A combined experimental and numerical approach to predict ship resistance and power demand in broken ice

Date

2023-12-11

Supervisor/s

Journal Title

Journal ISSN

Volume Title

Publisher

Elsevier

Department

Type

Article

ISSN

0029-8018
https://doi.org/10.1016/j.oceaneng.2023.116476

Format

Free to read from

Citation

Xue Y, Zhong K, Ni BY, et al., (2024) A combined experimental and numerical approach to predict ship resistance and power demand in broken ice. Ocean Engineering, Volume 292, January 2024, Article Number 116476

Abstract

Despite its remoteness and hostile environmental conditions, the Arctic holds significant shipping lanes, such as the Northern Sea Route (NSR) and the Northwest Passage (NWP). Typically, merchant ships operate along these routes in summer only, when the dominating type of ice is broken ice. A challenge of operating in such ice conditions is that there is no cost- and time-efficient method for predicting the resulting ice resistance, which makes route planning difficult, among others. To address this challenge, we present and analyze two complementary approaches to predict ship resistance in broken ice, of which one is experimental and the other numerical. The experimental approach makes use of a type of non-refrigerated synthetic model ice made of polypropylene, which makes it possible to test how a ship behaves in broken ice using a conventional non-refrigerated towing tank rather than an ice tank. The numerical approach, in turn, is based on the CFD-DEM method and can be used to consider fluid effects, such as the changes in fluid velocity and ship waves, while the ship is moving ahead. Validation calculations against established empirical approaches indicate that both approaches are reasonably accurate.

Description

Software Description

Software Language

Github

Keywords

Ship resistance, Broken ice, Coupled CFD-DEM approach, Model test, Non-refrigerated ice, Emperical formula

DOI

Rights

Attribution 4.0 International

Relationships

Relationships

Supplements

Funder/s

Horizon 2020 (723526)