Assessing structural reliability using real-time hybrid sub-structuring

Abstract

While numerical simulations can be used to predict the dynamic performance of structural systems, there are some instances where the dynamical behaviour and uncertainties of specific system components may be difficult to accurately model. In these instances, structural reliability assessments may be conducted by employing the cyber-physical real-time hybrid sub-structuring (RTHS) test method. In this approach, a numerical model of a larger structural system, incorporating uncertainty in specific parameters, is coupled with a physical test specimen of a system component to fully capture system-level dynamic interactions and facilitate uncertainty propagation. This paper specifically details a study performed to experimentally validate the previously proposed adaptive Kriging-Hybrid simulation (AK-HS) structural reliability method. The AK-HS method combines Kriging metamodeling, an adaptive learning algorithm, Monte Carlo simulation, and RTHS testing to iteratively estimate a structural system's probability of failure given random parameters in the numerical model. The method is validated with a series of bench-scale RTHS tests on a viscous damper connecting two adjacent 6-degree-of-freedom rigid body structures. The AK-HS method is shown to accurately predict probabilities of failure for systems with up to 24 random variables using a reasonable number of RTHS tests.