The industrial objective of lowering the mass of mechanical structures requires continuous improvement in controlling the mechanical properties of metallic materials. Steel cleanliness and especially control of inclusion size distribution have, therefore, become major challenges. Inclusions have a detrimental effect on fatigue that strongly depends both on inclusion content and on the size of the largest inclusions. Ladle treatment of liquid steel has long been recognized as the processing stage responsible for the inclusion of cleanliness. A multiscale modeling has been proposed to investigate the inclusion behavior. The evolution of the inclusion size distribution is simulated at the process scale due to coupling a computational fluid dynamics calculation with a population balance method integrating all mechanisms, i.e., flotation, aggregation, settling, and capture at the top layer. Particular attention has been paid to the aggregation mechanism and the simulations at an inclusion scale with fully resolved inclusions that represent hydrodynamic conditions of the ladle, which have been specifically developed. Simulations of an industrial-type ladle highlight that inclusion cleanliness is mainly ruled by aggregation. Quantitative knowledge of aggregation kinetics has been extracted and captured from mesoscale simulations. Aggregation efficiency has been observed to drop drastically when increasing the particle size ratio.

During the processing of maraging steels, Titanium easily combines with Nitrogen to form nitride inclusions, known to be deleterious for fatigue properties of the alloy. According to thermodynamic calculations, the precipitation occurs during solidification of the vacuum arc remelted (VAR) ingot. A coupled model of titanium nitride (TiN) inclusion precipitation and vacuum remelting has been set-up to study the inclusion cleanliness of the ingot. The nitrogen content, nuclei numeral density and solidification time appear as the key factors which control the inclusion size.

Vacuum metallurgical processes such as the electron beam melting are highly conducive to volatilization. In titanium processing, it concerns the alloying elements which show a high vapor pressure with respect to titanium matrix, such as Al. Two different experimental approaches using a laboratory electron beam furnace have been developed for the estimation of volatilization rate and activity coefficient of Al in Ti64. The first innovative method is based on the deposition rate of Al on Si wafers located at different angles θ above the liquid bath. We found that a deposition according to a cos²(π/2−θ) law describes well the experimental distribution of the weight of the deposition layer. The second approach relies on the depletion of aluminum in the liquid pool at two separate times of the volatilization process. Both approaches provide values of the Al activity coefficient at T=1, 860 °C in a fairly narrow range [0.044–0.0495], in good agreement with the range reported in the literature. Furthermore numerical simulation of the Al behavior in the liquid pool reveals (in the specific case of electron beam button melting) a weak transport resistance in the surface boundary layer.

Removing inclusions from the melt is an important task in metallurgy with critical impact on the quality of the final alloy. Processes employed with this purpose, such as flotation, crucially depend on the particle size. For small inclusions, the aggregation kinetics constitute the bottleneck and, hence, determine the efficiency of the entire process. If particles smaller than all flow scales are considered, the flow can locally be replaced by a plane shear flow. In this contribution, particle interactions in plane shear flow are investigated, computing the fully resolved hydrodynamics at finite Reynolds numbers, using a lattice Boltzmann method with an immersed boundary method. Investigations with various initial conditions, several shear values and several inclusion sizes are conducted to determine collision efficiencies. It is observed that although finite Reynolds hydrodynamics play a significant role in particle collision, statistical collision efficiency barely depends on the Reynolds number. Indeed, the particle size ratio is found to be the prevalent parameter. In a second step, modeled collision dynamics are applied to particles tracked in a fully resolved bubbly flow, and collision frequencies at larger flow scale are derived.