Comparison of two parallel/series flow turbofan propulsion concepts for supersonic V/STOL

The thrust, specific fuel consumption, and relative merits of the tandem fan and the dual reverse flow front fan propulsion systems for a supersonic V/STOL aircraft are discussed. Consideration is given to: fan pressure ratio, fan air burning, and variable core supercharging. The special propulsion system components required are described, namely: the deflecting front inlet/nozzle, the aft subsonic inlet, the reverse pitch fan, the variable core supercharger and the low pressure forward burner. The potential benefits for these unconventional systems are indicated

Design and Application of Distributed Economic Model Predictive Control for Large-Scale Building Temperature Regulation

Although recent research has suggested model predictive control as a promising solution for minimizing energy costs of commercial buildings, advanced control systems have not been widely deployed in practice. Large-scale implementations, including industrial complexes and university campuses, may contain thousands of air handler units each serving a multiplicity of zones. A single centralized control system for these applications is not desirable. In this paper, we propose a distributed control system to economically optimize temperature regulation for large-scale commercial building applications. The decomposition strategy considers the complexities of thermal energy storage, zone interactions, and chiller plant equipment while remaining computationally tractable. One of the primary benefits of the proposed formulation is that the low-level airside problem can be decoupled and solved in a distributed manner; hence, it can be easily extended to handle large applications. Peak demand charges, a major source of coupling, are included. The interactions of the airside system with the waterside system are also considered, including discrete decisions, such as turning chillers on and off. To deploy such a control scheme, a system model is required. Since using physical knowledge about building models can greatly reduce the number of parameters that must be identified, grey-box models are recommended to reduce the length of expensive identification testing. We demonstrate the effectiveness of this control system architecture and identification procedure via simulation studies

What makes it so hard to look and to listen? Exploring the use of the Cognitive and Affective Supervisory Approach with children’s social work managers

This paper reports on the findings of an ESRC-funded Knowledge Exchange project designed to explore the contribution of an innovative approach to supervision to social work practitioners’ assessment and decision-making practices. The Cognitive and Affective Supervisory Approach (CASA) is informed by cognitive interviewing techniques originally designed to elicit best evidence from witnesses and victims of crime. Adapted here for use in childcare social work supervision contexts, this model is designed to enhance the quantity and quality of information available for decision-making. Facilitating the reporting of both ‘event information’ and ‘emotion information’, it allows a more detailed picture to emerge of events, as recalled by the individual involved, and the meaning they give to them. Practice supervisors from Children’s Services in two local authorities undertook to introduce the CASA into supervision sessions and were supported in this through the provision of regular reflective group discussions. The project findings highlight the challenges for practitioners of ‘detailed looking’ and for supervisors of ‘active listening’. The paper concludes by acknowledging that the CASA’s successful contribution to decision-making is contingent on both the motivation and confidence of supervisors to develop their skills and an organisational commitment to, and resourcing of, reflective supervisory practices and spaces

Insect Controls for Organic Gardeners.

10 p

A Cross-Lingual Similarity Measure for Detecting Biomedical Term Translations

Bilingual dictionaries for technical terms such as biomedical terms are an important resource for machine translation systems as well as for humans who would like to understand a concept described in a foreign language. Often a biomedical term is first proposed in English and later it is manually translated to other languages. Despite the fact that there are large monolingual lexicons of biomedical terms, only a fraction of those term lexicons are translated to other languages. Manually compiling large-scale bilingual dictionaries for technical domains is a challenging task because it is difficult to find a sufficiently large number of bilingual experts. We propose a cross-lingual similarity measure for detecting most similar translation candidates for a biomedical term specified in one language (source) from another language (target). Specifically, a biomedical term in a language is represented using two types of features: (a) intrinsic features that consist of character n-grams extracted from the term under consideration, and (b) extrinsic features that consist of unigrams and bigrams extracted from the contextual windows surrounding the term under consideration. We propose a cross-lingual similarity measure using each of those feature types. First, to reduce the dimensionality of the feature space in each language, we propose prototype vector projection (PVP)—a non-negative lower-dimensional vector projection method. Second, we propose a method to learn a mapping between the feature spaces in the source and target language using partial least squares regression (PLSR). The proposed method requires only a small number of training instances to learn a cross-lingual similarity measure. The proposed PVP method outperforms popular dimensionality reduction methods such as the singular value decomposition (SVD) and non-negative matrix factorization (NMF) in a nearest neighbor prediction task. Moreover, our experimental results covering several language pairs such as English–French, English–Spanish, English–Greek, and English–Japanese show that the proposed method outperforms several other feature projection methods in biomedical term translation prediction tasks

Energy Savings in Food Processing Dehumidification

Food processors have the unique responsibility of maintaining environmental, process and sanitation standards for government and consumers. Usually the food plant is a large facility with many sources of contamination, all of which must be controlled. Condensation is a significant source of problems and on critical surfaces is not tolerated by the USDA. This challenges the Engineer to provide an energy efficient system to prevent condensation in our hot and humid climate. The problem is intensified because the building is frequently operating below the ambient dew point. Dally sanitation wash-downs are a further contributor to condensation, and failure to control condensation may result in product contamination and rejection, plant shutdown, loss of labor and, in extreme cases, litigation. Past solutions have included excess ammonia refrigeration tonnage, high ventilation rates prescribed by the USDA - often inadequate for this climate - or chemical dehumidification, which is energy intensive and often mechanically unreliable. For a decade, the authors have utilized sensible exchangers to enhance latent transfer for moisture removal in supermarkets, breweries, and HVAC applications. The correct application of these techniques results in improved moisture removal and significant energy savings. Presented here will be the results of a dehumidification test in a low temperature food processing application

Coupled Cluster Externally Corrected by Adaptive Configuration Interaction

An externally corrected coupled cluster (CC) method, where an adaptive configuration interaction (ACI) wave function provides the external cluster amplitudes, named ACI-CC, is presented. By exploiting the connection between configuration interaction and coupled cluster through cluster analysis, the higher-order T3 and T4 terms obtained from ACI are used to augment the T1 and T2 amplitude equations from traditional coupled cluster. These higher-order contributions are kept frozen during the coupled cluster iterations and do not contribute to an increased cost with respect to CCSD. We have benchmarked this method on three closed-shell systems: beryllium dimer, carbonyl oxide, and cyclobutadiene, with good results compared to other corrected coupled cluster methods. In all cases, the inclusion of these external corrections improved upon the "gold standard" CCSD(T) results, indicating that ACI-CCSD(T) can be used to assess strong correlation effects in a system and as an inexpensive starting point for more complex external corrections

Insect Controls for Organic Gardeners.

11 p

SHCal13 Southern Hemisphere calibration, 0–50,000 years cal BP

The Southern Hemisphere SHCal04 radiocarbon calibration curve has been updated with the addition of new data sets extending measurements to 2145 cal BP and including the ANSTO Younger Dryas Huon pine data set. Outside the range of measured data, the curve is based upon the Northern Hemisphere data sets as presented in IntCal13, with an interhemispheric offset averaging 43 ± 23 yr modeled by an autoregressive process to represent the short-term correlations in the offset