Multi-scale simulation of solidification behavior and microstructure evolution during vacuum electron beam welding of Al-Cu alloy

A multi-scale model is established to study the complex melting and solidification behaviors during the electron beam welding of an Al-Cu alloy. The model combines a macroscopic thermal-fluid algorithm for molten pool behavior and a microscopic cellular automaton algorithm for the microstructure evolution. The solidification parameters, including the thermal gradient and cooling rate, build a bridge between the macroscopic and microscopic simulations. The model is validated by comparing the experimental fusion profile results, microstructure, morphology, grain size and element distribution that result from different welding parameters. On the macroscopic scale, with an increase in beam current, the molten pool fluctuation intensity increases, the thermal gradient increases and the cooling rate decreases. On the microscopic scale, the grain growth process includes nucleation, growth and competitive growth. After solidification, the concentration of Cu on the grain boundaries is larger than that inside the grains. With increasing beam current, the grain size tends to increase, and the segregation ratio decreases. The power-law function between the grain size and cooling rate can be summarized as d proportional to CR-0.55, where d is the grain size and CR is the cooling rate. Moreover, the segregation ratio first increases and then decreases slowly with decreasing solidification time. We expect this study to provide a deeper understanding of how to control weld formation and microstructure and improve confidence in optimizing the actual welding process. (C) 2021 Elsevier Ltd. All rights reserved.

Automated summary

A multi-scale model combining macroscopic and microscopic simulations is established to study the complex melting and solidification behaviors during electron beam welding of an Al-Cu alloy. By comparing experimental results, the model provides a deeper understanding of controlling weld formation and microstructure, improving confidence in optimizing the actual welding process.