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    Capacity Building for an Infrastructure System in Case of Disaster Using the System's Associated Social and Technical Components

    Source: Journal of Management in Engineering:;2019:;Volume ( 035 ):;issue: 004
    Author:
    Juyeong Choi
    ,
    Nader Naderpajouh
    ,
    David J. Yu
    ,
    Makarand Hastak
    DOI: 10.1061/(ASCE)ME.1943-5479.0000697
    Publisher: American Society of Civil Engineers
    Abstract: Disasters often indirectly cause two impacts that may impede recovery: a decline in the capacity of a system because of failures in its supporting components and a surge in demand for the system's services. Therefore, there is a need to quantitatively assess how a system can extend its capacity to adapt to a trying situation where it is challenged to its limits by both direct and indirect impacts. In this paper, an alternative quantitative model is presented for the performance of an infrastructure system in the context of postdisaster operations. The functional stress and strain of various system components are then analyzed as a potential additional metric for resilience. The analysis quantifies the reciprocal effects between the social and technical components on the performance of a postdisaster infrastructure system during the recovery process. A stylized model of a healthcare infrastructure system is developed as a proof of concept. The model is used to present a systematic understanding of the strategic planning and policy development needed to enhance resilience in infrastructure systems. Specifically, strategies focused on the technical components of infrastructure systems are contrasted with strategies focused on social components. Through the application of the model, we improve our understanding of how a system can extend its capacity and still function in the face of disasters.
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      Capacity Building for an Infrastructure System in Case of Disaster Using the System's Associated Social and Technical Components

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    contributor authorJuyeong Choi
    contributor authorNader Naderpajouh
    contributor authorDavid J. Yu
    contributor authorMakarand Hastak
    date accessioned2019-09-18T10:43:02Z
    date available2019-09-18T10:43:02Z
    date issued2019
    identifier other%28ASCE%29ME.1943-5479.0000697.pdf
    identifier urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4260652
    description abstractDisasters often indirectly cause two impacts that may impede recovery: a decline in the capacity of a system because of failures in its supporting components and a surge in demand for the system's services. Therefore, there is a need to quantitatively assess how a system can extend its capacity to adapt to a trying situation where it is challenged to its limits by both direct and indirect impacts. In this paper, an alternative quantitative model is presented for the performance of an infrastructure system in the context of postdisaster operations. The functional stress and strain of various system components are then analyzed as a potential additional metric for resilience. The analysis quantifies the reciprocal effects between the social and technical components on the performance of a postdisaster infrastructure system during the recovery process. A stylized model of a healthcare infrastructure system is developed as a proof of concept. The model is used to present a systematic understanding of the strategic planning and policy development needed to enhance resilience in infrastructure systems. Specifically, strategies focused on the technical components of infrastructure systems are contrasted with strategies focused on social components. Through the application of the model, we improve our understanding of how a system can extend its capacity and still function in the face of disasters.
    publisherAmerican Society of Civil Engineers
    titleCapacity Building for an Infrastructure System in Case of Disaster Using the System's Associated Social and Technical Components
    typeJournal Paper
    journal volume35
    journal issue4
    journal titleJournal of Management in Engineering
    identifier doi10.1061/(ASCE)ME.1943-5479.0000697
    page04019013
    treeJournal of Management in Engineering:;2019:;Volume ( 035 ):;issue: 004
    contenttypeFulltext
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