Abstract

Secondary hot-working on dual phase titanium alloys are essential for microstructural modification to tailor mechanical properties, which is typically challenging due to a narrow available processing window, especially during industrial scale manufacturing. Poor workability, strain induced porosity and adiabatic temperature rise in α + β phase region (i.e., sub-transus) are some of the main challenges faced. Cyclic thermal treatment (CTT) is an emerging technology showing potentials for microstructure modification (i.e., globularisation) in Ti‐6Al‐4V with significantly reduced mechanical work in the α + β region. This study summarises the results of CTT investigations conducted on a wrought Ti‐6Al‐4V alloy subjected to various thermo-mechanical conditions to develop different initial microstructures. Samples with uniform strain distributions were extracted from pre-forged samples and subsequently subjected to CTT using both conventional electric furnace (i.e., for slow heating and cooling rates), and induction heating (i.e., for faster heating and cooling rates). CTT of the samples forged at sub-transus temperature in conventional furnace led to maximum (i.e. ~100%) globularisation and significant coarsening of α grains, resulting in an equiaxed bimodal microstructure. On the other hand, CTT with induction heating method has resulted in a maximum of 80% globularisation fraction in samples forged to 60% reduction, and ~35% globularisation fraction in those forged to 20% reduction. The globularisation mechanisms during CTT of the sub-transus forged samples was dominated by the boundary splitting and thermal grooving. A Johnson-Mehl-Avarmi-Kolmogorov (JMAK) based model has been developed to predict the evolution of globularisation and grain growth during CTT. The developed JMAK model was then successfully incorporated into DEFORM® software as post-processing user subroutines. The predicted microstructure evolution by Finite Element (FE) simulations shown a good convergence towards the experimentally measured data following CTT.

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