To date, only a few studies have examined the execution of the actuator disc approximation for a full-size turbine. Small-scale models have fewer constraints than large-scale models because the range of time-scale and length-scale is narrower. Hence, this article presents the methodology in implementing the actuator disc approach via the Reynolds-Averaged Navier-Stokes (RANS) momentum source term for a 20-m diameter turbine in an idealised channel. A structured grid, which varied from 0.5 m to 4 m across rotor diameter and width was used at the turbine location to allow for better representation of the disc. The model was tuned to match known coefficient of thrust and operational profiles for a set of validation cases based on published experimental data. Predictions of velocity deficit and turbulent intensity became almost independent of the grid density beyond 11 diameters downstream of the disc. However, in several instances the finer meshes showed larger errors than coarser meshes when compared to the measurements data. This observation was attributed to the way nodes were distributed across the disc swept area. The results demonstrate that the accuracy of the actuator disc was highly influenced by the vertical resolutions, as well as the grid density of the disc enclosure.

The flow field in the near wake region (up to six turbine diameters downstream) of a tidal current turbine is strongly driven by the combined wake of the device support structure and the rotor. Accurate characterisation of the near-wake region is important, but it is dominated by highly turbulent, slow-moving fluid. At present, limited number of research has been undertaken into the characterisation of the near-wake region for a Vertical Axis Tidal Turbine (VATT) device using the Reynolds Averaged Navier Stokes (RANS) model in the shallow water environment of Malaysia. This paper presents a comprehensive statistical analysis using the Mean Absolute Error (MEA), Mean Squared Error (MSE) and Root Mean Squared Error (RMSE) on the near-wake region for shallow water application by comparing numerical solutions (i.e., different types of RANS turbulence models using Ansys Fluent) with published experimental data. Seven RANS turbulence models with a single VATT, represented by using a cylindrical object, were employed in the preliminary study. The statistical analysis performed in this study is essential in exploring and giving a detailed understanding on the most suitable RANS turbulence model to be improved, specifically on its near-wake region. In this study, the near wake region is defined as D ≤ 6, where D is the device diameter. The analysis shows that the RANS numerical solutions are unable to accurately replicate the near-wake region based on large statistical errors computed. The average RMSE of near-wake region at z/D = [2, 3, 4, 6] are 0.5864, 0.4127, 0.4344 and 0.3577 while the average RMSE at far-wake region z/D = [8, 12] are 0.2269 and 0.1590, where z is the distance from the cylindrical object along the length of domain. The statistical error values are found to decrease with increasing downstream distance from a cylindrical object. Notably, the standard k–ε and realizable k–ε models are the two best turbulent models representing the near-wake region in RANS modelling, yielding the lowest statistical errors (RMSE at z/D = [2, 3, 4, 6] are 0.5666, 0.4020, 0.4113 and 0.3455) among the tested parameters

The placement of tidal turbines in a tidal farm is challenging owing to the flow resistance caused by individual devices. To successfully deploy tidal turbines, the wake interaction between devices, often determined by the array's layout and spacing, must be understood. In this study, the impact of array configuration for shallow water application is examined numerically using computational fluid dynamics (CFD). This is to propose a suitable array structure for possible implementation in Malaysia. This numerical study uses 15 turbines in a staggered and squared array with two sets of lateral and longitudinal spacing combinations. The horizontal axis tidal turbine (HATT) and vertical axis tidal turbine (VATT) are represented using disc and cylindrical models, respectively. The VATT with staggered setup and greater spacing model demonstrates faster wake recovery (between 10% to 21%), compared to the squared arrangement. This meets the far wake criteria and reduces the chance of wake mixing. It is also suitable for shallow depth implementation.