Bayesian dynamic mode decomposition for real-time ship motion digital twinning

TL;DR

This paper introduces a Bayesian extension to dynamic mode decomposition for real-time ship motion prediction, enhancing digital twin capabilities by providing accurate, adaptive, and reliable forecasts with uncertainty estimation.

Contribution

It proposes a Bayesian Hankel dynamic mode decomposition method tailored for ship motion nowcasting, enabling adaptive, real-time predictions with uncertainty quantification for digital twins.

Findings

Predictions maintain good accuracy up to five wave encounter periods.

Bayesian formulation improves deterministic forecast accuracy.

Uncertainty estimates correlate with prediction reliability.

Abstract

Digital twins are widely considered enablers of groundbreaking changes in the development, operation, and maintenance of novel generations of products. They are meant to provide reliable and timely predictions to inform decisions along the entire product life cycle. One of their most interesting applications in the naval field is the digital twinning of ship performances in waves, a crucial aspect in design and operation safety. In this paper, a Bayesian extension of the Hankel dynamic mode decomposition method is proposed for ship motion's nowcasting as a prediction tool for naval digital twins. The proposed algorithm meets all the requirements for formulations devoted to digital twinning, being able to adapt the resulting models with the data incoming from the physical system, using a limited amount of data, producing real-time predictions, and estimating their reliability. Results are presented and discussed for the course-keeping of the 5415M model in beam-quartering sea state 7 irregular waves at Fr = 0.33, using data from three different CFD solvers. The results show predictions keeping good accuracy levels up to five wave encounter periods, with the Bayesian formulation improving the deterministic forecasts. In addition, a connection between the predicted uncertainty and prediction accuracy is found.