Eine Plattform für die Wissenschaft: Bauingenieurwesen, Architektur und Urbanistik
Eine Plattform für die Wissenschaft: Bauingenieurwesen, Architektur und Urbanistik
Effect of building wind-retrofit strategies on socio-economic community-level resilience metrics ; 190 - Lisa Wang
Department of Civil and Environmental Engineering. ; Includes bibliographical references. ; 2020 Fall. ; Tornadoes occur at a high frequency in the United States compared with other natural hazards but have a substantially small footprint. A single high-intensity tornado can result in high casualty rates and catastrophic economic and social consequences, particularly for small to medium communities. Comprehensive community resilience assessment and improvement requires the analyst to develop a model of interacting physical, social, and economic systems, and to measure outcomes that result from specific decisions made. These outcomes often are in the form of metrics such as the number of people injured or the number of households or businesses without water, but it has been recognized that most community resilience metrics have socio-economic characteristics. In this study, for the first time, a fully quantitative interacting model is used to examine the effect of a tornado damaging physical infrastructure (buildings and electrical power network) and the effects on the population and the local economy for a real community. Then, three residential building retrofit strategies are considered as alternatives to improve community resilience and metrics from the physical, economic, and social sectors computed. An illustrative example is presented for the 2011 Joplin tornado in a new open-source Interdependent Networked Community Resilience Modeling Environment (IN-CORE), with a computable general equilibrium (CGE) economics model that computes household income, employment, and domestic supply before and after the tornado. Detailed demographic data was allocated to each structure to calculate resilience metrics related to population dislocation impacts from the tornado.
Effect of building wind-retrofit strategies on socio-economic community-level resilience metrics ; 190 - Lisa Wang
Department of Civil and Environmental Engineering. ; Includes bibliographical references. ; 2020 Fall. ; Tornadoes occur at a high frequency in the United States compared with other natural hazards but have a substantially small footprint. A single high-intensity tornado can result in high casualty rates and catastrophic economic and social consequences, particularly for small to medium communities. Comprehensive community resilience assessment and improvement requires the analyst to develop a model of interacting physical, social, and economic systems, and to measure outcomes that result from specific decisions made. These outcomes often are in the form of metrics such as the number of people injured or the number of households or businesses without water, but it has been recognized that most community resilience metrics have socio-economic characteristics. In this study, for the first time, a fully quantitative interacting model is used to examine the effect of a tornado damaging physical infrastructure (buildings and electrical power network) and the effects on the population and the local economy for a real community. Then, three residential building retrofit strategies are considered as alternatives to improve community resilience and metrics from the physical, economic, and social sectors computed. An illustrative example is presented for the 2011 Joplin tornado in a new open-source Interdependent Networked Community Resilience Modeling Environment (IN-CORE), with a computable general equilibrium (CGE) economics model that computes household income, employment, and domestic supply before and after the tornado. Detailed demographic data was allocated to each structure to calculate resilience metrics related to population dislocation impacts from the tornado.
Effect of building wind-retrofit strategies on socio-economic community-level resilience metrics ; 190 - Lisa Wang
Wang, Wanting (Lisa) (Autor:in) / van de Lindt, John (Autor:in)
30.11.2020
Bild
Elektronische Ressource
Englisch
DDC:
710
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