On the modelling of the thermal interactions between a spray curtain and an impinging cold gas cloud

A mixed Lagrangian-Eulerian model of a Water Curtain barrier is presented. The heat, mass and momentum processes are modelled in a Lagrangian framework for the dispersed phase and in an Eulerian framework for the carrier phase. The derivation of the coupling source terms is illustrated with reference to a given carrier phase cell. The turbulent character of the flow is treated with a single equation model, modified to directly account for the influence of the particles on the flow. The model is implemented in the form of a 2 D incompressible Navier Stokes solver, coupled to an adaptive Rung Kutta method for the Lagrangian sub-system. Simulations of a free standing full cone water spray show satisfactory agreement with experiment. Predictions of a Water Curtain barrier impacted by a cold gas cloud point to markedly different flow fields for the upward and downward configurations, which could influence the effectiveness of chemical absorption in the liquid phase.

Modeling the dynamics of electromagnetically agitated metallurgical flows: levitation, cold crucible, aluminium electrolysis, etc.

We present practical modelling techniques for electromagnetically agitated liquid metal flows involving dynamic change of the fluid volume and shape during melting and the free surface oscillation. Typically the electromagnetic field is strongly coupled to the free surface dynamics and the heat-mass transfer. Accurate pseudo-spectral code and the k-omega turbulence model modified for complex and transitional flows with free surfaces are used for these simulations. The considered examples include magnetic suspension melting, induction scull remelting (cold crucible), levitation and aluminium electrolysis cells. The process control and the energy savings issues are analysed.

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.

Experimental and numerical study of the cold crucible melting process

The cold crucible, or induction skull melting process as is otherwise known, has the potential to produce high purity melts of a range of difficult to melt materials, including Ti–Al and Ti6Al4V alloys for Aerospace, Ti–Ta and other biocompatible materials for surgical implants, silicon for photovoltaic and electronic applications, etc. A water cooled AC coil surrounds the crucible causing induction currents to melt the alloy and partially suspend it against gravity away from water-cooled surfaces. Strong stirring takes place in the melt due to the induced electromagnetic Lorentz forces and very high temperatures are attainable under the right conditions (i.e., provided contact with water cooled walls is minimised). In a joint numerical and experimental research programme, various aspects of the design and operation of this process are investigated to increase our understanding of the physical mechanisms involved and to maximise process efficiency. A combination of FV and Spectral CFD techniques are used at Greenwich to tackle this problem numerically, with the experimental work taking place at Birmingham University. Results of this study, presented here, highlight the influence of turbulence and free surface behaviour on attained superheat and also discuss coil design variations and dual frequency options that may lead to winning crucible designs.

Maximising heat transfer efficiency in the cold crucible induction melting process

Induction heating is an efficient method used to melt electrically conductive materials, particularly if melting takes place in a ceramic crucible. This form of melting is particularly good for alloys, as electromagnetic forces set up by the induction coil lead to vigorous stirring of the melt ensuring homogeneity and uniformity in temperature. However, for certain reactive alloys, or where high purity is required, ceramic crucibles cannot be used, but a water-cooled segmented copper crucible is employed instead. Water cooling prevents meltdown or distortion of the metal wall, but much of the energy goes into the coolant. To reduce this loss, the electromagnetic force generated by the coil is used to push the melt away from the walls and so minimise contact with water-cooled surfaces. Even then, heat is lost through the crucible base where contact is inevitable. In a collaborative programme between Greenwich and Birmingham Universities, computer modelling has been used in conjunction with experiments to improve the superheat attainable in the melt for a,number of alloys, especially for y-TiAl intermetallics to cast aeroengine turbine blades. The model solves the discretised form of the turbulent Navier-Stokes, thermal energy conservation and Maxwell equations using a Spectral Collocation technique. The time-varying melt envelope is followed explicitly during the computation using an adaptive mesh. This paper briefly describes the mathematical model used to represent the interaction between the magnetic field, fluid flow, heat transfer and change of phase in the crucible and identifies the proportions of energy used in the melt, lost in the crucible base and in the crucible walls. The role of turbulence is highlighted as important in controlling heat losses and turbulence damping is introduced as a means of improving superheat. Model validation is against experimental results and shows good agreement with measured temperatures and energy losses in the cooling fluid throughout the melting cycle.

Experimental and numerical study of the cold crucible melting process

The cold crucible, or induction skull melting process as is otherwise known, has the potential to produce high purity melts of a range of difficult to melt materials, including Ti–Al and Ti6Al4V alloys for Aerospace, Ti–Ta and other biocompatible materials for surgical implants, silicon for photovoltaic and electronic applications, etc. A water cooled AC coil surrounds the crucible causing induction currents to melt the alloy and partially suspend it against gravity away from water-cooled surfaces. Strong stirring takes place in the melt due to the induced electromagnetic Lorentz forces and very high temperatures are attainable under the right conditions (i.e., provided contact with water cooled walls is minimised). In a joint numerical and experimental research programme, various aspects of the design and operation of this process are investigated to increase our understanding of the physical mechanisms involved and to maximise process efficiency. A combination of FV and Spectral CFD techniques are used at Greenwich to tackle this problem numerically, with the experimental work taking place at Birmingham University. Results of this study, presented here, highlight the influence of turbulence and free surface behaviour on attained superheat and also discuss coil design variations and dual frequency options that may lead to winning crucible designs.

Cold crucible melting of reactive metals using combined DC and AC magnetic fields

Cold crucible furnace is widely used for melting reactive metals for high quality castings. Although the water cooled copper crucible avoids contamination, it produces a low superheat of the melt. Experimental and theoretical investigations of the process showed that the increase of the supplied power to the furnace leads to a saturation in the temperature rise of the melt, and no significant increase of the melt superheat can be obtained. The computer model of theprocess has been developed to simulate the time dependent turbulent flow, heat transfer with phase change, and AC and DC magnetohydrodynamics in a time varying liquid metal envelope. The model predicts that the supermimposition of a strong DC field on top of the normal AC field reduces the level of turbulience and stirring in the liquid metal, thereby reducing the heat loss through the base of the crucible and increasing the superheat. The direct measurements of the temperature in the commercial size cold crucbile has confirmed the computer redictions and showed that the addition of a DC field increased the superheat in molten TiAl from ~45C (AC field only) to ~81C (DC+AC fields). The present paper reports further predictions of the effect of a dDC field on top of the AC field and compares these with experimental data.

Liquid metal induction heating modelling for cold crucible applications

The time dependent numerical model of cold crucible melting is based on the coupled electromagnetic, temperature and turbulent velocity field calculation accounting for the magnetically confined liquid metal shape continuous change. The model is applied to investigate the process energy efficiency dependence on the critical choice of AC power supply frequency and an optional addition of a DC magnetic field. Test cases of the metal load up to 50 kg are considered. The behaviour of the numerical model at high AC frequencies is instructively validated by the use of the electromagnetic analytical solution for a sphere and temperature measurements in a commercial size cold crucible furnace

Dynamic melting model for small samples in cold crucible

Purpose – A small size cold crucible offers possibilities for melting various electrically conducting materials with a minimal wall contact. Such small samples can be used for express contamination analysis, preparing limited amounts of reactive alloys or experimental material analyses. Aims to present a model to follow the melting process. Design/methodology/approach – The presents a numerical model in which different types of axisymmetric coil configurations are analysed. Findings – The presented numerical model permits dynamically to follow the melting process, the high-frequency magnetic field distribution change, the free surface and the melting front evolution, and the associated turbulent fluid dynamics. The partially solidified skin on the contact to the cold crucible walls and bottom is dynamically predicted. The segmented crucible shape is either cylindrical, hemispherical or arbitrary shaped. Originality/value – The model presented within the paper permits the analysis of melting times, melt shapes, electrical efficiency and particle tracks.

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.