This paper focuses on proximity losses prediction in conductors of power electronics transformers. The method is based on the concept of equivalent complex permeability applied to rectangular conductors. A 1-D analytical model is analyzed. It has been shown that the 1-D model does not take into account edge effects. Two complementary approaches have been proposed. One treats scattered conductors; other deals with package of conductors. Both approaches are compared with a good accuracy and economic computation time

Distance magnetic nanoparticle detections were investigated by using a magnetoelectric based magnetic sensor with a long type bilayer Metglas/PZT laminate composite. In homogeneous magnetic fields, the sensor exhibits a sensitivity of 307.4 mV/Oe, which is possible for a detection limit of 2.7 × 10⁻⁷ emu. This sensor can detect an amount of 0.31 μg of the superparamagnetic Fe₃O₄-chitosan fluid at 2 mm height above the sensor surface. To detect a spot with magnetic nanoparticles at a distance of about 7.6 mm, it should contain at least 50 μg of iron oxide. This approach can develop the local detection of magnetic nanoparticles at a depth of centimeters in the body during clinical interventions.

The approach of magnetic scalar potential T/sub 0//spl phi/-/spl phi/ is widely popular for solving magnetic problems coupled with electric circuits. However, cuts are required to preserve the Ampere's law for the case of ferromagnetic circuits with holes surrounded by coils. The manual definition of cuts might not be evident even for experimented finite-element (FE) users. This paper presents a new automatic cuts generation algorithm. First, we present a tool that allows determining if a ferromagnetic region has holes or not. If holes are found, the region is then inflated to get automatically needed cuts. The presented algorithm is also applicable to generate electric cuts in massive conductors.