Uncertainty quantification (UQ) is a notion which has received much interest over the past decade. It involves the extraction of statistical information from a problem with inherent variability, where this variability may stem from a lack of model knowledge or through observational uncertainty. Traditionally, UQ has been a challenging pursuit owing to the lack of efficient methods available. The archetypal UQ method is Monte Carlo theory, however this method possesses a slow convergence rate and is therefore a computational burden. In contrast to Monte Carlo theory, polynomial chaos theory aims to spectrally expand the modelled uncertainty via polynomials of random variables which have deterministic coefficients. Once the spectral expansion has been fully defined, it is possible to obtain statistical properties using simple integration procedures. Although literature has proven polynomial chaos theory to be more efficient than Monte Carlo theory in several contexts, there has been very little effort to experimentally validate polynomial chaos theory. Hence, it is the aim of this paper to perform an experimental validation on an in-house physical T-Tail structure by analysing the first six vibrational modes of this structure, and comparing these against the predicted uncertainty bounds of polynomial chaos theory.
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