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.

Single wall carbon nanotubes (SWCNTs) show a variety of unparalleled properties such as high electrical and thermal conductivity, high specific surface area (SSA) and a large stiffness under axial loads. One of the major challenges in tapping the vast potential of SWCNTs is to fabricate nanotube based macrostructures that retain the unique properties of nanotubes. Pristine SWCNT aerogels are highly porous, isotropic structures of nanotubes mediated via van der Waals (VDW) interactions at junctions. The mechanical behavior of such aerogels is examined in several experimental studies. However, it is necessary to supplement these studies with insights from simulations in order to develop a fundamental understanding of deformation behavior of SWCNT aerogels. In this study, the mechanical behavior of SWCNT networks is studied using a multi-scale modeling approach. The mechanics of an individual nanotube and interactions between few nanotubes are modeled using molecular dynamics (MD) simulations. The results from atomistic simulations are used to inform meso-scale and continuum scale finite element (FE) models. The deformation mechanism of pristine SWCNT networks under large compressive strain is deduced from insights offered by meso-scale simulations. It is found that the elasticity of such networks is governed by the bending deformation of nanotubes while the plastic deformation is governed by the VDW interactions between nanotubes. The stress response of the material in the elastic regime is dictated by the VDW stresses on nanotubes while in the plastic regime, both the VDW and axial deformation stresses on nanotubes drive the overall stress response. In this study, the elastic behavior of a random SWCNT network with any set of junction stiffness and network density is also investigated using FE simulations. It is found that the elastic deformation of such networks can be governed either by the deformation of the nanotubes (bending, axial compression) or deformation of the junctions. The junction stiffness and the network density determine the network deformation mode. The results of the FE study are also applicable to any stiff fiber network.

Les travaux de cette thèse ont porté sur la caractérisation multi-échelle du polyéthylène(PE) en vue d'évaluer l'impact du vieillissement thermo-oxydatif. Cette étude a apporté un premier élément de réponse quant à l'efficacité de quelques méthodes de dosage des hydroperoxydes. Les résultats obtenus ont révélé une différence des concentrations en hydroperoxydes titrées par iodométrie par rapport à celles titrées par SO2 et MDSC lors de la deuxième période c'est-à-dire lors de la décomposition des hydroperoxydes. Cette différence semble directement reliée à l'apparition de double liaison. Les méthodes de dosage par SO2 et MDSC semblent être plus fiables. A l'échelle macromoléculaire, la chute de la masse molaire en poids Mw jusqu'à une valeur asymptotique de deux traduit des phénomènes de coupures de chaînes liés. A l'échelle microstructurale, l'augmentation de Xc est liée aux phénomènes de recuit et de chimicristallisation responsables de la formation et de l'épaississement des lamelles secondaires respectivement. Lors de la seconde période, l'augmentation de Mw liée à la diminution de Xc est due à la réticulation qui est confirmée par l'apparition des doubles liaisons et l'observation d'un gel lors de la dissolution du PEhd. Ces phénomènes de réticulation ont lieu au sein de la phase amorphe mais également à l'interphase avec la phase cristalline / The work of this thesis focused on the multi-scale characterization of polyethylene (PE) to assess the impact of thermo-oxidative aging. This study provided a first answer about the effectiveness of some hydroperoxides titration. The results revealed a difference in hydroperoxides concentrations titrated by iodometry compared to SO2 and MDSC in the second period that correpond to the decomposition of hydroperoxides. This difference appears to be linked to the occurrence of double bond. Titration methods with SO2 and MDSC seem to be more reliable. On the macromolecular scale, the decrease of the molecular weight Mw up to an asymptotic value of two is related to the chain scission process. On the microstructural scale, the increase of Xc is linked to the annealing and the chimicristallisation process which are responsible of the formation and the thickening of secondary lamellae. During the second period, the increase of Mw is related to the decrease of Xc due to crosslinking, which is confirmed by the occurrence of the double bonds and the observation of a gel during the dissolution of HDPE. These crosslinking phenomenon takes place in the amorphous phase but also in the transition region

Non seulement la structure hiérarchisée du tissu osseux mais aussi son hétérogénéité, son anisotropie et les incertitudes expérimentales de mesures liées aux matériaux vivants rendent en pratique impossible la définition d'un modèle déterministe fiable de ses propriétés matérielles. Dans une démarche d'aide au diagnostic clinique, l'objectif de cette thèse est de développer une modélisation robuste desdites propriétés à l'échelle de l'organe en intégrant l'incertitude expérimentale de mesures.Pour ce-faire, nous avons développé un modèle multi-échelle stochastique basé sur le principe du maximum d'entropie et des méthodes d’homogénéisation en champs moyens (micromécanique) qui s'est montré capable de prédire les propriétés matérielles du tissu osseux à l'échelle de l'organe en prenant en compte les incertitudes expérimentales de données issues de l’imagerie. Dans la perspective d'identifier le mécanisme de propagation de l’incertitude à travers le modèle multi-échelle, plusieurs versions de ce modèle ont été analysées.Le modèle principal utilise comme variables primaires la fraction volumique des constituants essentiels (le minéral, l'eau et le collagène) pour lesquelles une discussion est proposée échelle par échelle en examinant leur effet sur les propriétés effectives à chaque échelle. Cette description est à l’image d'une matryoshka, plus communément appelée poupée russe, via l’aspect multi-échelle. Chaque matryoshka est une série de poupées de tailles décroissantes placées les unes à l'intérieur des autres. Grâce à cette analyse, cette version du modèle a pu être liée de façon directe aux mesures expérimentales issues de l’imagerie médicale que sont la densité minérale du tissu (TMD) et la porosité haversienne (HP) de l'os cortical lors d’une calibration à l’échelle millimétrique. Cette version a été validée en utilisant plusieurs méthodes numériques telles que la méthode aux éléments finis et la méthode de la transformée de Fourier rapide. On a ainsi pu non seulement évaluer la précision de la méthode proposée mais aussi analyser le processus de transfert d'incertitudes entre les échelles.Enfin, la modélisation stochastique de l'os cortical a été complétée en introduisant des champs de tenseurs d’élasticité des matériaux impliqués dans le processus d’homogénéisation pour l’obtention des propriétés effectives. L’incertitude est introduite via un tenseur aléatoire et se propage spatialement en respectant des longueurs de corrélation et en une suite de réalisations. Ici encore, cette approche peut être vue comme une déclinaison des matryoshka via les champs de tenseurs d’élasticité qui se déclinent dans la procédure stochastique / The hierarchical structure of bone tissues, as well as the heterogeneity and anisotropy of its physical properties and the uncertainty on in vivo experimental measures make it impossible to establish a deterministic reliable model of bone mechanical properties. Aiming at providing a valuable aide to diagnostics in orthopaedic, the purpose of this thesis is to develop a robust mechanical model able to account for the experimental uncertainty.Therefore we developed a multi-scale stochastic model, based on continuum micromechanics and maximum entropy principle which has proved effective predicting the heterogeneous and anisotropic elastic properties of bone tissue at the organ scale accounting for experimental uncertainty affecting image-based input data.Aiming to clarify the mechanism of propagation of these uncertainties through the chosen principal multi-scale model, others versions have been analyzed. First, the principal model, which uses the volume fractions of the essential constituents (mineral, water, collagen), as primary variables, has been analyzed scale-by-scale (mineral foam, ultra-structure, cortical bone). The effect of the chosen homogenization methods and volume fractions on the resulting composites (as layers of a random Matryoshka) have been discussed. Thanks to this analysis, this model has been simplified and relied directly to the measures straightly accessible form medical imaging of the bone: the tissue mineral density (TMD) and the haversian porosity (HP) and their calibration at millimeter scale. This version of the stochastic model, proved to be as accurate as the proceeding one and, more effective in the description of the bone.Finally, the stochastic model of bone has been completed with the direct modeling of the elastic tensors of the involved materials. For this purpose, the random matrix theory has been applied. This theory can be seen as another declination of the Matryoshka paradigm. In this case, the uncertainty on the random tensor propagate from the inside (random germ) to outside (each layer of random matrix) through a suitable sequence of nonlinear operations. Thanks to the proposed decomposition, at once, the isotropic material class of the resulting material and his spatial variability has been included in the model

Les espaces montagnards représentent des zones à forts enjeux environnementaux, économiques, sociaux voire culturels. Les changements d’occupation et d’usage du sol qui s’y tiennent, qu’ils soient d’origine anthropiques ou non, ont engendré, au cours des dernières décennies, des dynamiques significatives d’enfrichement et de reforestation dans les Pyrénées françaises. Les tendances en cours laissent présager que ces dynamiques vont s’amplifier à l’avenir. Si ces dynamiques sont étroitement liées au déclin des activités agro-sylvo-pastorales, la localisation des zones potentiellement concernées constitue un réel enjeu pour les gestionnaires et les acteurs locaux. Dans une perspective de gestion à moyen ou long terme des espaces montagnards, il est aujourd’hui essentiel de pouvoir leur fournir une vision quantifiée des futurs possibles de leur territoire afin d’éclairer leurs décisions. L’objectif de ce travail est de construire des scénarios prospectifs spatialisés à trois échelles différentes et emboîtées (régionale, locale et micro-locale) afin d’identifier les espaces les plus vulnérables aux changements d’occupation et d’usage du sol et d’analyser l’influence des échelles spatiales et des approches de modélisation sur leur localisation. La démarche méthodologique s’articule autour de quatre étapes. La première étape consiste à identifier les approches de modélisation prospective qui sont privilégiées selon les échelles spatiales considérées. La seconde étape vise à construire « la base » des scénarios. La troisième étape consiste à produire les scénarios prospectifs spatialisés à chacune des échelles spatiales, selon des démarches de modélisation adaptées et des facteurs explicatifs pertinents, afin de simuler l’évolution possibles des paysages montagnards et d’identifier les espaces les plus vulnérables aux processus d’enfrichement et de reforestation. Enfin, la dernière étape consiste à analyser l’influence des échelles et des approches de modélisation au sein des travaux de prospective. Les scénarios prospectifs spatialisés ont permis (i) de quantifier et de spatialiser les impacts possibles de contextes socio-économiques et environnementaux contrastés sur les changements d’occupation et d’usage du sol et (ii) d’identifier les espaces les plus vulnérables aux changements à chacune des échelles considérées. Le croisement des scénarios produits a également permis d’évaluer l’incertitude spatiale des changements liée au futur. Les modèles pattern-based, utilisés à l’échelle régionale et locale, tendent à sous-estimer les changements par rapport au modèle process-based appliqué à l’échelle micro-locale. Au final, l’approche multi-scalaire a permis : d’apporter des connaissances sur le fonctionnement du système pyrénéen, voire de combler des lacunes quant aux données disponibles, qu’une approche mono-scalaire n’aurait pas produites ; de cibler les espaces les plus propices aux changements et d’établir un degré de confiance quant aux approches de modélisation choisies dans le but d’éclairer les politiques et stratégies de gestion. / Mountain areas exhibit high environmental, economic, social or cultural values. Land use and cover changes (LUCC), whether or not from anthropogenic origin, have led to significant encroachment and reforestation dynamics over the last decades in the French Pyrenees. Current trends suggest that these dynamics will amplify in the future. If they are closely related to the decline of agropastoral and forestry activities, the location of potentially affected areas is of great importance for managers and local stakeholders. For medium to long-term management perspectives, it is now essential to provide a quantified vision of possible futures of their territory to help in the definition of sustainable strategies. The objective of this work is to spatialize future scenarios at three different scales (regional, local and micro-local) to identify the most vulnerable areas to LUCC and analyze the influence of spatial scales and modeling approaches on their location. The methodology is based on four stages. The first step is to identify prospective modelling approaches that are preferred according to the considered spatial scales. The second step is to provide the knowledge for building scenarios. The third step is to simulate future scenarios at each spatial scales to identify the most vulnerable areas to encroachment and reforestation. The last step is to analyze the influence of scales and modeling approaches in the prospective framework. Spatially explicit scenarios allow to (i) quantify and assess possible impacts of contrasting socio-economic and environmental contexts on LUCC, and (ii) identify the most vulnerable areas to encroachment and reforestation for each considered spatial scale. Moreover, the combination of scenarios allows to evaluate the spatial uncertainty, regrouping the inherent and the ensemble uncertainties, related to future LUCC. The pattern-based models used at the regional and local levels tend to underestimate LUCC compared to the process-based model used. Finally, the multi-scale approach allowed to provide knowledge on the Pyrenean land system that a single scale approach would not have provided, to target the areas at stake regarding future LUCC and to establish a degree of confidence in the adopted modeling approaches in order to help in the definition and assessment of land use policies and strategies.

La stérilisation déstabilisant les protéines laitières acidifiées, des stabilisants sont généralement ajoutés. L’objectif de cette thèse était de comprendre les mécanismes physico-chimiques induits par l’acidification de formules laitières puis de rechercher des voies de stabilisation clean label pour les caséines acidifiées et traitées UHT. Des analyses décrivant la minéralisation, la charge de surface, l’hydratation et les modifications chimiques des caséines ont été mises en œuvre pour étudier leur stabilité.À l’échelle pilote, les caséines étaient plus stables à pH > 5,8 (entre pH 6,7 et 3,7), à basse température (8 versus 42°C), dans une formule riche en protéines (7 versus 3,2 %) et acidifiées par acide citrique (versus lactique). La meilleure stabilité dans ces conditions (parmi 140 combinaisons) s’expliquerait par des diminutions de répulsions électrostatiques, hydrophobes et de diffusion ainsi que par des augmentations de pouvoir tampon et de calcium chélaté par le citrate.Cependant, un traitement de 120°C / 15 s déstabilisait les micelles de caséines dès pH 6,2. L’ajout de matière grasse n’apportait pas d’amélioration. La lactosylation a ensuite été étudiée pour diminuer le pHi des caséines et donc les stabiliser à pH acide. Un prétraitement thermique (90°C / 60 min) à pH 7,5 avec du lactose leur a été appliqué dans différents environnements physico-chimiques. Les niveaux de lactosylation des caséines en milieu dilué étaient faibles mais augmentés avec une forte concentration en lactose (150 g/L) ou en milieu sec. Ce prétraitement appliqué en présence d’une concentration élevée en caséines (50 g/L) ou en minéraux -teneur en perméat triplée) améliorait davantage la stabilisation thermique des protéines acidifiées que la lactosylation seule. Cela s'exliquerait par un pouvoir tampon supérieur lié à cet environnement plus riche. / As sterilization destabilizes acidified dairy proteins, stabilizers are usually added. The objective of this thesis was to understand the physicochemical mechanisms induced by the acidification of dairy formulas and to look for clean label solutions to stabilize for acidified and heat treated caseins. To study their stability, the mineralization, surface charge, hydration and chemical modifications of caseins were characterized.At the pilot scale, caseins were more stable at pH > 5.8 (between pH 6.7 and 3.7), low temperature (8 versus 42°C), in formulas which were enriched in proteins (7 versus 3.2 %) and acidified with citric acid (versus lactic). This set of conditions (amid 140 combinations) would be the best to preserve the stability of proteins because it would correspond to a decrease of electrostatic and hydrophobic repulsions and of diffusion and to an increase of buffer strength and of citrate-chelated calcium content.However, a heat treatment at 120°C during 15 s destabilized casein micelles from pH 6.2 whatever the set of conditions. Adding fat did not bring any improvement.Next, lactosylation was studied to decrease the pHi of caseins so as to stabilize them at acidic pH. A heat pretreatment (90°C/60 min) at pH 7.5 in the presence of lactose was applied to casein micelles in several physicochemical environments. Lactosylation rates of casein in aqueous conditions were low but they were increased with high lactose content (150 g/L) or in dry conditions. This heat pretreatment, implemented with a high casein (50 g/L) or mineral (triple-concentrated permeate content) concentration improved even more the heat stability of acidified proteins than lactosylation only. This could be explained by higher buffer strength due to this richer environnement

Carbon nanotubes (CNT) could serve as potential reinforcement for metal matrix composites for improved mechanical properties. However dispersion of carbon nanotubes (CNT) in the matrix has been a longstanding problem, since they tend to form clusters to minimize their surface area. The aim of this study was to use plasma and cold spraying techniques to synthesize CNT reinforced aluminum composite with improved dispersion and to quantify the degree of CNT dispersion as it influences the mechanical properties. Novel method of spray drying was used to disperse CNTs in Al-12 wt.% Si pre-alloyed powder, which was used as feedstock for plasma and cold spraying. A new method for quantification of CNT distribution was developed. Two parameters for CNT dispersion quantification, namely Dispersion parameter (DP) and Clustering Parameter (CP) have been proposed based on the image analysis and distance between the centers of CNTs. Nanomechanical properties were correlated with the dispersion of CNTs in the microstructure. Coating microstructure evolution has been discussed in terms of splat formation, deformation and damage of CNTs and CNT/matrix interface. Effect of Si and CNT content on the reaction at CNT/matrix interface was thermodynamically and kinetically studied. A pseudo phase diagram was computed which predicts the interfacial carbide for reaction between CNT and Al-Si alloy at processing temperature. Kinetic aspects showed that Al4C3 forms with Al-12 wt.% Si alloy while SiC forms with Al-23wt.% Si alloy. Mechanical properties at nano, micro and macro-scale were evaluated using nanoindentation and nanoscratch, microindentation and bulk tensile testing respectively. Nano and micro-scale mechanical properties (elastic modulus, hardness and yield strength) displayed improvement whereas macro-scale mechanical properties were poor. The inversion of the mechanical properties at different scale length was attributed to the porosity, CNT clustering, CNT-splat adhesion and Al4C3 formation at the CNT/matrix interface. The Dispersion parameter (DP) was more sensitive than Clustering parameter (CP) in measuring degree of CNT distribution in the matrix.

Multi-scale modelling and analysis is becoming increasingly important and relevant. Analysis of the emergent properties from the interactions between scales of multi-scale systems is important to aid in solutions. There is no universally adopted theoretical/computational framework or language for the construction of multi-scale models. Most modelling approaches are specific to the problem that they are addressing and use a hybrid combination of modelling languages to model specific scales. This thesis addresses if process algebra can offer a unique opportunity in the definition and analysis of multi-scale models. In this thesis the generic Process Algebra with Layers (PAL) is defined: a language for multi-scale integration modelling. This work highlights the potential of process algebra to model multi-scale systems. PAL was designed based on features and challenges found from modelling a multi-scale system in an existing process algebra. The unique features of PAL are the layers: Population and Organism. The novel language modularises the spatial scales of the system into layers, therefore, modularising the detail of each scale. An Organism can represent a molecule, organelle, cell, tissue, organ or any organism. An Organism is described by internal species. An internal species, dependent on the scale of the Organism, can also represent a molecule, organelle, cell, tissue, organ or any organism. Populations hold specific types of Organism, for example, life stages, cell phases, infectious states and many more. The Population and Organism layers are integrated through mirrored actions. This novel language allows the clear definition of scales and interactions within and between these scales in one model. PAL can be applied to define a variety of multi-scale systems. PAL has been applied to two unrelated multi-scale system case studies to highlight the advantages of the generic novel language. Firstly the effects of ocean acidification on the life stages of the Pacific oyster. Secondly the effects of DNA damage from cancer treatment on the length of a cell cycle and cell population growth.

No description available.

I present a general methodology for inverting seismic data in either the data or image domains. It partially overcomes one of the most serious problems with current waveform inversion methods, which is the tendency to converge to models far from the actual one. The key idea is to develop a multiscale misfit function that is composed of both a simplified version of the data and one associated with the complex part of the data. Misfit functions based on simple data are characterized by many fewer local minima so that a gradient optimization method can make quick progress in getting to the general vicinity of the actual model. Once we are near the actual model, we then use the gradient based on the more complex data. Below, we describe two implementations of this multiscale strategy: wave equation traveltime inversion in the data domain and generalized differential semblance optimization in the image domain. • Wave Equation Traveltime Inversion in the Data Domain (WT): The main difficulty with iterative waveform inversion is that it tends to get stuck in local minima associated with the waveform misfit function. To mitigate this problem and avoid the need to fit amplitudes in the data, we present a waveequation method that inverts the traveltimes of reflection events, and so is less prone to the local minima problem. Instead of a waveform misfit function, the penalty function is a crosscorrelation of the downgoing direct wave and the upgoing reflection wave at the trial image point. The time lag which maximizes the crosscorrelation amplitude represents the reflection-traveltime residual that is back-projected along the reflection wavepath to update the velocity. Shot- and angle-domain crosscorrelation functions are introduced to estimate the reflection-traveltime residual by semblance analysis and scanning. In theory, only the traveltime information is inverted and there is no need to precisely fit the amplitudes or assume a high-frequency approximation. Results with both synthetic data and field records reveal both the benefits and limitations of WT. • Generalized Differental Semblance Optimization in the Image Domain (GDSO): We now extend the multiscale physics approach to differential semblance optimization (DSO) in the image domain. That is, we identify the space-lag offset H(x, z, h) in the subsurface-offset domain as an implicit function of velocity. It describes the smoothly varying moveout H(x, z, h) of the migration image m(x, z, h) in the subsurface-offset domain, which is analogous to the smoothly varying traveltime residual ∆τ(x) of a reflection event in a shot gather. The velocity model is found that minimizes the objective function ∑x,z,h H(x, z, h)2m(x, z, h)2, where coherent noise is eliminated everywhere except along the picked curve H(x, z, h). This method is denoted as generalized DSO (GDSO) and mitigates the coherent noise problem with DSO. Numerical examples are presented that empirically demonstrate its effectiveness in providing more accurate velocity models compared to conventional DSO.