73 research outputs found

    Multigrid Preconditioning for a Space-Time Spectral-Element Discontinuous-Galerkin Solver

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    In this work we examine a multigrid preconditioning approach in the context of a high- order tensor-product discontinuous-Galerkin spectral-element solver. We couple multigrid ideas together with memory lean and efficient tensor-product preconditioned matrix-free smoothers. Block ILU(0)-preconditioned GMRES smoothers are employed on the coarsest spaces. The performance is evaluated on nonlinear problems arising from unsteady scale- resolving solutions of the Navier-Stokes equations: separated low-Mach unsteady ow over an airfoil from laminar to turbulent ow. A reduction in the number of ne space iterations is observed, which proves the efficiency of the approach in terms of preconditioning the linear systems, however this gain was not reflected in the CPU time. Finally, the preconditioner is successfully applied to problems characterized by stiff source terms such as the set of RANS equations, where the simple tensor product preconditioner fails. Theoretical justification about the findings is reported and future work is outlined

    Numerical simulation of the flow about the F-18 HARV at high angle of attack

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    As part of NASA's High Alpha Technology Program, research has been aimed at developing and extending numerical methods to accurately predict the high Reynolds number flow about the NASA F-18 High Alpha Research Vehicle (HARV) at large angles of attack. The HARV aircraft is equipped with a bidirectional thrust vectoring unit which enables stable, controlled flight through 70 deg angle of attack. Currently, high-fidelity numerical solutions for the flow about the HARV have been obtained at alpha = 30 deg, and validated against flight-test data. It is planned to simulate the flow about the HARV through alpha = 60 deg, and obtain solutions of the same quality as those at the lower angles of attack. This report presents the status of work aimed at extending the HARV computations to the extreme angle of attack range

    Parallel High-Order Anisotropic Meshing Using Discrete Metric Tensors

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    This paper presents a metric-aligned meshing algorithm that relies on the Lp-Centroidal Voronoi Tesselation approach. A prototype of this algorithm was first presented at the Scitech conference of 2018 and this work is an extension to that paper. At the end of the previously presented work, a set of problems were mentioned which we are trying to address in this paper. First, we show a significant improvement in code performance since we were limited to present relatively benign (analytical) test cases. Second, we demonstrate here that we are able to rely on discrete metric data that is delivered by a Computational Fluid Dynamics (CFD) solver. Third, we demonstrate how to generate high-order curved elements that are aligned with the underlying discrete metric field

    Sparse Data Structures for Efficient State-to-State Kinetic Simulations

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    Higher-fidelity entry simulations can be enabled by integrating finer thermo-chemistry models into compressible flow physics. One such class of models are State-to-State (StS) kinetics, which explicitly track species populations among quantum energy levels. StS models can represent thermo-chemical non-equilibrium effects that are hardly captured by standard multi-temperature models. However, the associated increase in computational cost is dramatic. For implicit solution techniques that rely on standard block-sparse representations of the Jacobian, both the spatial complexity and the temporal complexity grow quadratically with respect to the number of quantum levels represented. We introduce a more efficient way to represent the Jacobian arising in first-order implicit simulations for compressible flow physics coupled with StS models. The key idea is to recognize that the density of local blocks of the Jacobian comes from rank-one updates that can be managed separately. This leads to a new Jacobian structure, consisting of a fully-sparse matrix and block-wise rank-one updates, whose overall complexity grows linearly with the number of quantum levels. This structure also brings forth a potentially faster variation of the block-Jacobi preconditioning algorithm by leveraging the Sherman-Morrison-Woodbury inversion formula

    Tensor-Product Preconditioners for Higher-Order Space-Time Discontinuous Galerkin Methods

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    space-time discontinuous-Galerkin spectral-element discretization is presented for direct numerical simulation of the compressible Navier-Stokes equat ions. An efficient solution technique based on a matrix-free Newton-Krylov method is developed in order to overcome the stiffness associated with high solution order. The use of tensor-product basis functions is key to maintaining efficiency at high order. Efficient preconditioning methods are presented which can take advantage of the tensor-product formulation. A diagonalized Alternating-Direction-Implicit (ADI) scheme is extended to the space-time discontinuous Galerkin discretization. A new preconditioner for the compressible Euler/Navier-Stokes equations based on the fast-diagonalization method is also presented. Numerical results demonstrate the effectiveness of these preconditioners for the direct numerical simulation of subsonic turbulent flows

    Spectral Element Method for the Simulation of Unsteady Compressible Flows

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    This work uses a discontinuous-Galerkin spectral-element method (DGSEM) to solve the compressible Navier-Stokes equations [1{3]. The inviscid ux is computed using the approximate Riemann solver of Roe [4]. The viscous fluxes are computed using the second form of Bassi and Rebay (BR2) [5] in a manner consistent with the spectral-element approximation. The method of lines with the classical 4th-order explicit Runge-Kutta scheme is used for time integration. Results for polynomial orders up to p = 15 (16th order) are presented. The code is parallelized using the Message Passing Interface (MPI). The computations presented in this work are performed using the Sandy Bridge nodes of the NASA Pleiades supercomputer at NASA Ames Research Center. Each Sandy Bridge node consists of 2 eight-core Intel Xeon E5-2670 processors with a clock speed of 2.6Ghz and 2GB per core memory. On a Sandy Bridge node the Tau Benchmark [6] runs in a time of 7.6s

    A Linear-Elasticity Solver for Higher-Order Space-Time Mesh Deformation

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    A linear-elasticity approach is presented for the generation of meshes appropriate for a higher-order space-time discontinuous finite-element method. The equations of linear-elasticity are discretized using a higher-order, spatially-continuous, finite-element method. Given an initial finite-element mesh, and a specified boundary displacement, we solve for the mesh displacements to obtain a higher-order curvilinear mesh. Alternatively, for moving-domain problems we use the linear-elasticity approach to solve for a temporally discontinuous mesh velocity on each time-slab and recover a continuous mesh deformation by integrating the velocity. The applicability of this methodology is presented for several benchmark test cases

    Numerical simulation of the flow about an F-18 aircraft in the high-alpha regime

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    The current research is aimed at developing and extending numerical methods to accurately predict the high Reynolds number flow about the NASA F-18 HARV at large angles of attack. The resulting codes are validated by comparison of the numerical results with in-flight aerodynamic measurements and flow visualization obtained on the HARV. Further, computations have been used to provide an analysis and numerical optimization of a pneumatic slot blowing concept, and a mechanical strake concept, for use as potential forebody flow control devices in improving high-alpha maneuverability
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