Influence of shock wave propagation on dielectric barrier discharge plasma actuator performance

Interest in plasma actuators as active flow control devices is growing rapidly due to their lack of mechanical parts, light weight and high response frequency. Although the flow induced by these actuators has received much attention, the effect that the external flow has on the performance of the actuator itself must also be considered, especially the influence of unsteady high-speed flows which are fast becoming a norm in the operating flight envelopes. The primary objective of this study is to examine the characteristics of a dielectric barrier discharge (DBD) plasma actuator when exposed to an unsteady flow generated by a shock tube. This type of flow, which is often used in different studies, contains a range of flow regimes from sudden pressure and density changes to relatively uniform high-speed flow regions. A small circular shock tube is employed along with the schlieren photography technique to visualize the flow. The voltage and current traces of the plasma actuator are monitored throughout, and using the well-established shock tube theory the change in the actuator characteristics are related to the physical processes which occur inside the shock tube. The results show that not only is the shear layer outside of the shock tube affected by the plasma but the passage of the shock front and high-speed flow behind it also greatly influences the properties of the plasma

Revealing the true partitioning character of zirconium in additively manufactured polycrystalline superalloys

International audienc

Development of measurement-based load models for the dynamic simulation of distribution grids

The advent of new types of loads, such as power electronics and the increased penetration of low-inertia motors in the existing distribution grids alter the dynamic behavior of conventional power systems. Therefore, more accurate dynamic, aggregate, load models are required for the rigorous assessment of the stability limits of modern distribution networks. In this paper, a measurement-based, input/output, aggregate load model is proposed, suitable for dynamic simulations of distribution grids. The new model can simulate complex load dynamics by employing variable-order transfer functions. The minimum required model order is automatically determined through an iterative procedure. The applicability and accuracy of the proposed model are thoroughly evaluated under distinct loading conditions and network topologies using measurements acquired from a laboratory-scale test setup. Furthermore, the performance of the proposed model is compared against other conventional load models, using the mean absolute percentage error

Quantification challenges for atom probe tomography of hydrogen and deuterium in zircaloy-4

Analysis and understanding of the role of hydrogen in metals is a significant challenge for the future of materials science, and this is a clear objective of recent work in the atom probe tomography (APT) community. Isotopic marking by deuteration has often been proposed as the preferred route to enable quantification of hydrogen by APT. Zircaloy-4 was charged electrochemically with hydrogen and deuterium under the same conditions to form large hydrides and deuterides. Our results from a Zr hydride and a Zr deuteride highlight the challenges associated with accurate quantification of hydrogen and deuterium, in particular associated with the overlap of peaks at a low mass-to-charge ratio and of hydrogen/deuterium containing molecular ions. We discuss possible ways to ensure that appropriate information is extracted from APT analysis of hydrogen in zirconium alloy systems that are important for nuclear power applications

mHealth system for the early detection of infectious diseases using biomedical signals

Latin American Congress on Automation and Robotics LACAR 2019, 30/10/2019-01/11/2019, Cali, Colombia.Detection at an early stage of an infection is a major clinical challenge. An infection that is not diagnosed in time can not only seriously affect the health of the infected patient, but also spread and initiate a contagious approach towards other people. This paper deals with mHealth system for medical care and pre-diagnosis. The developed mHealth system use an Android App that collects physiological signals from the patients with a portable and easy-to-use sensors kit. The focus of the work is put on being able to build a low-cost system that using a very small amounts of data (one set record per patient and day). The processed data are uploaded to an online database to train a clinical decision support system to automatically diagnose infections. The mHealth system may be operated by the same personnel on site not requiring to be medical or computational skilled at all. The implementation takes five kinds of measures simultaneously (Electrodermal Activity, Body Temperature, Blood Pressure, Heart Beat Rate and Oxygen Saturation (SPO2)). A real implementation has been tested and results confirm that the sampling process can be done very fast and steadily Finally, the App usability was tested, showing a fast learning curve and no significant differences are observable in learning time by people with different skills or age. These usability factors are key for the mHealth system success

Regional contributions of six preventable risk factors to achieving the 25 × 25 non-communicable disease mortality reduction target: a modelling study

Background Countries have agreed to reduce premature mortality from the four main non-communicable diseases (NCDs) by 25% from 2010 levels by 2025 (referred to as the 25 × 25 target). Countries also agreed on a set of global voluntary targets for selected NCD risk factors. Previous analyses have shown that achieving the risk factor targets can contribute substantially towards meeting the 25 × 25 mortality target at the global level. We estimated the contribution of achieving six of the globally agreed risk factor targets towards meeting the 25 × 25 mortality target by region. Methods We estimated the eff ect of achieving the targets for six risk factors (tobacco and alcohol use, salt intake, obesity, and raised blood pressure and glucose) on NCD mortality between 2010 and 2025. Our methods accounted for multicausality of NCDs and for the fact that, when risk factor exposure increases or decreases, the harmful or benefi cial eff ects on NCDs accumulate gradually. We used data for risk factor and mortality trends from systematic analyses of available country data. Relative risks for the eff ects of individual and multiple risks, and for change in risk after decreases or increases in exposure, were from reanalyses and meta-analyses of epidemiological studies. Findings The probability of dying between the ages 30 years and 70 years from the four main NCDs in 2010 ranged from 19% in the region of the Americas to 29% in southeast Asia for men, and from 13% in Europe to 21% in southeast Asia for women. If current trends continue, the probability of dying prematurely from the four main NCDs is projected to increase in the African region but decrease in the other fi ve regions. If the risk factor targets are achieved, the 25 × 25 target will be surpassed in Europe in both men and women, and will be achieved in women (and almost achieved in men) in the western Pacifi c; the regions of the Americas, the eastern Mediterranean, and southeast Asia will approach the target; and the rising trend in Africa will be reversed. In most regions, a more ambitious approach to tobacco control (50% reduction relative to 2010 instead of the agreed 30%) will contribute the most to reducing premature NCD mortality among men, followed by addressing raised blood pressure and the agreed tobacco target. For women, the highest contributing risk factor towards the premature NCD mortality target will be raised blood pressure in every region except Europe and the Americas, where the ambitious (but not agreed) tobacco reduction would have the largest benefi t. Interpretation No WHO region will meet the 25 × 25 premature mortality target if current mortality trends continue. Achieving the agreed targets for the six risk factors will allow some regions to meet the 25 × 25 target and others to approach it. Meeting the 25 × 25 target in Africa needs other interventions, including those addressing infectionrelated cancers and cardiovascular disease

A century of trends in adult human height

Being taller is associated with enhanced longevity, and higher education and earnings. We reanalysed 1472 population-based studies, with measurement of height on more than 18.6 million participants to estimate mean height for people born between 1896 and 1996 in 200 countries. The largest gain in adult height over the past century has occurred in South Korean women and Iranian men, who became 20.2 cm (95% credible interval 17.5–22.7) and 16.5 cm (13.3–19.7) taller, respectively. In contrast, there was little change in adult height in some sub-Saharan African countries and in South Asia over the century of analysis. The tallest people over these 100 years are men born in the Netherlands in the last quarter of 20th century, whose average heights surpassed 182.5 cm, and the shortest were women born in Guatemala in 1896 (140.3 cm; 135.8–144.8). The height differential between the tallest and shortest populations was 19-20 cm a century ago, and has remained the same for women and increased for men a century later despite substantial changes in the ranking of countries

Artificial-intelligence method for the derivation of generic aggregated dynamic equivalent models

Aggregated equivalent models for the dynamic analysis of active distribution networks (ADNs) can be efficiently developed using dynamic responses recorded through field measurements. However, equivalent model parameters are highly affected from the time-varying composition of power system loads and the stochastic behavior of distributed generators. Thus, equivalent models, developed through in situ measurements, are valid only for the operating conditions from which they have been derived. To overcome this issue, in this paper, a new method is proposed for the derivation of generic aggregated dynamic equivalent models, i.e., for equivalent models that can be used for the dynamic analysis of a wide range of network conditions. The method incorporates clustering and artificial neural network techniques to derive robust sets of parameters for a variable-order dynamic equivalent model. The effectiveness of the proposed method is evaluated using measurements recorded on a laboratory-scale ADN, while its performance is compared with a conventional technique. The corresponding results reveal the applicability of the proposed approach for the analysis and simulation of a wide range of distinct network conditions