A comparative multi-objective investigation for metallic and non-metallic materials on the erosion resistance of wind turbine blade with performance evaluation

Turbine blade erosion is a significant concern in the power generation industry, as it can reduce efficiency and increase maintenance costs. This study investigates the effect of impact speed, impact angle, and particle size on the erosion rate of turbine blades, using a combination of simulation models and experimental validation. Regression models were developed to analyze the influence of these factors on the erosion rates of both metallic and non-metallic turbine blade materials. The results indicate that erosion rates increase with particle size and impact speed, with impact angle playing a crucial role in the erosion behavior. For metallic alloys, erosion rates decrease with increasing impact angle, whereas, for non-metallic materials, the erosion rate increases proportionally with impact angle. To optimize erosion resistance and aerodynamic performance, three multi-objective optimization algorithms; Multi-objective Genetic Algorithm (MOGA), Multi-objective Pareto Search Algorithm (MOPSA), and Weighted Value Gray Wolf Optimizer (WVGWO), were applied. The optimization process incorporated both the erosion rate and lift-to-drag ratio as objective functions, with the optimal impact angles identified for different materials: 22.5° for Kevlar and fiber glass reinforced epoxy, 28° to 29° for stainless steel, and 32.5° for aluminum alloy. These findings offer valuable insights into the design optimization of wind turbines, aiming to minimize turbine blade erosion and reduce maintenance costs, while improving aerodynamic performance.