In this paper, dynamic material constants of 2-parameter Mooney-Rivlin model for elastomeric components are identified in broad frequency range. To consider more practical case, an elastomeric engine mount is used as the case study. Finite element model updating technique using Radial Basis Function neural networks is implemented to predict the dynamic material constants. Material constants of 2-parameter Mooney-Rivlin model are obtained by curve fitting on uni-axial stress-strain curve. The initial estimations of the material constants are achieved by using uni-axial tension test data. To ensure of the consistency of dynamic response of a real component, frequency response function of three similar engine mounts are extracted from experimental modal data and average of them used in the procedure. The results showed that this technique can successfully predict dynamic material constants of Mooney-Rivlin model for elastomeric components.
Mooney-Rivlin model; Dynamic Material Constants; Frequency response function; Radial Basis Function Neural Networks; Elastomeric components
