A Bayesian approach for shipboard lifetime wave load spectrum updating

Abstract

Updating design stage loading predictions with in-service measurements is an essential step for predicting the fatigue life of complex structures. This is especially true when the loading process is not statistically stationary. Ships and marine structures are an example of such structures. They are fatigue prone from being subject to alternating wave forces, and can also change their loading environment owing to their mobility. This manuscript proposes a two-level offline lifetime load updating scheme to address updating of non-stationary load processes. First, corrections to hydrodynamic predictions are established in short-term statistically stationary operating cells based upon spectral parameters. A hierarchical Bayesian model interpolates corrections between cells and infers correction factors for cells that are not yet observed. Finally, projected operational profiles of the vessel are used to combine cell predictions into an updated lifetime fatigue load profile. The effectiveness of this process is demonstrated on an example vessel in two case studies.