Development of an SPH-based numerical wave–current tank and application to wave energy converters

Abstract

This research proposes a high-fidelity based numerical tank designed to analyze the modified hydrodynamics that develops in waves–current fields, aimed at generating power matrices for wave energy converters (WEC). This tank is developed within the open source DualSPHysics Lagrangian framework using the Smoothed Particle Hydrodynamics (SPH) method, validated with physical data, and applied to simulate a point-absorber WEC. Our proposed numerical facility implements open boundary conditions, employing third-order consistent wave theory for direct generation, with flow field constrained by a Doppler correlation function. Reference data is collected from dedicated physical tests for monochromatic waves; the wave–current numerical basin demonstrates very high accuracy in terms of wave transformation and velocity field. In the second segment of this paper, a current-aware power transfer function is computed for the taut-moored point-absorber Uppsala University WEC (UUWEC). Parametrically defined regular waves with uniform currents are utilized to map an operational sea state featuring currents of different directions and intensities. In terms of power capture capabilities, the modified dynamics observed in presence of currents translates in a dependence of the WEC’s power matrix not only on wave parameters, but also on current layouts. The UUWEC’s power output has revealed that regardless of current directionality, annual output consistently decreases, with a registered power drop as high as 10% when an expected current field is introduced.

S. Capasso gratefully acknowledges Prof. B. Rogers for the valuable discussions, and the University of Manchester for hosting his research stay. The authors acknowledge the insightful comments provided by Prof. A.J.C. Crespo (University of Vigo, Spain) and Dr. J.M. Domínguez (University of Vigo, Spain). We acknowledge the CINECA award under the ISCRA initiative, for the availability of high-performance computing resources and support. S. Capasso acknowledges fundings from WECANet COST Action CA17105 “A pan-European Network for Marine Renewable Energy with a Focus on Wave Energy” supporting a STSM at the Universitat Politècnica de Catalunya – BarcelonaTech. We are grateful for the computing resources from the Northern Ireland High Performance Computing (NI-HPC) service funded by EPSRC, UK (EP/T022175). M. Göteman and B. Tagliafierro acknowledge the support provided by the National Academic Infrastructure for Super-computing in Sweden (NAISS) through the project NAISS 2023/5-351 for the use of the GPU partition Tetralith2 at the National Supercomputer Centre (NSC). I. Martínez-Estévez acknowledges funding from Xunta de Galicia under “Programa de axudas á etapa predoutoral da Consellería de Cultura, Educación e Universidades da Xunta de Galicia” (ED481A-2021/337). This work was partially supported by the project SURVIWEC PID2020-113245RB-I00 financed by MCIN/AEI/ 10.13039/501100011033 and by the project ED431C 2021/44 “Programa de Consolidación e Estructuración de Unidades de Investigación Competitivas” financed by Xunta de Galicia, Consellería de Cultura, Educación e Universidade, Spain. Grant TED2021-129479A-I00 funded by Ministerio de Ciencia e Innovacion (MCIN/AEI/10.13039/501100011033) and by the “European Union NextGenerationEU/PRTR”. Dr. Corrado Altomare acknowledges funding from the Spanish government and the European Social Found (ESF) under the programme “Ramón y Cajal 2020” (RYC2020-030197-I/AEI/10.13039/501100011033).

Peer Reviewed

Postprint (published version)