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Perturbation methods for the estimation of parameter variability in stochastic model updating

Conventional model updating methods have been well developed and are widely used in the industry. However, most of the existing methods are restricted to the assessment of Epistemic (reducible) uncertainties. Funded by the European Union's 6th Framework Project, this paper proposes an efficient probabilistic model updating method based on perturbation theory and validates the results experimentally. The method is capable of taking into account aleatoric (irreducible) uncertainties, such as the accumulated effects of manufacturing tolerances on the natural frequencies of nominally identical structures. This research has led to collaboration with DLR (German Aerospace Centre, http://www.dlr.de ).