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This is a challenging task since a large number of candidate parametrizations are available in any model updating problem.
It establishes a perturbation bound of a generalized centrosymmetric model updating problem with spectra constraints.
However, the model updating problem is an inverse problem prone to ill-posedness and ill-conditioning.
However, the model updating problem is often ill-posed with more unknown parameters than available data, such that parameters cannot be uniquely inferred from the data.
It is more important that, some numerical stability analysis on the model updating problem is given combining with numerical experiments.
By MCMC, the same algorithm can be used no matter the model updating problem is locally identifiable or not.
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The new method removes the restriction of modelling error magnitude being of second order in Euclidean norm as compared with that of system matrices, thereby making it a truly general method applicable to most practical model updating problems.
In the third phase of the study, the CLM method is compared with other local optimization methods such as the Levenberg Marquardt algorithm, Sequential Quadratic Programming and Gauss Newton methods and the results show that the CLM algorithm gives better results in FE model updating problems compared to the above-mentioned local optimization methods.
A numerical example of a simply supported beam and a practical example of a vehicle brake disc show that the SSM can provide higher speed and precision in FE model updating for engineering problems than traditional RSM.
Finite element model updating is an optimization problem to identify and correct uncertain modeling parameters.
Structural model updating is an optimisation problem where parameters that minimise the errors between the model and the actual structure are sought.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com