3D hp-adaptive finite element simulations of a magic-T electromagnetic waveguide structure

This paper employs a 3D hp self-adaptive grid-refinement finite element strategy for the solution of a particular electromagnetic waveguide structure known as Magic-T. This structure is utilized as a power divider/combiner in communication systems as well as in other applications. It often incorporates dielectrics, metallic screws, round corners, and so on, which may facilitate its construction or improve its design, but significantly difficult its modeling when employing semi-analytical techniques. The hp-adaptive finite element method enables accurate modeling of a Magic-T structure even in the presence of these undesired materials/geometries. Numerical results demonstrate the suitability of the hp-adaptive method for modeling a Magic-T rectangular waveguide structure, delivering errors below 0.5% with a limited number of unknowns. Solutions of waveguide problems delivered by the self-adaptive hp-FEM are comparable to those obtained with semi-analytical techniques such as the Mode Matching method, for problems where the latest methods can be applied. At the same time, the hp-adaptive FEM enables accurate modeling of more complex waveguide structures.

Temperature performance of AlGaN/GaN MOS-HEMTs on Si substrates using Gd2O3 as gate dielectric

GaN based high electron mobility transistors have draw great attention due to its potential in high temperature, high power and high frequency applications [1, 2]. However, significant gate leakage current is still one of the issues which need to be solved to improve the performance and reliability of the devices [3]. Several research groups have contributed to solve this problem by using metal–oxide–semiconductor HEMTs (MOSHEMTs), with a thin dielectric layer, such as SiO2 [4], Al2O3 [5], HfO2 [6] and Gd2O3 [7] between the gate and the barrier layer on AlGaN/GaN heterostructures. Gd2O3 has shown low interfacial density of states(Dit) with GaN and a high dielectric constant and low electrical leakage currents [8], thus is considered as a promising candidate for the gate dielectrics on GaN. MOS-HEMTs using Gd2O3 grown by electron-beam heating [7] or molecular beam epitaxy (MBE) [8] on GaN or AlGan/GaN structure have been investigated, but further research is still needed in Gd2O3 based AlGaN/GaN MOSHEMTs.

A clustering technique for partial discharge and noise sources identification in power cables by means of waveform parameters

On-line partial discharge (PD) measurements have become a common technique for assessing the insulation condition of installed high voltage (HV) insulated cables. When on-line tests are performed in noisy environments, or when more than one source of pulse-shaped signals are present in a cable system, it is difficult to perform accurate diagnoses. In these cases, an adequate selection of the non-conventional measuring technique and the implementation of effective signal processing tools are essential for a correct evaluation of the insulation degradation. Once a specific noise rejection filter is applied, many signals can be identified as potential PD pulses, therefore, a classification tool to discriminate the PD sources involved is required. This paper proposes an efficient method for the classification of PD signals and pulse-type noise interferences measured in power cables with HFCT sensors. By using a signal feature generation algorithm, representative parameters associated to the waveform of each pulse acquired are calculated so that they can be separated in different clusters. The efficiency of the clustering technique proposed is demonstrated through an example with three different PD sources and several pulse-shaped interferences measured simultaneously in a cable system with a high frequency current transformer (HFCT).