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Multi-disciplinary seismic resilience modeling for developing mitigation policies and recovery planning

Resilient Cities and Structures 2024年第2期3卷 66-84页

作者： Milad Roohi Saeid Ghasemi Omar Sediek Hwayoung Jeon John W.van de Lindt Martin Shields sara hamideh Harvey Cutler Durham School of Architectural Engineering and Construction University of Nebraska–LincolnOmahaNE68182 USA Dept.of Structural Engineering Cairo Univ.Giza 12613Egypt formerly Postdoctoral FellowDept.of Civil and Environmental EngineeringColorado State Univ.Fort CollinsCO 80523 USA Department of Economics Colorado State UniversityFort CollinsCO 80521 USA Harold H.Short Endowed Chair Professor Department of Civil and Environmental EngineeringColorado State UniversityFort CollinsCO 80523 USA School of Marine and Atmospheric Sciences Stony Brook UniversityStony BrookNY

The multi-disciplinary data and information available at a community level comprise the foundation of natural hazard resilience *** data enable and inform mitigation and recovery planning decisions prior to and following damaging events such as *** paper presents a multi-disciplinary seismic resilience mod-eling methodology to assess the vulnerability of the built environment and economic *** methodology can assist decision-makers with developing effective mitigation policies to improve the seismic resilience of *** complementary modeling strategies are designed to examine the impacts of scenario earthquakes from a combined engineering and economic *** engineering model is developed using a probabilis-tic fragility-based modeling approach and is analyzed using Monte Carlo(MC)simulations subject to seismic multi-hazard,including simulated ground shaking and resulting liquefaction of the soil,to quantify the physical damage to buildings and electric power substations(EPS).The outcome of the analysis is subsequently used as input to repair and recovery models to quantify repair cost and recovery time metrics for buildings and as input to functionality models to estimate the functionality of individual buildings and substations by accounting for their *** economic model consists of a spatial computable general equilibrium(SCGE)model that aggregates commercial buildings into sectors for retail,manufacturing,services,etc.,and aggregates residential buildings into a wide range of household *** SCGE model employs building functionality estimates to quantify the economic *** outcomes of this integrated modeling consist of engineering and economic impact metrics,which are used to investigate mitigation actions to help inform a community on approaches to achieve its resilience *** illustrative case study of Salt Lake County(SLC),Utah,developed through an extensive collaborative partner

关键词： Community resilience Infrastructure systems Multi-disciplinary Mitigation policy Functional recovery

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Multi-hazard socio-physical resilience assessment of hurricane-induced hazards on coastal communities

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Resilient Cities and Structures 2023年第2期2卷 67-81页

作者： Omar M.Nofal Kooshan Amini Jamie E.Padgett John W.van de Lindt Nathanael Rosenheim Yousef M.Darestani Amin Enderami Elaina J.Sutley sara hamideh Leonardo Duenas-Osorio Florida International University MiamiFLUnited States Rice University HoustonTXUnited States Colorado State University Fort CollinsCOUnited States Texas A&M University College StationTXUnited States Michigan Technological University HoughtonMIUnited States The University of Kansas LawrenceKSUnited States Stony Brook Stony Brook UniversityNYUnited States

Hurricane-induced hazards can result in significant damage to the built environment cascading into major impacts to the households,social institutions,and local *** quantifying physical impacts of hurricane-induced hazards is essential for risk analysis,it is necessary but not sufficient for community resilience *** there have been several studies on hurricane risk and recovery assessment at the building-and community-level,few studies have focused on the nexus of coupled physical and social disruptions,particularly when char-acterizing recovery in the face of coastal ***,this study presents an integrated approach to quantify the socio-physical disruption following hurricane-induced multi-hazards(e.g.,wind,storm surge,wave)by considering the physical damage and functionality of the built environment along with the population dynamics over ***,high-resolution fragility models of buildings,and power and transportation infrastructures capture the combined impacts of hurricane loading on the built *** simulat-ing recovery by tracking infrastructure network performance metrics,such as access to essential facilities,this coupled socio-physical approach affords projection of post-hazard population dislocation and temporal evolution of housing and household recovery constrained by the building and infrastructure *** results reveal the relative importance of multi-hazard consideration in the damage and recovery assessment of communities,along with the role of interdependent socio-physical system modeling when evaluating metrics such as housing recovery or the need for emergency ***,the methodology presented here provides a foundation for resilience-informed decisions for coastal communities.

关键词： Fragility analysis Hurricane damage Probabilistic damage assessment Transportation network Power network Housing recovery population impacts

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The interdependent networked community resilience modeling environment(IN-CORE)

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Resilient Cities and Structures 2023年第2期2卷 57-66页

作者： John W.van de Lind Jamie Kruse Daniel T.Cox Paolo Gardoni Jong Sung Lee Jamie Padgett Therese P.McAllister Andre Barbosa Harvey Cutler Shannon Van Zandt Nathanael Rosenheim Christopher M.Navarro Elaina Sutley sara hamideh Harold H.Short Endowed Chair Professor and Co-Director Center of Excellence for Risk-Based Community Resilience PlanningDepartment of Civil and Environmental EngineeringColorado State UniversityFort CollinsCO80523USA Co-Director Center of Excellence for Risk-Based Community Resilience Planning and THCAS Distinguished ProfessorDepartment of EconomicsEast Carolina UniversityGreenvilleNC27858USA CH2M Hill Professor in Civil Engineering School of Civil and Construction EngineeringOregon State UniversityCorvallisOR97331USA Alfredo H.Ang Family Professor and Excellence Faculty Scholar Department of Civil and Environmental Engineeringand DirectorMid-America Earthquake(MAE)CenterUniversity of Illinois at Urbana-ChampaignChampaignIL61820USA Deputy Associate Director National Center for Supercomputing ApplicationsUniversity of Illinois at Urbana-ChampaignChampaignIL61820USA Professor and Chair Department of Civil and Environmental EngineeringRice UniversityHoustonTX77005USA Acting Chief Materials and Structural Systems DivisionNational Institute of Standards and TechnologyGaithersburgMD20899USA Professor Department of EconomicsColorado State UniversityFort CollinsCO80523USA Professor School of ArchitectureLandscape Architecture&Urban PlanningTexas A&M UniversityCollege StationTX77843USA Research Associate Professor Landscape Architecture&Urban PlanningTexas A&M UniversityCollege StationTX77843USA Lead Research Software Engineer National Center for Supercomputing ApplicationsUniversity of Illinois at Urbana-ChampaignChampaignIL61820USA Associate Professor and Associate Dean for Diversity EquityInclusionand BelongingDepartment of Civil and Environmental EngineeringUniversity of KansasLawrenceKansasUSA Associate Professor State University of New York-Stony BrookSchool of Marine and Atmospheric SciencesStony BrookNew YorkUSA

In 2015,the U.S National Institute of Standards and Technology(NIST)funded the Center of Excellence for Risk-Based Community Resilience Planning(CoE),a fourteen university-based consortium of almost 100 col-laborators,including faculty,students,post-doctoral scholars,and NIST *** paper highlights the scientific theory behind the state-of-the-art cloud platform being developed by the CoE-the Interdisciplinary Networked Community Resilience Modeling Environment(IN-CORE).IN-CORE enables communities,consul-tants,and researchers to set up complex interdependent models of an entire community consisting of people,businesses,social institutions,buildings,transportation networks,water networks,and electric power networks and to predict their performance and recovery to hazard scenario events,including uncertainty propagation through the chained *** modeling environment includes a detailed building inventory,hazard scenario models,building and infrastructure damage(fragility)and recovery functions,social science data-driven house-hold and business models,and computable general equilibrium(CGE)models of local *** important aspect of IN-CORE is the characterization of uncertainty and its propagation throughout the chained models of the *** illustrative examples of community testbeds are presented that look at hazard impacts and recovery on population,economics,physical services,and social *** overview of the IN-CORE technology and scientific implementation is described with a focus on four key community stability areas(CSA)that encompass an array of community resilience metrics(CRM)and support community resilience informed *** testbed within IN-CORE has been developed by a team of engineers,social scientists,urban planners,and *** models,begin with a community description,i.e.,people,businesses,buildings,infras-tructure,and progresses to the damage and loss of functions caused by a hazard scenario

关键词： IN-CORE Community Resilience Natural hazards Disasters Risk Uncertainty propagation Decision-support Mitigation Adaptation Tornado Tsunami Earthquake Hurricane

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