Analyzing flexural strength data of ice: how useful is explainable machine learning?
The climate crisis results in a rapid sea ice decline, making shipping routes accessible for longer durations throughout the year and therefore increasing maritime traffic. At the same time, ice-structure interaction is known to cause damage to ships and structures. In this context, the flexural str...
| Main Authors: | , , , |
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| Format: | Conference Object |
| Language: | English |
| Published: |
American Society of Mechanical Engineers
2022
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| Subjects: | |
| Online Access: | http://hdl.handle.net/11420/14178 |
| _version_ | 1835009638180847616 |
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| author | Buil, Patrik Kellner, Leon Ehlers, Sören von Bock und Polach, Rüdiger Ulrich Franz |
| author_facet | Buil, Patrik Kellner, Leon Ehlers, Sören von Bock und Polach, Rüdiger Ulrich Franz |
| author_sort | Buil, Patrik |
| collection | Unknown |
| description | The climate crisis results in a rapid sea ice decline, making shipping routes accessible for longer durations throughout the year and therefore increasing maritime traffic. At the same time, ice-structure interaction is known to cause damage to ships and structures. In this context, the flexural strength is a key property of the ice. It is also an important factor in the process of the formation of ice ridges which then act as obstacles to marine transit. |
| format | Conference Object |
| genre | Arctic Sea ice |
| genre_facet | Arctic Sea ice |
| id | fttuhamburg:oai:tore.tuhh.de:11420/14178 |
| institution | Open Polar |
| language | English |
| op_collection_id | fttuhamburg |
| op_relation | Proceedings of the International Conference on Offshore Mechanics and Arctic Engineering - OMAE ASME 2022 41st International Conference on Ocean, Offshore and Arctic Engineering, OMAE 2022 9780791885918 http://hdl.handle.net/11420/14178 |
| publishDate | 2022 |
| publisher | American Society of Mechanical Engineers |
| record_format | openpolar |
| spelling | fttuhamburg:oai:tore.tuhh.de:11420/14178 2025-06-15T14:16:02+00:00 Analyzing flexural strength data of ice: how useful is explainable machine learning? Buil, Patrik Kellner, Leon Ehlers, Sören von Bock und Polach, Rüdiger Ulrich Franz 2022-06 http://hdl.handle.net/11420/14178 en eng American Society of Mechanical Engineers Proceedings of the International Conference on Offshore Mechanics and Arctic Engineering - OMAE ASME 2022 41st International Conference on Ocean, Offshore and Arctic Engineering, OMAE 2022 9780791885918 http://hdl.handle.net/11420/14178 Data analysis Explainable ai Flexural strength Ice mechanics Machine learning Material modeling 6: Technology::600: Technology Conference Paper Other 2022 fttuhamburg 2025-05-16T03:52:31Z The climate crisis results in a rapid sea ice decline, making shipping routes accessible for longer durations throughout the year and therefore increasing maritime traffic. At the same time, ice-structure interaction is known to cause damage to ships and structures. In this context, the flexural strength is a key property of the ice. It is also an important factor in the process of the formation of ice ridges which then act as obstacles to marine transit. Conference Object Arctic Sea ice Unknown |
| spellingShingle | Data analysis Explainable ai Flexural strength Ice mechanics Machine learning Material modeling 6: Technology::600: Technology Buil, Patrik Kellner, Leon Ehlers, Sören von Bock und Polach, Rüdiger Ulrich Franz Analyzing flexural strength data of ice: how useful is explainable machine learning? |
| title | Analyzing flexural strength data of ice: how useful is explainable machine learning? |
| title_full | Analyzing flexural strength data of ice: how useful is explainable machine learning? |
| title_fullStr | Analyzing flexural strength data of ice: how useful is explainable machine learning? |
| title_full_unstemmed | Analyzing flexural strength data of ice: how useful is explainable machine learning? |
| title_short | Analyzing flexural strength data of ice: how useful is explainable machine learning? |
| title_sort | analyzing flexural strength data of ice: how useful is explainable machine learning? |
| topic | Data analysis Explainable ai Flexural strength Ice mechanics Machine learning Material modeling 6: Technology::600: Technology |
| topic_facet | Data analysis Explainable ai Flexural strength Ice mechanics Machine learning Material modeling 6: Technology::600: Technology |
| url | http://hdl.handle.net/11420/14178 |