Journal of Materials Research and Technology (Sep 2024)
A prediction model for austenite grain size distribution of casting slab in thermal rebound process: Considering α-ferrite precipitation and re-austenization
Abstract
The precipitation and re-austenitization behavior of α-ferrite during thermal rebound process of casting slab are crucial to the austenite grain size distribution. Accurately obtaining austenite grain size distribution plays an important guiding role for avoiding the formation of slab cracks and effectively improving the quality of steel. In this work, a quantitative model to calculate α-ferrite precipitation at different temperatures has been constructed by employing high-temperature expansion test and peak area method. On this basis, a prediction model for the austenite grain size distribution of casting slab in the thermal rebound process has been theoretically derived with consideration of the α-ferrite precipitation and re-austenitization. Then, the accuracy of the quantitative model for α-ferrite precipitation and the prediction model for austenite grain size distribution have been evaluated by high-temperature quenching experiments. The results show that the maximum error between the calculation values of the prediction model and the experimental values is only 3.67 %, which can reliably predict the austenite grain size distribution of slab under different phase fractions of precipitated α-ferrite and initial austenite grain sizes. When the phase fraction of precipitated α-ferrite reaches about 70 %, the average grain size after re-austenitization comes to nearly 50 % of the initial size, which achieves the best refining effect. The reduction in initial austenite grain size is beneficial to the refinement of austenite grain after thermal rebound. Reasonable control of thermal rebound temperature and multiple cycles of phase transformation are effective means of obtaining austenite microstructure with smaller average grain size and more uniform distribution.
