Markov-Based Bridge Deterioration Model in Texas

dc.contributor.advisorWeissmann, José
dc.contributor.authorLiu, Taohsin
dc.contributor.committeeMemberPapagiannakis, A.T.
dc.contributor.committeeMemberDiaz, Manuel
dc.descriptionThis item is available only to currently enrolled UTSA students, faculty or staff. To download, navigate to Log In in the top right-hand corner of this screen, then select Log in with my UTSA ID.
dc.description.abstractIn Bridge Management Systems, bridge Network-level models are used to manage the population of bridges in a certain area. Due to limited funding and the increasing number of aging bridges, a good bridge network-level deterioration prediction methodology is needed. To provide information to managing bridges, the Texas Department of Transportation (TxDOT) has been inspecting bridge condition using discrete bridge elements since the year 2000. The TxDOT historical elemental inspection information was summarized by this thesis on an element by element basis for data spanning inspections from 2000 to 2008. A methodology to estimate the parameters of a Markov chain based bridge deterioration model was then developed and is documented by this thesis. Error minimization routines where also summarized in order to automate the estimation of the Markovian transition matrix parameters for each bridge element in the Texas bridge network. The recommended bridge deterioration modeling procedures in this thesis will support key bridge management decisions for the Texas bridge network, by allowing future development of routines to predict the condition and maintenance needs of the Texas bridge network.
dc.description.departmentCivil and Environmental Engineering
dc.format.extent96 pages
dc.subjectBridge Element Deterioration Curves
dc.subjectMarkov Chain Method
dc.subjectNetwork Level Bridge Condition Prediction
dc.subjectPrediction Average Error
dc.subjectTransition Probability Estimation
dc.subject.classificationCivil engineering
dc.titleMarkov-Based Bridge Deterioration Model in Texas
dcterms.accessRightspq_closed and Environmental Engineering of Texas at San Antonio of Science


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