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- W2607052913 abstract "Advancements in nonlinear dynamic simulation, seismichazard analysis, and performance-based earthquake engineering areenabling more scientific assessment of structural collapse risk andhow the risk is controlled by building code design requirements.Although current collapse assessment methods carefully account forthe nonlinear response of structures, most of these analyses do notexplicitly capture model uncertainties associated with variabilityin the structural properties and response characteristics ofcomponents. Instead, modeling uncertainties are typicallyconsidered through simplified assumptions and techniques. Thisdissertation focuses on modeling uncertainty in seismic performanceassessment and implications on seismic collapse safety ofstructures. A statistical framework assessing model parametercorrelations from component tests is proposed for characterizingthe modeling parameters that define dynamic response at a componentlevel and the interactions of multiple uncertain components instructural systems. The framework is illustrated using a datasetthat is composed of over two-hundred tests of reinforced concretecolumns. Statistics of the model parameters are establishedincluding the correlation structure of the inelastic modelparameters, both within a component and between differentcomponents. The analyses show that model parameters withinstructural components tend to be only mildly correlated, whereasthere are strong correlations between like parameters of differentcomponents within a building. Uncertainty propagation methods,including Monte-Carlo simulation-based, moment-based and surrogate(response surface and neural network) methods, are assessed forprobabilistic assessment of collapse risk. To reduce computationaldemand of collapse risk assessment, a Bayesian approach is proposedand demonstrated using a reinforced concrete archetype building.The results emphasize the sensitivity of collapse response tomodeling uncertainties and the challenges of balancing ofcomputational efficiency and robust uncertainty characterization.Impacts of modeling uncertainty are evaluated for fragilityfunctions and mean annual exceedance rates for drift limits andcollapse for thirty-three reinforced concrete archetype buildingconfigurations. Modeling uncertainty is shown to have considerableimpacts on collapse risk. Inclusion of modeling uncertainty isshown to increase the mean annual frequency of collapse by about1.7 times, as compared to analyses based on median modelparameters, for a high-seismic site in California. Modelinguncertainty has a smaller effect on drift demands at levels usuallyconsidered in building codes. A novel method is introduced torelate drift demands to collapse safety through a jointdistribution of deformation demand and capacity, taking intoaccount simulated instances of collapse and no-collapse. Thismethod enables linking seismic performance goals specified inbuilding codes to drift limits and other acceptance criteria. Thedistributions of drift demand at…" @default.
- W2607052913 created "2017-04-28" @default.
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- W2607052913 date "2015-01-01" @default.
- W2607052913 modified "2023-09-23" @default.
- W2607052913 title "Seismic reliability assessment of structures incorporatingmodeling uncertainty and implications for seismic collapsesafety" @default.
- W2607052913 hasPublicationYear "2015" @default.
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