Urban wind energy conversion: the potential of ducted turbines

The prospects for urban wind power are discussed. A roof-mounted ducted wind turbine, which uses pressure differentials created by wind flow around a building, is proposed as an alternative to more conventional approaches. Outcomes from tests at model and prototype scale are described, and a simple mathematical model is presented. Predictions from the latter suggest that a ducted turbine can produce very high specific power outputs, going some way to offsetting its directional sensitivity. Further predictions using climate files are made to assess annual energy output and seasonal variations, with a conventional small wind turbine and a photovoltaic panel as comparators. It is concluded that ducted turbines have significant potential for retro-fitting to existing buildings, and have clear advantages where visual impact and safety are matters of concern

Deployment of quality assurance procedures for digital library programmes

Many digital library programmes have a development philosophy based on use of open standards. In practice, however, projects may not have procedures in place to ensure that project deliverables make use of appropriate open standards. In addition there will be occasions when open standards are not sufficiently mature for deployment in a service environment or use of open standards will require expertise or resources which are not readily available

Nonlinear stability of the ensemble Kalman filter with adaptive covariance inflation

The Ensemble Kalman filter and Ensemble square root filters are data assimilation methods used to combine high dimensional nonlinear models with observed data. These methods have proved to be indispensable tools in science and engineering as they allow computationally cheap, low dimensional ensemble state approximation for extremely high dimensional turbulent forecast models. From a theoretical perspective, these methods are poorly understood, with the exception of a recently established but still incomplete nonlinear stability theory. Moreover, recent numerical and theoretical studies of catastrophic filter divergence have indicated that stability is a genuine mathematical concern and can not be taken for granted in implementation. In this article we propose a simple modification of ensemble based methods which resolves these stability issues entirely. The method involves a new type of adaptive covariance inflation, which comes with minimal additional cost. We develop a complete nonlinear stability theory for the adaptive method, yielding Lyapunov functions and geometric ergodicity under weak assumptions. We present numerical evidence which suggests the adaptive methods have improved accuracy over standard methods and completely eliminate catastrophic filter divergence. This enhanced stability allows for the use of extremely cheap, unstable forecast integrators, which would otherwise lead to widespread filter malfunction.Comment: 34 pages. 4 figure

Novel nanocomposite automotive temperature sensing technology

In recent years, automotive emissions legislation has been introduced and is rapidly becoming more stringent. With alternative vehicular propulsion methods far from becoming mainstream reality, leading automotive providers have intensified efforts in the direction of reducing the harmful footprint of their products. This is being accomplished via smaller, more optimally designed internal-combustion engines. A crucial means to that end is exhaust gas temperature monitoring and control. To enable such control, a mass-produced sensor, capable of operating reliably in the harsh automotive combustion environment, comprising a broad spectrum of high temperatures, severe shocks and a chemically aggressive ambient, has been used widely in the past decade, with performance demands growing constantly in line with advances in engine performance. This paper presents a technology overview of the potential of novel nano composite sensor design and manufacture using materials in an innovative way towards industrialising such a sensing solution. The presented sensor design implements the state-of-the-art in thick and thin film technology incorporating nano materials for improved strength, fabrication and performance properties

Fiscal Decentralisation and Economic Growth: A Bayesian Model Averaging Approach

This article re-examines the relationship between fiscal decentralisation and economic growth by employing Bayesian model averaging (BMA). BMA enables the consideration of a range of measures of fiscal decentralisation and allows the incorporation of model uncertainty into the empirical methodology. Posterior coefficient estimates suggest that not straightforward relationship exists between fiscal decentralisation and economic growth based on time-series data for Australia.