Discrete Prediction of Grain Evolution in Solid-State Welding of Ti<sub>6</sub>Al<sub>4</sub>- V Alloy

Titanium (Ti) alloys, known for their high strength and low weight, are essential in aircraft and aerospace applications. This study focuses on friction spot welding as an innovative, efficient process that creates robust Ti alloys joints while minimizing the carbon footprint. The research aims to develop a cellular automata (CA) model to analyze grain evolution during the friction stir spot welding of Ti6Al4V alloy. The methodology involved simulating the welding process at rotational speeds ranging from 800 to 1,200 rpm using a complex curved-thread shoulder. The CA model incorporated both deterministic and probabilistic approaches to capture the dynamic recrystallization (DRX) behavior. Grain nucleation and growth were modeled based on dislocation density, allowing for an in-depth assessment of the alloy's microstructural changes driven by hardening and softening mechanisms. Validation was performed by comparing the model's predictions with experimental measurements of temperature and grain size. The findings indicate that heat and deformation during welding significantly influence grain size evolution, enhancing the understanding of microstructural behavior in high-strength titanium joints. This work contributes valuable insights into optimizing welding techniques for titanium alloys in aerospace engineering.