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Analytical solutions for numerical wavetanks are limited presently to a simple bathymetry and third
order accuracy. Furthermore, tanks are generally characterised using linear transfer functions to relate
the wavemaker forcing amplitude to wave elevation at a probe located in the wavetank. This paper
reports on a numerical wavetank implemented using the OpenFOAM software package. The aim of
the research is to train neural networks to represent non-linear transfer functions mapping a desired
wave surface-elevation time-trace at a probe to the wavemaker input required to create it.
Original languageEnglish
Publication statusPublished - 03 Jun 2021
Event9th Conference on Computational Methods in Marine Engineering - Edinburgh, Edinburgh, United Kingdom
Duration: 02 Jun 202104 Jun 2021
Conference number: 9th


Conference9th Conference on Computational Methods in Marine Engineering
Abbreviated titleMARINE2021
Country/TerritoryUnited Kingdom
Internet address


  • computational fluid dynamics; neural networks; machine learning, OpenFOAM; tank transfer function


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