A Decision Framework for Improving Resilience of Civil Infrastructure Systems Considering Effects of Natural Disasters

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dc.contributor.advisor Ranji S. Ranjithan, Committee Co-Chair en_US
dc.contributor.advisor E. Downey Brill, Committee Co-Chair en_US
dc.contributor.advisor John Baugh, Committee Co-Chair en_US
dc.contributor.author Piper, Brian E en_US
dc.date.accessioned 2010-04-02T18:05:11Z
dc.date.available 2010-04-02T18:05:11Z
dc.date.issued 2009-08-03 en_US
dc.identifier.other etd-05112009-130034 en_US
dc.identifier.uri http://www.lib.ncsu.edu/resolver/1840.16/1567
dc.description.abstract There can be massive ramifications from natural disasters for civil infrastructure systems. Damage to infrastructure components, such as roads, bridges, levees, dams, buildings and houses, causes economic loss and disrupts critical lifelines. It is necessary to build more resilient infrastructure systems capable of withstanding and recovering from damaging effects caused by natural hazards. This thesis addresses the need for a framework capable of determining the decisions that can improve system resilience and reduce system-wide risk to natural disasters. A brief background is given of the concept of interdependent infrastructure components and the importance of including interdependencies in integrated modeling of infrastructure systems. Different categories of past modeling efforts are reviewed, with categories defined by both model structure and abilities, especially the abilities to change system behavior, prescribe decisions, and incorporate uncertainty in analysis. One of the issues with current infrastructure modeling is a deficiency in defining meaningful and varied system performance functions. Different types of quantitative performance measures (or metrics) for infrastructure systems are considered. Metrics are developed for characterizing serviceability (the potential for an infrastructure to fulfill the lifeline needs), property damage, travel time, and cost of upgrades and retrofits. These metrics are intended to evaluate the collective performance of the components of the system, and to prioritize and determine the effect of decisions such as upgrades and retrofits. Models are developed that are realizations of different scenarios, each based on particular combinations of the infrastructure system and its traits of interest, especially the interdependencies and interrelationships. The range of models developed begins with systems that have a protective infrastructure, such as a levee, and flexibility allows the modeling framework to consider numerous other situations. The definitions of the decision variables and the model expressions allow the formulation of generic mathematical optimization models that could be solved using mathematical programming techniques dependent on input data. An illustrative example demonstrates the validity of the concepts. en_US
dc.rights I hereby certify that, if appropriate, I have obtained and attached hereto a written permission statement from the owner(s) of each third party copyrighted matter to be included in my thesis, dis sertation, or project report, allowing distribution as specified below. I certify that the version I submitted is the same as that approved by my advisory committee. I hereby grant to NC State University or its agents the non-exclusive license to archive and make accessible, under the conditions specified below, my thesis, dissertation, or project report in whole or in part in all forms of media, now or hereafter known. I retain all other ownership rights to the copyright of the thesis, dissertation or project report. I also retain the right to use in future works (such as articles or books) all or part of this thesis, dissertation, or project report. en_US
dc.subject infrastructure systems en_US
dc.subject critical infrastructure en_US
dc.title A Decision Framework for Improving Resilience of Civil Infrastructure Systems Considering Effects of Natural Disasters en_US
dc.degree.name MS en_US
dc.degree.level thesis en_US
dc.degree.discipline Operations Research en_US


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