A Probabilistic Model for Estimating Ship Performance in Ice Conditions
Loading...
Access rights
openAccess
publishedVersion
URL
Journal Title
Journal ISSN
Volume Title
A4 Artikkeli konferenssijulkaisussa
This publication is imported from Aalto University research portal.
View publication in the Research portal (opens in new window)
View/Open full text file from the Research portal (opens in new window)
Other link related to publication (opens in new window)
View publication in the Research portal (opens in new window)
View/Open full text file from the Research portal (opens in new window)
Other link related to publication (opens in new window)
Unless otherwise stated, all rights belong to the author. You may download, display and print this publication for Your own personal use. Commercial use is prohibited.
Date
Major/Subject
Mcode
Degree programme
Language
en
Pages
11
Series
Proceedings of the 28th International Conference on Port and Ocean Engineering under Arctic Conditions, Proceedings of the International Conference on Port and Ocean Engineering under Arctic Conditions, POAC
Abstract
During the winter months, ice conditions can significantly impact ship performance, posing challenges for efficient navigation. Traditionally, deterministic models, such as semi-empirical approaches, have been used to estimate ship performance in ice, resulting in non-linear dependencies between ship's speed (v) and ice thickness (h), i.e. so-called h-v curve. However, these models often fall short in capturing the inherent variability and uncertainty associated with complex ice conditions. Given the complex and unpredictable nature of ice, there is a motivation to adopt probabilistic modeling techniques that can account for these uncertainties. As a preliminary exploration, this study models ship transit speed in ice using the h-v curve guided Gaussian Process Regression (HGP), providing a probabilistic relationship between ice conditions and ship speed. The proposed model is applied to independent navigation trips of merchant ships, and the outputs include the mean transit speed and the uncertainty of each estimation. Mean absolute error and the root mean squared error are used to evaluate the effectiveness of this approach. The output of the HGP is compared with that of the standard Gaussian Process model and the recorded ship speed, highlighting the need for combining the physics-based guidance with the data-driven insights for better supporting ship performance analysis in ice. The proposed approach could be further developed e.g., by refining the integration of physics-based guidance with data-driven approach, incorporating additional variables to represent ship maneuvers, and integrating observed ice data to mitigate inherent data uncertainties.Description
Publisher Copyright: © 2025 Lulea University of Technology. All rights reserved.
Other note
Citation
Liu, C, Arif, A, Kujala, P, Suominen, M & Musharraf, M 2025, A Probabilistic Model for Estimating Ship Performance in Ice Conditions. in Proceedings of the 28th International Conference on Port and Ocean Engineering under Arctic Conditions. Proceedings of the International Conference on Port and Ocean Engineering under Arctic Conditions, POAC, Curran Associates Inc., International Conference on Port and Ocean Engineering under Arctic Conditions, St. John's, Newfoundland and Labrador, Canada, 13/07/2025.