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...

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Bibliographic Details
Main Authors: Buil, Patrik, Kellner, Leon, Ehlers, Sören, von Bock und Polach, Rüdiger Ulrich Franz
Format: Conference Object
Language:English
Published: 2022
Subjects:
Data analysis
Explainable ai
Flexural strength
Ice mechanics
Machine learning
Material modeling
Arctic
Sea ice
Online Access:http://hdl.handle.net/11420/14178
Description
Summary: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.

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