5 resultados para dynamic causal modeling

em Greenwich Academic Literature Archive - UK


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In semilevitation melting, a cylindrical metal ingot is melted by a coaxial a.c. induction coil. A watercooled solid base supports the ingot, while the top and side free surface is confined by the magnetic forces as the melting front progresses. The dynamic interplay between gravity, hydrodynamic stress, and the Lorentz force in the fluid determines the instantaneous free surface shape. The coupled nonstationary equations for turbulent flow, heat with phase change, and high-frequency electromagnetic field are solved numerically for the axisymmetric time-dependent domain by a continuous mesh transformation, using a pseudospectral method. Results are obtained for the two actually existing coil configurations and several validation cases.

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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.

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Self-alignment of soldered electronic components such as flip-chips (FC), ball grid arrays (BGA) and optoelectronic devices during solder reflow is important as it ensures good alignment between components and substrates. Two uncoupled analytical models are presented which provide estimates of the dynamic time scales of both the chip and the solder in the self-alignment process. These predicted time scales can be used to decide whether a coupled dynamic analysis is required for the analysis of the chip motion. In this paper, we will show that for flip-chips, the alignment dynamics can be described accurately only when the chip motion is coupled with the solder motion because the two have similar time-scale values. To study this coupled phenomenon, a dynamic modeling method has been developed. The modeling results show that the uncoupled and coupled calculations result in significantly different predictions. The calculations based on the coupled model predict much faster rates of alignment than those predicted using the uncoupled approach.

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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.