Computationally Efficient Algorithm for Modeling Grain Growth Using Hillert's Mean-Field Approach.

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.

Process Maps for Predicting Austenite Fraction (vol.%) in Medium-Mn Third-Generation Advanced High-Strength Steels.

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.

Interface Segregation and Nitrogen Measurement in Fe-Mn-N Steel by Atom Probe Tomography.

Improved understanding of the interactions between solutes and the austenite/ferrite interface can benefit modeling of ferrite growth during austenite decomposition, as the transformation kinetic is significantly affected by solutes that influence interface mobility. Solute-interface interactions dominate solute segregation at the interface in binary systems, but in multi-component alloys, solute-solute interactions may also affect segregation. In this study, interface segregation in Fe-Mn-N is examined and compared with Fe-Mn-C, to reveal the extent to which C affects the segregation of Mn. Atom probe tomography (APT) is well-suited to analyze solute concentrations across the interface, as this technique combines high spatial resolution and compositional sensitivity. Measurements of Mn show that segregation is only observed for Fe-Mn-C. This demonstrates that Mn segregation is primarily driven by an affinity for C, which also segregates to the interface. However, the measurement of N in steels by APT may be affected by a variety of experimental factors. Therefore, in verifying the Fe-Mn-N result, systematic examination is conducted on the influence of pulsing method (voltage versus laser), sample preparation (ion milling versus electropolishing), and vacuum storage on the measured N concentration. Both laser pulsing and focused ion beam sample preparation are observed to decrease the apparent N concentration.