A machine learning architecture for including wave breaking in envelope-type wave models
Wave breaking is a complex physical process about which open questions remain. For some applications, it is critical to include breaking effects in phase-resolved envelope-based wave models such as the non-linear Schrödinger. A promising approach is to use machine learning to capture breaking effect...
| Main Authors: | , , , |
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| Format: | Journal article |
| Language: | English |
| Published: |
Elsevier
2024
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