A coupled thermal and metallurgical model for welding simulation of Ti–6Al–4V alloy

• Published in: Journal of materials processing technology 2014-11, Vol.214 (11), p.2434-2443
• Main Authors: Mi, Gaoyang, Wei, Yanhong, Zhan, Xiaohong, Gu, Cheng, Yu, Fengyi
• Format: Article
• Language: English
• Subjects: Cooling; JMAK equation; Mathematical analysis; Mathematical models; Phase transformations; Temperature distribution; Thermal properties; Thermal–metallurgical coupling; TIG welding; Titanium base alloys; Welding
• ISSN: 0924-0136
• DOI: 10.1016/j.jmatprotec.2014.05.011

•We developed a coupled thermal–metallurgical model for Ti–6Al–4V alloys to simulate welding.•We compared the coupled model with two classical models.•The coupled model describes the temperature profile during cooling accurately. The accurate prediction of the mechanical behavior of welded components made of Ti–6Al–4V requires a particular material model considering the significant effects of the material behavior during welding. Especially, phase transformations are assumed to have an influence on the temperature distribution. The flow curves of the material are changed during welding by complex mechanisms which might be describable using time-temperature history dependent flow curves. The following paper shows (as a step forward), how the influence of phase transformations on the transient heat conduction in components made of Ti–6Al–4V during tungsten inert gas (TIG) arc welding is investigated using a coupled thermal and metallurgical model. Kinetics of α+β→β phase transformation during heating and β→α phase transformation during cooling are studied using the Johnson–Mehl–Avrami–Kolmogorov (JMAK) equation. A numerical heat transfer model is used to calculate the transient temperature field during welding. The thermal properties are calculated by a linear mixing rule based on the phase fractions and the thermal properties of each pure phase. Using these obtained thermal properties, the welding process of Ti–6Al–4V alloy is modeled using finite-elements for the spatial discretization and finite-differences to predict the transient temperature field. Additional calculations neglecting the phase changes are carried out to compare the temperatures and visualize the effects of phase transformations on the cooling behavior. The comparison of these models with measurements shows that the model considering the influence of solid phase transformations describes the temperature profile during cooling accurately.