Sound from Explosive Chemical Reactions

Jet noise research has seen increased use of autocorrelation analyses to glean physical insight about the source and its radiation properties. Length scales and other features have been identified in support of models incorporating large-scale (LSS) and fine-scale (FSS) turbulent structures. In this paper, the meaningful use of autocorrelation in jet noise analysis is further examined. A key finding is that the effect of the peak frequency on autocorrelation width needs to be removed prior to making conclusions about the relative LSS and FSS contributions. In addition, the Hilbert transform is applied to create an envelope of the autocorrelation function to more consistently define a characteristic time scale. These methods are first applied to the analytical LSS and FSS similarity spectra, previously developed by Tam et al. [AIAA 96-1716, 1996]. It is found that the envelope of the FSS similarity autocorrelation function is more similar to that of a delta function than the LSS envelope. These curves are used to more effectively quantify FSS and LSS features in noise spectra from the F-22A Raptor. [Work supported by ONR.]

During the advent of active structural acoustic control, attempts were made to target and control structural vibration mode shapes to reduce radiated sound power. In the late eighties and early nineties work on acoustic radiation mode shapes developed an alternative way to target structural acoustic radiation. By attempting to control the radiation mode shapes, contributing structural modes could be more easily targeted. Radiation mode shapes have been examined previously for rectangular plates. The method has been extended to demonstrate radiation mode shapes of circular plates and cylindrical shells. Certain spatial derivatives of plate vibration have been found to be highly correlated with the most efficiently radiating radiation mode shapes at low frequencies. A weighted sum of these spatial derivatives is proposed as a new, generalized control metric.

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. (C) 2013 Acoustical Society of America

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. (C) 2013 Acoustical Society of America

Crackle, the impulsive quality sometimes present in supersonic jet noise, has traditionally been defined in terms of the pressure waveform skewness. However, recent work has shown that the pressure waveform time derivative is a better quantifier of the acoustic shocks believed to be responsible for its perception. This paper discusses two definitions of crackle, waveform asymmetry versus shock content, and crackle as a source or propagation-related phenomenon. Data from two static military jet aircraft tests are used to demonstrate that the skewed waveforms radiated from the jet undergo significant nonlinear steepening and shock formation, as evidenced by the skewness of the time derivative. Thus, although skewness is a source phenomenon, crackle’s perceived quality is heavily influenced by propagation through the near field and into the far field to the extent that crackle is caused by the presence of shock-like features in the waveform.

Spatial dependence of levels and spectral characteristics of the near-field noise spectra from the afterburning F-22A Raptor and their transition toward far-field behavior are described. It is shown that the measured spectra in the vicinity of the aircraft show relatively good agreement with overall shape of large and fine-scale similarity spectra, with two exceptions. First, the measured spectral shapes have shallower slopes at high frequencies than the similarity spectra at most downstream locations. The variation in high-frequency slope with downstream distance is quantified and, in the vicinity of the maximum radiation direction, approaches the !/!! limit associated with shock formation. This measured slope agrees with some previous laboratory and full-scale measurements of supersonic jet noise. Second, the spectra at downstream distances corresponding to the region of maximum radiation exhibit a double peak, a characteristic not predicted by the similarity spectra nor seen in laboratory-scale measurements. In addition, the maximum in the peak-frequency region does not vary continuously with downstream distance, but rather exhibits discrete frequency jumps, with relative contributions of the different peaks varying as a function of downstream distance. These observations have implications in finding ties between the noise from high performance, full-scale engines and laboratory-scale experiments and computational modeling efforts. Furthermore, they indicate the limitations in applying the present similarity spectra models to full-scale engine noise.