In this paper we study a methodology for the numerical simulation of stable structures of fluid membranes and vesicles in biological organisms. In particular, we discuss the effects of spontaneous curvature on vesicle cell membranes under the bending energy for given volume and surface area. The geometric modeling of the vesicle shapes are undertaken by means of surfaces generated as Partial Differential Equations (PDEs). We combine PDE based geometric modeling with numerical optimization in order to study the stable shapes adopted by the vesicle membranes. Thus, through the PDE method we generate a generic template of a vesicle membrane which is then efficiently parameterized. The parameterization is taken as a basis to set up a numerical optimization procedure which enables us to predict a series of vesicle shapes subject to given surface area and volume.

Yes / An important issue in many of today's biometric applications is the development of efficient and accurate techniques for representing related 3D data. Such data is often available through the process of digitization of complex geometric objects which are of importance to biometric applications. For example, in the area of 3D face recognition a digital point cloud of data corresponding to a given face is usually provided by a 3D digital scanner. For efficient data storage and for identification/authentication in a timely fashion such data requires to be represented using a few parameters or variables which are meaningful. Here we show how mathematical techniques based on Partial Differential Equations (PDEs) can be utilized to represent complex 3D data where the data can be parameterized in an efficient way. For example, in the case of a 3D face we show how it can be represented using PDEs whereby a handful of key facial parameters can be identified for efficient storage and verification.

Yes

We present immersed discontinuous Galerkin finite element methods for one and two dimensional acoustic wave propagation problems in inhomogeneous media where elements are allowed to be cut by the material interface. The proposed methods use the standard discontinuous Galerkin finite element formulation with polynomial approximation on elements that contain one fluid while on interface elements containing more than one fluid they use specially-built piecewise polynomial shape functions that satisfy appropriate interface jump conditions. The finite element spaces on interface elements satisfy physical interface conditions from the acoustic problem in addition to extended conditions derived from the system of partial differential equations. Additional curl-free and consistency conditions are added to generate bilinear and biquadratic piecewise shape functions for two dimensional problems. We established the existence and uniqueness of one dimensional immersed finite element shape functions and existence of two dimensional bilinear immersed finite element shape functions for the velocity. The proposed methods are tested on one dimensional problems and are extended to two dimensional problems where the problem is defined on a domain split by an interface into two different media. Our methods exhibit optimal $O(h^{p+1})$ convergence rates for one and two dimensional problems. However it is observed that one of the proposed methods is not stable for two dimensional interface problems with high contrast media such as water/air. We performed an analysis to prove that our immersed Petrov-Galerkin method is stable for interface problems with high jumps across the interface. Local time-stepping and parallel algorithms are used to speed up computation. Several realistic interface problems such as ether/glycerol, water/methyl-alcohol and water/air with a circular interface are solved to show the stability and robustness of our methods. / Ph. D.

Cette thèse concerne le problème de désocclusion d'images, au moyen des équations aux dérivées partielles. Dans la première partie de la thèse, la désocclusion est modélisée par un problème de Cauchy qui consiste à déterminer une solution d'une équation aux dérivées partielles avec des données aux bords accessibles seulement sur une partie du bord de la partie à recouvrir. Ensuite, on a utilisé des algorithmes de minimisation issus de la théorie des jeux, pour résoudre ce problème de Cauchy. La deuxième partie de la thèse est consacrée au choix des paramètres de régularisation pour des EDP d'ordre deux et d'ordre quatre. L'approche développée consiste à construire une famille de problèmes d'optimisation bien posés où les paramètres sont choisis comme étant une fonction variable en espace. Ceci permet de prendre en compte les différents détails, à différents échelles dans l'image. L'apport de la méthode est de résoudre de façon satisfaisante et objective, le choix du paramètre de régularisation en se basant sur des indicateurs d'erreur et donc le caractère à posteriori de la méthode (i.e. indépendant de la solution exacte, en générale inconnue). En outre, elle fait appel à des techniques classiques d'adaptation de maillage, qui rendent peu coûteuses les calculs numériques. En plus, un des aspects attractif de cette méthode, en traitement d'images est la récupération et la détection de contours et de structures fines. / Image inpainting refers to the process of restoring a damaged image with missing information. Different mathematical approaches were suggested to deal with this problem. In particular, partial differential diffusion equations are extensively used. The underlying idea of PDE-based approaches is to fill-in damaged regions with available information from their surroundings. The first purpose of this Thesis is to treat the case where this information is not available in a part of the boundary of the damaged region. We formulate the inpainting problem as a nonlinear boundary inverse problem for incomplete images. Then, we give a Nash-game formulation of this Cauchy problem and we present different numerical which show the efficiency of the proposed approach as an inpainting method.Typically, inpainting is an ill-posed inverse problem for it most of PDEs approaches are obtained from minimization of regularized energies, in the context of Tikhonov regularization. The second part of the thesis is devoted to the choice of regularization parameters in second-and fourth-order energy-based models with the aim of obtaining as far as possible fine features of the initial image, e.g., (corners, edges, … ) in the inpainted region. We introduce a family of regularized functionals with regularization parameters to be selected locally, adaptively and in a posteriori way allowing to change locally the initial model. We also draw connections between the proposed method and the Mumford-Shah functional. An important feature of the proposed method is that the investigated PDEs are easy to discretize and the overall adaptive approach is easy to implement numerically.

We study the equilibrium solutions of an integrodifferential equation used to model one-dimensional biological swarms. We assume that the motion of the swarm is governed by pairwise interactions, or a convolution in the continuous setting, and derive a continuous model from conservation laws. The steady-state solution found for the model is compactly supported and is shown to be an attractive equilibrium solution via linear perturbation theory. Numerical simulations support that the steady-state solution is attractive for all initial swarm distributions. Some initial results for the model in higher dimensions are also presented.

We consider a variational formulation of a Bernoulli-type free boundary problem for the Laplacian operator with discontinuous boundary data. We show the existence of a weak solution to the problem. Moreover, we show that the solution has symmetry properties inherited by symmetric data. These results are achieved through the use of comparison arguments, the celebrated method of moving planes, and several elaborated techniques from existing literature. / Vi studerar ett Bernoulli frirandsproblem för Laplaceoperatorn med diskontinuerliga randdata. Detta görs via en variationsformulering av problemet. Vi visar att en svag lösning existerar för problemet. Utöver det visar vi bland annat att den svaga lösningen har symmetriegenskaper. Dessa resultat uppnås genom jämförelseargument, den välkända "moving-plane” metoden, samt flera utarbetade tekniker från befintlig litteratur.

Thesis (MSc)--Stellenbosch University, 2011. / ENGLISH ABSTRACT: In several numerical approaches to PDEs shifted linear systems of the form (zI - A)x = b, need to be solved for several values of the complex scalar z. Often, these linear systems are large and sparse. This thesis investigates efficient numerical methods for these systems that arise from a contour integral approximation to PDEs and compares these methods with direct solvers. In the first part, we present three model PDEs and discuss numerical approaches to solve them. We use the first problem to demonstrate computations with a dense matrix, the second problem to demonstrate computations with a sparse symmetric matrix and the third problem for a sparse but nonsymmetric matrix. To solve the model PDEs numerically we apply two space discrerization methods, namely the finite difference method and the Chebyshev collocation method. The contour integral method mentioned above is used to integrate with respect to the time variable. In the second part, we study a Hessenberg reduction method for solving shifted linear systems with a dense matrix and present numerical comparison of it with the built-in direct linear system solver in SciPy. Since both are direct methods, in the absence of roundoff errors, they give the same result. However, we find that the Hessenberg reduction method is more efficient in CPU-time than the direct solver. As application we solve a one-dimensional version of the heat equation. In the third part, we present efficient techniques for solving shifted systems with a sparse matrix by Krylov subspace methods. Because of their shift-invariance property, the Krylov methods allow one to obtain approximate solutions for all values of the parameter, by generating a single approximation space. Krylov methods applied to the linear systems are generally slowly convergent and hence preconditioning is necessary to improve the convergence. The use of shift-invert preconditioning is discussed and numerical comparisons with a direct sparse solver are presented. As an application we solve a two-dimensional version of the heat equation with and without a convection term. Our numerical experiments show that the preconditioned Krylov methods are efficient in both computational time and memory space as compared to the direct sparse solver. / AFRIKAANSE OPSOMMING: In verskeie numeriese metodes vir PDVs moet geskuifde lineêre stelsels van die vorm (zI − A)x = b, opgelos word vir verskeie waardes van die komplekse skalaar z. Hierdie stelsels is dikwels groot en yl. Hierdie tesis ondersoek numeriese metodes vir sulke stelsels wat voorkom in kontoerintegraalbenaderings vir PDVs en vergelyk hierdie metodes met direkte metodes vir oplossing. In die eerste gedeelte beskou ons drie model PDVs en bespreek numeriese benaderings om hulle op te los. Die eerste probleem word gebruik om berekenings met ’n vol matriks te demonstreer, die tweede probleem word gebruik om berekenings met yl, simmetriese matrikse te demonstreer en die derde probleem vir yl, onsimmetriese matrikse. Om die model PDVs numeries op te los beskou ons twee ruimte-diskretisasie metodes, naamlik die eindige-verskilmetode en die Chebyshev kollokasie-metode. Die kontoerintegraalmetode waarna hierbo verwys is word gebruik om met betrekking tot die tydveranderlike te integreer. In die tweede gedeelte bestudeer ons ’n Hessenberg ontbindingsmetode om geskuifde lineêre stelsels met ’n vol matriks op te los, en ons rapporteer numeriese vergelykings daarvan met die ingeboude direkte oplosser vir lineêre stelsels in SciPy. Aangesien beide metodes direk is lewer hulle dieselfde resultate in die afwesigheid van afrondingsfoute. Ons het egter bevind dat die Hessenberg ontbindingsmetode meer effektief is in terme van rekenaartyd in vergelyking met die direkte oplosser. As toepassing los ons ’n een-dimensionele weergawe van die hittevergelyking op. In die derde gedeelte beskou ons effektiewe tegnieke om geskuifde stelsels met ’n yl matriks op te los, met Krylov subruimte-metodes. As gevolg van hul skuifinvariansie eienskap, laat die Krylov metodes mens toe om benaderde oplossings te verkry vir alle waardes van die parameter, deur slegs een benaderingsruimte voort te bring. Krylov metodes toegepas op lineêre stelsels is in die algemeen stadig konvergerend, en gevolglik is prekondisionering nodig om die konvergensie te verbeter. Die gebruik van prekondisionering gebasseer op skuif-en-omkeer word bespreek en numeriese vergelykings met direkte oplossers word aangebied. As toepassing los ons ’n twee-dimensionele weergawe van die hittevergelyking op, met ’n konveksie term en daarsonder. Ons numeriese eksperimente dui aan dat die Krylov metodes met prekondisionering effektief is, beide in terme van berekeningstyd en rekenaargeheue, in vergelyking met die direkte metodes.

Les systèmes de réaction-diffusion interviennent pour décrire les transitions de phase dans de nombreux champs d'application. Cette thèse porte sur l'analyse mathématique de modèles de propagation dans des milieux diffusifs, non bornés et hétérogènes, et s'inscrit ainsi dans la lignée d'une recherche particulièrement active. La première partie concerne l'équation simple: on s'y intéressera à la structure interne des fronts, mais on exhibera aussi de nouvelles dynamiques où la vitesse d'un profil de propagation n'est pas unique. Dans la seconde partie, on s'intéresse aux systèmes à deux équations, pour lesquels l'absence de principe du maximum pose de nombreuses difficultés. Ces travaux, en portant sur un vaste éventail de situations, offrent une meilleure compréhension des phénomènes de propagation, et mettent en avant de nouvelles propriétés des problèmes de réaction-diffusion, aidant ainsi à améliorer l'analyse théorique comme alternative à l'approche empirique. / Reaction-diffusion systems arise in the description of phase transitions in various fields of natural sciences. This thesis is concerned with the mathematical analysis of propagation models in some diffusive, unbounded and heterogeneous media, which comes within the scope of an active research subject. The first part deals with the single equation, by looking at the inside structure of fronts, or by exhibiting new dynamics where the profile of propagation may not have a unique speed. In a second part, we take interest in some systems of two equations, where the lack of maximum principles raises many theoretical issues. Those works aim to provide a better understanding of the underlying processes of propagation phenomena. They highlight new features for reaction-diffusion problems, some of them not known before, and hence help to improve the theoretical approach as an alternative to empirical analysis.

L’analyse de sensibilité (AS) concerne la quantification des changements dans la solution d’un système d’équations aux dérivées partielles (EDP) dus aux varia- tions des paramètres d’entrée du modèle. Les techniques standard d’AS pour les EDP, comme la méthode d’équation de sensibilité continue, requirent de dériver la variable d’état. Cependant, dans le cas d’équations hyperboliques l’état peut présenter des dis- continuités, qui donc génèrent des Dirac dans la sensibilité. Le but de ce travail est de modifier les équations de sensibilité pour obtenir un syst‘eme valable même dans le cas discontinu et obtenir des sensibilités qui ne présentent pas de Dirac. Ceci est motivé par plusieurs raisons : d’abord, un Dirac ne peut pas être saisi numériquement, ce qui pourvoit une solution incorrecte de la sensibilité au voisinage de la discontinuité ; deuxièmement, les pics dans la solution numérique des équations de sensibilité non cor- rigées rendent ces sensibilités inutilisables pour certaines applications. Par conséquent, nous ajoutons un terme de correction aux équations de sensibilité. Nous faisons cela pour une hiérarchie de modèles de complexité croissante : de l’équation de Burgers non visqueuse au système d’Euler quasi-1D. Nous montrons l’influence de ce terme de correction sur un problème d’optimisation et sur un de quantification d’incertitude. / Sensitivity analysis (SA) concerns the quantification of changes in Partial Differential Equations (PDEs) solution due to perturbations in the model input. Stan- dard SA techniques for PDEs, such as the continuous sensitivity equation method, rely on the differentiation of the state variable. However, if the governing equations are hyperbolic PDEs, the state can exhibit discontinuities yielding Dirac delta functions in the sensitivity. We aim at modifying the sensitivity equations to obtain a solution without delta functions. This is motivated by several reasons: firstly, a Dirac delta function cannot be seized numerically, leading to an incorrect solution for the sensi- tivity in the neighbourhood of the state discontinuity; secondly, the spikes appearing in the numerical solution of the original sensitivity equations make such sensitivities unusable for some applications. Therefore, we add a correction term to the sensitivity equations. We do this for a hierarchy of models of increasing complexity: starting from the inviscid Burgers’ equation, to the quasi 1D Euler system. We show the influence of such correction term on an optimization algorithm and on an uncertainty quantification problem.