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.

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.

Deriving explanations from partial temporal information

The representation and manipulation of natural human understanding of temporal phenomena is a fundamental field of study in Computer Science, which aims both to emulate human thinking, and to use the methods of human intelligence to underpin engineering solutions. In particular, in the domain of Artificial Intelligence, temporal knowledge may be uncertain and incomplete due to the unavailability of complete and absolute temporal information. This paper introduces an inferential framework for deriving logical explanations from partial temporal information. Based on a graphical representation which allows expression of both absolute and relative temporal knowledge in incomplete forms, the system can deliver a verdict to the question if a given set of statements is temporally consistent or not, and provide understandable logical explanation of analysis by simplified contradiction and rule based reasoning.

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.

Radio propagation modeling for capacity optimization in wireless relay MIMO systems with partial CSI

The enormous growth of wireless communication systems makes it important to evaluate the capacity of such channels. Multiple Input Multiple Output (MIMO) wireless communication systems are shown to yield significant performance improvement to data rates when compared to the traditional Single Input Single Output (SISO) wireless systems. The benefits of multiple antenna elements at the transmitter and receiver have become necessary to the research and the development of the next generation of mobile communication systems. In this paper we propose the use of Relaying MIMO wireless communication systems for use over long throughput. We investigate how Relays can be used in a "demodulate-and-forward" operation when the transmitter is equipped with spatially correlated multiple antenna elements and the receiver has only partial knowledge of the statistics of the channel. We show that Relays between the source and destination nodes of a wireless communication system in MIMO configuration improve the throughput of the system when compared to the typical MIMO systems, or achieve the desired channel capacity with significantly lower power resources needed.