Tesis Doctorales

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Archivo Abierto Institucional de la Universidad Carlos III de Madrid: Tesis Doctorales Guía "Buscar tesis en e-Archivo"

Esta colección contiene tesis leídas en la Universidad Carlos III, cuyos autores han autorizado su depósito en E-Archivo. A partir de 2012 se depositan todas las tesis leídas en la Universidad Carlos III de Madrid, conforme a lo dispuesto en el Real Decreto 99/2011, de 28 de enero por el que se regulan las enseñanzas oficiales de doctorado (art. 14.5), y al Reglamento de la Escuela de Doctorado de la Universidad Carlos III de Madrid, de 7 de febrero de 2013 (art. 26.5, art. 31.1 y art. 32.2).

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    Data Analytics and Applied Machine Learning: Tool Health Monitoring in Automatic Drilling Operations in Aeronautical Structural Components
    (2024-02) Domínguez Monferrer, Carlos; Cantero Guisández, José Luis; Universidad Carlos III de Madrid.; Cantero Guisández, José Luis
    In aircraft manufacturing, the assembly process depends on creating multiple holes for accommodating bolts and rivets for the secure interlocking of structural components within the aircraft fuselage. The increasing integration of sensor systems in this domain has significantly enhanced data generation during hole-making. This development presents an opportunity to refine machining operations through real-time Tool Health Monitoring Systems. The focus of this doctoral thesis is on the utilization of data generated during automatic drilling operations in an aeronautical production system to reduce non-productive times and consumable costs, thereby fostering a highly efficient and adaptable machining ecosystem. The research centers on developing a Tool Failure Detection System and a Tool Wear Monitoring System. Both systems are based on a systematic methodology for collecting, processing and analyzing spindle power consumption data and other machining-related information. This development process utilizes cutting-edge Data Analytics and Machine Learning techniques to enhance the precision and effectiveness of the systems. The Tool Failure Detection System based on Multiresolution Analysis has demonstrated exceptional adaptability and high accuracy rates in diverse breakage scenarios involving various cutting tools. On the other hand, exploring the Tool Wear Monitoring System, employing a range of Machine Learning algorithms from Linear models to k-nearest Neighbors, Decision Trees, and Ensemble models, has highlighted the challenge of surpassing human-level performance. This challenge is attributed to data quality and quantity limitations. Future research will focus on overcoming current limitations and expanding the capabilities of these systems, further enhancing their practical application in other machining environments.
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    Metodología de análisis experimental y numérico de protecciones de cabeza para uso deportivo
    (2024-03) Mantecón Padín, Ramiro; Miguélez Garrido, María Henar; Díaz Álvarez, José; Universidad Carlos III de Madrid.; Díaz Álvarez, José
    Biomechanics is the science dedicated to analysing the mechanical behaviour of biological systems, encompassing both motion – kinematics – and the forces and stresses endured – dynamics –, two interdependent branches of biomechanical study. Analysis of the human body is hindered by the impossibility of in vivo testing characterising this mechanical response, along with the limited ex vivo representativity of biological tissues. Impacts sustained by the head constitute cases of particular interest due to the consequences arising from mechanisms of brain injury, spanning a wide range of potential effects from mild to severe. Analysing the biomechanical damage caused by impulsive loads on the head requires elements simulating the mechanical behaviour of the studied biological component. This thesis aims to develop a methodology for the analysis of head protective equipment based on the use of head surrogates. Manufacturing surrogates through additive technologies necessitates studying and analysing the fabrication process, given the peculiarities and variability of results associated with these technologies. Thus, the thermomechanical effect of the 3D printing process with the selected polymers for obtaining the surrogates was explored. The results indicate a need to control the method and selected parameters. This variability stems from the thermal evolution and the influence of the manufactured component's interactions with the elements of the printer, which makes it particularly interesting in the design of large components. This methodology was employed to design and manufacture skull surrogates with two alternative geometries, validating the material's small-scale mechanical behaviour and studying the effects of full-size manufacturing strategy. The designed substitutes underwent representative tests of the sports head protection evaluation methodology for cycling, conducting impact tests with a helmet demonstrator compared to a commercial surrogate. These surrogates were complemented with finite element models, demonstrating the great potential of the application of these surrogates in the biomechanical study of head impacts, enabling the assessment of other damage mechanisms not measured in experimental tests. These surrogates also result in cost reduction in testing campaigns, as well as the expansion of head protection evaluation methods, paving the way for future work to explore more complex and representative load scenarios observed in the sports domain.
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    Medical Grade Bioabsorbable Composites for the 3D Printing of Multi-Material Orthopaedic Devices
    (2023-12) Thompson, Cillian; Llorca Martínez, Javier; González Martínez, Carlos Daniel; Universidad Carlos III de Madrid. Departamento de Ciencia e Ingeniería de Materiales e Ingenieria Química; Agencia Estatal de Investigación (España); Campos Gómez, Mónica
    Biodegradable polymer composites fabricated by 3D printing may overcome many of the challenges associated with permanent non-degradable metals (Ti, stainless steel, Co-Cr) or with biodegradable polymers (PLA, PLGA, and PCL) and biodegradable metals (Mg, Zn, Fe) by achieving a final material with synergistic properties for orthopaedic implant applications. This thesis deals with the development of a filament production process for combining biodegradable polymers and metals through a two-step extrusion process. PLA was combined with Mg or Zn particles and extruded into filaments with constant diameter and a homogeneous dispersion of particles, suitable for 3D printing. This strategy was then used to 3D print biocompatible composites comprised of medical grade PLDL with a 4% volume fraction of Mg or Zn metallic particles. The addition of Mg and Zn to the PLDL material was able to increase the degradation rate of PLDL, and reduce the acidity of the PBS environment at 37◦C over a 1-year period. The addition of the particles slightly increased the stiffness, but reduced the strength of the PLDL due to the stress concentrations around the metallic particles. The composite materials exhibited excellent biocompatibility properties in terms of the material-cell interactions and cell proliferation. This study demonstrates that the addition of metallic particles to the polymer matrix can tailor the degradation properties but does not improve the mechanical properties. To overcome this latter limitation, a customised FFF 3D printer was developed to incorporate continuous metallic wires into a polymer matrix. The 3D printer comprised of 4 individual print heads capable of printing with 4 different materials, one of which was a continuous metallic wire, while the others could print thermoplastic polymers/composites. Unidirectionally reinforced PLA/Al wire composites were manufactured with 15% and 25% volume fractions of Al wire. The composite reinforced with 25% volume fraction of Al wires showed a six-fold increase in elastic modulus while the strength improved by 63% with respect to the polymeric matrix. Furthermore, medical grade PLDL composite coupons unidirectionally reinforced with a 15% volume fraction of Mg wires were manufactured by 3D printing. Mg wires with and without a surface treatment by plasma electrolytic oxidation were used. The mechanical properties showed a three-fold increase in the elastic modulus and up to a 80% increase in tensile strength compared to the matrix in air and at ambient temperature. Excellent interface strength was observed in the composites containing the Mg wire modified by plasma electrolytic oxidation. The oxide layer on the Mg wires reduced the degradation rate of the Mg wires and suppressed pitting corrosion. The mechanical properties of the PLDL matrix in the composite decreased dramatically when tested in water at 37◦C very likely because of the increased chain mobility induced by the disruption of the intermolecular interactions due to the synergistic contribution of water and temperature. Finally, a multi-material composite material was fabricated using three print heads on the customised printer. The coupon consisted of various layers of PLA, PLA reinforced with Mg particles, and PLA reinforced with Mg wires. This proof-of-concept demonstrates the possibility to create 3D printed multilayer scaffolds in which the properties of each layer can be tailored to meet specific requirements in terms of mechanical properties, degradation rate, and cytocompatibility, opening the path to manufacturing 3D printed multimaterial biomedical devices.
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    Design and processing of particle strengthened High Entropy Alloys by Powder Metallurgy
    (2023-09) Reverte Palomino, Eduardo; Cornide Arce, Juan; Universidad Carlos III de Madrid.; Comunidad de Madrid; Agencia Estatal de Investigación (España); Ministerio de Ciencia e Innovación (España); Gordo Odériz, Elena
    High entropy alloys (HEAs) are a family of materials that have recently raised attention in Materials Science. These alloys distance themselves from the traditional metallurgy of alloys with one element as the main component. Moreover, they are named multicomponent alloys, where up to 6 elements act as the main constituents of the material. Contrary to common alloys, the high entropy of mixing favours the formation of simple crystalline structures, such as BCC, FCC or, in minor cases, HCP. In terms of performance, they have shown good mechanical properties depending on the composition designed. Other properties include wear resistance, hardness and good oxidation resistance at high temperatures. These alloys’ novelty and unknown properties make them the subject of study for many industrial applications, more so if we consider the increasingly strict requirements pushing the development and optimisation of alloys further for new advanced applications. One example is the future technologies involving nuclear fission or fusion investigations. In this work, producing a novel HEA with body centered cubic structure (BCC) was studied with particle reinforcements that will strengthen the material, which could even improve the high temperature properties. The processing of this alloy is based on powder metallurgy (PM) techniques instead of standard casting techniques. The thesis follows all the stages of alloy production, from the design of the alloy, evaluating several thermodynamic parameters favouring obtaining a BCC structure, to the production of the powders and their consolidation. The design of the alloy focused on nowadays know-how of prediction rules for HEAs, which are mainly about thermodynamic parameters, such as entropy or enthalpy of mixing. Among them, the electron concentration factor of compositions was crucial to the design of the alloy. Finally, the composition was set to Al1.8CoCrCu0.5FeNi. Three different routes were used for the production of powder, (1) elemental powder blends, (2) gas atomisation and (3) high energy milling. The powder blend route was discarded for the atomised powder for later hardening by oxides. The crystalline structure of the atomised powder was a main BCC phase, with minor segregation of copper. The quality of the powders was addressed with various characterisation techniques such as density measurements, particle sizes, differential thermal analysis (DTA) and X-ray diffraction (XRD). In this context, the prediction of the alloy’s structure was accurate as it was designed initially. The next challenge of the PhD was the sintering stage of the powders, studying techniques such as Spark plasma sintering (SPS), conventional Press and Sinter (P&S) and Electrical Resistance Sintering (ERS). The differences in heating rates and sintering times resulted in multiple phase morphologies and arrangements. These samples were studied via scanning electron microscope (SEM), X-ray diffraction (XRD), differential thermal analysis (DTA) and transmission electron microscopy (TEM) to observe the influence of the processing route. For the introduction of the oxides, the milling process was optimised, evaluating the morphology, microstrain and crystallite size of the lattice structure during the process. Afterwards, the powder was consolidated following the results of standard HEA samples and analysed using similar techniques. The strengthened material showed an increase in hardness values compared to the base HEA.
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    Multiple localization and fracture in metallic rings and plates subjected to dynamics expansion
    (2023-12) Murlidhar, Anil Kumar; Rodríguez Martínez, José Antonio; UC3M. Departamento de Mecánica de Medios Continuos y Teoría de Estructuras; European Commission; Rodríguez Martínez, José Antonio
    Ductile materials are commonly used in high-strain rate applications involving impact or blast loads due to their notable capacity to absorb energy and undergo plastic deformation before fracture. Over the last two decades, studies on dynamic strain rates have evolved dramatically, leading to a better knowledge of material behavior under high-speed loading situations and generating advances in a variety of industries. Imperfections in ductile metals, such as cracks, inclusions, and voids, are significant, and these imperfections can significantly impact the material’s mechanical properties and structural integrity, thereby affecting its suitability for various industrial applications. Hence, further research is necessary to understand the mechanical behavior of ductile metals with imperfections. This doctoral thesis investigates the effect of porosity, anisotropy, and tensioncompression asymmetry on the mechanical response of metallic materials under dynamic loading conditions. In the first part of the thesis, we used linear stability analysis and unit-cell finite element calculations to investigate the onset of necking instabilities in porous ductile plates under biaxial loading. In the next part of the work, we used three techniques-linear stability analysis, a nonlinear two-zone model, and unit-cell finite element calculations-to examine the necking formability of anisotropic and tension-compression asymmetric metallic sheets subjected to in-plane loading paths spanning plane strain tension to near equal-biaxial tension. The last part of the study focused on examining the fragmentation process of 3D-printed AlSi10Mg porous ring specimens. This was achieved by implementing two experimental ring expansion test setups and subjecting the aluminum alloy to electromagnetic and mechanical loadings. The objective was to gain insights into the behavior of these alloys when exposed to high strain rates.
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    Non-myocytes as electrophysiological contributors to cardiac conduction and atrial fibrillation maintenance
    (2024-01-15) Simón Chica, Ana; Kohl, Peter; Figueiras Rama, David; UC3M. Departamento de Bioingeniería; Vaquero López, Juan José
    Cardiac research has traditionally focused on the electrical and mechanical activity of cardiomyocytes (CM). However, the heterocellular nature of the heart has received more attention in recent years. In addition to CM as the key cell type responsible for the electromechanical activity of the heart, non-myocytes (NM) such as endothelial cells, fibroblasts, or immune cells are emerging as key players, influencing and modulating CM activity. This thesis aims at providing new insights into direct and indirect electrophysiological interactions between NM and CM, and their implications in cardiac conduction and arrhythmias. The followed research approach, ranging from basic electrophysiological characterization to computational modeling and translational animal models, provides a multifaceted perspective on the relevance of NM in cardiac electrophysiology under both homeostatic and patho-physiological conditions. In the first part of this thesis, we characterize passive and active electrophysiological properties of murine cardiac resident macrophages, and model their potential electrophysiological relevance for CM. We combined classic electrophysiological approaches with 3D florescence imaging, RNA-sequencing, pharmacological interventions, and computer simulations. Our results provide novel electrophysiological characterization of cardiac resident macrophages, and a computational model to quantitatively explore their relevance in the heterocellular heart. In the second part of the thesis, we focus on distinguishing electrophysiological effects of NM in patho-physiological remodelling, when NM change their phenotype, proliferate, and/or invade from external sources. More specifically, we study the role of NM on atrial fibrillation (AF) maintenance. The clinical relevance is highlighted by the fact that AF is the most frequent sustained cardiac arrhythmia, and nowadays there is no definitive treatment. Part of longterm inefficacy of pharmacological and ablation therapies can be explained by atrial functional and structural changes associated with AF remodelling. In fact, the role of NM on modulating atrial remodelling and their implications on longterm AF maintenance are poorly understood. Here, we generated a translational porcine model of long-term self-sustained persistent AF to identify the mechanisms underlying AF progression and maintenance. This pig model enabled us to use clinically-applicable tools for investigation tasks, therefore enhancing the clinical translation of the results. We analysed electrical, structural and inflammatory changes during AF progression from early stages of atrial remodelling to long-term persistent stages of advanced atrial cardiomyopathy. More specifically, we studied two clinically relevant porcine models of AF: (i) a model resembling lone AF progression without underlying structural heart disease (PsAF), and (ii) a second model with infarctrelated atrial myopathy (MI-PsAF) to increase the translational impact in clinical scenarios with other common comorbidities like ischaemic cardiomyopathy. The study was mainly focused on two NM populations that included the fibroblasts and immune cells and how they contribute to AF maintenance. We specifically performed single-cell RNA sequencing (scRNA-seq) for identifying these two cell phenotypes and their changes in animals with AF compared to sham-operated controls. Animals underwent advanced electroanatomical mapping in vivo to identify specific atrial regions associated with AF maintenance (i.e., driver regions). Further ex vivo studies after electroanatomical mapping showed differential molecular and histopathological properties between driver and nondriver regions during AF. Finally, we focused the analyses on regional differences of fibroblasts and immune cell populations that may explain hierarchical organization of atrial regions, which further support the notion that AF maintenance relies on a few atrial regions capable of sustaining higher than surrounding activation rates.
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    Análisis y optimización del convertidor dual active bridge con triple fase desplazada, conmutación suave en todo el rango de funcionamiento, y mínima corriente eficaz
    (2023-09) Calderón Benavente, Carlos Alberto; Barrado Bautista, Andrés; UC3M. Departamento de Tecnología Electrónica; Barrado Bautista, Andrés
    Los actuales retos medioambientales de la sociedad están motivando que muchos sistemas basados en el uso de combustibles fósiles se transformen en sistemas más eléctrico, como los vehículos híbridos o los vehículos completamente eléctricos. Esta tendencia, también se puede apreciar en otros sectores, tal como en el sector de las energías renovables, o en general en aquellas aplicaciones donde se requiera del almacenamiento de energía en fuentes de energía secundarias, como son las baterías y supercondensadores. Para llevar a cabo esta transformación, los convertidores bidireccionales forman parte importante del conjunto de convertidores que se utilizan para conseguir sistemas más eléctricos. Los convertidores bidireccionales presentan múltiples topologías, y se pueden clasificar como aislados y no aislados. De entre los convertidores bidireccionales aislados se encuentra la topología denominada Dual Active Bridge, que en la actualidad despierta un gran interés para los investigadores. Esta tesis, se centra en el análisis de los modos de conmutación del convertidor Dual Active Bridge que se pueden obtener con una estrategia de modulación por triple desfase o Triple Phase Shift (TPS), considerando las condiciones de funcionamiento reductora y elevadora, cubriendo así, una necesidad presente en el estado de la técnica. Además, se realiza un análisis completo para conseguir una conmutación suave en todos sus interruptores. Adicionalmente, se desarrolla un método del optimización sencillo, basado en la reducción de la corriente RMS por la bobina en serie que se incluye en la topología Dual Active Bridge, en comparación con los propuesto en la literatura. También, se propone una alternativa que reduce la complejidad de la implementación en los dispositivos digitales, sin poner en riesgo la actualización de los parámetros de control en modo online. Con el objetivo de proporciona autonomía y flexibilidad al sistema, se realiza el diseño de un regulador digital y de una interfaz que permite cambiar las condiciones de funcionamiento de manera online. Finalmente, el estudio teórico realizado se valida a través de simulaciones y a nivel experimental, mediante un prototipo de 1kW. El análisis, desarrollo de los procedimientos propuestos, diseño e implementación se estructuran en los siguientes capítulos: En el Capítulo 1 se realiza la introducción de la problemática presente sobre el uso de los combustibles fósiles en los diferentes sectores y su impacto en el medioambiente. Como respuesta a este problema, la tendencia social evoluciona hacia un mundo más eléctrico que reduzca las emisiones al medioambiente. Partiendo de esta idea, los convertidores bidireccionales forman parte de esta propuesta, en sus diferentes topologías en función de las necesidades del sector de aplicación. Resaltando la importancia del convertidor Dual Active Bridge. En el Capítulo 2 se enfoca en el análisis del estado de la técnica de las diferentes estrategias de modulación que son aplicadas en Dual Active Bridge, y en los diferentes métodos de optimización. A partir del análisis previo, se presenta los objetivos de la tesis. En el Capítulo 3 se realiza un profundo análisis de los modos de conmutación presentes en el Dual Active Bridge bajo una modulación por triple desfase. En este análisis, se definen cuatro Casos de estudio y 14 modos de conmutación por Caso de estudio, al considerar desfases positivos y negativos, Además, se realiza un análisis para obtener conmutación suave en todos los interruptores. En el Capítulo 4 se presenta un análisis para obtener una mínima corriente RMS a través de la bobina, para todo el rango de funcionamiento. El resultado del análisis muestra que la trayectoria de mínima corriente se compone de tres Trayectos (AB, BC y CD), y se propone un método para obtenerlo sin hacer uso de métodos de optimización complejos. Adicionalmente, se propone la linealización del Trayecto BC que permite la optimización desde el punto de vista de la implementación en los dispositivos digitales. El Capítulo 5 se enfoca en el modelado de todas las partes que componen el convertidor Dual Active Bridge, y en el diseño del regulador digital que incluye el cálculo de los parámetros óptimos. Además, se desarrolla el software y el firmware que permiten el funcionamiento en lazo cerrado del convertidor, así como la interfaz con el usuario que posibilita un funcionamiento online del convertidor Dual Active Bridge. Finalmente, en el Capítulo 6 se presentan las conclusiones del trabajo realizado en la tesis, así como los trabajos futuros que no sean podido abarcar en esta investigación.
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    Weakly supervised Deep Learning for Natural Language Processing
    (2023-06) Colón Ruiz, Cristóbal; Segura Bedmar, Isabel; UC3M.; Segura Bedmar, Isabel
    The main hypothesis of this Ph.D. dissertation is that the use of transfer learning mechanisms, semi-supervised approaches and pre-trained generative language models can improve the performance of models in scenarios with limited annotated data. This can be achieved by transferring the learned knowledge from one task to another, reducing the need for large amounts of annotated data, and generating synthetic instances or representations that enrich the training set, improving the robustness and generalization of the models. In particular, using Deep Learning algorithms that allow acquiring knowledge from tasks with similar features can mitigate the bottleneck problem of lack of rich annotated corpora, thus improving the learning of relevant features for specific Natural Language Processing tasks. The increasing availability of Electronic Health Records (EHR) and patient reviews has resulted in a large volume of clinical documents where some information is unstructured. Due to the high cost of time and resources to extract information from clinical texts, there has been an increased interest in research and development of Natural Language Processing techniques to automate the process and optimize research into new clinical solutions and approaches to improve patient results. However, clinical documents present additional challenges compared to generic texts due to the difference in the language features used, specific acronyms, and non-standardized jargon by each system or clinical center. In addition, the need to de-identify and anonymize texts to guarantee data privacy means that access to clinical documents is limited, leading to a scarcity of annotated corpora. In the present document, datasets consisting of drug reviews and EHRs are employed for Sentiment Analysis and Named Entity Recognition tasks in few-data scenarios in order to validate the hypothesis. The results show that pre-trained models on large corpora based on transformers overcome other Deep Learning algorithms. However, its performance declines when the number of annotated data is limited or when classes are under-represented. Furthermore, the results suggest that employing unlabeled data in semi-supervised approaches or including synthetic instances of pre-trained generative language models improves the performance of discriminative models fine-tuned in a few-data scenario. However, their performance decreases when there is enough training data to learn task-specific relevant features.
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    Development of systems based on visible light communications for high added value applications
    (2023-10) Betancourt Perlaza, Juan Sebastián; Torres Zafra, Juan Carlos; Sánchez Pena, José Manuel; UC3M. Departamento de Tecnología Electrónica; Comunidad de Madrid; Sánchez Pena, José Manuel
    The discovery of the blue Light-emitting diodes (LEDs) in the last decade of the last century changed the way we as a society approach the need for artificial lighting, as the combination of the blue light emitted by the LED with a yellow phosphor layer reactive to the blue wavelength generates white light. White LEDs are more efficient than incandescent bulbs and last longer, which is a benefit not only for the end user but for everyone as the energy used for lighting could be significantly reduced and therefore the impact on the environment. LEDs not only improve the efficiency of existing light bulbs, but because they are based on semiconductors, their switching speed is several orders of magnitude higher than other types of illumination technologies. On the other hand, the radio frequency spectrum is becoming saturated due to the incredible rate at which more and more devices are being connected wirelessly. The growing market of Internet of things (IoT) devices and the concept of the smart home, where everything can be connected and controlled from the palm of your hand, has limited the available bandwidth for data exchange with the Internet. However, because wireless communications can penetrate walls and travel tens of meters, even in low-power devices, our devices are not the only ones fighting for a space to transmit information, but we share the available channel with all of our neighbors’ devices. This ability of signals to cross physical borders also threatens our data security, as the data may be accessible to third parties. Considering these two ideas, Visible light communication (VLC) is gaining a lot of interest in recent years, as it can provide a secure connection limited to the light spot where it is transmitted. In this way, LED bulbs will not only cover our need for lighting but also support part of the communication, helping to free up the radio frequency channel. VLCs also offers alternatives in places with high electromagnetic interference, and the bandwidth is fully available for each transmitter. VLC has also been recognized as a viable technology for indoor positioning, as the system can know where it is, based on transmitter localization (LED lamp). This is particularly useful because it can achieve centimeter accuracy, which is impossible with other positioning systems such as satellite navigation. Therefore, this thesis work aims to design and develop a working VLC system that supports multiple end applications. The intended system must be small and inexpensive to be attractive for future adaptations. With this we try to gain knowledge about the inherent challenges that VLC systems have and, with it, help VLC technology to go one step further to be useful and adaptable to our daily lives. First, we realized that LEDs are a main element in any VLC system, and therefore the more knowledge we have about it, the better performance we can achieve with this type of solution. VLC uses Intensity modulation/Direct detection (IM/DD) to transmit information, and to do so, the intensity of the LED is varied over time by modulating the current injected into the device. For this reason, the knowledge of the electrical equivalent of the LEDs is a useful tool for the correct design of VLC systems. In this thesis work, we have proposed a method to electrically characterize high-power white LEDs and, with it, create an equivalent electrical circuit useful for simulation and driver design. Then, we study the different modulation formats used in wireless communication channels and the modulation formats that can only be implemented with VLC, such as Color shift keying (CSK). In this aspect, we have noticed that even if the modulation formats are mature and well known, VLC channels present some peculiarities that need to be explored more deeply in order to adapt the modulations to this type of channel. In the case of this thesis, we explore the implementation of an Orthogonal frequency division multiplexing (OFDM) modulation in a VLC channel, and with it, we found a novel way to perform the time synchronization and phase correction in a pilot-based OFDM. The requirement that the transmitted signal be real was overcome by using the hermitian symmetry property of the Inverse fast Fourier transform (IFFT). In summary, we were able to develop a working VLC system in all stages, hardware, firmware, and software, reaching transmission speeds up to 234 kbps. The system works with a custom Android application designed for this prototype. The received light information is transformed into bits at the receiver and then sent through Bluetooth low energy (BLE) to the Android device. The application processes the received data and displays useful information to the user. In this prototype, the information is used for indoor localization, but it is not limited to that. The system also supports the addition of Augmented reality (AR) glasses to enhance the user experience. The transmitter prototype is an LED bulb, which can be connected directly to the power grid with a GU-10 or GUZ-10 socket. The VLC receiver measures 34.5x46.6x17.6mm, and it is powered by a CR2032 battery.
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    Design and development of a linear beam-down concentrated solar technology for industrial applications
    (2024-02) Taramona Fernández, Sebastián; Santana Santana, Domingo José; Gómez Hernández, Jesús; Universidad Carlos III de Madrid.; UC3M. Departamento de Ingeniería Térmica y de Fluidos; Santana Santana, Domingo José
    Recientemente, se ha venido llevando a cabo un esfuerzo importante para descarbonizar la generación de electricidad, así como para reducir las emisiones asociadas al sector del transporte. Esto se ha logrado principalmente mediante la implementación de tecnologías renovables. Sin embargo, hay otro sector que ha sido dejado en segundo plano: el sector industrial. Los procesos productivos requieren tanto energía eléctrica como calor, y las Tecnologías de Concentración Solar (CSTs) se presentan como una alternativa para suministrar el calor necesario a los procesos industriales, ya sea de manera directa o indirecta. Los reflectores lineales Fresnel (LFRs) son una CST que utiliza varias filas de espejos ligeramente curvados para concentrar la radiación solar de manera lineal en un receptor situado sobre ellos. Esta tecnología puede lograr concentraciones de hasta 80 soles y temperaturas operativas entre 250 y 560 °C, coincidiendo con procesos industriales de media temperatura, como la destilación o el secado. Un beam-down es un reflector secundario ubicado encima de la línea de espejos primarios que redirige la energía solar concentrada hacia el suelo. Se basa en figuras bifocales, aprovechando su propiedad óptica donde todos los rayos dirigidos a un punto focal, al ser intersectados por la forma, se reflejan hacia el otro foco. Acoplando un reflector secundario beam-down con un LFR, se pueden procesar materiales particulados pesados, como agregados de asfalto, cerca del suelo con calor solar concentrado aplicado directamente. Esta tesis tiene como objetivo contribuir a la descarbonización de procesos industriales de baja-media temperatura, diseñando, desarrollando, construyendo y probando un reflector lineal Fresnel beam-down para casos de uso industrial, centrándose en particular en el secado de áridos asfálticos. En primer lugar, se desarrolló el proceso de diseño del campo solar. En el enfoque adoptado en esta tesis, el beam-down está compuesto por espejos planos ubicados a la misma altura, lo que permite reducir costos y simplificar el proceso de construcción. Para este caso, se caracterizó el rendimiento del campo solar utilizando dos parámetros adimensionales que relacionan la altura focal con el ancho de apertura solar y la altura del beam-down. Se puede lograr una concentración de entre 31 y 17 soles, con eficiencias ópticas que varían entre el 40 y el 60% con respecto a las concentraciones anteriores. Posteriormente, se adaptó una configuración del campo solar que maximiza la concentración para construir un prototipo solar utilizando espejos planos tanto para el campo LFR como para el beam-down. Se comparó el dispositivo final con el diseñado y se estudió experimentalmente en pruebas solares, donde se midió una concentración promedio de 6.91 soles con una eficiencia óptica del 34.41% sobre un receptor de 10 cm de ancho. Además, se realizó un análisis de los diferentes componentes de la eficiencia, demostrando los principales factores a mejorar para las siguientes iteraciones de pruebas. El diseño del prototipo se utilizó como base para realizar un Análisis del Ciclo de Vida de esta tecnología, estudiando el impacto en el Potencial de Calentamiento Global (GWP), el Potencial de Agotamiento de Ozono (ODP) y las Partículas en Suspensión (PM), así como la energía anual producida de un campo solar con una apertura fija, pero con diferentes alturas de beam-down. Se encontró que los beam-downs más bajos requieren más materiales y presentan un mayor GWP, mientras que al considerar la energía anual producida, una altura de beam-down entre 0.51 y 0.75 veces la altura focal generó resultados similares en términos de GWP, ODP y PM. De estas alturas, la más alta produjo la mayor energía anual con concentraciones de aproximadamente 15 soles. Se desarrolló un modelo numérico utilizando MATLAB para simular el secado de un lecho de partículas directamente irradiado desde arriba, como en la tecnología solar estudiada. Este modelo adoptó un enfoque macroscópico Lumped, donde los flujos de calor y masa se resuelven para un pequeño incremento temporal con las condiciones del lecho en un momento específico, y después de encontrar la solución, se actualizan las condiciones del lecho y se repite el proceso hasta que se cumple el criterio de detención deseado. Este puede ser un tiempo total de simulación, una temperatura específica o un porcentaje de humedad dentro del lecho. Este modelo fue validado con pruebas experimentales al sol, donde se calentó y secó un lecho de partículas utilizando la radiación solar concentrada. El modelo mostró una buena correlación con los resultados experimentales, donde un lecho de 9 mm de profundidad fue secado en menos de 30 minutos con un flujo de calor entrante de 2.63 kW/m2. Se obtuvieron resultados adicionales al modificar la profundidad del lecho y el flujo de calor, y se encontró que la profundidad es un parámetro de mayor importancia que la concentración solar, ya que lechos de 1 cm de profundidad con un 5% de contenido inicial de humedad pueden secarse en menos de 10 minutos al concentrar más de 18 kW/m2. Finalmente, se adaptó un campo solar comercial existente con un beam-down. Este reflector secundario se diseñó teniendo en cuenta la configuración LFR y considerando que fuera fácil de instalar. Se tomaron medidas experimentales y se compararon con los resultados esperados, donde los 4100 W/m2 medidos no alcanzaron los 7750 W/m2 esperados, principalmente debido a errores constructivos en la altura del reflector beam-down. Es importante señalar que el campo solar tenía una orientación casi Este-Oeste, con una inclinación del eje longitudinal de 18° según el sentido de las agujas del reloj, respecto al eje Este-Oeste, y los espejos solares no estaban en condiciones óptimas al tomar las mediciones. Para las condiciones de diseño con una orientación Norte-Sur y mediodía solar, se esperaba que el LFR modificado con el beam-down concentrara 16 soles.
  • Publication
    Unsteady Aerodynamics of Delta Kites applied to Airborne Wind Energy Systems
    (2023-10) Castro Fernández, Iván; Sánchez Arriaga, Gonzalo; Cavallaro, Rauno; Universidad Carlos III de Madrid.; Ministerio de Educación, Cultura y Deporte (España); Agencia Estatal de Investigación (España); Sánchez Arriaga, Gonzalo
    Airborne wind energy (AWE) is an emerging field within the wind power sector that aims at harvesting energy or gain traction from tethered aircraft flying at high altitudes. Aerodynamics becomes one of its critical areas due to its influence on both the flight physics and the energy generation process during typical figure-of-eight and circular trajectories. Despite the dynamic nature of these maneuvers, unsteady aerodynamics remains nearly unexplored in AWE. This dissertation studies the aerodynamics of a two-line rigid-framed delta kite applied to AWE with the objective of improving the aerodynamic understanding and preparing models to be combined with dynamic and control software. The contents are classified into two main blocks: the first focuses on numerical unsteady aerodynamics, and the second involves the preparation and testing of a small-scale AWE testbed aimed at the aerodynamic characterization of kites. The first block investigates the aerodynamics of the delta kite through numerical simulation with particular emphasis on the unsteady behavior. A fast unsteady potentialflow aerodynamic tool (UnPaM) was firstly benchmarked against experimental data from a previous flight test campaign. The estimated state vector included the kinematic state of the kite (aerodynamic velocity vector and angular rates, among others) and the aerodynamic force and moment coefficients about the kite center of mass. The recorded kite kinematics was prescribed in UnPaM and the resulting numerical aerodynamic coefficients were compared with the experimental counterparts. The inviscid tool was able to reproduce the order of magnitude and trend of the experimental lift and lateral force coefficients versus the angle of attack and sideslip angle, respectively. The drag coefficient was underestimated by UnPaM, which ignores viscous drag and flow separation. Although the numerical and experimental moment coefficients were in the same order, the comparison was cumbersome due to experimental uncertainties. Moreover, steady, quasi-steady and unsteady potential-flow effects were compared by performing three independent simulations with UnPaM. The quasi-steady assumption, which considers the full kite kinematics but neglects wake roll-up, among others, resulted sufficient for this case study. A further post-processing of the former experimental data and new flow visualization data of the delta kite suggested dynamic stall phenomenology induced by periodic changes in the angle of attack. These evidences inspired a numerical study on dynamic stall by using three unsteady aerodynamic tools at different levels of approximation and computational cost. The first is the potential-flow tool UnPaM presenting the lowest fidelity. The second tool is the open-source computational fluid dynamics (CFD) code SU2 configured to solve the Reynolds-averaged Navier-Stokes equations closed with the k − ! SST turbulence model. The third, with a fidelity level between UnPaM and SU2, is a semi-empirical dynamic stall tool based on the Leishman-Beddoes model that combines attached flow through UnPaM with a phenomenological module. The latter consists of three ordinary differential equations with free empirical parameters that were fine tuned with CFD data from SU2. The periodic kite kinematics was imposed in the three tools and the aerodynamic coefficients were compared among one another and the experimental results. UnPaM was unable to reproduce dynamic stall due to its inherent inviscid nature. The CFD and semi-empirical tools provided very consistent lift and drag coefficients versus the angle of attack curves that qualitatively matched the experimental hysteresis behavior. Moreover, a leading-edge vortex that periodically forms and detaches on the kite extrados was identified from CFD data corroborating experimental flow visualizations. Finally, a preliminary analysis of aerostructural deflections revealed that dynamic stall and fluid-structure interaction may work collaboratively causing stronger hysteresis cycles. The second block of this dissertation focuses on the development and testing of a small-scale AWE infrastructure for aerodynamic, dynamic and control characterization of two-line and three-line kites. The testbed consists of a rigid-framed delta kite and a ground control unit on the air and ground segments, respectively. The kite avionics includes an inertial measurement unit, a magnetometer, two differential GNSS receivers and a flow visualization system. The latter was used to record surface tufts covering the kite extrados. The control unit has lateral steering and reel-in/reel-out capabilities through an automatic linear actuator and a winch. Moreover, it is equipped, among others, with load cells, a wind station and a novel visual motion tracking system. The latter is based on three cameras and an artificial neural network and has the capability of reconstructing the kite position and course angle. The results of a five-min flight were used to characterize the control of the delta kite and ground control unit. Linear correlations between the time derivative of the course angle and the delayed steering input and differential tether tension were identified. The dispersion between the time derivative of the course angle and the differential tether tension was lower, suggesting that such a variable may be adequate to close the control loop. The reconstructed kite position and course angle by the visual motion tracking system presented a good agreement with independent onboard data. Moreover, the three-camera system proved robust due to its nearly continuous operation (99.9% of the time), opening the possibility of using it as a redundant observation or backup system for the avionics.
  • Publication
    Augmented Reality in Image-Guided Therapy to Improve Surgical Planning and Guidance
    (2023-11) Pose Díez de la Lastra, Alicia; Pascau González-Garzón, Javier; Universidad Carlos III de Madrid.; Pascau González-Garzón, Javier
    The latest technological advancements have propelled image-guided therapy (IGT) to achieve remarkable progress in enhancing surgical outcomes. Traditional commercial navigation systems have been long used to provide surgical guidance by offering accurate pose information of surgical tools in relation to the patient. However, cost, and physical requirements limit their availability in many treatment scenarios. Moreover, they show information on external screens, diverting physicians' attention away from the patient. In contrast, augmented reality (AR) emerges as a promising solution, harnessing the potential to provide more affordable and space-efficient alternatives that deliver intuitive and immersive experiences within surgical scenarios. As such, this thesis explores the integration of this technology in the medical field, following IGT methodology to enhance surgical planning and guidance. AR technology can be deployed onto cost-effective, hand-held devices, offering a shared view of virtual information. Conversely, head-mounted displays (HMD), commonly called AR glasses, provide a more intuitive and immersive experience to the wearer. Previous works have explored AR solutions to enhance surgical workflows. However, their implementations often prove too specific for the targeted task or are hardly transferable to real clinical practice. In this thesis, we present universal solutions for both types of AR devices that aim to enhance surgical workflows. Our approaches have been meticulously developed in collaboration with expert clinicians, always incorporating real clinical experience, including patients' data, to ensure the robustness and direct translation of our advancements into clinical practice. We began by exploring the implementation of AR technology in microtia correction procedures using flat-screen devices. Accompanied by 3D printing technology, the AR application facilitates the precise creation and placement of a reconstructed ear within a patient. The approach's usability and accuracy were validated through controlled experiments, showcasing significant improvements over traditional methods, and achieving results comparable to state-of-the-art AR projection systems. Notably, the system underwent testing during an actual surgery, and the outcome demonstrated a divergence of only 2.7 ± 2.4 mm from the ideal plan. This minimal error accounts for morphometric deviations resulting from inflammation and other issues intended to be addressed in a subsequent stage of surgery. Consequently, we can confidently assert that the overall error induced by the AR system remains negligible, firmly supporting the adoption of hand-held AR for surgical guidance in similar scenarios. Excited by the promising results of our methodology, we transferred it to a HMD and explored the capabilities these devices offer to interact with virtual information. To kickstart, we integrated the AR tracking method presented in the previous chapter on the two generations of Microsoft's seethrough AR headsets. Employing patient-specific phantoms from orthopedic oncological surgeries, we calculated the AR projection accuracy attained by both models. Furthermore, we evaluated the influence of the technical enhancements in the second model to endorse its use for surgical guidance. The favorable outcomes gleaned from our experimental analysis, coupled with the positive feedback received from surgeons, encouraged us to further our research in this domain. Then, we sought to develop an alternative method for automatic registration between the virtual and real worlds. Specifically, we compared the AR tracking capabilities offered by the Vuforia SDK with those provided by blob detection algorithms and image processing from depth camera information. We designed and conducted experiments both in simulation and surgical scenarios. Both tracking methods exhibited sufficiently low enough errors, affirming their suitability for clinical tasks. Consequently, we concluded that the choice between these methods can be based on the specific application requirements and the available resources. Despite the significant achievements in our previous work, we recognized that the limited computational capabilities of AR glasses compared to computers impose constraints on developing highly complex AR applications. In the final chapter of this thesis, we aimed to leverage the integration of 3D models into the real world offered by HMD and the medical image processing capabilities of 3D Slicer image computing platform. To achieve this, we utilized OpenIGTLink to establish a seamless communication link between both platforms, enabling the transfer of geometrical transformations and images in real time. The resulting application allows users to intuitively manipulate a virtual plane over a 3D model of a patient using their hands and simultaneously viewing real-time resliced CT images received from 3D Slicer. We tested this application in the clinical context of pedicle screw placement planning, although experimental outcomes indicated that the system could be readily adaptable to almost any other clinical application. The key contribution lies in the potential for easy communication with other HMD devices for collaborative decision-making, or even with other OpenIGTLink-compatible devices, such as conventional tracking systems. This integration not only may enhance the precision of the AR glasses but also broaden the scope of possible applications. Overall, our results will facilitate advanced surgical practices and seamless collaboration among medical professionals. Overall, the thesis demonstrates the transformative potential of integrating AR technology into surgical workflows, offering enhanced precision and improved outcomes.
  • Publication
    Development of Models Simulating Multiple-Simultaneous Contact Events Using the Multibody System Dynamics
    (2023-12) Gismeros Moreno, Raúl; Corral Abad, Eduardo; UC3M. Departamento de Ingeniería Mecánica; Meneses Alonso, Jesús
    The development of computing technology in the last decades has led to the emergence of a wide variety of methodologies aiming at reducing the costs of design, manufacturing and maintenance stages of products during their life cycle. Out of these three phases, maintenance has proved to have the biggest impact in most industrial contexts both in terms of energy consumption and economical costs. For this reason, the proposal of different techniques that allow an accurate simulation of the working conditions of mechanical systems and an early detection of any possible faults that can arise is of interest to researchers and industry. In this thesis, special attention is paid to the definition of computational modelling methodologies based on multibody dynamics which can be used as digital twins, which allow the virtualization of certain conditions of the real system, thus playing an important role in the early identification of potential issues, prediction of failures, and optimization of maintenance processes of industrial systems. Emphasis will be placed on the modelling of systems in which multiple contact events take place simultaneously, which is a trending and challenging research topic. In this regard, a comprehensive review of the existing methodologies is carried out. Then, an in-house code will be used to test the proposed algorithms by using a simple validation application. The conclusions obtained will subsequently be applied to the simulation of mechanical elements in working conditions. The results obtained are consistent with those available in the literature, both theoretical and experimental, and set a wide variety of paths for future research lines.
  • Publication
    Desarrollo de aleaciones de alta entropía con Cu para su uso en reactores de fusión nuclear
    (2023-10) Rodríguez López, Álvaro; UC3M. Departamento de Física; Comunidad de Madrid; Ministerio de Ciencia e Innovación (España); Agencia Estatal de Investigación (España)
    High entropy alloys (HEAs) have garnered significant attention from both academic and industrial research communities due to their exceptional structural and functional properties. However, the exploration of Cu-based HEAs remains a relatively underexplored area, leading to a limited understanding of this alloy class. The primary objective of this thesis is to produce and characterize HEAs with low activation elements for potential application in nuclear fusion reactors. To accomplish this objective, the research is divided into three sections: i) Design, fabrication, and characterization of the CuCrFeVTi HEA family. The Cu content within the alloys was systematically varied to investigate the influence of this element on microstructure and mechanical properties. Based on the obtained results, the optimal Cu content was determined. ii) Study of the Cu5Cr35Fe35V20(Ti, Ta, W, Mo)5 HEA system. Four alloys were examined, each alloy varying a single element while maintaining the same atomic ratios as the most favorable composition determined in part i). Microstructural and mechanical properties were analyzed, and the results were correlated to the compositional differences. iii) Assessment of HEAs as potential thermal barriers. The thermal properties of the Cu5Cr35Fe35V20(Ti, Ta, W, Mo)5 alloys were evaluated to determine their viability as thermal barriers. By undertaking this research, the thesis aims to contribute to the understanding of Cu-based HEAs containing low activation elements, with the ultimate goal of advancing their use in nuclear fusion reactor applications.
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    Aplicación de herramientas de Inteligencia Artificial como metodología emergente para el análisis de la toxicidad de la conversación en redes sociales
    (2024-04) Carral Vilar, Uxia; Elías Pérez, Carlos José; Universidad Carlos III de Madrid.
    Se estudia una nueva metodología de inteligencia artificial (IA), entendiendo que la comunicación se presenta como uno de los campos de trabajo más trascendentes para su aplicación. Además de las fases de recolección y producción de contenido, otras áreas dentro del mundo de la comunicación como la distribución, y en concreto la moderación de comentarios -en plataformas sociales y en medios- también están viviendo un período de innovación, pero de forma menos evidente de cara a la audiencia. Por ello, en este trabajo de investigación se procede a conocer cómo el ensamblaje entre diversas herramientas de IA (Communalytic, Perspective API y Botometer) puede medir la calidad de la conversación y combatir la toxicidad en espacios comunicativos. Para ello, se han analizado 125,551 tweets publicados entre el 1 y el 15 de abril de 2023 correspondientes a quince políticos de España, Francia e Italia y a la cascada de contestaciones recibidas de sus audiencias. De esta manera, las herramientas de IA permiten conocer en detalle las tasas de diversas categorías de toxicidad y la tipología de la naturaleza de los usuarios que conversan. En consecuencia, se han abierto varias líneas de discusión sobre la generación de toxicidad y el incremento de bots según factores geográficos, institucionales y de género. Igualmente, se percibe una diferencia de comportamiento en los usuarios entre la conversación horizontal entre pares y la vertical con los políticos. Visto lo anterior, esta investigación muestra cómo una nueva metodología de IA ayuda a visibilizar y cuantificar nuevas realidades como la toxicidad online, con el fin último de llegar a erradicarla y sanear el debate en el mundo digital. Además, contradice los hallazgos previos sobre bots como difusores de toxicidad, demostrando que son los usuarios reales quienes amplifican el contenido tóxico.
  • Publication
    Advanced Inference and Representation Learning Methods in Variational Autoencoders
    (2023-04) Peis Aznarte, Ignacio; Artés Rodríguez, Antonio; Martínez Olmos, Pablo; UC3M. Departamento de Teoría de la Señal y Comunicaciones; Artés Rodríguez, Antonio
    Deep Generative Models have gained significant popularity in the Machine Learning research community since the early 2010s. These models allow to generate realistic data by leveraging the power of Deep Neural Networks. The field experienced a significant breakthrough when Variational Autoencoders (VAEs) were introduced. VAEs revolutionized Deep Generative Modeling by providing a scalable and flexible framework that enables the generation of complex data distributions and the learning of potentially interpretable latent representations. They have proven to be a powerful tool in numerous applications, from image, sound and video generation to natural language processing or drug discovery, among others. At their core, VAEs encode natural information into a reduced latent space and decode the learned latent space into new synthetic data. Advanced versions of VAEs have been developed to handle challenges such as handling heterogeneous incomplete data, encoding into hierarchical latent spaces for representing abstract and richer concepts, or modeling sequential data, among others. These advances have expanded the capabilities of VAEs and made them a valuable tool in a wide range of fields. Despite the significant progress made in VAE research, there is still ample room for improvement in their current state-of-the-art. One of the major challenges is improving their approximate inference. VAEs typically assume Gaussian approximations of the posterior distribution of the latent variables in order to make the training objective tractable. The parameters of this approximation are provided by encoder networks. However, this approximation leads to a lower bounded objective, which can degrade the performance of any task that requires samples from the approximate posterior, due to the implicit bias. The second major challenge addressed in this thesis is related to achieving meaningful latent representations, or more broadly, how the latent space disentangles generative factors of variation. Ideally, the latent space would modulate meaningful properties separately within each dimension. However, Maximum Likelihood optimizations require the marginalization of latent variables, leading to non-unique solutions that may or may not achieve this desired disentanglement. Additionally, properties learned at the observation level in VAEs assume that every observation is generated independently, which may not be the case in some scenarios. To address these limitations, more robust VAEs have been developed to learn disentangled properties at the supervised group (also referred to as global) level. These models are capable of generating groups of data with shared properties. The work presented in this doctoral thesis focuses on the development of novel methods for improving the state-of-the-art in VAEs. Specifically, three fundamental challenges are addressed: achieving meaningful global latent representations, obtaining highly-flexible priors for learning more expressive models, and improving current approximate inference methods. As a first main contribution, an innovative technique named UG-VAE from Unsupervised-Global VAE, aims to enhance the ability of VAEs in capturing factors of variations at data (local) and group (global) level. By carefully desigining the encoder and the decoder, and throughout conductive experiments, it is demonstrated that UG-VAE is effective in capturing unsupervised global factors from images. Second, a non-trivial combination of highly-expressive Hierarchical VAEs with robust Markov Chain Monte Carlo inference (specifically Hamiltonian Monte Carlo), for which important issues are successfully resolved, is presented. The resulting model, referred to as the Hierarchical Hamiltonian VAE model for Mixed-type incomplete data (HH-VAEM), addresses the challenges associated with imputing and acquiring heterogeneous missing data. Throughout extensive experiments, it is demonstrated that HH-VAEM outperforms existing one-layered and Gaussian baselines in the tasks of missing data imputation and supervised learning with missing features, thanks to its improved inference and expressivity. Furthermore, another relevant contribution is presented, namely a sampling-based approach for efficiently computing the information gain when missing features are to be acquired with HH-VAEM. This approach leverages the advantages of HH-VAEM and is demonstrated to be effective in the same tasks.
  • Publication
    On the compressive behaviour of woven CFRP laminates under high loading rate
    (2024-01) Rodríguez Sereno, José Manuel; Pernas Sánchez, Jesús; Artero Guerrero, José Alfonso; UC3M. Departamento de Mecánica de Medios Continuos y Teoría de Estructuras; López Puente, Jorge
    En la industria aeronáutica, el rendimiento de los materiales compuestos ante un posible impacto es de gran interés en los últimos años. Aunque el efecto de la velocidad de deformación en materiales compuestos afecta significativamente el comportamiento mecánico, la mayoría de las investigaciones estudian este comportamiento sin tener en cuenta la dependencia de la velocidad de deformación en las propiedades mecánicas de dichos materiales. El presente estudio analiza la dependencia de la velocidad de deformación en el comportamiento durante un impacto de un laminado AS4-8552-AGP193-PW (también denominado AGP193-PW), compuesto de fibra de carbono con resina epoxi en configuración de tejido. Para ello, se realiza una caracterización de este material mediante ensayos de compresión a tres velocidades de deformación (hasta 500 s−1) y diferentes ángulos de orientación de las fibras para dibujar la envolvente de fallo. A continuación, se desarrolló un nuevo modelo constitutivo para implementar numéricamente el cambio en las propiedades mecánicas estudiadas del compuesto de tejido ante un cambio de la velocidad de deformación. Este modelo considera el comportamiento de cortadura no lineal, el inicio y la evolución del daño del material. Posteriormente, se estudió el efecto de orificios en muestras similares ensayadas a compresión a tres velocidades de deformación y diferentes ángulos de fibra, de igual manera que en los ensayos de caracterización. Además, se desarrolló un modelo de elementos finitos en Abaqus/Explicit para validar el comportamiento constitutivo propuesto, incluyendo una subrutina de usuario para programar el comportamiento del material. Las simulaciones numéricas predicen el comportamiento mecánico de las muestras con orificio bajo cargas cuasi-estáticas y dinámicas, donde se demuestra la importancia de implementar el efecto de la velocidad de deformación en las propiedades mecánicas. Finalmente, en este trabajo se ha estudiado el comportamiento ante impacto de laminados de AGP193-PW. Fragmentos de estos laminados fueron lanzados contra una barra Hopkinson con un rango amplio de velocidades de impacto (90-160 m/s). La metodología experimental desarrollada se ha mostrado como una forma efectiva de analizar los diferentes mecanismos de fallo durante el proceso de fractura cuando los fragmentos de compuesto tipo tejido actúan a modo de proyectil, proporcionando una mejor comprensión de su comportamiento físico. También se desarrolló un modelo de elementos finitos para simular los ensayos de impacto utilizando la subrutina de usuario de elemento sólido para programar el comportamiento del material compuesto. El modelo constitutivo se validó comparando las fuerzas e impulsos inducidos por los fragmentos en las pruebas experimentales y las simulaciones numéricas. Los modelos de elementos finitos también fueron esenciales para estudiar la influencia de las desviaciones en diferentes ejes de rotación ("yaw" y "pitch") del fragmento en la fuerza e impulso inducidos durante los impactos.
  • Publication
    Compliance with Human Rights Standards in Life Sentencing: A Comparative Law Study of Spain's Prisión Permanente Revisable and Life Sentences in the United States of America
    Sartorio, Pablo; Garrocho Salcedo, Ana María; UC3M. Departamento de Derecho Penal, Procesal e Historia del Derecho
  • Publication
    Protection Scheme for Optimal Allocation of Green Distributed Generation in Iraqi Distribution Grid
    (2024-03) Majeed, Ammar Abbas; Abderrahim Fichouche, Mohamed; Abbood Al-khazraji, Anwer; UC3M. Departamento de Ingeniería de Sistemas y Automática; Abderrahim Fichouche, Mohamed