Development of an Analytic Nodal Diffusion Solver in Multigroups for 3D Reactor Cores with Rectangular or Hexagonal Assemblies.

More accurate modelling of physical phenomena involved in present and future nuclear reactors requires a multi-scale and multi-physics approach. This challenge can be accomplished by the coupling of best-estimate core-physics, thermal-hydraulics and multi-physics solvers. In order to make viable that coupling, the current trends in reactor simulations are along the development of a new generation of tools based on user-friendly, modular, easily linkable, faster and more accurate codes to be integrated in common platforms. These premises are in the origin of the NURESIM Integrated Project within the 6th European Framework Program, which is envisaged to provide the initial step towards a Common European Standard Software Platform for nuclear reactors simulations. In the frame of this project and to reach the above-mentioned goals, a 3-D multigroup nodal solver for neutron diffusion calculations called ANDES (Analytic Nodal Diffusion Equation Solver) has been developed and tested in-depth in this Thesis. ANDES solves the steady-state and time-dependent neutron diffusion equation in threedimensions and any number of energy groups, utilizing the Analytic Coarse-Mesh Finite-Difference (ACMFD) scheme to yield the nodal coupling equations. It can be applied to both Cartesian and triangular-Z geometries, so that simulations of LWR as well as VVER, HTR and fast reactors can be performed. The solver has been implemented in a fully encapsulated way, enabling it as a module to be readily integrated in other codes and platforms. In fact, it can be used either as a stand-alone nodal code or as a solver to accelerate the convergence of whole core pin-by-pin code systems. Verification of performance has shown that ANDES is a code with high order definition for whole core realistic nodal simulations. In this paper, the methodology developed and involved in ANDES is presented

Microstructural optimization of unalloyed ductile cast irons with a ferritic matrix used in the manufacture of wind turbine rotors

The aim of this work was the microstructural optimization of cast irons with nodular graphite for the manufacture of wind turbine hubs, paying preferential attention to the geometry and distribution of graphite spheroids to ensure the required mechanical properties for this application. The target was pursued based upon microstructure-properties correlation, in an environment of great competitiveness and exigency marked by current international standards. The methodology followed consisted of the generation of knowledge from tailor-made industrial castings, followed by the analysis of their microstructures, in order to extract valuable conclusions for the production process through the use of statistical analysis. The approach method employed was a Fractional Design of Experiments (DOE) with 7 factors, 16 experiments and resolution IV. The samples from each experiment were cubes of identical geometry, and designed to match a surface-to-volume module equal to 4 cm (1.57 in) found as the highest values in real hubs of 3 MW power wind turbines. It is concluded that the use of nodulizers with traces of lanthanum favour the reduction of the volume fraction of pearlite, although La has proved not to promote the spherical shape of primary graphite. The negative effect of pre-inoculants containing SiC on the spheroidal morphology of graphite has also been verified, and also that low-Mn bearing scrap favours graphite formation and the reduction of the volume fraction of pearlite, in spite of being a carbide forming element. The whitening effect of Mn was minimized with low carbon equivalent melts

Resolución de ambigüedades GPS: técnicas empleadas y estudios

El fin de este artículo es una profundización en lo que se denomina en argot GPS, Resolución de la Ambigüedad. Ésta, es clave en mediciones GPS cuando se trabaja con técnicas estáticas de corta base o cinemáticas principalmente en tiempo real. La razón estriba en el empleo del observable de la fase de la portadora, afectado éste del término de la Ambigüedad N, esto es, por un número desconocido de completas longitudes de onda que se producen entre el satélite GPS y el receptor. Esta ambigüedad ha de ser determinada con técnicas de aproximación que exploren al completo el potencial de la precisión de las medidas GPS de la fase portadora, dado que es la naturaleza del número entero lo que garantiza la alta precisión

Rendimiento diagnóstico del qSOFA vs SIRS en pacientes con sospecha de sepsis en tres instituciones de salud del departamento de Risaralda Colombia

Desde hace varios siglos, el hombre ha intentado entender la sepsis como entidad patológica, dada su alta incidencia y la heterogeneidad de su presentación. Es tal vez el tema sobre el que más se ha escrito en las últimas décadas en medicina crítica, teniendo diferentes matices a lo largo de los años: empezando desde su definición, diagnóstico, biomarcadores, relación con la inflamación, abordaje terapéutico, seguimiento, hasta su pronóstico. A pesar de los esfuerzos por disminuir la morbimortalidad que conlleva, ha sido difícil modificar de manera sustancial los desenlaces finales alrededor de la misma. Por este motivo, un reconocimiento temprano se ha convertido en el objetivo de diferentes sociedades científicas alrededor del mundo. Desde hace 25 años, se ha pretendido definir la sepsis basándose en diversos criterios diagnósticos, cruzando variables clínicas, hemodinámicas y paraclínicas relacionadas en scores; ya que no existe un marcador definitivo. Entonces se ha pretendido buscar signos universales aplicables a la cabecera del paciente, con suficiente poder para detectar la presencia de esta entidad en la mayor cantidad posible de personas de manera temprana, lo que permitiría iniciar un tratamiento oportuno y de manera consecuente disminuir la morbimortalidad. Por esa razón, se ha planteado una nueva propuesta en cuanto a su definición, que se ajuste a las necesidades del clínico para la aproximación en el diagnóstico temprano de sepsis: el quick SOFA (Sequential Organ Failure Assessment) ó qSOFA (Tensión arterial sistólica menor a 100 mmHg, frecuencia respiratoria mayor a 22 resp/min y alteración del estado de consciencia Glasgow < 15); este nace del score mas usado para medición de disfunción orgánica SOFA, el cual ha demostrado mayor capacidad discriminativa y diagnostica en sepsis, sin embargo, esto ha suscitado un sin número de controversias en cuanto a su aplicabilidad y validez; por lo tanto se pretende poner a prueba el rendimiento diagnóstico del qSOFA vs la definición clásica con el sindrome de respuesta inflamatoria sistemica (SIRS) de manera prospectiva, midiendo su impacto en desenlaces a corto y mediano plazo en el paciente séptico

Learning Bayesian network classifiers for multidimensional supervised classification problems by means of a multiobjective approach

A classical supervised classification task tries to predict a single class variable based on a data set composed of a set of labeled examples. However, in many real domains more than one variable could be considered as a class variable, so a generalization of the single-class classification problem to the simultaneous prediction of a set of class variables should be developed. This problem is called multi-dimensional supervised classification. In this paper, we deal with the problem of learning Bayesian net work classifiers for multi-dimensional supervised classification problems. In order to do that, we have generalized the classical single-class Bayesian network classifier to the prediction of several class variables. In addition, we have defined new classification rules for probabilistic classifiers in multi-dimensional problems. We present a learning approach following a multi-objective strategy which considers the accuracy of each class variable separately as the functions to optimize. The solution of the learning approach is a Pareto set of non-dominated multi-dimensional Bayesian network classifiers and their accuracies for the different class variables, so a decision maker can easily choose by hand the classifier that best suits the particular problem and domain

Optical Chirality in Dispersive and Lossy Media

[EN] Several dynamical properties of electromagnetic waves such as energy, momentum, angular momentum, and optical helicity have been recently reexamined in dispersive and lossless media. Here, we address an alternative derivation for the optical chirality, extending it so as to include dissipative effects as well. To this end, we first elaborate on the most complete form of the conservation law for the optical chirality, without any restrictions on the nature of the medium. As a result we find a general expression for the optical chirality density both in lossless and lossy dispersive media. Our definition is perfectly consistent with that originally introduced for electromagnetic fields in free space, and is applicable to any material system, including dielectrics, plasmonic nanostructures, and left-handed metamaterials.The authors are grateful to C. Garcia-Meca for valuable comments and discussions. This work was supported by funding from Ministerio de Economia y Competitividad (MINECO) of Spain under Contract No. TEC2014-51902-C2-1-R.Vázquez-Lozano, JE.; Martínez Abietar, AJ. (2018). Optical Chirality in Dispersive and Lossy Media. Physical Review Letters. 121(4):043901-1-043901-7. https://doi.org/10.1103/PhysRevLett.121.043901S043901-1043901-7121

An Augmented Lagrangian Neural Network for the Fixed-Time Solution of Linear Programming

In this paper, a recurrent neural network is proposed using the augmented Lagrangian method for solving linear programming problems. The design of this neural network is based on the Karush-Kuhn-Tucker (KKT) optimality conditions and on a function that guarantees fixed-time convergence. With this aim, the use of slack variables allows transforming the initial linear programming problem into an equivalent one which only contains equality constraints. Posteriorly, the activation functions of the neural network are designed as fixed time controllers to meet KKT optimality conditions. Simulations results in an academic example and an application example show the effectiveness of the neural network

Sistemas modernos y eficaces. Iconografía publicitaria de la oficina moderna. 1918-1924.

El presente artículo de reflexión de investigación aborda una visión panorámica de la representación de la oficina y los objetos relacionados con las actividades asociadas a dicho espacio, dentro del marco de anuncios ilustrados publicados en revistas bogotanas entre los años 1918 y 1924.  Con una metodología lógico inductiva, concluimos que esta representación está ligada a una visión religiosa del mundo que impone el diseño publicitario y que, en particular, modela la visión de este espacio como encarnación del mito de la modernidad burocrática