The objective of this PhD research programme is to investigate the effectiveness of a finite volume method incorporating radial basis functions for simulating nonlinear transport processes. The finite volume method is the favoured numerical technique for solving the advection-diffusion equations that arise in transport simulation. The method transforms the original problem into a system of nonlinear, algebraic equations through the process of discretisation. The accuracy of this discretisation determines to a large extent the accuracy of the final solution. A new method of discretisation is presented that employs radial basis functions (rbfs) as a means of local interpolation. When combined with Gaussian quadrature integration methods, the resulting finite volume discretisation leads to accurate numerical solutions without the need for very fine meshes, and the additional overheads they entail. The resulting nonlinear, algebraic system is solved efficiently using a Jacobian-free Newton-Krylov method. By employing the new method as an extension of existing shape function-based approaches, the number of nonlinear iterations required to obtain convergence can be reduced. Furthermore, information obtained from these iterations can be used to increase the efficiency of subsequent rbf-based iterations, as well as to construct an effective parallel reconditioner to further reduce the number of nonlinear iterations required. Results are presented that demonstrate the improved accuracy offered by the new method when applied to several test problems. By successively refining the meshes, it is also possible to demonstrate the increased order of the new method, when compared to a traditional shape function basedmethod. Comparing the resources required for both methods reveals that the new approach can be many times more efficient at producing a solution of a given accuracy.

This thesis develops theoretical and computational methods for the robustness analysis of uncertain systems. The considered systems are linearized and depend rationally on random parameters with an associated probability distribution. The uncertainty is tackled by applying a polynomial chaos expansion (PCE), a series expansion for random variables similar to the well-known Fourier series for periodic time signals. We consider the linear perturbations around a system's operating point, i.e., reference trajectory, both from a probabilistic and worst-case point of view. A chief contribution is the polynomial chaos series expansion of uncertain linear systems in linear fractional representation (LFR). This leads to significant computational benefits when analyzing the probabilistic perturbations around a system's reference trajectory. The series expansion of uncertain interconnections in LFR further delivers important theoretical insights. For instance, it is shown that the PCE of rational parameter-dependent linear systems in LFR is equivalent to applying Gaussian quadrature for numerical integration. We further approximate the worst-case performance of uncertain linear systems with respect to quadratic performance metrics. This is achieved by approximately solving the underlying parametric Riccati differential equation after applying a polynomial chaos series expansion. The utility of the proposed probabilistic robustness analysis is demonstrated on the example of an industry-sized autolanding system for an Airbus A330 aircraft. Mean and standard deviation of the stochastic perturbations are quantified efficiently by applying a PCE to a linearization of the system along the nominal approach trajectory. Random uncertainty in the aerodynamic coefficients and mass parameters are considered, as well as atmospheric turbulence and static wind shear. The approximate worst-case analysis is compared with Monte Carlo simulations of the complete nonlinear model. The methods proposed throughout the thesis rapidly provide analysis results in good agreement with the Monte Carlo benchmark, at reduced computational cost.

Indiana University-Purdue University Indianapolis (IUPUI) / Joint models of longitudinal and survival outcomes have been used with increasing frequency in clinical investigations. Correct specification of fixed and random effects, as well as their functional forms is essential for practical data analysis. However, no existing methods have been developed to meet this need in a joint model setting. In this dissertation, I describe a penalized likelihood-based method with adaptive least absolute shrinkage and selection operator (ALASSO) penalty functions for model selection. By reparameterizing variance components through a Cholesky decomposition, I introduce a penalty function of group shrinkage; the penalized likelihood is approximated by Gaussian quadrature and optimized by an EM algorithm. The functional forms of the independent effects are determined through a procedure for structural discovery. Specifically, I first construct the model by penalized cubic B-spline and then decompose the B-spline to linear and nonlinear elements by spectral decomposition. The decomposition represents the model in a mixed-effects model format, and I then use the mixed-effects variable selection method to perform structural discovery. Simulation studies show excellent performance. A clinical application is described to illustrate the use of the proposed methods, and the analytical results demonstrate the usefulness of the methods.

Les calculs d'équilibres à triphasiques et quadriphasiques sont au cœur des simulations de réservoirs impliquant des processus de récupérations tertiaires. Dans les procédés d'injection de gaz ou de vapeur, le système huile-gaz est enrichi d'une nouvelle phase qui joue un rôle important dans la récupération de l'huile en place. Les calculs d'équilibres représentent la majeure partie des temps de calculs dans les simulations de réservoir compositionnelles où les routines thermodynamiques sont appelées un nombre conséquent de fois. Il est donc important de concevoir des algorithmes qui soient fiables, robustes et rapides. Dans la littérature peu de simulateurs basés sur des équations d'état sont applicables aux procédés de récupération thermique. A notre connaissance, il n'existe pas de simulation thermique complètement compositionnelle de ces procédés pour des cas d'applications aux huiles lourdes. Ces simulations apparaissent essentielles et pourraient offrir des outils améliorés pour l’étude prédictive de certains champs. Dans cette thèse, des algorithmes robustes et efficaces de calculs d’équilibre multiphasiques sont proposés permettant de surmonter les difficultés rencontrés durant les simulations d'injection de vapeur pour des huiles lourdes. La plupart des algorithmes d'équilibre de phases sont basés sur la méthode de Newton et utilisent les variables conventionnelles comme variables indépendantes. Dans un premier temps, des améliorations de ces algorithmes sont proposées. Les variables réduites permettent de réduire la dimensionnalité du système de nc (nombre de composants) dans le cas des variables conventionnelles, à M (M<<nc), et sont déjà utilisées dans certains simulateurs de réservoirs commerciaux. La méthode de réduction proposée par Nichita and Graciaa (Fluid Phase Equil. 302 (2011) 226-233) est étendue à l'analyse de stabilité et aux calculs d'équilibres multiphasiques. A l'inverse des précédentes méthodes de réduction, les variables ne sont pas bornées. La méthode de Newton nécessite une Hessienne définie positive pour pouvoir être utilisée. D'autres méthodes de minimisations sont testées permettant de s'affranchir de cette contrainte; les méthodes Quasi-Newton et Trust-Region qui garantissent une direction de descente à chaque itération. Ces dernières présentent un grand intérêt puisqu'elles permettent de réaliser des pas supra-linéaires (même lorsque la Hessienne n'est pas définie positive) et quadratiques (Trust-Region) ou proches de quadratiques (Quasi-Newton) dans le cas contraire. Un nouveau vecteur de variables indépendantes est proposé (construit afin d'obtenir une meilleure mise échelle du problème) et utilisé au sein d'un algorithme BFGS modifié. De même, une méthode de Trust-Region est développée pour les problèmes de tests de stabilités et d'équilibres multiphasiques. Ensuite, considérant le fluide comme semi-continu, une méthodologie basée sur une procédure de quadrature Gaussienne est proposée pour calculer mathématiquement les pseudo-composants capables de représenter le comportement du fluide. La méthodologie peut être vue comme une procédure de groupement/dégroupement, applicable pour tout nombre de points de quadratures et toute composition de mélange. Dans une dernière partie, un algorithme général pour le calcul d’équilibre multiphasique est présenté incluant tous les algorithmes développés. Ce dernier est testé et validé contre des données expérimentales et de la littérature. Des simulations triphasiques et quadriphasiques d'injection de CO2 démontrent la capacité du programme à traiter un nombre arbitraire de phases. Des simulations de balayages par la vapeur sont réalisées pour des réservoirs montrant d'importantes hétérogénéités. Finalement, une simulation complètement compositionnelle du processus de Steam Assisted Gravity Drainage est réalisée. A notre connaissance, il s'agit de la première simulation de la sorte pour des cas d'applications d'huiles lourdes. / Three to four phase equilibrium calculations are in the heart of tertiary recovery simulations. In gas/steam injection processes, additional phases emerging from the oil-gas system are added to the set and have a significant impact on the oil recovery. The most important computational effort in many chemical process simulators and in petroleum compositional reservoir simulations is required by phase equilibrium and thermodynamic property calculations. In field scale reservoir simulations, a huge number of phase equilibrium calculations is required. For all these reasons, the algorithms must be robust and time-saving. In the literature, few simulators based on equations of state (EoS) are applicable to thermal recovery processes such as steam injection. To the best of our knowledge, no fully compositional thermal simulation of the steam injection process has been proposed with extra-heavy oils; these simulations are essential and will offer improved tools for predictive studies of the heavy oil fields. Thus, in this thesis different algorithms of improved efficiency and robustness for multiphase equilibrium calculations are proposed, able to handle conditions encountered during the simulation of steam injection for heavy oil mixtures. Most of the phase equilibrium calculations are based on the Newton method and use conventional independent variables. These algorithms are first investigated and different improvements are proposed. Michelsen’s (Fluid Phase Equil. 9 (1982) 21-40) method for multiphase-split problems is modified to take full advantage of symmetry (in the construction of the Jacobian matrix and the resolution of the linear system). The reduction methods enable to reduce the space of study from nc (number of components) for conventional variables to M (M<<nc) and are already used in some commercial reservoir simulators. The reduction method proposed by Nichita and Graciaa (Fluid Phase Equil. 302 (2011) 226-233) is extended to phase stability analysis and multiphase-split calculations. Unlike previous reduction methods, the set of variables is unbounded and the convergence path is the same as in conventional methods using the logarithm of equilibrium constants as variables. The Newton method requires a positive definite Hessian for convergence. Other kinds of minimization methods are investigated which overcome this constraint; the Quasi-Newton and Trust-region methods always guarantee a descent direction. These methods represent an interesting alternative since they can reach supra-linear steps even when the Hessian is non-positive definite, and can reach quadratic steps (Trust-Region) or nearly quadratic steps (Quasi-Newton) otherwise. A new set of independent variables is proposed (designed to ensure a better scaling of the problem) for a modified BFGS (which ensures the positive definiteness of the approximation of the Hessian matrix) algorithm and a Trust-Region method is also proposed for the stability-testing and phase-split problems. Subsequently, by assuming the fluid composition as semi-continuous, a methodology based on a Gaussian quadrature is proposed to mathematically compute a set of pseudo-components capable of representing the fluid behavior. The methodology can be seen as a lumping-delumping procedure, applicable to any number of quadrature points and to any feed distribution. In a last part, a general multiphase flash procedure implementing all the developed algorithms is presented, and tested against experimental and literature data. Three- and four phase CO2 injection simulations demonstrate the capability of the program to handle any number of phases. Simulations of steam flooding are performed for highly heterogeneous reservoirs. Finally, a fully compositional simulation of the steam assisted gravity drainage process is realized. To the best of our knowledge, this is the first simulation of the kind for heavy oil mixtures.

This thesis compares Weibull weakest link theory with inclusion of one and all three principal stresses. Principal stresses needed for this theory were calculated with finite element method. The informational research is in the introduction of this thesis. It includes ceramic materials, Weibull weakest link theory, Gaussian quadrature over spherical surface and ceramic head of hip joint endoprothesis. Theoretical part is used for next calculations of probability of failure. The probability of failure of ceramic rod loaded by four-point bending is calculated in first calculations. This task is solved as contact in the next step. Next part of this thesis is about selection of suitable method of numerical integration. This method will be used in the calculation with all three principal stresses. The results of calculation with all three principal stresses are compared with the results of the calculation which includes only first principal stress. Firstly, this is done for cylindrical body and then used on head of hip joint endoprothesis. In the last part of this thesis, probability of fracture of head hip joint endoprothesis with shape deviation of nominal conicity is calculated.