Analysis of Contributions to NO2 Ambient Air Quality Levels in Madrid City (Spain) through Modeling. Implications for the Development of Policies and Air Quality Monitoring

As environmental standards become more stringent (e.g. European Directive 2008/50/EC), more reliable and sophisticated modeling tools are needed to simulate measures and plans that may effectively tackle air quality exceedances, common in large cities across Europe, particularly for NO2. Modeling air quality in urban areas is rather complex since observed concentration values are a consequence of the interaction of multiple sources and processes that involve a wide range of spatial and temporal scales. Besides a consistent and robust multi-scale modeling system, comprehensive and flexible emission inventories are needed. This paper discusses the application of the WRF-SMOKE-CMAQ system to the Madrid city (Spain) to assess the contribution of the main emitting sectors in the region. A detailed emission inventory was compiled for this purpose. This inventory relies on bottom-up methods for the most important sources. It is coupled with the regional traffic model and it makes use of an extensive database of industrial, commercial and residential combustion plants. Less relevant sources are downscaled from national or regional inventories. This paper reports the methodology and main results of the source apportionment study performed to understand the origin of pollution (main sectors and geographical areas) and define clear targets for the abatement strategy. Finally the structure of the air quality monitoring is analyzed and discussed to identify options to improve the monitoring strategy not only in the Madrid city but the whole metropolitan area.

Large scale multiphysics modeling of neurites

Situado en el límite entre Ingeniería, Informática y Biología, la mecánica computacional de las neuronas aparece como un nuevo campo interdisciplinar que potencialmente puede ser capaz de abordar problemas clínicos desde una perspectiva diferente. Este campo es multiescala por naturaleza, yendo desde la nanoescala (como, por ejemplo, los dímeros de tubulina) a la macroescala (como, por ejemplo, el tejido cerebral), y tiene como objetivo abordar problemas que son complejos, y algunas veces imposibles, de estudiar con medios experimentales. La modelización computacional ha sido ampliamente empleada en aplicaciones Neurocientíficas tan diversas como el crecimiento neuronal o la propagación de los potenciales de acción compuestos. Sin embargo, en la mayoría de los enfoques de modelización hechos hasta ahora, la interacción entre la célula y el medio/estímulo que la rodea ha sido muy poco explorada. A pesar de la tremenda importancia de esa relación en algunos desafíos médicos—como, por ejemplo, lesiones traumáticas en el cerebro, cáncer, la enfermedad del Alzheimer—un puente que relacione las propiedades electrofisiológicas-químicas y mecánicas desde la escala molecular al nivel celular todavía no existe. Con ese objetivo, esta investigación propone un marco computacional multiescala particularizado para dos escenarios respresentativos: el crecimiento del axón y el acomplamiento electrofisiológicomecánico de las neuritas. En el primer caso, se explora la relación entre los constituyentes moleculares del axón durante su crecimiento y sus propiedades mecánicas resultantes, mientras que en el último, un estímulo mecánico provoca deficiencias funcionales a nivel celular como consecuencia de sus alteraciones electrofisiológicas-químicas. La modelización computacional empleada en este trabajo es el método de las diferencias finitas, y es implementada en un nuevo programa llamado Neurite. Aunque el método de los elementos finitos es también explorado en parte de esta investigación, el método de las diferencias finitas tiene la flexibilidad y versatilidad necesaria para implementar mode los biológicos, así como la simplicidad matemática para extenderlos a simulaciones a gran escala con un coste computacional bajo. Centrándose primero en el efecto de las propiedades electrofisiológicas-químicas sobre las propiedades mecánicas, una versión adaptada de Neurite es desarrollada para simular la polimerización de los microtúbulos en el crecimiento del axón y proporcionar las propiedades mecánicas como función de la ocupación de los microtúbulos. Después de calibrar el modelo de crecimiento del axón frente a resultados experimentales disponibles en la literatura, las características mecánicas pueden ser evaluadas durante la simulación. Las propiedades mecánicas del axón muestran variaciones dramáticas en la punta de éste, donde el cono de crecimiento soporta las señales químicas y mecánicas. Bansándose en el conocimiento ganado con el modelo de diferencias finitas, y con el objetivo de ir de 1D a 3D, este esquema preliminar pero de una naturaleza innovadora allana el camino a futuros estudios con el método de los elementos finitos. Centrándose finalmente en el efecto de las propiedades mecánicas sobre las propiedades electrofisiológicas- químicas, Neurite es empleado para relacionar las cargas mecánicas macroscópicas con las deformaciones y velocidades de deformación a escala microscópica, y simular la propagación de la señal eléctrica en las neuritas bajo carga mecánica. Las simulaciones fueron calibradas con resultados experimentales publicados en la literatura, proporcionando, por tanto, un modelo capaz de predecir las alteraciones de las funciones electrofisiológicas neuronales bajo cargas externas dañinas, y uniendo lesiones mecánicas con las correspondientes deficiencias funcionales. Para abordar simulaciones a gran escala, aunque otras arquitecturas avanzadas basadas en muchos núcleos integrados (MICs) fueron consideradas, los solvers explícito e implícito se implementaron en unidades de procesamiento central (CPU) y unidades de procesamiento gráfico (GPUs). Estudios de escalabilidad fueron llevados acabo para ambas implementaciones mostrando resultados prometedores para casos de simulaciones extremadamente grandes con GPUs. Esta tesis abre la vía para futuros modelos mecánicos con el objetivo de unir las propiedades electrofisiológicas-químicas con las propiedades mecánicas. El objetivo general es mejorar el conocimiento de las comunidades médicas y de bioingeniería sobre la mecánica de las neuronas y las deficiencias funcionales que aparecen de los daños producidos por traumatismos mecánicos, como lesiones traumáticas en el cerebro, o enfermedades neurodegenerativas como la enfermedad del Alzheimer. ABSTRACT Sitting at the interface between Engineering, Computer Science and Biology, Computational Neuron Mechanics appears as a new interdisciplinary field potentially able to tackle clinical problems from a new perspective. This field is multiscale by nature, ranging from the nanoscale (e.g., tubulin dimers) to the macroscale (e.g., brain tissue), and aims at tackling problems that are complex, and sometime impossible, to study through experimental means. Computational modeling has been widely used in different Neuroscience applications as diverse as neuronal growth or compound action potential propagation. However, in the majority of the modeling approaches done in this field to date, the interactions between the cell and its surrounding media/stimulus have been rarely explored. Despite of the tremendous importance of such relationship in several medical challenges—e.g., traumatic brain injury (TBI), cancer, Alzheimer’s disease (AD)—a bridge between electrophysiological-chemical and mechanical properties of neurons from the molecular scale to the cell level is still lacking. To this end, this research proposes a multiscale computational framework particularized for two representative scenarios: axon growth and electrophysiological-mechanical coupling of neurites. In the former case, the relation between the molecular constituents of the axon during its growth and its resulting mechanical properties is explored, whereas in the latter, a mechanical stimulus provokes functional deficits at cell level as a consequence of its electrophysiological-chemical alterations. The computational modeling approach chosen in this work is the finite difference method (FDM), and was implemented in a new program called Neurite. Although the finite element method (FEM) is also explored as part of this research, the FDM provides the necessary flexibility and versatility to implement biological models, as well as the mathematical simplicity to extend them to large scale simulations with a low computational cost. Focusing first on the effect of electrophysiological-chemical properties on the mechanical proper ties, an adaptation of Neurite was developed to simulate microtubule polymerization in axonal growth and provide the axon mechanical properties as a function of microtubule occupancy. After calibrating the axon growth model against experimental results available in the literature, the mechanical characteristics can be tracked during the simulation. The axon mechanical properties show dramatic variations at the tip of the axon, where the growth cone supports the chemical and mechanical signaling. Based on the knowledge gained from the FDM scheme, and in order to go from 1D to 3D, this preliminary yet novel scheme paves the road for future studies with FEM. Focusing then on the effect of mechanical properties on the electrophysiological-chemical properties, Neurite was used to relate macroscopic mechanical loading to microscopic strains and strain rates, and simulate the electrical signal propagation along neurites under mechanical loading. The simulations were calibrated against experimental results published in the literature, thus providing a model able to predict the alteration of neuronal electrophysiological function under external damaging load, and linking mechanical injuries to subsequent acute functional deficits. To undertake large scale simulations, although other state-of-the-art architectures based on many integrated cores (MICs) were considered, the explicit and implicit solvers were implemented for central processing units (CPUs) and graphics processing units (GPUs). Scalability studies were done for both implementations showing promising results for extremely large scale simulations with GPUs. This thesis opens the avenue for future mechanical modeling approaches aimed at linking electrophysiological- chemical properties to mechanical properties. Its overarching goal is to enhance the bioengineering and medical communities knowledge on neuronal mechanics and functional deficits arising from damages produced by direct mechanical insults, such as TBI, or neurodegenerative evolving illness, such as AD.

Image sub-segmentation by PFCM and Artificial Neural Networks to detect pore space in 2D and 3D CT soil images

The image by Computed Tomography is a non-invasive alternative for observing soil structures, mainly pore space. The pore space correspond in soil data to empty or free space in the sense that no material is present there but only fluids, the fluid transport depend of pore spaces in soil, for this reason is important identify the regions that correspond to pore zones. In this paper we present a methodology in order to detect pore space and solid soil based on the synergy of the image processing, pattern recognition and artificial intelligence. The mathematical morphology is an image processing technique used for the purpose of image enhancement. In order to find pixels groups with a similar gray level intensity, or more or less homogeneous groups, a novel image sub-segmentation based on a Possibilistic Fuzzy c-Means (PFCM) clustering algorithm was used. The Artificial Neural Networks (ANNs) are very efficient for demanding large scale and generic pattern recognition applications for this reason finally a classifier based on artificial neural network is applied in order to classify soil images in two classes, pore space and solid soil respectively.

Balancing groundwater conservation and rural livelihoods under water and climate uncertainties: An integrated hydro-economic modeling framework

In arid countries worldwide, social conflicts between irrigation-based human development and the conservation of aquatic ecosystems are widespread and attract many public debates. This research focuses on the analysis of water and agricultural policies aimed at conserving groundwater resources and maintaining rurallivelihoods in a basin in Spain's central arid region. Intensive groundwater mining for irrigation has caused overexploitation of the basin's large aquifer, the degradation of reputed wetlands and has given rise to notable social conflicts over the years. With the aim of tackling the multifaceted socio-ecological interactions of complex water systems, the methodology used in this study consists in a novel integration into a common platform of an economic optimization model and a hydrology model WEAP (Water Evaluation And Planning system). This robust tool is used to analyze the spatial and temporal effects of different water and agricultural policies under different climate scenarios. It permits the prediction of different climate and policy outcomes across farm types (water stress impacts and adaptation), at basin's level (aquifer recovery), and along the policies’ implementation horizon (short and long run). Results show that the region's current quota-based water policies may contribute to reduce water consumption in the farms but will not be able to recover the aquifer and will inflict income losses to the rural communities. This situation would worsen in case of drought. Economies of scale and technology are evidenced as larger farms with cropping diversification and those equipped with modern irrigation will better adapt to water stress conditions. However, the long-term sustainability of the aquifer and the maintenance of rurallivelihoods will be attained only if additional policy measures are put in place such as the control of illegal abstractions and the establishing of a water bank. Within the policy domain, the research contributes to the new sustainable development strategy of the EU by concluding that, in water-scarce regions, effective integration of water and agricultural policies is essential for achieving the water protection objectives of the EU policies. Therefore, the design and enforcement of well-balanced region-specific polices is a major task faced by policy makers for achieving successful water management that will ensure nature protection and human development at tolerable social costs. From a methodological perspective, this research initiative contributes to better address hydrological questions as well as economic and social issues in complex water and human systems. Its integrated vision provides a valuable illustration to inform water policy and management decisions within contexts of water-related conflicts worldwide.

Mathematical and Numerical Modeling in Maritime Geomechanics

A theoretical and numerical framework to model the foundation of marine offshore structures is presented. The theoretical model is composed by a system of partial differential equations describing coupling between seabed solid skeleton and pore fluids (water, air, oil,…) combined with a system of ordinary differential equations describing the specific constitutive relation of the seabed soil skeleton. Once the theoretical model is described, the finite element numerical procedure to achieve an approximate solution of the governing equations is outlined. In order to validate the proposed theoretical and numerical framework the seaward tilt mechanism induced by the action of breaking waves over a vertical breakwater is numerically reproduced. The results numerically attained are in agreement with the main conclusions drawn from the literature associated with this failure mechanism

Propagation of Cross-Section Uncertainties in Criticality Calculations in the Framework of UAM-Phase I Using MCNPX-2.7e and SCALE-6.1

In the framework of the OECD/NEA project on Benchmark for Uncertainty Analysis in Modeling (UAM) for Design, Operation, and Safety Analysis of LWRs, several approaches and codes are being used to deal with the exercises proposed in Phase I, “Specifications and Support Data for Neutronics Cases.” At UPM, our research group treats these exercises with sensitivity calculations and the “sandwich formula” to propagate cross-section uncertainties. Two different codes are employed to calculate the sensitivity coefficients of to cross sections in criticality calculations: MCNPX-2.7e and SCALE-6.1. The former uses the Differential Operator Technique and the latter uses the Adjoint-Weighted Technique. In this paper, the main results for exercise I-2 “Lattice Physics” are presented for the criticality calculations of PWR. These criticality calculations are done for a TMI fuel assembly at four different states: HZP-Unrodded, HZP-Rodded, HFP-Unrodded, and HFP-Rodded. The results of the two different codes above are presented and compared. The comparison proves a good agreement between SCALE-6.1 and MCNPX-2.7e in uncertainty that comes from the sensitivity coefficients calculated by both codes. Differences are found when the sensitivity profiles are analysed, but they do not lead to differences in the uncertainty.

Multiscale Modeling of Composites: Toward Virtual Testing ... and Beyond

Recent developments in the area of multiscale modeling of fiber-reinforced polymers are presented. The overall strategy takes advantage of the separa-tion of length scales between different entities (ply, laminate, and component) found in composite structures. This allows us to carry out multiscale modeling by computing the properties of one entity (e.g., individual plies) at the relevant length scale, homogenizing the results into a constitutive model, and passing this information to the next length scale to determine the mechanical behavior of the larger entity (e.g., laminate). As a result, high-fidelity numerical sim-ulations of the mechanical behavior of composite coupons and small compo-nents are nowadays feasible starting from the matrix, fiber, and interface properties and spatial distribution. Finally, the roadmap is outlined for extending the current strategy to include functional properties and processing into the simulation scheme.

Self-organizing cultured neural networks: Image analysis techniques for longitudinal tracking and modeling of the underlying network structure

Esta tesis estudia la evolución estructural de conjuntos de neuronas como la capacidad de auto-organización desde conjuntos de neuronas separadas hasta que forman una red (clusterizada) compleja. Esta tesis contribuye con el diseño e implementación de un algoritmo no supervisado de segmentación basado en grafos con un coste computacional muy bajo. Este algoritmo proporciona de forma automática la estructura completa de la red a partir de imágenes de cultivos neuronales tomadas con microscopios de fase con una resolución muy alta. La estructura de la red es representada mediante un objeto matemático (matriz) cuyos nodos representan a las neuronas o grupos de neuronas y los enlaces son las conexiones reconstruidas entre ellos. Este algoritmo extrae también otras medidas morfológicas importantes que caracterizan a las neuronas y a las neuritas. A diferencia de otros algoritmos hasta el momento, que necesitan de fluorescencia y técnicas inmunocitoquímicas, el algoritmo propuesto permite el estudio longitudinal de forma no invasiva posibilitando el estudio durante la formación de un cultivo. Además, esta tesis, estudia de forma sistemática un grupo de variables topológicas que garantizan la posibilidad de cuantificar e investigar la progresión de las características principales durante el proceso de auto-organización del cultivo. Nuestros resultados muestran la existencia de un estado concreto correspondiente a redes con configuracin small-world y la emergencia de propiedades a micro- y meso-escala de la estructura de la red. Finalmente, identificamos los procesos físicos principales que guían las transformaciones morfológicas de los cultivos y proponemos un modelo de crecimiento de red que reproduce el comportamiento cuantitativamente de las observaciones experimentales. ABSTRACT The thesis analyzes the morphological evolution of assemblies of living neurons, as they self-organize from collections of separated cells into elaborated, clustered, networks. In particular, it contributes with the design and implementation of a graph-based unsupervised segmentation algorithm, having an associated very low computational cost. The processing automatically retrieves the whole network structure from large scale phase-contrast images taken at high resolution throughout the entire life of a cultured neuronal network. The network structure is represented by a mathematical object (a matrix) in which nodes are identified neurons or neurons clusters, and links are the reconstructed connections between them. The algorithm is also able to extract any other relevant morphological information characterizing neurons and neurites. More importantly, and at variance with other segmentation methods that require fluorescence imaging from immunocyto- chemistry techniques, our measures are non invasive and entitle us to carry out a fully longitudinal analysis during the maturation of a single culture. In turn, a systematic statistical analysis of a group of topological observables grants us the possibility of quantifying and tracking the progression of the main networks characteristics during the self-organization process of the culture. Our results point to the existence of a particular state corresponding to a small-world network configuration, in which several relevant graphs micro- and meso-scale properties emerge. Finally, we identify the main physical processes taking place during the cultures morphological transformations, and embed them into a simplified growth model that quantitatively reproduces the overall set of experimental observations.

Self-organizing cultured neural networks: Image analysis techniques for longitudinal tracking and modeling of the underlying network structure (versión actualizada)

Esta tesis estudia la evolución estructural de conjuntos de neuronas como la capacidad de auto-organización desde conjuntos de neuronas separadas hasta que forman una red (clusterizada) compleja. Esta tesis contribuye con el diseño e implementación de un algoritmo no supervisado de segmentación basado en grafos con un coste computacional muy bajo. Este algoritmo proporciona de forma automática la estructura completa de la red a partir de imágenes de cultivos neuronales tomadas con microscopios de fase con una resolución muy alta. La estructura de la red es representada mediante un objeto matemático (matriz) cuyos nodos representan a las neuronas o grupos de neuronas y los enlaces son las conexiones reconstruidas entre ellos. Este algoritmo extrae también otras medidas morfológicas importantes que caracterizan a las neuronas y a las neuritas. A diferencia de otros algoritmos hasta el momento, que necesitan de fluorescencia y técnicas inmunocitoquímicas, el algoritmo propuesto permite el estudio longitudinal de forma no invasiva posibilitando el estudio durante la formación de un cultivo. Además, esta tesis, estudia de forma sistemática un grupo de variables topológicas que garantizan la posibilidad de cuantificar e investigar la progresión de las características principales durante el proceso de auto-organización del cultivo. Nuestros resultados muestran la existencia de un estado concreto correspondiente a redes con configuracin small-world y la emergencia de propiedades a micro- y meso-escala de la estructura de la red. Finalmente, identificamos los procesos físicos principales que guían las transformaciones morfológicas de los cultivos y proponemos un modelo de crecimiento de red que reproduce el comportamiento cuantitativamente de las observaciones experimentales. ABSTRACT The thesis analyzes the morphological evolution of assemblies of living neurons, as they self-organize from collections of separated cells into elaborated, clustered, networks. In particular, it contributes with the design and implementation of a graph-based unsupervised segmentation algorithm, having an associated very low computational cost. The processing automatically retrieves the whole network structure from large scale phase-contrast images taken at high resolution throughout the entire life of a cultured neuronal network. The network structure is represented by a mathematical object (a matrix) in which nodes are identified neurons or neurons clusters, and links are the reconstructed connections between them. The algorithm is also able to extract any other relevant morphological information characterizing neurons and neurites. More importantly, and at variance with other segmentation methods that require fluorescence imaging from immunocyto- chemistry techniques, our measures are non invasive and entitle us to carry out a fully longitudinal analysis during the maturation of a single culture. In turn, a systematic statistical analysis of a group of topological observables grants us the possibility of quantifying and tracking the progression of the main networks characteristics during the self-organization process of the culture. Our results point to the existence of a particular state corresponding to a small-world network configuration, in which several relevant graphs micro- and meso-scale properties emerge. Finally, we identify the main physical processes taking place during the cultures morphological transformations, and embed them into a simplified growth model that quantitatively reproduces the overall set of experimental observations.

Neurite, a finite difference large scale parallel program for the simulation of the electrical signal propagation in neurites under mechanical loading

With the growing body of research on traumatic brain injury and spinal cord injury, computational neuroscience has recently focused its modeling efforts on neuronal functional deficits following mechanical loading. However, in most of these efforts, cell damage is generally only characterized by purely mechanistic criteria, function of quantities such as stress, strain or their corresponding rates. The modeling of functional deficits in neurites as a consequence of macroscopic mechanical insults has been rarely explored. In particular, a quantitative mechanically based model of electrophysiological impairment in neuronal cells has only very recently been proposed (Jerusalem et al., 2013). In this paper, we present the implementation details of Neurite: the finite difference parallel program used in this reference. Following the application of a macroscopic strain at a given strain rate produced by a mechanical insult, Neurite is able to simulate the resulting neuronal electrical signal propagation, and thus the corresponding functional deficits. The simulation of the coupled mechanical and electrophysiological behaviors requires computational expensive calculations that increase in complexity as the network of the simulated cells grows. The solvers implemented in Neurite-explicit and implicit-were therefore parallelized using graphics processing units in order to reduce the burden of the simulation costs of large scale scenarios. Cable Theory and Hodgkin-Huxley models were implemented to account for the electrophysiological passive and active regions of a neurite, respectively, whereas a coupled mechanical model accounting for the neurite mechanical behavior within its surrounding medium was adopted as a link between lectrophysiology and mechanics (Jerusalem et al., 2013). This paper provides the details of the parallel implementation of Neurite, along with three different application examples: a long myelinated axon, a segmented dendritic tree, and a damaged axon. The capabilities of the program to deal with large scale scenarios, segmented neuronal structures, and functional deficits under mechanical loading are specifically highlighted.

Multiscale modeling of the plastic behaviour in single crystal tungsten: from atomistic to crystal plasticity simulations

En una planta de fusión, los materiales en contacto con el plasma así como los materiales de primera pared experimentan condiciones particularmente hostiles al estar expuestos a altos flujos de partículas, neutrones y grandes cargas térmicas. Como consecuencia de estas diferentes y complejas condiciones de trabajo, el estudio, desarrollo y diseño de estos materiales es uno de los más importantes retos que ha surgido en los últimos años para la comunidad científica en el campo de los materiales y la energía. Debido a su baja tasa de erosión, alta resistencia al sputtering, alta conductividad térmica, muy alto punto de fusión y baja retención de tritio, el tungsteno (wolframio) es un importante candidato como material de primera pared y como posible material estructural avanzado en fusión por confinamiento magnético e inercial. Sin embargo, el tiempo de vida del tungsteno viene controlado por diversos factores como son su respuesta termo-mecánica en la superficie, la posibilidad de fusión y el fallo por acumulación de helio. Es por ello que el tiempo de vida limitado por la respuesta mecánica del tungsteno (W), y en particular su fragilidad, sean dos importantes aspectos que tienes que ser investigados. El comportamiento plástico en materiales refractarios con estructura cristalina cúbica centrada en las caras (bcc) como el tungsteno está gobernado por las dislocaciones de tipo tornillo a escala atómica y por conjuntos e interacciones de dislocaciones a escalas más grandes. El modelado de este complejo comportamiento requiere la aplicación de métodos capaces de resolver de forma rigurosa cada una de las escalas. El trabajo que se presenta en esta tesis propone un modelado multiescala que es capaz de dar respuestas ingenieriles a las solicitudes técnicas del tungsteno, y que a su vez está apoyado por la rigurosa física subyacente a extensas simulaciones atomísticas. En primer lugar, las propiedades estáticas y dinámicas de las dislocaciones de tipo tornillo en cinco potenciales interatómicos de tungsteno son comparadas, determinando cuáles de ellos garantizan una mayor fidelidad física y eficiencia computacional. Las grandes tasas de deformación asociadas a las técnicas de dinámica molecular hacen que las funciones de movilidad de las dislocaciones obtenidas no puedan ser utilizadas en los siguientes pasos del modelado multiescala. En este trabajo, proponemos dos métodos alternativos para obtener las funciones de movilidad de las dislocaciones: un modelo Monte Cario cinético y expresiones analíticas. El conjunto de parámetros necesarios para formular el modelo de Monte Cario cinético y la ley de movilidad analítica son calculados atomísticamente. Estos parámetros incluyen, pero no se limitan a: la determinación de las entalpias y energías de formación de las parejas de escalones que forman las dislocaciones, la parametrización de los efectos de no Schmid característicos en materiales bcc,etc. Conociendo la ley de movilidad de las dislocaciones en función del esfuerzo aplicado y la temperatura, se introduce esta relación como ecuación de flujo dentro de un modelo de plasticidad cristalina. La predicción del modelo sobre la dependencia del límite de fluencia con la temperatura es validada experimentalmente con ensayos uniaxiales en tungsteno monocristalino. A continuación, se calcula el límite de fluencia al aplicar ensayos uniaxiales de tensión para un conjunto de orientaciones cristalográticas dentro del triángulo estándar variando la tasa de deformación y la temperatura de los ensayos. Finalmente, y con el objetivo de ser capaces de predecir una respuesta más dúctil del tungsteno para una variedad de estados de carga, se realizan ensayos biaxiales de tensión sobre algunas de las orientaciones cristalográficas ya estudiadas en función de la temperatura.-------------------------------------------------------------------------ABSTRACT ----------------------------------------------------------Tungsten and tungsten alloys are being considered as leading candidates for structural and functional materials in future fusion energy devices. The most attractive properties of tungsten for the design of magnetic and inertial fusion energy reactors are its high melting point, high thermal conductivity, low sputtering yield and low longterm disposal radioactive footprint. However, tungsten also presents a very low fracture toughness, mostly associated with inter-granular failure and bulk plasticity, that limits its applications. As a result of these various and complex conditions of work, the study, development and design of these materials is one of the most important challenges that have emerged in recent years to the scientific community in the field of materials for energy applications. The plastic behavior of body-centered cubic (bcc) refractory metals like tungsten is governed by the kink-pair mediated thermally activated motion of h¿ (\1 11)i screw dislocations on the atomistic scale and by ensembles and interactions of dislocations at larger scales. Modeling this complex behavior requires the application of methods capable of resolving rigorously each relevant scale. The work presented in this thesis proposes a multiscale model approach that gives engineering-level responses to the technical specifications required for the use of tungsten in fusion energy reactors, and it is also supported by the rigorous underlying physics of extensive atomistic simulations. First, the static and dynamic properties of screw dislocations in five interatomic potentials for tungsten are compared, determining which of these ensure greater physical fidelity and computational efficiency. The large strain rates associated with molecular dynamics techniques make the dislocation mobility functions obtained not suitable to be used in the next steps of the multiscale model. Therefore, it is necessary to employ mobility laws obtained from a different method. In this work, we suggest two alternative methods to get the dislocation mobility functions: a kinetic Monte Carlo model and analytical expressions. The set of parameters needed to formulate the kinetic Monte Carlo model and the analytical mobility law are calculated atomistically. These parameters include, but are not limited to: enthalpy and energy barriers of kink-pairs as a function of the stress, width of the kink-pairs, non-Schmid effects ( both twinning-antitwinning asymmetry and non-glide stresses), etc. The function relating dislocation velocity with applied stress and temperature is used as the main source of constitutive information into a dislocation-based crystal plasticity framework. We validate the dependence of the yield strength with the temperature predicted by the model against existing experimental data of tensile tests in singlecrystal tungsten, with excellent agreement between the simulations and the measured data. We then extend the model to a number of crystallographic orientations uniformly distributed in the standard triangle and study the effects of temperature and strain rate. Finally, we perform biaxial tensile tests and provide the yield surface as a function of the temperature for some of the crystallographic orientations explored in the uniaxial tensile tests.

A model for turbulent combustion simulation of large scale hydrogen explosions

El agotamiento, la ausencia o, simplemente, la incertidumbre sobre la cantidad de las reservas de combustibles fósiles se añaden a la variabilidad de los precios y a la creciente inestabilidad en la cadena de aprovisionamiento para crear fuertes incentivos para el desarrollo de fuentes y vectores energéticos alternativos. El atractivo de hidrógeno como vector energético es muy alto en un contexto que abarca, además, fuertes inquietudes por parte de la población sobre la contaminación y las emisiones de gases de efecto invernadero. Debido a su excelente impacto ambiental, la aceptación pública del nuevo vector energético dependería, a priori, del control de los riesgos asociados su manipulación y almacenamiento. Entre estos, la existencia de un innegable riesgo de explosión aparece como el principal inconveniente de este combustible alternativo. Esta tesis investiga la modelización numérica de explosiones en grandes volúmenes, centrándose en la simulación de la combustión turbulenta en grandes dominios de cálculo en los que la resolución que es alcanzable está fuertemente limitada. En la introducción, se aborda una descripción general de los procesos de explosión. Se concluye que las restricciones en la resolución de los cálculos hacen necesario el modelado de los procesos de turbulencia y de combustión. Posteriormente, se realiza una revisión crítica de las metodologías disponibles tanto para turbulencia como para combustión, que se lleva a cabo señalando las fortalezas, deficiencias e idoneidad de cada una de las metodologías. Como conclusión de esta investigación, se obtiene que la única estrategia viable para el modelado de la combustión, teniendo en cuenta las limitaciones existentes, es la utilización de una expresión que describa la velocidad de combustión turbulenta en función de distintos parámetros. Este tipo de modelos se denominan Modelos de velocidad de llama turbulenta y permiten cerrar una ecuación de balance para la variable de progreso de combustión. Como conclusión también se ha obtenido, que la solución más adecuada para la simulación de la turbulencia es la utilización de diferentes metodologías para la simulación de la turbulencia, LES o RANS, en función de la geometría y de las restricciones en la resolución de cada problema particular. Sobre la base de estos hallazgos, el crea de un modelo de combustión en el marco de los modelos de velocidad de la llama turbulenta. La metodología propuesta es capaz de superar las deficiencias existentes en los modelos disponibles para aquellos problemas en los que se precisa realizar cálculos con una resolución moderada o baja. Particularmente, el modelo utiliza un algoritmo heurístico para impedir el crecimiento del espesor de la llama, una deficiencia que lastraba el célebre modelo de Zimont. Bajo este enfoque, el énfasis del análisis se centra en la determinación de la velocidad de combustión, tanto laminar como turbulenta. La velocidad de combustión laminar se determina a través de una nueva formulación capaz de tener en cuenta la influencia simultánea en la velocidad de combustión laminar de la relación de equivalencia, la temperatura, la presión y la dilución con vapor de agua. La formulación obtenida es válida para un dominio de temperaturas, presiones y dilución con vapor de agua más extenso de cualquiera de las formulaciones previamente disponibles. Por otra parte, el cálculo de la velocidad de combustión turbulenta puede ser abordado mediante el uso de correlaciones que permiten el la determinación de esta magnitud en función de distintos parámetros. Con el objetivo de seleccionar la formulación más adecuada, se ha realizado una comparación entre los resultados obtenidos con diversas expresiones y los resultados obtenidos en los experimentos. Se concluye que la ecuación debida a Schmidt es la más adecuada teniendo en cuenta las condiciones del estudio. A continuación, se analiza la importancia de las inestabilidades de la llama en la propagación de los frentes de combustión. Su relevancia resulta significativa para mezclas pobres en combustible en las que la intensidad de la turbulencia permanece moderada. Estas condiciones son importantes dado que son habituales en los accidentes que ocurren en las centrales nucleares. Por ello, se lleva a cabo la creación de un modelo que permita estimar el efecto de las inestabilidades, y en concreto de la inestabilidad acústica-paramétrica, en la velocidad de propagación de llama. El modelado incluye la derivación matemática de la formulación heurística de Bauwebs et al. para el cálculo de la incremento de la velocidad de combustión debido a las inestabilidades de la llama, así como el análisis de la estabilidad de las llamas con respecto a una perturbación cíclica. Por último, los resultados se combinan para concluir el modelado de la inestabilidad acústica-paramétrica. Tras finalizar esta fase, la investigación se centro en la aplicación del modelo desarrollado en varios problemas de importancia para la seguridad industrial y el posterior análisis de los resultados y la comparación de los mismos con los datos experimentales correspondientes. Concretamente, se abordo la simulación de explosiones en túneles y en contenedores, con y sin gradiente de concentración y ventilación. Como resultados generales, se logra validar el modelo confirmando su idoneidad para estos problemas. Como última tarea, se ha realizado un analisis en profundidad de la catástrofe de Fukushima-Daiichi. El objetivo del análisis es determinar la cantidad de hidrógeno que explotó en el reactor número uno, en contraste con los otros estudios sobre el tema que se han centrado en la determinación de la cantidad de hidrógeno generado durante el accidente. Como resultado de la investigación, se determinó que la cantidad más probable de hidrogeno que fue consumida durante la explosión fue de 130 kg. Es un hecho notable el que la combustión de una relativamente pequeña cantidad de hidrogeno pueda causar un daño tan significativo. Esta es una muestra de la importancia de este tipo de investigaciones. Las ramas de la industria para las que el modelo desarrollado será de interés abarca la totalidad de la futura economía de hidrógeno (pilas de combustible, vehículos, almacenamiento energético, etc) con un impacto especial en los sectores del transporte y la energía nuclear, tanto para las tecnologías de fisión y fusión. ABSTRACT The exhaustion, absolute absence or simply the uncertainty on the amount of the reserves of fossil fuels sources added to the variability of their prices and the increasing instability and difficulties on the supply chain are strong incentives for the development of alternative energy sources and carriers. The attractiveness of hydrogen in a context that additionally comprehends concerns on pollution and emissions is very high. Due to its excellent environmental impact, the public acceptance of the new energetic vector will depend on the risk associated to its handling and storage. Fromthese, the danger of a severe explosion appears as the major drawback of this alternative fuel. This thesis investigates the numerical modeling of large scale explosions, focusing on the simulation of turbulent combustion in large domains where the resolution achievable is forcefully limited. In the introduction, a general description of explosion process is undertaken. It is concluded that the restrictions of resolution makes necessary the modeling of the turbulence and combustion processes. Subsequently, a critical review of the available methodologies for both turbulence and combustion is carried out pointing out their strengths and deficiencies. As a conclusion of this investigation, it appears clear that the only viable methodology for combustion modeling is the utilization of an expression for the turbulent burning velocity to close a balance equation for the combustion progress variable, a model of the Turbulent flame velocity kind. Also, that depending on the particular resolution restriction of each problem and on its geometry the utilization of different simulation methodologies, LES or RANS, is the most adequate solution for modeling the turbulence. Based on these findings, the candidate undertakes the creation of a combustion model in the framework of turbulent flame speed methodology which is able to overcome the deficiencies of the available ones for low resolution problems. Particularly, the model utilizes a heuristic algorithm to maintain the thickness of the flame brush under control, a serious deficiency of the Zimont model. Under the approach utilized by the candidate, the emphasis of the analysis lays on the accurate determination of the burning velocity, both laminar and turbulent. On one side, the laminar burning velocity is determined through a newly developed correlation which is able to describe the simultaneous influence of the equivalence ratio, temperature, steam dilution and pressure on the laminar burning velocity. The formulation obtained is valid for a larger domain of temperature, steam dilution and pressure than any of the previously available formulations. On the other side, a certain number of turbulent burning velocity correlations are available in the literature. For the selection of the most suitable, they have been compared with experiments and ranked, with the outcome that the formulation due to Schmidt was the most adequate for the conditions studied. Subsequently, the role of the flame instabilities on the development of explosions is assessed. Their significance appears to be of importance for lean mixtures in which the turbulence intensity remains moderate. These are important conditions which are typical for accidents on Nuclear Power Plants. Therefore, the creation of a model to account for the instabilities, and concretely, the acoustic parametric instability is undertaken. This encloses the mathematical derivation of the heuristic formulation of Bauwebs et al. for the calculation of the burning velocity enhancement due to flame instabilities as well as the analysis of the stability of flames with respect to a cyclic velocity perturbation. The results are combined to build a model of the acoustic-parametric instability. The following task in this research has been to apply the model developed to several problems significant for the industrial safety and the subsequent analysis of the results and comparison with the corresponding experimental data was performed. As a part of such task simulations of explosions in a tunnel and explosions in large containers, with and without gradient of concentration and venting have been carried out. As a general outcome, the validation of the model is achieved, confirming its suitability for the problems addressed. As a last and final undertaking, a thorough study of the Fukushima-Daiichi catastrophe has been carried out. The analysis performed aims at the determination of the amount of hydrogen participating on the explosion that happened in the reactor one, in contrast with other analysis centered on the amount of hydrogen generated during the accident. As an outcome of the research, it was determined that the most probable amount of hydrogen exploding during the catastrophe was 130 kg. It is remarkable that the combustion of such a small quantity of material can cause tremendous damage. This is an indication of the importance of these types of investigations. The industrial branches that can benefit from the applications of the model developed in this thesis include the whole future hydrogen economy, as well as nuclear safety both in fusion and fission technology.

Modeling of GRBAS perceptual evaluation using spectral features obtained from an auditory-based filterbank.

Perceptual voice evaluation according to the GRBAS scale is modelled using a linear combination of acoustic parameters calculated after a filter-bank analysis of the recorded voice signals. Modelling results indicate that for breathiness and asthenia more than 55% of the variance of perceptual rates can be explained by such a model, with only 4 latent variables. Moreover, the greatest part of the explained variance can be attributed to only one or two latent variables similarly weighted by all 5 listeners involved in the experiment. Correlation factors between actual rates and model predictions around 0.6 are obtained.