Ice Model Tests for Dynamic Positioning Vessel in Managed Ice

Wang, Jungyong; Sayeed, Tanvir; Millan, D.; Gash, Robert; Islam, Mohammed; Millan, James

doi:10.4043/27430-ms

Cited by 7 publications

(4 citation statements)

References 6 publications

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“…Other research into modeling a DP vessel in ice include Zhou, 30 Nguyen et al, 31 Lubbad and Løset, 32 Sayed et al, 33 and Millan and Wang. 34 These works are more like Metrikin and colleagues 18,26,27 and Tannuri et al 28 in that they present details of the various numerical models related to DP in ice simulations, rather than a platform like DPIVP that could use and validate such models. That's not to say some DP in ice simulations do not have similar platforms to DPIVP, but to the authors best knowledge, no description of the development of such a software platform has been presented before.…”

Section: Introductionmentioning

confidence: 99%

DP in ice environments—development of a dynamic positioning in ice validation platform (DPIVP)

et al. 2023

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This paper presents the development of a dynamic positioning in ice validation platform (DPIVP) which is part of a larger research project aimed at developing dynamic positioning (DP) system technologies for ice-rich environments. One outcome is simulation software to aid research in this area. The DPIVP software was designed to realistically simulate the dynamics of ice-structure interactions for real-time applications and to validate components common to DP in ice simulations. The software consists of many components which the DPIVP ties together as a unified system. All components have well-defined interfaces. Many of them are also distributed, allowing execution on separate computers and/or CPUs which helps ensure real-time operation. These two characteristics also decreases coupling and encourages a more modular design with the benefit of easily substituting alternative component implementations without reprogramming the DPIVP. Alternate implementations are useful for conducting research in specific DP in ice areas without substantially changing the system, such as alternative ice force models, DP control algorithms, vessel models, 3D and 2D visualization, environment models, and data acquisition systems. The integrated system was tested and evaluated using unit testing, integration testing, and system testing. The completed system was also validated using test cases that match physical model tests; the results compared favorably. Although the software has some limitations, for example, validated ice-force models being limited to two vessels, and thus lacks the generality we wish, the end result is a working prototype that satisfies the research requirements and provides an architecture and framework for future development.

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Section: Introductionmentioning

confidence: 99%

DP in ice environments—development of a dynamic positioning in ice validation platform (DPIVP)

et al. 2023

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“…Tests performed in ice tanks can also generate good data to evaluate the ice load on floaters [5]. Representative examples of such tests are the drillshiprelated experiments carried out as part of the international joint research project DYPIC (DYnamic Positioning in Ice Condition) [6,7] and the model tests performed by the National Research Council (NRC) of Canada [8,9]. However, such ice tank tests are still costly, and they have limitations in reflecting other environmental loads, such as wind, currents, and waves.…”

Section: Introductionmentioning

confidence: 99%

Untitled

2023

Brodogradnja

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To evaluate the time-domain positioning performance of arctic marine structures, it is necessary to generate an ice load appropriate for the current position and heading of the structure. The position and orientation angle of a floating body continuously change with time. Therefore, an ice load is required for any attitude in the time-domain simulation. In this study, we present a fundamental technique for analyzing ice loads in the frequency domain based on data measured at various angles in the ice-water tank experiment. We perform spectral analysis instead of general FFT to analyze the ice load, which has the characteristics of a random signal. To generate the necessary ice load in the time domain, we must first interpolate the measured data in the frequency domain. Using the Blackman-Tukey method, we estimate the spectrum for the measured data, then process the data to generate the training set required for machine learning. Based on the results, we perform regression analysis by applying four representative techniques, including linear regression, random forest, or neural network, and compare the results with MSE. The deep neural network method performed best, but we provide further discussion for each model.

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“…As a part of the project entitled dynamic positioning in ice condition, i.e., the DYPIC project, a model test was conducted for an Arctic drilling vessel in 2014 [8,9]. In addition, Canada's National Research Council (NRC) also conducted an ice tank test for a drilling vessel [10]. However, these on-site tests and ice tank tests are expensive and have limitations when it comes to changing the test conditions.…”

Section: Introductionmentioning

confidence: 99%

A Study on the Effectiveness of the Heading Control on the Mooring Line Tension and Position Offset for an Arctic Floating Structure under Complex Environmental Loads

Kang

Lee

Lim

et al. 2021

JMSE

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Even though interest in developing the Arctic region is increasing continuously, the standard procedure to be used to analyze the station-keeping performance of a floater considering ice loads has not been established yet. In this paper, the effectiveness of heading control with a dynamic positioning system is analyzed to evaluate the improvement of the performance of the station-keeping system in the ice conditions. Complex environmental loads with ice-induced forces were generated and applied to a ship type floater with dynamic positioning and mooring systems. Three-hour time-domain simulations were conducted for the two different station-keeping systems with mooring only and mooring with a dynamic positioning system. Position offsets and mooring line tensions for the two scenarios were compared with maximum values and most probable maxima (MPM) values. The results of the simulation showed that the heading control can reduce 8.2% of MPM values for the mooring lines and improve the station-keeping performance by about 16.3%. The validity of the station-keeping system that was designed was confirmed, and it is expected that the specification of mooring lines can be relaxed with the heading control.

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Ice Model Tests for Dynamic Positioning Vessel in Managed Ice

Cited by 7 publications

References 6 publications

DP in ice environments—development of a dynamic positioning in ice validation platform (DPIVP)

DP in ice environments—development of a dynamic positioning in ice validation platform (DPIVP)

Untitled

A Study on the Effectiveness of the Heading Control on the Mooring Line Tension and Position Offset for an Arctic Floating Structure under Complex Environmental Loads

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