Estudio de iones de Zr, Cd y Ag mediante espectrometría de ruptura inducida por láser

En este trabajo se ha hecho un estudio de los iones ZrIII, CdII y AgII mediante la técnica de la espectrometría de ruptura inducida por láser (LIBS). Para ello, se ha llevado a cabo la puesta a punto de un sistema de adquisición de espectros de emisión de plasmas producidos por láser y se ha obtenido la respuesta espectral del citado sistema en el rango de los 1900 a los 7000 Å. Se ha realizado un estudio espectroscópico de los diferentes plasmas empleados. De esta forma se han determinado parámetros de ellos tales como su composición, su temperatura o la densidad de electrones y la autoabsorción que presentaban. También, y gracias a los parámetros mencionados, se ha determinado si los plasmas estaban en Equilibrio Termodinámico Local y si eran ópticamente delgados.Se han medido experimentalmente las probabilidades de transición de las transiciones que parten de los niveles 4d5d y 4d5p del ZrIII, de los niveles 5p, 5d, 6s, 4d95s2, 6p, 4d95s5p, 4f, 7p, 5f y 8p del CdII y de los niveles 5s2 y 6s 3D3 de la AgII. Estos experimentos se han realizado con oxido de zirconio y una aleación de Zr-Cu para el caso del ZrIII, con cadmio puro y una aleación de Cd-Zn para el caso del CdII y con plata pura para el caso de la AgII. También se han calculado teóricamente mediante el método de Hartree-Fock relativista con mezcla de configuraciones las probabilidades de transición y las vidas medias de los niveles anteriormente mencionados del ZrIII y CdII

Montera: A Framework for Efficient Execution of Monte Carlo Codes on Grid Infrastructures

he objective of this work is to improve the performance of Monte Carlo codes on Grid production infrastructures. To do so, the codes and the grid sites are characterized with simple parameters to model their behaviors. Then, a new performance model for grid infrastructures is proposed, and an algorithm that employs this information is described. This algorithm dynamically calculates the number and size of tasks to execute on each site to maximize the performance and reduce makespan. Finally, a newly developed framework called Montera is presented. Montera deals with the execution of Monte Carlo codes in an unattended way, isolating the complexity of the problem from the final user. By employing two fusion Monte Carlo codes as example cases, along with the described characterizations and scheduling algorithm, a performance improvement up to 650 % over current best results is obtained on a real production infrastructure, together with enhanced stability and robustness

Enhancing Energy Production with Exascale HPC Methods

High Performance Computing (HPC) resources have become the key actor for achieving more ambitious challenges in many disciplines. In this step beyond, an explosion on the available parallelism and the use of special purpose processors are crucial. With such a goal, the HPC4E project applies new exascale HPC techniques to energy industry simulations, customizing them if necessary, and going beyond the state-of-the-art in the required HPC exascale simulations for different energy sources. In this paper, a general overview of these methods is presented as well as some specific preliminary results.The research leading to these results has received funding from the European Union's Horizon 2020 Programme (2014-2020) under the HPC4E Project (www.hpc4e.eu), grant agreement n° 689772, the Spanish Ministry of Economy and Competitiveness under the CODEC2 project (TIN2015-63562-R), and from the Brazilian Ministry of Science, Technology and Innovation through Rede Nacional de Pesquisa (RNP). Computer time on Endeavour cluster is provided by the Intel Corporation, which enabled us to obtain the presented experimental results in uncertainty quantification in seismic imagingPostprint (author's final draft

Problem solving as a way of learning Civil Law

Enlace del libro en Editorial US: https://editorial.us.es/es/detalle-libro/720286/ciclos-de-mejora-en-el-aula-ano-2020 DOI del libro: https://dx.doi.org/10.12795/978844723100

Evolution of the maintainability of HPC facilities at CIEMAT headquarters

Desde su creación en 1951, el CIEMAT ha estado impulsando continuamente el uso de la computación como un método de investigación, desplegando plataformas de cómputo innovadoras. De esta manera, arquitecturas vectoriales, MPP, NUMA y otras completamente distribuidas han sido gestionadas en el CIEMAT, acumulando un extenso conocimiento sobre su sostenibilidad y sobre las necesidades de las comunidades científicas relacionadas con proyectos internacionales. Actualmente, la evolución del hardware y el software para HPC es cada vez más rápida e implica un desafío constante para aumentar su disponibilidad debido al número de iniciativas que el centro apoya. Para abordar esta tarea, el equipo TIC ha estado cambiando su gestión hacia un modelo flexible, con una mirada puesta en las adquisiciones futuras.Since its establishment in 1951, CIEMAT has been continuously boosting the use of computation as a research method, deploying innovative computing facilities. Hence, Vectorial, MPP, NUMA, and distributed architectures have been managed at CIEMAT, resulting in an extensive expertise on HPC maintainability as well as on the computational needs of the community related to international projects. Nowadays, the evolution of HPC hardware and software is progressively faster and implies a continuous challenge to increase their availability for the greater number of different initiatives supported. To address this task, the ICT team has been changing towards a flexible management model, with a look toward future acquisitions

Patrimonio académico como herramienta para el desarrollo de futuras carreras científicas

Desde hace tiempo la Unión Europea busca y fomenta la cooperación entre la Universidad y los Institutos de Educación Secundaria para el desarrollo de futuras carreras científicas. Después de varios proyectos de investigación competitivos desarrollados por separado, hemos encontrado importantes confluencias entre el patrimonio custodiado por la Universidad Complutense y el IES San Isidro; ambas instituciones cuentan con una larga historia y atesoran un patrimonio científico, artístico y educativo de gran interés que es necesario conectar y poner en valor. La universidad ha desarrollado varios programas de cooperación en varios niveles y muchas de ellos planteaban mostrar y experimentar con el fin de descubrir, propuesta en la que queremos ahondar y avanzar a través del patrimonio educativo

CHAIN-REDS DART Challenge

CHAIN-REDS (Coordination and Harmonisation of Advanced e-infrastructure for Research and Education Data Sharing) is EU project focused on promoting and supporting technological and scientific collaboration across different communities established in various continents. Nowadays, one of the most challenging scenarios scientist and scientific communities are facing is huge amount of data emerging from vast networks of sensors and form computational simulations performed in a diversity of computing architectures and e-infrastructure. The new knowledge coming out from the interpretation of these datasets, reported on the scholar literature, is increasingly problematic to be reproducible due to the difficulty to access measured data repositories and/or computational applications that generate synthetic data through computer simulations. This paper presents CHAIN REDS approach, several tools and services, based on the adoption of standards, aimed at providing easy/seamless access to datasets, data repositories, open access document repositories and to the applications that could make use of them. All these tools and services are enclosed in what we have called the Data Accessibility, Reproducibility and Trustworthiness (DART) challenge. This initiative allows researchers to easily find data of his interest and directly use them in a code running by means of a Science Gateway (SG) that provides access to cluster, Grid and Cloud infrastructure worldwide. In this scenario, the datasets are found by means of either the CHAIN-REDS Knowledge Base (KB) or the Semantic Search Engine (SSE), the applications ran on the CHAIN-REDS SG, accessible through an Identity Federation. The datasets can be both identified by Persistent Identifier (PID) and assigned unique number ID. Scientists can then access the data and the corresponding application in order to either reproduce and extend the results of a given study or start a new investigation. The new data (and the new paper if any) are stored on the Data Infrastructure and can be easily found by the people belonging to the same domain making possible to start the cycle again.Repositório de dados científicos.Ibero-American Science and Technology Education Consortium (ISTEC

Rendimiento académico de los estudios de informática en algunos centros españoles

Se presentan los resultados de un estudio sobre el rendimiento académico de los estudios de Informática (ingenierías técnicas e ingeniería superior) en ocho universidades públicas españolas. Se estudian separadamente los alumnos de nuevo ingreso y el total de alumnos de una titulación, desagregados por sexo, edad, procedencia y nota de ingreso. Se calculan valores medios y agregados para cada titulación, teniendo en cuenta que cada una de las universidades participantes aportó aquellos datos de los que podía disponer. Los indicadores calculados se refieren a tasas de éxito, rendimiento, abandono, demanda en 1ª opción y duración media de los estudios.Peer Reviewe

Applying future Exascale HPC methodologies in the energy sector

The appliance of new exascale HPC techniques to energy industry simulations is absolutely needed nowadays. In this sense, the common procedure is to customize these techniques to the specific energy sector they are of interest in order to go beyond the state-of-the-art in the required HPC exascale simulations. With this aim, the HPC4E project is developing new exascale methodologies to three different energy sources that are the present and the future of energy: wind energy production and design, efficient combustion systems for biomass-derived fuels (biogas), and exploration geophysics for hydrocarbon reservoirs. In this work, the general exascale advances proposed as part of HPC4E and its outcome to specific results in different domains are presented.The research leading to these results has received funding from the European Union's Horizon 2020 Programme (2014-2020) under the HPC4E Project (www.hpc4e.eu), grant agreement n° 689772, the Spanish Ministry of Economy and Competitiveness under the CODEC2 project (TIN2015-63562-R), and from the Brazilian Ministry of Science, Technology and Innovation through Rede Nacional de Pesquisa (RNP). Computer time on Endeavour cluster is provided by the Intel Corporation, which enabled us to obtain the presented experimental results in uncertainty quantification in seismic imaging.Postprint (author's final draft