Resilience Assessment of the Built Environment of a Virtual City

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Cascading Hazard Analysis of a Hospital Building

Recently multiple-hazards engineering has received more attention when evaluating the capacity and analyzing the behavior of a system that is exposed to more than one type of hazard. In this paper, the principle of multiple-hazards is investigated and a new methodology has been developed to assess cumulative damage of structural elements. The proposed approach is able to combine structural damage caused by sequential hazards through their conditional probability of occurrence. The damage related to each hazard has been evaluated independently. The corresponding physical models associated to each hazard have been used to assess the conditional probability of hazard’s occurrence. The method has been applied to a hospital located in California, US. Three hazards (earthquake, blast and fire) have been analyzed. First, non-linear time-history analyses have been performed using seven ground motions scaled to five different earthquake levels and the seismic response of the structure has been evaluated. The seismic input has damaged the hospital’s power supply (LPG reservoir tank) which has caused a blast. The probability of explosion has been estimated taking into account the probabilities of fuel leakage, fuel concentration, and ignition respectively. A set of twelve blast intensity levels has been considered in the analyses, corresponding to different quantities of fuel content inside the tank. Afterwards, a fire hazard is generated following the explosion, whose intensity level has been evaluated using the compartmental heat flux. The fire effects have been modeled assuming an increment of temperature in the steel frame. The proposed multi-hazard approach can be used for both improving the structural safety and reducing the building life cycle costs to enhance in the end, the resilience of the hospital. Results show that this methodology can be used to provide risk mitigation measures within a more general resilience framework

Resilience assessment for the built environment of a virtual city

This paper presents a new methodology to predict the potential damage and physical impacts of earthquake on the built environment through nonlinear dynamic simulations. A virtual city consisting of different building categories has been designed. Four building sectors that provide essential functions to a community, including housing (residential building, hotel, shelter, etc.), education (school, university, library, etc.), business (shopping center, retail store, heavy industry, etc.), and public services (hospital, police station, church, airport, etc.) are considered. Once the buildings are integrated into the city, parallel simulations are applied to compute the system functionality following a disruptive scenario. Nonlinear response of a multi degree of freedom model for each residential building is obtained considering the dominant modal shapes and irregularities. The post-elastic behavior is estimated through collapse analysis which allows identification of the over strength factor associated to the most probable failure mechanism of the building. Monte Carlo Simulations (MCS) are applied in order 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 methodology allows decision-makers to explore how their community will respond to a disruptive event, quantify the performance of critical infrastructure following a hazard, and to plan better resilience-building strategies in order to minimize losses and recovery time

COMMUNITY RESILIENCE ASSESSMENT TOOLS BASED ON THE PEOPLES FRAMEWORK: WEB APP AND DESKTOP SOFTWARE

Measuring community resilience has been an exploding field of inquiry in the last decade. Many options for measuring resilience ranging from specific measurements to frameworks can be found in literature. Among the different options available, indicators are perceived as an important instrument to assess the resilience of communities due to the simplicity involved in the process. This paper introduces indicator-based software tools to compute the resilience of communities. The tools are implemented in the form of web and desktop application that is accessible from any platform. The algorithm adopted in these tools is based on the PEOPLES framework. PEOPLES is a framework for defining and measuring the resilience of communities at various scales. The presented tools allow the user to choose both the type of hazard and community (rural, urban, industry) against which the resilience is measured. These inputs identify what indicators should be considered and suggest what weighting factor each indicator should take. The software tools take as inputs the performance of the indicators before and after a disaster event as well as the restoration time. The output is presented in the form of a resilience curve of the whole community. The developed tools have been tested to assess the level of resilience of San Francisco. Results of the case study show that the developed tools allow decision makers to derive key aspects on which most effort should be placed to improve their community resilience

A new approach to Multi-hazard analysis

Multi-hazard engineering is increasingly recognized as a serious worldwide concern. In this paper, the principle of multi-hazard is applied to an essential steel structure (a hospital) located in California, US. The studied structure is assumed to be exposed to a sequence of three different cascading hazards (earthquake, blast, and fire). First, non-linear time-history analyses are performed and the seismic response of the structure is evaluated. The seismic input is assumed to cause damage to the hospital’s power supply which it turns to generate an explosion. The probability of explosion is estimated accounting for the probabilities of fuel leakage, fuel concentration, and ignition. A set of twelve blast intensity levels is considered in the analysis, corresponding to the different quantity of fuel content inside the tank. Afterward, a fire hazard is generated following the explosion, whose intensity level is evaluated using the compartmental heat flux. The effect of the fire is translated into an increase in the steel’s temperature, and damage is consequently evaluated. A methodology is proposed to accumulate the cascading damage caused by multi-hazard based on the conditional probability of occurrence. This method is capable of predicting the damage severity of the structural and non-structural components with a high accuracy. The proposed multi-hazard method is considered a significant step in improving the accuracy of loss estimation and in providing risk mitigation measures within the resilience-based environment. The results obtained in this paper verify the effectiveness and the practicality of the proposed method

A new framework to estimate the probability of fire following earthquake

Fire following earthquake has been recognized as a very significant risk in the past decade. Several studies have been performed by researchers to develop analytical and experimental methods to assess the economic and life losses due to fire after an earthquake event. While the outcome of these efforts has resulted in significant advances, an accurate and simplified framework to be utilized by practicing engineers is still lacking. In this paper, a new methodology to predict the probability to have fire following a seismic event considering the building seismic damage is proposed. Earthquake was considered as the main hazard, whereas blast and fire were assumed as a cascading hazards. Bayesian approach was used to estimate conditional probability of fire caused by an earthquake. A hospital building has been assumed as case study, while a LPG tank located nearby the structure has been considered as potential source of blast and ignition. A physical-based simulation was used to evaluate intra-structure ignition probability due to leakage and/or breaks of the gas pipelines. Several parameters were considered to model the occurrence of intra-structure ignitions such as structural and non-structural damage, earthquake intensity, buildings geometry and occupancy and earthquake scenario time. proposed framework is considered a significant step to accurately predict fire risk following a seismic event with affordable time and it can be an alternative solution to the statistical ignition model currently being used in many fire following hazard methods

Resilience Assessment of Urban Communities

The multiple uncertainties of both natural and man-made disasters have prompted increased attention in 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 disaster resilience of communities at various scales. It consists of seven dimensions summarized with the acronym PEOPLES: Population; Environment; Organized governmental services; Physical infrastructures; Lifestyle; Economic; and Social capital. Each of the dimensions is split into several components and indicators, which have been 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. Higher functionality of the indicator leads to 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 analysed 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 a resilience metric have been computed

Resilience of critical structures, infrastructure, and communities

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

RESTORATION CURVES TO ESTIMATE THE DOWNTIME OF CRITICAL INFRASTRUCTURES

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

PEOPLES: indicator based tool to compute community resilience

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