Bayesian Experimental Design of Cyber-Physical Tests for Hydrodynamic Model Calibration

Abstract

An application of cyber-physical testing to the empirical estimation of difference-frequency quadratic transfer functions is presented. As an alternative to today's procedure based on hydrodynamic tests with broad-banded or realistic (e.g., JONSWAP) wave spectra, tests in bichromatic waves are considered. The laboratory setup is the one developed by Sauder \& Tahchiev (2020) that enables magnifying the sensitivity of the floater response to the low-frequency wave loading by adjusting the stiffness and damping parameters of a virtual soft mooring system. Bayesian experimental design is proposed to optimize the selection of the control variables (frequencies in the bichromatic wave and properties of the virtual mooring system) for a batch of cyber-physical tests. The experimental design algorithm is based on the recent work of Huan \& Marzouk (2013). In a virtual yet realistic case study using an uncertain parametric quadratic transfer function, we demonstrate how the uncertainty of its describing parameters and other calibration parameters (low-frequency added mass and hydrodynamic damping) can be reduced. Results indicate that the proposed procedure has the potential for reducing experimental cost for calibration of hydrodynamic models.

A cross validation‐Voronoi and entropy based adaptive sampling strategy for uncertainty quantification through hybrid simulation

“…A nonlinear 2 degrees of freedom (2‐DOF) series system is considered as shown in Figure 11. A similar system was also used by Abbiati & Marelli 38 in a numerical benchmark study for adaptive Kriging‐based hybrid simulation for structural reliability analysis. The spring connecting the two masses is assumed to be the experimental substructure and has inelastic behavior, while the spring connecting the two masses to the fixed support is linear elastic.…”