Evaluation of selected state-of-the-art methods for ship transit simulation in various ice conditions based on full-scale measurement

Li, Fang; Goerlandt, Floris; Kujala, Pentti; Lehtiranta, Jonni; Lensu, Mikko

doi:10.1016/j.coldregions.2018.03.008

Cited by 32 publications

(13 citation statements)

References 19 publications

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“…Computer simulations of ship performance in such ice fieldsalso known as ship ice transit simulationspresent an important tool for designers of icecapable ships streaming for the most efficient design (von Bock und Polach et al 2015), as well as for the ship operators who need to accurately estimate the ship performance in ice in order to reduce the risk of accidents (Goerlandt et al 2017). The majority of the existing tools for the simulation of ship resistance/speed profile in ice are based on mechanistic approaches, as summarised in Li et al (2018). These can be roughly divided in two groups: (1) simulations using semiempirical methods (e.g.…”

Section: State Of the Artmentioning

confidence: 99%

A machine learning-based method for simulation of ship speed profile in a complex ice field

Milaković

Marouf

et al. 2019

Ships and Offshore Structures

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Computational methods for predicting ship speed profile in a complex ice field have traditionally relied on mechanistic simulations. However, such methods have difficulties capturing the entire complexity of shipice interaction process due to the incomplete understanding of the underlying physical phenomena. Therefore, data-driven approaches have recently gained increased attention in this context. Hence, this paper proposes a concept of a first machine learning-based simulator of ship speed profile in a complex ice field. The developed approach suggests using supervised machine learning to trace a function mapping several ship and ice parameters to the ship acceleration/deceleration between the two adjacent points along the route. The simulator is trained and tested on a dataset obtained from the full-scale tests of an icebreaking ship. The results show high accuracy of the developed method, with an average error of the simulated ship speed against the measured one ranging from 2.6% to 9.4%.

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Section: State Of the Artmentioning

confidence: 99%

A machine learning-based method for simulation of ship speed profile in a complex ice field

Milaković

Marouf

et al. 2019

Ships and Offshore Structures

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“…Compared with the original car-following model proposed by Pipes (1953), ship navigation in ice is more complex, due to the influence of the ice conditions on the vessel dynamics: the presence of ice affects the ship's speed and acceleration, where thicker ice reduces the ships' speed more than thinner (Li et al, 2018). Ice also poses a hazard to the ship hull, where higher speeds correspond to higher ice loads (Kotilainen et al, 2018).…”

Section: Ship Following Model: Process and Icebreaking Resistancementioning

confidence: 99%

“…Breaking this ice is associated with a high icebreaking resistance. There are many studies of ice resistance of ships (Li et al, 2018). In this study, a relatively simple formula is applied for calculating the ice resistance (Cho et al, 2015…”

Section: Figure 3 Schematic Model Of the Multi-ship Following Behavior In Ice Conditionsmentioning

confidence: 99%

“…Most models for ship performance in ice focus on continuous icebreaking in independent navigation, typically focusing on the assessment of ship resistance and speed, and ice loads on the hull (Li et al, 2018). Such models are mostly used for the design of the ship's structure (Su et al, 2011), but can also be applied for operational purposes such as route planning (Guinness et al, 2014).…”

Section: Introductionmentioning

confidence: 99%

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A multi-ship following model for icebreaker convoy operations in ice-covered waters

et al. 2019

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Most vessels cannot safely sail in areas with sea ice. In the Northern Baltic Sea area, the presence of sea ice often requires icebreaking ships to open up ice-covered areas so merchant vessels can proceed to their destinations. In this environment there is an increasing number of ships. With growing transport volumes in sea ice environments, icebreaker operations such as convoys have become increasingly important to ensure navigation safety. This paper proposes a model of multi-ship following for icebreaker convoy operations in continuous icebreaking conditions, using modelling principles from earlier proposed car following models combined with considerations of safe distance and safe speed in ship convoy operations in ice conditions. The model parameters are calibrated with empirical data from actual icebreaker convoy operations, using data from the Automatic Identification System (AIS) and sea ice model data. The model determines ice resistance according to ice thickness, type, and bending strength, and the main dimensions of the icebreaker leading the convoy. The maximum safe navigable speed is used to assess the following ships' ability to sail in sea ice. The multi-ship following simulation results were found to be in good agreement with empirical data. The new proposed model can provide a theoretical reference for icebreaker convoy operations, can have practical use in ship simulators to improve training, and could be useful for traffic modelling and planning purposes.

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“…Although literature and tools which optimise open water routes with respect to general weather can be found in abundance, the number of studies on e-Navigation for ice-covered seas is somewhat limited. Recent examples include Montewka et al (2018a), Krata and Szlapczynska (2018), Montewka et al (2018b) and Li et al (2018). The two most essential objectives that the majority of ice routing tools incorporate are travel efficiency (for example, time) and ship safety.…”

Section: Introductionmentioning

confidence: 99%

Sea Captains’ Views on Automated Ship Route Optimization in Ice-covered Waters

2019

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Safety in ice-covered polar waters can be optimised via the choice of a ship's route. This is of utmost importance for conventional as well as autonomous ships. However, the current state of the art in e-Navigation tools has left two open questions. First, what essential information are these tools still missing, and second, how they are seen by sea captains. In order to address these questions, we organised an ice navigation workshop to systematically collect routing justifications given by and waypoints planned by experienced sea captains that are particularly seasoned in ice navigation. Here, we report the outcome of that workshop. Our key findings include the reasoning and the commentary of the participants in looking for a better and safer route. These comments shed light upon both the official and unofficial code of conduct in open waters and boil down into a list of additional prerequisite information if further steps towards system autonomy are sought. Finally, the expert-planned waypoints are to be published alongside this paper to act as a benchmark for future maritime studies.

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Evaluation of selected state-of-the-art methods for ship transit simulation in various ice conditions based on full-scale measurement

Cited by 32 publications

References 19 publications

A machine learning-based method for simulation of ship speed profile in a complex ice field

A machine learning-based method for simulation of ship speed profile in a complex ice field

A multi-ship following model for icebreaker convoy operations in ice-covered waters

Sea Captains’ Views on Automated Ship Route Optimization in Ice-covered Waters

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