Munekazu Ohno

Reliable prediction of macrosegregation requires accurate thermophysical properties that govern melt flow, particularly the thermal expansion coefficient 𝛽T and kinematic viscosity 𝜈. However, these properties are difficult to measure with sufficient accuracy. In this study, we develop a data assimilation approach that combines the modified lattice Boltzmann method (MLBGK) with a particle filter to estimate 𝛽T and 𝜈 using only thermal analysis data. A two-dimensional system with a horizontal temperature gradient was considered, and twin experiments were performed to evaluate the feasibility of the method. The results show that both 𝛽T and 𝜈 can be estimated with high accuracy. In single-parameter estimation, convergence to the true value was achieved rapidly for particle numbers 𝑁≥200. Simultaneous estimation was also successful. The estimation accuracy depended on the number of measurement points and the filtering interval, and estimation of 𝛽T is generally more accurate than 𝜈. The proposed approach provides a practical means of determining flow-related properties of molten steel from thermal analysis measurements.

Reliable prediction of macrosegregation requires accurate thermophysical properties that govern melt flow, particularly the thermal expansion coefficient βT and kinematic viscosity ν. However, these properties are difficult to measure with sufficient accuracy. In this study, we develop a data assimilation approach that combines the modified lattice Boltzmann method (MLBGK) with a particle filter to estimate βT and ν using only thermal analysis data. A two-dimensional system with a horizontal temperature gradient was considered, and twin experiments were performed to evaluate the feasibility of the method. The results show that both βT and ν can be estimated with high accuracy. In single-parameter estimation, convergence to the true value was achieved rapidly for particle numbers N ≥ 200. Simultaneous estimation was also successful. The estimation accuracy depended on the number of measurement points and the filtering interval, and estimation of βT is generally more accurate than ν. The proposed approach provides a practical means of determining flow-related properties of molten steel from thermal analysis measurements.

Understanding the solid–liquid interfacial thermodynamics of pure metals under undercooled conditions is essential for predicting microstructure evolution, yet quantitative data on the temperature dependence of interfacial free energy and its anisotropy remain limited. In this study, we extend the capillary fluctuation method (CFM) to moving solid–liquid interfaces obtained from molecular dynamics simulations of solidification in undercooled pure Al. By tracking the instantaneous interface position during steady-state migration and analyzing the fluctuation spectra of the interface height, the average interfacial free energy γ0 and the anisotropy strengths ϵ1 and ϵ2 were determined as functions of temperature. The fluctuation spectra retained a characteristic k−2 dependence even for moving interfaces, demonstrating that the CFM is applicable under non-equilibrium solidification conditions. The results show that γ0 tends to increase with decreasing temperature near the melting point, consistent with theoretical expectations and previous computational studies. The anisotropy parameters exhibit only weak temperature dependence: ϵ1 remains nearly constant over the investigated temperature range, whereas ϵ2 tends to decrease toward zero with increasing undercooling. These trends indicate that the anisotropy of the interfacial free energy at high undercoolings is primarily governed by ϵ1.

The effect of the inclination angle of the columnar dendrite on the microsegregation during directional solidification of a model alloy, i.e., Al-3 mass% Cu alloy, was investigated using two-dimensional quantitative phase-field simulation. The extent of the microsegregation was characterized by the fraction of the eutectic region in the as-cast microstructure. It was found that the microsegregation significantly decreases as the average value of the primary arm spacing increases for each inclination angle. In addition, the microsegregation decreases as the inclination angle increases. These behaviors are mainly ascribed to the change of shape of last-solidified liquid related to contribution of back diffusion for different values of the primary arm spacing and inclination angle. Furthermore, the degree of microsegregation was well-predicted from the inclination angles and primary dendrite arm spacings. This suggests the possibility that the microsegregation can be simply predicted from inclination angles and primary dendrite arm spacings.