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dc.contributor.author
Nasrazadani, Hossein
dc.contributor.author
Mahsuli, Mojtaba
dc.contributor.editor
Papadrakakis, Manolis
dc.contributor.editor
Fragiadakis, Michalis
dc.date.accessioned
2021-02-15T08:27:06Z
dc.date.available
2021-02-12T23:41:36Z
dc.date.available
2021-02-15T08:27:06Z
dc.date.issued
2017
dc.identifier.isbn
978-618828441-8
en_US
dc.identifier.other
10.7712/120117.5544.17232
en_US
dc.identifier.uri
http://hdl.handle.net/20.500.11850/469330
dc.description.abstract
This paper puts forward a comprehensive framework for probabilistic quantification of community resilience considering multiple interdependent infrastructure systems. The proposed framework integrates various dimensions of resilience including technical, organizational, social, and economic. To this end, first the post-hazard status of the components of the community, e.g., infrastructure systems, is determined through casualty and damage models. Next, discrete events simulation is employed to quantify the recovery of the community, and the infrastructures thereof. For this purpose, the community restoration capacity, comprising workforce, material, and equipment, is assigned to the damaged components, which produces repair events. Once a component restored, the status of all components is updated considering interdependencies. At this point, the framework quantifies the costs incurred by the community comprising direct costs, i.e., restoration and relocation costs, and indirect costs, i.e., business interruption and socioeconomic costs due to absence of services, during the pre-repair period. Thereafter, the released restoration capacity is reassigned to another unrestored component, producing another event. This process continues until all components reach the intended functionality. The total community cost, which is the accumulated cost over the entire recovery period, is regarded as an indicator of the community resilience. The functionality of different infrastructure systems as well as different dimensions of resilience is incorporated in this single global indicator. This, in turn, provides the ability to determine the importance of each component based on the extent of contribution to this indicator. Therefore, the proposed framework provides decision makers with a decision support tool to identify the optimal resource allocation strategy to achieve a resilient community. The proposed framework is showcased by an application to a community with a building portfolio, commercial units, transportation network, healthcare facilities, and a power distribution network.
en_US
dc.language.iso
en
en_US
dc.publisher
Institute of Structural Analysis and Antiseismic Research, School of Civil Engineering, National Technical University of Athens (NTUA)
en_US
dc.title
Probabilistic quantification of community resilience using discrete event simulation
en_US
dc.type
Conference Paper
dc.type
Conference Paper
ethz.book.title
COMPDYN 2017: Computational Methods in Structural Dynamics and Earthquake Engineering. Proceedings of the 6th International Conference on Computational Methods in Structural Dynamics and Earthquake Engineering
en_US
ethz.journal.volume
1
en_US
ethz.pages.start
1994
en_US
ethz.pages.end
2004
en_US
ethz.event
6th International Conference on Computational Methods in Structural Dynamics and Earthquake Engineering (COMPDYN 2017)
en_US
ethz.event.location
Rhodes Island, Greece
en_US
ethz.event.date
June 15-17, 2017
en_US
ethz.identifier.scopus
ethz.publication.place
Athens
en_US
ethz.publication.status
published
en_US
ethz.identifier.orcidWorkCode
79327019
ethz.date.deposited
2021-02-12T23:41:48Z
ethz.source
FORM
ethz.eth
no
en_US
ethz.availability
Metadata only
en_US
ethz.rosetta.installDate
2021-02-15T08:27:31Z
ethz.rosetta.lastUpdated
2022-03-29T05:12:18Z
ethz.rosetta.versionExported
true
ethz.COinS
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