Full Configuration Low Boom Model and Grids for 2014 Sonic Boom Prediction Workshop

Morgenstern, John M.

doi:10.2514/6.2013-647

Cited by 13 publications

(13 citation statements)

References 6 publications

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“…The second test case corresponds to the lm-1021 low-boom aircraft example that was used in sbpw1. 2,24 In order to ensure that all participants started from a common baseline, these prescribed nearfield signatures are completely independent of the participants' own signatures submitted in sbpw1 or sbpw2. As before, sBOOM (v2.5) 19 is used for propagation and noise metrics are computed with lcasb.…”

Section: Propagation Resultsmentioning

confidence: 99%

Cart3D Simulations for the Second AIAA Sonic Boom Prediction Workshop

Anderson¹,

Aftosmis

Nemec

2017

35th AIAA Applied Aerodynamics Conference

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Simulation results are presented for all test cases prescribed in the Second AIAA Sonic Boom Prediction Workshop. For each of the four nearfield test cases, we compute pressure signatures at specified distances and o↵-track angles, using an inviscid, embedded-boundary Cartesian-mesh flow solver with output-based mesh adaptation. The cases range in complexity from an axisymmetric body to a full low-boom aircraft configuration with a powered nacelle. For e ciency, boom carpets are decomposed into sets of independent meshes and computed in parallel. This also facilitates the use of more e↵ective meshing strategieseach o↵-track angle is computed on a mesh with good azimuthal alignment, higher aspect ratio cells, and more tailored adaptation. The nearfield signatures generally exhibit good convergence with mesh refinement. We introduce a local error estimation procedure to highlight regions of the signatures most sensitive to mesh refinement. Results are also presented for the two propagation test cases, which investigate the e↵ects of atmopsheric profiles on ground noise. Propagation is handled with an augmented Burgers' equation method (NASA's sBOOM), and ground noise metrics are computed with LCASB. NomenclatureA ref Reference area C D/L/M Drag/lift/pitching moment coe cients C p Local pressure coe cient e Integrated signature di↵erences E Local error estimate J Aerodynamic output functional Distance along signature L Reference length for propagation M Mach number p Static pressure p Order of convergence r Distance from flight path T Temperature w Weight in functional ↵ Angle of attack p M 2 1 1 ✓ O↵set angle to avoid sonic glitch µ Mach angle = sin 1 (1/M 1 ) ⇢ Density ⌧ Normalized x-distance from nose Mach cone O↵-track/Azimuthal angle Subscripts (•) 1 Freestream value (•) t Stagnation value (•) c Coarse (•) f Fine (•) m Medium Abbreviations asel/csel A-/C-weighted sound exposure level axie Axisymmetric body (Case I) axie-prop Axisymmetric body (Prop. Case I) c25f C25d with flow-through nacelle (Case III) c25p C25d with powered nacelle (Case IV) jwb jaxa wing-body (Case II) lcasb Loudness Code for Asymmetric Sonic Booms lm-1021 Lockheed Martin 1021 (Prop. Case II) pl Perceived level of noise sbpw Sonic Boom Prediction Workshop

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Section: Propagation Resultsmentioning

confidence: 99%

Cart3D Simulations for the Second AIAA Sonic Boom Prediction Workshop

Anderson¹,

Aftosmis

Nemec

2017

35th AIAA Applied Aerodynamics Conference

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“…All methods are within the experimental uncertainty for the flat-top portion of the forward signature x = [28,37] and below the experimental expansion pressure x = [38,43] including uncertainty. The final recovery pressure x = [45,55] is within the uncertainty of the experimental measurements.…”

Section: Signaturesmentioning

confidence: 89%

Specialized CFD Grid Generation Methods for Near-Field Sonic Boom Prediction

Park

Campbell

Elmiligui

et al. 2014

52nd Aerospace Sciences Meeting

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Ongoing interest in analysis and design of low sonic boom supersonic transports requires accurate and efficient Computational Fluid Dynamics (CFD) tools. Specialized grid generation techniques are employed to predict near-field acoustic signatures of these configurations. A fundamental examination of grid properties is performed including grid alignment with flow characteristics and element type. The issues affecting the robustness of cylindrical surface extrusion are illustrated. This study will compare three methods in the extrusion family of grid generation methods that produce grids aligned with the freestream Mach angle. These methods are applied to configurations from the First AIAA Sonic Boom Prediction Workshop.

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“…For clarity, we will refer to this propagation case as AXIE-PROP. The second test case corresponds to the LM-1021 low-boom aircraft example that was used in SBPW1 [2,28]. To ensure that all participants started from a common baseline, these prescribed nearfield signatures are completely independent of the participants' own signatures submitted in SBPW1 or SBPW2.…”

Section: Propagation Resultsmentioning

confidence: 99%

Cart3D Simulations for the Second AIAA Sonic Boom Prediction Workshop

Anderson

Aftosmis

Nemec

2019

Journal of Aircraft

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Simulation results are presented for all test cases prescribed in the Second AIAA Sonic Boom Prediction Workshop. An inviscid, embedded-boundary Cartesian-mesh flow solver is used to compute "boom carpets"-pressure signatures at a range of specified distances and off-track angles. To accelerate the process, each boom carpet is automatically decomposed into several independent meshes, computed in parallel. Each mesh uses output-based mesh adaptation to affordably obtain credible results. This paper discusses improved Cartesian meshing strategies for boom prediction, including Mach alignment, azimuthal alignment, high-aspect-ratio cells, and adaptation functional weighting. The resulting nearfield signatures generally exhibit good convergence with mesh refinement. For an independent evaluation of our results, this study introduces a local error estimation procedure that highlights regions of the signatures most sensitive to mesh refinement. Results are also presented for the two atmospheric propagation test cases, which investigate the effects of atmospheric profiles on ground noise. Propagation is handled with an augmented Burgers' equation method (NASA's sBOOM), and ground noise metrics are compared.

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Full Configuration Low Boom Model and Grids for 2014 Sonic Boom Prediction Workshop

Cited by 13 publications

References 6 publications

Cart3D Simulations for the Second AIAA Sonic Boom Prediction Workshop

Cart3D Simulations for the Second AIAA Sonic Boom Prediction Workshop

Specialized CFD Grid Generation Methods for Near-Field Sonic Boom Prediction

Cart3D Simulations for the Second AIAA Sonic Boom Prediction Workshop

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