ABSTRACT

This study presents a detailed computational analysis of a modified 1:40 geometric scale of the U.S. Department of Energy's Reference Model-1 horizontal axis marine current turbine. The turbine features 0.5 m diameter rotors with NACA 4415 profiles. The CAD model was created using SOLIDWORKS, while ANSYS ICEM CFD was employed to generate an unstructured tetrahedral mesh for discretising the turbine surfaces and flow domain. ANSYS Fluent 2023R2 was used for simulation, applying a k-ω SST turbulence model and the SIMPLE algorithm for pressure-velocity coupling. Initial results showed discrepancies, including the power coefficient curve not reaching stall and torque values exceeding the Betz limit. These issues were attributed to the challenges in accurately capturing flow separation at the blade's small trailing edge. Subsequent modifications to the turbulence model, including the activation of the Kato-Launder limiter and curvature correction, improved the simulation accuracy. The study also explored the impact of boundary layer thickness through Y+ analysis. The final results agreed well with experimental data, particularly at higher tip speed ratios (TSR).

INTRODUCTION

The advancement of marine renewable energies presented a significant opportunity and an appealing alternative for reducing greenhouse gas emissions. Oceans offer an enormous reservoir of potential energy resources, including fluid flow, thermal gradients, surface waves, and salinity gradients. Hydro energy extraction, though not recent, could be achieved through two primary systems: harnessing the kinetic energy of flowing water and utilizing the potential energy of rising water levels. Hydrokinetic turbines were employed to capture this energy, helping to meet increasing energy demands while minimizing the impact on hydrological ecosystems (Di Felice Fabio et al., 2023; Jing et al., 2017). The effective deployment of hydrokinetic turbines depended on accurately predicting their hydrodynamic performance. Computational Fluid Dynamics (CFD) modelling was vital for this purpose. Researchers employed CFD to simulate the intricate interactions between fluid flow and turbine blades, offering detailed insights into various performance metrics. These models facilitated the analysis of flow behaviour, pressure distribution, and turbulence, which were crucial for understanding and enhancing turbine efficiency (Tiwari et al., 2020). CFD models were instrumental in identifying key performance indicators, such as power coefficients and torque values, across different operating conditions. They precisely predicted flow separation and reattachment points on the turbine blades, essential for reducing energy losses and boosting overall efficiency (Nishi Y et al., 2023; Zhang et al., 2019).

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