Tidal Turbine Benchmarking Project: Stage I - Steady Flow Blind Predictions

R.H.J. Willden, Xiaosheng Chen, S.W. Tucker Harvey, H. Edwards, C.R. Vogel, K. Bhavsar, T. Allsop, J Gilbert, Hannah Mullings, M Ghobrial, P Ouro, D Apsley, T Stallard, Ian Benson, Anna Young, Pal Schmitt, Federico Zilic de Arcos, M-A Dufour, C Choma Bex, G PinonA Evans, M Togneri, Ian Masters, L da Silva Ignacio, C Duarte, F Souza, Stefano Gambuzza, Yabin Liu, Ignazio Maria Viola, M Rentschler, G Vaz, R Azcueta, H Ward, F Salvatore, Z Sarichloo, D Calcagni, T T Tran, H Ross, M Oliviera, R Puraca, B Carmo

Research output: Chapter or section in a book/report/conference proceedingChapter in a published conference proceeding

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Abstract

This paper presents the first blind prediction stage of the Tidal Turbine Benchmarking Project conducted and funded by the UK’s EPSRC and Supergen ORE Hub. In this first stage, only steady flow conditions, at low and elevated turbulence levels (3.1%), were considered. Prior to the blind prediction stage, a large laboratory-scale experiment was conducted in which a highly instrumented 1.6 m diameter tidal rotor was towed through a large towing tank in well-defined flow conditions with and without an upstream turbulence grid. Details of the test campaign and rotor design were released as part of this community blind prediction exercise. Participants were invited to simulate turbine performance and loads using appropriate methods. 26 submissions were received from 12 groups across academia and industry using techniques ranging from blade resolved Computational Fluid Dynamics through Actuator Line, Boundary Integral Equation Model, Vortex methods to engineering Blade Element Momentum methods. The comparisons between experiments and blind predictions were very positive, not only helping to provide validation and uncertainty estimates for the models, but also validating the experimental tests themselves. The exercise demonstrated that the experimental turbine data provides a robust dataset against which researchers and engineers can test their models and implementations, helping to reduce uncertainty and provide increased confidence in engineering processes, as well as a basis against which modellers can evaluate and refine approaches.
Original languageEnglish
Title of host publicationProceedings of the European Wave and Tidal Energy Conference
Volume15
DOIs
Publication statusPublished - 2 Sept 2023
EventThe 15th European Wave and Tidal Energy Conference - Bilbao, Spain
Duration: 3 Sept 20237 Sept 2023
https://ewtec.org/ewtec-2023/

Publication series

NameProceedings of the European Wave and Tidal Energy Conference
PublisherEuropean Wave and Tidal Energy Conference
ISSN (Print)2706-6932

Conference

ConferenceThe 15th European Wave and Tidal Energy Conference
Country/TerritorySpain
CityBilbao
Period3/09/237/09/23
Internet address

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