• Login
    View Item 
    •   DSpace Home
    • ASME
    • ASME Journal of Engineering for Sustainable Buildings and Cities
    • View Item
    •   DSpace Home
    • ASME
    • ASME Journal of Engineering for Sustainable Buildings and Cities
    • View Item
    JavaScript is disabled for your browser. Some features of this site may not work without it.

    Resilience of Complex Adaptive Systems: A Pedagogical Framework for Engineering Education and Research

    Thumbnail
    View/Open
    jesbc_1_2_021004.pdf (339.3Kb)
    Date
    2020
    Author
    Reddy, T. Agami
    Metadata
    Show full item record
    Abstract
    The discourse on resilience, currently at the forefront of research and implementation in a wide variety of fields, is confusing because of its multi-disciplinary/spatial/temporal nature. Resilience analysis is a discipline that allows the assessment and enhancement of the coping and recovery behaviors of systems when subjected to short-lived high-impact external shocks leading to partial or complete failure. This paper, meant for pedagogical teaching and research formulation, starts by providing an overview of different aspects of resilience in general and then focuses on communities and regions that are complex adaptive systems (CAS) involving multiple engineered infrastructures providing essential services to local inhabitants and adapted to available natural resources and social requirements. Next, for objective analysis and assessment, it is proposed that resilience be characterized by four different quantifiable sub-attributes. This paper then describes the standard technocentric manner in which different temporal phases during and in the aftermath of disasters are generally visualized and analyzed, and discusses how these relate to reliability and risk analyses. Subsequently, two prevalent types of frameworks are described and representative literature reviewed: (i) those that aim at improving general resilience via soft methods such as subjective means (interviews, narratives) and census data, and (ii) those that are meant to enhance specific resilience under certain threat scenarios using hard/objective methods such as data-driven analysis and performance-predictive modeling methods, akin to resource allocation problems in operations research. Finally, the need for research into an integrated framework is urged; one that could potentially combine the strengths of both approaches.
    URI
    http://yetl.yabesh.ir/yetl1/handle/yetl/4273453
    Collections
    • ASME Journal of Engineering for Sustainable Buildings and Cities

    DSpace software copyright © 2002-2015  DuraSpace
    Contact Us | Send Feedback
    Theme by 
    @mire NV
     

     

    Browse

    All of DSpaceCommunities & CollectionsBy Issue DateAuthorsTitlesSubjectsThis CollectionBy Issue DateAuthorsTitlesSubjects

    My Account

    LoginRegister

    Statistics

    View Usage Statistics

    DSpace software copyright © 2002-2015  DuraSpace
    Contact Us | Send Feedback
    Theme by 
    @mire NV