Bayesian inference to damping identification of fiber-reinforced composites from experimental modal data

For stochastic vibration analysis of the composite plate in-situ stochastic data of the elastic parameters and damping loss factors are essential. Deterministic values of the elastic and damping parameters of the composite plates can be identify using various optimization technique. In recent decades various stochastic inverse identification procedures are shown to evaluate the in-situ stochastic parameters of the elastic constants of the composite plate. However, identification of the damping loss factor of the composite plate has received less attention. A stochastic Bayesian inverse identification technique is used here to evaluate the in-situ uncertainty of the damping loss factors of the glass-epoxy composite plate. Experimentally evaluated first 4 modal damping ratio of the glass-epoxy composite plate are incorporated in Bayesian inverse inference formulation through likelihood function. Novelty of the study lies in the development Bayesian inverse formulation considering modal damping response to identify the stochastic damping loss factors of the glass-epoxy composite plate.