An interpolation-based parametric reduced order model combined with component mode synthesis

This paper presents an efficient interpolation-based parametric reduced order model with component mode synthesis. The off-line sampling of a large-scale structural dynamic system containing many parameters requires many computations to investigate the parameter-dependency of a dynamical system. Therefore, we introduce a dynamic substructuring scheme to execute off-line sampling in the subdomain level. In addition, we suggest discriminating the interpolation of the subsystem depending on the characteristics of each substructural mode. We synthesize the substructures, and we then construct a two-level, semi-parametrized ROM by reducing the degrees of freedom of the interface in the on-line stage. We then demonstrate the efficiency and accuracy of the present method by computing the relative eigenvalue errors and the transient responses of the system with random values for the parameters, and we conduct the design optimization of large-scale systems under dynamic loading conditions. A comparison of the present method with the full order model and a conventional reduced order model indicates that the present method is useful in carrying out an efficient analysis and design optimization for various large-scale structural dynamic systems.