AC losses of superconducting racetrack coil in various magnetic conditions

High-temperature superconductors have created the opportunity for a step change in the technology of power applications. Racetrack superconducting coils made from YBCO coated conductors have been used in several engineering applications including SMES, rotor or stator windings of electric machines. AC loss is one of the most important factors that determine the design and performance of superconducting devices. In this paper, a numerical model is developed to calculate the AC losses in superconducting racetrack coils in different magnetic conditions. This paper first discusses the AC losses of the coils in self-field or external field only. It then goes to investigate the AC losses of the coils being exposed to AC ripple field and a DC background field. Finally, the AC losses of the coils carrying DC current and being exposed to AC field are calculated. These two scenarios correspond to using superconducting coils as the rotor field winding of an electric machine. © 2010 IEEE.

A review of TRIZ, and its benefits and challenges in practice

TRIZ (the theory of inventive problem solving) has been promoted by several enthusiasts as a systematic methodology or toolkit that provides a logical approach to developing creativity for innovation and inventive problem solving. The methodology, which emerged from Russia in the 1960s, has spread to over 35 countries across the world. It is now being taught in several universities and it has been applied by a number of global organisations who have found it particularly useful for spurring new product development. However, while its popularity and attractiveness appear to be on a steady increase, there are practical issues which make the use of TRIZ in practice particularly challenging. These practical difficulties have largely been neglected by TRIZ literature. This paper takes a step away from conventional TRIZ literature, by exploring not just the benefits associated with TRIZ knowledge, but the challenges associated with its acquisition and application based on practical experience. Through a survey, first-hand information is collected from people who have tried (successfully and unsuccessfully) to understand and apply the methodology. The challenges recorded cut across a number of issues, ranging from the complex nature of the methodology to underlying organisational and cultural issues which hinder its understanding and application. Another contribution of this paper, potentially useful for TRIZ beginners, is the indication of what tools among the several contained in the TRIZ toolkit would be most useful to learn first, based on their observed degree of usage by the survey respondents. © 2012 Elsevier Ltd. All rights reserved.

Slowness: an objective for spike-timing-dependent plasticity?

Our nervous system can efficiently recognize objects in spite of changes in contextual variables such as perspective or lighting conditions. Several lines of research have proposed that this ability for invariant recognition is learned by exploiting the fact that object identities typically vary more slowly in time than contextual variables or noise. Here, we study the question of how this "temporal stability" or "slowness" approach can be implemented within the limits of biologically realistic spike-based learning rules. We first show that slow feature analysis, an algorithm that is based on slowness, can be implemented in linear continuous model neurons by means of a modified Hebbian learning rule. This approach provides a link to the trace rule, which is another implementation of slowness learning. Then, we show analytically that for linear Poisson neurons, slowness learning can be implemented by spike-timing-dependent plasticity (STDP) with a specific learning window. By studying the learning dynamics of STDP, we show that for functional interpretations of STDP, it is not the learning window alone that is relevant but rather the convolution of the learning window with the postsynaptic potential. We then derive STDP learning windows that implement slow feature analysis and the "trace rule." The resulting learning windows are compatible with physiological data both in shape and timescale. Moreover, our analysis shows that the learning window can be split into two functionally different components that are sensitive to reversible and irreversible aspects of the input statistics, respectively. The theory indicates that irreversible input statistics are not in favor of stable weight distributions but may generate oscillatory weight dynamics. Our analysis offers a novel interpretation for the functional role of STDP in physiological neurons.

Acoustic analogy in swirling mean flow applied to predict rotor trailing-edge noise

The present study aims at accounting for swirling mean flow effects on rotor trailing-edge noise. Indeed, the mean flow in between the rotor and the stator of the fan or of a compressor stage is highly swirling. The extension of Ffowcs-Williams & Hawkings' acoustic analogy in a medium at rest with moving surfaces and of Goldstein's acoustic analogy in a circular duct with uniform mean flow to a swirling mean flow in an annular duct is introduced. It is first applied to tonal noise. In most cases, the swirl modifies the pressure distribution downstream of the fan. In several configurations, when the swirl is rather close to a solid body swirl, it is often sufficient to apply a simple Doppler effect correction when predicting the duct modes in uniform mean flow in order to predict accurately the noise radiated with swirl. However, in other realistic configurations, the swirling mean-flow effect cannot be addressed using this simple Doppler effect correction. Second, a rotor trailing-edge noise model accounting for both the effects of the annular duct and the swirling mean flow is developed and applied to a realistic fan rotor with different swirling and sheared mean flows (and as a result different associated blade stagger angles). The benchmark cases are built from the Boeing 18-inch Fan Rig Broadband Noise Test. In all cases the swirling mean flow has an effect. In some cases the a simple Doppler effect may address it, but, in other realistic configurations our acoustic analogy with swirl is needed. © 2012 by the authors. Published by the American Institute of Aeronautics and Astronautics, Inc.

Nanoscale light-matter interactions in atomic cladding waveguides.

Alkali vapours, such as rubidium, are being used extensively in several important fields of research such as slow and stored light nonlinear optics quantum computation, atomic clocks and magnetometers. Recently, there is a growing effort towards miniaturizing traditional centimetre-size vapour cells. Owing to the significant reduction in device dimensions, light-matter interactions are greatly enhanced, enabling new functionalities due to the low power threshold needed for nonlinear interactions. Here, taking advantage of the mature platform of silicon photonics, we construct an efficient and flexible platform for tailored light-vapour interactions on a chip. Specifically, we demonstrate light-matter interactions in an atomic cladding waveguide, consisting of a silicon nitride nano-waveguide core with a rubidium vapour cladding. We observe the efficient interaction of the electromagnetic guided mode with the rubidium cladding and show that due to the high confinement of the optical mode, the rubidium absorption saturates at powers in the nanowatt regime.