| Author | Search for: Lau, Michael1 |
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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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| Conference | ASME 2021 40th International Conference on Ocean, Offshore and Arctic Engineering OMAE2021, June 21-30, 2021, Virtual, Online |
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| Subject | numerical; modeling; review; ice; ships; performance; prediction |
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| Abstract | This paper provides a general review of available models used in the NRC-OCRE (National Research Council – Ocean, Coastal and River Engineering) that could be used to support the assessment of a ship’s performance in ice conditions. The models were separated into three main categories: empirical, numerical and real-time, and reviewed in terms of key strengths and weaknesses. A general overview of the modelling categories and specific models within each category is given. Within each modelling category, specific models were compared to outline the key features of both the independent models and the modelling category itself. A representative model within each category and sub-category was selected and used to present the output for a given scenario. This enabled a demonstration of output capabilities for each modelling category. It also provides the reader with additional information pertaining to the input requirements and validation for the selected models. A discussion of the integration of an ice loading model into an existing ship simulation framework is included. A specific case was reviewed in which a successful integration had occurred and was documented. This allowed for demonstration of a process that could be followed for updating one’s numerical modelling capabilities. Based on this review, guidance was provided in terms of selecting a numerical tool to extend current ship performance modelling capabilities to consider ice operations. Each modelling category and sub-category has a unique set of advantages and disadvantages. These should be considered in detail to ensure that the numerical model(s) selected are optimal in terms of their ability to assess desired scenarios and interface with existing software. |
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| Publication date | 2021-06-21 |
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| Publisher | ASME |
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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 | 6f46906f-2ef2-468c-b08b-a05d692f9e6b |
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| Record created | 2021-07-06 |
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| Record modified | 2021-07-06 |
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