Parcourir par sujet "Stochastic simulation algorithms"
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Bayesian Hierarchical Models for Uncertainty Quantification in Structural Dynamics
(2014)The Bayesian framework for hierarchical modeling is applied to quantify uncertainties, arising mainly due to manufacturing variability, for a group of identical structural components. Parameterized Gaussian models of ... -
Bayesian uncertainty quantification and propagation in nonlinear structural dynamics
(2013)A Bayesian uncertainty quantification and propagation (UQ&P) framework is presented for identifying nonlinear models of dynamic systems using vibration measurements of their components. The measurements are taken to be ... -
Efficient techniques for bayesian inverse modeling of large-order computational models
(2013)Bayesian tools for inverse modeling are based on asymptotic approximations and Stochastic Simulation Algorithms (SSA). Such tools require a number of moderate to large number of system re-analyses. For large-order numerical ... -
Uncertainty calibration of large-order models of bridges using ambient vibration measurements
(2014)A computational efficient Bayesian inference framework based on stochastic simulation algorithms is presented for calibrating the parameters of large-order linear finite element (FE) models of bridges. The effectiveness ...