Date of Award:
Master of Science (MS)
Civil and Environmental Engineering
James A. Bay
Transportation networks, as important lifelines linking communities and goods, are indispensable for the smooth functioning of society. These networks are, however, fragile and vulnerable to natural and manmade disasters, which can disrupt their vital functionality. The role of the transportation sector becomes more crucial during disasters due to its role in pre-disaster evacuation as well as post-disaster recovery. The ability of transportation systems to retain performance during and after disasters undergoing little to no loss and their ability to return to the normal state of operation quickly after disasters defines their resilience. Authorities need to understand the degree of resilience within the transportation system under their jurisdiction and plan for improvements. In this research, attempts have been made to deal with resilience in quantitative ways to provide defensible data to decision makers to support investment strategies.
Total loss in the network performance can be quantified by dealing with the variation of network performance over time after disasters and the network resilience can be measured by the ability to minimize this loss. It has been shown that robust networks retain better performance after disruptions and recovery works, which follow optimized recovery paths, in spite of constraints of resources and time, help to minimize the total losses and enhance the network resilience. The objective of this research is to create a conceptual framework to quantify resilience and discuss quantitatively the properties determining resilience of transportation networks. The concepts presented are applied to a test network to illustrate the mathematical procedures. Such methods can help decision makers analyze relative improvements in resiliency as a consequence of proposed project alternatives and help to perform benefit-cost analysis for such projects.
Pant, Sunil Babu, "Transportation Network Resiliency: A Study of Self-Annealing" (2012). All Graduate Theses and Dissertations. 1434.
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