In this dissertation we study multiscale methods for slowly varying porous media, fluid and solid coupling, and application to geomechanics. The thesis consists of three closely connected results. We outline them and their relation. First, we derive a homogenization result for Stokes flow in slowly varying porous media. These results are important for homogenization in deformable porous media. Traditionally, these techniques are applied to periodic media, however, in the case of Fluid-Structure Interaction (FSI) slowly varying domains occur naturally. We then develop a computational methodology to compute effective quantities to construct homogenized equations for such media. Next, to extend traditional geomechanics models based primarily on the Biot equations, we use formal two-scale asymptotic techniques to homogenize the fully coupled FSI model. Prior models have assumed trivial pore scale deformation. Using the FSI model as a fine-scale model, we are able to incorporate non-trivial pore scale deformation into the macroscopic equations. The primary challenge here being the fluid and solid equations are represented in different coordinate frames. We reformulate the fluid equation in the fixed undeformed frame. This unified domain formulation is known as the Arbitrary Lagrange-Eulerian (ALE). Finally, we utilize the ALE formulation of the Stokes equations to develop an efficient multiscale finite element method. We use this method to compute the permeability tensor with much less computational cost. We build a dense hierarchy of macro-grids and a corresponding collection of nested approximation spaces. We solve local cell problems at dense macro-grids with low accuracy and use neighboring high accuracy solves to correct. With this method we obtain the same order of accuracy as we would if we computed all the local problems with highest accuracy.

The objective of this study was to investigate the application of multiscale satellite remote sensing data for assessment of land cover change in the rural-urban fringe. Inherent in this assessment process was the interpretation of multispectral data collected by several medium resolution satellite systems and evaluation of the quality of the resulting change information. Each dataset was acquired for a single date and classified at two levels of detail using standard classification algorithms. The optimum classification approach for each date was identified and the changes in land cover evaluated in several ways. The contribution of spatial and thematic errors and their propagation through the analysis process was investigated.Data for this research were acquired over an area approximately 4.5 km square located in the southern metropolitan area of Perth, Western Australia. At the time of the initial data acquisition in 1972 the area was predominantly rural and comprised mostly dense pine plantations, however by the final stages of data acquisition in 1991, the area was almost completely given over to urban residential land use. Changes were interpreted from classified Landsat Multispectral Scanner (MSS), Landsat Thematic Mapper (TM) and SPOT (System Pour l'Observation de la Terre) High Resolution Visible (HRV) multispectral data, and were compared to reference maps compiled from medium scale aerial photographs. The geometric properties of high resolution panchromatic IRS1-D data were also evaluated to test the geometric potential of high resolution satellite data.Supervised and unsupervised classification algorithms were used for derivation of land cover maps from each multispectral dataset at two levels of detail. Data were classified onto four general levels at the broadest (Level I) classification, and into nine levels at the finest (Level II) classification. The ++ / Kappa statistic and its variance were used to determine the optimum classification approach for each dataset and at each level of detail. No significant differences were observed between classification techniques at Level I, however at Level II the supervised classification approach produced significantly better results for the Landsat TM and SPOT HRV data. Classification at the more general Level I did not produce substantially higher classification rates compared to the same data at Level II. Additionally, higher spatial resolution data did not provide increased accuracy, however this was due mainly to a much greater complexity of land covers present at the time the higher resolution Landsat TM and SPOT HRV data were recorded.Land cover changes were assessed separately at Level I for all datasets, and also between Landsat TM and SPOT HRV data at Level II. Integrated multiscale assessment of land cover change was undertaken using classified Landsat MSS data at Level I and Landsat TM data at Level 11. This enabled the continuity of change to be established across classification levels and sensor systems, even though there were variations in the level of detail extracted from each image.The sources of spatial and thematic errors in the data were investigated and their effects on change assessment analysed. The evaluation of high resolution panchromatic satellite data emphasised the contribution to the analysis of spatial errors contained within the reference data. The multiscale data also indicated that combined propagation of spatial and thematic errors requires investigation using appropriate simulation modelling to establish the influence of data uncertainty on classification and change assessment results.This research provides useful results for demonstrating a process for the integration of information derived from remotely sensed data at different measurement ++ / scales. Availability of data from an increasing range of remote sensing platforms and uncertainty of long term data availability emphasises the need to develop flexible interpretation and analysis approaches. This research adds value to the existing data archive by demonstrating how historical data may be integrated regardless of the spectral and spatial characteristics of the sensors.

abstract: This research focuses on the benefits of using nanocomposites in aerospace structural components to prevent or delay the onset of unique composite failure modes, such as delamination. Analytical, numerical, and experimental analyses were conducted to provide a comprehensive understanding of how carbon nanotubes (CNTs) can provide additional structural integrity when they are used in specific hot spots within a structure. A multiscale approach was implemented to determine the mechanical and thermal properties of the nanocomposites, which were used in detailed finite element models (FEMs) to analyze interlaminar failures in T and Hat section stringers. The delamination that first occurs between the tow filler and the bondline between the stringer and skin was of particular interest. Both locations are considered to be hot spots in such structural components, and failures tend to initiate from these areas. In this research, nanocomposite use was investigated as an alternative to traditional methods of suppressing delamination. The stringer was analyzed under different loading conditions and assuming different structural defects. Initial damage, defined as the first drop in the load displacement curve was considered to be a useful variable to compare the different behaviors in this study and was detected via the virtual crack closure technique (VCCT) implemented in the FE analysis. Experiments were conducted to test T section skin/stringer specimens under pull-off loading, replicating those used in composite panels as stiffeners. Two types of designs were considered: one using pure epoxy to fill the tow region and another that used nanocomposite with 5 wt. % CNTs. The response variable in the tests was the initial damage. Detailed analyses were conducted using FEMs to correlate with the experimental data. The correlation between both the experiment and model was satisfactory. Finally, the effects of thermal cure and temperature variation on nanocomposite structure behavior were studied, and both variables were determined to influence the nanocomposite structure performance. / Dissertation/Thesis / Doctoral Dissertation Aerospace Engineering 2014

Dans le cadre du stockage des déchets nucléaires en couche géologique profonde (projet Cigéo), il est nécessaire de pouvoir prédire l'écoulement des radionucléides sous forme ionique dans des milieux poreux chargés tels que l'argile. Les matériaux argileux sont complexes et il est difficile de connaître leur structure, surtout à l'échelle nanoscopique où les phénomènes électrocinétiques deviennent primordiaux. Dans ce cas, la stratégie adoptée dans ce travail est de représenter la porosité à l'aide d'un réseau de pores connectés entre eux par des canaux. Cela nécessite de connaître les propriétés du transport couplé à l'échelle du canal en prenant en compte les flux de solvant, de solutés et de charges sous l'influence de gradients de pression, de concentration en sel et de potentiel électrostatique. La description du transport électrocinétique utilisée correspond à celle du modèle de Poisson-Nernst-Planck. On peut ainsi montrer que le comportement de ces propriétés peut différer entre l'échelle du canal et celle de l'échantillon (réseaux construits aléatoirement à partir de distributions de paramètres). Par exemple, on constate que la perméabilité d'un réseau diminue si les effets électrocinétiques augmentent, ce qui n'est pas le cas à l'échelle du canal. Ces différences proviennent de la présence simultanée de couplages entre les flux et de l'hétérogénéité du milieu. Un échantillon numérique ayant les mêmes propriétés qu'un échantillon réel d'argile a ainsi été créé au terme d'un processus de sélection des distributions de paramètres des canaux, il a ainsi servi à réaliser des études préliminaires sur le colmatage et la désaturation. / As part of the disposal of nuclear waste in deep geological formations (Cigéo project), it is necessary to predict the flow of radionuclides in ionic form in charged porous media such as clays. The clay materials are complex and it is difficult to know their structure, especially at the nanoscale where electrokinetic phenomena become paramount. In this case, the strategy adopted in this work is to represent the porosity with a network of pores interconnected by channels. This requires to know the properties of the coupled transport at the channel scale taking into account the flow of solvent, solutes and charges under the influence of gradients of pressure, salt concentration and electrostatic potential. We used the Poisson-Nernst-Planck model to describe the electrokinetic transport in the channels. It can be shown that the behavior of these properties may vary between the channel scale and the sample scale (random networks constructed from parameters distributions). For example, it is found that the permeability of a network decreases as electrokinetic effects increase, which is not the case at the level of a single channel. These differences arise from the simultaneous presence of coupling between the flows and the heterogeneity of the sample. A numerical sample having the same properties as real clay sample has been created following a process of selection of the channels parameters, it has been used to conduct preliminary studies on clogging and desaturation in clay.

Ce travail de thèse a pour but de modéliser la macroségrégation des produits obtenus par solidification en prenant en compte le transport des grains équiaxes. Le modèle de solidification à deux phases (solide et liquide) est traité par une méthode d'éléments finis, consistant à résoudre les équations de conservation moyennées de l'énergie, de la quantité de mouvement et de la masse, dans lesquelles les évolutions multi-échelles de la masse des phases et des solutés sont modélisées en utilisant une approche de splitting. D'après cette technique, la variation des quantités est considérée comme résultant de la contribution de deux étapes : l'étape de croissance et l'étape de transport. L'implémentation numérique du modèle a été réalisée avec trois opérations principales : tout d'abord implémenter le modèle de croissance des grains, ensuite intégrer des phénomènes de transport résultant de la convection thermo-solutale du liquide et du mouvement du solide, enfin mettre en œuvre le modèle complet en combinant les étapes de croissance et de transport. Lors de ces opérations, une investigation attentive a été consacrée à l'établissement de la résolution par éléments finis pour les équations de transport avec champs discontinus de vitesse à divergence non nulle, afin de surmonter des problèmes numériques en respectant la qualité des solutions physiques. Parallèlement à ces travaux, différents tests de simulation 2D ont été effectués à chaque étape d'implémentation. De bons accords ont été globalement obtenus entre les solutions données par le modèle présent et celles de référence dans la littérature. Finalement, des applications industrielles et des simulations 3D ont été menées, pour lesquelles les résultats numériques reproduisent les configurations caractéristiques des mesures expérimentales : un profil typique de macroségrégation des lingots composé d'une ségrégation négative occupant de la zone inférieure et d'une ségrégation positive en zone supérieure. Ce profil est la signature caractéristique de la sédimentation des cristaux et de la convection thermo-solutale. En outre, un modèle à trois phases étendu à partir du modèle à deux phases précédent – en distinguant la phase liquide interdendritique – s'est avéré capable de décrire la morphologie des grains dendritiques. / The present work aims at modeling macrosegregation of castings, accounting for the transport of equiaxed grains. A two-phase (solid and liquid) finite element solidification model is presented, consisting in solving a system of volume-averaged conservation equations of energy, momentum, solute, in which the multi-scale evolutions of phase and solute mass are modeled by using a splitting method. According to this approach, the variation of quantities is considered as due to the contribution of two stages: the growth stage and the transport stage. The numerical implementation was realized with three principal steps: first implementing growth processes, then integrating transport phenomena including the thermo-solutal liquid convection and the solid movement, lastly combing the growth and transport stages to achieve a complete growth-transport model. Of these steps, solving the transport equations with discontinuous and non-divergence-free velocity fields by using finite element method required an attentive investigation in order to overcome numerical issues while respecting for physical solutions. Parallel to these works, various two-dimensional simulation tests were carried out in each implementation step. Agreements were globally found between results obtained from the present model and those of reference from the literature. Finally, industrial applications and three-dimensional simulations were performed, which show that computational solutions can predict essential features of experimental measurements. In particular, a typical macrosegregation profile of steel ingots, containing a negative segregation in the lower zone and a positive segregation in the upper zone, which is predominantly characterized by crystals sedimentation and fluid circulation was retrieved. Moreover, a three-phase model considering two different liquid phases, extended from the above-mentioned two-phase model, which enables to describe the morphology of dendritic solid crystals was implemented.

This thesis covers the simulation and modelling of the transesterification of triglyceride oils to make biodiesel, using heterogeneous catalysts. Initially, data fitting was performed to fit overall kinetic rate equations to experimental data, ignoring diffusional behaviour. Additionally, experiments were undertaken to investigate the influence of feed ratio on the reaction kinetics. A single site mechanism with surface reaction as the rate limiting step was found to most closely match the experimental conversion profiles for the operating conditions studied. To incorporate diffusional behaviour into the modelling a multicomponent diffusion methodology was adapted for use within this system. To verify transport properties of the system and the suitability of this theoretical diffusion calculation, measurement of density and viscosity for a range of mixtures was undertaken, along with molecular dynamics simulation to produce diffusion coefficients. Finally, a novel algorithm was developed to simulate coupled diffusion and reaction within the pores of the catalyst and the subsequent bulk concentration changes this produced.

Orientadores: Hélio Pedrini, William Robson Schwartz / Dissertação (mestrado) - Universidade Estadual de Campinas, Instituto de Computação / Made available in DSpace on 2018-08-24T04:06:04Z (GMT). No. of bitstreams: 1 Siqueira_FernandoRobertide_M.pdf: 20841189 bytes, checksum: 62053b7b36d54bbdccc8b5aa3650fe6a (MD5) Previous issue date: 2013 / Resumo: Visão computacional e processamento de imagens desempenham um papel importante em diversas áreas, incluindo detecção de objetos e classificação de imagens, tarefas muito importantes para aplicações em imagens médicas, sensoriamento remoto, análise forense, detecção de pele, entre outras. Estas tarefas dependem fortemente de informação visual extraída de imagens que possa ser utilizada para descrevê-las eficientemente. Textura é uma das principais propriedades usadas para descrever informação tal como distribuição espacial, brilho e arranjos estruturais de superfícies. Para reconhecimento e classificação de imagens, um grande grupo de descritores de textura foi investigado neste trabalho, sendo que apenas parte deles é realmente multiescala. Matrizes de coocorrência em níveis de cinza (GLCM) são amplamente utilizadas na literatura e bem conhecidas como um descritor de textura efetivo. No entanto, este descritor apenas discrimina informação em uma única escala, isto é, a imagem original. Escalas podem oferecer informações importantes em análise de imagens, pois textura pode ser percebida por meio de diferentes padrões em diferentes escalas. Dessa forma, duas estratégias diferentes para estender a matriz de coocorrência para múltiplas escalas são apresentadas: (i) uma representação de escala-espaço Gaussiana, construída pela suavização da imagem por um filtro passa-baixa e (ii) uma pirâmide de imagens, que é definida pelo amostragem de imagens em espaço e escala. Este descritor de textura é comparado com outros descritores em diferentes bases de dados. O descritor de textura proposto e então aplicado em um contexto de detecção de pele, como forma de melhorar a acurácia do processo de detecção. Resultados experimentais demonstram que a extensão multiescala da matriz de coocorrência exibe melhora considerável nas bases de dados testadas, exibindo resultados superiores em relação a diversos outros descritores, incluindo a versão original da matriz de coocorrência em escala única / Abstract: Computer vision and image processing techniques play an important role in several fields, including object detection and image classification, which are very important tasks with applications in medical imagery, remote sensing, forensic analysis, skin detection, among others. These tasks strongly depend on visual information extracted from images that can be used to describe them efficiently. Texture is one of the main used characteristics that describes information such as spatial distribution, brightness and surface structural arrangements. For image recognition and classification, a large set of texture descriptors was investigated in this work, such that only a small fraction is actually multi-scale. Gray level co-occurrence matrices (GLCM) have been widely used in the literature and are known to be an effective texture descriptor. However, such descriptor only discriminates information on a unique scale, that is, the original image. Scales can offer important information in image analysis, since texture can be perceived as different patterns at distinct scales. For that matter, two different strategies for extending the GLCM to multiple scales are presented: (i) a Gaussian scale-space representation, constructed by smoothing the image with a low-pass filter and (ii) an image pyramid, which is defined by sampling the image both in space and scale. This texture descriptor is evaluated against others in different data sets. Then, the proposed texture descriptor is applied in skin detection context, as a mean of improving the accuracy of the detection process. Experimental results demonstrated that the GLCM multi-scale extension has remarkable improvements on tested data sets, outperforming many other feature descriptors, including the original GLCM / Mestrado / Ciência da Computação / Mestre em Ciência da Computação

abstract: This dissertation explores thermal effects and electrical characteristics in metal-oxide-semiconductor field effect transistor (MOSFET) devices and circuits using a multiscale dual-carrier approach. Simulating electron and hole transport with carrier-phonon interactions for thermal transport allows for the study of complementary logic circuits with device level accuracy in electrical characteristics and thermal effects. The electrical model is comprised of an ensemble Monte Carlo solution to the Boltzmann Transport Equation coupled with an iterative solution to two-dimensional (2D) Poisson’s equation. The thermal model solves the energy balance equations accounting for carrier-phonon and phonon-phonon interactions. Modeling of circuit behavior uses parametric iteration to ensure current and voltage continuity. This allows for modeling of device behavior, analyzing circuit performance, and understanding thermal effects. The coupled electro-thermal approach, initially developed for individual n-channel MOSFET (NMOS) devices, now allows multiple devices in tandem providing a platform for better comparison with heater-sensor experiments. The latest electro-thermal solver allows simulation of multiple NMOS and p-channel MOSFET (PMOS) devices, providing a platform for the study of complementary MOSFET (CMOS) circuit behavior. Modeling PMOS devices necessitates the inclusion of hole transport and hole-phonon interactions. The analysis of CMOS circuits uses the electro-thermal device simulation methodology alongside parametric iteration to ensure current continuity. Simulating a CMOS inverter and analyzing the extracted voltage transfer characteristics verifies the efficacy of this methodology. This work demonstrates the effectiveness of the dual-carrier electro-thermal solver in simulating thermal effects in CMOS circuits. / Dissertation/Thesis / Doctoral Dissertation Electrical Engineering 2019

Analytic and computational micromechanics techniques based on the composite cylinders method and the finite element method, respectively, have been used to determine the effective coefficient of thermal expansion (CTE) of carbon nanotube-epoxy nanocomposites containing aligned nanotubes. Both techniques have been used in a parametric study of the influence of interphase stiffness and interphase CTE on the effective CTE of the nanocomposites.  For both the axial and transverse CTE of aligned nanotube nanocomposites with and without interphase regions, the computational and analytic micromechanics techniques were shown to give similar results.  The Mori-Tanka method has been used to account for the effect of randomly oriented fibers.   Analytic and computational micromechanics techniques have also been used to assess the effects of clustering and clustering with interphase on the effective CTE components.  Clustering is observed to have a minimal impact on the effective axial CTE of the nanocomposite and a 3-10%.  However, there is a combined effect with clustering and one of the interphase layers. / Master of Science

The majority of clinical impairments following a concussion resolve within 7-10 days. However, there is limited clarity as to long-term impact of this injury on neurocognitive function, motor control, and particularly integration of these domains. While repetitive head trauma is associated with numerous neurological disorders, the link is not well described. Visual-motor tracking tasks have been used to identify differences in visual processing, error detection, and fine motor control in aging and numerous pathologies. Examining the complexity of motor output from visual-motor tracking provides insight into multiple cognitive and motor function domains, and into fine motor control used for daily living, work, and sport. The purpose of this dissertation was, therefore, to: (1) use multiple regression to determine the extent to which concussion history and symptoms (loss of consciousness and amnesia) influence visual-motor task performance multiscale complexity, and (2) determine whether task performance complexity can distinguish, through logistic regression and prediction, between individuals with and without a history of concussion. In study 1, individuals with (n = 35) and without (n = 15) a history of concussion performed a visual-motor tracking task. Men and women exhibited linear decreases in task performance complexity, as well as midand high-frequency task performance components, with increasing numbers of concussions. However, men and women exhibited differing patterns, as did those with and without a history of concussion-related loss of consciousness. Finally, trial-to-trial complexity variability increased with increasing numbers of concussions. Findings indicate (1) a cumulative reduction in the way in which previously concussed individuals process and integrate visual information to guide behavior and (2) gender is an important consideration in concussion-related visual-motor outcomes. In Study 2, individuals with (n = 85) and without (n = 42) a history of concussion performed a visualmotor tracking task. Linear and nonlinear measures of task performance were used to build gender-specific logistic classification models using 10-fold cross-validation. When ensuring 80% sensitivity, the best models were 75-80% accurate in predicting a history of concussion. Such discrimination has clinical value in identifying individuals who merit further evaluation and observation over time for conditions related to repetitive head traumas.