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dc.contributor.authorSaeidpour, Arash
dc.date.accessioned2018-03-17T04:30:14Z
dc.date.available2018-03-17T04:30:14Z
dc.date.issued2017-08
dc.identifier.othersaeidpour_arash_201708_phd
dc.identifier.urihttp://purl.galileo.usg.edu/uga_etd/saeidpour_arash_201708_phd
dc.identifier.urihttp://hdl.handle.net/10724/37488
dc.description.abstractNumerous bridges along the Gulf Coast of the United States sustained significant damage in the recent hurricanes. The overall cost to repair and rebuild damaged bridges by hurricane Katrina alone was estimated over $1 billion. Besides physical damage, any loss of functionality in transportation networks will disrupt the post-disaster recovery operations in the near term and will lead to slow economic and social development of affected regions in the long run. Reliability of the transportation infrastructure during hurricane events is mainly dependent on the bridges as they are most vulnerable nodes of the network. A comprehensive hurricane risk analysis of bridges enables the owners to assign their resources to the most critical bridges in the inventory through a risk-informed decision making process and minimize the potential loss. In the present dissertation, a probabilistic framework for fragility analysis and risk assessment of coastal bridges vulnerable to hurricanes is proposed. Various sources of uncertainty associated with hurricane hazard and bridge response are identified and incorporated in the fragility analysis. Two different methods for conducting fragility analysis of bridges are proposed. In the first method, a detailed procedure for deriving parameterized fragility functions, by means of surrogate models, is introduced for bridges subjected to hurricane forces. Several surrogate models are compared in terms of prediction accuracy, and the Random Forest method is shown to yield the most accurate results. A parametric finite element model for nonlinear dynamic analysis of bridges is developed in OpenSees and is used to obtain the response of bridge samples under hypothetical hurricane scenarios. The second method is a computationally efficient single hazard Intensity Measure (IM)-based risk assessment approach developed for simply supported bridges. The novelty of the proposed method includes the consideration of uncertainties in extreme wave height and wave period, by means of a wave spectral density distribution, in the calculation of wave forces. The proposed hurricane risk analysis method was successfully applied to approximately 500 coastal bridges located in the state of Georgia, U.S.A.
dc.languageeng
dc.publisheruga
dc.rightsOn Campus Only Until 2019-08-01
dc.subjectFragility
dc.subjectRisk
dc.subjectReliability
dc.subjectCatastrophe
dc.subjectHurricane
dc.subjectMachine Learning
dc.subjectMetamodel
dc.subjectRandom Forest
dc.subjectWave Spectra
dc.titleFragility analysis of coastal bridges susceptible to hurricanes incorporating uncertainties in extreme wave parameters by means of wave spectra and enhancement of vulnerability assessment methodologies
dc.typeDissertation
dc.description.degreePhD
dc.description.departmentEngineering
dc.description.majorEngineering
dc.description.advisorMi Geum Chorzepa
dc.description.committeeMi Geum Chorzepa
dc.description.committeeStephan Durham
dc.description.committeeJason Christian


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