Optimization of CCT Equations Using Calculated Grain Boundary Soluble Compositions for the Simulation of Austenite Decomposition of Steels

Abstract

New CCT equations have been developed and optimized to simulate the start temperatures of the austenite decomposition process in low-alloyed steels using experimental CCT data published in the literature. Exceptionally, this optimization does not apply the nominal compositions of the steels, but the corresponding soluble compositions of the grain boundaries calculated using IDS software, depending on the reported austenitization treatments of the steels. These compositions, rather than the nominal ones, are expected to control the start of the austenite decomposition, which usually initiates at the grain boundaries. The new optimization treatment takes into account the solute microsegregation and the possible precipitate formation. Using IDS software, the new equations were validated with new experimental CCT data. Agreement was good not only for the austenite decomposition start temperatures, but also for the final phase fractions, indicating fairly reasonable predictions of phase transformation kinetics by the IDS. In addition, IDS simulations were compared with the experimental CCT data of five high-carbon steels, applying both the new equations based on grain boundary soluble compositions as well as the equations based on the nominal compositions. With the same experimental CCT data used in optimization, better agreement was obtained with the new equations, indicating the importance of determining the soluble compositions at the grain boundaries where the austenite decomposition process is likely to begin.

Simulation of Runout Table Cooling

“…In general, this heat source is described using where is the latent heat of phase transformation at temperature , is the change of the volume fraction transformed in time increment dt . The kinetics of the isothermal austenite decomposition is frequently described by the Johnson‐Mehl‐Avrami‐Kolmogorov(JMAK) approach, that is, here, X e is the equilibrium or maximum fraction transformed for the considered transformation product and temperature, is a rate constant which depends on steel chemistry and temperature, and is the JMAK exponent. This equation can typically be extended to non‐isothermal transformation that occurs on the ROT by using the additivity rule .…”

Thermodynamic, Kinetic, and Microstructure Data for Modeling Solidification of Fe-Al-Mn-Si-C Alloys

“…Also simulated, below the solidus, were the ferrite/austenite transformations and the solute microsegregation, including the determination of the soluble grain boundary compositions. As these compositions, instead of the nominal ones, are expected to control the start of austenite decomposition, [3] they will play an important role in a later study, in which we plan to extend the current simulation work on high-AlMnSi (Al ‡ 0.5 wt pct, Mn ‡ 2 wt pct, Si ‡ 1 wt pct) steels to their austenite decomposition process. These simulations will apply new continuous cooling transformation (CCT) equations, which take into account the Al alloying that was not considered in the previously optimized CCT equations of Miettinen et al [3] A. IDS Tool…”

Statistical Modeling for Prediction of CCT Diagrams of Steels Involving Interaction of Alloying Elements

“…The nonlinearity relationship between the heat treatment and the alloying elements is a known characteristic that specifies the interactions between the alloying elements. [36] This description was also confirmed in Reference 37 with the occurrence of concave regions signifying the interaction between alloying elements either enhancing or reducing each other's effects. This agrees with our results as Table IV further shows that the analysis of the interaction of C-Ni in ferrite transformation starts with the physical contribution of high hardenability.…”