Fabricación de piezas de geometría compleja mediante infusión empleando tecnología de impresión 3D para la generacion de utillaje

Los procesos de fabricación con materiales compuestos fuera de autoclave están actualmente en auge, debido a la flexibilidad y la reducción de costes asociados. Entre estos métodos de fabricación destaca el proceso de infusión por vacío modificada, el cual permite obtener geometrías relativamente complejas, de grandes dimensiones y con un mayor nivel de integración, mediante el apilado de tejido seco y la posterior inyección de resina líquida. Uno de los principales costes de este método es el de la fabricación de los útiles necesarios, que se incrementa considerablemente al aumentar la complejidad de la geometría de la pieza a fabricar. En este trabajo se presentan los resultados obtenidos en la fabricación de piezas complejas mediante infusión, empleando útiles fabricados con tecnología de impresión 3D de plástico.En concreto, se fabricó un perfil alar de dimensiones aproximadas 500 x 340 mm con capacidad sustentadora (psu-90-125wl-il), empleando un conjunto de 12 moldes fabricados en PLA mediante impresión 3D. Para ello, se diseñó el útil necesario con herramientas CAD a partir de la geometría del perfil a fabricar, para posteriormente dividirlo en secciones fabricables usando los medios de impresión 3D disponibles en TITANIA. Se estudiaron los métodos de relleno de y encolado de las secciones, a fin de lograr un único molde con la geometría requerida. Así mismo, se estudió el sistema de sellado de la superficie del útil que permitiese la generación y mantenimiento del vacío requerido para infusionar la pieza, logrando finalmente su fabricación. De este trabajo práctico se han extraído una serie de conclusiones y limitaciones a considerar en el futuro desarrollo de esta técnica de fabricación de utillaje, la cual puede resultar de interés para la fabricación de piezas mediante infusión a bajo coste

Industry 4.0: Materials and CFRP manufacturing process control through digital laboratory

Aerospace industry is well known to be one of the most demanding sectors to work with. It is strongly normalized, monitored and audited on behalf of airworthiness. In this scenario, continuous improvement is a must, to comply not only with requirements, but also lead times and costs. TITANIA, one of most recognized materials testing labs working for aerospace, moved to a tailor-made integral management system to deal with the high volume of data they deliver to their customers. After a two years effort, now is exploiting its results by offering better lead time compliances, robust test reports and new data analysis services. Digital transformation has pushed TITANIA into Industry 4.0. This paper presents the followed methodology and the first results obtained

Characterization of thermal protection elements for composites materials through thermal analysis

Highest level automotive competition is one of the sectors that takes the materials to the limit of their specifications in their commissioning, creating in this way knowledge in new technological fields. An example would be the use of structures made in CFRPs in competition, being gradually movin on the general automotive industry. The objective of this work is to determine the effectiveness of thermal protection elements that have to be installed in those structures of vehicles manufactured in CFRP exposed to high temperatures, such as pontoons covering the power unit and its exhaust manifolds, treating to discriminate which of them offer better protection at the lowest possible weight. In this work, 3 different protection systems have been evaluated, subjecting them to 3 types of tests, such as adhesion, weight and effectiveness of thermal protection. The method described here has made possible to evaluate the different efficacy of the systems tested, yielding additional data on the weight, adhesion and cost of the protection system

Riemann-Finsler geometry for diffusion weighted magnetic resonance imaging

We consider Riemann-Finsler geometry as a potentially powerful mathematical framework in the context of diffusion weighted magnetic resonance imaging. We explain its basic features in heuristic terms, but also provide mathematical details that are essential for practical applications, such as tractography and voxelbased classification. We stipulate a connection between the (dual) Finsler function and signal attenuation observed in the MRI scanner, which directly generalizes Stejskal-Tanner’s solution of the Bloch-Torrey equations and the diffusion tensor imaging (DTI) model inspired by this. The proposed model can therefore be regarded as an extension of DTI. Technically, reconstruction of the (dual) Finsler function from diffusion weighted measurements is a fairly straightforward generalization of the DTI case. The extension of the Riemann differential geometric paradigm for DTI analysis is, however, nontrivial.</p

A Riemannian Scalar Measure for Diffusion Tensor Images

We study a well-known scalar quantity in Riemannian geometry, the Ricci scalar, in the context of diffusion tensor imaging (DTI), which is an emerging non-invasive medical imaging modality. We derive a physical interpretation for the Ricci scalar and explore experimentally its significance in DTI. We also extend the definition of the Ricci scalar to the case of high angular resolution diffusion imaging (HARDI) using Finsler geometry. We mention that the Ricci scalar is not only suitable for tensor valued image analysis, but it can be computed for any mapping

Idiosyncratic relationships between pond invertebrates and environmental, temporal and patch-specific predictors of incidence

The incidence of eight species of microcrustacea and seven species of Dytiscidae (adults) was recorded from 30 small, temporary pools, in January and early summer, over six years. Incidence of each species, both in January and in summer, was modelled using logistic regression. Three categories of predictor variables were included in the models. Firstly systematic environmental variables; length of previous summer's dry phase, inter-pond links caused by flooding, distance between ponds and macrophyte structural density. Secondly temporal factors; year and previous incidence. Thirdly individual ponds, representing patch-specific effects. Logistic regression provided effective models of incidence for most species. However individual species varied in the factors that provided significant prediction of presence and absence. Systematic, temporal and patch-specific predictors were all significant predictors for different species of both microcrustacea and Dytiscidae. No single factor dominated most models. Individual factors showed positive or negative relationships with incidence with different species. Length of previous summer dry-phase was the most common predictor for microcrustacea and beetles in January. Summer models were more varied; length of previous dry phase and flood linkage between ponds and macrophyte density were significant predictors in many models, year and distance less important. Patch-specific predictors were significant for five of the microcrustacea and four of the beetles. The results suggest that individual species show idiosyncratic responses to systematic, temporal and patch-specific factors, rather than most species responding in a similar way to one or two dominant influences