AC and DC magnetic levitation: melting, fluid flow and oscillations

The presented numerical modelling for the magnetic levitation involves coupling of the electromagnetic field, liquid shape change, fluid velocities and the temperature field at every time step during the simulation in time evolution. Combination of the AC and DC magnetic fields can be used to achieve high temperature, stable levitation conditions. The oscillation frequency spectra are analysed for droplets levitated in AC and DC magnetic fields at various combinations. An electrically poorly conducting, diamagnetic droplet (e.g. water) can be stably levitated using the dia- and para-magnetic properties of the sample material in a high intensity, gradient DC field.

Coupled 3-D finite difference time domain and finite volume methods for solving microwave heating in porous media

Computational results for the microwave heating of a porous material are presented in this paper. Combined finite difference time domain and finite volume methods were used to solve equations that describe the electromagnetic field and heat and mass transfer in porous media. The coupling between the two schemes is through a change in dielectric properties which were assumed to be dependent both on temperature and moisture content. The model was able to reflect the evolution of temperature and moisture fields as the moisture in the porous medium evaporates. Moisture movement results from internal pressure gradients produced by the internal heating and phase change.

Dynamic evolution in information sharing networks

This study examines the roll-out of a collaborative information repository or 'knowledge-base' in a medium-sized UK professional services firm over a six year period. Data from usage logs provides the basis for analysis of the dynamic evolution of social networks around the depository during this time. The adoption pattern follows an 's-curve' and usage exhibits something of a power law distribution, both attributable to network effects and network opposition is associated with organisational performance on a number of indicators. But periodicity in usage is evident and the usage distribution displays an exponential cut-off. Fourier analysis provides some evidence of mathematical complexity in the periodicity. Some implications of complex patterns in social network data for research and management are discussed.