Le soudage hybride arc / laser représente une solution adéquate à l'assemblage de tôles d'acier de forte épaisseur. La présence d'une source laser en amont de la torche MIG permet d'accroître la productivité du procédé tout en assurant une excellente qualité de la soudure. Cependant la phénoménologie complexe de ce procédé multiphysique n'est pas encore totalement maîtrisée, ce qui motive le développement d'outils de simulation numérique. La présente étude s'est déroulée dans le cadre d'un projet multipartenaires "SISHYFE" (ANR Matériaux et Procédés).Dans ce but un modèle éléments finis 3D non stationnaire a été développé. Construit à partir de l'approche level set, il est en mesure de simuler un procédé multi-passes de soudage hybride arc / laser. Il a été développé autour de quatre principaux axes. (1) Une modélisation plus réaliste de l'apport de chaleur a conduit à la définition d'un nouveau modèle basé sur le rayonnement thermique pour décrire la source MIG. (2) Grâce au couplage entre l'intégration de termes source de matière et de chaleur dans les équations de conservation et l'actualisation de l'interface gaz / métal, le modèle proposé est capable de simuler le développement d'un cordon de soudure. (3) L'intégration d'une modélisation des écoulements du bain de fusion dans une approche level set a été évaluée et son impact sur la distribution thermique dans le métal analysé. (4) La simulation de la formation des contraintes pendant et après soudage a été possible grâce à l'adaptation d'un solveur thermomécanique.La modélisation finale a permis de simuler une configuration industrielle de soudage hybride arc / laser multi-passes. Des mesures expérimentales effectuées par les partenaires du projet "SISHYFE" ont été utilisées afin d'évaluer le modèle et d'éprouver sa capacité à reproduire l'expérience.

Reservoir characterization is one of the most important problems in petroleum engineering. It involves forward reservoir modeling that predicts the fluid behavior in the reservoir and inverse problem that calibrates created reservoir models with given data. In this dissertation, we focus on two problems in the field of reservoir characterization: depth of investigation in heterogeneous reservoirs, and history matching and uncertainty quantification of channelized reservoirs. The concept of depth of investigation is fundamental to well test analysis. Much of the current well test analysis relies on analytical solutions based on homogeneous or layered reservoirs. However, such analytic solutions are severely limited for heterogeneous and fractured reservoirs, particularly for unconventional reservoirs with multistage hydraulic fractures. We first generalize the concept to heterogeneous reservoirs and provide an efficient tool to calculate drainage volume using fast marching methods and estimate pressure depletion based on geometric pressure approximation. The applicability of proposed method is illustrated using two applications in unconventional reservoirs including flow regime visualization and stimulated reservoir volume estimation. Due to high permeability contrast and non-Gaussianity of channelized permeability field, it is difficult to history match and quantify uncertainty of channelized reservoirs using traditional approaches. We treat facies boundaries as level set functions and solve the moving boundary problem (history matching) with the level set equation. In addition to level set methods, we also exploit the problem using pixel based approach. The reversible jump Markov Chain Monte Carlo approach is utilized to search the parameter space with flexible dimensions. Both proposed approaches are demonstrated with two and three dimensional examples.

Techn. Hochsch., Diss.--Aachen, 2007.

Essen, University, Diss., 2005--Duisburg.

Changes in retinal structure are related to different eye diseases. Various retinal imaging techniques, such as fundus imaging and optical coherence tomography (OCT) imaging modalities, have been developed for non-intrusive ophthalmology diagnoses according to the vasculature changes. However, it is time consuming or even impossible for ophthalmologists to manually label all the retinal structures from fundus images and OCT images. Therefore, computer aided diagnosis system for retinal imaging plays an important role in the assessment of ophthalmologic diseases and cardiovascular disorders. The aim of this PhD thesis is to develop segmentation methods to extract clinically useful information from these retinal images, which are acquired from different imaging modalities. In other words, we built the segmentation methods to extract important structures from both 2D fundus images and 3D OCT images. In the first part of my PhD project, two novel level set based methods were proposed for detecting the blood vessels and optic discs from fundus images. The first one integrates Chan-Vese's energy minimizing active contour method with the edge constraint term and Gaussian Mixture Model based term for blood vessels segmentation, while the second method combines the edge constraint term, the distance regularisation term and the shape-prior term for locating the optic disc. Both methods include the pre-processing stage, used for removing noise and enhancing the contrast between the object and the background. Three automated layer segmentation methods were built for segmenting intra-retinal layers from 3D OCT macular and optic nerve head images in the second part of my PhD project. The first two methods combine different methods according to the data characteristics. First, eight boundaries of the intra-retinal layers were detected from the 3D OCT macular images and the thickness maps of the seven layers were produced. Second, four boundaries of the intra-retinal layers were located from 3D optic nerve head images and the thickness maps of the Retinal Nerve Fiber Layer (RNFL) were plotted. Finally, the choroidal layer segmentation method based on the Level Set framework was designed, which embedded with the distance regularisation term, edge constraint term and Markov Random Field modelled region term. The thickness map of the choroidal layer was calculated and shown.

abstract: Many physical phenomena and industrial applications involve multiphase fluid flows and hence it is of high importance to be able to simulate various aspects of these flows accurately. The Dynamic Contact Angles (DCA) and the contact lines at the wall boundaries are a couple of such important aspects. In the past few decades, many mathematical models were developed for predicting the contact angles of the inter-face with the wall boundary under various flow conditions. These models are used to incorporate the physics of DCA and contact line motion in numerical simulations using various interface capturing/tracking techniques. In the current thesis, a simple approach to incorporate the static and dynamic contact angle boundary conditions using the level set method is developed and implemented in multiphase CFD codes, LIT (Level set Interface Tracking) (Herrmann (2008)) and NGA (flow solver) (Desjardins et al (2008)). Various DCA models and associated boundary conditions are reviewed. In addition, numerical aspects such as the occurrence of a stress singularity at the contact lines and grid convergence of macroscopic interface shape are dealt with in the context of the level set approach. / Dissertation/Thesis / Masters Thesis Mechanical Engineering 2015

This thesis proposes a probabilistic level set method to be used in segmentation of tumors with heterogeneous intensities. It models the intensities of the tumor and surrounding tissue using Gaussian mixture models. Through a contour based initialization procedure samples are gathered to be used in expectation maximization of the mixture model parameters. The proposed method is compared against a threshold-based segmentation method using MRI images retrieved from The Cancer Imaging Archive. The cases are manually segmented and an automated testing procedure is used to find optimal parameters for the proposed method and then it is tested against the threshold-based method. Segmentation times, dice coefficients, and volume errors are compared. The evaluation reveals that the proposed method has a comparable mean segmentation time to the threshold-based method, and performs faster in cases where the volume error does not exceed 40%. The mean dice coefficient and volume error are also improved while achieving lower deviation.

CoordenaÃÃo de AperfeiÃoamento de Pessoal de NÃvel Superior / A identificaÃÃo correta do ventrÃculo esquerdo em imagens de ecocardiograma constitui uma importante ferramenta no auxÃlio ao diagnÃstico precoce de doenÃas cardiovasculares. No entanto, limitaÃÃes inerentes ao processo de aquisiÃÃo das imagens, como baixa relaÃÃo sinal-ruÃdo e presenÃa de sombras acÃsticas, tornam essa identificaÃÃo uma tarefa complexa. Neste trabalho, com o objetivo de segmentar o ventrÃculo esquerdo, contornos ativos geomÃtricos e paramÃtricos sÃo aplicados sobre imagens de ecocardiografia. Uma nova variaÃÃo dos contornos ativos paramÃtricos, o mÃtodo dos contornos ativos algÃbricos, e duas modalidades de mÃtodo level-set, uma baseada no gradiente e outra baseada em regiÃes, sÃo testadas e comparadas. SÃo propostas, neste trabalho, quatro contribuiÃÃes à literatura. Uma à a filtragem do Hamiltoniano por uma janela gaussiana a afim de acelerar o movimento do contorno. Outra à uma funÃÃo sinal, que permite que o contorno mude sua direÃÃo radial automaticamente. AlÃm disso, a prÃpria concepÃÃo do mÃtodo dos contornos ativos algÃbricos à uma das contribuiÃÃes. Finalmente, a ultima à a superposiÃÃo de mapas de contorno, que aumenta a Ãrea de influÃncia do contorno ativo sem perda de precisÃo. Conclui-se que, apesar da capacidade dos contornos ativos geomÃtricos de dividirem-se e unificarem-se independentemente de novas parametrizaÃÃes, o mÃtodo dos contornos ativos algÃbricos Ã, dentre os avaliados, o Ãnico capaz de realizar a segmentaÃÃo do ventrÃculo esquerdo nas imagens de ecocardiografia conforme o padrÃo-ouro fornecido pelos especialistas.

Locating and segmenting objects such as bones or internal organs is a common problem in medical imaging. Existing segmentation methods are often cumbersome to use for medical staff, since they require a close initial guess and a range of different parameters to be set appropriately. For this work, we present a two-stage segmentation framework which relies on an initial isosurface interactively extracted by topological analysis. The initial isosurface seldom provides a correct segmentation, so we refine the surface using an iterative level set method to better match the desired object boundary. We present applications and improvements to both the flexible isosurface interface and level set segmentation without edges.

We present a method for stable buildup of snow on surfaces of arbitrary topology and geometric complexity. This is achieved by tracing quantities of snow, so-called snow packages, through a dynamic wind field. Dual compact level sets are used to represent geometry as well as accumulated snow. The level sets have also proven to be well suited for the internal boundaries for our Navier-Stokes solver, which produces a wind field that changes according to snow buildup. Our method is different from previous work in that all the addition of snow is done by local operations, avoiding computationally expensive global refinement procedures. The main contribution of this work is a dual level set method for particle interaction with level sets.