A Rapid, Open-Source CCT Predictor for Low-Alloy Steels, and Its Application to Compositionally Heterogeneous Material

Abstract

The ability to predict transformation behaviour during steel processing, such as primary heat treatments or welding, is extremely beneficial for tailoring microstructures and properties to a desired application. In this work, a model for predicting the continuous cooling transformation (CCT) behaviour of low-alloy steels is developed, using semi-empirical expressions for isothermal transformation behaviour. Coupling these expressions with Scheil’s additivity rule for converting isothermal to non-isothermal behaviour, continuous cooling behaviour can be predicted. The proposed model adds novel modifications to the Li model in order to improve CCT predictions through the addition of a carbon-partitioning model, thermodynamic boundary conditions, and a Koistinen–Marburger expression for martensitic behaviour. These modifications expanded predictions to include characteristic CCT behaviour, such as transformation suppression, and an estimation of the final constituent fractions. The proposed model has been shown to improve CCT predictions for EN3B, EN8, and SA-540 B24 steels by better reflecting experimental measurements. The proposed model was also adapted into a more complex simulation that considers the chemical heterogeneity of the examined SA-540 material, showing a further improvement to CCT predictions and demonstrating the versatility of the model. The model is rapid and open source.