A Hybrid Computational Fluid Dynamics Procedure for Sonic Boom Prediction

Laflin, Kelly R.; Klausmeyer, Steven M.; Chaffin, Mark S.

doi:10.2514/6.2006-3168

Cited by 12 publications

(9 citation statements)

References 11 publications

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“…One is by providing dense meshes within the sonic boom pressure disturbance along with mesh rotation techniques 5 to align the mesh with the Mach angle, or alternatively by using solution-adaptive techniques. [6][7][8][9][10][11][12][13][14][15] Also, structured overset grid methods, 16 or hybrid methods [16][17][18][19][20] that utilize unstructured flow solutions in the near-field and a structured grid solutions in the far-field can also provide accurate on-track calculations. Grid generation tools that allow stretching of the mesh in addition to alignment to the Mach angle [21][22][23] offer smaller meshes that maintain density in the axial direction and reduce the effects of dissipation along characteristic lines.…”

Section: Courtesy Of the Boeing Companymentioning

confidence: 99%

Experimental and Computational Sonic Boom Assessment of Boeing N+2 Low Boom Models

Durston

Elmiligui

Cliff

et al. 2014

32nd AIAA Applied Aerodynamics Conference

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Near-field pressure signatures were measured and computational predictions made for several sonic boom models representing Boeing's Quiet Experimental Validation Concept (QEVC) supersonic transport, as well as for three axisymmetric calibration models. The concept was designed under a NASA Research Announcement (NRA) contract to address environmental and performance goals, specifically for low sonic boom loudness levels and high cruise efficiency, for an aircraft anticipated to enter service in the 2020-timeframe. Wind tunnel tests were conducted on the aircraft and calibration models during Phases I and II of the NRA contract from 2011 to 2013 in the NASA Ames 9-by 7-Foot and NASA Glenn 8-by 6-Foot Supersonic Wind Tunnels. Sonic boom pressure signatures were acquired primarily at Mach 1.6 and 1.8, and force and moment data were acquired from Mach 0.8 to 1.8. The sonic boom test data were obtained using a 2-in. flat-top pressure rail and a 14-in. tapered "reflection factor 1" (RF1) pressure rail. Both rails capture an entire pressure signature in one data point, and successive signatures at varying positions along or above the rail were used to improve data quality through spatial averaging. The sonic boom data obtained by the rails were validated with high-fidelity numerical simulations of offbody pressures. The test results showed good agreement between the computational and experimental data when a variety of testing techniques including spatial averaging of a series of pressure signatures were employed. The two wind tunnels generally produced comparable data. NomenclatureCAD = computer-aided design CoR = center of rotation h, h_nose = model altitude at model nose, in. h/L, h_nose_L = model altitude non-dimensionalized by model length HumidAvg = average humidity from wind tunnel sensors, ppm by weight L = model reference length, in. M = Mach number

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Section: Courtesy Of the Boeing Companymentioning

confidence: 99%

Experimental and Computational Sonic Boom Assessment of Boeing N+2 Low Boom Models

Durston

Elmiligui

Cliff

et al. 2014

32nd AIAA Applied Aerodynamics Conference

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“…To improve alignment, isotropic unstructured grids are stretched to align the tetrahedra with the freestream Mach angle to improve signal propagation for initial grids [3]. This alignment issue has also given rise to hybrid methods [4][5][6], in which near-body unstructured-grid solutions are interpolated to shockaligned structured-grid methods to increase accuracy.…”

mentioning

confidence: 99%

Validation of an Output-Adaptive, Tetrahedral Cut-Cell Method for Sonic Boom Prediction

Park

Darmofal

2010

AIAA Journal

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A cut-cell approach to computational fluid dynamics that uses the median dual of a tetrahedral background grid is described. The discrete adjoint is also calculated for an adaptive method to control error in a specified output. The adaptive method is applied to sonic boom prediction by specifying an integral of offbody pressure signature as the output. These predicted signatures are compared to wind-tunnel measurements to validate the method for sonic boom prediction. Accurate midfield 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 are produced by this method from coarse isotropic grids created without prior knowledge of shock locations. A heuristic reconstruction limiter provides 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 automates the volume grid generation task after a triangular mesh is generated for the cut surface.

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“…A recent paper using a feature-based grid optimization method 10 has shown promising results without the need for the adjoint information. Several authors 11,12 have developed hybrid methods that use overset or unstructured grids to compute the very near-field solution, then use these results as boundary conditions for a structured grid case that will extend the pressures to mid-field. While this approach has also been successful, the complexity of setting up and interacting two different grids and flow solver runs would suggest that increasing the mid-field accuracy of the original unstructured grid solution and eliminating the need for a second grid would be a significant improvement to the process.…”

Section: Introductionmentioning

confidence: 99%

Efficient Unstructured Grid Adaptation Methods for Sonic Boom Prediction

Campbell

Carter

Deere

et al. 2008

26th AIAA Applied Aerodynamics Conference

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This paper examines the use of two grid adaptation methods to improve the accuracy of the near-to-mid field pressure signature prediction of supersonic aircraft computed using the USM3D unstructured grid flow solver. The first method (ADV) is an interactive adaptation process that uses grid movement rather than enrichment to more accurately resolve the expansion and compression waves. The second method (SSGRID) uses an a priori adaptation approach to stretch and shear the original unstructured grid to align the grid with the pressure waves and reduce the cell count required to achieve an accurate signature prediction at a given distance from the vehicle. Both methods initially create negative volume cells that are repaired in a module in the ADV code. While both approaches provide significant improvements in the near field signature (< 3 body lengths) relative to a baseline grid without increasing the number of grid points, only the SSGRID approach allows the details of the signature to be accurately computed at mid-field distances (3-10 body lengths) for direct use with mid-field-to-ground boom propagation codes. NomenclatureΔp/p = (local static pressure -free-stream static pressure)/free-stream static pressure H = vertical distance from body to boom measurement station L = reference length x = distance in the streamwise direction Xcone = distance in the streamwise direction relative to initial shock

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A Hybrid Computational Fluid Dynamics Procedure for Sonic Boom Prediction

Cited by 12 publications

References 11 publications

Experimental and Computational Sonic Boom Assessment of Boeing N+2 Low Boom Models

Experimental and Computational Sonic Boom Assessment of Boeing N+2 Low Boom Models

Validation of an Output-Adaptive, Tetrahedral Cut-Cell Method for Sonic Boom Prediction

Efficient Unstructured Grid Adaptation Methods for Sonic Boom Prediction

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