A dynamic convergence control scheme for the solution of the radial equilibrium equation in through-flow analyses

One of the most frequently encountered numerical problems in scientific analyses is the solution of non-linear equations. Often the analysis of complex phenomena falls beyond the range of applicability of the numerical methods available in the public domain, and demands the design of dedicated algorithms that will approximate, to a specified precision, the mathematical solution of specific problems. These algorithms can be developed from scratch or through the amalgamation of existing techniques. The accurate solution of the full radial equilibrium equation (REE) in streamline curvature (SLC) through-flow analyses presents such a case. This article discusses the development, validation, and application of an 'intelligent' dynamic convergence control (DCC) algorithm for the fast, accurate, and robust numerical solution of the non-linear equations of motion for two-dimensional flow fields. The algorithm was developed to eliminate the large extent of user intervention, usually required by standard numerical methods. The DCC algorithm was integrated into a turbomachinery design and performance simulation software tool and was tested rigorously, particularly at compressor operating regimes traditionally exhibiting convergence difficulties (i.e. far off-design conditions). Typical error histories and comparisons of simulated results against experimental are presented in this article for a particular case study. For all case studies examined, it was found that the algorithm could successfully 'guide' the solution down to the specified error tolerance, at the expense of a slightly slower iteration process (compared to a conventional Newton-Raphson scheme). This hybrid DCC algorithm can also find use in many other engineering and scientific applications that require the robust solution of mathematical problems by numerical instead of analytical means

An Authorisation Scenario for S-OGSA

The Semantic Grid initiative aims to exploit knowledge in the Grid to increase the automation, interoperability and flexibility of Grid middleware and applications. To bring a principled approach to developing Semantic Grid Systems, and to outline their core capabilities and behaviors, we have devised a reference Semantic Grid Architecture called S-OGSA. We present the implementation of an S-OGSA observant semantically-enabled Grid authorization scenario, which demonstrates two aspects: 1) the roles of different middleware components, be them semantic or non-semantic, and 2) the utility of explicit semantics for undertaking an essential activity in the Grid: resource access control

Managing semantic Grid metadata in S-OGSA

Grid resources such as data, services, and equipment, are increasingly being annotated with descriptive metadata that facilitates their discovery and their use in the context of Virtual Organizations (VO). Making such growing body of metadata explicit and available to Grid services is key to the success of the VO paradigm. In this paper we present a model and management architecture for Semantic Bindings, i.e., firstclass Grid entities that encapsulate metadata on the Grid and make it available through predictable access patterns. The model is at the core of the S-OGSA reference architecture for the Semantic Grid

S-OGSA as a Reference Architecture for OntoGrid and for the Semantic Grid

The Grid aims to support secure, flexible and coordinated resource sharing through providing a middleware platform for advanced distributing computing. Consequently, the Grid’s infrastructural machinery aims to allow collections of any kind of resources—computing, storage, data sets, digital libraries, scientific instruments, people, etc—to easily form Virtual Organisations (VOs) that cross organisational boundaries in order to work together to solve a problem. A Grid depends on understanding the available resources, their capabilities, how to assemble them and how to best exploit them. Thus Grid middleware and the Grid applications they support thrive on the metadata that describes resources in all their forms, the VOs, the policies that drive then and so on, together with the knowledge to apply that metadata intelligently

Architectural Patterns for the Semantic Grid

The Semantic Grid reference architecture, S-OGSA, includes semantic provisioning services that are able to produce semantic annotations of Grid resources, and semantically aware Gridservices that are able to exploit those annotations in various ways. In this paper we describe the dynamic aspects of S-OGSA by presenting the typical patterns of interaction among these services. A use case for a Grid meta-scheduling service is used to illustrate how the patterns are applied in practice

The effect of upstream duct boundary layer growth and compressor blade lean angle variation on an axial compressor performance

The compressor of a gas turbine engine is extremely vulnerable on upstream duct- induced flow non-uniformities whether the duct is an engine intake or an interconnecting duct. This is justified by its position being literally an extension of the duct flow path, coupled to the fact that it operates under adverse pressure gradients. In particular, this study focuses on performance deviations between installed and uninstalled compressors. Test results acquired from a test bed installation will differ from those recorded when the compressor operates as an integral part of an engine. The upstream duct, whether an engine intake or an inter-stage duct, will affect the flow-field pattern ingested into the compressor. The case study presented here aims mostly at qualifying the effect of boundary layer growth along the upstream duct wall on compressor performance. Additionally, the compressor performance response on blade lean angle variation is also addressed, with the aim of acquiring an understanding as to how compressor blade lean angle changes interact with intake-induced flow non-uniformities. Such studies are usually conducted as part of the preliminary design phase. Consequently, experimental performance investigation is excluded at this stage of development, and therefore, computer-aided simulation techniques are used if not the only option for compressor performance prediction. Given the fact that many such design parameters need to be assessed under the time pressure exerted by the tight compressor development programme, the compressor flow simulation technique needs to provide reliable results while consuming the least possible computational time. Such a low computational time compressor flow simulation method, among others, is the two-dimensional streamline curvature (SLC) method, being also applied within the frame of reference of the current study. The paper is introduced by a brief discussion on SLC method. Then, a reference is made to the radial equilibrium equation, which is the mathematical basis of SOCRATES, a turbomachinery flow simulation tool that was used in this study. Subsequently, the influence of the upstream duct on the compressor inlet radial flow distribution is being addressed, with the aim of adjusting the compressor blade inlet lean angle, in order to minimize compressor performance deterioration. The paper concludes with a discussion of the results

Low seropositivity for SARS-CoV-2 antibodies among healthcare workers after the first COVID-19 pandemic wave in Greece

Objectives: To estimate the prevalence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) seropositivity among healthcare workers (HCWs) in Greece and to identify high-risk groups in healthcare facilities. Study design: The study design used in this study is a nationwide cross-sectional study. Methods: Data were collected from 1 June to 9 July 2020. HCWs in the Greek National Health System were offered a free SARS-CoV-2 IgG antibody test, regardless of symptoms. Results: Overall, 379 of 57,418 HCWs (0.66%, 95% confidence interval [CI]: 0.59–0.73) were positive for SARS-CoV-2 antibodies. The adjusted overall seroprevalence was 0.43% (95% CI: 0.35–0.51). We found that HCWs in non-reference hospitals for COVID-19 (odds ratio [OR]: 1.81, 95% CI: 1.23–2.64; P = 0.002) and reference hospitals for COVID-19 (OR: 1.66, 95% CI: 1.06–2.58; P = 0.03) were more likely to be seropositive than HCWs in primary care centres. Regarding professions, nurses (OR: 1.45, 95% CI: 1.07–1.98; P = 0.02), physicians (OR: 1.43, 95% CI: 1.06–1.93; P = 0.02), and administrative, cleaning and security staff (OR: 1.50, 95% CI: 1.09–2.06; P = 0.01) had a statistically higher chance of having a positive serology than laboratory employees. Conclusions: The adjusted overall seroprevalence found in this study indicates a very low prevalence of SARS-CoV-2 among HCWs in Greece. This result is in line with the low incidence of COVID-19 during the first wave of the pandemic and is a direct benefit from the early implementation of lockdown. © 2021 The Royal Society for Public Healt

Low seropositivity for SARS-CoV-2 antibodies among healthcare workers after the first COVID-19 pandemic wave in Greece

Objectives: To estimate the prevalence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) seropositivity among healthcare workers (HCWs) in Greece and to identify high-risk groups in healthcare facilities. Study design: The study design used in this study is a nationwide cross-sectional study. Methods: Data were collected from 1 June to 9 July 2020. HCWs in the Greek National Health System were offered a free SARS-CoV-2 IgG antibody test, regardless of symptoms. Results: Overall, 379 of 57,418 HCWs (0.66%, 95% confidence interval [CI]: 0.59-0.73) were positive for SARS-CoV-2 antibodies. The adjusted overall seroprevalence was 0.43% (95% CI: 0.35-0.51). We found that HCWs in non-reference hospitals for COVID-19 (odds ratio [OR]: 1.81, 95% CI: 1.23-2.64; P = 0.002) and reference hospitals for COVID-19 (OR: 1.66, 95% CI: 1.06-2.58; P = 0.03) were more likely to be seropositive than HCWs in primary care centres. Regarding professions, nurses (OR: 1.45, 95% CI: 1.07-1.98; P = 0.02), physicians (OR: 1.43, 95% CI: 1.06-1.93; P = 0.02), and administrative, cleaning and security staff (OR: 1.50, 95% CI: 1.09-2.06; P = 0.01) had a statistically higher chance of having a positive serology than laboratory employees. Conclusions: The adjusted overall seroprevalence found in this study indicates a very low prevalence of SARS-CoV-2 among HCWs in Greece. This result is in line with the low incidence of COVID-19 during the first wave of the pandemic and is a direct benefit from the early implementation of lockdown. (C) 2021 The Royal Society for Public Health. Published by Elsevier Ltd. All rights reserved

Using Web Service Technologies to Create an Information Broker

No description supplie

Proving the concept of a data broker as an emergent alternative to supra-enterprise EPR systems

Electronic Patient Records systems configured into large enterprise models have become the assumed best route forward. In England, as in several other countries, this has expanded to a major meta-enterprise procurement programme. However, concerns are raised that such systems lack user ownership, and experience from other sectors shows difficulties with large enterprise systems. At a time of great change and once again shifting organizations, is this move simply building large and ponderous edifices with unstable materials? Latest software engineering research is now demonstrating the potential of an alternative model, enabling trusted information brokers to search out in real time at point of use data held in registered local and departmental systems. If successful, this could enable a new and less cumbersome paradigm. The data could move where needed whatever the service configuration. A concept demonstrator has been built set in the context of health and social care in England. It is important for all technological support to the health sector to be reviewed as new technologies emerge so as to identify and exploit new opportunities, and the results of this 3 year project show that the health record information broker route merits further investigative research