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dc.contributor.authorWanting “Lisa” Wang
dc.contributor.authorJohn W. van de Lindt
dc.contributor.authorBlythe Johnston
dc.contributor.authorP. Shane Crawford
dc.contributor.authorGuirong Yan
dc.contributor.authorThang Dao
dc.contributor.authorTrung Do
dc.contributor.authorKatie Skakel
dc.contributor.authorMojtaba Harati
dc.contributor.authorTu Nguyen
dc.contributor.authorRobinson Umeike
dc.contributor.authorSilvana Croope
dc.contributor.authorAndre R. Barbosa
dc.date.accessioned2024-04-27T22:26:15Z
dc.date.available2024-04-27T22:26:15Z
dc.date.issued2024/06/01
dc.identifier.other10.1061-JPCFEV.CFENG-4650.pdf
dc.identifier.urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4296651
dc.description.abstractFrom December 10 to December 11, 2021, a deadly tornado outbreak struck across several states in the US, including Arkansas, Illinois, Kentucky, and Tennessee. This tornado outbreak resulted in at least $3.9 billion in damage, more than 90 fatalities, and hundreds of injuries. Mayfield, Kentucky, a small city in the eastern United States, was hit by a long-track tornado rated as an Enhanced Fujita 4 (EF4) scale and was one of the communities most heavily damaged during the tornado outbreak. Following the 2021 tornado event, an analysis was performed in the Interdependent Networked Community Resilience Modeling Environment (IN-CORE) for the City of Mayfield to investigate a design code change for residential structures and its effect on communitywide metrics related to functionality and dislocation. Specifically, the IN-CORE modeling environment was used to hindcast the community-level building damage and forecast the community-level building recovery in Mayfield for residential buildings. This required the development of a Mayfield test bed for IN-CORE with a focus on buildings. The generalization of multidisciplinary community resilience modeling from a test bed community to a real community impacted by a recent major tornado event is intended to benchmark that IN-CORE has a strong potential and capability to forecast/hindcast community resilience and provide what-if scenarios for decision makers, city planners, and stakeholders in communities with similar sizes.
dc.publisherASCE
dc.titleApplication of Multidisciplinary Community Resilience Modeling to Reduce Disaster Risk: Building Back Better
dc.typeJournal Article
dc.journal.volume38
dc.journal.issue3
dc.journal.titleJournal of Performance of Constructed Facilities
dc.identifier.doi10.1061/JPCFEV.CFENG-4650
dc.journal.fristpage04024012-1
dc.journal.lastpage04024012-12
dc.page12
dc.treeJournal of Performance of Constructed Facilities:;2024:;Volume ( 038 ):;issue: 003
dc.contenttypeFulltext


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