[pt] Escoamentos de fluidos sobre paredes flexíveis se fazem presentes em diversos processos biológicos e industriais. A flexibilidade do sólido permite a propagação de ondas na interface, podendo levar o sistema a se tornar instável mesmo a baixos valores do número de Reynolds. Esta perda de estabilidade provoca uma alteração nas características hidrodinâmicas e na transferência de calor do processo. Os trabalhos disponíveis na literatura se concentram em torno de análise de estabilidade linear e experimentos de determinação de parâmetros críticos. Entretanto estas metodologias não são capazes de descrever o comportamento do sistema após sua desestabilização. Neste trabalho, o regime instável de um escoamento de Couette de um fluido Newtoniano sobre um sólido incompressível e impermeável de MooneyRivlin é estudado numericamente através da solução acoplada das equações de conservação de quantidade de movimento linear transiente de cada meio. O número de Reynolds foi escolhido pequeno o suficiente para afastar a possibilidade de que mecanismos inerciais se façam presentes. Diferentes razões de espessura líquido-sólido flexível foram utilizadas para se determinar os efeitos desta grandeza sobre o processo. O sistema de equações diferenciais foram integradas no espaço pelo método de Galerkinjelementos finitos, e no tempo por diferenças finitas. A necessidade de se utilizar passos de tempo variáveis exigiu o desenvolvimento de uma fórmula específica para a aproximação da derivada segunda presente no termo transiente do sólido. / [en] Fluid flow over flexible wall are present in several biological and industrial processes. The flexibility of the solid body permits the waves propagation along the interface, leading the system to become unstable even at low value of Reynolds number. This loss of stability induce some changes on the hydrodynamic characteristics and on the heat transfer of the process. Works available on literature are concentrated around linear stability analysis and experiments of determining critical parameters. Nevertheless these methodologies are not able of describing the system behavior after the desestabilization. In this work, the unstable regime of a Newtonian fluid Couette flow over an incompressible and impermeable Mooney-Rivlin solid is numerically studied by solving the coupled fluid and solid momentum equation. The Reynolds number has been chosen small enough to avoid the presence of inertial mechanisms. Different liquid-flexible solid thickness ratio were used to determine the effect of this parameter on the problem. The system of differential equations were integrated by Galerki s/finite elements method on space, and by finite differences on time. The necessity of using variables changeables time steps demanded the development of a specific equation to approximates the second material derivative present on the unsteady solid term.

The combination of X-ray imaging and diffraction techniques provides a unique tool for structural and mechanical analysis of engineering components. A variety of modes can be employed in terms of the spatial resolution (length-scale), time resolution (frequency), and the nature of the physical quantity being interrogated. This thesis describes my contributions towards the development of novel X-ray “rich” imaging experimental techniques and data interpretation. The experimental findings have been validated via comparison with other experimental methods and numerical modelling. The combination of fast acquisition rate and high penetration properties of X-ray beams allows the collection of high-resolution 3-D tomographic data sets at submicron resolution during in situ deformation experiments. Digital Volume Correlation analysis tools developed in this study help understand crack propagation mechanisms in quasi-brittle materials and elasto-plastic deformation in co-sprayed composites. For the cases of crystalline specimens where the knowledge of “live” or residual elastic strain distributions is required, diffraction techniques have been advanced. Diffraction Strain Tomography (DST) allows non-destructive reconstruction of the 2-D (in-plane) variation of the out-of-plane strain component. Another diffraction modality dubbed Laue Orientation Tomography (LOT), a grain mapping approach has been proposed and developed based on the translate-rotate tomographic acquisition strategy. It allows the reconstruction of grain shape and orientation within polycrystalline samples, and provides information about intragranular lattice strain and distortion. The implications of this method have been thoroughly investigated. State-of-the-art engineering characterisation techniques evolve towards scrutinising submicron scale structural features and strain variation using the complementarity of X-ray imaging and diffraction. The first successful feasibility study is reported of in operando stress analysis in an internal combustion engine. Finally, further advancement of ‘rich’ imaging techniques is illustrated via the first successful application of Time-of-Flight Neutron Diffraction Strain (TOF-NDST) tomography for non-destructive reconstruction of the complete strain tensor using an inverse eigenstrain formulation.

No description available.

Laser beam welding has been widely applied in different industrial sectors due to its unique advantages. However, there are still challenges, such as beam positioning in T-joint welding, and gap bridging in butt joint welding,especially in the case of varying gap width along a joint. It is expected that enabling more advanced control to a welding system, and obtaining more in-depth process knowledge could help to solve these issues. The aim of this work is to address such welding issues by a laser beam shaping technology using a novel deformable mirror together with computer vision methods and also to increase knowledge about the benefits and limitations with this approach. Beam shaping in this work was realized by a novel deformable mirror system integrated into an industrial processing optics. Together with a wave front sensor, a controlled adaptive beam shaping system was formed with a response time of 10 ms. The processes were monitored by a coaxial camera with selected filters and passive or active illumination. Conduction mode autogenous bead-on-plate welding and butt joint welding experiments have been used to understand the effect of beam shaping on the melt pool geometry. Circular Gaussian, and elliptical Gaussian shapes elongated transverse to and along the welding direction were studied. In-process melt pool images and cross section micrographs of the weld seams/beads were analyzed. The results showed that the melt pool geometry can be significantly modified by beam shaping using the deformable mirror. T-joint welding with different beam offset deviations relative to the center of the joint line was conducted to study the potential of using machine learning to track the process state. The results showed that machine learning can reach sufficient detection and estimation performance, which could also be used for on-line control. In addition, in-process and multidimensional data were accurately acquired using computer vision methods. These data reveal weaknesses of current thermo-fluid simulation model, which in turn can help to better understand and control laser beam welding. The obtained results in this work shows a huge potential in using the proposed methods to solve relevant challenges in laser beam welding. / Lasersvetsning används i stor utsträckning i olika industrisektorer på grund av dess unika fördelar. Det finns emellertid fortfarande utmaningar, såsom rätt positionering av laserstrålen vid genomträngningssvetsning av T-fogar och hantering av varierande spaltbredd längs fogen vid svetsning av stumfogar. Sådana problem förväntas kunna lösas med avancerade metoder för automatisering, metoder som också förväntas ge fördjupade kunskaper om processen. Syftet med detta arbete är att ta itu med dessa problem med hjälp av en teknik för lasereffektens fördelning på arbetsstycket, s.k. beam shaping. Det sker med hjälp av en ny typ av i realtid deformerbar spegel tillsammans med bildbehandling av kamerabilder från processen. För- och nackdelar med detta tillvägagångssätt undersöks.Beam shaping åstadkoms med hjälp av ny typ av deformerbart spegelsystem som integreras i en industriell processoptik. Tillsammans med en vågfrontsensor bildas ett adaptivt system för beam shaping med en svarstid på 10 ms. Processen övervakas av en kamera linjerad koaxialt med laserstrålen. För att kunna ta bilder av svetspunkten belyses den med ljus av lämplig våglängd, och kameran är försedd med ett motsvarande optiskt filter. Försök har utförts med svetsning utan tillsatsmaterial, direkt på plåtar, svetsning utan s.k. nyckelhål, för att förstå effekten av beam shaping på svetssmältans geometri. Gauss fördelade cirkulära och elliptiska former, långsträckta både tvärs och längs svetsriktningen har studerats. Bilder från svetssmältan har analyserats och även mikrostrukturen i tvärsnitt från de svetsade plåtarna. Resultaten visar att svetssmältans geometri kan modifieras signifikant genom beam shaping med hjälp av det deformerbara spegelsystemet. Genomträngningssvetsning av T-fogar med avvikelser relativt foglinjens centrum genomfördes för att studera potentialen i att använda maskininlärning för att fånga processens tillstånd. Resultaten visade att maskininlärning kan nå tillräcklig prestanda för detektering och skattning av denna avvikelse. Något som också kan användas för återkopplad styrning. Flerdimensionell processdata har samlats i realtid och analyserats med hjälp av bildbehandlingsmetoder.  Dessa data avslöjar brister i nuvarande simuleringsmodeller,vilket i sin tur hjälper till med att bättre förstå och styra lasersvetsning.Resultaten från detta arbete uppvisar en god potential i att använda de föreslagna metoderna för att lösa relevanta utmaningar inom lasersvetsning. / <p>Till licentiatuppsats hör 2 inskickade artiklar, som visas inte nu.</p>

Les dispositifs de protection de sites sensibles doivent permettre de détecter des menaces potentielles suffisamment à l’avance pour pouvoir mettre en place une stratégie de défense. Dans cette optique, les méthodes de détection et de reconnaissance d’aéronefs se basant sur des images infrarouge multispectrales doivent être adaptées à des images faiblement résolues et être robustes à la variabilité spectrale et spatiale des cibles. Nous mettons au point dans cette thèse, des méthodes statistiques de détection et de reconnaissance d’aéronefs satisfaisant ces contraintes. Tout d’abord, nous spécifions une méthode de détection d’anomalies pour des images multispectrales, combinant un calcul de vraisemblance spectrale avec une étude sur les ensembles de niveaux de la transformée de Mahalanobis de l’image. Cette méthode ne nécessite aucune information a priori sur les aéronefs et nous permet d’identifier les images contenant des cibles. Ces images sont ensuite considérées comme des réalisations d’un modèle statistique d’observations fluctuant spectralement et spatialement autour de formes caractéristiques inconnues. L’estimation des paramètres de ce modèle est réalisée par une nouvelle méthodologie d’apprentissage séquentiel non supervisé pour des modèles à données manquantes que nous avons développée. La mise au point de ce modèle nous permet in fine de proposer une méthode de reconnaissance de cibles basée sur l’estimateur du maximum de vraisemblance a posteriori. Les résultats encourageants, tant en détection qu’en classification, justifient l’intérêt du développement de dispositifs permettant l’acquisition d’images multispectrales. Ces méthodes nous ont également permis d’identifier les regroupements de bandes spectrales optimales pour la détection et la reconnaissance d’aéronefs faiblement résolus en infrarouge / Surveillance systems should be able to detect potential threats far ahead in order to put forward a defence strategy. In this context, detection and recognition methods making use of multispectral infrared images should cope with low resolution signals and handle both spectral and spatial variability of the targets. We introduce in this PhD thesis a novel statistical methodology to perform aircraft detection and classification which take into account these constraints. We first propose an anomaly detection method designed for multispectral images, which combines a spectral likelihood measure and a level set study of the image Mahalanobis transform. This technique allows to identify images which feature an anomaly without any prior knowledge on the target. In a second time, these images are used as realizations of a statistical model in which the observations are described as random spectral and spatial deformation of prototype shapes. The model inference, and in particular the prototype shape estimation, is achieved through a novel unsupervised sequential learning algorithm designed for missing data models. This model allows to propose a classification algorithm based on maximum a posteriori probability Promising results in detection as well as in classification, justify the growing interest surrounding the development of multispectral imaging devices. These methods have also allowed us to identify the optimal infrared spectral band regroupments regarding the low resolution aircraft IRS detection and classification

No description available.

Historically 3D game environments have almost always been immutable. Mutable environments are a technical challenge that will affect performance. For games of the future to continue approaching realism, mutable environments are an essential step. Popularized by the game title Minecraft (2009), the use of voxel engines in games has become increasingly common. However, by the nature of the discrete position of voxels, the method is limited in representing arbitrary polyhedral shapes like angled slopes. It also prohibits smooth mutations including proper movement and rotation of objects within the voxelization. This is generally mitigable with more voxels. However, this paper proposes a more precise solution to the problem. A tetrahedral mesh engine (tetra engine). By altering tetrahedral topology, vertex positions, and material of individual tetrahedrons, tetras are intended to solve the issue of arbitrary polyhedral shapes for voxels. Additionally, the tetrahedral mesh shows other promises such as providing a robust collision detection method and as an acceleration structure for e.g. raycasting. The research question can be summarized as investigating the feasibility of a tetra engine as a mutable game environment. 3 sub-research questions are given: The first regarding performance, the second regarding robustness, and the third different types mutations. The research questions are addressed along with a proof of concept (POC). The POC intends to investigate a proposal for the most efficient robust solution possible for the most basic mutation type known as edits. Because of time constraints, it does not cover all parts of the research questions but works as a bottom-up approach to understand what is required to realize a full-fledged tetra engine. Thus, a large part of the research question is answered theoretically both hypothetically with grounds from the POC and through previous work. The result shows a much more critical robustness consideration than expected and suggests relying on slower but more robust algorithms that are known to work. In conclusion, nothing suggests that a scalable future-proof tetra engine is impossible, but the algorithms required are much less efficient than those for voxels and robustness is an issue to overcome. However, numerous hypothetical advantages particularly regarding deformation and fluid simulation are still recognized and it is not obvious that future mutable environments would not benefit from a tetra engine rather than voxels. / Historiskt sätt har 3D-datorspelmiljöer nästan uteslutande varit oföränderliga. Det finns goda anledningar till detta. Föränderliga miljöer är en teknisk utmaning som påverkar speleffektiviteten. Om man däremot vill fortsätta utveckla mer realistiska datorspel är föränderliga spelmiljöer ett naturligt steg. Spelet Minecraft (2009) populariserade användandet av voxlar i datorspel vars material kan ändras för att förändra miljön. Sedan dess har voxlar i datorspel blivit mer och mer populära. Dock, på grund av voxlars diskreta positioner har de begränsningar i dess förmåga att representera godtyckliga polyedriska former så som arbiträrt vinklade plan. Detta omöjliggör även mjuka rörelser inklusive rörelse och rotering inom voxeliseringen. Det här problemet kan generellt dämpas med hjälp av mindre och fler voxlar. Men, för att lösa problemet ordentligt föreslår den här rapporten en annan lösning, nämligen en tetrahedrisk-mesh-motor (tetramotor). Genom att ändra tetraedrisk topologi, hörn positioner, samt material av individuella tetraedrar ska tetrorna kunna forma arbiträra polyedriska former och lösa problemet med voxlar. Utöver detta visar en tetraedrisk mesh andra intressanta möjligheter likt en metod för robust kollisions hantering och som en accelereringsstruktur för till exempel ray-casting. Forskningsfrågan kan sammanfattas som att utforska tillämpbarheten av en tetramotor för föränderliga datorspelsmiljöer. Tre underfrågor ges: Den första handlar om beräkningseffektivitet, den andra angående robusthet och den tredje oliky typer av mutationer. Forskningsfrågorna angrips med hjälp av en proof of concept lösning (POC). POC:en är menad att utforska ett förslag på en effektiv och robust metod för direkta förändringar. På grund av tidsbegränsningar så täcker inte POC:en alla delar av frågeställningarna men är menad som en botten upp lösning för att inse och förstå kraven för en komplett tetramotor. På grund av detta är en stor del av forskningsfrågorna svarade teoretiskt, både hypotetiskt baserat på insikterna från POC:en och med grund från tidigare forskning. Resultatet visar en mycket mer kritisk hänsyn till robusthet än förväntat och föreslår att man använder sig av långsammare men fungerande existerande lösningar. Slutsatsen är att inget tyder på att en skalbar framtidssäker tetramotor är en omöjlighet, men att algoritmerna är mycket långsammare än de som krävs för voxlar. Däremot finns potentieally fördelar med en tetra motor, främst med hänsyn till deformering och flödessimulering. Det är därför inte självklart att framtida muterbara spelmijöer inte skulle ha fördelar av en tetramotor istället för voxlar.

[pt] Esta dissertação introduz um simulador híbrido inovador que combina um resolvedor de Equações Diferenciais Parciais (EDP) numérico de Elementos Finitos (FE) com uma Rede Neural de Passagem de Mensagens (MPNN) para realizar simulações de dinâmicas de sólidos deformáveis em malhas pouco refinadas. Nosso trabalho visa fornecer simulações precisas com um erro comparável ao obtido com malhas mais refinadas em discretizações FE,mantendo a eficiência computacional ao usar um componente MPNN que corrige os erros numéricos associados ao uso de uma malha menos refinada. Avaliamos nosso modelo focando na precisão, capacidade de generalização e velocidade computacional em comparação com um solucionador numérico de referência que usa malhas 64 vezes mais refinadas. Introduzimos um novo conjunto de dados para essa comparação, abrangendo três casos de referência numéricos: (i) deformação livre após um impulso inicial, (ii) alongamento e (iii)torção de sólidos deformáveis. Baseado nos resultados de simulação, o estudo discute as forças e fraquezas do nosso método. O estudo mostra que nosso método corrige em média 95,4 por cento do erro numérico associado à discretização, sendo até 88 vezes mais rápido que o solucionador de referência. Além disso, nosso modelo é totalmente diferenciável em relaçao a funções de custo e pode ser incorporado em uma camada de rede neural, permitindo que seja facilmente estendido por trabalhos futuros. Dados e código estão disponíveis em https://github.com/Kerber31/fast_coarse_FEM para investigações futuras. / [en] This thesis introduces a novel hybrid simulator that combines a numerical Finite Element (FE) Partial Differential Equation solver with a Message Passing Neural Network (MPNN) to perform simulations of deformable solid dynamics on coarse meshes. Our work aims to provide accurate simulations with an error comparable to that obtained with more refined meshes in FE discretizations while maintaining computational efficiency by using an MPNN component that corrects the numerical errors associated with using a coarse mesh. We evaluate our model focusing on accuracy, generalization capacity, and computational speed compared to a reference numerical solver that uses 64 times more refined meshes. We introduce a new dataset for this comparison, encompassing three numerical benchmark cases: (i) free deformation after an initial impulse, (ii) stretching, and (iii) torsion of deformable solids. Based on simulation results, the study thoroughly discusses our method s strengths and weaknesses. The study shows that our method corrects an average of 95.4 percent of the numerical error associated with discretization while being up to 88 times faster than the reference solver. On top of that, our model is fully differentiable in relation to loss functions and can be embedded into a neural network layer, allowing it to be easily extended by future work. Data and code are made available on https://github.com/Kerber31/fast_coarse_FEM for further investigations.

This biomedical engineering thesis explores the opportunities and challenges of 2D+t contrast echocardiography for left ventricle functional analysis, both clinically and within a computer vision atlas-based deformable template model framework. A database was created for the experiments in this thesis, with 21 studies of contrast Dobutamine Stress Echo, in all 4 principal planes. The database includes clinical variables, human expert hand-traced myocardial contours and visual scoring. First the problem is studied from a clinical perspective. Quantification of endocardial global and local function using standard measures shows expected values and agreement with human expert visual scoring, but the results are less reliable for myocardial thickening. Next, the problem of segmenting the endocardium with a computer is posed in a standard landmark and atlas-based deformable template model framework. The underlying assumption is that these models can emulate human experts in terms of integrating previous knowledge about the anatomy and physiology with three sources of information from the image: texture, geometry and kinetics. Probabilistic atlases of contrast echocardiography are computed, while noting from histograms at selected anatomical locations that modelling texture with just mean intensity values may be too naive. Intensity analysis together with the clinical results above suggest that lack of external boundary definition may preclude this imaging technique for appropriate measuring of myocardial thickening, while endocardial boundary definition is appropriate for evaluation of wall motion. Geometry is presented in a Principal Component Analysis (PCA) context, highlighting issues about Gaussianity, the correlation and covariance matrices with respect to physiology, and analysing different measures of dimensionality. A popular extension of deformable models ---Active Appearance Models (AAMs)--- is then studied in depth. Contrary to common wisdom, it is contended that using a PCA texture space instead of a fixed atlas is detrimental to segmentation, and that PCA models are not convenient for texture modelling. To integrate kinetics, a novel spatio-temporal model of cardiac contours is proposed. The new explicit model does not require frame interpolation, and it is compared to previous implicit models in terms of approximation error when the shape vector changes from frame to frame or remains constant throughout the cardiac cycle. Finally, the 2D+t atlas-based deformable model segmentation problem is formulated and solved with a gradient descent approach. Experiments using the similarity transformation suggest that segmentation of the whole cardiac volume outperforms segmentation of individual frames. A relatively new approach ---the inverse compositional algorithm--- is shown to decrease running times of the classic Lucas-Kanade algorithm by a factor of 20 to 25, to values that are within real-time processing reach.