Noise measured in the vicinity of an F-22A Raptor has been compared to similarity spectra found previously to represent mixing noise from large-scale and fine-scale turbulent structures in laboratory-scale jet plumes. Comparisons have been made for three engine conditions using ground-based sideline microphones, which covered a large angular aperture. Even though the nozzle geometry is complex and the jet is nonideally expanded, the similarity spectra do agree with large portions of the measured spectra. Toward the sideline, the fine-scale similarity spectrum is used, while the large-scale similarity spectrum provides a good fit to the area of maximum radiation. Combinations of the two similarity spectra are shown to match the data in between those regions. Surprisingly, a combination of the two is also shown to match the data at the farthest aft angle. However, at high frequencies the degree of congruity between the similarity and the measured spectra changes with engine condition and angle. At the higher engine conditions, there is a systematically shallower measured high-frequency slope, with the largest discrepancy occurring in the regions of maximum radiation.

[1] A fundamental goal of volcano acoustics is to relate observed infrasonic signals to the eruptive processes generating them. A link between acoustic power˘and volcanic gas exit velocity V was proposed by Woulff and McGetchin (1976) based upon the prevailing jet noise theory at the time (acoustic analogy theory). We reexamine this approach in the context of the current understanding of jet noise, using data from a laboratory jet, a full-scale military jet aircraft, and a full-scale rocket motor. Accurate estimates of˘require good spatial sampling of jet noise directionality; this is not usually possible in volcano acoustic field experiments. Typical volcano acoustic data better represent point measurements of acoustic intensity I( ) at a particular angle  from the jet axis rather than˘. For pure air jet flows, velocity-scaling laws currently proposed for acoustic intensity differ from those for acoustic power and are of the form I( ) (V/c) n  , where c is the ambient sound speed and n  varies nonlinearly from 5 to 10 as a function of temperature ratio and angle  . Volcanic jet flows are more complex than the pure air laboratory case, which suggests that we do not currently know how the exponent n  varies for a volcanic jet flow. This indicates that the formulation of Woulff and McGetchin (1976) can lead to large errors when inferring eruption parameters from acoustic data and thus requires modification. Quantitative integration of field, numerical, and laboratory studies within a modern aeroacoustics framework will lead to a more accurate relationship between volcanic infrasound and eruption parameters.

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The identification of acoustic sources is critical to targeted noise reduction efforts for jets on high-performance tactical aircraft. This paper describes the imaging of acoustic sources from a tactical jet using near-field acoustical holography techniques. The measurement consists of a series of scans over the hologram with a dense microphone array. Partial field decomposition methods are performed to generate coherent holograms. Numerical extrapolation of data beyond the measurement aperture mitigates artifacts near the aperture edges. A multisource equivalent wave model is used that includes the effects of the ground reflection on the measurement. Multisource statistically optimized near-field acoustical holography (M-SONAH) is used to reconstruct apparent source distributions between 20 and 1250 Hz at four engine powers. It is shown that M-SONAH produces accurate field reconstructions for both inward and outward propagation in the region spanned by the physical hologram measurement. Reconstructions across the set of engine powers and frequencies suggests that directivity depends mainly on estimated source location; sources farther downstream radiate at a higher angle relative to the inlet axis. At some frequencies and engine powers, reconstructed fields exhibit multiple radiation lobes originating from overlapped source regions, which is a phenomenon relatively recently reported for full-scale jets.

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.

The lowermost portion of an explosive volcanic eruption column is considered a momentum‐driven jet. Understanding volcanic jets is critical for determining eruption column dynamics and mitigating volcanic hazards; however, volcanic jets are inherently difficult to observe due to their violence and opacity. Infrasound from the 2011 eruption of Nabro Volcano, Eritrea has waveform features highly similar to the “crackle” phenomenon uniquely produced by man‐made supersonic jet engines and rockets and is characterized by repeated asymmetric compressions followed by weaker, gradual rarefactions. This infrasonic crackle indicates that infrasound source mechanisms in sustained volcanic eruptions are strikingly similar to jet noise sources from heated, supersonic jet engines and rockets, suggesting that volcanologists can utilize the modeling and physical understandings of man‐made jets to understand volcanic jets. The unique, distinctive infrasonic crackle from Nabro highlights the use of infrasound to remotely detect and characterize hazardous eruptions and its potential to determine volcanic jet parameters.

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.

Spatial properties of noise statistics near unheated, laboratory-scale supersonic jets yield insights into source characteristics and near-field shock formation. Primary findings are (1) waveforms with positive pressure skewness radiate from the source with a directivity upstream of maximum overall level and (2) skewness of the time derivative of the pressure waveforms increases significantly with range, indicating formation of shocks during propagation. These results corroborate findings of a previous study involving full-scale engine data. Further, a comparison of ideally and over-expanded laboratory data show that while derivative skewness maps are similar, waveform skewness maps are substantially different for the two cases.