Orientador: Gilberto Pechoto de Melo / Resumo: O uso da metodologia de observadores de estado para detecção de dano requer a análise da observabilidade do modelo físico-matemático do sistema e aponta para a necessidade de posicionar sensores de forma otimizada. Visto que plataformas veiculares podem se apresentar como sistemas com amortecimento não proporcional, é apresentada uma metodologia para o cálculo de índices de posicionamento H2 para este tipo de sistema. Para a plataforma veicular analisada com amortecimento proporcional, índices de posicionamento H2 são comparados com índices grammianos, sendo demonstrado que ambos resultam em uma mesma configuração ótima de sensores. A análise da observabilidade é conduzida a partir dos principais modos de vibrar , sendo utilizada a norma H2 para definição de quais modos devem ser retidos no modelo reduzido. Observadores robustos, atuando em paralelo com o sistema, são utilizados para localização e quantificação da severidade do dano. É mostrado que, para plataformas veiculares excitadas pela base com deslocamentos do tipo degrau, um índice de dano que compara as saídas medidas e estimadas permite alcançar este objetivo. / Abstract: The use of state observer's methodology for damage detection requires the observability analysis of the physical-mathematical model of the system and points to the need of positioning sensors optimally. Since vehicle platforms can be presented as systems with non-proportional damping, a methodology for calculating H2 positioning indices for this type of system is presented. For the vehicle platform analyzed with proportional damping, H2 positioning indices are compared with Grammian indices, showing that both result in the same optimal sensor con guration. The observability analysis is conducted from the main modes of vibration, using the H2 norm to define which modes should be retained in the reduced model. Robust observers acting in parallel with the system are used to locate and quantify the severity of the damage. It is shown that, for vehicle platforms stimulated by the base with step-type displacements, a damage index that compares the measured and estimated outputs reaches this goal. / Mestre

Graphene nanoplatelets have been introduced into the interphase between electrically insulating glass fibre and polymer matrix to functionalize the traditional composite. Owing to the distribution of network structure of GNPs, the interphase can transfer the signals about various internal change of material. Consequently, due to the novel bio-inspired overlapping structure, our GNPs-glass fibre shows a unique opportunity as a micro-scale multifunctional sensor. The following conclusions can be drawn from present research: • We prepared GNPs solution via a scalable and highly effective liquid-phase exfoliation method. This method produces high-quality, unoxidized graphene flakes from flake graphite. We control the thickness and size of GNPs by varying the centrifugation rate. • A simple fibre oriented capillary flow which can suppress ‘coffee ring’ effect to deposit GNPs onto the curved glass fibre surface. The GNPs form continuous fish scales like overlapping structure. • The electrical conductivity of our GNPs-glass fibre shows semiconductive property. The electrical resistance value scattering and the advancing contact angle value scattering indicate a uniform deposit structure. The uniform overlapping structure is a key factor for higher electrical conductivity compared with our previous work with CNTs. • The contact angles of our GNPs-glass fibre with water indicate that the GNPs are almost unoxidized, so the inert GNPs coating decreases the interfacial shears strength. • A micro scale GNPs-glass fibre sensor for gas sensing is achieved by deposit GNPs onto glass fibre surface. This sensor can be used to detect solvents vapours, such as water, ethanol and acetone. All these vapours work as electron acceptor when reacting with GNPs. The acetone shows the highest sensitivity (45000%) compared with water and ethanol. • The doping-dedoping of GNPs-glass fibres during adsorption-desorption cycles of acetone result in the efficient “break-junction” (GNPs lost electron carrier concentration) mechanism, which provides the possibility to fabricate the electrochemical “switch” in a simple and unique way. • The resistance of our GNPs-glass fibre shows exponential relationship with RH. This is attributed to two points. Firstly, the water vapours show similar exponential adsorption on carbon surface; secondly, the bandgap of GNPs increases with the increase of adsorbed water vapour concentration. • Due to the weak van der Waals interaction when water molecules are adsorbed on GNPs surface, our GNPs-glass fibre shows extreme fast response and recovery time with RH. It is potential for our GNPs-glass fibre being used to monitor the breath frequency. • Utilizing the negative temperature coefficient of GNPs, our GNPs-glass fibre can be used as temperature sensor with a sensing region of -150 to 30 °C. • Through the observed abnormal resistance change at a temperature of about – 18 °C, we discovered a phase change of the trance confined water in graphene layers. Based on the resistance change, we can study the interaction of water and carbon nanoparticles. • The bio-inspired novel overlapped multilayer structure of GNPs coating shows structural colours. Even more, our GNPs-glass fibre can be used to monitor the loading force in the interphase when it is embedded into epoxy resin. • Our GNPs-glass fibre shows an excellent piezoresistive property, the single GNPs-glass fibre shows a larger gauge factor than the commercial strains sensor. • The semiconductive interphase was formed when the GNPs-glass fibre was embedded in polymer matrix. This semiconductive interphase is very sensitive to the deformation of material, therefore, an in-situ strain sensor was manufactured to real-time monitor the microcracks in a composite instead of external sensors. The area of resistance ‘jump’ increase can be seen as the feature area for damage’s early warning. • Monitoring the resistance variation of the single fibre composite was conducted under cyclic loading with progressively increasing the strain peaks in order to further investigate the response of in-situ sensor to the interphase damage process. The deviation of resistance/strain when the stress is larger than 2 % highlights the accumulation of damage, which gives insight into the mechanism of resistance change.

Ziel der vorliegenden Arbeit war die Entwicklung eines Sensors zur gleichzeitigen Bestimmung von Spannungsintensitätsfaktoren (K-Faktoren) und der Risslage. Im Gegensatz zum Stand der Technik werden zwei Aufgaben zur Charakterisierung der Risse (Detektierung von Risslage und Größe und Quantifizierung des Beanspruchungszustandes an der Rissspitze) mit Hilfe nur eines Sensors ermöglicht. Es wurde effiziente, kostengünstige und leicht zu applizierende Technik zur experimentellen bruchmechanischen Beanspruchungsanalyse entwickelt. Eine Struktur mit Riss wird großflächig mit einer piezoelektrischen Polyvinylidenfluorid-Folie (PVDF-Folie) beklebt und eine ausreichende Anzahl von Elektroden befindet sich im Bereich des möglichen/vorhandenen Risses. Die an den Elektroden abgegriffenen elektrischen Potentiale bzw. Ladungen sind ein Maß für die Verzerrungen an der Oberfläche des Bauteils und ermöglichen die Berechnung der bruchmechanischen Größen am Riss. Dabei beschränkte man sich auf die Anwendung des Sensorkonzeptes im Rahmen der Scheiben- und Plattentheorie.

A functional nanometer-scale hybrid coating layer with multi-walled carbon nanotubes (MWCNTs) and/or nanoclays, as mechanical enhancement to ‘heal’ surface microcracks and environmental barrier layer is applied to alkaliresistant glass (ARG) fibres. The nanostructured and functionalised traditional glass fibres show both significantly improved mechanical properties and environmental corrosion resistance. Early warning material damage can be achieved by carbon nanotubes concentrated interphases in the composites. / Eine funktionale nanometerskalige Hybridbeschichtung mit multi-walled carbon nanotubes (MWCNTs) und/oder Nanoclay wurde als mechanische Verbesserung des „Ausheilens“ von Oberflächen-Mikrorissen und Barriereschicht gegenüber Umwelteinflüssen auf alkaliresistente Glasfasern (ARG) appliziert. Die nanostrukturierten und funktionalisierten traditionellen Glasfasern zeigen signifikant verbesserte mechanische Eigenschaften und Korrosionsbeständigkeit. Die Frühwarnung des Materialversagens kann durch Carbon Nanotubes, konzentriert in der Grenzschicht der Composites, erreicht werden.

The field of monitoring is one of rapid development. Advances in sensor technologies, in data communication paradigms and data processing algorithms all influence the possibilities of Structural Health Monitoring, damage detection, traffic monitoring and other implementations of monitoring systems. Bridges are a very critical part of a country’s infrastructure, they are expensive to build and maintain, and many uncertainties surround important factors determining the serviceability and deterioration of bridges. As such, bridges are good candidates for monitoring. Monitoring can extend the service life and avoid or postpone replacement, repair or strengthening work. Many bridges constitute a bottleneck in the transport network they serve with few or no alternative routes. The amount of resources saved, both to the owner and the users, by reducing the amount of non-operational time can easily justify the extra investment in monitoring. This thesis consists of an extended summary and three appended papers. The thesis presents advances in sensor technology, damage identification algorithms and Bridge Weigh-In-Motion techniques. Two case studies are carried out. In the first a bridge and traffic monitoring system is implemented in a highway suspension bridge to study the cause of unexpected wear in the bridge bearings. In the second a fully operational Bridge Weigh-In-Motion system is developed and deployed in a steel railway bridge. The gathered data was studied to obtain a characterization of the site specific traffic. / QC 20111122

<div>Self-sensing materials are engineered to transduce mechanical effects like deformations and damages into detectable electrical changes. As such, they have received immense research attention in areas including aerospace, civil infrastructure, robotic skin, and biomedical devices. In structural health monitoring (SHM) and nondestructive evaluation (NDE) applications, damages in the material cause breakage in the conductive filler networks, resulting in changes in the material's conductivity. Most SHM and NDE applications of self-sensing materials have used direct current (DC) measurements. DC-based methods have shown advantages with regard to sensitivity to microscale damages compared to other SHM methods. Comparatively, alternating current (AC) measurement techniques have shown potential for improvement over existent DC methods. For example, using AC in conjunction with self-sensing materials has potential for benefits such as greater data density, higher sensitivity through electrodynamics effects (e.g., coupling the material with resonant circuitry), and lower power requirements. Despite these potential advantages, AC techniques have been vastly understudied compared to DC techniques. </div><div><br></div><div>To overcome this gap in the state of the art, this thesis presents two contributions: First, an experimental study is conducted to elucidate the effect of different damage types, numbers, and sizes on AC transport in a representative self-sensing composite. And second, experimental data is used to inform a computational study on using AC methods to improve damage detection via electrical impedance tomography (EIT) – a conductivity imaging modality commonly paired with self-sensing materials for damage localization. For the first contribution, uniaxial glass fiber specimens containing 0.75 wt.% of carbon nanofiber (CNF) are induced with five types of damage (varying the number of holes, size of holes, number of notches, size of notches, and number of impacts). Impedance magnitude and phase angle were measured after each permutation of damage to study the effect of the new damage on AC transport. It was observed that permutations of hole and notch damages show clear trends of increasing impedance magnitude with the increasing damage, particularly at low frequencies. These damages had little-to-no effect on phase angle, however. Increasing numbers of impacts on the specimens did not show any discernable trend in either impedance magnitude or phase angle, except at high frequencies. This shows that different AC frequencies can be more or less useful for finding particular damage types.</div><div><br></div><div>Regarding the second contribution, AC methods were also explored to improve damage detection in self-sensing materials via EIT. More specifically, the EIT technique could benefit from developing a baseline-free (i.e., not requiring a ‘healthy’ reference) formulations enabled by frequency-difference (fd) imaging. For this, AC conductivity measurements ranging from 100 Hz to 10 MHz were collected from various weight fractions of CNF-modified glass fiber/epoxy laminates. This experimental data was used to inform fdEIT simulations. In the fdEIT simulations, damage was simulated as a simple through-hole. Simulations used 16 electrodes with four equally spaced electrodes on each side of the domain. The EIT forward problem was used to predict voltage-current response on the damaged mesh, and a fdEIT inverse problem was formulated to reconstructs the damage state on an undamaged mesh. The reconstruction images showed the simulated damage clearly. Based on this preliminary study, this research shows that fdEIT does have potential to eliminate the need for a healthy baseline in NDE applications, which can potentially help proliferate the use of this technique in practice.</div>

Un système SHM par ondes guidées a pour but d'évaluer l'intégrité d'une grande variété de structures fines, telles que les fuselages d'avions, les tuyaux, les réservoirs, etc. Un tel système est basé sur un réseau de capteurs piézoélectriques pour l'excitation et la mesure des ondes guidées. Cette méthode de SHM par ondes guidées est prometteuse pour l'inspection de structures de grande taille, ces ondes se propageant sur de grandes distances avec peu d'atténuation, tout en étant sensibles aux défauts surfaciques et subsurfaciques.Cette thèse présente les travaux menés dans le but de développer un système de SHM par ondes guidées capable de détecter, localiser et dimensionner efficacement les défauts dans des structures aéronautiques assimilables à des plaques, en matériaux composites ou en aluminium. Des simulations et des méthodes d'apprentissage sont utilisées pour déterminer les caractéristiques principales des ondes guidées propagées, notamment les vitesses de phase et de groupe ainsi que la fonction de Green 3D. Celles-ci sont ensuite utilisées pour traiter les signaux des ondes guidées afin de produire des images représentant l'intégrité des structures étudiées. Ce travail comprend également une étude approfondie des algorithmes d'imagerie DAS, MV et Excitelet, les plus prometteurs parmi ceux de la littérature, une évaluation de leurs performances par analyse statistique sur une grande base de données de résultats de simulations d'imagerie par ondes guidées et propose une méthode d'imagerie parcimonieuse.Alors que la détection et la localisation des défauts à partir de l'analyse des images est aisée, le dimensionnement du défaut est un problème plus complexe en raison de sa forte dimensionnalité et de sa non-linéarité. Il est démontré que ce problème peut être résolu par des méthodes d'apprentissage automatique sur une grande base de données de résultats de simulations d'imagerie par ondes guidées. Ces méthodes d'imagerie nécessitent cependant une référence, mesurée sur la structure dans un état supposé sain. Elles sont efficaces dans des conditions opérationnelles stationnaires mais sont sensibles aux variations de l'environnement et notamment aux fluctuations de température.Ce travail présente donc l'étude de la robustesse face aux effets thermiques des méthodes d'imagerie par ondes guidées et propose un modèle de détection de défauts capable d'analyser des résultats d'imagerie détériorés. Plusieurs techniques de compensation des effets thermiques sont étudiées et des améliorations sont proposées. Leur efficacité est validée pour les plaques d'aluminium mais des améliorations supplémentaires sont nécessaires pour les étendre aux plaques de composites. / A guided wave-based structural health monitoring (SHM) system aims at determining the integrity of a wide variety of plate-like structures, including aircraft fuselages, pipes, tanks etc. It relies on a sparse array of piezoelectric transducers for guided waves (GWs) excitation and sensing. With a number of benefits, these waves are standing out among other methods as a promising method for the inspection of large structures. They can propagate on significant distances with small attenuation while being sensitive to surface and subsurface defects.This thesis presents studies conducted with the purpose of developing such a GWs-based SHM system that is capable of efficient defect detection, localization and sizing aeronautical plate-like structures made of aluminum and composite materials. Simulation and data-driven approaches are presented for determining principal characteristics of propagating GWs, namely modal group and phase velocities, 3D Green's functions etc. in structures of interest. They are then used for GWs signals processing in order to compute images representing the integrity of studied structures. This work also provides a comprehensive overview of DAS, MV and Excitelet defect imaging algorithms, determines their performance using statistical analysis of an extensive dataset of simulated guided waves imaging (GWI) results and proposes a method for sparse defect imaging.While defect detection and localization are straightforward from the image analysis, the defect sizing is a more complex problem due to its high dimensionality and non-linearity. It is demonstrated that this problem can be solved by means of machine learning methods, relying on an extensive database of simulated GWI results. Aforementioned defect imaging methods are baseline demanding. They are efficient under stationary operational conditions but vulnerable to environmental variations, especially to the temperature fluctuation.Finally, this work presents studies on the robustness of GWI methods against thermal effects, and a defect detection model capable of analyzing deteriorated GWI results is proposed. Different techniques for thermal effects compensation are reviewed, and improvements are proposed. Their effectiveness is validated for aluminum plates but further improvements are required to translate these techniques to composite plates.

La surveillance de santé structurelle, SHM en anglais, est un domaine en plein essor avec l'arrivée massive des composites dans les transports. Ce matériau plus léger que les alliages traditionnels investit les avions, les trains, les bateaux ou les voitures. Permettant des économies substantielles d'énergie, il présente néanmoins l'inconvénient de pouvoir développer des défauts internes invisibles par une inspection visuelle. Dès lors leur surveillance est primordiale. Les pales d'avions turbopropulseurs (A400M, ATR, etc…) répondent aux mêmes exigences. Etre capable de déterminer un endommagement de la structure par le biais de capteur est tout l'enjeu des recherches. Cet objectif implique deux points : étudier le comportement de la pale et y développer un système embarqué pour obtenir des données et/ou surveiller. Dans ce contexte, ce travail de recherche a pour objectif de mener les premières études en déterminant une premier modèle comportementale des pales; en développant un premier microsystème enregistreur de paramètres de pales; en élaborant un premier algorithme de surveillance de la pale et d'événements endommageant (impacts, survitesses, survibrations) / The structural health monitoring, or SHM, represents today a key challenge today, with a massive use of composites in the field of transport. This material, lighter than a conventional alloy, is very attractive for airplanes, trains, boats or cars manufacturing. This allows significant energy savings, but can hide internal defects invisible from the outside. At this point, dedicated supervision is essential. Blades of turboprop plane (A400M, ATR, etc.) are in face of the same problems. Determination of structural defects by the use of sensors is the key solution for the research in this field. Thus, this problem has two solutions: studying blade performances and designing an embedded system able to record data and/or monitoring the structural health. The research studies presented in this thesis represent the first results of damaged blade performances. It leads to the design of a first embedded data recorder of blade parameters and computes a first dedicated algorithm for monitoring the blade structural health and damaging events (shocks, over-speeds, over-vibrations)

[EN] Structural Health Monitoring (SHM) is a discipline that quantitatively assesses the integrity and performance of infrastructures, relying on sensors, and support the development of efficient Maintenance and Rehabilitation (M&R) plans. Optical Multicore Fiber (MCF) Shape Sensors offer an innovative alternative to traditional methods and enable the reconstruction of the deformed shape of structures directly and in real-time, with no need of computation models or visual contact and exploiting all the advantages of Optical Fiber Sensors (OFS) technology. Despite the intense research efforts centered on this topic by research groups worldwide, a comprehensive investigation on the parameters that influence the performance of these sensors has not been conducted yet. The first part of the thesis presents a numerical study that examines the effects of strain measurement accuracy and core position errors on the performance of optical multicore fiber shape sensors in sensing three-dimensional curvature, which is at the basis of shape reconstruction. The analysis reproduces the strain measurement process using Monte Carlo Method (MCM) and identifies several parameters which play a key role in the phenomenon, including core spacing (distance between outer cores and sensor axis), number of cores and curvature measured. Finally, a set of predictive models were calibrated, by fitting the results of the simulations, to predict the sensors performance. Afterward, an experimental study is proposed to evaluate the performance of optical multicore fiber in sensing shape, with particular focus on the influence of strain sensors length. Two shape sensors were fabricated, by inscribing long (8.0 mm) and short (1.5 mm) Fiber Bragg Gratings (FBG) into the cores of a multicore seven-core fiber. Thus, the performance of the two sensors was assessed and compared, at all the necessary phases for shape reconstruction: strain sensing, curvature calculation and shape reconstruction. To conclude, an innovative approach, based on the Saint-Venant's Torsion Theory, is presented to determine the twisting of multicore fiber and to compensate the errors due to twisting during shape reconstruction. The efficiency of the theoretical approach was then corroborated performing a series of twisting tests on a shape sensor, fabricated by inscribing FBGs sensors into an optical spun multicore seven-core fiber. The investigation of the mechanical behavior of multicore optical shape sensors has synergically involved diverse disciplines: Solid Mechanics, Photonics, Statistics and Data Analysis. Such multidisciplinary research has arisen from the prolific cooperation between the Institutes of the Institute of Science and Technology of Concrete (ICITECH) and the Institute of Telecommunications and Multimedia Applications (iTEAM) - Photonics Research Labs (PRL) - of Universitat Politècnica de València (UPV), in addition to valuable collaboration with other members of the European ITN-FINESSE project, to which this work belongs. This research work aims to enhance the performance optical multicore fiber shape sensors and support the development of new sensor geometries, with great potential for structural health monitoring applications. / [ES] La Monitorización de la Salud Estructural (MSE) evalúa cuantitativamente la integridad y el comportamiento de las infraestructuras y permite desarrollar planes eficaces de Mantenimiento y Rehabilitación (M&R), utilizando los datos de los sensores. Sensores de forma basados en fibra óptica multinúcleo ofrecen una alternativa a los métodos tradicionales y permiten la reconstrucción de la deformada de estructuras de forma directa y en tiempo real, sin necesidad de modelos de cálculo o contacto visual y con todas las ventajas de la tecnología de los Sensores de Fibra Óptica (SFO). A pesar de los grandes esfuerzos en la investigación centrada en este tema por parte de los grupos de investigación de todo el mundo, todavía no se ha realizado una investigación exhaustiva que estudie los parámetros que influyen en el comportamiento de estos sensores. En la primera parte de la tesis se presenta un estudio numérico en el que se examinan los efectos de la precisión de la medición de la tensión y los errores de posición del núcleo en el comportamiento de los sensores de forma basados en fibra óptica multinúcleo para definir la curvatura tridimensional, que es la base de la reconstrucción de la forma. El análisis reproduce el proceso de medición de la tensión utilizando el método de Monte Carlo (MC) e identifica una serie de parámetros que desempeñan un papel en el proceso, entre ellos la separación del núcleo (distancia entre los núcleos exteriores y el eje del sensor), el número de núcleos y la curvatura medida. Por último, se calibró un conjunto de modelos de predicción ajustando los resultados de las simulaciones para predecir el comportamiento de los sensores. A continuación, se propone un estudio experimental para evaluar el comportamiento de los sensores de forma basado en fibra óptica multinúcleo, con especial atención en la influencia de la longitud de los sensores de deformación. Se fabricaron dos sensores de forma, inscribiendo Fiber Bragg Gratings (FBG) con longitudes de 8,0 mm y 1,5 mm en los núcleos de una fibra multinúcleo de siete núcleos. Así, se evaluó y comparó el comportamiento de los dos sensores en todas las fases necesarias para la reconstrucción de la forma, incluyendo la medición de la tensión, el cálculo de la curvatura y la reconstrucción de la forma. Para concluir, se presenta un enfoque innovador, basado en la Teoría de la Torsión de Saint-Venant, para determinar la torsión de la fibra multinúcleo y compensar los errores debidos a la torsión durante la reconstrucción de la forma. La eficiencia del enfoque teórico fue verificada realizando una serie de pruebas de torsión en un sensor de forma, fabricado inscribiendo los sensores de FBGs en una fibra óptica multinúcleo torcida y siete núcleos. La investigación del comportamiento mecánico de los sensores ópticos de forma multinúcleo ha involucrado sinérgicamente diversas disciplinas: Mecánica del sólido, Fotónica, Estadística y Análisis de datos. Esta investigación multidisciplinaria ha surgido de la prolífica cooperación entre el Instituto de Ciencia y Tecnología del Hormigón (ICITECH) y el Instituto de Telecomunicaciones y Aplicaciones Multimedia (iTEAM) - Laboratorio de Investigación Fotónica (LIF) - de la Universidad Politécnica de Valencia (UPV), además de la valiosa colaboración con otros miembros del proyecto europeo ITN-FINESSE, al que pertenece este trabajo. Este trabajo de investigación puede permitir mejorar el comportamiento de los sensores de forma basados en fibra óptica multinúcleo y apoyar el desarrollo de nuevas geometrías de sensores, con un gran potencial para aplicaciones de control de la salud estructural. / [CA] Structural Health Monitoring (SHM) avalua quantitativament la integritat i el comportament de les infraestructures i permet desenrotllar plans eficaços de Maintenance and Rehabilitation (M&R), utilitzant les dades dels sensors. Optical Multicore Fiber (MCF) Shape Sensors oferixen una alternativa als mètodes tradicionals i permeten la reconstrucció de la forma de la deformació de les estructures de forma directa i en temps real, sense necessitat de models de càlcul o contacte visual i amb tots els avantatges de l'Optical Fiber Sensors (OFS) Technology. A pesar dels grans esforços en la investigació centrada en aquest tema per part dels grups d'investigació de tot el món, encara no s'ha realitzat una investigació exhaustiva que estudie els paràmetres que influïxen en el comportament d'aquestos sensors. En la primera part de la tesi es presenta un estudi numèric en què s'examinen els efectes de la precisió del mesurament de la tensió i els errors de posició del nucli en el comportament dels sensors de forma basats en fibra òptica multinucli per a definir la curvatura tridimensional, que és la base de la reconstrucció de la forma. L'anàlisi reproduïx el procés de mesurament de la tensió utilitzant el mètode de Monte Carlo (MC) i identifica una sèrie de paràmetres que exercixen un paper en el procés, entre ells la separació del nucli (distància entre els nuclis exteriors i l'eix del sensor), el nombre de nuclis i la mesura de la curvatura. Finalment, es va calibrar un conjunt de models de predicció ajustant els resultats de les simulacions per a predir el comportament dels sensors. A continuació, es proposa un estudi experimental per a avaluar el comportament dels sensors de forma basat en fibra òptica multinucli, amb especial atenció en la influència de la longitud dels sensors de deformació. Es van fabricar dos sensors de forma, inscrivint Fiber Bragg Gratings (FBG) amb longituds de 8,0 mm i 1,5 mm en els nuclis d'una fibra multinucli de set nuclis. Així, es va avaluar i es va comparar el comportament dels dos sensors en totes les fases necessàries per a la reconstrucció de la forma, incloent el mesurament de la tensió, el càlcul de la curvatura i la reconstrucció de la forma. Per a concloure, es presenta un enfocament innovador, basat en la Teoria de la Torsió de Saint-Venant, per a determinar la torsió de la fibra multinucli i compensar els errors deguts a la torsió durant la reconstrucció de la forma. L'eficiència de l'enfocament teòric va ser verificada realitzant una sèrie de proves de torsió en un sensor de forma, fabricat inscrivint els sensors de FBGs en una fibra òptica de set nuclis de filat múltiple. La investigació del comportament mecànic dels sensors òptics de forma multinucli ha involucrat sinèrgicament diverses disciplines: Mecànica del sòlid, Fotónica, Estadística i Anàlisi de dades. Aquesta investigació multidisciplinària ha sorgit de la prolífica cooperació entre l'Institut de Ciència i Tecnologia del Formigó (ICITECH) i l'Institut de Telecomunicacions i Aplicacions Multimèdia (iTEAM) - Laboratori de investigación fotònica (LIF) - de la Universitat Politècnica de València (UPV), a més de la valuosa col·laboració amb altres membres del projecte europeu ITN- FINESSE, al qual pertany aquest treball. Aquest treball d'investigació pot permetre millorar el comportament dels sensors de forma basats en fibra òptica multinucli i ajudar al desenrotllament de noves geometries de sensors, amb un gran potencial per a aplicacions de control de la salut estructural. / Floris, I. (2020). Optical Multicore Fiber Shape Sensors. A numerical and experimental performance assessment [Tesis doctoral no publicada]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/148715 / TESIS

Indiana University-Purdue University Indianapolis (IUPUI) / Autonomous Emergency Braking (AEB) system uses vehicle’s on-board sensors such as radar, LIDAR, camera, infrared, etc. to detect the potential collisions, alert the driver and make safety braking decision to avoid a potential collision. Its limitation is that it requires clear line-of-sight to detect what is in front of the vehicle. Whereas, in current V2V (vehicle-to-vehicle communication) systems, vehicles communicate with each other over a wireless network and share information about their states. Thus the safety of a V2V system is limited to the vehicles with communication capabilities. Our idea is to integrate the complementary capabilities of V2V and AEB systems together to overcome the limitations of V2V and AEB systems. In a V2V-AEB system, vehicles exchange data about the objects information detected by their onboard sensors along with their locations, speeds, and movements. The object information detected by a vehicle and the information received through the V2V network is processed by the AEB system of the subject vehicle. If there is an imminent crash, the AEB system alerts the driver or applies the brake automatically in critical conditions to prevent the collision. To make V2V-AEB system advance, we have developed an intelligent heart Monitoring system and integrated it with the V2V-AEB system of the vehicle. The advancement of wearable and implantable sensors enables them to communicate driver’s health conditions with PC’s and handheld devices. Part of this thesis work concentrates on monitoring the driver’s heart status in real time by using fitness tracker. In the case of a critical health condition such as the cardiac arrest of a driver, the system informs the vehicle to take an appropriate operation decision and broadcast emergency messages over the V2V network. Thus making other vehicles and emergency services aware of the emergency condition, which can help a driver to get immediate medical attention and prevent accident casualties. To ensure that the effectiveness of the V2V-AEB system is not reduced by a time delay, it is necessary to study the effect of delay thoroughly and to handle them properly. One common practice to control the delayed vehicle trajectory information is to extrapolate trajectory to the current time. We have put forward a dynamic system that can help to reduce the effect of delay in different environments without extrapolating trajectory of the pedestrian. This method dynamically controls the AEB start braking time according to the estimated delay time in the scenario. This thesis also addresses the problem of communication overload caused by V2V-AEB system. If there are n vehicles in a V2V network and each vehicle detects m objects, the message density in the V2V network will be n*m. Processing these many messages by the receiving vehicle will take considerable computation power and cause a delay in making the braking decision. To prevent flooding of messages in V2V-AEB system, some approaches are suggested to reduce the number of messages in the V2V network that include not sending information of objects that do not cause a potential collision and grouping the object information in messages.