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

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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Publication Details

Journal
Journal of Structural Engineering
Published
2025-03-05
DOI
https://doi.org/10.1061/jsendh.steng-13222
Citations
3
Primary Topic
Infrastructure Resilience and Vulnerability Analysis
Type
article
Field-Weighted Citation Impact
2.86
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article

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

Elaina J. Sutley, Xiangnan Zhou, Hwayoung Jeon, John W. van de Lindt et al.
3 citations
Journal of Structural Engineering
Infrastructure Resilience and Vulnerability Analysis
2.86
article

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

Elaina J. Sutley, Xiangnan Zhou, Hwayoung Jeon, John W. van de Lindt, Nathanael Rosenheim, S. Amin Enderami, Jayant Patil, Leonardo Dueñas‐Osorio, Harvey Cutler, Omar M. Nofal, Sabarethinam Kameshwar, Chen Wang, Eun Jeong, Tao Lu
article en
3 citations

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.

Journal of Structural EngineeringVol. 151(5)
Louisiana State University (US), University of Kansas (US), University of Illinois Urbana-Champaign (US), Florida International University (US), Mitchell Institute (US), Rice University (US), Colorado State University (US)
Openalex Percentile: Top 9%
Infrastructure Resilience and Vulnerability Analysis
2.86
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