365 research outputs found

    Hybrid mimetic finite-difference and virtual element formulation for coupled poromechanics

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    We present a hybrid mimetic finite-difference and virtual element formulation for coupled single-phase poromechanics on unstructured meshes. The key advantage of the scheme is that it is convergent on complex meshes containing highly distorted cells with arbitrary shapes. We use a local pressure-jump stabilization method based on unstructured macro-elements to prevent the development of spurious pressure modes in incompressible problems approaching undrained conditions. A scalable linear solution strategy is obtained using a block-triangular preconditioner designed specifically for the saddle-point systems arising from the proposed discretization. The accuracy and efficiency of our approach are demonstrated numerically on two-dimensional benchmark problems.Comment: 25 pages, 17 figure

    The integrated space-time finite volume method

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    Reconstructed discontinuous Galerkin methods for high Reynolds number flows

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    Reconstructed Discontinuous Galerkin (rDG) methods aim to provide a unified framework between Discontinuous Galerkin (DG) and finite volume (FV) methods. This unification leads to a new family of spatial discretization schemes from order three upwards. The first of these new schemes is the rDG(P1P2) method, which represents the solution on each element as linear functions while reconstructing quadratic contributions to compute the fluxes inside the element and over the faces. For the rDG(P1P2) method, two different reconstruction methods were implemented. The first of these reconstruction methods is a least-squares based reconstruction. For this reconstruction, an inverse distance weighting was introduced to improve the discretization error in anisotropic mesh regions, as well as an extended reconstruction stencil variant, which aims to stabilise the reconstruction on simplicial meshes. The inclusion of an inverse distance weighting was found to be beneficial for high Reynolds number flows on the example of the two-dimensional zero pressure gradient flat plate. As a second method, a variational reconstruction method was implemented. For the variational reconstruction rDG methods it was shown that they can offer significantly reduced discretization errors compared to DG methods for smooth flows. It was shown on the example of a method of manufactured solutions, that all implemented methods reach their designed order of accuracy and can provide lower spatial discretization errors than a DG method of a comparable order on regular and randomly perturbed hexahedral meshes as well as on tetrahedral meshes. The rDG methods was applied to several two and three-dimensional RANS test cases. For these test cases, a stronger influence of the Reynolds number on the discretization error of rDG methods was found compared to the weaker influence observed for DG methods. For all test-cases, it was shown that rDG methods converge faster on the same mesh, however, yield a higher absolute error, due to the lower number of degrees of freedom compared to native DG methods

    Arbitrary-Lagrangian-Eulerian discontinuous Galerkin schemes with a posteriori subcell finite volume limiting on moving unstructured meshes

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    We present a new family of high order accurate fully discrete one-step Discontinuous Galerkin (DG) finite element schemes on moving unstructured meshes for the solution of nonlinear hyperbolic PDE in multiple space dimensions, which may also include parabolic terms in order to model dissipative transport processes. High order piecewise polynomials are adopted to represent the discrete solution at each time level and within each spatial control volume of the computational grid, while high order of accuracy in time is achieved by the ADER approach. In our algorithm the spatial mesh configuration can be defined in two different ways: either by an isoparametric approach that generates curved control volumes, or by a piecewise linear decomposition of each spatial control volume into simplex sub-elements. Our numerical method belongs to the category of direct Arbitrary-Lagrangian-Eulerian (ALE) schemes, where a space-time conservation formulation of the governing PDE system is considered and which already takes into account the new grid geometry directly during the computation of the numerical fluxes. Our new Lagrangian-type DG scheme adopts the novel a posteriori sub-cell finite volume limiter method, in which the validity of the candidate solution produced in each cell by an unlimited ADER-DG scheme is verified against a set of physical and numerical detection criteria. Those cells which do not satisfy all of the above criteria are flagged as troubled cells and are recomputed with a second order TVD finite volume scheme. The numerical convergence rates of the new ALE ADER-DG schemes are studied up to fourth order in space and time and several test problems are simulated. Finally, an application inspired by Inertial Confinement Fusion (ICF) type flows is considered by solving the Euler equations and the PDE of viscous and resistive magnetohydrodynamics (VRMHD).Comment: 39 pages, 21 figure

    Wall Distance Evaluation Via Eikonal Solver for RANS Applications

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    RÉSUMÉ Les logiciels de mĂ©canique des fluides assistĂ©e par ordinateur (CFD) sont de plus en plus utilisĂ©s pour la conception d’aĂ©ronefs. L’utilisation de grappes informatiques haute performance permet d’augmenter la puissance de calcul, aux prix de modifier la structure du code. Dans les codes CFD, les Ă©quations de Navier-Stokes moyennĂ©es (plus connues sous le nom des Ă©quations RANS) sont souvent rĂ©solues. Par consĂ©quent, les modĂšles de turbulence sont utilisĂ©s pour approximer les effets de la turbulence. Dans l’industrie aĂ©ronautique, le modĂšle Spalart-Allmaras est bien acceptĂ©. La distance Ă  la paroi dans ce modĂšle, par exemple, joue un rĂŽle clĂ© dans l’évaluation des forces aĂ©rodynamiques. L’évaluation de ce paramĂštre gĂ©omĂ©trique doit alors ĂȘtre prĂ©cis et son calcul efficace. Avec les nouveaux dĂ©veloppement des hardwares, un besoin se crĂ©e dans la communautĂ© afin d’adapter les codes CFD Ă  ceux-ci. Les algorithmes de recherche comme les distances euclidienne et projetĂ©e sont des mĂ©thodes souvent utilisĂ©es pour le calcul de la distance Ă  la paroi et ont tendance Ă  prĂ©senter une mauvaise scalabilitĂ©. Pour cette raison, un nouveau solveur pour la distance Ă  la paroi doit ĂȘtre dĂ©veloppĂ©. Pour utiliser les solveurs et techniques d’accĂ©lĂ©ration dĂ©jĂ  existantes au sein du code CFD, l’équation Eikonal, une Ă©quation aux diffĂ©rentielles partielles non-linĂ©aires, a Ă©tĂ© choisie. Dans la premiĂšre partie du projet, le solveur d’équation Eikonal est dĂ©veloppĂ© en 2D et est rĂ©solue dans sa forme advective au centre de cellule. Les mĂ©thodes des diffĂ©rences finies et des volumes finis sont testĂ©es. L’équation est rĂ©solue Ă  l’aide d’une discrĂ©tisation spatiale de premier ordre en amont. Les solveurs ont Ă©tĂ© vĂ©rifiĂ©s sur des cas canoniques, tels une plaque plane et un cylindre. Les deux mĂ©thodes de discrĂ©tisation rĂ©ussissent Ă  corriger les effets de maillages obliques et courbes. La mĂ©thode des diffĂ©rences finies possĂšde un taux de convergence en maillage de deuxiĂšme ordre tandis que la mĂ©thode des volumes finis a un taux de convergence de premier ordre. L’addition d’une reconstruction linĂ©aire de la solution Ă  la face permet d’étendre la mĂ©thode des volumes finis Ă  une mĂ©thode de deuxiĂšme ordre. De plus, les mĂ©thodes de diffĂ©rence finie et de volume fini de deuxiĂšme ordre permettent de bien reprĂ©senter la distance Ă  la paroi dans les zones de fort Ă©largissement des cellules. L’équation Eikonal est ensuite vĂ©rifiĂ© sur plusieurs cas dont un profil NACA0012 en utilisant trois modĂšles de turbulence : Spalart-Allmaras, Menter SST et Mener-Langtry SST transitionnel.----------ABSTRACT Computational fluid dynamics (CFD) software is being used more often nowadays in aircraft design. The use of high performance computing clusters can increase computing power, but requires change in the structure of the software. In the aeronautical industry, CFD codes are often used to solve the Reynolds-Averaged Navier-Stokes (RANS) equations, and turbulence models are frequently used to approximate turbulent effects on flow. The Spalart-Allmaras turbulence model is widely accepted in the industry. In this model, wall distance plays a key role in the evaluation of aerodynamic forces. Therefore calculation of this geometric parameter needs to be accurate and efficient. With new developments in computing hardware, there is a need to adapt CFD codes. Search algorithms such as Euclidean and projected distance are often the methods used for computation of wall distance but tend to exhibit poor scalability. For this reason, a new wall distance solver is developed here using the Eikonal equation, a non-linear partial differential equation, chosen to make use of existing solvers and acceleration techniques in RANS solvers. In the first part of the project, the Eikonal equation solver was developed in 2D and solved in its advective form at the cell center. Both finite difference and finite volume methods were tested. The Eikonal equation was also solved using a first-order upwind spatial discretization. The solvers were verified through canonical cases like a flat plate and a cylinder. Both methods were able to correct the effects of skewed and curved meshes. The finite difference method converged at a second-order rate in space while the finite volume method converged at a first-order rate. The addition of a linear reconstruction of the solution at the face extended the finite volume method to a second-order method. Moreover, both finite difference and second-order finite volume methods were well represented by wall distance in zones of strong cell growth. The finite difference method was chosen, as it required less computing time. The Eikonal equation was then verified for several cases including a NACA0012 using three turbulence models: Spalart-Allmaras, Menter’s SST and Menter-Langtry transitional SST. For the first model, the Eikonal equation was able to correct grid skewness on the turbulent viscosity as well as on the aerodynamic coefficients, while for the other two yielded results similar to Euclidean and projected distance. To verify the implementation and convergence of the multi-grid scheme, the new wall distance solver was tested on an ice-accreted airfoil. In addition, the overset grid capabilities of the wall distance solver were verified on the McDonnell Douglas airfoil. Finally, the DLR-F6, a 3D case, was solved to show that the Eikonal equation can be extended to 3D meshes

    Wall Distance Evaluation Via Eikonal Solver for RANS Applications

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    RÉSUMÉ Les logiciels de mĂ©canique des fluides assistĂ©e par ordinateur (CFD) sont de plus en plus utilisĂ©s pour la conception d’aĂ©ronefs. L’utilisation de grappes informatiques haute performance permet d’augmenter la puissance de calcul, aux prix de modifier la structure du code. Dans les codes CFD, les Ă©quations de Navier-Stokes moyennĂ©es (plus connues sous le nom des Ă©quations RANS) sont souvent rĂ©solues. Par consĂ©quent, les modĂšles de turbulence sont utilisĂ©s pour approximer les effets de la turbulence. Dans l’industrie aĂ©ronautique, le modĂšle Spalart-Allmaras est bien acceptĂ©. La distance Ă  la paroi dans ce modĂšle, par exemple, joue un rĂŽle clĂ© dans l’évaluation des forces aĂ©rodynamiques. L’évaluation de ce paramĂštre gĂ©omĂ©trique doit alors ĂȘtre prĂ©cis et son calcul efficace. Avec les nouveaux dĂ©veloppement des hardwares, un besoin se crĂ©e dans la communautĂ© afin d’adapter les codes CFD Ă  ceux-ci. Les algorithmes de recherche comme les distances euclidienne et projetĂ©e sont des mĂ©thodes souvent utilisĂ©es pour le calcul de la distance Ă  la paroi et ont tendance Ă  prĂ©senter une mauvaise scalabilitĂ©. Pour cette raison, un nouveau solveur pour la distance Ă  la paroi doit ĂȘtre dĂ©veloppĂ©. Pour utiliser les solveurs et techniques d’accĂ©lĂ©ration dĂ©jĂ  existantes au sein du code CFD, l’équation Eikonal, une Ă©quation aux diffĂ©rentielles partielles non-linĂ©aires, a Ă©tĂ© choisie. Dans la premiĂšre partie du projet, le solveur d’équation Eikonal est dĂ©veloppĂ© en 2D et est rĂ©solue dans sa forme advective au centre de cellule. Les mĂ©thodes des diffĂ©rences finies et des volumes finis sont testĂ©es. L’équation est rĂ©solue Ă  l’aide d’une discrĂ©tisation spatiale de premier ordre en amont. Les solveurs ont Ă©tĂ© vĂ©rifiĂ©s sur des cas canoniques, tels une plaque plane et un cylindre. Les deux mĂ©thodes de discrĂ©tisation rĂ©ussissent Ă  corriger les effets de maillages obliques et courbes. La mĂ©thode des diffĂ©rences finies possĂšde un taux de convergence en maillage de deuxiĂšme ordre tandis que la mĂ©thode des volumes finis a un taux de convergence de premier ordre. L’addition d’une reconstruction linĂ©aire de la solution Ă  la face permet d’étendre la mĂ©thode des volumes finis Ă  une mĂ©thode de deuxiĂšme ordre. De plus, les mĂ©thodes de diffĂ©rence finie et de volume fini de deuxiĂšme ordre permettent de bien reprĂ©senter la distance Ă  la paroi dans les zones de fort Ă©largissement des cellules. L’équation Eikonal est ensuite vĂ©rifiĂ© sur plusieurs cas dont un profil NACA0012 en utilisant trois modĂšles de turbulence : Spalart-Allmaras, Menter SST et Mener-Langtry SST transitionnel.----------ABSTRACT Computational fluid dynamics (CFD) software is being used more often nowadays in aircraft design. The use of high performance computing clusters can increase computing power, but requires change in the structure of the software. In the aeronautical industry, CFD codes are often used to solve the Reynolds-Averaged Navier-Stokes (RANS) equations, and turbulence models are frequently used to approximate turbulent effects on flow. The Spalart-Allmaras turbulence model is widely accepted in the industry. In this model, wall distance plays a key role in the evaluation of aerodynamic forces. Therefore calculation of this geometric parameter needs to be accurate and efficient. With new developments in computing hardware, there is a need to adapt CFD codes. Search algorithms such as Euclidean and projected distance are often the methods used for computation of wall distance but tend to exhibit poor scalability. For this reason, a new wall distance solver is developed here using the Eikonal equation, a non-linear partial differential equation, chosen to make use of existing solvers and acceleration techniques in RANS solvers. In the first part of the project, the Eikonal equation solver was developed in 2D and solved in its advective form at the cell center. Both finite difference and finite volume methods were tested. The Eikonal equation was also solved using a first-order upwind spatial discretization. The solvers were verified through canonical cases like a flat plate and a cylinder. Both methods were able to correct the effects of skewed and curved meshes. The finite difference method converged at a second-order rate in space while the finite volume method converged at a first-order rate. The addition of a linear reconstruction of the solution at the face extended the finite volume method to a second-order method. Moreover, both finite difference and second-order finite volume methods were well represented by wall distance in zones of strong cell growth. The finite difference method was chosen, as it required less computing time. The Eikonal equation was then verified for several cases including a NACA0012 using three turbulence models: Spalart-Allmaras, Menter’s SST and Menter-Langtry transitional SST. For the first model, the Eikonal equation was able to correct grid skewness on the turbulent viscosity as well as on the aerodynamic coefficients, while for the other two yielded results similar to Euclidean and projected distance. To verify the implementation and convergence of the multi-grid scheme, the new wall distance solver was tested on an ice-accreted airfoil. In addition, the overset grid capabilities of the wall distance solver were verified on the McDonnell Douglas airfoil. Finally, the DLR-F6, a 3D case, was solved to show that the Eikonal equation can be extended to 3D meshes

    Coupling different discretizations for fluid structure interaction in a monolithic approach

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    In this thesis we present a monolithic coupling approach for the simulation of phenomena involving interacting fluid and structure using different discretizations for the subproblems. For many applications in fluid dynamics, the Finite Volume method is the first choice in simulation science. Likewise, for the simulation of structural mechanics the Finite Element method is one of the most, if not the most, popular discretization method. However, despite the advantages of these discretizations in their respective application domains, monolithic coupling schemes have so far been restricted to a single discretization for both subproblems. We present a fluid structure coupling scheme based on a mixed Finite Volume/Finite Element method that combines the benefits of these discretizations. An important challenge in coupling fluid and structure is the transfer of forces and velocities at the fluidstructure interface in a stable and efficient way. In our approach this is achieved by means of a fully implicit formulation, i.e., the transfer of forces and displacements is carried out in a common set of equations for fluid and structure. We assemble the two different discretizations for the fluid and structure subproblems as well as the coupling conditions for forces and displacements into a single large algebraic system. Since we simulate real world problems, as a consequence of the complexity of the considered geometries, we end up with algebraic systems with a large number of degrees of freedom. This necessitates the use of parallel solution techniques. Our work covers the design and implementation of the proposed heterogeneous monolithic coupling approach as well as the efficient solution of the arising large nonlinear systems on distributed memory supercomputers. We apply Newton’s method to linearize the fully implicit coupled nonlinear fluid structure interaction problem. The resulting linear system is solved with a Krylov subspace correction method. For the preconditioning of the iterative solver we propose the use of multilevel methods. Specifically, we study a multigrid as well as a two-level restricted additive Schwarz method. We illustrate the performance of our method on a benchmark example and compare the afore mentioned different preconditioning strategies for the parallel solution of the monolithic coupled system

    An Accurate and Robust Numerical Scheme for Transport Equations

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    En esta tesis se presenta una nueva técnica de discretización para ecuaciones de transporte en problemas de convección-difusión para el rango completo de números de Péclet. La discretización emplea el flujo exacto de una ecuación de transporte unidimensional en estado estacionario para deducir una ecuación discreta de tres puntos en problemas unidimensionales y cinco puntos en problemas bidimensionales. Con "flujo exacto" se entiende que se puede obtener la solución exacta en función de integrales de algunos parámetros del fluido y flujo, incluso si estos parámetros son vari- ables en un volumen de control. Las cuadraturas de alto orden se utilizan para lograr resultados numéricos cercanos a la precisión de la máquina, incluso con mallas bastas.Como la discretización es esencialmente unidimensional, no está garantizada una solución con precisión de máquina para problemas multidimensionales, incluso en los casos en que las integrales a lo largo de cada coordenada cartesiana tienen una primitiva. En este sentido, la contribución principal de esta tesis consiste en una forma simple y elegante de obtener soluciones en problemas multidimensionales sin dejar de utilizar la formulación unidimensional. Además, si el problema es tal que la solución tiene precisión de máquina en el problema unidimensional a lo largo de las líneas coordenadas, también la tendrá para el dominio multidimensional.In this thesis, we present a novel discretization technique for transport equations in convection-diffusion problems across the whole range of Péclet numbers. The discretization employs the exact flux of a steady-state one-dimensional transport equation to derive a discrete equation with a three-point stencil in one-dimensional problems and a five-point stencil in two-dimensional ones. With "exact flux" it is meant that the exact solution can be obtained as a function of integrals of some fluid and flow parameters, even if these parameters are variable across a control volume. High-order quadratures are used to achieve numerical results close to machine- accuracy even with coarse grids. As the discretization is essentially one-dimensional, getting the machine- accurate solution of multidimensional problems is not guaranteed even in cases where the integrals along each Cartesian coordinate have a primitive. In this regard, the main contribution of this thesis consists in a simple and elegant way of getting solutions in multidimensional problems while still using the one-dimensional formulation. Moreover, if the problem is such that the solution is machine-accurate in the one-dimensional problem along coordinate lines, it will also be for the multidimensional domain.<br /
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