Modeling Innovative Power Take-Off Based on Double-Acting Hydraulic Cylinders Array for Wave Energy Conversion

One of the key systems of a Wave Energy Converter for extraction of wave energy is the Power Take-Off (PTO) device. This device transforms the mechanical energy of a moving body into electrical energy. This paper describes the model of an innovative PTO based on independently activated double-acting hydraulic cylinders array. The model has been developed using a simulation tool, based on a port-based approach to model hydraulics systems. The components and subsystems used in the model have been parameterized as real components and their values experimentally obtained from an existing prototype. In fact, the model takes into account most of the hydraulic losses of each component. The simulations show the flexibility to apply different restraining torques to the input movement depending on the geometrical configuration and the hydraulic cylinders on duty, easily modified by a control law. The combination of these two actions allows suitable flexibility to adapt the device to different sea states whilst optimizing the energy extraction. The model has been validated using a real test bench showing good correlations between simulation and experimental tests.

Optimización del proyecto de auscultación, dirigido al estudio de las deformaciones de un elemento patrimonial, mediante técnicas topográficas clásicas

[ES] Para más información véase el trabajo LDGP_mem_003-2: "Estudio topográfico de las deformaciones del conjunto arquitectónico de la iglesia de Nuestra Señora de la Blanca (Agoncillo, La Rioja) [Julio 2007 – Octubre 2009]", http://hdl.handle.net/10810/7050

Thin Magnetically Soft Wires for Magnetic Microsensors

Recent advances in technology involving magnetic materials require development of novel advanced magnetic materials with improved magnetic and magneto-transport properties and with reduced dimensionality. Therefore magnetic materials with outstanding magnetic characteristics and reduced dimensionality have recently gained much attention. Among these magnetic materials a family of thin wires with reduced geometrical dimensions (of order of 1-30 mu m in diameter) have gained importance within the last few years. These thin wires combine excellent soft magnetic properties (with coercivities up to 4 A/m) with attractive magneto-transport properties (Giant Magneto-impedance effect, GMI, Giant Magneto-resistance effect, GMR) and an unusual re-magnetization process in positive magnetostriction compositions exhibiting quite fast domain wall propagation. In this paper we overview the magnetic and magneto-transport properties of these microwires that make them suitable for microsensor applications.

Efficient learning of decomposable models with a bounded clique size

The learning of probability distributions from data is a ubiquitous problem in the fields of Statistics and Artificial Intelligence. During the last decades several learning algorithms have been proposed to learn probability distributions based on decomposable models due to their advantageous theoretical properties. Some of these algorithms can be used to search for a maximum likelihood decomposable model with a given maximum clique size, k, which controls the complexity of the model. Unfortunately, the problem of learning a maximum likelihood decomposable model given a maximum clique size is NP-hard for k > 2. In this work, we propose a family of algorithms which approximates this problem with a computational complexity of O(k · n^2 log n) in the worst case, where n is the number of implied random variables. The structures of the decomposable models that solve the maximum likelihood problem are called maximal k-order decomposable graphs. Our proposals, called fractal trees, construct a sequence of maximal i-order decomposable graphs, for i = 2, ..., k, in k − 1 steps. At each step, the algorithms follow a divide-and-conquer strategy based on the particular features of this type of structures. Additionally, we propose a prune-and-graft procedure which transforms a maximal k-order decomposable graph into another one, increasing its likelihood. We have implemented two particular fractal tree algorithms called parallel fractal tree and sequential fractal tree. These algorithms can be considered a natural extension of Chow and Liu’s algorithm, from k = 2 to arbitrary values of k. Both algorithms have been compared against other efficient approaches in artificial and real domains, and they have shown a competitive behavior to deal with the maximum likelihood problem. Due to their low computational complexity they are especially recommended to deal with high dimensional domains.

Syntactic change

[ES] En este trabajo se define el cambio sintáctico, se analizan los factores que lo causan o facilitan y se estudian sus tipos principales en griego antiguo.

Diseño y fabricación de un conjunto de estriberas y semimanillares para moto de competición.

[ES]El objeto del presente trabajo consiste en diseñar un conjunto de estriberas y semimanillares para una moto de competición, que cumplan con una serie de requerimientos geométricos y que garanticen las mejores prestaciones posibles en cuanto a competición, entre las que destacan la seguridad y comodidad del piloto. A continuación se procederá a elegir los procesos más adecuados para la fabricación de los mismos, teniendo en cuenta requisitos económicos y de calidad, para sacar al mercado un producto lo más competitivo posible. El estudio se basa principalmente en el análisis de diferentes alternativas que se pueden adoptar para obtener el diseño de los productos y posterior fabricación. Para ello se estudiarán los objetivos y condiciones que se deben cumplir. Cabe destacar que la idea de desarrollo de este proyecto surgió dentro de otro de mayor envergadura, la competición MotoStudent. MotoStudent es una competición internacional entre universidades de todo el mundo en la que los equipos de estudiantes se enfrentan al desafío de diseñar y desarrollar un prototipo de motocicleta de competición similar a la categoría mundialista de Moto3.