Fun3D / OptiGRID Coupling for Unstructured Grid Adaptation for Sonic Boom Problems

Ozcer, Isik; Kandil, Osama A.

doi:10.2514/6.2008-61

Cited by 16 publications

(12 citation statements)

References 3 publications

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“…To improve the prediction accuracy of CFD approach, many efforts have been made to near field grid adaptation. [15][16][17][18][19] The influence of viscous effects, turbulence models and higher order schemes has also been investigated. 20,21 In this paper, four benchmark cases including two axisymmetric body, a simple delta wing body and a full configuration includes fuselage, wing, tail, flow-through nacelles, and blade wing were computed with a RANS based flow solver to predicted the near field sonic boom signature.…”

Section: Introductionmentioning

confidence: 99%

Near Field Sonic Boom Analysis with HUNS3D Solver

Wang

Ren

et al. 2017

55th AIAA Aerospace Sciences Meeting

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Accurate analysis of sonic boom pressure signature using Computational Fluid Dynamics (CFD) is still a challenging task. In this paper, four benchmark cases including two axisymmetric body, a simple delta wing body and a full configuration includes fuselage, wing, tail, flow-through nacelles, and blade wing were computed with a Reynold-averaged Navier-Stokes (RANS) based flow solver to predicted the near field sonic boom signature. The computed results from CFD agree well with the measured data in wind tunnel experiment. The effects of geometry equivalent radius, grid size, turbulence model and spatial discretization schemes are investigated and discussed. I.

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Section: Introductionmentioning

confidence: 99%

Near Field Sonic Boom Analysis with HUNS3D Solver

Wang

Ren

et al. 2017

55th AIAA Aerospace Sciences Meeting

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“…This configuration has also been used by other researchers to evaluate their signature prediction techniques. 12,15 The pressure integral output function was defined as a cylinder, six body lengths in radius, centered about the geometry axis. The cylinder is clipped forward of 3 body lengths behind the nose, aft of 9 body lengths behind the nose, and outside of 0.1 body lengths off the centerline to focus only on the region where wind tunnel data is available.…”

Section: Via Cone-cylinder Configurationmentioning

confidence: 99%

“…10 This alignment issue has also given rise to hybrid methods [11][12][13] where near-body unstructured grid solutions are interpolated to shock-aligned structured grid methods to increase accuracy. The hybrid methods are hindered by the interpolation process, so adaptive grid methods 14,15 are employed to improve the accuracy of unstructured grid methods for long propagation distances. These previous adaptive methods have used only primal solution information (Mach and density) to drive the adaptive process.…”

mentioning

confidence: 99%

Output-Adaptive Tetrahedral Cut-Cell Validation for Sonic Boom Prediction

Park¹,

Darmofal

2008

26th AIAA Applied Aerodynamics Conference

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A cut-cell approach to Computational Fluid Dynamics (CFD) that utilizes the median dual of a tetrahedral background grid is described. The discrete adjoint is also calculated, which permits adaptation based on improving the calculation of a specified output (off-body pressure signature) in supersonic inviscid flow. These predicted signatures are compared to wind tunnel measurements on and off the configuration centerline 10 body lengths below the model to validate the method for sonic boom prediction. Accurate mid-field sonic boom pressure signatures are calculated with the Euler equations without the use of hybrid grid or signature propagation methods. Highly-refined, shock-aligned anisotropic grids were produced by this method from coarse isotropic grids created without prior knowledge of shock locations. A heuristic reconstruction limiter provided stable flow and adjoint solution schemes while producing similar signatures to Barth-Jespersen and Venkatakrishnan limiters. The use of cut-cells with an output-based adaptive scheme completely automated this accurate prediction capability after a triangular mesh is generated for the cut surface. This automation drastically reduces the manual intervention required by existing methods.

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“…More comparison results of CFD predictions and flight data at approximately 100 ft below the aircraft for the F-5E can be found in [9]. A detailed CFD analysis of the F-5E using FUN3D with grid adaptation is documented in [10], which includes a comparison of a FUN3D solution to the Northrop-Grumman CFD prediction of dp/p at 1.5 body lengths (or 75 ft) below the aircraft, as well as a comparison of a FUN3D solution to the flight data at 1.82 body lengths (or 91 ft) below the aircraft. Comparison of CFD predictions and flight data for the NASA F-15B with the Gulfstream's quiet spike is documented in [11].…”

Section: Introductionmentioning

confidence: 99%

Integration of Engine, Plume, and CFD Analyses in Conceptual Design of Low-Boom Supersonic Aircraft

Campbell

Geiselhart

et al. 2009

47th AIAA Aerospace Sciences Meeting Including the New Horizons Forum and Aerospace Exposition

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This paper documents an integration of engine, plume, and computational fluid dynamics (CFD) analyses in the conceptual design of low-boom supersonic aircraft, using a variable fidelity approach. In particular, the Numerical Propulsion Simulation System (NPSS) is used for propulsion system cycle analysis and nacelle outer mold line definition, and a low-fidelity plume model is developed for plume shape prediction based on NPSS engine data and nacelle geometry. This model provides a capability for the conceptual design of low-boom supersonic aircraft that accounts for plume effects. Then a newly developed process for automated CFD analysis is presented for CFD-based plume and boom analyses of the conceptual geometry. Five test cases are used to demonstrate the integrated engine, plume, and CFD analysis process based on a variable fidelity approach, as well as the feasibility of the automated CFD plume and boom analysis capability.

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Fun3D / OptiGRID Coupling for Unstructured Grid Adaptation for Sonic Boom Problems

Cited by 16 publications

References 3 publications

Near Field Sonic Boom Analysis with HUNS3D Solver

Near Field Sonic Boom Analysis with HUNS3D Solver

Output-Adaptive Tetrahedral Cut-Cell Validation for Sonic Boom Prediction

Integration of Engine, Plume, and CFD Analyses in Conceptual Design of Low-Boom Supersonic Aircraft

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