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Analyzing flexural strength data of ice: how useful is explainable machine learning?
Publikationstyp
Conference Paper
Date Issued
2022-06
Sprache
English
Article Number
V006T07A012
Citation
ASME 41st International Conference on Ocean, Offshore and Arctic Engineering (OMAE 2022)
Contribution to Conference
Publisher DOI
Scopus ID
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.
Subjects
Data analysis
Explainable ai
Flexural strength
Ice mechanics
Machine learning
Material modeling