Bayesian posteriors of uncertainty quantification in computational structural dynamics for low-and medium-frequency ranges

•Novel methodology for the identification of stochastic models of uncertainties.•Linear computational structural dynamics for the low-and medium-frequency ranges.•Uncertain system parameters and model uncertainties induced by modeling errors.•Bayesian posteriors of uncertainty quantification in computational structural dynamics.

The paper is devoted to the modeling and identification of uncertainties in computational structural dynamics for low-and medium-frequency ranges. A complete methodology is presented for the identification procedure. The first eigenfrequencies are used to quantify the uncertainties in the low-frequency band while the frequency response functions are used to quantify the uncertainties in the medium-frequency band. The system-parameter uncertainties are taken into account with the parametric probabilistic approach. The model uncertainties are taken into account with the nonparametric probabilistic approach. The posterior stochastic model of system-parameter uncertainties is identified using the Bayes method.