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    A Probabilistic Framework for Resilience Quantification of Residential Building Portfolios Exposed to Tropical Cyclone Winds

    Source: ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering:;2023:;Volume ( 009 ):;issue: 004::page 04023040-1
    Author:
    Cao Wang
    ,
    Lip H. Teh
    ,
    Kairui Feng
    DOI: 10.1061/AJRUA6.RUENG-1129
    Publisher: ASCE
    Abstract: Residential buildings in coastal areas often suffer from dramatic cyclone-induced damages. Resilience analysis is a powerful tool to quantify the object’s (e.g., a building portfolio’s) ability to withstand disruptive events. The key aspects include (1) the modeling of the recovery process in the aftermath of a cyclone event, which is intrinsically complex and is conditional on multiple factors (e.g., the available resources, the damage state immediately after a hazardous event), and (2) a reasonable index for resilience quantification that is capable of reflecting the asset owner/decision-maker’s requirement for the recovery process. In this paper, a new resilience measure is proposed that incorporates a requirement of anticipated recovery time (i.e., whether the recovery can be completed before the anticipated time) for the object. A novel framework for resilience quantification of residential building portfolios is also developed, which involves an optimal resource allocation strategy to maximize the resilience of building portfolios. The applicability of the proposed framework is illustrated through examining the resilience of a virtual community subjected to cyclone winds. The impacts of resourcefulness, wind field uncertainty, and correlation between building capacities on the building portfolio resilience are investigated.
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      A Probabilistic Framework for Resilience Quantification of Residential Building Portfolios Exposed to Tropical Cyclone Winds

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    contributor authorCao Wang
    contributor authorLip H. Teh
    contributor authorKairui Feng
    date accessioned2024-04-27T20:58:55Z
    date available2024-04-27T20:58:55Z
    date issued2023/12/01
    identifier other10.1061-AJRUA6.RUENG-1129.pdf
    identifier urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4296379
    description abstractResidential buildings in coastal areas often suffer from dramatic cyclone-induced damages. Resilience analysis is a powerful tool to quantify the object’s (e.g., a building portfolio’s) ability to withstand disruptive events. The key aspects include (1) the modeling of the recovery process in the aftermath of a cyclone event, which is intrinsically complex and is conditional on multiple factors (e.g., the available resources, the damage state immediately after a hazardous event), and (2) a reasonable index for resilience quantification that is capable of reflecting the asset owner/decision-maker’s requirement for the recovery process. In this paper, a new resilience measure is proposed that incorporates a requirement of anticipated recovery time (i.e., whether the recovery can be completed before the anticipated time) for the object. A novel framework for resilience quantification of residential building portfolios is also developed, which involves an optimal resource allocation strategy to maximize the resilience of building portfolios. The applicability of the proposed framework is illustrated through examining the resilience of a virtual community subjected to cyclone winds. The impacts of resourcefulness, wind field uncertainty, and correlation between building capacities on the building portfolio resilience are investigated.
    publisherASCE
    titleA Probabilistic Framework for Resilience Quantification of Residential Building Portfolios Exposed to Tropical Cyclone Winds
    typeJournal Article
    journal volume9
    journal issue4
    journal titleASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering
    identifier doi10.1061/AJRUA6.RUENG-1129
    journal fristpage04023040-1
    journal lastpage04023040-12
    page12
    treeASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering:;2023:;Volume ( 009 ):;issue: 004
    contenttypeFulltext
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