Computing-assisted optimization of friction stir processing for magnesium-based hybrid surface composites using the aquila optimizer
摘要
The main purpose of the present investigation is to optimize the friction stir processing parameters in the fabrication of the YSZ/Al2O3 particulate-reinforced AZ31 magnesium alloy-based surface composites with enhanced porosity and corrosion rate. In the present work, the response surface method based on the central composite design was used to study the effects of the tool rotational speed, tool traverse speed, and tool axial force on the porosity and corrosion rate of the AZ31 magnesium alloy-based surface composites. In the present work, the developed response surfaces based on the prediction of the porosity and corrosion rate of the AZ31 magnesium alloy-based surface composites were statistically significant, with a high predictive accuracy of R2 = 0.9928 and R2 = 0.9954, respectively. Sensitivity analysis showed that the tool traverse speed had the highest effect on the AZ31 magnesium alloy-based surface composites, followed by the tool rotational speed and the tool axial force. Using the multi-response optimization method based on the Aquila Optimizer Algorithm, the optimum friction stir processing parameters in the fabrication of the AZ31 magnesium alloy-based surface composites were determined as a tool rotational speed of 1136.234 rpm, a tool traverse speed of 104.426 mm/min, and a tool axial force of 10.621 kN. At the optimum friction stir processing parameters, the surface composite revealed an optimum porosity of 1.12% and an optimum corrosion rate of 2.15 mm/year. The results revealed that the surface composite fabricated at the optimum friction stir processing parameters had an optimum microstructure. Finally, the optimized conditions are crucial for enhancing the performance of composites, making them ideal for applications in aerospace, automotive, and other industries that require lightweight, high-performance composites.
Graphical abstract