Giorgi, G. and Ringwood, John (2018) Parametric motion detection for an oscillating water column spar buoy. In: Advances in Renewable Energies Offshore. Taylor & Francis, pp. 502-512. ISBN 9781138585355

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Abstract

Parametric resonance is a highly nonlinear phenomenon, difficult to model and foresee, with often detrimental consequences on the power production efficiency of wave energy converters. Parametric excitation, due to time-varying parameters of the system, activates an internal excitation mechanism, which diverts part of the energy from the principal degree of freedom, consequently generating parasitic motions. Although the ability of a mathematical model to articulate parametric instability is beneficial for design and control purposes, the increase in computational burden and complexity is often unacceptable. However, using computationally frugal nonlinear Froude-Krylov force calculations, applicable to axisymmetric devices, it is possible to define mathematical models fast enough for computation in real time. The focus of the paper is a floating oscillating water column device, inspired by the Sparbuoy device, in order to demonstrate the ability of such a mathematical model to describe parametric roll responses.

Item Type:	Book Section
Additional Information:	Funding: This paper is based upon work supported by Science Foundation Ireland under Grant No. 13/IA/1886.
Keywords:	Parametric; motion detection; oscillating water column; spar buoy;
Academic Unit:	Faculty of Science and Engineering > Research Institutes > Centre for Ocean Energy Research Faculty of Science and Engineering > Electronic Engineering
Item ID:	14298
Identification Number:	https://doi.org/10.1201/9780429505324
Depositing User:	Professor John Ringwood
Date Deposited:	01 Apr 2021 13:34
Publisher:	Taylor & Francis
Refereed:	Yes
Funders:	Science Foundation Ireland (SFI)
URI:	Publisher
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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