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Dynamic Analysis of Levee Infrastructure Failure Risk: A Framework for Enhanced Critical Infrastructure Management

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dc.contributor.authorLam, Juan Carlosen
dc.contributor.committeechairMartin, James R. IIen
dc.contributor.committeememberSinha, Sunil K.en
dc.contributor.committeememberde la Garza, Jesus M.en
dc.contributor.departmentCivil Engineeringen
dc.date.accessioned2014-03-14T21:37:48Zen
dc.date.adate2012-06-18en
dc.date.available2014-03-14T21:37:48Zen
dc.date.issued2012-05-29en
dc.date.rdate2012-06-18en
dc.date.sdate2012-06-10en
dc.description.abstractCurrent models that assess infrastructure failure risk are "linear," and therefore, only consider the direct influence attributed to each factor that defines risk. These models do not consider the undeniable relationships that exist among these parameters. In reality, factors that define risk are interdependent and influence each other in a "non-linear" fashion through feedback effects. Current infrastructure failure risk assessment models are also static, and do not allow infrastructure managers and decision makers to evaluate the impacts over time, especially the long-term impact of risk mitigation actions. Factors that define infrastructure failure risk are in constant change. In a strategic manner, this research proposes a new risk-based infrastructure management framework and supporting system, Risk-Based Dynamic Infrastructure Management System (RiskDIMS), which moves from linear to non-linear risk assessment by applying systems engineering methods and analogs developed to address non-linear complex problems. The approach suggests dynamically integrating principal factors that define infrastructure failure risk using a unique platform that leverages Geospatial Information System services and extensions in an unprecedented manner. RiskDIMS is expected to produce results that are often counterintuitive and unexpected, but aligned to our complex reality, suggesting that the combination of geospatial and temporal analyses is required for sustainable risk-based decision making. To better illustrate the value added of temporal analysis in risk assessment, this study also develops and implements a non-linear dynamic model to simulate the behavior over time of infrastructure failure risk associated with an existing network of levees in New Orleans due to diverse infrastructure management investments. Although, the framework and RiskDIMS are discussed here in the context of levees, the concept applies to other critical infrastructure assets and systems. This research aims to become the foundation for future risk analysis system implementation.en
dc.description.degreeMaster of Scienceen
dc.identifier.otheretd-06102012-172831en
dc.identifier.sourceurlhttp://scholar.lib.vt.edu/theses/available/etd-06102012-172831/en
dc.identifier.urihttp://hdl.handle.net/10919/43106en
dc.publisherVirginia Techen
dc.relation.haspartLam_JC_T_2012.pdfen
dc.rightsIn Copyrighten
dc.rights.urihttp://rightsstatements.org/vocab/InC/1.0/en
dc.subjectsystems engineeringen
dc.subjectsystem of systemsen
dc.subjectsystem dynamicsen
dc.subjectgeospatial analysisen
dc.subjectgeographic information systemen
dc.subjectcloud computingen
dc.subjectservice-oriented architectureen
dc.subjectMarkov chainsen
dc.subjectinfrastructure managementen
dc.subjectdecision makingen
dc.subjectinfrastructure failureen
dc.subjectrisken
dc.subjectleveesen
dc.subjectflood protectionen
dc.subjectcritical infrastructureen
dc.titleDynamic Analysis of Levee Infrastructure Failure Risk: A Framework for Enhanced Critical Infrastructure Managementen
dc.typeThesisen
thesis.degree.disciplineCivil Engineeringen
thesis.degree.grantorVirginia Polytechnic Institute and State Universityen
thesis.degree.levelmastersen
thesis.degree.nameMaster of Scienceen

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