Unavoidable tip clearance between blade tip and casing shroud plays an important role in the performance and characteristics of a tidal propeller turbine. In this work, the tip-leakage vortex (TLV) induced in the end-wall region was numerically illustrated by using the shear-stress transport (SST) k–ω turbulence model at various flow conditions and different tip-clearance sizes (TCSs). The swirling strength criterion was employed to visualize the tip-leakage vortex trajectory and investigate vortex evolution according to clearance size change. Although TLV occurs in both design and off-design conditions, vortex intensity develops strongly under excess flow rate with increased tip gap. The extreme influence of TCS on the turbine’s generated power and efficiency was predicted in steady simulations for four TCS cases, namely, δ = 0%, 0.25%, 0.5%, and 0.75%. With the extension of the tip gap, turbine performance was drastically reduced because of vigorous turbulent leakage flow combined with considerable volumetric loss. The effect of TCS on pressure fluctuation intensity were also explored on the basis of the transient simulation statistic. Maximal pressure variation amplitude and dominant frequency were presented in spectrum analysis utilizing fast Fourier transform.

To commercialize tidal power turbines, it is essential to ensure high efficiency and structural integrity. In this study, a rule of mixture design approach is applied to the turbine blades, and the optimal structural design is determined based on criteria for structural safety and mass reduction. The blades for megawatt tidal power turbines are hydrodynamically designed using blade element momentum (BEM) theory, and made of composite materials—glass fiber-reinforced plastics and carbon fiber-reinforced plastics. The layered structure of the composite is designed to meet the failure criteria under both normal and extreme operating conditions, and the structural integrity of the layered blade design is verified through finite element modeling, adhering to failure theories based on limit criteria, interaction criteria, and separation mode criteria. Additionally, a genetic algorithm is employed to calculate the optimal structural design model, setting the shell and spar cap as design parameters and performing load analysis according to the stacking reduction ratio. Using this process, the candidates for the optimal design model are selected based on the assigned weights on the Pareto frontier. As a result, the mass of the blade is reduced by 23.6% compared to the initial model, and the structural safety factors meet all the failure criteria under extreme load conditions, thereby ensuring a broad operational range for the tidal power turbines.