The Generalized Additivity Rule for Thermal Path-Dependent Diffusion-Controlled Phase Transformation by Simultaneous Nucleation and Growth and Its Mathematical Solutions

Scheil's additivity rule is widely applied to converting isothermal phase transformation kinetics to anisothermal ones. However, it often causes serious discrepancies between the calculated and experimental results. To better describe anisothermal phase transformation kinetics, a generalized additivity model was proposed in this paper, in which Johnson-Mehl-Avrami-Kolmogorov equation in couple with diffusion-controlled nucleation and growth was taken into account. The mathematical solutions of kinetic parameters for austenite to ferrite and pearlite transformations were determined by using machine learning under the generalized additivity rule. Conversions between isothermal and anisothermal kinetics for austenite to ferrite and pearlite transformations were carried out, which indicated that the new additivity rule was in better agreement with the experimental values than the Scheil's additivity rule. Furthermore, the generalized isokinetic condition considering the thermal path effect was discussed and analyzed.

Automated summary

In this paper, a generalized additivity model is proposed to better describe anisothermal phase transformation kinetics. Machine learning is used to determine the kinetic parameters and compare them with experimental results. The effect of thermal path on anisothermal kinetics is also discussed.