Structural health monitoring condition assessment and seismic vulnerability estimation of highway bridges

dc.contributorGraduate Program in Civil Engineering.
dc.contributor.advisorSoyöz, Serdar.
dc.contributor.authorÇolak, Hüseyin.
dc.date.accessioned2023-03-16T10:51:06Z
dc.date.available2023-03-16T10:51:06Z
dc.date.issued2016.
dc.description.abstractSeismic vulnerability estimation is one of the crucial targets of performance evaluation and risk assessment strategies in structural engineering and it is widely achieved by developing fragility and/or capacity curves using analytical models of structures. Since the accuracy of nite element models and analysis results has a key role in the evaluation of existing structures, this study focuses on two important factors a ecting the accuracy of models and analyses results. The rst one is structural condition and the second factor is the nonlinear modelling of structural elements. Conventional practices of condition assessment rely on visual inspection. However, it is well-known that to have a quick and reliable visual-based assessment is almost impossible due to several limitations such as subjective judgement of a damage and unreachable locations of huge structures. On the other hand, structural health monitoring can revolutionize the way of condition assessment in a rapid and objective way. For this purpose, implementation of vibration-based monitoring and system identi cation of reinforced concrete bridges is presented. An ordinary highway bridge in Istanbul is instrumented with acceleration sensors and vibration measurements are used to calibrate the nite element model of the bridge developed according to design drawings. Afterwards, measurements of a large scale bridge experiment carried out at University of Nevada-Reno is used to validate the proposed condition assessment method by comparing the identi ed sti - ness values with ones calculated using curvature measurements. Moreover, e ects of nonlinear modelling on condition assessment and seismic vulnerability estimation were investigated by nonlinear time history analyses carried out using two hinge models.
dc.format.extent30 cm.
dc.format.pagesxvii, 75 leaves ;
dc.identifier.otherCE 2016 C76
dc.identifier.urihttps://digitalarchive.library.bogazici.edu.tr/handle/123456789/13995
dc.publisherThesis (M.S.) - Bogazici University. Institute for Graduate Studies in Science and Engineering, 2016.
dc.subject.lcshBridges -- Earthquake effects.
dc.titleStructural health monitoring condition assessment and seismic vulnerability estimation of highway bridges

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