Optimization of a Horizontal Axis Tidal (HAT) turbine for powering a Reverse Osmosis (RO) desalination system using Computational Fluid Dynamics (CFD) and Taguchi method

Horizontal Axis Tidal (HAT) turbines can be used to power RO (reverse osmosis) desalination systems. The greatest weakness of these turbines is the high price of design, development, and manufacturing. Traditionally, optimization of turbine geometry is achieved by running several numerical models of the turbine which can become time consuming and expensive. The Taguchi-CFD (Computational Fluid Dynamics) approach has recently been introduced as an inexpensive and rapid tool for optimizing industrial devices. This technique can be used as a straightforward solution for optimization of geometry of HAT turbines. In this work, a conceptual design of a tidal power reverse osmosis (TPRO) desalination unit was proposed. Subsequently, the geometry of the HAT turbine, which can power the whole desalination system, was optimized with combination of only 16 CFD simulations using the Taguchi method. The effects of blade size, number of blades, hub radius, and hub shape were studied and optimized. The Taguchi results revealed that the most important parameters influencing the power output of HAT turbine are the number of blades, size of blade, hub radius, and hub shape respectively. Moreover, the results of the superposition model showed that the minimum signal-to-noise ratio (SNR) is 21% less than the amount achieved in the Taguchi approach. The power coefficient (C-p) of the optimized HAT turbine was 0.44 according to the results of CFD simulations, which was 10% higher than that of the baseline model (0.40) at tip speed ratio (TSR) of 5. The weight of the optimized model was less than the baseline model by 17%. The results of this study provide a comprehensive guidance for horizontal turbine optimization process.

Automated summary

Horizontal Axis Tidal (HAT) turbines can be optimized for powering RO desalination systems using Taguchi-CFD method with only 16 simulations for geometry optimization. The key parameters influencing the power output of HAT turbines are blade size, number of blades, hub radius, and hub shape. The optimized HAT turbine showed a 10% increase in power coefficient compared to the baseline model at a tip speed ratio of 5, with a 17% reduction in weight.