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.@en

The multiple uncertainties of both natural and human-caused disasters have attracted increased attention to the topic of resilience engineering. In this paper, an indicator-based method for measuring urban community resilience is proposed. The method is based on the PEOPLES framework, which is a hierarchical framework for defining the disaster resilience of communities at various scales. It consists of seven dimensions, summarized by the acronym PEOPLES, which stands for population, environmental and ecosystem, organized governmental services, physical infrastructures, lifestyle, economic development, and social capital. Each of the dimensions is split into several components and indicators, which were derived by the authors or collected from a wide range of literature. Each indicator is represented using a performance function, which portrays the functionality of the indicator in time. A higher functionality of the indicator denotes a higher resilience of the community. These functions can be constructed in a systematic manner using damage and restoration parameters. The aggregation of the performance functions passing through the different hierarchical levels of PEOPLES framework leads to one function that represents the dynamic performance of the analyzed community. This paper also introduces a matrix-based interdependency technique that serves as a weighting scheme for the different indicators. As a case study, the proposed methodology is applied to the city of San Francisco for which a resilience curve and resilience metric have been computed.@en

Community resilience is becoming a growing concern for authorities and decision makers. This paper introduces two indicator-based methods to evaluate the resilience of communities based on the PEOPLES framework. PEOPLES is a multi-layered framework that defines community resilience using seven dimensions. Each of the dimensions is described through a set of resilience indicators collected from literature and they are linked to a measure allowing the analytical computation of the indicator’s performance. The first method proposed in this paper requires data on previous disasters as an input and returns as output a performance function for each indicator and a performance function for the whole community. The second method exploits a knowledge-based fuzzy modeling for its implementation. This method allows a quantitative evaluation of the PEOPLES indicators using descriptive knowledge rather than deterministic data including the uncertainty involved in the analysis. The output of the fuzzy-based method is a resilience index for each indicator as well as a resilience index for the community. The paper also introduces an open source online tool in which the first method is implemented. A case study illustrating the application of the first method and the usage of the tool is also provided in the paper.@en

Community resilience is becoming a growing concern for authorities and decision makers. This paper introduces two indicator-based methods to evaluate the resilience of communities based on the PEOPLES framework. PEOPLES is a multi-layered framework that defines community resilience using seven dimensions. Each of the dimensions is described through a set of resilience indicators collected from literature and they are linked to a measure allowing the analytical computation of the indicator’s performance. The first method proposed in this paper requires data on previous disasters as an input and returns as output a performance function for each indicator and a performance function for the whole community. The second method exploits a knowledge-based fuzzy modeling for its implementation. This method allows a quantitative evaluation of the PEOPLES indicators using descriptive knowledge rather than deterministic data including the uncertainty involved in the analysis. The output of the fuzzy-based method is a resilience index for each indicator as well as a resilience index for the community. The paper also introduces an open source online tool in which the first method is implemented. A case study illustrating the application of the first method and the usage of the tool is also provided in the paper.@en

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.@en

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.@en

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.@en

In recent years, the concept of resilience has been introduced to the field of engineering as it relates to disaster mitigation and management. However, the built environment is only one element that supports community functionality. Maintaining community functionality during and after a disaster, defined as resilience, is influenced by multiple components. This report summarizes the research activities of the first two years of an ongoing collaboration between the Politecnico di Torino and the University of California, Berkeley, in the field of disaster resilience. Chapter 1 focuses on the economic dimension of disaster resilience with an application to the San Francisco Bay Area; Chapter 2 analyzes the option of using base-isolation systems to improve the resilience of hospitals and school buildings; Chapter 3 investigates the possibility to adopt discrete event simulation models and a meta-model to measure the resilience of the emergency department of a hospital; Chapter 4 applies the meta-model developed in Chapter 3 to the hospital network in the San Francisco Bay Area, showing the potential of the model for design purposes Chapter 5 uses a questionnaire combined with factorial analysis to evaluate the resilience of a hospital; Chapter 6 applies the concept of agent-based models to analyze the performance of socio-technical networks during an emergency. Two applications are shown: a museum and a train station; Chapter 7 defines restoration fragility functions as tools to measure uncertainties in the restoration process; and Chapter 8 focuses on modeling infrastructure interdependencies using temporal networks at different spatial scales. @en

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

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

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

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

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

Last decades have been characterized by an increasing number of disasters all over the world. Therefore, the concept of community resilience has attracted the attention of the scientists who started to explore and assess the ability of communities to recover after undesirable events. In this work, a method for assessing the earthquake community resilience based on the PEOPLES framework is presented. PEOPLES is a framework that defines community resilience using seven dimensions. Each of the dimensions is defined through a set of indicators to describe the different aspects of resilience. The exact evaluation of the indicators is usually not possible due to the lack of deterministic data related to the damaged system after the disaster. The proposed method exploits a knowledge-based fuzzy modelling to allow the quantitative evaluation of the PEOPLES indicators taking into account uncertainties. The output of the implemented fuzzy method is a resilience index.@en

Last decades have been characterized by an increasing number of disasters all over the world. Therefore, the concept of community resilience has attracted the attention of the scientists who started to explore and assess the ability of communities to recover after undesirable events. In this work, a method for assessing the earthquake community resilience based on the PEOPLES framework is presented. PEOPLES is a framework that defines community resilience using seven dimensions. Each of the dimensions is defined through a set of indicators to describe the different aspects of resilience. The exact evaluation of the indicators is usually not possible due to the lack of deterministic data related to the damaged system after the disaster. The proposed method exploits a knowledge-based fuzzy modelling to allow the quantitative evaluation of the PEOPLES indicators taking into account uncertainties. The output of the implemented fuzzy method is a resilience index.@en