Shielding of Turbomachinery Broadband Noise from a Hybrid wing Body Aircraft Configuration

Hutcheson, Florence V.; Brooks, Thomas F.; Burley, Casey L.; Bahr, Christopher J.; Stead, Daniel J.; Pope, D. Stuart

doi:10.2514/6.2014-2624

Cited by 28 publications

(31 citation statements)

References 10 publications

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“…11 did not capture the transition between shielded and unshielded regions. However other data from the test did capture this transition 21 . The extrapolated data in both Fig.…”

Section: A Bens Suppressionmentioning

confidence: 94%

“…The first focused on characterizing shielding by the HWB airframe of inlet and aft radiated broadband noise based on engine placement and variations in vertical tail configurations. 21 The broadband engine noise component was simulated using two Broadband Engine Noise Simulators (BENS) 21 . Shielding of the inlet and exhaust radiated noise was measured separately by capping, respectively, the exhaust or inlet of the BENS nacelles.…”

Section: Acoustic Data Processing and Noise Scalingmentioning

confidence: 99%

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Noise Scaling and Community Noise Metrics for the Hybrid Wing Body Aircraft

Burley

Brooks

Hutcheson

et al. 2014

20th AIAA/CEAS Aeroacoustics Conference

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An aircraft system noise assessment was performed for the hybrid wing body aircraft concept, known as the N2A-EXTE. This assessment is a result of an effort by NASA to explore a realistic HWB design that has the potential to substantially reduce noise and fuel burn. Under contract to NASA, Boeing designed the aircraft using practical aircraft design principles with incorporation of noise technologies projected to be available in the 2020 timeframe. NASA tested a 5.8% scale-model of the design in the NASA Langley 14-by 22-Foot Subsonic Tunnel to provide source noise directivity and installation effects for aircraft engine and airframe configurations. Analysis permitted direct scaling of the model-scale jet, airframe, and engine shielding effect measurements to full-scale. Use of these in combination with ANOPP predictions enabled computations of the cumulative (CUM) noise margins relative to FAA Stage 4 limits. The CUM margins were computed for a baseline N2A-EXTE configuration and for configurations with added noise reduction strategies. The strategies include reduced approach speed, over-the-rotor liner and soft-vane fan technologies, vertical tail placement and orientation, and modified landing gear designs with fairings. Combining the inherent HWB engine shielding by the airframe with added noise technologies, the cumulative noise was assessed at 38.7 dB below FAA Stage 4 certification level, just 3.3 dB short of the NASA N+2 goal of 42 dB. This new result shows that the NASA N+2 goal is approachable and that significant reduction in overall aircraft noise is possible through configurations with noise reduction technologies and operational changes. Nomenclature ANOPP = NASA's aircraft noise prediction program 1 ANOPP2 = NASA's aircraft noise prediction program2, a multi-fidelity framework AOA = angle of attack, degrees AP = approach flight condition BENS = broadband engine noise simulators BPR = engine bypass ratio CB = cutback flight conditionThis material is declared a work of the U.S. Government and is not subject to copyright protection in the United States. AIAA Aviation 2 CJES = compact jet engine simulators CUM = cumulative noise (summation of takeoff, cutback and approach EPNL), EPNdB D = fan nozzle exit diameter, ft. dB = decibel EPNL = effective perceived noise level, dB, also referred to as EPNdB FLOPS = flight optimization system 2 f = frequency HWB = hybrid wing body LE = leading edge L/D = lift/drag M = Mach number PNL = perceived noise level, dB PNLT = tone-corrected perceived noise level, dB R = distance from source to observer SF = model-scale/full-scale = 0.058 SFC = specific fuel consumption SL = sideline (full-throttle flight condition) certification point SPL = sound pressure level X = axial coordinate, ft. Greek φ = azimuthal directivity angle, degrees θ = polar directivity angle, degrees Subscript fs = full-scale ms = model-scale nb = narrowband

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“…11 did not capture the transition between shielded and unshielded regions. However other data from the test did capture this transition 21 . The extrapolated data in both Fig.…”

Section: A Bens Suppressionmentioning

confidence: 94%

Section: Acoustic Data Processing and Noise Scalingmentioning

confidence: 99%

Noise Scaling and Community Noise Metrics for the Hybrid Wing Body Aircraft

Burley

Brooks

Hutcheson

et al. 2014

20th AIAA/CEAS Aeroacoustics Conference

Self Cite

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“…The research version contains several data sources and prediction models that are not yet part of the publicly released version of ANOPP. The data sources are identified in the figure highlighting the prediction process as experimental data inputs, stemming from work carried out in the past several years [11][12][13][14][15]. These data are incorporated into the prediction in several ways.…”

Section: Noise Prediction Detailsmentioning

confidence: 99%

“…With respect to the airframe noise, the gear are modeled using the Guo landing gear method [21]; the Krueger noise is modeled with the Guo leading edge method [22]; and trailing edge noise is modeled using the Fink airframe model [23]. Shielding effects are accounted for using suppressions based on previous wind tunnel experiments in the Boeing Low Speed Aeroacoustic Facility (LSAF) [12] and the NASA Langley Research Center 14-by 22-Foot Subsonic Tunnel [13].…”

Section: Anopp-researchmentioning

confidence: 99%

Aircraft System Noise Prediction Uncertainty Quantification for a Hybrid Wing Body Subsonic Transport Concept

June

Thomas

Guo³

2018

2018 AIAA/CEAS Aeroacoustics Conference

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Aircraft system level noise prediction for advanced, unconventional concepts has undergone significant improvement over the past two decades. The prediction modeling uncertainty must be quantified so that potential benefits of unconventional configurations, which are outside of the range of empirical models, can be reliably assessed. This paper builds on previous work in an effort to improve estimates of element prediction uncertainties where the prediction methodology has been improved, or new experimental validation data are available, to provide an estimate of the system level uncertainty in the prediction process. In general, the uncertainty of the prediction will be strongly dependent on the aircraft configuration as well as which technologies are integrated. While the quantitative uncertainty values contained here are specific to the hybrid wing body design presented, the underlying process is the same regardless of configuration. A refined process for determining the uncertainty for each element of the noise prediction is detailed in this paper. The system level uncertainty in the prediction of the aircraft noise is determined at the three certification points, using a Monte Carlo method. Comparisons with previous work show a reduction of 1 EPNdB in the 95 % coverage interval of the cumulative noise level. The largest impediment for continued reduction in uncertainty for the hybrid wing body concept is the need for improved modeling and validation experiments for fan noise, propulsion airframe aeroacoustic effects, and the Krueger flap, which comprise the bulk of the uncertainty in the cumulative certification noise level.

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“…This instrumentation allows the exhaustive analysis of the sound field directivity ( [7]). In particular, a study of jet engines noise shielding by an hybrid wing body aircraft has been conducted by [8,9]. Traversing array acquisitions are also used in closed test section facilities such in the Arnold Engineering Development Complex (AEDC) at NASA Ames.…”

Section: Introductionmentioning

confidence: 99%

S1MAWind Tunnel New Aeroacoustic Capability: a Traversing Microphone Array

Nicolas¹,

Rey²

2018

2018 AIAA/CEAS Aeroacoustics Conference

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This paper aims at describing the new measurement device installed in S1MA wind tunnel for aeroacoustics tests. We present here the in-situ qualification of a traversing microphone array which equipped the acoustic closed test section of the wind tunnel. First, we show that it allows us to capture very complex directivity patterns thanks to a very good spatial resolution. Secondly, we demonstrate the ability of continuous scans measurements to perform as well as stabilized acquisitions, leading to a major improvement in wind tunnel productivity. Finally, we also take advantage of the microphone array to denoise acquisition data using beamforming processing.

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Shielding of Turbomachinery Broadband Noise from a Hybrid wing Body Aircraft Configuration

Cited by 28 publications

References 10 publications

Noise Scaling and Community Noise Metrics for the Hybrid Wing Body Aircraft

Noise Scaling and Community Noise Metrics for the Hybrid Wing Body Aircraft

Aircraft System Noise Prediction Uncertainty Quantification for a Hybrid Wing Body Subsonic Transport Concept

S1MAWind Tunnel New Aeroacoustic Capability: a Traversing Microphone Array

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