Identifying Stochastic Frequency Response Functions Using Real-Time Hybrid Substructuring, Principal Component Analysis, and Kriging Metamodeling

Abstract

Real-time hybrid substructuring (RTHS) has previously been shown to be an effective tool to quantify the effect of parametric uncertainties on the response of a structural system. Proposed and implemented in this paper is a method that combines RTHS, Principal Component Analysis, and Kriging to metamodel the frequency response functions of a structure. The proposed method can be used to account for parametric variation in both the numerical and physical substructures. This approach is demonstrated using a series of bench-scale RTHS tests of a magnetorheological (MR) fluid damper used to control a 2 degree-of-freedom mass-spring system. The numerical system spring stiffnesses and the physical current supplied to the MR damper are each treated as uniformly distributed random variables. The RTHS test data is used to train computationally fast metamodels, which can then be used to conduct Monte Carlo simulations to determine distributions of the system response. The proposed methodology is shown to be both efficient and accurate.