La RFID sans puce, en raison du très faible coût des tags, a ouvert une nouvelle voie pour les systèmes d'identification. Les étiquettes RFID sans puce fonctionnant dans le domaine temporel ont l'avantage d'être compatibles avec de grandes distances de lecture, de l'ordre de quelques mètres, et de pouvoir fonctionner dans les bandes de fréquence ISM. Cependant, les tags de ce type développés jusqu'à lors n'offraient qu'une faible capacité de codage. Cette thèse propose une nouvelle méthode pour augmenter la capacité de codage des tags fonctionnant dans le domaine temporel en utilisant des C-sections, c'est-à-dire des lignes de transmission repliées de manière à avoir des zones fortement couplées, ce qui leur donne un caractère dispersif. Une autre approche basée sur une technique multi-couches a également été introduite de façon à augmenter considérablement la capacité de codage. Pour terminer, la preuve de concept d'un tag-capteur d'humidité, basé sur l'utilisation de nano fils de silicium, est également présentée. / Chipless RFID tags, owing to their low cost, have opened a new way to the identification systems. Chipless RFID tags operating in the time domain have the advantage of being compatible with large reading distances of the order of a few meters, and also can operate in the ISM frequency bands. However, time domain tags developed until now offer poor coding capacity. This thesis proposes a new method to increase the coding capacity of tags operating in time domain by using C-sections, i.e. the transmission lines are folded so as to have tightly coupled zones that give them a dispersive nature. Another approach based on a multi-layer technique was also introduced, in order to increase the coding capacity considerably. Finally, the proof of concept of a humidity sensor tag based on silicon nanowires is also presented.

Cette étude porte sur la construction d’un modèle de prévision de la durée de vie à écaillage des barrièresthermiques protégeant les aubes de turbines aéronautiques, par le développement et l’exploitation d’essaisd’adhérence. La chaîne de modélisation de la durée de vie proposée comporte trois étapes. Tout d’abord, leschamps mécaniques dans les différentes couches du système sont évalués par un modèle semi-analytique decomportement de la structure multicouche, qui a été modifié pour favoriser son adaptabilité industrielle. Àpartir de l’histoire thermo-mécanique du substrat comme donnée d’entrée, qui peut être extraite d’un calculd’aube par EF, ce modèle prévoit la déformation de l’interface entre la pièce métallique et sa protectioncéramique lorsqu’un champ de contraintes lié à l’oxydation du métal lui est appliqué. Des mesures de rumpling,provoqué par le vieillissement du système à différentes températures, ont permis d’identifier et de valider lemodèle.Dans un deuxième temps, l’énergie d’adhérence est estimée au travers d’un modèle d’endommagements’appuyant sur la réponse mécanique du modèle de comportement précédent. L’endommagement, écrit àl’échelle de l’interface et découplé du comportement mécanique, a été identifié sur l’énergie d’adhérencequantifiée expérimentalement. Afin de caractériser au mieux l’énergie d’adhérence de la barrière thermiquesur son substrat, plusieurs essais ont été mis en oeuvre, permettant de solliciter l’interface dans une largegamme de mixité modale. Pour ce faire, des essais spécifiques ont été développés pour se rapprocher d’unepropagation de la fissure interfaciale en mode de cisaillement. Finalement, un critère énergétique permet dedéterminer la durée de vie du système, par comparaison de l’énergie d’adhérence et de l’énergie disponibledans le système pour la propagation d’une fissure interfaciale. Cette chaîne de prévision de la durée de vie estapplicable en post-traitement d’un calcul d’aube. Il a été montré que les tendances expérimentales sontcorrectement reproduites par la chaîne de durée de vie mise en place. / The aim of this study is to build a lifetime assessment model for thermal barrier coatings protecting aircraftturbine blades, by setting up and using adhesion tests. The model involves three steps: first, the mechanicalfields inside the layers are computed by a semi-analytical model of the multi-layered system behaviour, whichwas improved to fit the industrial demands. Given the thermo-mechanical history of the substrate (which canbe derived from FE computations), the model computes the interface strains between the metallic substrateand the ceramic protection under a stress field induced by oxidation. The model has been identified andvalidated with respect to rumpling measurements for different ageing temperatures of the system.During a second step, the interface toughness is estimated through a damage model depending on themechanical response of the multi-layered system. The damage parameters have been identified on toughnessmeasurements, and are not coupled to the multi-layer behaviour. In order to characterize the TBC toughness,several shear mode interface crack propagation tests have been developed and carried out.Finally, an energetic approach allows computing the system lifetime by comparing the decreasing interfacetoughness to the elastic stored energy. This lifetime assessment model can be applied as a post-processing of afinite element computation on a turbine blade and it has been shown that the experimental trends areconsistent with the lifetime given by the model.

Identificação e predição do comportamento aeroelástico representa um grande desafio para a análise e controle de fenômenos aeroelásticos adversos. A modelagem aeroelástica requer informações tanto sobre a dinâmica estrutural quanto sobre o comportamento aerodinâmico não estacionário. No entanto, a maioria das metodologias disponíveis atualmente são baseadas no desacoplamento entre o modelo estrutural e o modelo aerodinâmico não estacionário. Conseqüentemente, métodos alternativos são bem vindos na área de pesquisa aerolástica. Entre os métodos alternativos está o funcional multicamada, que fornece uma rigorosa representação matemática apropriada para modelagem aeroelástica e pode ser obtido através de redes neurais artificiais. Esse trabalho apresenta uma aplicação desse método, consistindo de um procedimento de identificação baseado em redes neurais artificiais que representam o funcional da resposta aeroelástica. O modelo neural foi treinado usando o algoritmo de Levenberg-Marquardt, o qual tem sido considerado um método de otimização muito eficiente. Ele combina a garantia de convergência do método do gradiente e o alto desempenho do método de Newton, sem a necessidade de calcular as derivadas de segunda ordem. Um modelo de asa ensaiado em túnel de vento foi usado para fornecer a resposta aeroelástica. A asa foi fixada a uma mesa giratória e um motor elétrico lhe fornecia o movimento de incidência. Essa representação aeroelástica funcional foi testada para diversas condições operacionais do túnel de vento. Os resultados mostraram que o uso de redes neurais na identificação da resposta aeroelástica é um método alternativo promissor, o qual permite uma rápida avaliação da resposta aerolástica do modelo. / Identification and prediction of aeroelastic behavior presents a significant challenge for the analysis and control of adverse aeroelastic phenomena. Aeroelastic modeling requires information from both structural dynamics and unsteady aerodynamic behavior. However, the majority of methodologies available today are based on the decoupling of structural model from the unsteady aerodynamic model. Therefore, alternative methods are mostly welcome in the aeroelastic research field. Among the alternative methods there is the multi-layer functional (MLF), that allows a rigorous mathematical framework appropriate for aeroelastic modeling and can be realized by means of artificial neural networks. This work presents an identification procedure based on artificial neural networks to represent the motion-induced aeroelastic response functional. The neural network model has been trained using the Levenberg-Marquardt algorithm that has been considered a very efficient optimization method. It combines the guaranteed convergence of steepest descent and the higher performance of the Newton\'s method, without the necessity of second derivatives calculation. A wind tunnel aeroelastic wing model has been used to provide motion-induced aeroelastic responses. The wing has been fixed to a turntable, and an electrical motor provides the incidence motion to the wing. This aeroelastic functional representation is then tested for a range of the wind tunnel model operational boundaries. The results showed that the use of neural networks in the aeroelastic response identification is a promising alternative method, which allows fast evaluation of aeroelastic response model.

Dans cette thèse nous étudions un problème fondamental, le partitionnement de graphe, dans le contexte de la croissance rapide des données, le volume des données continues à augmenter, allant des réseaux sociaux à l'internet des objets. En particulier, afin de vaincre les propriétés intraitables existant dans de nombreuses graphies, par exemple, la distribution des degrés en loi de puissance, nous appliquons un nouveau mode pour coupe de sommet, à la place de la méthode traditionnelle (coupe de bord), ainsi que pour assurer une charge de travail équilibrée et raisonnablement dans le traitement de graphe distribué. En outre, pour réduire le coût de communication inter-partitions, nous proposons une méthode de partition de bord basée sur les blocs, qui peut explorer efficacement les structures graphiques sous-jacentes au niveau local. , afin d'optimiser l'exécution de l'algorithme de graphe. Par cette méthode, le temps d'exécution et des communications généraux peuvent être considérablement réduits par rapport aux approches existantes. Les challenges qui se posent dans les grands graphiques comprennent également leur grande variété. Comme nous le savons, la plupart des applications graphiques au monde réel produisent des ensembles de données hétérogènes, dans lesquels les sommets et / ou les arêtes peuvent avoir des différents types ou des différentes étiquettes. De nombreuses algorithmes de fouille de graphes sont également proposés avec beaucoup d'intérêt pour les attributs d'étiquette. Pour cette raison, notre travail est étendu aux graphes de multicouches en prenant en compte la proximité des arêtes et la distribution des étiquettes lors du processus de partitionnement. En fin de cette thèse, Nous démontré à la ses performances exceptionnelles sur les ensembles de données du monde réel. / In this thesis, we mainly focus on a fundamental problem, graph partitioning, in the context of unexpectedly fast growth of data sources, ranging from social networks to internet of things. Particularly, to conquer intractable properties existing in many graphs, e.g. power-law degree distribution, we apply the novel fashion vertex-cut, instead of the traditional edge-cut method, for achieving balanced workload in distributed graph processing. Besides, to reduce the inter-partition communication cost, we present a block-based edge partition method who can efficiently explore the locality underlying graphical structures, to enhance the execution of graph algorithm. With this method, the overhead of both communication and runtime can be decreased greatly, compared to existing approaches. The challenges arising in big graphs also include their high-variety. As we know, most of real life graph applications produce heterogenous datasets, in which the vertices and/or edges are allowed to have different types or labels. A big number of graph mining algorithms are also proposed with much concern for the label attributes. For this reason, our work is extended to multi-layer graphs with taking into account the edges closeness and labels distribution during partitioning process. Its outstanding performance over real-world datasets is demonstrated finally.

京都大学 / 0048 / 新制・課程博士 / 博士(工学) / 甲第20684号 / 工博第4381号 / 新制||工||1681(附属図書館) / 京都大学大学院工学研究科都市社会工学専攻 / (主査)教授 澤田 純男, 教授 清野 純史, 准教授 後藤 浩之 / 学位規則第4条第1項該当 / Doctor of Philosophy (Engineering) / Kyoto University / DGAM

This paper reports the evaluation results of the mechanical structures of MEMS (micro electro mechanical systems) sensor implemented in the integrated MEMS inertial sensor for a wide sensing range from below 0.1 G to 20 G (1 G = 9.8 m/s^2). To investigate the mechanical tolerance, a maximum target acceleration of 20G was applied to the sub-1G sensor which had the heaviest proof mass of all that sensors had. The structure stability of Ti/Au multi-layered structures was also examined by using Ti/Au micro cantilevers. The results showed that the stoppers effectively functioned to prevent the proof mass and the springs from self-destruction, and that the stability of Ti/Au structures increased with an increase in width. Those results suggest that the proposed stopper and spring structures could be promising to realize MEMS sensors.

The objective of this research is to develop a scalable manufacturing process for high-volume production of low-cost graphene materials from lignin. The process includes preparation of catalyst-lignin precursors, pretreatment of precursors, and catalytic graphitization of kraft lignin to graphene materials. A growth concept, “catalytic thermal molecular welding (CTMW)” technique is proposed and validated to produce graphene materials from solid carbon resources. CTMW technique is a single process with two stages, i.e., the carbon-encapsulated metal nanostructures are first prepared. Then in the second stage these core-shell structures are opened by “scissoring molecules”, the cracked carbon shell units are welded and reconstructed to multilayer graphene materials under high temperature with selected “welding reagent gases” like light hydrocarbons (methane, natural gas, etc.) and hydrogen. Multi-layer nano-shell structure-based graphene materials, such as fluffy graphene, graphene chains, multi-layer graphene nanoplatelets, flatten or curved sheet-like graphene can be produced through altering fabrication conditions. The effects of transitional metal catalysts (Ni, Cu, Fe, and Mo) on the yields and structures of multi-layer nano-shell structure-based graphene materials from lignin are compared. The effects of the iron chemical resources (Fe(NO3)3, FeCl2, FeCl3, and Fe2O3 (nano)), iron loading on the yields and structures of multi-layer graphene materials from lignin are also examined. The influences of temperature, heating rate, heating time, metal-lignin precursor particle size, and welding reagent gas types on the yield of multi-layer graphene materials from lignin resources are investigated. Welding temperatures are optimized as1,000°C or above, with heating rates of 10°C or above. Welding gases including, argon (Ar), hydrogen (H2), methane (CH4), natural gas (NG), and mixed of these gases, are used at flow rates from 20 to 300 mL/min. Heating time is controlled between 0 to 5 hours. The effect of precursor particle size on final products is examined between 44 to 426 microns (Delta-m).

This work develops three models for simulation of the high-current operation of Li-ion batteries. Simulation as a tool can provide understanding beyond what experiments can offer. Different types of electrodes such as graphite, silicon, and NMC are modeled to study cell performance and aging under aggressive operating conditions. The first part of this work focuses on the effect of electrode microscale lateral heterogeneity on the degradation of conventional Li-ion batteries, especially for fast-charge applications. The non-uniform pore distribution leads to the nonuniform current density and state of charge (SoC), which can finally result in non-uniform Li plating and aging. The interactions of electrode regions a few mm away from each other with different ionic conductivity are simulated by combining conventional models in parallel with submodels to treat additional physics. The onset and growth of lithium metal deposits on the anode are predicted. The next topic is to investigate the structure of multilayer anodes (MLA) consisting of two layers in the through-plane direction with different ionic resistances. The model is intended to simulate a commercially made cell. Simulation results demonstrate that coating a higher-density layer near the current collector and a lower-density layer near the separator provides improved accessibility to active material during cell fast charge through better ionic transport. In addition, the improved anode further augments the cathode performance in high-current discharges, leading to greater energy density and power density of the cell. The last topic is to develop a numerically efficient mechanical and electrochemical model for silicon anodes. Silicon has a much higher energy density than graphite as a material for the anode; however, it undergoes high volume expansion and contraction ($\sim$ 280\%) which affects cell thickness and electrode ionic transport. The mechanical model treats these volume-change phenomena in a continuum fashion and is integrated into a P2D model of a Si half cell. As shown by the model, the external casing material of such cells can improve or restrict electrode utilization. Different cell designs are simulated to predict the degree of lithiation.

Multiple-layer Lamina Emergent Mechanisms (MLEMs) are mechanisms made from multiple sheets (lamina) of material with motion that emerges out of the fabrication plane. This study has shown that understanding how layers are used in existing products and in nature provides insight into how MLEMs can also use layers to achieve certain tasks. The multi-layered nature of MLEMs and the interactions between these layers are what enhance the capabilities of MLEMs and allow them to better meet design objectives. Layer separation is one objective for which MLEMs are well-suited. Layer separation can have a variety of applications and there are a number of different ways to design a MLEM to achieve this objective. Single-layer LEM and MLEM designs could greatly benefit from suitable actuation techniques; those that are consistent with the advantages of these mechanisms and could be incorporated into their design. This work presents shape memory alloys, piezoelectrics and dielectric elastomers as suitable ways of actuating LEMs and MLEMs. A number of novel MLEMs are presented throughout this thesis.

The study of the instabilities in boiling water reactors is of significant importance to the safety withwhich they can be operated, as they can cause damage to the reactor posing risks to both equipmentand personnel. The instabilities that concern this paper are progressive growths in the oscillatingpower of boiling-water reactors. As thermal power is oscillatory is important to be able to identifywhether or not the power amplitude is stable. The main focus of this paper has been the development of a neural network estimator of these insta-bilities, fitting a non-linear model function to data by estimating it’s parameters. In doing this, theambition was to optimize the networks to the point that it can deliver near ”best-guess” estimationsof the parameters which define these instabilities, evaluating the usefulness of these networks whenapplied to problems like this. The goal was to design both MLP(Multi-Layer Perceptron) and SVR/KRR(Support Vector Regres-sion/Kernel Rigde Regression) networks and improve them to the point that they provide reliableand useful information about the waves in question. This goal was accomplished only in part asthe SVR/KRR networks proved to have some difficulty in ascertaining the phase shift of the waves.Overall, however, these networks prove very useful in this kind of task, succeeding with a reasonabledegree of confidence to calculating the different parameters of the waves studied.