Browsing by Author "Kruse, Jamie"

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    Ep. #013 - Cultures of Energy 5
    (Cultures of Energy, Rice University, 2017-12-14) Boyer, Dominic (podcast host); Howe, Cymene (podcast host); Daggett, Cara; Malm, Andreas; Badia, Lynn; Macdonald, Graeme; Ellsworth, Elizabeth; Kruse, Jamie
    This week’s energy humanities podcast recaps and takes inspiration from CENHS’s fifth annual spring research symposium, otherwise known as Cultures of Energy 5 (http://culturesofenergy.com/cultures-of-energy-april-21-23-2016-poster-and-schedule/), which took place at Rice last week in the afterwash of Houston’s historic flooding. Cymene and Dominic share fond memories from the symposium and then, inspired by the Lexicon for an Anthropocene Yet Unseen project, (http://www.culanth.org/fieldsights/803-lexicon-for-an-anthropocene-yet-unseen), several of our distinguished visitors offer short takes and keywords for the Anthropocene. Cara Daggett (Johns Hopkins) goes to “work” (13:50), Andreas Malm (Lund) offers “resistance” (17:47), and Lynn Badia (Alberta) muses on “free” (22:50). Graeme Macdonald (Warwick) shows us his “passport” (24:58) and smudge studio (Elizabeth Ellsworth and Jamie Kruse, http://www.smudgestudio.org) walk us through “ippo” (30:00). Finally, Toronto-based poet Mathew Henderson reads (36:30) from his remarkable collection, The Lease (http://www.chbooks.com/catalogue/lease). All in all, we celebrate energy humanities as an alien intelligence in our petrocultural system. Get ready for Cultures of Energy 6 in 2017!
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    The interdependent networked community resilience modeling environment (IN-CORE)
    (Elsevier, 2023) van de Lindt, John W.; Kruse, Jamie; Cox, Daniel T.; Gardoni, Paolo; Lee, Jong Sung; Padgett, Jamie; McAllister, Therese P.; Barbosa, Andre; Cutler, Harvey; Van Zandt, Shannon; Rosenheim, Nathanael; Navarro, Christopher M.; Sutley, Elaina; Hamideh, Sara
    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.