京都大学 / 0048 / 新制・課程博士 / 博士(工学) / 甲第22474号 / 工博第4735号 / 新制||工||1740(附属図書館) / 京都大学大学院工学研究科化学工学専攻 / (主査)教授 山本 量一, 教授 渡辺 宏, 准教授 谷口 貴志 / 学位規則第4条第1項該当 / Doctor of Philosophy (Engineering) / Kyoto University / DFAM

The selective laser sintering (SLS) process or the additive manufacturing (AM) enables the construction of a three-dimensional object through melting and solidification of metal powder. The primary advantage of AM over the conventional process is providing the manufacturing flexibility, especially for highly complicated products. The quality of AM products depends upon various processing parameters such as laser power, laser scanning velocity, laser scanning pattern, layer thickness, and hatch spacing. The improper selection of these parameters would lead to parts with defects, severe distortion, and even cracking. I herein perform the numerical and experimental analysis to investigate the interplay between processing parameters and the defect generation. The analysis aims to resolve issues at two different scales, micro-scale and product-scale. At the micro-scale, while the numerical model is developed to investigate the interaction of the laser and materials in the AM process, its advantages and disadvantages compared to an analytical approach (Rosenthal’s equation), which provides a quicker thermal solution, are thoroughly studied. Additionally, numerical results have been verified by series of experiments. Based on the analysis, it is found that the simultaneous consideration of multiple processing parameters could be achieved using the energy density. Moreover, together with existing criteria, a processing window is numerically developed as a guideline for AM users to avoid common defects at this scale including the lack of fusion, balling effect, and over-melting. Thermal results at a micro-scale are extended as an input to determine the residual stress initiation in AM products. The effect of energy density and substrate temperature on a residual stress magnitude is explored. Results show that the stress magnitude within a layer is a strong function of the substrate temperature, where a higher substrate temperature results in a lower stress. Moreover, the stress formation due to a layer’s addition is studied, in which the stress relaxation at locations away from a top surface is observed. Nevertheless, even though the micro-scale analysis can resolve some common defects in AM, it is not capable of predicting product-scale responses such as residual stress development and entire product’s distortion. As a result, the multiscale modeling platform is developed for the numerical investigation at the product level. Three thermal models at various scales are interactively used to yield an effective thermal development calculation at a product-scale. In addition, the influence of the multiple layers, energy densities and scanning patterns on the residual stress formation has been addressed, which leads to the prediction of the residual stress development during the fabrication. The distortion of products due to the residual stress can be described by the product-scale model. Furthermore, among many processing parameters, the energy input and the scanning length are found to be important factors, which could be controlled to achieve the residual stress reduction in AM products. An optimal choice of a scanning length and energy input can reduce an as-built residual stress magnitude by almost half of typically encountered values. Ultimately, the present work aims to illustrate the integration of the computational method as tools to provide manufacturing qualification for part production by the AM process.

Dans ces travaux , nous avons deux principaux objectifs physique et numérique. Le problème physique consiste à trouver la solution de Rayleigh-Bénard pour des fluides newtoniens et non-newtoniens. Dans la présente étude, une présentation générale des résultats de la convection de Rayleigh-Bénard (RBC) est donnée dans le cas des fluides newtoniens et non-newtoniens tels que des fluides rhéofluidifiants modélisés par la loi puissance et des fluides viscoplastiques (fluides de Bingham, Herschel-Bulkley et Casson), en régime permanent et transitoire. Dans le cas des fluides viscoplastiques, les modèles macroscopiques ne prenant pas bien en compte la réalité physique de la contrainte seuil ont fait l'objet d'une modélisation. Un modèle mesoscopique proposé par Hébraud et Lequeux a été utilisé. Le problème numérique consiste à développer la méthode de résolution PGD (Proper Generalized Decomposition) pour résoudre les modèles non linéaires couplés transitoires, dans le cas du problème de Rayleigh-Bénard. Cette méthode est également utilisée pour résoudre le problème RBC paramétrique en y ajoutant quelques variables physiques comme coordonnées supplémentaires. Par ailleurs, dans le cas des fluides non-newtoniens, nous avons utilisé la PGD pour résoudre les équations mesoscopiques et macroscopiques couplées. / In this research work we are looking for two main physical and numerical purposes. The physical problem is to find the solution of Rayleigh Bénard convection for several conditions dependent on fluid thermo-physical properties such as temperature, viscosity and initial and boundary conditions. Continuing previous research works in this study we have provided the results of Rayleigh Bénard convection for Newtonian, Power-law and viscoplastic fluids (Bingham, Herschel-Bulkley and Casson) and for steady state and transient conditions. We also solve this problem for Nano and soft glassy materials. In some cases the results are interesting not only as a part of the Rayleigh Bénard convection analysis but also on a larger scale as a part of the heat transfer and mechanical fluid analysis such as viscoplastic and soft glassy material studies. Numerically, it was interesting to develop Proper Generalized Decomposition (PGD) method for solving transient coupled non-linear models, in particular the one related to the Rayleigh–Bénard flow. This model also was used to solve RBC problem parametrically by adding some physical properties as extra coordinates. For soft glassy material we used PGD to connect micro and macro equations together.

L'objectif de la thèse présentée ici est l'optimisation de matériaux carbonésnanoporeux au moyen de la “conception de matériaux virtuels”. En ce qui concerne cette échelle de travail (~ 10nm), la Nanotomographie FIB-SEM est la seule technique d'imagerie donnant accès à une information sur la géométrie tridimensionnelle. Cependant, pour l'optimisation du comportement, l'espace des pores doit être reconstruit à partir des données tirées des images obtenues. Jusqu'à présent ce problème n'était pas résolu. Pour pouvoir le maîtriser, on a développé une simulation d'images FIB-SEM. Les images FIB-SEM simulées peuvent être utilisées pour la vérification et la validation des algorithmes de segmentation. En utilisant les données d'image simulées, un nouvel algorithme pour la reconstruction de l'espace des pores à partir des données FIB-SEM a été développé.Deux études de cas avec des carbones nanoporeux utilisés pour le stockage d'énergie sont présentées, en utilisant les nouvelles techniques pour la caractérisation et l'optimisation des électrodes Li-ion de type EDLC'S (« electric double-layer capacitors », soit supercondensateurs). L'espace des pores reconstruit est modélisé géométriquement à l'aide de la géométrie stochastique. Enfin, on a simulé les propriétés électriques des matériaux enutilisant des structures modélisées et simulées. / The aim of the work presented here is to optimize nanoporous carbon materials by means of 'virtual material design'. On this length scale (~ 10nm) Focused Ion Beam – Scanning Electron Microscopy Nanotomography (FIB-SEM) is the only imaging technique providing three dimensional geometric information. Yet, for the optimization, the pore space of the materials must be reconstructed from the resulting image data, which was a generally unsolved problem so far.To overcome this problem, a simulation method for FIB-SEM images was developed. The resulting synthetic FIB-SEM images could then be used to test and validate segmentation algorithms. Using simulated image data, a new algorithm for the morphological segmentation of the highly porous structures from FIB-SEM data was developed, enabling the reconstruction of the three dimensional pore space from FIB-SEM images.Two case studies with nanoporous carbons used for energy storage are presented, using the new techniques for the characterization and optimization of electrodes of Li-ion batteries and electric double layer capacitors (EDLC's), respectively. The reconstructed pore space is modeled geometrically by means of stochastic geometry. Finally, the electrical properties of the materials were simulated using both imaged real and modeled structures.

L’utilisation croissante des matériaux composites à matrice thermoplastique dans l’industrie aéronautique passe par une meilleure compréhension de leur comportement mécanique lors d’une exposition à un flux rayonnant (conséquence d’un incendie). Cette étude, portant sur le comportement thermo-mécanique de stratifiés tissés quasi-isotropes composés d’une matrice PPS renforcée par des fibres de carbone, se divise en 3 parties. Tout d’abord, la décomposition thermique du matériau et l’évolution de ses propriétés mécaniques avec la température sont étudiées. Ces données permettent ensuite d’appréhender le comportement de ces matériaux soumis à des chargements combinés (flux rayonnant et chargement mécanique en traction ou en compression, de type monotone à rupture et en fluage). La dernière partie vise à identifier les paramètres matériau nécessaires pour la simulation thermo-mécanique aux échelles macroscopique et mésoscopique. / The increasing use of thermoplastic-based composite materials in the aeronautical industry requires a better understanding of their mechanical behavior when exposed to radiant heat flux (consequence of a fire exposure). This study, which examines the thermo-mechanical behavior of quasi-isotropic woven laminates composed of PPS reinforced with carbon fibers, is divided into 3 parts. First, the thermal decomposition of the material and the evolution of its mechanical properties with temperature is studied. These data help to understand the behavior of these materials subjected to combined loads (radiant heat flux and tensile or compressive loadings). The last part aims to identify the material parameters necessary for thermo-mechanical simulation at macroscopic and mesoscopic scales.

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