A NEW GIBBS SAMPLING BASED BAYESIAN MODEL UPDATING APPROACH USING MODAL DATA FROM MULTIPLE SETUPS

2015 ◽  
Vol 5 (4) ◽  
pp. 361-374 ◽  
Author(s):  
Sahil Bansal
Keyword(s):  
Gibbs Sampling ◽  
Bayesian Model ◽  
Model Updating ◽  
Modal Data

Comparison of Direct and Iterative Methods for Model Updating of a Curved Cable-stayed Bridge Using Experimental Modal Data

2016 ◽  
Vol 106 (8) ◽  
pp. 538-545 ◽  
Author(s):  
Guanzhe Fa ◽  
Enrico Mazzarolo ◽  
Leqia He ◽  
Bruno Briseghella ◽  
Luigi Fenu ◽  
...  
Keyword(s):  
Iterative Methods ◽  
Model Updating ◽  
Modal Data ◽  
Cable Stayed Bridge

Validating and Updating Finite Element Models Using Experimental Measurements of Dynamics

1990 ◽  
Vol 204 (1) ◽  
pp. 45-50
Author(s):  
C F McCulloch ◽  
P Vanhonacker ◽  
E Dascotte
Keyword(s):  
Finite Element ◽  
Structural Dynamics ◽  
Model Updating ◽  
Measured Data ◽  
Physical Parameters ◽  
Experimental Measurements ◽  
Finite Element Models ◽  
Data Sets ◽  
Modal Data ◽  
Modelling Assumptions

A method is proposed for updating finite element models of structural dynamics using the results of experimental modal analysis, based on the sensitivities to changes in physical parameters. The method avoids many of the problems of incompatibility and inconsistency between the experimental and analytical modal data sets and enables the user to express confidence in measured data and modelling assumptions, allowing flexible but automated model updating.

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