In this paper we introduce a novel modeling framework aimed to develop a meta-model estimating the expected response of a selected passenger ship prior to initiating evasive maneuvers, and taking into account the stochastic nature of irregular waves. By design, the meta-model should allow for two modes of operation, namely predictive and diagnostic, thus employing forward and backward reasoning. The predictive application could be used to assess the probability of the response variables (e.g. ship motions) for given operational or environmental parameters, such as rudder angle, ship speed, wave height, etc. The diagnostic mode could be, in turn, used to figure out how the ship’s operational parameters should be set in the observed environmental conditions to maintain response variables in the desired limits.
Mateusz Gil, Jakub Montewka, Przemysław Krata, Predicting a passenger ship’s response during evasive maneuvers using Bayesian Learning, Reliability Engineering & System Safety, Volume 256, 2025, 110765, ISSN 0951-8320, https://doi.org/10.1016/j.ress.2024.110765