The morphology and reproductive structures of Mediterranean species of the genus Nemastoma J. Agardh, nom. cons. (Nemastomataceae, Nemastomatales): Nemastoma dichotomum and N. dumontioides

The morphology and reproductive structures of Mediterranean species of the genus Nemastoma J. Agardh, nom. cons. (Nemastomataceae, Nemastomatales): Nemastoma dichotomum and N. dumontioides

Simplification, approximation and deformation of large models

The high level of realism and interaction in many computer graphic applications requires techniques for processing complex geometric models. First, we present a method that provides an accurate low-resolution approximation from a multi-chart textured model that guarantees geometric fidelity and correct preservation of the appearance attributes. Then, we introduce a mesh structure called Compact Model that approximates dense triangular meshes while preserving sharp features, allowing adaptive reconstructions and supporting textured models. Next, we design a new space deformation technique called *Cages based on a multi-level system of cages that preserves the smoothness of the mesh between neighbouring cages and is extremely versatile, allowing the use of heterogeneous sets of coordinates and different levels of deformation. Finally, we propose a hybrid method that allows to apply any deformation technique on large models obtaining high quality results with a reduced memory footprint and a high performance.

Probabilistic models to assist maintenance of multiple instruments

The paper discusses maintenance challenges of organisations with a huge number of devices and proposes the use of probabilistic models to assist monitoring and maintenance planning. The proposal assumes connectivity of instruments to report relevant features for monitoring. Also, the existence of enough historical registers with diagnosed breakdowns is required to make probabilistic models reliable and useful for predictive maintenance strategies based on them. Regular Markov models based on estimated failure and repair rates are proposed to calculate the availability of the instruments and Dynamic Bayesian Networks are proposed to model cause-effect relationships to trigger predictive maintenance services based on the influence between observed features and previously documented diagnostics

A proposal for the diagnosis of uncertain dynamic systems based on interval models

The performance of a model-based diagnosis system could be affected by several uncertainty sources, such as,model errors,uncertainty in measurements, and disturbances. This uncertainty can be handled by mean of interval models.The aim of this thesis is to propose a methodology for fault detection, isolation and identification based on interval models. The methodology includes some algorithms to obtain in an automatic way the symbolic expression of the residual generators enhancing the structural isolability of the faults, in order to design the fault detection tests. These algorithms are based on the structural model of the system. The stages of fault detection, isolation, and identification are stated as constraint satisfaction problems in continuous domains and solved by means of interval based consistency techniques. The qualitative fault isolation is enhanced by a reasoning in which the signs of the symptoms are derived from analytical redundancy relations or bond graph models of the system. An initial and empirical analysis regarding the differences between interval-based and statistical-based techniques is presented in this thesis. The performance and efficiency of the contributions are illustrated through several application examples, covering different levels of complexity.

Simulation of interlaminar and intralaminar damage in polymer-based composites for aeronautical applications under impact loading

La aplicación de materiales compuestos de matriz polimérica reforzados mediante fibras largas (FRP, Fiber Reinforced Plastic), está en gradual crecimiento debido a las buenas propiedades específicas y a la flexibilidad en el diseño. Uno de los mayores consumidores es la industria aeroespacial, dado que la aplicación de estos materiales tiene claros beneficios económicos y medioambientales. Cuando los materiales compuestos se aplican en componentes estructurales, se inicia un programa de diseño donde se combinan ensayos reales y técnicas de análisis. El desarrollo de herramientas de análisis fiables que permiten comprender el comportamiento mecánico de la estructura, así como reemplazar muchos, pero no todos, los ensayos reales, es de claro interés. Susceptibilidad al daño debido a cargas de impacto fuera del plano es uno de los aspectos de más importancia que se tienen en cuenta durante el proceso de diseño de estructuras de material compuesto. La falta de conocimiento de los efectos del impacto en estas estructuras es un factor que limita el uso de estos materiales. Por lo tanto, el desarrollo de modelos de ensayo virtual mecánico para analizar la resistencia a impacto de una estructura es de gran interés, pero aún más, la predicción de la resistencia residual después del impacto. En este sentido, el presente trabajo abarca un amplio rango de análisis de eventos de impacto a baja velocidad en placas laminadas de material compuesto, monolíticas, planas, rectangulares, y con secuencias de apilamiento convencionales. Teniendo en cuenta que el principal objetivo del presente trabajo es la predicción de la resistencia residual a compresión, diferentes tareas se llevan a cabo para favorecer el adecuado análisis del problema. Los temas que se desarrollan son: la descripción analítica del impacto, el diseño y la realización de un plan de ensayos experimentales, la formulación e implementación de modelos constitutivos para la descripción del comportamiento del material, y el desarrollo de ensayos virtuales basados en modelos de elementos finitos en los que se usan los modelos constitutivos implementados.