Supersonic Jet Noise Characteristics &amp; Propagation: Engine and Model Scale

20th AIAA/CEAS Aeroacoustics Conference

Neilsen

et al. 2014

Beamforming techniques for aeroacoustics applications have undergone significant advances over the past decade to account for difficulties that arise when traditional methods are applied to distributed sources such as those found in jet noise. Nevertheless, successful source reconstructions depend on array geometry and the assumed source model. The application of phased-array algorithms to ground array measurements of a fullscale tactical jet engine at military and afterburner engine conditions yield different source reconstructions. A deconvolution approach for the mapping of acoustic sources (DAMAS) is utilized to remove array effects seen in conventional beamforming and allows for improved interpretation of results. However, the distributed nature of the jet noise source, as well as large correlation lengths at low frequencies, can result in inaccurate source locations and/or amplitudes for both conventional beamforming and DAMAS. Results using DAMAS-C, an extension of DAMAS, indicate the degree of source correlation within the military aircraft noise. Source reconstructions on the jet centerline for different one-third octave band frequencies confirm the greater source correlation at low frequencies. These preliminary results represent the first implementation of DAMAS-C on full-scale jet noise data. Nomenclature = Point-spread functions matrix = Total beamform response vector = Beamwidth of the array CSM = Cross spectral matrix = Ambient sound speed = Scaling factor to limit residual component variability = Steering element = Steering vector = Frequency ′ = Cross spectral elements = Conjugate matrix transpose = Wavenumber = Measurement location index = Number of measurement locations = Scan point index = Number of scan points ( ) = Residual component at each iteration 2 0 = Distance from measurement to reference location = Distance from measurement to scan location = Iteration number = Matrix transpose = Vector of monopole source strengths Δ = Spacing between scan points 0 = Cross-source amplitude from and 0 ( ) = Source strength at scan point and iteration = Beamformed response for scan point

Section: Resultssupporting

confidence: 91%

“…Schlinker et al 18 measured noise from a supersonic tactical engine using a 30 microphone phased array located within the maximum radiation region and 16 nozzle diameters from the jet centerline. Source distributions as a function of engine condition were presented and comparisons were made to a laboratory-scale jet.…”

Section: Introductionmentioning

confidence: 99%

Phased-array measurements of full-scale military jet noise

Harker

20th AIAA/CEAS Aeroacoustics Conference

Neilsen

et al. 2014

“…Early studies 1,2 of nonlinear propagation effects in noise radiated from full-scale supersonic jet engines have been extended recently [3][4][5][6][7][8][9] and include a far-field analysis of F-35A static run-up data. 10 Comparison of the measurements in Ref.…”

Section: Introductionmentioning

confidence: 99%

Near-field shock formation in noise propagation from a high-power jet aircraft

The Journal of the Acoustical Society of America

Neilsen

Downing

et al. 2013

Noise measurements near the F-35A Joint Strike Fighter at military power are analyzed via spatial maps of overall and band pressure levels and skewness. Relative constancy of the pressure waveform skewness reveals that waveform asymmetry, characteristic of supersonic jets, is a source phenomenon originating farther upstream than the maximum overall level. Conversely, growth of the skewness of the time derivative with distance indicates that acoustic shocks largely form through the course of near-field propagation and are not generated explicitly by a source mechanism. These results potentially counter previous arguments that jet “crackle” is a source phenomenon.

“…Gee et al 4 analyzed F/A-18E data for evidence of nonlinear propagation effects; this study has been followed up by further full-scale engine tests that showed evidence of nonlinear propagation along the peak directivity direction. 5,6 Laboratory experiments 7 performed on model-scale jets have shown a modest nonlinear transfer of spectral energy to high frequencies [Ͻ10 dB relative to far-field, linear predictions out to a scaled distance of 289 jet nozzle diameters ͑D j ͒] and that the range of angles over which nonlinear effects are present increases 8 as the jet's convective Mach number becomes progressively greater than one. However, the strongest evidence of the relevance of nonlinearity in high-amplitude jet noise propagation has come from work that involved field measurements of the noise radiated by the F-22 Raptor.…”

Section: Introductionmentioning

confidence: 99%

Bicoherence analysis of model-scale jet noise

The Journal of the Acoustical Society of America

Atchley

Falco

et al. 2010

Bicoherence analysis has been used to characterize nonlinear effects in the propagation of noise from a model-scale, Mach-2.0, unheated jet. Nonlinear propagation effects are predominantly limited to regions near the peak directivity angle for this jet source and propagation range. The analysis also examines the practice of identifying nonlinear propagation by comparing spectra measured at two different distances and assuming far-field, linear propagation between them. This spectral comparison method can lead to erroneous conclusions regarding the role of nonlinearity when the observations are made in the geometric near field of an extended, directional radiator, such as a jet.