Investigation of the cold crucible melting process: experimental and numerical study

The dynamic process of melting different materials in a cold crucible is being studied experimentally with parallel numerical modelling work. The numerical simulation uses a variety of complementing models: finite volume, integral equation and pseudo-spectral methods combined to achieve the accurate description of the dynamic melting process. Results show the temperature history of the melting process with a comparison of the experimental and computed heat losses in the various parts of the equipment. The free surface visual observations are compared to the numerically predicted surface shapes.

Modelling induction skull melting design modifications

Induction Skull Melting (ISM) is a technique for heating, melting, mixing and, possibly, evaporating reactive liquid metals at high temperatures with a minimum contact at solid walls. The presented numerical modelling involves the complete time dependent process analysis based on the coupled electromagnetic, temperature and turbulent velocity fields during the melting and liquid shape changes. The simulation model is validated against measurements of liquid metal height, temperature and heat losses in a commercial size ISM furnace. The observed typical limiting temperature plateau for increasing input electrical power is explained by the turbulent convective heat losses. Various methods to increase the superheat within the liquid melt, the process energy efficiency and stability are proposed.

The multiphysics modeling of solidification and melting processes

Solidification and melting processes involve a range of physical phenomena and their interactions (i.e., multiphysics). Computational modeling of such processes presents a significant challenge, both in representing the physics involved and in handling the resulting coupled behavior. Two methods for the computational modeling of multiphysics processes in complex geometries are highlighted in the context of four challenging applications

Modelling induction skull melting design modifications

Induction Skull Melting (ISM) is used for heating, melting, mixing and, possibly, evaporating reactive liquid metals at high temperatures when a minimum contact at solid walls is required. The numerical model presented here involves the complete time dependent process analysis based on the coupled electromagnetic, temperature and turbulent velocity fields during the melting and liquid shape changes. The simulation is validated against measurements of liquid metal height, temperature and heat losses in a commercial size ISM furnace. The often observed limiting temperature plateau for ever increasing electrical power input is explained by the turbulent convective heat losses. Various methods to increase the superheat within the liquid melt, the process energy efficiency and stability are proposed.

Dynamic model for metal cleanness evaluation by melting in a cold crucible

Melting of metallic samples in a cold crucible causes inclusions to concentrate on the surface owing to the action of the electromagnetic force in the skin layer. This process is dynamic, involving the melting stage, then quasi-stationary particle separation, and finally the solidification in the cold crucible. The proposed modeling technique is based on the pseudospectral solution method for coupled turbulent fluid flow, thermal and electromagnetic fields within the time varying fluid volume contained by the free surface, and partially the solid crucible wall. The model uses two methods for particle tracking: (1) a direct Lagrangian particle path computation and (2) a drifting concentration model. Lagrangian tracking is implemented for arbitrary unsteady flow. A specific numerical time integration scheme is implemented using implicit advancement that permits relatively large time-steps in the Lagrangian model. The drifting concentration model is based on a local equilibrium drift velocity assumption. Both methods are compared and demonstrated to give qualitatively similar results for stationary flow situations. The particular results presented are obtained for iron alloys. Small size particles of the order of 1 μm are shown to be less prone to separation by electromagnetic field action. In contrast, larger particles, 10 to 100 μm, are easily “trapped” by the electromagnetic field and stay on the sample surface at predetermined locations depending on their size and properties. The model allows optimization for melting power, geometry, and solidification rate.