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dc.contributor.authorOmar Kammouh; Ali Zamani Noori; Gian Paolo Cimellaro; Stephen A. Mahin
dc.date.accessioned2019-03-10T11:52:51Z
dc.date.available2019-03-10T11:52:51Z
dc.date.issued2019
dc.identifier.otherAJRUA6.0001004.pdf
dc.identifier.urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4254432
dc.description.abstractThe 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.
dc.publisherAmerican Society of Civil Engineers
dc.titleResilience Assessment of Urban Communities
dc.typeJournal Paper
dc.journal.volume5
dc.journal.issue1
dc.journal.titleASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering
dc.identifier.doi10.1061/AJRUA6.0001004
dc.page04019002
dc.treeASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering:;2019:;Volume ( 005 ):;issue: 001
dc.contenttypeFulltext


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