Computational Fluid Dynamics and Visualisation of Coastal Flows in Tidal Channels Supporting Ocean Energy Development

Enayatollah Zangiabadi, Matt Edmunds, Iain A. Fairley, Michael Togneri, Alison J. Williams, Ian Masters and Nick Croft
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Enayatollah Zangiabadi: Marine Energy Research Group, Swansea University, Singleton Park, Swansea SA2 8PP, UK
Matt Edmunds: Marine Energy Research Group, Swansea University, Singleton Park, Swansea SA2 8PP, UK
Iain A. Fairley: Marine Energy Research Group, Swansea University, Singleton Park, Swansea SA2 8PP, UK
Michael Togneri: Marine Energy Research Group, Swansea University, Singleton Park, Swansea SA2 8PP, UK
Alison J. Williams: Marine Energy Research Group, Swansea University, Singleton Park, Swansea SA2 8PP, UK
Ian Masters: Marine Energy Research Group, Swansea University, Singleton Park, Swansea SA2 8PP, UK
Nick Croft: Marine Energy Research Group, Swansea University, Singleton Park, Swansea SA2 8PP, UK

Energies, 2015, vol. 8, issue 6, 1-16

Abstract: Flow characteristics in coastal regions are strongly influenced by the topography of the seabed and understanding the fluid dynamics is necessary before installation of tidal stream turbines (TST). In this paper, the bathymetry of a potential TST deployment site is used in the development of the a CFD (Computational Fluid Dynamics) model. The steady state k-? and transient Large Eddy Simulation (LES) turbulence methods are employed and compared. The simulations are conducted with a fixed representation of the ocean surface, i.e., a rigid lid representation. In the vicinity of Horse Rock a study of the pressure difference shows that the small change in height of the water column is negligible, providing confidence in the simulation results. The stream surface method employed to visualise the results has important inherent characteristics that can enhance the visual perception of complex flow structures. The results of all cases are compared with the flow data transect gathered by an Acoustic Doppler Current Profiler (ADCP). It has been understood that the k-? method can predict the flow pattern relatively well near the main features of the domain and the LES model has the ability to simulate some important flow patterns caused by the bathymetry.

Keywords: renewable energy; tidal stream turbine; real bathymetry; turbulence (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2015
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

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