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Design and analysis of wave energy buoy integrated with seaweed farming

Design and analysis of wave energy buoy integrated with seaweed farming

Tee, Kong Fah ORCID: 0000-0003-3202-873X and Olanrewaju, Sulaiman O. (2018) Design and analysis of wave energy buoy integrated with seaweed farming. International Journal of Critical Infrastructures, 14 (4). pp. 336-359. ISSN 1475-3219 (Print), 1741-8038 (Online) (doi:

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Farming facilities in offshore face natural disasters caused by tropical storms. Without reliable design of mooring system, the wave load on the structure can easily damage it during a natural disaster event that could lead to unacceptable economic loss. Mooring failure represents the most common reason for the loss of ocean devices due to environmental load action and inappropriate design; because the developers concentrate much of their efforts on optimising the efficiency of the device and not enough attention is paid to the design of the mooring system. Thus, ensuring the security and safe deployment of very large floating structure system is very important issue for industrial marine farm and ocean energy activities. This paper presents design and analysis of wave energy integrated with seaweed farming system. The static model will predict the tension and tilt at each mooring component, including the anchor, for which the safe mass will be evaluated in terms of the vertical and horizontal tensions. Predictions can be saved to facilitate mooring motion correction. Time dependent currents can be entered to predict the dynamic response of the mooring.

Item Type: Article
Uncontrolled Keywords: wave energy; mooring failure; environmental loads; buoy; seaweed farming.
Subjects: T Technology > TA Engineering (General). Civil engineering (General)
Faculty / Department / Research Group: Faculty of Engineering & Science
Faculty of Engineering & Science > School of Engineering (ENN)
Last Modified: 23 Mar 2019 23:24
Selected for GREAT 2016: None
Selected for GREAT 2017: None
Selected for GREAT 2018: None
Selected for GREAT 2019: None
Selected for REF2021: None

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