RESUMEN
To investigate the interconnected effects of manufacturing processes on microstructure evolution during hot-rolling, a through process model is required. A novel numerical implementation of the mean-field approach was introduced to efficiently describe the grain growth of larger systems and extended durations. In this approach, each grain is embedded within an average medium and interacts with the average medium, thus avoiding the complexities of individual grain interactions. The proposed upsampling approach dynamically adjusts the simulation grain ensemble, ensuring efficiency and accuracy regardless of the initial number of grains present. This adaptation prevents undersampling artifacts during grain growth. The accuracy of the model is verified against analytical solutions and experimental data, demonstrating high agreement. Moreover, the effects of different initial conditions are successfully investigated, demonstrating the model's versatility. Due to its simplicity and efficiency, the model can be seamlessly integrated into other microstructure evolution models.
RESUMEN
Process maps were developed using a combination of microstructural analysis and DICTRA-based modeling to predict the austenite vol.% as a function of the intercritical annealing parameters and starting microstructure. The maps revealed a strong dependence of the calculated austenite fraction (vol.%) on the Mn content (4-12 wt.%) and intercritical annealing temperatures (600 °C to 740 °C). The calculations were carried out for constant carbon, Al, and Si contents of 0.2 wt.%, 1.5 wt.%, and 1.0 wt.%, respectively. A modified empirical equation proposed by Koistinen and Marburger was employed to calculate the room-temperature retained austenite vol.% as a function of the intercritical annealing temperature, including the effect of the austenite composition. The process maps offer valuable insights for designing intercritical treatments of medium-Mn steels, aiding in the optimization of steel properties for automotive applications.