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    Methodology for Interdependent Population–Building–Infrastructure Posthazard Functionality Assessment for Communities

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    JSENDH.STENG-13222.pdf (1.781Mb)
    Date
    2025
    Author
    Omar M. Nofal
    Nathanael Rosenheim
    Sabarethinam Kameshwar
    Jayant Patil
    Xiangnan Zhou
    John W. van de Lindt
    Leonardo Duenas-Osorio
    Eun Jeong Cha
    Amin Endrami
    Elaina Sutley
    Harvey Cutler
    Hwayoung Jeon
    Tao Lu
    Chen Wang
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    Abstract
    Modeling and improving community resilience to natural hazards has gained substantial interest over the past two decades, in part, due to the increased level of coupled risk resulting from climate change and urbanization. Evidence suggests that climate change increases both the frequency and intensity of climatic hazards, such as hurricanes, tornadoes, and floods. Further, urbanization in hazard-prone areas increases exposure and the vulnerability of communities. Although significant progress has been made in resilience research, a model that can quantify the posthazard functionality of buildings by considering the state of nonphysical factors has not yet been fully explored. This is due to the complexity of coupling physics-based and data-driven models, which include population demographics, buildings, and distributed infrastructure along with their physical, social, and economic interdependencies. Therefore, in this paper, a novel probabilistic formulation is developed to model the interdependent population-buildings-infrastructure relationship and quantify their role in community resilience, with a focus on immediate posthazard functionality. This is accomplished by developing a new posthazard functionality method for a computational environment (IN-CORE) that allows an analyst to perform comprehensive community-level analysis at building-level and household-level resolution. The methodology is developed such that it quantifies the probabilistic functionality of each subsystem separately (e.g., buildings, utilities, social institutions, etc.), and then combines their functionality in a functionality matrix that has the exceedance probability for a prescribed functionality state. This probabilistic functionality matrix is then converted into a deterministic functionality vector that has the total functionality ratio for each subsystem using the contribution of each functionality state corresponding to each subsystem to the total building functionality. The novel contribution of this approach is the ability to systematically quantify across scales posthazard functionality of communities by combining physical and nonphysical systems and their components after including interdependencies and uncertainties within these systems.
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    http://yetl.yabesh.ir/yetl1/handle/yetl/4306662
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