3D modeling of high-T c superconductors by finite element software

A three-dimensional (3D) numerical model is proposed to solve the electromagnetic problems involving transport current and background field of a high-T c superconducting (HTS) system. The model is characterized by the E-J power law and H-formulation, and is successfully implemented using finite element software. We first discuss the model in detail, including the mesh methods, boundary conditions and computing time. To validate the 3D model, we calculate the ac loss and trapped field solution for a bulk material and compare the results with the previously verified 2D solutions and an analytical solution. We then apply our model to test some typical problems such as superconducting bulk array and twisted conductors, which cannot be tackled by the 2D models. The new 3D model could be a powerful tool for researchers and engineers to investigate problems with a greater level of complicity.

FPGA, physics-based modeling of IGBT and pin diode for hardware co-simulation of complex power electronic converters and systems

This paper presents the steps and the challenges for implementing analytical, physics-based models for the insulated gate bipolar transistor (IGBT) and the PIN diode in hardware and more specifically in field programmable gate arrays (FPGAs). The models can be utilised in hardware co-simulation of complex power electronic converters and entire power systems in order to reduce the simulation time without compromising the accuracy of results. Such a co-simulation allows reliable prediction of the system's performance as well as accurate investigation of the power devices' behaviour during operation. Ultimately, this will allow application-specific optimisation of the devices' structure, circuit topologies as well as enhancement of the control and/or protection schemes.

Design of brushless doubly-fed machines based: On magnetic circuit modeling

This paper proposes a magnetic circuit model (MCM) for the design of a brushless doubly-fed machine (BDFM). The BDFM possesses advantages in terms of high reliability and reduced gearbox stages, and it requires a fractionally-rated power converter. This makes it suitable for utilization in offshore wind turbines. It is difficult for conventional design methods to calculate the flux in the stator because the two sets of stator windings, which have different pole number, form a complex flux pattern which is not easily determined using common analytical approaches. However, it is advantageous to predict the flux density in the teeth and air-gap at the initial design stage for sizing purposes without recourse finite element analysis. Therefore a magnetic circuit model is developed in this paper to calculate the flux density. A BDFM is used as a case study with FEA validation. © 1965-2012 IEEE.

Development of a new apparatus for modeling deep excavation related problems in geotechnical centrifuge

Underground space is commonly exploited both to maximise the utility of costly land in urban development and to reduce the vertical load acting on the ground. Deep excavations are carried out to construct various types of underground infrastructure such as deep basements, subways and service tunnels. Although the soil response to excavation is known in principle, designers lack practical calculation methods for predicting both short- and long-term ground movements. As the understanding of how soil behaves around an excavation in both the short and long term is insufficient and usually empirical, the judgements used in design are also empirical and serious accidents are common. To gain a better understanding of the mechanisms involved in soil excavation, a new apparatus for the centrifuge model testing of deep excavations in soft clay has been developed. This apparatus simulates the field construction sequence of a multi-propped retaining wall during centrifuge flight. A comparison is given between the new technique and the previously used method of draining heavy fluid to simulate excavation in a centrifuge model. The new system has the benefit of giving the correct initial ground conditions before excavation and the proper earth pressure distribution on the retaining structures during excavation, whereas heavy fluid only gives an earth pressure coefficient of unity and is unable to capture any changes in the earth pressure coefficient of soil inside the zone of excavation, for example owing to wall movements. Settlements of the ground surface, changes in pore water pressure, variations in earth pressure, prop forces and bending moments in the retaining wall are all monitored during excavation. Furthermore, digital images taken of a cross-section during the test are analysed using particle image velocimetry to illustrate ground deformation and soil–structure interaction mechanisms. The significance of these observations is discussed.

Zonal RANS-LES modeling for turbines in aeroengines

The cost of large-eddy simulation (LES) modeling in various zones of gas turbine aeroengines is outlined. This high cost clearly demonstrates the need to perform hybrid Reynolds-averaged Navier-Stokes-LES (RANS-LES) over the majority of engine zones because the Reynolds number is too high for pure LES. The RANS layer is used to cover over the fine streaks found in the inner part of the boundary layer. The hybrid strategy is applied to various engine zones, which is shown to typically give much greater predictive accuracy than pure RANS simulations. However, the cost estimates show that the RANS layer should be disposed within the low-pressure turbine zone. Also, the nature of the flow physics in this zone makes LES most sensible. © 2012 by Begell House, Inc.

Strategies for modeling turbulent flows in electronics

Hybrid methods based on the Reynolds Averaged Navier Stokes (RANS) equations and the Large Eddy Simulation (LES) formulation are investigated to try and improve the accuracy of heat transfer and surface temperature predictions for electronics systems and components. Two relatively low Reynolds number flows are studied using hybrid RANS-LES, RANS-Implicit-LES (RANS-ILES) and non-linear LES models. Predictions using these methods are in good agreement with each other, even using different grid resolutions. © 2008 IEEE.

3D modeling of high temperature superconducting staggered array undulator

A 3-D model of a superconducting staggered array undulator has been built, which could serve as a powerful tool to solve electromagnetic problems and to realize field optimization of such design. Given the limitation of 2-D simulation for irregular shapes and complex geometries, 3-D models are more desirable for a comprehensive investigation. An optimization method for the undulator peak field is proposed; up to 32% enhancement can be achieved by introducing major segment bulks. Some improvements of the undulator design are obtained by careful analyzing of the simulation results. © 2002-2011 IEEE.

Evaluation and modeling of lanthanum diffusion in TiN/La 2O 3/HfSiON/SiO 2/Si high-k stacks

In this study, TiN/La 2O 3/HfSiON/SiO 2/Si gate stacks with thick high-k (HK) and thick pedestal oxide were used. Samples were annealed at different temperatures and times in order to characterize in detail the interaction mechanisms between La and the gate stack layers. Time-of-flight secondary ion mass spectrometry (ToF-SIMS) measurements performed on these samples show a time diffusion saturation of La in the high-k insulator, indicating an La front immobilization due to LaSiO formation at the high-k/interfacial layer. Based on the SIMS data, a technology computer aided design (TCAD) diffusion model including La time diffusion saturation effect was developed. © 2012 American Institute of Physics.

Modeling natural sounds with modulation cascade processes

Natural sounds are structured on many time-scales. A typical segment of speech, for example, contains features that span four orders of magnitude: Sentences ($\sim1$s); phonemes ($\sim10$−$1$ s); glottal pulses ($\sim 10$−$2$s); and formants ($\sim 10$−$3$s). The auditory system uses information from each of these time-scales to solve complicated tasks such as auditory scene analysis [1]. One route toward understanding how auditory processing accomplishes this analysis is to build neuroscience-inspired algorithms which solve similar tasks and to compare the properties of these algorithms with properties of auditory processing. There is however a discord: Current machine-audition algorithms largely concentrate on the shorter time-scale structures in sounds, and the longer structures are ignored. The reason for this is two-fold. Firstly, it is a difficult technical problem to construct an algorithm that utilises both sorts of information. Secondly, it is computationally demanding to simultaneously process data both at high resolution (to extract short temporal information) and for long duration (to extract long temporal information). The contribution of this work is to develop a new statistical model for natural sounds that captures structure across a wide range of time-scales, and to provide efficient learning and inference algorithms. We demonstrate the success of this approach on a missing data task.