Weakly nonlinear Surface Wave Prediction Using a Data‑Driven Method with the Help of Physical Understanding

Research output: Chapter in Book/Conference paperConference paperpeer-review

Abstract

Accurate surface wave prediction can potentially improve the safety and efficiency of various offshore operations, such as heavy lifts and active control of wave energy converters and floating wind turbines. Prediction of surface waves, even if only for a few periods in advance, is of value for decision-making. This study aims to predict weakly nonlinear surface waves (up to the 2nd-order) in real-time using a data-driven model based on Artificial Neural Networks (ANN), where the application of physics is investigated to aid the development of a data-driven model. Based on numerically synthesized nonlinear wave records calculated using exact 2nd-order theory, ANN models were trained to separate the nonlinear bound components at an up-wave location, propagate the linear waves and reintroduce the nonlinear components as a correction to the prediction at a down-wave location. The results show that the optimal approach is to predict each stage separately following the basic physical structure of weakly nonlinear water waves using a series of ANN rather than direct prediction in a single step using ANN. Further, the generalization of the models for different sea states and the impact of the 2nd-order bound waves on prediction accuracy is investigated.
Original languageEnglish
Title of host publicationOffshore Technology
Place of PublicationUnited States
PublisherASME International
ISBN (Electronic)978-0-7918-8683-0
DOIs
Publication statusPublished - 22 Sept 2023
Event42nd International Conference on Ocean, Offshore and Arctic Engineering (OMAE 2023) - Melbourne, Australia
Duration: 11 Jun 202316 Jun 2023
https://event.asme.org/OMAE

Publication series

NameProceedings of the International Conference on Offshore Mechanics and Arctic Engineering - OMAE
Volume1

Conference

Conference42nd International Conference on Ocean, Offshore and Arctic Engineering (OMAE 2023)
Country/TerritoryAustralia
CityMelbourne
Period11/06/2316/06/23
Internet address

Fingerprint

Dive into the research topics of 'Weakly nonlinear Surface Wave Prediction Using a Data‑Driven Method with the Help of Physical Understanding'. Together they form a unique fingerprint.

Cite this