| DOI | Resolve DOI: https://doi.org/10.1016/j.oceaneng.2022.112939 |
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| Author | Search for: Islam, Mohammed1ORCID identifier: https://orcid.org/0000-0002-2129-5333; Search for: Mills, Jason1ORCID identifier: https://orcid.org/0000-0002-3040-9048; Search for: Gash, Robert1; Search for: Pearson, Wayne1ORCID identifier: https://orcid.org/0000-0003-2163-0071 |
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| Affiliation | - National Research Council of Canada. Ocean, Coastal and River Engineering
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| Format | Text, Article |
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| Abstract | Empirical models based on measurements are often preferred over high-fidelity numerical models when real-time predictions of broken ice-field actions on ships and floating offshore platforms are needed. This paper presents the methodologies and validations of a novel numerical model based on empirical-statistical techniques for predicting dynamically positioned (DP) vessels and ice-field interactions. The authors developed multiple regression models for predicting the time-averaged and average peaks of thruster forces and yawing moment of the DP vessel due to managed ice actions. Monte Carlo Simulations and other empirical techniques were then developed to predict the time series of the ice forces and moment on the DP vessel in managed ice scenarios. The authors then carried out model validations for several ice-field and vessel operating scenarios. The model showed reasonable accuracy in predicting the effects of several ice-field parameters on the forces and moments of two DP-controlled vessels. Subsequently, integration of the model into a DP-in-ice validation platform is offered, which can simulate and optimize the performance of a DP-controlled vessel in ice-infested water. Finally, the uniqueness and limitations of the models are discussed, and recommendations for future work are provided. |
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| Publication date | 2022-11-02 |
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| Publisher | Elsevier |
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| In | |
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| Language | English |
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| Peer reviewed | Yes |
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| Export citation | Export as RIS |
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| Report a correction | Report a correction (opens in a new tab) |
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| Record identifier | 160f12ce-65e1-4f54-8237-a114467a189e |
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| Record created | 2025-04-25 |
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| Record modified | 2025-04-28 |
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