Abstract
High-fidelity Computational Fluid Dynamics (CFD) approaches, such as Reynolds-Averaged Navier–Stokes (RANS) and Large Eddy Simulation (LES), are widely used to model tidal current turbines. However, their application to turbine arrays remains computationally expensive and physically restrictive, as the rotational speed of each turbine must typically be prescribed a priori. This requirement necessitates multiple iterative simulations and limits the scalability of conventional CFD-based array modeling.
To address these limitations, this study develops and validates a coupled Computational Fluid Dynamics–Rigid Body Dynamics (CFD–RBD) framework employing a six-degree-of-freedom (6-DOF) solver. In this approach, the turbine rotor angular velocity is computed dynamically from hydrodynamic forces acting on the blades, rather than being imposed as a boundary condition. This enables the entire turbine performance curve to be obtained within a single transient simulation run.
The proposed methodology is verified against experimental data for a standalone tidal current turbine. The results show good agreement with measurements, with a maximum deviation in the power coefficient (Cp) of approximately 11% at the optimal tip speed ratio (TSR = 5.1). A key advantage of the framework is its computational efficiency: the full performance curve is obtained using approximately 140 central processing unit hours, compared to 749 central processing unit hours required by conventional RANS-based CFD, representing a reduction in computational cost exceeding 80%.
The validated framework is subsequently applied to a two-turbine co-axial array with a sub-optimal axial spacing of 4D. The results show that the upstream turbine induced a velocity deficit exceeding 47% at the downstream turbine location, leading to significant performance degradation. Extension of the methodology to a staggered three-turbine array further demonstrates its capability to capture complex turbine–turbine interactions and flow acceleration effects within a single simulation framework.
Overall, this study demonstrates that the coupled CFD–RBD methodology provides a physically consistent and computationally efficient tool for simulating tidal turbine arrays, with strong potential for future array optimization and farm-scale analysis.