Jayanta Panda

The sources of jet noise: experimental evidence

The primary objective of this investigation is to determine experimentally the sources of jet mixing noise. In the present study, four different approaches are used. It is reasonable to assume that the characteristics of the noise sources are imprinted on their radiation fields. Under this assumption, it becomes possible to analyse the characteristics of the far-field sound and then infer back to the characteristics of the sources. The first approach is to make use of the spectral and directional information measured by a single microphone in the far field. A detailed analysis of a large collection of far-field noise data has been carried out. The purpose is to identify special characteristics that can be linked directly to those of the sources. The second approach is to measure the coherence of the sound field using two microphones. The autocorrelations and cross-correlations of these measurements offer not only valuable information on the spatial structure of the noise field in the radial and polar angle directions, but also on the sources inside the jet. The third approach involves measuring the correlation between turbulence fluctuations inside a jet and the radiated noise in the far field. This is the most direct and unambiguous way of identifying the sources of jet noise. In the fourth approach, a mirror microphone is used to measure the noise source distribution along the lengths of high-speed jets. Features and trends observed in noise source strength distributions are expected to shed light on the source mechanisms. It will be shown that all four types of data indicate clearly the existence of two distinct noise sources in jets. One source of noise is the fine-scale turbulence and the other source is the large turbulence structures of the jet flow. Some of the salient features of the sound field associated with the two noise sources are reported in this paper.

Rayleigh Scattering Diagnostic for Measurement of Velocity and Density Fluctuation Spectra

A new molecular Rayleigh scattering based flow diagnostic is used for the first time to measure the power spectrum of gas density and radial velocity component in the plumes of high speed jets. The technique is based on analyzing the Rayleigh scattered light with a Fabry-Perot interferometer used in the static, imaging mode. The PC based data acquisition system is capable of simultaneous sampling of velocity and density at rates to 100 kHz and data record lengths to 10 million. Velocity and density power spectra and velocity-density cross spectra are presented for a subsonic jet, an underexpanded screeching jet, and for Mach 1.4 and Mach 1.8 supersonic jets. Software and hardware interfaces were developed to allow computer control of all aspects of the experiment and data acquisition.

Rayleigh Scattering Diagnostic for Dynamic Measurement of Velocity and Temperature

A new technique for measuring dynamic gas velocity and temperature is described. The technique is based on molecular Rayleigh scattering of laser light, so no seeding of the flow is necessary. The Rayleigh scattered light is filtered with a fixed cavity, planar mirror Fabry-Perot interferometer. A minimum number of photodetectors were used in order to allow the high data acquisition rate needed for dynamic measurements. One photomultiplier tube (PMT) was used to measure the total Rayleigh scattering, which is proportional to the gas density. Two additional PMTs were used to detect light that passes through two apertures in a mask located in the interferometer fringe plane. An uncertainty analysis was used to select the optimum aperture parameters and to predict the measurement uncertainty due to photon shot-noise. Results of an experiment to measure the velocity of a subsonic free jet are presented.

Further Progress in Noise Source Identification in High Speed Jets via Causality Principle

To locate noise sources in high-speed jets, the sound pressure fluctuations p / , measured at far field locations, were correlated with each of density ρ, axial velocity u, radial velocity v, ρuu and ρvv fluctuations measured from various points in jet plumes. The experiments followed the cause-and-effect method of sound source identification, where the cross-correlation coefficients, , etc., could be related to various source terms of Lighthill’s equation. Detailed correlation surveys were conducted in three fully expanded, unheated plumes of Mach number 0.95, 1.4 and 1.8. The velocity and density fluctuations were measured simultaneously using a recently developed, non-intrusive, point measurement technique based on molecular Rayleigh scattering (Seasholtz, Panda & Elam, AIAA paper no 2002-0827). The technique uses a continuous wave, narrow line-width laser, Fabry-Perot interferometer and photon counting electronics. Light scattered by air molecules from a point on the laser beam was collected and spectrally resolved by a Fabry-Perot Interferometer. To determine Doppler shift caused by air flow, the image, formed after the interferometer, was split into two concentric parts and the intensity-ratio was measured by a pair of photomultiplier tubes. The change in the intensity ratio from that created by incident laser light provided a measure of a velocity component. Photo-electron counting over short-duration, contiguous bins provided a time history of velocity variation u(t), v(t). In addition, a part of the Rayleigh scattered light was measured directly, without passing through the interferometer, using a third photomultiplier tube to obtain a time history of density fluctuations ρ(t); and finally, multiplications of the time series data provided ρuu(t) and ρvv(t). Two separate collection arrangements were used to measure Doppler shifts from u and v velocity components. Fourier transforms of the time series data provided respective spectra. It was observed that the density spectra Sρ were in general similar to the axial velocity spectra while the radial velocity spectra Sv were somewhat different. The ρ-u cross-spectra show progressively decreasing correlation with increasing frequency. To determine sources of sound pressure fluctuations microphone signals from 50 nozzle diameters and at polar angles from 30° to 90° to the jet axis, were cross-correlated with individual flow variables. The sound pressure fluctuations at 30° to the jet axis provided the highest correlation coefficients with flow fluctuations. With an increase in microphone polar angle, the correlation coefficients decreased sharply, and beyond about 60° all correlation mostly fell below the experimental noise floor. Among all turbulent fluctuations correlations showed the highest values. Interestingly, , in all respects, were very similar to . Both

Rayleigh Scattering Diagnostic for Dynamic Measurement of Velocity Fluctuations in High Speed Jets

Richard G. SeasholtzGlenn Research Center, Cleveland, OhioJayanta PandaOhio Aerospace Institute, Brook Park, OhioKristie A. ElamAkima Corporation, Fairview Park, OhioPrepared for the39th Aerospace Sciences Meeting and Exhibitsponsored by the American Institute of Aeronautics and AstronauticsReno, Nevada, January 8--11, 2001National Aeronautics andSpace AdministrationGlenn Research Center

Non-intrusive jet noise study combining Rayleigh scattering and phased array measurement techniques

A one -inch diameter cold jet at the NASA-Glenn Research Center was studied with a Rayleigh scattering technique to measure the unsteady density in selected probe volume locations and, simultaneously, with a phased array of 32 microphones arranged in a partial cylinder that was centered on the jet and the probe volume. Phased array beamforming was performed to visualize the jet noise sources and test the effect of ray tracing for array steering and the DAMAS2 deconvolution technique. Correlation coefficients between the microphone signals and between the acoustic data and the unsteady density from the Rayleigh probe were examined. The primary goal was to determine whether the array would increase the correlation coefficient relative to previo us work in which the unsteady density from the Rayleigh system was correlated with the output of individual microphones. Results are presented for the case of M = 0.95. Increased correlation was observed, but, contrary to expectations, the optimal array steering points were not coincident with the probe volume. At low frequency, the highest correlation coefficient was seen when then array was steered upstream of the probe volume . At high frequency, significant correlation between the microphones and the de nsity occurred only when the probe volume was in the jet shear layer. In this case, the delay between the density signal and the acoustic pressure was negative, i.e., the density fluctuations in the probe volume lagged the pressure waves at the microphones. The optimal array steering point in this case was downstream of the probe volume, and coincided with peak acoustic source region seen in beamforming with array by itself.

Rayleigh Scattering Diagnostic for Simultaneous Measurements of Dynamic Density and Velocity

A flow diagnostic technique based on the molecular Rayleigh scattering of laser light is used to obtain dynamic density and velocity data in turbulent flows. The technique is based on analyzing the Rayleigh scattered light with a Fabry-Perot interferometer and recording information about the interference pattern with a multiple anode photomultiplier tube (PMT). An artificial neural network is used to process the signals from the PMT to recover the velocity time history, which is then used to calculate the velocity power spectrum. The technique is illustrated using simulated data. The results of an experiment to measure the velocity power spectrum in a low speed (100 rn/sec) flow are also presented.

Experimental Investigation of Reynolds and Favre Averaging in High-Speed Jets

Recent advancements in a molecular Rayleigh scattering based diagnostic technique allowed for simultaneous measurement of velocity and density fluctuations with high sampling rates. The technique was used to investigate unheated high subsonic and supersonic fully expanded free jets in the Mach number range from 0.8 to 1.8. The difference between the Favre-averaged and the Reynolds-averaged axial velocity and axial component of the turbulent kinetic energy is found to be small. On average, estimates based on Morkovin’s strong Reynolds analogy are found to underpredict turbulent density fluctuations.

Experimental Investigation of the Differences Between Reynolds-Averaged and Favre-Averaged Velocity in Supersonic Jets

Abstract Recent advancement in the molecular Rayleigh scattering based technique allowed for simultaneous measurement of velocity and density fluctuations with high sampling rates. The technique was used to investigate unheated high subsonic and supersonic fully expanded free jets in the Mach number range of 0.8 to 1.8. The difference between the Favre averaged and Reynolds averaged axial velocity and axial component of the turbulent kinetic energy is found to be small. Estimates based on the Morkovin’s ‘Strong Reynolds Analogy’ were found to provide lower values of turbulent density fluctuations than the measured data. I. Introduction Reynolds averaging involves dividing a fluid flow parameter w into a time-averaged w , and a fluctuating w′ part: ∫→ ∞= + ′ = T0Tw dtT1w (1) (t) w w (t), w Lim In the Favre-averaging process a density-weighted filtering is used to calculate time average w~ and the remaining fluctuating part w′′: ∫→ ∞= + ′′ = T0T ρw dtT1Limρ1w(t) w~ w (t), w~ (2) where ρ denotes air density. As there is no mass flux across the Favre-averaged streamline, the use of the Favre-averaged variables makes the governing equations for the mean density, mean velocity and the mean enthalpy more compact. In compressible flow, such simplifications are unattainable by the Reynolds averaging process. Experimental data, such as those measured by Particle image Velocimetry and the present Rayleigh scattering technique, however, produce Reynolds averaged quantities. The differences between the two averages for parameters such as the axial velocity u and the turbulent kinetic energy become a concern whenever computational results are to be compared against experimental data.

Time-Averaged Velocity, Temperature and Density Surveys of Supersonic Free Jets

A spectrally resolved molecular Rayleigh scattering technique was used to simultaneously measure axial component of velocity U, static temperature T, and density ρ in unheated free jets at Mach numbers Mj = 0.6, 0.95, 1.4 and 1.8. The latter two conditions were achieved using contoured convergent-divergent nozzles. A narrow line-width continuous wave laser was passed through the jet plumes and molecular scattered light from a small region on the beam was collected and analyzed using a Fabry-Perot interferometer. The optical spectrum analysis provided measures of velocity and static temperature. The local air density at the probe volume was determined by monitoring the intensity variation of the scattered light using photomultiplier tubes. The Fabry-Perot interferometer was operated in the imaging mode, whereby the fringe formed at the image plane was captured by a cooled CCD camera. Special attention was given to remove dust particles from the plume and to provide adequate vibration isolation to the optical components. The velocity profiles from various operating conditions were compared with that measured by a Pitot tube. An excellent comparison within 5m/s demonstrated the maturity of the technique. Temperature was measured least accurately, within 10K, while density was measured within 1% uncertainty. The survey data consisted of centerline variations and radial profiles of time-averaged U, T and ρ. The static temperature and density values were used to determine static pressure variations inside the jet. The data provided a comparative study of jet growth rates with increasing Mach number. The current work is part of a data-base development project for Computational Fluid Dynamics and Aeroacoustics codes that endeavor to predict noise characteristics of high speed jets. A limited amount of far field noise spectra from the same jets are also presented. Finally, a direct experimental validation was obtained for the Crocco-Busemann equation which is commonly used to predict temperature and density profiles from known velocity profiles. Data presented in this paper are available in ASCII format upon request.Copyright