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Davidson, Josh, Giorgi, Simone and Ringwood, John (2016) Identification of Wave Energy Device Models From Numerical Wave Tank Data—Part 1: Numerical Wave Tank Identification Tests. IEEE Transactions on Sustainable Energy, 7 (3). pp. 1012-1019. ISSN 1949-3029
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Abstract
In this paper and its companion, the identification of mathematical models describing the behaviour of wave energy devices (WECs) in the ocean is investigated through the use of numerical wave tank (NWT) experiments. This paper deals with the identification tests used to produce the data for the model identification. NWTs, implemented using computational fluid dynamics (CFD), are shown as an effective platform to perform the identification tests. The design of the NWT experiments, to ensure the production of information-rich data for the model identification, is discussed. A case study is presented to illustrate the design and implementation of NWT experiments for the identification of WEC models.
| Item Type: | Article |
|---|---|
| Additional Information: | This work was supported in part by the Enterprise Ireland under Grant EI/CF/2011/1320, in part by the Irish Government and the European Union under Ireland’s EU Structural and Investment Funds Programme 2014–2020, and in part by the Science Foundation Ireland under Grant 13/IA/1886. Paper no. TSTE-00634-2015. |
| Keywords: | Wave energy conversion; hydrodynamic modelling; system identification; numerical wave tank; computational fluid dynamics; |
| Academic Unit: | Faculty of Science and Engineering > Electronic Engineering Faculty of Science and Engineering > Research Institutes > Centre for Ocean Energy Research |
| Item ID: | 9398 |
| Identification Number: | 10.1109/TSTE.2016.2515512 |
| Depositing User: | Professor John Ringwood |
| Date Deposited: | 23 Apr 2018 16:06 |
| Journal or Publication Title: | IEEE Transactions on Sustainable Energy |
| Publisher: | Institute of Electrical and Electronics Engineers (IEEE) |
| Refereed: | Yes |
| Funders: | Enterprise Ireland (EI), European Structural and Investment Funds Programme, Science Foundation Ireland (SFI) |
| Related URLs: | |
| URI: | https://mu.eprints-hosting.org/id/eprint/9398 |
| Use Licence: | This item is available under a Creative Commons Attribution Non Commercial Share Alike Licence (CC BY-NC-SA). Details of this licence are available here |
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