No description available.

This dissertation consists of two parts, i.e. dynamic approaches for subgrid-scale (SGS) stress modelling for large eddy simulation and advanced assessment of the resolved scale motions related to turbulence geometrical statistics and topologies. The numerical simulations are based on turbulent Couette flow. The first part of the dissertation presents four contributions to the development of dynamic SGS models. The conventional integral type dynamic localization SGS model is in the form of a Fredholm integral equation of the second kind. This model is mathematically consistent, but demanding in computational cost. An efficient solution scheme has been developed to solve the integral system for turbulence with homogeneous dimensions. Current approaches to the dynamic two-parameter mixed model (DMM2) are mathematically inconsistent. As a second contribution, the DMM2 has been optimized and a modelling system of two integral equations has been rigorously obtained. The third contribution relates to the development of a novel dynamic localization procedure for the Smagorinsky model using the functional variational method. A sufficient and necessary condition for localization is obtained and a Picard's integral equation for the model coefficient is deduced. Finally, a new dynamic nonlinear SGS stress model (DNM) based on Speziale's quadratic constitutive relation [J. Fluid Mech., 178, p.459, 1987] is proposed. The DNM allows for a nonlinear anisotropic representation of the SGS stress, and exhibits a significant local stability and flexibility in self-calibration. In the second part, the invariant properties of the resolved velocity gradient tensor are studied using recently developed methodologies, i.e. turbulence geometrical statistics and topology. The study is a posteriori based on the proposed DNM, which is different than most of the current a priori approaches based on experimental or DNS databases. The performance of the DNM is further validated in terms of its capability of simulating advanced geometrical and topological features of resolved scale motions. Phenomenological results include, e.g. the positively skewed resolved enstrophy generation, the alignment between the vorticity and vortex stretching vectors, and the pear-shape joint probability function contour in the tensorial invariant phase plane. The wall anisotropic effect on these results is also examined.

This dissertation consists of two parts, i.e. dynamic approaches for subgrid-scale (SGS) stress modelling for large eddy simulation and advanced assessment of the resolved scale motions related to turbulence geometrical statistics and topologies. The numerical simulations are based on turbulent Couette flow. The first part of the dissertation presents four contributions to the development of dynamic SGS models. The conventional integral type dynamic localization SGS model is in the form of a Fredholm integral equation of the second kind. This model is mathematically consistent, but demanding in computational cost. An efficient solution scheme has been developed to solve the integral system for turbulence with homogeneous dimensions. Current approaches to the dynamic two-parameter mixed model (DMM2) are mathematically inconsistent. As a second contribution, the DMM2 has been optimized and a modelling system of two integral equations has been rigorously obtained. The third contribution relates to the development of a novel dynamic localization procedure for the Smagorinsky model using the functional variational method. A sufficient and necessary condition for localization is obtained and a Picard's integral equation for the model coefficient is deduced. Finally, a new dynamic nonlinear SGS stress model (DNM) based on Speziale's quadratic constitutive relation [J. Fluid Mech., 178, p.459, 1987] is proposed. The DNM allows for a nonlinear anisotropic representation of the SGS stress, and exhibits a significant local stability and flexibility in self-calibration. In the second part, the invariant properties of the resolved velocity gradient tensor are studied using recently developed methodologies, i.e. turbulence geometrical statistics and topology. The study is a posteriori based on the proposed DNM, which is different than most of the current a priori approaches based on experimental or DNS databases. The performance of the DNM is further validated in terms of its capability of simulating advanced geometrical and topological features of resolved scale motions. Phenomenological results include, e.g. the positively skewed resolved enstrophy generation, the alignment between the vorticity and vortex stretching vectors, and the pear-shape joint probability function contour in the tensorial invariant phase plane. The wall anisotropic effect on these results is also examined.

京都大学 / 0048 / 新制・論文博士 / 博士(理学) / 乙第13108号 / 論理博第1556号 / 新制||理||1620(附属図書館) / (主査)准教授 重 尚一, 教授 余田 成男, 教授 石川 裕彦 / 学位規則第4条第2項該当 / Doctor of Science / Kyoto University / DGAM

The aim of the present study is to develop subgrid-scale models that are relevant for complex flows and combustion. A stochastic model based on a stochastic Smagorinsky constant with adjustable variance and time scale is proposed. The stochastic model is shown to provide for backscatter of both kinetic energy and scalar variance without causing numerical instabilities. A new subgrid-scale scalar flux model is developed using the same kind of methodology that leads to the explicit algebraic scalar flux model, EASFM, for RANS. The new model predicts the anisotropy of the subgrid-scales in a more realistic way than the eddy diffusion model. Both new models were tested in rotating homogeneous shear flow with a passive scalar. Rogallo’s method of moving the frame with the mean flow to enable periodic boundary conditions was used to simulate homogeneous shear flow. / QC 20101119

No description available.

This thesis is concerned with the numerical simulation of high Reynolds number, three-dimensional, incompressible flows in open domains. Many problems treated in Computational Fluid Dynamics (CFD) occur in free space: e.g., external aerodynamics past vehicles, bluff bodies or aircraft; shear flows such as shear layers or jets. In observing all these flows, we can remark that they are often unsteady, appear chaotic with the presence of a large range of eddies, and are mainly dominated by convection. For years, it was shown that Lagrangian Vortex Element Methods (VEM) are particularly well appropriate for simulating such flows. In VEM, two approaches are classically used for solving the Poisson equation. The first one is the Biot-Savart approach where the Poisson equation is solved using the Green's function approach. The unbounded domain is thus implicitly taken into account. In that case, Parallel Fast Multipole (PFM) solvers are usually used. The second approach is the Vortex-In-Cell (VIC) method where the Poisson equation is solved on a grid using fast grid solvers. This requires to impose boundary conditions or to assume periodicity. An important difference is that fast grid solvers are much faster than fast multipole solvers. We here combine these two approaches by taking the advantages of each one and, eventually, we obtain an efficient VIC-PFM method to solve incompressible flows in open domain. The major interest of this combination is its computational efficiency: compared to the PFM solver used alone, the VIC-PFM combination is 15 to 20 times faster. The second major advantage is the possibility to run Large Eddy Simulations (LES) at high Reynolds number. Indeed, as a part of the operations are done in an Eulerian way (i.e. on the VIC grid), all the existing subgrid scale (SGS) models used in classical Eulerian codes, including the recent "multiscale" models, can be easily implemented.

This thesis is concerned with the numerical simulation of high Reynolds number, three-dimensional, incompressible flows in open domains. Many problems treated in Computational Fluid Dynamics (CFD) occur in free space: e.g., external aerodynamics past vehicles, bluff bodies or aircraft; shear flows such as shear layers or jets. In observing all these flows, we can remark that they are often unsteady, appear chaotic with the presence of a large range of eddies, and are mainly dominated by convection. For years, it was shown that Lagrangian Vortex Element Methods (VEM) are particularly well appropriate for simulating such flows. In VEM, two approaches are classically used for solving the Poisson equation. The first one is the Biot-Savart approach where the Poisson equation is solved using the Green's function approach. The unbounded domain is thus implicitly taken into account. In that case, Parallel Fast Multipole (PFM) solvers are usually used. The second approach is the Vortex-In-Cell (VIC) method where the Poisson equation is solved on a grid using fast grid solvers. This requires to impose boundary conditions or to assume periodicity. An important difference is that fast grid solvers are much faster than fast multipole solvers. We here combine these two approaches by taking the advantages of each one and, eventually, we obtain an efficient VIC-PFM method to solve incompressible flows in open domain. The major interest of this combination is its computational efficiency: compared to the PFM solver used alone, the VIC-PFM combination is 15 to 20 times faster. The second major advantage is the possibility to run Large Eddy Simulations (LES) at high Reynolds number. Indeed, as a part of the operations are done in an Eulerian way (i.e. on the VIC grid), all the existing subgrid scale (SGS) models used in classical Eulerian codes, including the recent "multiscale" models, can be easily implemented.

The objective of this thesis is to study the evolution of scalar field carried by a flow from a temporal image sequence. The estimation of the velocity field of turbulent flow is of major importance for understanding the physical phenomenon. Up to now the problem of turbulence is generally ignored in the flow equation of existing methods. An information given by image is discrete at pixel size. Depending on the turbulent rate of the flow, pixel and time resolutions may become too large to neglect the effect of sub-pixel small-scales on the pixel velocity field. For this, we propose a flow equation defined by a filtered concentration transport equation where a classic turbulent sub-grid eddy viscosity model is introduced in order to account for this effect. To formulate the problem, we use a Markovian approach. An unwarping multiresolution by pyramidal decomposition is proposed which reduces the number of operations on images. The optimization coupled with a multigrid approach allows to estimate the optimal 2D real velocity field. Our approach is tested on synthetic andreal image sequences (PIV laboratory experiment and remote sensing data of dust storm event) with high Reynolds number. Comparisons with existing approaches are very promising.

L’objectif de cette thèse est l’étude de l’évolution de champ scalaire transporté par un écoulement à partir d’une séquence d’images temporelles. L’estimation du champ de vitesse d’un écoulement turbulent est d’une importance majeure pour mieux comprendre le phénomène physique. Jusqu’à présent, le problème de la turbulence est généralement ignoré dans l’équation de mouvement des méthodes existantes. Les images contiennent une information discrète correspondant à la taille du pixel. Selon le niveau de turbulence de l’écoulement, les résolutions des pixels et du temps peuvent devenir trop grandes pour négliger l’effet des petites échelles (sous-pixel) sur le champ de vitesse. Nous proposons pour cela, une équation de mouvement définie par l’équation de transport de concentration filtrée pour laquelle un modèle classique de viscosité turbulente sous-maille est introduit afin de tenir compte de cet effet. Nous utilisons pour formuler le problème, une approche Markovienne. Une méthode de multirésolution par décomposition pyramidale, sans transformation d’image intermédiaire au cours du processus, est proposée. Cela permet de diminuer le nombre d’opérations sur les images. La méthode d’optimisation utilisée, couplée avec une approche multigrille, permet d’obtenir le champ de vitesse réel optimal. Notre approche est testée sur des séquences d’images synthétiques et réelles (expérience PIV et tempête de sable à partir d’image de télédétection) avec des nombres de Reynolds élevés. Les comparaisons avec des approches existantes sont très prometteuses. / The objective of this thesis is to study the evolution of scalar field carried by a flow from a temporal image sequence. The estimation of the velocity field of turbulent flow is of major importance for understanding the physical phenomenon. Up to now the problem of turbulence is generally ignored in the flow equation of existing methods. An information given by image is discrete at pixel size. Depending on the turbulent rate of the flow, pixel and time resolutions may become too large to neglect the effect of sub-pixel small-scales on the pixel velocity field. For this, we propose a flow equation defined by a filtered concentration transport equation where a classic turbulent sub-grid eddy viscosity model is introduced in order to account for this effect. To formulate the problem, we use a Markovian approach. An unwarping multiresolution by pyramidal decomposition is proposed which reduces the number of operations on images. The optimization coupled with a multigrid approach allows to estimate the optimal 2D real velocity field. Our approach is tested on synthetic andreal image sequences (PIV laboratory experiment and remote sensing data of dust storm event) with high Reynolds number. Comparisons with existing approaches are very promising.