Correlation analyses of ground-based acoustic-pressure measurements of noise from a tethered F-22A provide insights into the sound-field characteristics with position and engine condition. Time-scaled single-point (auto) correlation functions show that, to the side of the nozzle exit, the temporal-correlation envelope decays rapidly, whereas the envelope decays more slowly in the maximum radiation region and farther downstream. This type of spatial variation has been previously attributed to a transition from fine-to large-scale mixing noise in laboratoryscale jets. Two-point space-time (cross) correlation functions demonstrate that noise from a single engine operating at intermediate power is similar to that from a heated, convectively subsonic laboratory-scale jet, whereas additional features are seen at afterburner, relative to supersonic laboratory jets. A complementary coherence analysis provides estimates of coherence lengths as a function of frequency and location. Acoustic coherence lengths across the ground microphone array are used to analyze one-dimensional, equivalent-source-coherence lengths obtained from the DAMAS-C beamforming algorithm. The source coherence reaches its maximum downstream of the maximum source level, suggesting that uncorrelated sources meaningfully contribute to the dominant source region. In addition to revealing further the nature of the sound field near an advanced tactical engine, the characteristics seen should be useful as a phenomenological comparison point for those trying to model military-scale results both experimentally and numerically.
Time reversal (TR) utilizes an array of transducers, a time reversal mirror (TRM), to locate sources. Here TR is applied to simple sources using steady-state waveforms in a numerical, point source model in a half-space environment. It is found that TR can effectively localize a simple source broadcasting a continuous wave, depending on the angular spacing. Furthermore, the angular spacing and the aperture of the TRM are the most important parameters when creating a setup of receivers for imaging a source. This work optimizes a TRM when the source's location is known within a region of certainty.
Full-scale tactical aircraft noise exhibits multiple radiation lobes not seen in laboratoryscale jets. These lobes have different radiation directions yet appear to have similar, overlapping source regions. Near-field acoustical holography (NAH) source reconstructions, in conjunction with partial field decomposition (PFD) methods that produce physically meaningful partial fields, are used in the current work to investigate the nature of these radiation patterns. First, it is shown that the two main radiation lobes are highly incoherent, suggesting independent partial sources. Second, these lobes are isolated as mutually orthogonal partial fields. In this representation, the lobes seem to be generated by independent yet spatially coincident extended partial sources. Source comparisons are made between non-afterburner and afterburner engine powers to investigate whether afterburner combustion produces any sources that are fundamentally different from those of nonafterburner operations. The current results show no qualitative changes occur due to the addition of the afterburner thrust aside from minor variations in source distribution, level, and the nature of the overlap between the multiple lobes.
Meaningful use of the autocorrelation in jet noise analysis is examined. The effect of peak frequency on the autocorrelation function width is removed through a temporal scaling prior to making comparisons between measurements or drawing conclusions about source characteristics. In addition, a Hilbert transform-based autocorrelation envelope helps to define consistent characteristic time scales. Application of these processes to correlation functions based on large and fine-scale similarity spectra reveal that the large-scale noise radiation from an F-22A deviates from the similarity spectrum model.
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
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