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Kevin E Jacobson

Publications and source records attributed to Kevin E Jacobson.

At least 19 records

FUN3D Manual: 14.1

This manual describes the installation and execution of FUN3D version 14.1, including optional dependent packages. FUN3D is a suite of computational fluid dynamics simulation and design tools that uses mixed-element unstructured grids in a large number of formats, including structured multiblock and overset grid systems. A discretely-exact adjoint solver may be used for formal design optimization, error estimation, and mesh adaptation. FUN3D also offers a reacting, real-gas capability and provides GPU acceleration of many common simulation options.

William K Anderson↗

FUN3D Manual: 14.0.2

This manual describes the installation and execution of FUN3D version 14.0.2, including optional dependent packages. FUN3D is a suite of computational fluid dynamics simulation and design tools that uses mixed-element unstructured grids in a large number of formats, including structured multiblock and overset grid systems. A discretely-exact adjoint solver may be used for formal design optimization, error estimation, and mesh adaptation. FUN3D also offers a reacting, real-gas capability and provides GPU acceleration of many common simulation options.

William K Anderson↗

FUN3D Manual: 14.0

This manual describes the installation and execution of FUN3D version 14.0,including optional dependent packages. FUN3D is a suite of computational fluid dynamics simulation and design tools that uses mixed-element unstructured grids in a large number of formats, including structured multiblock and overset grid systems. A discretely-exact adjoint solver may be used for for-mal design optimization, error estimation, and mesh adaptation. FUN3D also offers a reacting, real-gas capability and provides GPU acceleration of many common simulation options.1

William K Anderson↗

FUN3D Manual: 13.7

This manual describes the installation and execution of FUN3D version 13.7, including optional dependent packages. FUN3D is a suite of computational fluid dynamics simulation and design tools that uses mixed-element unstructured grids in a large number of formats, including structured multiblock and overset grid systems. A discretely-exact adjoint solver may be used for formal design optimization, error estimation, and mesh adaptation. FUN3D also offers a reacting, real-gas capability and provides GPU acceleration of many common simulation options.

FUN3D↗

Flutter Analysis with Stabilized Finite Elements Based on the Linearized Frequency-Domain Approach

When designing and certifying aircraft, engineers must take into consideration aeroelastic effects such as flutter. Design and certification of a vehicle may require analysis of thousands of aeroelastic responses. Standard tools in the aerospace industry are based on linear aerodynamic models such as the doublet-lattice method, but these methods can be nonconservative in certain situations such as in the transonic regime. While computational fluid dynamics (CFD) is a higher fidelity alternative, the time-marching approach has a drastically increased computational cost compared to the linear aerodynamic methods. By taking advantage of the periodic nature of flutter, frequency-domain methods offer a more efficient alternative to time-marching CFD. In this work, a linearized frequency-domain method is implemented and verified in the stabilized finite-element solver in FUN3D. The linearized frequency-domain method is demonstrated and compared to other methods for traditional benchmark cases for computational aeroelasticity: the AGARD 445.6 wing, the Benchmark Supercritical Wing, and the Benchmark NACA 0012Wing.

Kevin E Jacobson↗

Sparse Linear Algebra Toolkit for Computational Aerodynamics

Finding solutions to sparse linear systems of equations is an essential step in Computational Engineering applications of interest to NASA. Linear systems of equations are composed and solved in almost every computational engineering application. The characteristics of linear systems vary greatly from one application to another. Accordingly, there are a wide variety of methods for the solution of linear systems of equations. The operations and methods prepared by the authors are focused on linear systems of interest to NASA, primarily those associated with Computational Fluid Dynamics (CFD), Aeroelasticity, and Aeroacoustics. The Sparse Linear Algebra Toolkit (SLAT) is a coordinated collection of software featuring operations, methods, and data structures that are useful when solving sparse linear systems of equations on modern computer architectures. The implemented operations and methods are designed and tuned for parallelism in shared memory, in distributed memory, and across the hybrid combination of distributed-shared memory. The toolkit includes novel methods and implementations for modern architectures and facilitates development of new approaches for meeting NASA’s evolving computational engineering challenges using evolving computer architectures that are not available in vendor libraries. In this paper, significant features and interfaces within SLAT are presented and verified for simulations performed with NASA’s CFD solver, FUN3D. The runtime and scaling performance of the Generalized Minimum Residual (GMRES) method implemented in SLAT is analyzed for the linear subproblems within the solution of turbulent Navier-Stokes equations employed in the simulation of high-lift configurations. Prior to this work, the SPARSKIT GMRES implementation was the only Krylov subspace method available within FUN3D. A strong scaling study shows the SLAT GMRES implementation facilitates accurate Reynolds-averaged Navier-Stokes CFD solutions between 15% and 56% faster than the SPARSKIT GMRES implementation.

Stephen L Wood↗

Impacts of Hybrid Parallelism and Vectorization on the Performance of Newton-Krylov Methods in Computational Aerodynamics

Finding the numerical solution of moderate and high-fidelity aerodynamics problems on modern computer architectures involves, 1) decomposing the domain into smaller regions of nearly equal size, and 2) allocating computational resources for calculations on each domain and communication between domains. Modern computer clusters are composed from hierarchies of processing, memory, and communication resources with varying capabilities and latencies.This paper focuses on the combination of domain decomposition provided by ParMETIS [1]and Newton-Krylov Methods [2–5] for the solution of Computational Aerodynamics problems of interest to NASA. Herein, trade-offs encountered when mapping aerodynamics problems to modern computer architectures are explored through examples and discussions of trade-offs in parallelism from MPI [6], Open MP [7], and vectorization as partition sizes and computational resources are varied. An example of the impact that domain decomposition and MPI+OpenMPresource allocation can have on an adjoint calculation is presented in this abstract. The full paper will include more detailed examples, discussions of difficulties and potential methods to overcome them, and topics identified for future study.

Computational Aerodynamics, Hybrid Parallelism, Ve↗

Adjoint-based Sensitivities of Flutter Predictions based on the Linearized Frequency-domain Approach

Flutter is a critical factor in designing and certifying aircraft. The linearized frequency-domain method offers a lower cost alternative to time-marching computational fluid dynamics for high-fidelity flutter analysis. In this work, adjoint-based sensitivities are added to a flutter analysis based on the linearized frequency-domain method to efficiently compute derivatives of flutter cost functions with respect to design variables or uncertain parameters. The derivation of the adjoint equations, which involve complications such as derivatives of a nonlinear generalized eigenvalue problem with complex-valued inputs and derivatives of the linearized Navier-Stokes equations, is provided. The implemented adjoint terms and derivatives are verified before demonstrating the approach for derivatives of flutter dynamic pressure with respect to Mach number for the AGARD 445.6 wing.

Aeroelasticity↗

Multiscale Mesh Adaptation for Transonic Aeroelastic Flutter Problems

This work applies multiscale mesh adaptation with refine to reduce spatial discretization error of aeroelastic computational fluid dynamics (CFD) simulations. Benchmark flutter models, such as the pitch and plunge NACA64A-010 airfoil and the benchmark supercritical wing, are studied with both a linearized frequency-domain solver and time-marching CFD coupled to a modal structural solver in FUN3D. The undeformed NASA Common Research Model (CRM), an aeroelastic jig shape variant of the CRM, is also studied with the linearized frequency-domain approach. For these cases, the adaptation process converges to comparable flutter predictions to hand-generated meshes but with smaller node counts. However the additional disciplines of the linearized frequency-domain analysis, the mesh deformation, and the unsteady finite-volume solver create robustness challenges that need to be addressed before it can be applied as a fully automated process for complex transonic aeroelastic problems. In particular, negative volumes are observed to be an issue for FUN3D’s linear elasticity mesh deformation solver when moving the adapted meshes.

Aeroelasticity↗

Angle-of-Attack Sweep with Mesh Adaptation for High-Lift Configurations

This paper reports an angle-of-attack (alpha) sweep study with mesh adaptation for the high-lift configuration - JAXA Standard Model (JSM) from the 3rd AIAA High-Lift Prediction Workshop. The method of angle-of-attack (alpha) continuation, where the flow-field at a certain angle of attack is initialized from the solution obtained at the previous angle of attack, is applied to adapted unstructured meshes. Since the meshes are continuously adapted, flow-field initialization on a particular mesh for a certain angle is done through linear interpolation of the solution from the previous mesh. Interpolated initial conditions usually prevent massively separated solutions that may otherwise occur with impulsive initial conditions. Alpha continuations are done in both forward (increasing alpha) and reverse (decreasing alpha) directions, resulting in the formation of hysteresis loops. Skin frictions are compared with the wind-tunnel oil flow images and pressure coefficients are compared with the wind-tunnel values, at selected angles of attack. Final paper will include results also for the high-lift version of the Common Research Model (CRM-HL) from the 4th AIAA High-Lift Prediction Workshop. A thorough comparison of the results will also be made with the available wind-tunnel data.

Mesh Adaptation↗

Aeroelastic Analysis of Highly Flexible Wings with Linearized Frequency-Domain Aerodynamics

Flutter analysis of configurations with geometric structural nonlinearities typically is done with time-domain analysis. The results from this process are computationally expensive and can yield cumbersome results that may be difficult to manage/interpret. Compared to time-domain methods, frequency-domain flutter analysis can provide additional insight into the characteristics of a flutter stability problem. By linearizing the aeroelastic problem about the nonlinear equilibrium state, this work applies frequency-domain aeroelastic analysis to the Pazy wing, the subject of the Large Deformation Working Group in the Aeroelastic Prediction Workshop. Generalized aerodynamic forces (GAFs) are computed with both a doublet-lattice method and a computational fluid dynamics solver at a range of reduced frequencies as well as a range of dynamic pressures to account for the dependence of the mode shapes on the nonlinear equilibrium state. These GAFs are used in a p-k flutter solver, which is modified to handle the dependence of the stiffness matrix and GAFs on the dynamic pressure.

Bret K Stanford↗

Progress on Transonic Flutter and Shock Buffet Computationsin Support of the Third Aeroelastic Prediction Workshop

This paper reports on the progress of the NASA Langley team contributions to the third Aeroelastic Pre-diction Workshop’s (AePW-3) High Angle Working Group (HAWG). The primary objectives of HAWG is to predict the fluter dynamic pressure of the NASA Benchmark Supercritical Wing (BSCW) configuration at Mach 0.8 and 5◦angle of attack. The secondary objective is to determine if a shock-buffet onset is present at or near that flow condition. The computational results are obtained using FUN3D, an unstructured grid Reynolds-averaged Navier-Stokes solver developed at the NASA Langley Research Center. The preliminary analysis results show a computationally-obtained flutter dynamic pressure of approximately 120 psf. Initial results describing unforced BSCW unsteady flow environment at flutter condition are also presented.

Pawel Chwalowski↗