Davide Raviolo
A Bayesian optimization approach for finite element model updating.
Rel. Rosario Ceravolo, Luca Zanotti Fragonara, Marco Civera. Politecnico di Torino, Corso di laurea magistrale in Ingegneria Civile, 2021
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Abstract
Model updating aims at estimating unknown system properties, that are described by parameters in numerical models, when actual observations of the physical system response are available. Typically, besides plain model calibration purposes, model updating procedures are employed for non-destructive damage assessment of structures. In this framework, damage can be located and quantified by updating stiffness-related parameters: a local reduction of stiffness denotes localized structural damage. When iterative model updating methods that make use of a cost function are concerned, three major critical aspects may compromise the success of the whole updating procedure: the FE model validity, the reliability of the experimental data and the complexity of the optimization problem at the computational level.
Usually, the insidious nature of the model updating problem along with the use of sophisticated FE models generate expensive and non-convex cost functions which minimization is a non-trivial task
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