Investigating core influence on transformers insulation diagnostics

In a healthy power transformer, the power factor (PF) of the low-voltage winding insulation to the ground (CL) is expected to be less than 0.5 %. In recent cases, the CL PF measured during the factory testing exhibited high values close or above 0.5 %. Investigations have determined that the issue might be related to a higher than usual core steel interlaminar resistance, occurring due to a combination of shorter burrs and higher non-uniform insulation resistance between laminations. This article describes the phenomena and proposes a test protocol to differentiate the problem from other issues that cause high CL PFs, such as moisture or contamination / deterioration of the insulation

Not Hydro: Using Neural Networks to estimate galaxy properties on a Dark-Matter-Only simulation

Using data from TNG300-2, we train a neural network (NN) to recreate the stellar mass ($M^*$) and star formation rate (SFR) of central galaxies in a dark-matter-only simulation. We consider 12 input properties from the halo and sub-halo hosting the galaxy and the near environment. $M^*$ predictions are robust, but the machine does not fully reproduce its scatter. The same happens for SFR, but the predictions are not as good as for $M^*$. We chained neural networks, improving the predictions on SFR to some extent. For SFR, we time-averaged this value between $z=0$ and $z=0.1$, which improved results for $z=0$. Predictions of both variables have trouble reproducing values at lower and higher ends. We also study the impact of each input variable in the performance of the predictions using a leave-one-covariate-out approach, which led to insights about the physical and statistical relation between input variables. In terms of metrics, our machine outperforms similar studies, but the main discoveries in this work are not linked with the quality of the predictions themselves, but to how the predictions relate to the input variables. We find that previously studied relations between physical variables are meaningful to the machine. We also find that some merger tree properties strongly impact the performance of the machine. %We highlight the value of machine learning (ML) methods in helping understand the information contained in different variables, since with its help we were able to obtain useful insights resulting from studying the impact of input variables on the resulting behaviour of galaxy properties. We conclude that ML models are useful tools to understand the significance of physical different properties and their impact on target characteristics, as well as strong candidates for potential simulation methods.Comment: 17 pages, 16 figures, to be published in MNRA

La franja aurífera de Xallas (Galicia occidental, España): Las mineralizaciones de Albores dentro de un contexto tectónico y metalogénico evolutivo.

Las mineralizaciones de oro de Albores (Galicia occidental) se encuadran dentro de una franja metalogénica N-S a NE de edad hercínica-tardihercínica (franja aurífera de Xallas). Dicha franja comprende una serie de indicios auríferos caracterizados por la presencia de una fase sulfurada rica en arsenopirita y otra metálica con oro/electrum. Estas mineralizaciones encajan generalmente en estructuras frágiles desarrolladas en zonas de cizalla de componente horizontal y vertical, que incluyen mílonitas, ultramilonitas, cataclasitas y brechas.Las mineralizaciones de Albores incluyen una paragénesis compleja consistente en arsenopirita, oro/electrum, pirrotina, marcasita, pirita, bismuto, bismutina, esfalerita, galena y calcopirita. Estudios de inclusionesfluidas en cuarzos acompañantes de la mineralización sugieren que ésta fue depositada por fluidos acuoso-carbónicos complejos de moderada baja salinidad (<56-9 por 100 eq. NaCI; salinidades máximas) operando en un rango de temperaturas epi a mesotermal (Th: 18Cl°-36Cl° CJ. Estas mineralizaciones se formaron durante un régimen extensional desarrollado durante el período comprendido entre la fase deformativa 3 hercínica (D3; Carbonífero Medio) y el episodio frágil tardihercínico (Carbonífero Superior/Pérmico Inferior}. La etapa extensional se caracterizó por el desarrollo de corredores miloníticos principalmente extensionales, de bajo ángulo (zona de cizalla de Xallas) con superposición de estructuras frágiles sobre la fábrica dúctil, estructuras antiformes, y fallas normales de gran ángulo de carácter frágil

Characterization of a biomethane-like synthetic gas mixture through accurate density measurements from (240 to 350) K and pressures up to 14 MPa

Producción CientíficaIn this work the thermodynamic behavior of a synthetic four-component biomethane-like mixture, composed mainly of methane (96.48%), with small amounts of carbon dioxide (2.00%), nitrogen (1.50%), and traces of oxygen (0.02%), is studied using accurate (p,ρ,T) experimental data. Two mixtures of identical nominal compositions were prepared by the gravimetric method at the Spanish National Metrology Institute (Centro Español de Metrología, CEM) and at the Slovak National Metrology Institute (Slovenský Metrologický Ústav, SMÚ). The composition was double checked by Gas Chromatography, at both NMI and at the beginning and end of the measurements. An additional test of the consistency of the given compositions was performed by measuring the density of both mixtures at selected points, with two different techniques, in two different laboratories. Accurate density measurements have been taken over a wide temperature range, from (240 to 350) K, and pressures up to 14 MPa, using a single-sinker densimeter with magnetic suspension coupling. Experimental data are compared with the densities calculated with the GERG-2008 and AGA8-DC92 equations of state. Deviations between experimental and GERG-2008-estimated densities are within a ±0.03% band at all temperatures, which shows the outstanding performance of the current reference equation for natural gases when describing a biomethane-like mixture. Deviations between experimental and AGA-8-estimated densities are higher than 0.04% at 250 K for pressures greater than 10 MPa and also at 240 K for pressures higher than 9 MPa. This work is part of the research project ‘Metrology for Biogas’ supported by the European Metrology Research Program.2019-06-152019-06-15ENE2013-47812-RJunta de Castilla y León VA035U16European Metrology Research Program ENG5

Cosmology with the SKA: theoretical prospectives

We briefly review the context of the SKA in the panorama of modern Cosmology. The SKA will undoubtedly be one of the most powerful tools for Cosmology during the first half of the XXIst century. Many of the fundamental questions of modern Cosmology, such as the nature of the dark energy and dark matter that dominate the dynamics of the Universe, will be answered by SKA-driven science. Moreover, SKA will shed light on many aspects of large-scale structure growth and galaxy formation as well as fundamental Physics regarding the early Universe, inflation and tests of General Relativity.The authors acknowledge partial support from the Spanish MINECO through projects AYA2013- 48623-C2-2, AYA2007-68058-C03-01, AYA2010-21766-C03-02, AYA2012-30789 and the Consolider-Ingenio projects CSD2010-00064 (EPI: Exploring the Physics of Inflation) and CSD2009-00064 (MultiDark), and from the Generalitat Valenciana through grants PROMETEOII/2014/060 and PROMETEOII/2014/084. RAL acknowledges the Spanish grant FPA2014-58183-P. CHM acknowledges the support of the Ramón y Cajal fellowship RyC 2011 148062 awarded by the Spanish MICINN and the Marie Curie Career Integration Grant CIG 294183.Peer reviewe

IODP workshop: developing scientific drilling proposals for the Argentina Passive Volcanic Continental Margin (APVCM) – basin evolution, deep biosphere, hydrates, sediment dynamics and ocean evolution

The Argentine margin contains important sedimentological, paleontological and chemical records of regional and local tectonic evolution, sea level, climate evolution and ocean circulation since the opening of the South Atlantic in the Late Jurassic–Early Cretaceous as well as the present-day results of post-depositional chemical and biological alteration. Despite its important location, which underlies the exchange of southern- and northern-sourced water masses, the Argentine margin has not been investigated in detail using scientific drilling techniques, perhaps because the margin has the reputation of being erosional. However, a number of papers published since 2009 have reported new high-resolution and/or multichannel seismic surveys, often combined with multi-beam bathymetric data, which show the common occurrence of layered sediments and prominent sediment drifts on the Argentine and adjacent Uruguayan margins. There has also been significant progress in studying the climatic records in surficial and near-surface sediments recovered in sediment cores from the Argentine margin. Encouraged by these recent results, our 3.5-day IODP (International Ocean Discovery Program) workshop in Buenos Aires (8–11 September 2015) focused on opportunities for scientific drilling on the Atlantic margin of Argentina, which lies beneath a key portion of the global ocean conveyor belt of thermohaline circulation. Significant opportunities exist to study the tectonic evolution, paleoceanography and stratigraphy, sedimentology, and biosphere and geochemistry of this margin.Facultad de Ciencias Naturales y Muse

Dynamic location of mobiles and obstacles for robotics applications

Usando algoritmos de procesamiento de imágenes y detección de movimientos se logró obtener la posición de dos móviles y de dos obstáculos fijos en un escenario en el cual se controlan las condiciones de color de los mismos. Para tal fin, se implementaron tres algoritmos, el primero de ellos se basa en los gradientes espacial y temporal para realizar la detección de los bordes de los objetos en movimiento dentro de la escena, el segundo es una detección en color, con la cual se identifica el color de los móviles y el tercero se basa en correlación de imágenes para realizar la búsqueda del objeto en movimiento. La detección de los obstáculos (objetos estáticos) para los tres algoritmos se realizó por medio de reconocimiento de un color característico en los obstáculos. Después de detectados los objetos de interés en la escena, se realiza su localización en la imagen por medio del centroide, para posteriormente entregar su posición y orientación en unidades de longitud.Using algorithms of processing of images and detection of movements was possible to obtain the position of two mobile objects and two fixed obstacles in a scene where they interact under controlled conditions of color. For such an end, three algorithms were implemented, the first of them is based on the spatial and temporal gradients to carry out the detection of the borders of the objects in movement inside the scene, the second is a detection in color, with which the color of the mobile objects is identified and the third is based on correlation of images to accomplish the search of the object in movement. The detection of the obstacles (static objects) for the three algorithms was carried out through recognition of a characteristic color in the obstacles. After having detected the objects of interest in the scene, is carried out their localization in the image through the centroide (center), for later on to give their position and orientation in centimeters

Localización dinámica de móviles y obstáculos para aplicaciones en robótica

Usando algoritmos de procesamiento de im&aacute;genes y detecci&oacute;n de movimientos se logr&oacute; obtener la posici&oacute;n de dos m&oacute;viles y de dos obst&aacute;culos fijos en un escenario en el cual se controlan las condiciones de color de los mismos. Para tal fin, se implementaron tres algoritmos, el primero de ellos se basa en los gradientes espacial y temporal para realizar la detecci&oacute;n de los bordes de los objetos en movimiento dentro de la escena, el segundo es una detecci&oacute;n en color, con la cual se identifica el color de los m&oacute;viles y el tercero se basa en correlaci&oacute;n de im&aacute;genes para realizar la b&uacute;squeda del objeto en movimiento. La detecci&oacute;n de los obst&aacute;culos (objetos est&aacute;ticos) para los tres algoritmos se realiz&oacute; por medio de reconocimiento de un color caracter&iacute;stico en los obst&aacute;culos. Despu&eacute;s de detectados los objetos de inter&eacute;s en la escena, se realiza su localizaci&oacute;n en la imagen por medio del centroide, para posteriormente entregar su posici&oacute;n y orientaci&oacute;n en unidades de longitud.Palabras Clave: An&aacute;lisis din&aacute;mico de im&aacute;genes, color, correlaci&oacute;n, gradientes, identificaci&oacute;n, segmentaci&oacute;n