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- W566550888 abstract "The problem of updating a structural model and its associated uncertamt1es by utilizingstructural response data is addressed using a Bayesian statistical framework which canhandle the inherent ill-conditioning and possible nonuniqueness in model updatingapplications. The model updating is done by using Bayes theorem to update the probabilitymodel for the parameters of the structural model set and the parameters of the prediction-errorprobability model set. From this perspective, model updating is viewed as part ofrobust analysis where modeling uncertainties are explicitly addressed in the analysis of asystem. The exact expressions for updated model predictions are given by multi-dimensionalintegrals whose direct evaluation is usually computationally prohibitive. Asymptoticapproximations are presented for both identifiable and unidentifiable model sets. Anillustrative example is given using robust and updated reliabilities to achieve a moreeffective optimal design of a tuned-mass damper for a simple bridge system." @default.
- W566550888 created "2016-06-24" @default.
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- W566550888 date "1998-06-01" @default.
- W566550888 modified "2023-09-23" @default.
- W566550888 title "A Bayesian Probability Approach to Updating Structural Models and Their Uncertainties" @default.
- W566550888 hasPublicationYear "1998" @default.
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