Community and infrastructure resilience against natural and man-made hazards is paramount for the well-being of modern societies. To adapt to the fast-changing world, having communities that can effectively respond to the continuously changing (physical and social) environment is essential. Despite the existing literature on resilience definition and estimation, few frameworks and associated tools can effectively help decision-making. In addition, these tools are usually not well integrated into the community and infrastructure management processes so that decision-makers and authorities can effectively use them. This paper aims at developing a resilience-based risk assessment approach at the community level. It combines the risk analysis parameters with the intrinsic resilience of the community. The proposed approach offers essential insights into the quantitative resilience analysis of communities at different scales and for different natural hazards. It enables the combination of the risk parameters (hazard, exposure, and vulnerability) with the inherent resilience of all the systems that constitute a community. This paper also presents an easy-to-interpret tool for visualizing the resilience results obtained from the introduced approach. It translates the paper's scientific contribution into an interactive and visualization instrument that can ultimately support policymaking to ensure their communities' short and long-term resilience under known and unknown hazardous events.@en

Due to the increasing frequency of disastrous events, the challenge of creating large-scale simulation models has become of major significance. Indeed, several simulation strategies and methodologies have been recently developed to explore the response of communities to natural disasters. Such models can support decision-makers during emergency operations allowing to create a global view of the emergency identifying consequences. An integrated platform that implements a community hybrid model with real-time simulation capabilities is presented in this paper. The platform's goal is to assess seismic resilience and vulnerability of critical infrastructures (e.g., built environment, power grid, socio-technical network) at the urban level, taking into account their interdependencies. Finally, different seismic scenarios have been applied to a large-scale virtual city model. The platform proved to be effective to analyze the emergency and could be used to implement countermeasures that improve community response and overall resilience.

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This paper introduces a new methodology to evaluate the resilience of communities. The methodology is based on the PEOPLES framework and it makes use of resilience indicators to evaluate community resilience. The methodology requires data for the indicators as input and returns a resilience function as an output. The resilience function shows the serviceability of the community for a given period of time following the disaster. This methodology has been implemented in the form of two software tools. The first one is a web app that is accessible at http://www.resiltronics.org/PEOPLES/login.php or http://borispio.ddns.net/PEOPLES/login.php while the other is a desktop software. The output quality provided by the tools is not compromised with their usage simplicity. Both softwares are meant to assist the user to use the introduced resilience framework by offering a user-friendly interface. As a case study, the resilience of the city of San Francisco city has been evaluated using both tools.

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Recent social developments and economic transformation have changed the engineering design approach from building design level towards community design level (city, region, country). The latter approach involves modeling of interconnections between different systems (buildings, transportation, water network, etc.) rather than designing the buildings individually. Thus, new analysis tools are expected to be developed to simulate the complex response of a community subsequently to disasters. The need of such rational tools is the object of this research work. Two different numerical approaches to simulate the response of a largescale built environment after a seismic scenario are explored by developing multipurpose numerical codes. A district of a virtual city is considered as a case study and the level of damage for built environment is estimated. This work could be the first step for further urban loss analysis, e.g. through agent-based models that could be updated online with the proposed simulation.@en

This paper presents a new methodology to predict the potential damage and physical impacts of an earthquake on the built environment. A new methodology to the urbanized systems and large-scale simulations within a seismic scenario are explored, by evaluating multipurpose codes for numerical simulation. A 3-D building shape of a standard virtual city is developed for evaluating the seismic effects at increasing intensities. Once the buildings are integrated into the city, parallel simulations are applied to compute the global behavior of buildings after a disruptive scenario. Monte Carlo Simulations (MCS) are applied to take into account the epistemic uncertainties associated with geometry and mechanical properties within the range of observations. For each set of buildings' data, the nonlinear dynamic analysis is performed through SAP2000 Application Programming Interface (API) in order to assess the dynamic response of the buildings in an organized and automatic fashion. Accordingly, the city is mapped into different zones representative to the possibility of having different levels of damage (complete, extensive, moderate, and slight). This tool supports decision-makers to explore how their community will respond to a disruptive event, to develop different strategies for monitoring and control the emergency in urbanized areas.@en

Modeling the performance of critical infrastructures and their interdependencies is an important task in the resilience assessment. In this paper, restoration curves for four critical lifelines (power, water, gas, telecommunication, and transportation) have been developed using a probabilistic approach. To do that, a large database on infrastructure downtime has been collected for most of the earthquakes that occurred in the past century. The restoration curves have been grouped based on the earthquake magnitude and the level of development of the country in which the earthquake occurred. The curves are presented in terms of probability of recovery and time; the longer is the time after the disaster, the higher is the probability of the infrastructure to recover its functions.@en

To improve the resilience of critical infrastructure systems, their intrinsic properties need to be understood and their resilience state needs to be identified. In the literature, several methods to evaluate networks’ reliability and resilience can be found. However, the applicability of these methods is usually restricted to small-size networks. In this paper, the transportation network of a large-scale virtual city is considered as a case study. A random removal strategy of the links (roads) is applied to simulate the network’s failure. The network reliability is then calculated using the Destruction Spectrum (D-spectrum) method and a Monte Carlo approach has been developed to generate failure permutations that are necessary for the evaluation of the D-spectrum. In addition, the Birnbaum Importance Measure (BIM) has been adopted in this study to determine the importance of the network’s components. The methodology adopted in this study can be also extended to all network-based systems. The paper also introduces resilience indicators as a soft tool to predict the performance and the serviceability of the transportation networks.

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This paper presents a new approach to predict the potential damage and physical impacts of an earthquake on the built environment. A new methodology for large-scale simulations within a seismic scenario are explored by evaluating multipurpose codes. In particular, a 3-D model of a virtual city is developed for evaluating the seismic effects at increasing intensities. Four different building sectors that provide essential functions to a community, including housing, education, business, and public services are considered. Once the buildings are integrated into the city, parallel simulations are applied to compute the system functionality following a disruptive scenario. Trilinear elastoplastic backbone curve representative of the global shear behavior of each building is estimated considering the dominant modal shapes and building irregularities. Monte Carlo Simulations (MCS) are applied to take into account the epistemic uncertainties associated with geometry and mechanical properties within the range of observations. The nonlinear dynamic analyses are performed through SAP2000 Application Programming Interface (API) in order to assess the dynamic response of the buildings in an organized and automatic fashion. Accordingly, the city is mapped into different zones representative to the possibility of having different levels of damage (complete, extensive, moderate, and slight). This methodology supports decision-makers to explore the community response to a disruptive events, to develop monitoring and control strategies in urbanized areas, to plan better resilience-building and evacuation strategies.

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