Windt, Christian, Davidson, Josh and Ringwood, John (2018) High-fidelity numerical modelling of ocean wave energy systems: A review of computational fluid dynamics-based numerical wave tanks. Renewable and Sustainable Energy Reviews, 93. pp. 610-630. ISSN 1364-0321
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Abstract
For the research and development (R&D) of wave energy converters (WECs), numerical wave tanks (NWTs) provide an excellent numerical tool, enabling a cost-effective testbed for WEC experimentation, analysis and optimisation. Different methods for simulating the fluid dynamics and fluid structure interaction (FSI) within the NWT have been developed over the years, with increasing levels of fidelity, and associated computational expense. In the past, the high computational requirements largely precluded Computational Fluid Dynamics (CFD) from being applied to WEC analysis. However, the continual improvement and availability of high performance computing has led to the steady increase of CFD-based NWTs (CNWT) for WEC experiments. No attempt has yet been undertaken to comprehensively review CNWT approaches for WECs. This paper fills this gap and presents a thorough review of high-fidelity numerical modelling of WECs using CNWTs. In addition to collating the published literature, this review tries to make a step towards a best practice guideline for the applications of CFD in the field of wave energy.
Item Type: | Article |
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Additional Information: | This paper is based upon work supported by Science Foundation Ireland under Grant No. 13/IA/1886. |
Keywords: | Wave energy conversion; Computational fluid dynamics; RANS; Numerical wave tank; |
Academic Unit: | Faculty of Science and Engineering > Electronic Engineering Faculty of Science and Engineering > Research Institutes > Centre for Ocean Energy Research |
Item ID: | 12542 |
Identification Number: | 10.1016/j.rser.2018.05.020 |
Depositing User: | Professor John Ringwood |
Date Deposited: | 04 Mar 2020 17:07 |
Journal or Publication Title: | Renewable and Sustainable Energy Reviews |
Publisher: | Elsevier |
Refereed: | Yes |
Funders: | Science Foundation Ireland (SFI) |
Related URLs: | |
URI: | https://mural.maynoothuniversity.ie/id/eprint/12542 |
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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