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Subfilter scalar variance is a key quantity for scalar mixing at the small scales of a turbulent flow and thus plays a crucial role in large eddy simulation (LES) of combustion. While prior studies have mainly focused on the physical aspects of modeling subfilter variance, the current work discusses variance models in conjunction with numerical errors due to their implementation using finite difference methods. Because of the prevalence of grid-based filtering in practical LES, the smallest filtered scales are generally under-resolved. These scales, however, are often important in determining the values of subfilter models. A priori tests on data from direct numerical simulation (DNS) of homogenous isotropic turbulence are performed to evaluate the numerical implications of specific model forms in the context of practical LES evaluated with finite differences. As with other subfilter quantities, such as kinetic energy, subfilter variance can be modeled according to one of two general methodologies. In the first of these, an algebraic equation relating the variance to gradients of the filtered scalar field is coupled with a dynamic procedure for coefficient estimation. Although finite difference methods substantially underpredict the gradient of the filtered scalar field, the dynamic method is shown to mitigate this error through overestimation of the model coefficient. The second group of models utilizes a transport equation for the subfilter variance itself or for the second moment of the scalar. Here, it is shown that the model formulation based on the variance transport equation is consistently biased toward underprediction of the subfilter variance. The numerical issues stem from making discrete approximations to the chain rule manipulations used to derive convective and diffusive terms in the variance transport equation associated with the square of the filtered scalar. This set of approximations can be avoided by solving the equation for the second moment of the scalar, suggesting that model's numerical superiority. / text

The choice of reference frames used in simulations is typically fixed in dynamic models based on modeling decisions made early during their development, restricting model fidelity, numerical accuracy and integration into large-scale simulations. Individual simulation components typically need to model the transformations between multiple reference frames in order to interact with other components, resulting in additional development effort, time and cost. This dissertation describes the methods for defining and managing different reference frames in a simulation, thereby creating a shared simulation environment that can provide reference frame transformations, comprising of kinematics and rotations, to all simulation components through a Reference Frame Manager. Simulation components can use this Reference Frame Manager to handle all kinematics and rotations when interacting with components using different reference frames, improving the interoperability of simulation components, especially in parallel and distributed simulation, while reducing their development time, effort and cost. The Reference Frame Manager also facilitates the development of Generic Dynamic Models that encapsulate the core service of dynamic model, enabling the rapid development of dynamic models that can be reused and reconfigured for different simulation scenarios and requirements. The Reference Frame Manager can also be used to introduce Intermediate Frames that bound the magnitudes of vehicle states, reducing roundoff error and improving numerical accuracy.

Computational fluid dynamics (CFD) simulations can provide tremendous insight into complex physical processes and are often faster and more cost-effective to execute than experiments. However, each CFD result inherently contains numerical errors that can significantly degrade the accuracy of a simulation. Discretization error is typically the largest contributor to the overall numerical error in a given simulation. Discretization error can be very difficult to estimate since the generation, transport, and diffusion of these errors is a highly nonlinear function of the computational grid and discretization scheme. As CFD is increasingly used in engineering design and analysis, it is imperative that CFD practitioners be able to accurately quantify discretization errors to minimize risk and improve the performance of engineering systems. In this work, improvements are made to the accuracy and efficiency of existing error estimation techniques. Discretization error is estimated by deriving and solving an error transport equation (ETE) for the local discretization error everywhere in the computational domain. Truncation error is shown to act as the local source for discretization error in numerical solutions. An equivalence between adjoint methods and ETE methods for functional error estimation is presented. This adjoint/ETE equivalence is exploited to efficiently obtain error estimates for multiple output functionals and to extend the higher-order properties of adjoint methods to ETE methods. Higher-order discretization error estimates are obtained when truncation error estimates are sufficiently accurate. Truncation error estimates are demonstrated to deteriorate on grids with a non-smooth variation in grid metrics (e.g., unstructured grids) regardless of how smooth the underlying exact solution may be. The loss of accuracy is shown to stem from noise in the discrete solution on the order of discretization error. When using conventional least-squares reconstruction techniques, this noise is exactly captured and introduces a lower-order error into the truncation error estimate. A novel reconstruction method based on polyharmonic smoothing splines is developed to smoothly reconstruct the discrete solution and improve the accuracy of error estimates. Furthermore, a method for iteratively improving discretization error estimates is devised. Efficiency and robustness considerations are discussed. Results are presented for several inviscid and viscous flow problems. To facilitate the study of discretization error estimation, a new, higher-order finite-volume solver is developed. A detailed description of the code base is provided along with a discussion of best practices for CFD code design. / Ph. D. / Computational fluid dynamics (CFD) is a branch of computational physics at the intersection of fluid mechanics and scientific computing in which the governing equations of fluid motion, such as the Euler and Navier-Stokes equations, are solved numerically on a computer. CFD is utilized in numerous fields including biomedical engineering, meteorology, oceanography, and aerospace engineering. CFD simulations can provide tremendous insight into physical processes and are often preferred over experiments because they can be performed more quickly, are typically more cost-effective, and can provide data in regions where it may be difficult to measure. While CFD can be an extremely powerful tool, CFD simulations are inherently subject to numerical errors. These errors, which are generated when the governing equations of fluid motion are solved on a computer, can have a significant impact on the accuracy of a CFD solution. If numerical errors are not accurately quantified, ill-informed decision-making can lead to poor system performance, increased risk of injury, or even system failure. In this work, research efforts are focused on numerical error estimation for the finite -volume method, arguably the most widely used numerical algorithm for solving CFD problems. The error estimation techniques provided herein target discretization error, the largest contributor to the overall numerical error in a given simulation. Discretization error can be very difficult to estimate since these errors are generated, convected, and diffused by the same physical processes embedded in the governing equations. In this work, improvements are made to the accuracy and efficiency of existing discretization error estimation techniques. Results are presented for several inviscid and viscous flow problems. To facilitate the study of these error estimators, a new, higher-order finite -volume solver is developed. A detailed description of the code base is provided along with a discussion of best practices for CFD code design.

As análises de erros são conduzidas antes de qualquer projeto a ser desenvolvido. A necessidade do conhecimento do comportamento do erro numérico em malhas estruturadas e não-estruturadas surge com o aumento do uso destas malhas nos métodos de discretização. Desta forma, o objetivo deste trabalho foi criar uma metodologia para analisar os erros de discretização gerados através do truncamento na Série de Taylor, aplicados às equações de Poisson e de Advecção-Difusão estacionárias uni e bidimensionais, utilizando-se o Método de Volumes Finitos em malhas do tipo Voronoi. A escolha dessas equações se dá devido a sua grande utilização em testes de novos modelos matemáticos e função de interpolação. Foram usados os esquemas Central Difference Scheme (CDS) e Upwind Difference Scheme(UDS) nos termos advectivos. Verificou-se a influência do tipo de condição de contorno e a posição do ponto gerador do volume na solução numérica. Os resultados analíticos foram confrontados com resultados experimentais para dois tipos de malhas de Voronoi, uma malha cartesiana e outra triangular comprovando a influência da forma do volume finito na solução numérica obtida. Foi percebido no estudo que a discretização usando o esquema CDS tem erros menores do que a discretização usando o esquema UDS conforme literatura. Também se percebe a diferença nos erros em volumes vizinhos nas malhas triangulares o que faz com que não se tenha uma uniformidade nos gráficos dos erros estudados. Percebeu-se que as malhas cartesianas com nó no centróide do volume tem menor erro de discretização do que malhas triangulares. Mas o uso deste tipo de malha depende da geometria do problema estudado / The analyses of errors are conducted before any project to be developed. The necessity of studying the behavior of the numerical error on structured and unstructured grids comes up with the increasing use of these methods of discretization meshes. Thus, the objective was to create a methodology to analyze the errors generated by discretization of the truncation in the Taylor series, applied to the equations of Poisson and Advection-Diffusion stationary and uni and bi-dimensional, using the Finite Volume Method on Voronoi mesh. The choice of these equations is due to its wide use in testing new mathematical models and interpolation function. The schemes used were the Central Difference Scheme (CDS) and the Upwind Difference Scheme (UDS) in the advective terms. There was the influence of boundary condition and position of the generator in the numerical solution of the volume. The analytical results were compared with experimental results for two types of Voronoi meshes, a Cartesian mesh and a triangular shape showing the influence of finite volume in the numerical solution obtained. It was perceived that the discretization in the study using the CDS scheme has smaller errors than the discretization scheme using the UDS as literature. Also notice the difference in the errors in neighboring volumes in triangular meshes which means that there has been no uniformity in the graphs of errors studied. It was noticed that the Cartesian meshes with node at the centroid of the volume is smaller than discretization error triangular meshes. But using this type of meshes depends on the geometry of the problem studied

As análises de erros são conduzidas antes de qualquer projeto a ser desenvolvido. A necessidade do conhecimento do comportamento do erro numérico em malhas estruturadas e não-estruturadas surge com o aumento do uso destas malhas nos métodos de discretização. Desta forma, o objetivo deste trabalho foi criar uma metodologia para analisar os erros de discretização gerados através do truncamento na Série de Taylor, aplicados às equações de Poisson e de Advecção-Difusão estacionárias uni e bidimensionais, utilizando-se o Método de Volumes Finitos em malhas do tipo Voronoi. A escolha dessas equações se dá devido a sua grande utilização em testes de novos modelos matemáticos e função de interpolação. Foram usados os esquemas Central Difference Scheme (CDS) e Upwind Difference Scheme(UDS) nos termos advectivos. Verificou-se a influência do tipo de condição de contorno e a posição do ponto gerador do volume na solução numérica. Os resultados analíticos foram confrontados com resultados experimentais para dois tipos de malhas de Voronoi, uma malha cartesiana e outra triangular comprovando a influência da forma do volume finito na solução numérica obtida. Foi percebido no estudo que a discretização usando o esquema CDS tem erros menores do que a discretização usando o esquema UDS conforme literatura. Também se percebe a diferença nos erros em volumes vizinhos nas malhas triangulares o que faz com que não se tenha uma uniformidade nos gráficos dos erros estudados. Percebeu-se que as malhas cartesianas com nó no centróide do volume tem menor erro de discretização do que malhas triangulares. Mas o uso deste tipo de malha depende da geometria do problema estudado / The analyses of errors are conducted before any project to be developed. The necessity of studying the behavior of the numerical error on structured and unstructured grids comes up with the increasing use of these methods of discretization meshes. Thus, the objective was to create a methodology to analyze the errors generated by discretization of the truncation in the Taylor series, applied to the equations of Poisson and Advection-Diffusion stationary and uni and bi-dimensional, using the Finite Volume Method on Voronoi mesh. The choice of these equations is due to its wide use in testing new mathematical models and interpolation function. The schemes used were the Central Difference Scheme (CDS) and the Upwind Difference Scheme (UDS) in the advective terms. There was the influence of boundary condition and position of the generator in the numerical solution of the volume. The analytical results were compared with experimental results for two types of Voronoi meshes, a Cartesian mesh and a triangular shape showing the influence of finite volume in the numerical solution obtained. It was perceived that the discretization in the study using the CDS scheme has smaller errors than the discretization scheme using the UDS as literature. Also notice the difference in the errors in neighboring volumes in triangular meshes which means that there has been no uniformity in the graphs of errors studied. It was noticed that the Cartesian meshes with node at the centroid of the volume is smaller than discretization error triangular meshes. But using this type of meshes depends on the geometry of the problem studied

L’arithmétique virgule flottante est une approximation de l’arithmétique réelle dans laquelle chaque opération peut introduire une erreur. La norme IEEE 754 requiert que les opérations élémentaires soient aussi précises que possible, mais au cours d’un calcul, les erreurs d’arrondi s’accumulent et peuvent conduire à des résultats totalement faussés. Cela arrive avec une expression aussi simple que ab + cd, pour laquelle l’algorithme naïf retourne parfois un résultat aberrant, avec une erreur relative largement supérieure à 1. Il est donc important d’analyser les algorithmes utilisés pour contrôler l’erreur commise. Je m’intéresse à l’analyse de briques élémentaires du calcul en cherchant des bornes fines sur l’erreur relative. Pour des algorithmes suffisamment précis, en arithmétique de base β et de précision p, on arrive en général à prouver une borne sur l'erreur de la forme α·u + o(u²) où α > 0 et u = 1/2·β1-p est l'unité d'arrondi. Comme indication de la finesse d'une telle borne, on peut fournir des exemples numériques pour les précisions standards qui approchent cette borne, ou bien un exemple paramétré par la précision qui génère une erreur de la forme α·u + o(u²), prouvant ainsi l'optimalité asymptotique de la borne. J’ai travaillé sur la formalisation d’une arithmétique à virgule flottante symbolique, sur des nombres paramétrés par la précision, et à son implantation dans le logiciel de calcul formel Maple. J’ai aussi obtenu une borne d'erreur très fine pour un algorithme d’inversion complexe en arithmétique flottante. Ce résultat suggère le calcul d'une division décrit par la formule x/y = (1/y)·x, par opposition à x/y = (x·y)/|y|². Quel que soit l'algorithme utilisé pour effectuer la multiplication, nous avons une borne d'erreur plus petite pour les algorithmes décrits par la première formule. Ces travaux sont réalisés avec mes directeurs de thèse, en collaboration avec Claude-Pierre Jeannerod (CR Inria dans AriC, au LIP). / Floating-point arithmetic is an approximation of real arithmetic in which each operation may introduce a rounding error. The IEEE 754 standard requires elementary operations to be as accurate as possible. However, through a computation, rounding errors may accumulate and lead to totally wrong results. It happens for example with an expression as simple as ab + cd for which the naive algorithm sometimes returns a result with a relative error larger than 1. Thus, it is important to analyze algorithms in floating-point arithmetic to understand as thoroughly as possible the generated error. In this thesis, we are interested in the analysis of small building blocks of numerical computing, for which we look for sharp error bounds on the relative error. For this kind of building blocks, in base and precision p, we often successfully prove error bounds of the form α·u + o(u²) where α > 0 and u = 1/2·β1-p is the unit roundoff. To characterize the sharpness of such a bound, one can provide numerical examples for the standard precisions that are close to the bound, or examples that are parametrized by the precision and generate an error of the same form α·u + o(u²), thus proving the asymptotic optimality of the bound. However, the paper and pencil checking of such parametrized examples is a tedious and error-prone task. We worked on the formalization of a symbolicfloating-point arithmetic, over numbers that are parametrized by the precision, and implemented it as a library in the Maple computer algebra system. We also worked on the error analysis of the basic operations for complex numbers in floating-point arithmetic. We proved a very sharp error bound for an algorithm for the inversion of a complex number in floating-point arithmetic. This result suggests that the computation of a complex division according to x/y = (1/y)·x may be preferred, instead of the more classical formula x/y = (x·y)/|y|². Indeed, for any complex multiplication algorithm, the error bound is smaller with the algorithms described by the “inverse and multiply” approach.This is a joint work with my PhD advisors, with the collaboration of Claude-Pierre Jeannerod (CR Inria in AriC, at LIP).

Since the last few years, the unprecedented growth of communication systems involving the propagation of electromagnetic waves is particularly due to developments in mobile phone technology. The reverberation chamber is a reliable bench-test, enabling the study of the effects of electromagnetic waves on a specific electronic appliance. However, the operating of a reverberation chamber being rather complicated, development of numerical models are of utmost importance to determine the crucial parameters to be considered.This thesis consists in the modelling and the simulation of the operating principles of a reverberation chamber by means of the Finite-Difference Time-Domain method. After a brief study based on field and power measurements performed in a reverberation chamber, the second chapter deals with the different problems encountered during the modelling. The consideration of losses being a very important factor in the operating of the chamber, two methods of implementation of these losses are set out in this chapter. Chapter~3 consists in the analysis of the influence of the stirrer on the first eigenmodes of the chamber; the latter modes can undergo a frequency shift of several MHz. Chapter~4 shows a comparison of results issued from high frequency simulations and theoretical statistical results. The problem of an object placed in the chamber, resulting in a field disturbance is also tackled. Finally, in the fifth chapter, a comparison of statistical results for stirrers having different shapes is set out.