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

被引:0
|
作者
van de Lindt, John W. [1 ]
Kruse, Jamie [2 ]
Cox, Daniel T. [3 ]
Gardoni, Paolo [4 ]
Lee, Jong Sung [5 ]
Padgett, Jamie [6 ]
McAllister, Therese P. [7 ]
Barbosa, Andre [3 ]
Cutler, Harvey [8 ]
Van Zandt, Shannon [9 ]
Rosenheim, Nathanael [10 ]
Navarro, Christopher M. [11 ]
Sutley, Elaina [12 ]
Hamideh, Sara [13 ]
机构
[1] 不详
[2] Contact Author],Harold H. Short Endowed Chair Professor and Co-Director, Center of Excellence for Risk-Based Community Resilience Planning, Department of Civil and Environmental Engineering, Colorado State University, Fort Collins,CO,80523, United States
[3] Co-Director, Center of Excellence for Risk-Based Community Resilience Planning and THCAS Distinguished Professor, Department of Economics, East Carolina University, NC, Greenville,27858, United States
[4] CH2M Hill Professor in Civil Engineering, School of Civil and Construction Engineering, Oregon State University, Corvallis,OR,97331, United States
[5] Alfredo H. Ang Family Professor and Excellence Faculty Scholar, Department of Civil and Environmental Engineering, and Director, Mid-America Earthquake (MAE) Center, University of Illinois at Urbana-Champaign, Champaign,IL,61820, United States
[6] Deputy Associate Director, National Center for Supercomputing Applications, University of Illinois at Urbana-Champaign, Champaign,IL,61820, United States
[7] Professor and Chair, Department of Civil and Environmental Engineering, Rice University, Houston,TX,77005, United States
[8] Acting Chief, Materials and Structural Systems Division, National Institute of Standards and Technology, Gaithersburg,MD,20899, United States
[9] Professor, Department of Economics, Colorado State University, Fort Collins,CO,80523, United States
[10] Professor, School of Architecture, Landscape Architecture & Urban Planning, Texas A&M University, College Station,TX,77843, United States
[11] Research Associate Professor, Landscape Architecture & Urban Planning, Texas A&M University, College Station,TX,77843, United States
[12] Lead Research Software Engineer, National Center for Supercomputing Applications, University of Illinois at Urbana-Champaign, Champaign,IL,61820, United States
[13] Associate Professor and Associate Dean for Diversity, Equity, Inclusion, and Belonging, Department of Civil and Environmental Engineering, University of Kansas, Lawrence,KS, United States
[14] Associate Professor, State University of New York – Stony Brook, School of Marine and Atmospheric Sciences, Stony Brook,NY, United States
来源
Resilient Cities and Structures | 2023年 / 2卷 / 02期
关键词
Behavioral research - Computer system recovery - Decision making - Decision support systems - Earthquakes - Economics - Hazards - Hurricanes - Recovery - Storms - Testbeds - Tornadoes - Tsunamis - Uncertainty analysis;
D O I
10.1016/j.rcns.2023.07.004
中图分类号
学科分类号
摘要
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 collaborators, including faculty, students, post-doctoral scholars, and NIST researchers. This 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, consultants, 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 models. The modeling environment includes a detailed building inventory, hazard scenario models, building and infrastructure damage (fragility) and recovery functions, social science data-driven household and business models, and computable general equilibrium (CGE) models of local economies. An important aspect of IN-CORE is the characterization of uncertainty and its propagation throughout the chained models of the platform. Three illustrative examples of community testbeds are presented that look at hazard impacts and recovery on population, economics, physical services, and social services. An 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 decision-making. Each testbed within IN-CORE has been developed by a team of engineers, social scientists, urban planners, and economists. Community models, begin with a community description, i.e., people, businesses, buildings, infrastructure, and progresses to the damage and loss of functions caused by a hazard scenario, i.e., a flood, tornado, hurricane, or earthquake. This process is accomplished through chaining of modular algorithms, as described. The baseline community characteristics and the hazard-induced damage sets are the initial conditions for the recovery models, which have been the least studied area of community resilience but arguably one of the most important. Communities can then test the effect of mitigation and/or policies and compare the effects of what if scenarios on physical, social, and economic metrics with the only requirement being that the change much be able to be numerically modeled in IN-CORE. © 2023
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页码:57 / 66
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