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dc.contributor.advisorGardoni, Paolo
dc.contributor.advisorBarroso, Luciana
dc.creatorBakhtiary, Esmaeel
dc.date.accessioned2013-10-02T21:27:02Z
dc.date.available2015-05-01T05:57:08Z
dc.date.created2013-05
dc.date.issued2013-01-15
dc.date.submittedMay 2013
dc.identifier.urihttps://hdl.handle.net/1969.1/149244
dc.description.abstractThis thesis presents a probability model to predict the maximum rotation of rocking bodies exposed to seismic excitations given specific earthquake intensity measures. After obtaining the nonlinear equations of motion and clarification of the boundaries applied to a rocking body to avoid sliding, a complete discussion is provided on the estimation of approximate period and equivalent damping ratio for the rocking motion. Thereafter, instead of using an iterative solution, which was previously proven defective, a new approximate technique is developed by finding the best representative ground motion intensities. Suitable transformation and normalization are applied to these intensities, and the Bayesian Updating approach is employed to construct a probability model. The proposed probability model is capable of accurately predicting the maximum rotation of a symmetric rocking block given displacement design spectra, peak ground acceleration, peak ground velocity, and arias intensity of an earthquake. This probabilistic model along with the approximate capacity of rocking blocks are used to estimate the fragility curves for rocking blocks with specific geometrical parameters. At the end, a comprehensive and practical form of fragility curves and numerical examples are provided for design purposes.en
dc.format.mimetypeapplication/pdf
dc.subjectRocking bodiesen
dc.subjectSymmetric blocksen
dc.subjectOverturningen
dc.subjectEarthquake Excitationen
dc.subjectProbability.en
dc.titleProbabilistic Seismic Demand Model and Fragility Estimates for Symmetric Rigid Blocks Subject to Rocking Motionsen
dc.typeThesisen
thesis.degree.departmentCivil Engineeringen
thesis.degree.disciplineCivil Engineeringen
thesis.degree.grantorTexas A&M Universityen
thesis.degree.nameMaster of Scienceen
thesis.degree.levelMastersen
dc.contributor.committeeMemberSherman, Michael
dc.type.materialtexten
dc.date.updated2013-10-02T21:27:02Z
local.embargo.terms2015-05-01


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