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dc.contributor.authorMohammad Baradaranshoraka; Jean-Paul Pinelli; Kurt Gurley; Mingwei Zhao; Xinlai Peng; Andres Paleo-Torres
dc.date.accessioned2019-03-10T11:52:53Z
dc.date.available2019-03-10T11:52:53Z
dc.date.issued2019
dc.identifier.otherAJRUA6.0001006.pdf
dc.identifier.urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4254434
dc.description.abstractRisk management programs and catastrophe models use fragility and vulnerability curves extensively. For the case of coastal flood events, the independent variable for these damage functions is usually the inundation depth, sometimes combined with some expression of water velocity or wave action. Postdisaster surveys often provide the basis for these damage functions, where the investigators classify the observed damage into broad categories based on qualitative descriptions. This paper describes a method to transform these qualitative evaluations into quantitative descriptions of damage states, which are then applied to develop fragility and vulnerability curves. The authors present this process within the context of the development of coastal flood fragility and vulnerability functions for the Florida Public Hurricane Loss Model. The model characterizes and quantifies the damage states specific to a set of fragility curves by using damage distributions and component cost analysis and transforms the fragility curves into a vulnerability curve. The paper analyzes the uncertainties in the model due to the number and quantification of the damage states and an adjustment function included in the discretization process. The analysis shows that the number of damage states governs the overall uncertainty. Model outputs are compared with USACE expert opinion depth-damage functions to validate the model and identify aspects for further refinement.
dc.publisherAmerican Society of Civil Engineers
dc.titleCharacterization of Coastal Flood Damage States for Residential Buildings
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/AJRUA6.0001006
dc.page04019001
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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