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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 19 records
All sourcesNASA NTRSDOE OSTI
NASA NTRS1975

Air pollution source identification

The techniques available for source identification are reviewed: remote sensing, injected tracers, and pollutants themselves as tracers. The use of the large number of trace elements in the ambient airborne particulate matter as a practical means of identifying sources is discussed. Trace constituents are determined by sensitive, inexpensive, nondestructive, multielement analytical methods such as instrumental neutron activation and charged particle X-ray fluorescence. The application to a large data set of pairwise correlation, the more advanced pattern recognition-cluster analysis approach with and without training sets, enrichment factors, and pollutant concentration rose displays for each element is described. It is shown that elemental constituents are related to specific source types: earth crustal, automotive, metallurgical, and more specific industries. A field-ready source identification system based on time and wind direction resolved sampling is described.

Fordyce, J. S.↗
NASA NTRS1975

Air pollution source identification

Techniques for air pollution source identification are reviewed, and some results obtained with them are evaluated. Described techniques include remote sensing from satellites and aircraft, on-site monitoring, and the use of injected tracers and pollutants themselves as tracers. The use of a large number of trace elements in ambient airborne particulate matter as a practical means of identifying sources is discussed in detail. Sampling and analysis techniques are described, and it is shown that elemental constituents can be related to specific source types such as those found in the earth's crust and those associated with specific industries. Source identification sytems are noted which utilize charged particle X-ray fluorescence analysis of original field data.

Fordyce, J. S.↗
NASA NTRS2010

A Parameter Identification Method for Helicopter Noise Source Identification and Physics-Based Semi-Empirical Modeling

A new physics-based parameter identification method for rotor harmonic noise sources is developed using an acoustic inverse simulation technique. This new method allows for the identification of individual rotor harmonic noise sources and allows them to be characterized in terms of their individual non-dimensional governing parameters. This new method is applied to both wind tunnel measurements and ground noise measurements of two-bladed rotors. The method is shown to match the parametric trends of main rotor Blade-Vortex Interaction (BVI) noise, allowing accurate estimates of BVI noise to be made for operating conditions based on a small number of measurements taken at different operating conditions.

Greenwood, Eric, II↗
NASA NTRS1976

Elemental composition of airborne particulates and source identification - An extensive one year survey

Concentrations of 60 chemical elements in the airborne particulate matter were measured at 16 sites in Cleveland, OH over a 1 year period during 1971 and 1972 (45 to 50 sampling days). Analytical methods used included instrumental neutron activation, emission spectroscopy, and combustion techniques. Uncertainties in the concentrations associated with the sampling procedures, the analytical methods, the use of several analytical facilities, and samples with concentrations below the detection limits are evaluated in detail. The data are discussed in relation to other studies and source origins. The trace constituent concentrations as a function of wind direction are used to suggest a practical method for air pollution source identification.

King, R. B.↗
NASA NTRS2001

Source Identification and Location Techniques

Mr. Weir presented source location results obtained from an engine test as part of the Engine Validation of Noise Reduction Concepts program. Two types of microphone arrays were used in this program to determine the jet noise source distribution for the exhaust from a 4.3 bypass ratio turbofan engine. One was a linear array of 16 microphones located on a 25 ft. sideline and the other was a 103 microphone 3-D "cage" array in the near field of the jet. Data were obtained from a baseline nozzle and from numerous nozzle configuration using chevrons and/or tabs to reduce the jet noise. Mr. Weir presented data from two configurations: the baseline nozzle and a nozzle configuration with chevrons on both the core and bypass nozzles. This chevron configuration had achieved a jet noise reduction of 4 EPNdB in small scale tests conducted at the Glenn Research Center. IR imaging showed that the chevrons produced significant improvements in mixing and greatly reduced the length of the jet potential core. Comparison of source location data from the 1-D phased array showed a shift of the noise sources towards the nozzle and clear reductions of the sources due to the noise reduction devices. Data from the 3-D array showed a single source at a frequency of 125 Hz. located several diameters downstream from the nozzle exit. At 250 and 400 Hz., multiple sources, periodically spaced, appeared to exist downstream of the nozzle. The trend of source location moving toward the nozzle exit with increasing frequency was also observed. The 3-D array data also showed a reduction in source strength with the addition of chevrons. The overall trend of source location with frequency was compared for the two arrays and with classical experience. Similar trends were observed. Although overall trends with frequency and addition of suppression devices were consistent between the data from the 1-D and the 3-D arrays, a comparison of the details of the inferred source locations did show differences. A flight test is planned to determine if the hardware tested statically will achieve similar reductions in flight.

Weir, Donald↗
NASA NTRSDate not supplied

Multiplanar Synthetic Arrays and Their Application to Full-Scale Landing Gear Noise Source Identification

Identification and quantification of noise sources generated by the landing gears of large civil transports are critical for the development of viable abatement technologies that can be applied locally to affect solely the source regions. Leveraging validated computational data sets obtained from airframe noise simulations of a full-scale B777-300ER aircraft, a frame-work based on multiplanar synthetic arrays was developed to examine landing gear sources. The position of the arrays relative to the aircraft nose or main landing gears, the number of microphones in each array, and their distribution pattern were judiciously selected to provide adequate spatial resolution of the sources in the primary flyover, sideline, and upstream directions while maintaining reasonable signal-to-noise ratio and beamwidth over a wide frequency range. Overall, seven synthetic arrays with 800 microphones each, for a total of 5,600 microphones, were used in the framework. Fully synchronous synthetic pressure records at each microphone location were obtained from the simulated data sets via a Ffowcs-Williams and Hawkings integral approach, with flow quantities on a permeable data surface enclosing the source regions used as input. Various applications of synthetic multiplanar arrays to acoustic data analysis are presented; the advantages of the framework in properly resolving and identifying the B777 landing gear sources is demonstrated by comparing three-dimensional source distribution maps with those obtained from a synthetic version of the ground-based microphone array used during flight tests of the same aircraft.

airframe noise↗
NASA NTRS1987

Rotor blade-vortex interaction impulsive noise source identification and correlation with rotor wake predictions

An acoustic source localization scheme applicable to noncompact moving sources is developed and applied to the blade-vortex interaction (BVI) noise data of a 40-percent scale BO-105 model rotor. A generalized rotor wake code is employed to predict possible VBI locations on the rotor disk and is found quite useful in interpreting the acoustic localization results. The highly varying directivity patterns of different BVI impulses generated at the same test condition are explained by both the localization results and predicted tip vortex trajectories. The effects of rotor tip-path-plane angle and advance ratio on the BVI source positions is studied. Decreasing tip-path-plane angle (at constant advance ratio) moves the general interaction region upwind on the rotor disk, significantly changing the interaction geometry. Increasing advance ratio (at constant tip-path-plane angle) shifts the general source region downwind on the rotor disk with the increased convection of the vortices until about 60 deg azimuth, where the BVI sources appear to become acoustically less effective. The region of strongest BVI sources lies between 60 and 70 deg azimuth and 80 and 90 percent radius for the moderate range of advance ratios studied.

Splettstoesser, W. R.↗
NASA NTRS2004

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 p, axial velocity u, radial velocity v, puu and pvv fluctuations measured from various points in 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, and Elam, AIAA Paper 2002-0827). The technique uses a continuous wave, narrow line-width laser, Fabry-Perot interferometer and photon counting electronics. The far field sound pressure fluctuations at 30 to the jet axis provided the highest correlation coefficients with all flow variables. The correlation coefficients decreased sharply with increased microphone polar angle, and beyond about 60 all correlation mostly fell below the experimental noise floor. Among all correlations < puu; p/> showed the highest values. Interestingly, , in all respects, were very similar to . The and correlations with 90deg microphone fell below the noise floor. By moving the laser probe at various locations in the jet it was found that the strongest noise source lies downstream of the end of the potential core and extends many diameters beyond. Correlation measurement from the lip shear layer showed a Mach number dependency. While significant correlations were measured in Mach 1.8 jet, values were mostly below the noise floor for subsonic Mach 0.95 jet. Various additional analyses showed that fluctuations from large organized structures mostly contributed to the measured correlation, while that from small scale structures fell below the noise floor.

Panda, J.↗
NASA NTRS2001

Sound Source Identification Through Flow Density Measurement and Correlation With Far Field Noise

Sound sources in the plumes of unheated round jets, in the Mach number range 0.6 to 1.8, were investigated experimentally using "casuality" approach, where air density fluctuations in the plumes were correlated with the far field noise. The air density was measured using a newly developed Molecular Rayleigh scattering based technique, which did not require any seeding. The reference at the end provides a detailed description of the measurement technique.

Panda, J.↗
NASA NTRS1977

Spectrophotometric observations of Molonglo radio source identifications

The paper presents spectrophotometric observations of 76 optical objects identified with radio sources from the MC2 and MC3 catalogs. Line intensities, equivalent widths, line widths, and optical spectral indices are presented for 44 objects confirmed as quasi-stellar objects. The statistical and physical properties of the Molonglo sample are briefly discussed.

Smith, H. E.↗
NASA NTRS1988

A noise source identification technique using an inverse Helmholtz integral equation method

A technique is developed which utilizes numerical models and field pressure information to characterize acoustic fields and identify acoustic sources. The numerical models are based on boundary element numerical procedures. Either pressure, velocity, or passive boundary conditions, in the form of impedance boundary conditions, may be imposed on the numerical model. Alternatively, if no boundary information is known, a boundary condition can be left unspecified. Field pressure data may be specified to overdetermine the numerical problem. The problem is solved numerically for the complete sound field from which the acoustic sources may be determined. The model can then be used to idenfify acoustic intensity paths in the field. The solution can be modified and the model used to evaluate design alternatives. In this investigation the method is tested analytically and verified. In addition, the sensitivity of the method to random and bias error in the input data is demonstrated.

Gardner, B. K.↗
NASA NTRS1978

Pattern recognition methods and air pollution source identification

Directional air samplers, used for resolving suspended particulate matter on the basis of time and wind direction were used to assess the feasibility of characterizing and identifying emission source types in urban multisource environments. Filters were evaluated for 16 elements and X-ray fluorescence methods yielded elemental concentrations for direction, day, and the interaction of direction and day. Large numbers of samples are necessary to compensate for large day-to-day variations caused by wind perturbations and/or source changes.

Leibecki, H. F.↗
NASA NTRSDate not supplied

Aeroacoustic Computations of a Transonic Truss-Braced Wing Aircraft: Part 2 – Acoustic Signature and Noise Source Identification

High-fidelity, time-dependent simulations of a Boeing-designed, transonic, truss-braced-wing aircraft in cruise (clean) and landing configurations are leveraged to generate synthetic microphone-phased-array data for airframe noise prediction and assessment. These data sets are used to compute source localization (beamform) maps to determine the location and strength of primary and secondary airframe noise sources associated with this unique configuration. The synthetic phased-array implementation mimics the setup of a flight test. As this study is ongoing, preliminary integrated far-field spectra for the cruise configuration obtained at multiple spatial resolutions revealed significant tonal content that lacked convergence with increased resolution. The origin of several of these tones and their unusual convergence behavior was traced to the larger-than-normal trailing-edge thickness of the “as-tested” cruise model being simulated. Reducing the trailing-edge thickness to more realistic values eliminated most of the tones at low to moderate frequencies and improved spectrum convergence significantly. Applying lessons learned from the cruise simulations, several modifications to the geometry of the landing configuration were made and are described in this work. Results from permeable and solid Ffowcs-Williams and Hawkings surfaces at two different spatial resolutions (coarse and medium) are used to illustrate the major noise sources and determine convergence of the CLEAN integrated noise levels for the entire aircraft as well as major subcomponents. We demonstrate that the low-frequency content of the far-field spectrum is dominated by noise generated from the main landing gear, while the medium- and high-frequency content is dominated by the wing-leading-edge Krueger flaps. Since analysis of the acoustic maps for the landing configuration revealed several clusters of multiple sources along the wing leading edge, “high resolution” processing of the array data was used to distinguish more accurately the locations of sources.

Transonic Truss-Braced Wing↗
NASA NTRS1976

Further studies of static to flight effects on fan tone noise using inlet distortion control for source identification

Current experimental investigations have linked static inflow distortion phenomena such as the ground vortex, atmospheric turbulence, and teststand structure interference to the generation of fan tone noise at the blade passing frequency. Since such distortions do not exist in flight, it is important to remove them from the static test environment and thereby improve the static-to-flight tone-noise correlation. In the course of providing evidence for this position, a recent investigation used a distortion control inlet with a modern day turbofan engine to assess atmospheric turbulence effects. Although the initial results were encouraging, they were incomplete. The present investigation continues this work and shows more completely the effect of atmospheric turbulence on tone-noise generation. Further, use is made of the distortion control inlet to identify other competing tone-noise sources in the test engine such as a rotor-core stator interaction which was confirmed by engine modifications.

Hodder, B. K.↗
NASA NTRSDate not supplied

Aeroacoustic Computations of a Generic Low Boom Concept in Landing Configuration: Part 3 - Aerodynamic Validation and Noise Source Identification

Wind tunnel test data were used to validate the predicted aerodynamic behavior of a 15%-scale version of a generic, low-boom aircraft. The test was conducted in the NASA Langley 14- by 22-Foot Subsonic Tunnel to determine the low-speed aerodynamic characteristics of the model. Measured steady surface pressures and global forces were used to validate predicted aerodynamic results obtained from high-fidelity simulations of the model as installed in the tunnel. Very good agreement between predicted and measured aerodynamic trends was demonstrated, providing the impetus to proceed with companion airframe noise simulations that were conducted in a free-air setting. Computed near-field flow variables acquired on a permeable data surface were used to generate synthetic pressure records for two 800-element phased microphone arrays positioned overhead and to the side of the model. The array data were beamformed to generate noise source localization maps for the clean model and several landing configurations. Primary and secondary airframe sources were identified and their relative strengths were determined. Far-field integrated noise spectra for the full aircraft, as well as individual components, were obtained from the source maps via integration of tailored regions. The analysis showed that noise produced by the landing gear was the dominant contributor to the far-field acoustic signature of the model, followed by flap noise. The effects of permeable data surface end caps, spatial resolution, array orientation, angle of attack, component interaction, velocity scaling, and numerical precision on synthetic far-field spectra were also evaluated.

low boom↗