Updating models and their uncertainties

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Boston: Computational Mechanics Publications, September 1991, p.Model updating procedures are applied in order to improve the matching between experimental data and corresponding model output. improved, finite element (FE) model can be used for more reliable predictions of the structural performance in the target mechanical environment.A new sampling method of the transitional Markov chain Monte Carlo is incorporated with the structure’s finite element model for implementing the approach to damage identification of truss structures.This method can not only draw samples which approximate the updated probability distributions of uncertain model parameters but also provide model evidence that quantify probabilities of uncertain model classes.► The study focuses on the field of Bayesian model updating.► The investigated model uncertainties consist of not considered nonlinearities.The proposed probabilistic framework and its applicability for addressing joint uncertainties are illustrated and examined with an application example.

The precision of the parameter estimates of the optimal structural models, as well as the precision of the optimal prediction-error parameters, can be examined. (2012) Stochastic Models of Uncertainties in Computational Structural Dynamics and Structural Acoustics. Several approaches have been proposed for taking model uncertainties into consideration, where the focus of this manuscript will be set on the updating procedure within the Bayesian statistical framework.The problem of updating a structural model and its associated uncertainties by utilizing structural response data is addressed.Using a Bayesian probabilistic formulation, 6the updated “posterior” probability distribution of the uncertain parameters is obtained and it is found that for a large number of data points it is very peaked at some “optimal” values of the parameters.

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