior of systems against natural and man-made hazards. Yet a comprehensive, updated review of methods and frameworks to assess and improve the resilience and safety of civil engineering systems and communities is lacking. In this paper, a bibliometric and visualization method is implemented to explore the status of resilience research in civil engineering applications by analyzing journal papers published from 1996 to 2020. The concept of resilience and safety is investigated through eight subject categories identified by the authors in the literature: recovery time strategies and downtime, critical infrastructures, probabilistic approaches, fuzzy logic approaches, structural health monitoring, health care facilities, emergency management and decision-making, community and urban resilience. Results show that resilience research has increased rapidly since its introduction, most notably in the past seven years. The analysis identifies two main research approaches: frameworks and conceptual models, and case study based. The latter is the most adopted methodology by the analyzed works. In terms of geographical distribution, most of them have been carried out in the USA, the United Kingdom, China, and Italy. The authors' keywords analysis reveals that recovery strategies, critical infrastructures, vulnerability, and community resilience and safety have attracted prominent attention in the past decade. Finally, we conclude that further multidisciplinary research is needed to model multi-hazard scenarios and cascading effects, to collect data, and to define new performance metrics

A refined output-only modal identification technique for structural health monitoring of civil infrastructures

The increasing installation of structural health monitoring systems has raised the need for efficient and rapid data interpretation algorithms. Operational modal analysis is currently one of the most used techniques for extracting modal properties, and some attempts have been made to automate this procedure. However, automated techniques often require manual calibration of hyperparameters and show inconsistencies across different case studies. This paper proposes a refined version of the automated frequency domain decomposition (AFDD) using the modal assurance criterion (MAC) to obtain natural frequencies and mode shapes. Sensitivity analyses were conducted on the ambient vibration response of the Yonghe cable-stayed bridge in China, accounting for influential factors including noise levels, acceleration record length, sensor layouts. A novel approach is then introduced to interpret the results of the sensitivity analyses. The approach consists in plotting the result of each analysis in a stabilization diagram and then using a Gaussian mixture model that clusters the poles into core and outliers. This allows to identify regions where the MAC thresholds are optimal. By comparing the results of all the sensitivity analyses it was possible to define a single optimal MAC threshold, avoiding the need for fixing a value based on the user’s experience. Three substantially different case studies were analyzed to extensively test the methodology: the Yonghe cable-stayed bridge, the PolyU footbridge in Hong Kong, and Moletta Tower in the Circus Maximus archeological site in Italy. The analysis compared the proposed AFDD algorithm to the traditional frequency domain decomposition and covariance-driven stochastic subspace identification. Specifically, the efficiency in identifying close frequencies, weakly excited modes, spurious peaks, and complex modes was evaluated for each method, which highlighted the robustness of the proposed optimized AFDD. The analysis showcases peculiar characteristics and drawbacks of each method when trying to identify complex vibrational modes of the specific case studies. It was found that the proposed AFDD procedure performs better than traditional methods despite it may misidentify complex modes due to the constraints of a narrower modal domain and similar geometries

Generating ground motions using the Fourier amplitude spectrum

In this paper, a simplified method aimed at generating ground motions records using a Fourier amplitude spectrum model obtained by a response spectrum is presented. The use of white noise with specific conditions on the variance and inter-frequency correlation allows to get a realistic variability of the Fourier amplitude spectrum. Moreover, a two-corner frequency model is defined from empirical ground-motion data and a filter is applied to capture the attenuation at high frequencies. The generated series of stochastic ground motions accurately match the mean value of the target response spectrum. The procedure was tested on an Italian site and results showed excellent matching in terms of mean and dispersion values with either the median obtained from ground motion prediction equations (GMPE) and conditional mean spectra (CMS). The advantage of the proposed methodology is that time-histories can be generated with low computational effort, they do not need scaling or frequency content adjustments and are spectrum compatible with a given target spectrum

RELIABILITY AND COMPONENT VULNERABILITY ANALYSIS OF CITY-SCALE NETWORKS: APPLICATION TO THE TRANSPORTATION SYSTEM OF A VIRTUAL CITY

Infrastructure systems are crucial for the development of communities as they provide essential services to the habitants. To improve the resilience of such systems, their intrinsic properties need to be understood and their resilience state needs be identified. In the literature, several methods to evaluate networks’ reliability and resilience can be found. However, the applicability of these methods is restricted to small-size networks due to several computational limitations. In this paper, the case of large scale networks is tackled. The transportation network of a virtual city is considered as a case study. First, the road map of the city is transformed into an undirected graph. A random removal of the roads is applied until the network’s failure point is reached. The network reliability is then calculated using the Destruction Spectrum (D-spectrum) approach. A Monte Carlo approach has been developed to generate failure permutations, which are necessary for the evaluation of the D-spectrum set. In addition, the Birnbaum Importance Measure (BIM) has been adopted in this study to determine the importance of the network’s components. Due to the large size of the network, several computational problems have been faced. To solve the problems, two coding algorithms have been introduced in the paper to evaluate both the reliability and the BIM indexes for large scale networks. The analysis concept adopted in this study is applicable to all network-based systems such as water, gas, transportation, etc

The Digital Living Archive and the construction of a participatory cultural memory in the DARE-UIA project (Digital Environment for collaborative Alliances to Regenerate urban Ecosystems in middle-sized cities)

Living Archives perform a function of social memory sharing, which contributes to building social bonds, communities, and identities. This potential lays in the ability of Living Archives to put together an archival function, which allows with the conservation and transmission of memory, with an artistic, performative and creative function linked to the present. As part of the DARE-UIA (Digital environment for colaborative alliances to regenerate urban ecosystem in middle-sized cities) project, the creation of a living digital archive made possible to create a narrative that would consolidate the cultural memory of the Darsena district of the city of Ravenna. The aim of the project is to stimulate the urban regeneration of a suburban area of a city, enhancing its cultural memory and identity heritage, through digital heritage tools. The methodology used involves various digital storytelling actions necessary for the overall narrative using georeferencing systems (GIS), storymaps and 3D reconstructions for a transversal narration of historical content such as personal and institutional historical photos and to enhance the industrial archeology heritage of the neighborhood. The aim is the creation of an interactive and replicable narrative in similar contexts to the Darsena district in Ravenna. The Living Archive, in which all the digital contents are inserted, finds its manifestation towards the outside with the form of a museum spread throughout the neighborhood, making the contents usable on smartphones via QR codes and totems inserted on-site, creating thematic itineraries spread around the neighborhood. The construction of an interactive and engaging digital narrative has made possible to enhance the material and immaterial heritage of the neighborhood by recreating the community that has historically always distinguished it

Resilience assessment of large scale water distribution networks: a simulation approach

The capacity of a community to react and resist to an emergency situation is strictly related to the proper functioning of its own infrastructure systems. This paper proposes a simulation oriented approach to evaluate the resilience of large scale water distribution networks. The case study used in this research is the water network of a large scale virtual city. The water network is modeled using the software EPANET 2.0 with the help of an integrated Matlab toolbox. The network consists of 16000 junctions and 19000 water pipes buried under the road network of the city. A series of earthquake scenarios is applied to the water network and the damage induced by the earthquakes has been determined using fragility function. The failure of the system occurs when the water flow and the water pressure go below a certain threshold. The resilience of the network is then evaluated using two indices: (1) the number of users without water, (2) the drop in the total water supply

Experimental Investigation of the Static and Dynamic behaviors of 3D-Printed Shell Structures

Over the last years, several optimization strategies were conducted to find the optimal shape minimazing internal stress or total weight (volume) of shell structures. In recent times, this structure typology gained a great importance among researchers and the scientific community for the renowed interest in the form-findind optimization of column-free space solution for large span roofing constructions. In the present paper, a form-finding of a shallow grid shells was introduced basing on the multy-body rope approach (MRA) for the definitions of vault shapes and different hole percentage. In order to obtain an experimental validation, a physical model was reproduced at the laboratory scale performing ad hoc measurements to compare the observed respect to the simulated behaviour. A 3D printing procedure based on the Fuse Deposition Modeling (FDM) technique in polylactide (PLA) material was used to realise form-works of the cement based blocks of the scaled prototype. Several static and dynamic load configurations are investigated, collecting into a sensitivity analysis the parameters which mainly affect the structural behaviour. To simulate earthquake ground motion an assigned frequency range as dynamic input to the structure was provided by a shaking table. Finally, some preliminary considerations of the dynamic response of the model were provided testing the robustness of the form-finding approach when horizontal load are taken into account