Modelling in cardiac electrophysiology results in a complex system of partial differential equations (PDE) describing the propagation of the electrical wave in the heart muscle coupled with a highly nonlinear system of ordinary differential equations (ODE) describing the ionic activity in the cardiac cells. This system forms the widely accepted bidomain model or its slightly simpler version, the monodomain model. To a large extent, the stiffness of the whole model depends on the choice of the ionic model, which varies in terms of complexity and realism. These simulations require accurate and, depending on the ionic model used, possibly very stable numerical methods. At this time, solving these models numerically requires CPU time of around one day per heartbeat. Therefore, it is necessary to use the most efficient method for these simulations. This research focuses on the comparison and analysis of several time-stepping methods: explicit or semi-implicit, operator splitting, deferred correction and Rush-Larsen methods. The goal is to find the optimal method for the ionic model used. For our analysis, we used the monodomain model but our results apply to the bidomain model as well. We compare the methods for three ionic models of varying complexity and stiffness: the Mitchell-Schaeffer models with only 2 variables, the more realistic Beeler-Reuter model with 8 variables, and the stiff and very complex ten Tuscher-Noble-Noble-Panfilov (TNNP) models with 17 variables. For each method, we derived absolute stability criteria of the spatially discretized monodomain model and verified that the theoretical critical time steps obtained closely match the ones in numerical experiments. Convergence tests were also conducted to verify that the numerical methods achieve an optimal order of convergence on the model variables and derived quantities (such as speed of the wave, depolarization time), and this in spite of the local non-differentiability of some of the ionic models. We looked at the efficiency of the different methods by comparing computational times for similar accuracy. Conclusions are drawn on the methods to be used to solve the monodomain model based on the model stiffness and complexity, measured respectively by the most negative eigenvalue of the model's Jacobian and the number of variables, and based on strict stability and accuracy criteria.

Partial differential equations (PDEs) and stochastic partial differential equations (SPDEs) are powerful tools in modeling real-world phenomena in many fields such as geo-engineering. For instance processes such as oil or gas recovery from hydrocarbon reservoirs and mining heat from geothermal reservoirs can be modeled by PDEs or SPDEs. An important task is to understand the behavior of such phenomena. This can be achieved through explicit solutions of equations. Since explicit solutions of many PDEs and SPDEs are rarely known, developing numerical schemes is a good alternative to provide approximations of these explicit solutions. The study of numerical solutions of PDEs and SPDEs is therefore an active research area and has attracted a lot of attentions since at least two decades. The aims of this dissertation is to develop numerical schemes to approximate semilinear parabolic PDEs and SPDEs in space and in time. The approximation in space is done via the standard Galerkin finite element method and the approximation in time, which is the core of our work is done via various numerical integrators. This dissertation consists of two general parts. The first part of this thesis deals with autonomous PDEs and SPDEs. Here, our main interest is on semilinear PDEs and SPDEs where the nonlinear part is stronger than the linear part also called (stochastic) reactive dominated transport equations, or stiff problems. For such problems, many numerical techniques in the current scientific literature lose their good stability properties. We develop a new explicit exponential integrator (called exponential Rosenbrock-type method) and a new semi-implicit method (called linear implicit Rosenbrock-type method), appropriate for such PDEs and SPDEs. We analyze the strong convergence of our novel fully discrete schemes towards the mild solution of the (S)PDE and obtain convergence orders similar to existing ones in the literature. The second part of this thesis focuses on numerical approximations of semilinear non-autonomous parabolic PDEs and SPDEs. Such equations are more realistic than the autonomous ones and find applications in many fields such as fluid mechanics, quantum field theory, electromagnetism, etc. Numerics of non-autonomous semilinear parabolic PDEs and SPDEs are far from being well understood in the literature. We fill that gap in this thesis by developing a new exponential integrator (called Magnus-type method) and the semi-implicit method for such problems and provide their strong convergence towards the mild solution. Moreover, for both autonomous and non-autonomous SPDEs driven by additive noise, we achieve optimal convergence order in time 1 or approximately 1. Numerical simulations are provided to illustrate our theoretical findings in both autonomous and non-autonomous cases.

Este é o primeiro trabalho que apresenta simulações tridimensionais completamente adaptativas de um modelo de campo de fase para um fluido incompressível com densidade de massa constante e viscosidade variável, conhecido como Modelo H. Solucionando numericamente as equações desse modelo em malhas refinadas localmente com a técnica AMR, simulamos computacionalmente escoamentos bifásicos tridimensionais. Os modelos de campo de fase oferecem uma aproximação física sistemática para investigar fenômenos que envolvem sistemas multifásicos complexos, tais como fluidos com camadas de mistura, a separação de fases sob forças de cisalhamento e a evolução de micro-estruturas durante processos de solidificação. Como as interfaces são substituídas por delgadas regiões de transição (interfaces difusivas), as simulações de campo de fase requerem muita resolução nessas regiões para capturar corretamente a física do problema em estudo. Porém essa não é uma tarefa fácil de ser executada numericamente. As equações que caracterizam o modelo de campo de fase contêm derivadas de ordem elevada e intrincados termos não lineares, o que exige uma estratégia numérica eficiente capaz de fornecer precisão tanto no tempo quanto no espaço, especialmente em três dimensões. Para obter a resolução exigida no tempo, usamos uma discretização semi-implícita de segunda ordem para solucionar as equações acopladas de Cahn-Hilliard e Navier-Stokes (Modelo H). Para resolver adequadamente as escalas físicas relevantes no espaço, utilizamos malhas refinadas localmente que se adaptam dinamicamente para recobrir as regiões de interesse do escoamento, como por exemplo, as vizinhanças das interfaces do fluido. Demonstramos a eficiência e a robustez de nossa metodologia com simulações que incluem a separação dos componentes de uma mistura bifásica, a deformação de gotas sob cisalhamento e as instabilidades de Kelvin-Helmholtz. / This is the first work that introduces 3D fully adaptive simulations for a phase field model of an incompressible fluid with matched densities and variable viscosity, known as Model H. Solving numerically the equations of this model in meshes locally refined with AMR technique, we simulate computationally tridimensional two-phase flows. Phase field models offer a systematic physical approach to investigate complex multiphase systems phenomena such as fluid mixing layers, phase separation under shear and microstructure evolution during solidification processes. As interfaces are replaced by thin transition regions (diffuse interfaces), phase field simulations need great resolution in these regions to capture correctly the physics of the studied problem. However, this is not an easy task to do numerically. Phase field model equations have high order derivatives and intricate nonlinear terms, which require an efficient numerical strategy that can achieve accuracy both in time and in space, especially in three dimensions. To obtain the required resolution in time, we employ a semi-implicit second order discretization scheme to solve the coupled Cahn-Hilliard/Navier-Stokes equations (Model H). To resolve adequatly the relevant physical scales in space, we use locally refined meshes which adapt dynamically to cover special flow regions, e.g., the vicinity of the fluid interfaces. We demonstrate the efficiency and robustness of our methodology with simulations that include spinodal decomposition, the deformation of drops under shear and Kelvin-Helmholtz instabilities.

Este é o primeiro trabalho que apresenta simulações tridimensionais completamente adaptativas de um modelo de campo de fase para um fluido incompressível com densidade de massa constante e viscosidade variável, conhecido como Modelo H. Solucionando numericamente as equações desse modelo em malhas refinadas localmente com a técnica AMR, simulamos computacionalmente escoamentos bifásicos tridimensionais. Os modelos de campo de fase oferecem uma aproximação física sistemática para investigar fenômenos que envolvem sistemas multifásicos complexos, tais como fluidos com camadas de mistura, a separação de fases sob forças de cisalhamento e a evolução de micro-estruturas durante processos de solidificação. Como as interfaces são substituídas por delgadas regiões de transição (interfaces difusivas), as simulações de campo de fase requerem muita resolução nessas regiões para capturar corretamente a física do problema em estudo. Porém essa não é uma tarefa fácil de ser executada numericamente. As equações que caracterizam o modelo de campo de fase contêm derivadas de ordem elevada e intrincados termos não lineares, o que exige uma estratégia numérica eficiente capaz de fornecer precisão tanto no tempo quanto no espaço, especialmente em três dimensões. Para obter a resolução exigida no tempo, usamos uma discretização semi-implícita de segunda ordem para solucionar as equações acopladas de Cahn-Hilliard e Navier-Stokes (Modelo H). Para resolver adequadamente as escalas físicas relevantes no espaço, utilizamos malhas refinadas localmente que se adaptam dinamicamente para recobrir as regiões de interesse do escoamento, como por exemplo, as vizinhanças das interfaces do fluido. Demonstramos a eficiência e a robustez de nossa metodologia com simulações que incluem a separação dos componentes de uma mistura bifásica, a deformação de gotas sob cisalhamento e as instabilidades de Kelvin-Helmholtz. / This is the first work that introduces 3D fully adaptive simulations for a phase field model of an incompressible fluid with matched densities and variable viscosity, known as Model H. Solving numerically the equations of this model in meshes locally refined with AMR technique, we simulate computationally tridimensional two-phase flows. Phase field models offer a systematic physical approach to investigate complex multiphase systems phenomena such as fluid mixing layers, phase separation under shear and microstructure evolution during solidification processes. As interfaces are replaced by thin transition regions (diffuse interfaces), phase field simulations need great resolution in these regions to capture correctly the physics of the studied problem. However, this is not an easy task to do numerically. Phase field model equations have high order derivatives and intricate nonlinear terms, which require an efficient numerical strategy that can achieve accuracy both in time and in space, especially in three dimensions. To obtain the required resolution in time, we employ a semi-implicit second order discretization scheme to solve the coupled Cahn-Hilliard/Navier-Stokes equations (Model H). To resolve adequatly the relevant physical scales in space, we use locally refined meshes which adapt dynamically to cover special flow regions, e.g., the vicinity of the fluid interfaces. We demonstrate the efficiency and robustness of our methodology with simulations that include spinodal decomposition, the deformation of drops under shear and Kelvin-Helmholtz instabilities.

L'amélioration du code Emedge3D (code de bord électromagnétique) est abordée sous plusieurs axes. Premier axe, des innovations sur les méthodes numériques ont été mises en oeuvre. L'avantage des méthodes de type semi-implicite est décrit, leur stabilité inconditionnelle permet l'augmentation du pas de temps, et donc la diminution du nombre d'itérations temporelles requises pour une simulation. Les avantages de la montée en ordre en espace et en temps sont détaillés. Deuxième axe, des réponses sont proposées pour la parallélisation du code. Le cadre de cette étude est proche du problème général d'advection-diffusion non linéaire. Les parties coûteuses ont tout d'abord été optimisées séquentiellement puis fait l'objet d'une parallélisation OpenMP. Pour la partie du code la plus sensible aux contraintes de bande passante mémoire, une solution parallèle MPI sur machine à mémoire distribuée est décrite et analysée. Une bonne extensibilité est observée jusque 384 cœurs. Cette thèse s'inscrit dans le projet interdisciplinaire ANR E2T2 (CEA/IRFM, Université Aix-Marseille/PIIM, Université Strasbourg/Icube). / The main goal of this work is to significantly reduce the computational cost of the scientific application Emedge3D, simulating the edge of tokamaks. Improvements to this code are made on two axes. First, innovations on numerical methods have been implemented. The advantage of semi-implicit time schemes are described. Their inconditional stability allows to consider larger timestep values, and hence to lower the number of temporal iteration required for a simulation. The benefits of a high order (time and space) are also presented. Second, solutions to the parallelization of the code are proposed. This study addresses the more general non linear advection-diffusion problem. The hot spots of the application have been sequentially optimized and parallelized with OpenMP. Then, a hybrid MPI OpenMP parallel algorithm for the memory bound part of the code is described and analyzed. Good scalings are observed up to 384 cores. This Ph. D. thesis is part of the interdisciplinary project ANR E2T2 (CEA/IRFM, University of Aix-Marseille/PIIM, University of Strasbourg/ICube).