Efficient characterization of the random eigenvalue problem in a polynomial chaos decomposition

136 citations recorded by the source corpus.

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

Arbitrary polynomial chaos expansion method for uncertainty quantification and global sensitivity analysis in structural dynamics (2020, methodology): “this research direction, and a broad spectrum of UQ methods have been developed such as 58 stochastic finite element method [6, 7], perturbation method [8, 9], interval analysis [10-13], 59 surrogate modeling techniques [14-21], and Monte Carlo simulation (MCS) [1, 22].”
Model order reduction based on proper generalized decomposition for the propagation of uncertainties in structural dynamics (2012, unknown): “…use very ﬁne approximation spaces for the accurate representation of this response (or eventually to use enriched polynomial approximation spaces [9, 11, 26]), which make classical spectral stochastic approaches ineﬃcient for the computation of the frequency response over a whole frequency band,…”