Flow mechanisms and machine learning-based formation optimization on ultrasonic-assisted friction stir channeling of cast aluminum alloys

Key Points

• Optimized formation was achieved through ultrasonic-assisted friction stir channeling, improving material properties.
• Key evidence shows an increase in efficiency by 30% when using machine learning models for process parameters.
• Analysis of experimental data revealed the effectiveness of machine learning in refining friction stir techniques.
• This approach may enable enhanced material processing methods, indicating potential shifts in manufacturing standards.