Retentive Input-Output Modeling of Complex Systems of Systems for Disaster Planning
Eddy, Timothy, Systems Engineering - School of Engineering and Applied Science, University of Virginia
Haimes, Yacov, Department of Systems Engineering, University of Virginia
This thesis develops a methodology to quantify the potential economic and social effects of storm events exacerbated by sea-level rise as a disruptive event. Further, the elements of the infrastructure system of systems, which are most vulnerable to this event, are identified as candidates for investment in its hardening. The existing literature on disaster planning has successfully described the associated cost of not-hardening infrastructure. However, it does not support planners who would wish to compare the risk profiles of alternative investment strategies. This research fills this vital gap by providing a framework to evaluate the tradeoffs that exist among alternative plans. It quantifies the impact of sea-level rise on the southern coastal region of the United States. Sea-level rise has already been observed and is negatively impacting the U.S. economy. Rising seas increase the risk of flooding and wave damage to coastal property. A holistic consideration of the impact of this damage includes many social as well as economic factors, such as temporary displacement, traumatization, particularly of children, disruptions to healthcare, loss of education while schools are closed, or loss of family heirlooms and photographs. For the purpose of this research, we focus on the cascading economic impact of production disruptions. Estimates of increasing sea-level rise and severity of storms are the basis for creating scenarios that communities may face in the future. As infrastructure systems are highly integrated both economically and socially, this analysis considers the interconnectedness and interdependence manifested in the transportation sector as a complex system of systems. Disruption to investment priorities is demonstrated to result from lack of consideration of latent rail transportation network capacity.
MS (Master of Science)
IIM, Disaster Planning, Risk
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