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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 NTRS1985

Contribution of tonal components to the overall loudness, annoyance and noisiness of noise: Relation between single tones and noise spectral shape

A large scale laboratory investigation of loudness, annoyance, and noisiness produced by single-tone-noise complexes was undertaken to establish a broader data base for quanitification and prediction of perceived annoyance of sounds containing tonal components. Loudness, annoyance, and noisiness were distinguished as separate, distinct, attributes of sound. Three different spectral patterns of broadband noise with and without added tones were studied: broadband-flat, low-pass, and high-pass. Judgments were obtained by absolute magnitude estimation supplement by loudness matching. The data were examined and evaluated to determine the potential effects of (1) the overall sound pressure level (SPL) of the noise-tone complex, (2) tone SPL, (3) noise SPL, (4) tone-to-noise ratio, (5) the frequency of the added tone, (6) noise spectral shape, and (7) subjective attribute judged on absolute magnitude of annoyance. Results showed that, in contrast to noisiness, loudness and annoyance growth behavior depends on the relationship between the frequency of the added tone and the spectral shape of the noise. The close correspondence between the frequency of the added tone and the spectral shape of the noise. The close correspondence between loundness and annoyance suggests that, to better understand perceived annoyance of sound mixtures, it is necessary to relate the results to basic auditory mechanisms governing loudness and masking.

Hellman, R. P.↗
NASA NTRS2007

Fan Rig Noise Spectral Correction for NASA 9'x 15' Low-Speed Wind Tunnel

Aircraft engine noise research and development depends on the ability to study and predict the noise created by each engine component in isolation. Fan noise testing, however, requires a significant support system including a drive mechanism to turn the fan, a device to smooth the flow into the fan, and a stand to raise the fan off the ground each of which has the potential to create its own noise. A methodology was therefore developed to improve the data quality for the 9x15 Low Speed Wind Tunnel (LSWT) at the NASA Glenn Research Center that identifies three noise sources: fan noise, jet noise, and rig noise. The jet noise and rig noise was then measured by mounting a scale model of the 9x15 LSWT setup in a jet rig to simulate everything except the rotating machinery that characterizes fan noise. The data showed that the spectra measured in the LSWT has a strong rig noise component at frequencies as high as 3 kHz depending on the fan and speed. The jet noise was determined to be significantly lower than the rig noise. A mathematical model for the rig noise was then developed using a multi-dimensional least squares fit to the rig noise data. This allows the rig noise to be subtracted or removed, depending on the amplitude of the rig noise relative to the fan noise, at any given frequency, observer angle, or nozzle pressure ratio. The impact of isolating the fan noise with this method on spectra, overall power level (OAPWL), and Effective Perceived Noise Level (EPNL) is studied.

Schifer, Nick↗
NASA NTRS1994

Investigation of Allan variance for determining noise spectral forms with application to microwave radiometry

An investigation of the Allan variance method as a possible means for characterizing fluctuations in radiometric noise diodes has been performed. The goal is to separate fluctuation components into white noise, flicker noise, and random-walk noise. The primary means is by discrete-time processing, and the study focused primarily on the digital processes involved. Noise satisfying the requirements was generated by direct convolution, fast Fourier transformation (FFT) processing in the time domain, and FFT processing in the frequency domain. Some of the numerous results obtained are presented along with the programs used in the study.

Stanley, William D.↗
NASA NTRS1976

Relative effectiveness of several simulated jet engine noise spectral treatments in reducing annoyance in a TV-viewing situation

An experiment was conducted in order to determine the relative effectiveness of several hypothetical jet engine noise treatments and to test hypothesis that speech interference, at least in part, mediates annoyance in a TV-viewing situation. Twenty-four subjects watched television in a simulated living room. Recorded jet flyover noises were presented in such a way as to create the illusion that aircraft were actually flying overhead. There were 27 stimuli (nine spectra at three overall levels) presented at an average rate of approximately one flight every 2 minutes. Subjects judged the annoyance value of individual stimuli using either a category rating method or magnitude estimation method in each of two 1-hour sessions. The spectral treatments most effective in reducing annoyance were at 1.6 Khz and 800 Hz, in that order. The degree of annoyance reduction resulting from all treatments was affected by the overall sound level of the stimuli, with the greatest reduction at the intermediate overall sound level, about 88 to 89 db(A), peak value. The results are interpreted as supporting the hypothesis that speech interference, at least in part, mediates annoyance with aircraft noise in a TV-viewing situation.

Gunn, W. J.↗
NASA NTRS1992

256x256 switched-FET multiplexer for spaceborne astronomical applications

A novel cryogenic design of a source follower per detector (SFD) direct readout multiplexer is demonstrated. This design has proven to be a good prototype for the development of new low-noise large-area cryogenic multiplexers. In the absence of clocking noise, the readout demonstrates as low as about 30 electrons of rms read noise. There is still an excess noise component feeding through when the array is clocked, which manifests itself only at the lower temperatures. The shape of this component is dependent on a number of the bias voltages, and especially on the temperature of the chip. Analysis of the noise spectral density of the unit cell under various bias conditions shows that there is an excess spectral noise component at the lower temperatures.

Mcmurray, Robert E., Jr.↗
NASA NTRS2011

Development of Jet Noise Power Spectral Laws

High-quality jet noise spectral data measured at the Aero-Acoustic Propulsion Laboratory (AAPL) at NASA Glenn is used to develop jet noise scaling laws. A FORTRAN algorithm was written that provides detailed spectral prediction of component jet noise at user-specified conditions. The model generates quick estimates of the jet mixing noise and the broadband shock-associated noise (BBSN) in single-stream, axis-symmetric jets within a wide range of nozzle operating conditions. Shock noise is emitted when supersonic jets exit a nozzle at imperfectly expanded conditions. A successful scaling of the BBSN allows for this noise component to be predicted in both convergent and convergent-divergent nozzles. Configurations considered in this study consisted of convergent and convergent- divergent nozzles. Velocity exponents for the jet mixing noise were evaluated as a function of observer angle and jet temperature. Similar intensity laws were developed for the broadband shock-associated noise in supersonic jets. A computer program called sJet was developed that provides a quick estimate of component noise in single-stream jets at a wide range of operating conditions. A number of features have been incorporated into the data bank and subsequent scaling in order to improve jet noise predictions. Measurements have been converted to a lossless format. Set points have been carefully selected to minimize the instability-related noise at small aft angles. Regression parameters have been scrutinized for error bounds at each angle. Screech-related amplification noise has been kept to a minimum to ensure that the velocity exponents for the jet mixing noise remain free of amplifications. A shock-noise-intensity scaling has been developed independent of the nozzle design point. The computer program provides detailed narrow-band spectral predictions for component noise (mixing noise and shock associated noise), as well as the total noise. Although the methodology is confined to single streams, efforts are underway to generate a data bank and algorithm applicable to dual-stream jets. Shock-associated noise in high-powered jets such as military aircraft can benefit from these predictions.

Khavaran, Abbas↗
NASA NTRS2009

Development of Jet Noise Power Spectral Laws Using SHJAR Data

High quality jet noise spectral data measured at the Aeroacoustic Propulsion Laboratory at the NASA Glenn Research Center is used to examine a number of jet noise scaling laws. Configurations considered in the present study consist of convergent and convergent-divergent axisymmetric nozzles. Following the work of Viswanathan, velocity power factors are estimated using a least squares fit on spectral power density as a function of jet temperature and observer angle. The regression parameters are scrutinized for their uncertainty within the desired confidence margins. As an immediate application of the velocity power laws, spectral density in supersonic jets are decomposed into their respective components attributed to the jet mixing noise and broadband shock associated noise. Subsequent application of the least squares method on the shock power intensity shows that the latter also scales with some power of the shock parameter. A modified shock parameter is defined in order to reduce the dependency of the regression factors on the nozzle design point within the uncertainty margins of the least squares method.

Khavaran, Abbas↗
NASA NTRS1984

Airfoil tip vortex formation noise

Spectral data are presented for the noise produced due to the turbulent three-dimensional vortex flow existing near the rounded tip of lifting airfoils. The results are obtained by the comparison of sets of two- and three-dimensional test data for different airfoil model sizes, angles of attack, and tunnel flow velocities. Microphone cross-correlation and cross-spectral methods were used to determine the radiated noise. Corrections were made for tunnel shear layer and source directivity effects. Interpretation of the results are aided by a three-dimensional flow analysis developed for this study which determines open tunnel and finite aspect ratio corrections heretofore neglected in tip vortex studies. Hot wire measurements were made in the tip vortex formation region for the specification of governing flow parameters. The spectral data is normalized in a format considered most useful for subsequent quantitative prediction of this noise mechanism for practical systems such as helicopter rotors. Comparison is made to the analysis of George and Chou. A recommended prediction method is given.

Brooks, T. F.↗
DOE OSTI2026

Evaluating Limits of Machine Learning-Assisted Raman Spectroscopy in Classification of Biological Samples

Machine learning (ML)-assisted Raman spectroscopy has become a powerful analytical tool for the classification and identification of analytes; however, technical challenges impacting its detection accuracy have not been thoroughly investigated. This study explores experimental factors affecting classification performance. Among the evaluated ML models, ML algorithms show minimal impact on classification accuracy. Instead, experimental factors, including spectral similarity between tested samples and data quality, dominate detection performance. Increases in spectral noise and spectral similarity significantly reduce classification accuracy. In well-controlled samples with low experimental noise, ML-assisted Raman spectroscopy can discriminate lipid mixtures with a composition difference of 1.85 mol %. To assess the effect of biological heterogeneity, we analyzed single-cell Raman spectra from Saccharomyces cerevisiae strains carrying single, double, or triple gene mutations. Intrinsic cell-to-cell variability introduced substantial spectral differences, severely reducing the accuracy of multiclass classification of these genetically similar strains at the single-cell level. Averaging Raman spectra across multiple cells improved classification accuracy by reducing this spectral variability. We also assess the effectiveness of transfer learning across different Raman spectrometers, specifically by applying an ML model trained on one instrument to another Raman spectrometer. Transfer learning can be improved with proper instrument calibration, highlighting the importance of instrument standardization. Overall, our results demonstrate that data quality and spectral similarity are the primary bottlenecks in ML-assisted Raman spectroscopy. Careful attention to sample preparation, data acquisition, measurement conditions, and instrument calibration is critical to achieving robust and reliable classification performance.

Fungi↗
NASA NTRS1995

Spectral identification of minerals using imaging spectrometry data: Evaluating the effects of signal to noise and spectral resolution using the tricorder algorithm

The rapid development of sophisticated imaging spectrometers and resulting flood of imaging spectrometry data has prompted a rapid parallel development of spectral-information extraction technology. Even though these extraction techniques have evolved along different lines (band-shape fitting, endmember unmixing, near-infrared analysis, neural-network fitting, and expert systems to name a few), all are limited by the spectrometer's signal to noise (S/N) and spectral resolution in producing useful information. This study grew from a need to quantitatively determine what effects these parameters have on our ability to differentiate between mineral absorption features using a band-shape fitting algorithm. We chose to evaluate the AVIRIS, HYDICE, MIVIS, GERIS, VIMS, NIMS, and ASTER instruments because they collect data over wide S/N and spectral-resolution ranges. The study evaluates the performance of the Tricorder algorithm, in differentiating between mineral spectra in the 0.4-2.5 micrometer spectral region. The strength of the Tricorder algorithm is in its ability to produce an easily understood comparison of band shape that can concentrate on small relevant portions of the spectra, giving it an advantage over most unmixing schemes, and in that it need not spend large amounts of time reoptimizing each time a new mineral component is added to its reference library, as is the case with neural-network schemes. We believe the flexibility of the Tricorder algorithm is unparalleled among spectral-extraction techniques and that the results from this study, although dealing with minerals, will have direct applications to spectral identification in other disciplines.

Swayze, Gregg A.↗
NASA NTRS1984

Relationship between Allan variances and Kalman Filter parameters

A relationship was constructed between the Allan variance parameters (H sub z, H sub 1, H sub 0, H sub -1 and H sub -2) and a Kalman Filter model that would be used to estimate and predict clock phase, frequency and frequency drift. To start with the meaning of those Allan Variance parameters and how they are arrived at for a given frequency source is reviewed. Although a subset of these parameters is arrived at by measuring phase as a function of time rather than as a spectral density, they all represent phase noise spectral density coefficients, though not necessarily that of a rational spectral density. The phase noise spectral density is then transformed into a time domain covariance model which can then be used to derive the Kalman Filter model parameters. Simulation results of that covariance model are presented and compared to clock uncertainties predicted by Allan variance parameters. A two state Kalman Filter model is then derived and the significance of each state is explained.

Vandierendonck, A. J.↗
NASA NTRS1981

Microwave limb sounder

Trace gases in the upper atmosphere can be measured by comparing spectral noise content of limb soundings with the spectral noise content of cold space. An offset Cassegrain antenna system and tiltable input mirror alternately look out at the limb and up at cold space at an elevation angle of about 22. The mirror can also be tilted to look at a black body calibration target. Reflection from the mirror is directed into a radiometer whose head functions as a diplexer to combine the input radiation and a local ocillator (klystron) beam. The radiometer head is comprised of a Fabry-Perot resonator consisting of two Fabry-Perot cavities spaced a number of half wavelengths apart. Incoming radiation received on one side is reflected and rotated 90 deg in polarization by the resonator so that it will be reflected by an input grid into a mixer, while the klystron beam received on the other side is also reflected and rotated 90 deg, but not without passing some energy to be reflected by the input grid into the mixer.

Gustincic, J. J.↗
NASA NTRS2023

Use of Machine Learning and Principal Component Analysis to Retrieve Nitrogen Dioxide (NO 2 ) With Hyperspectral Imagers and Reduce Noise in Spectral Fitting

Nitrogen dioxide (NO 2 ) is an important trace-gas pollutant and climate agent whose presence also leads to spectral interference in ocean color retrievals. NO 2 column densities have been retrieved with satellite UV–Vis spectrometers such as the Ozone Monitoring Instrument (OMI) and the Tropospheric Monitoring Instrument (TROPOMI) that typically have spectral resolutions of the order of 0.5 nm or better and spatial footprints as small as 3.6 km × 5.6 km. These NO 2 observations are used to estimate emissions, monitor pollution trends, and study effects on human health. Here, we investigate whether it is possible to retrieve NO 2 amounts with lower-spectral-resolution hyperspectral imagers such as the Ocean Color Instrument (OCI) that will fly on the Plankton, Aerosol, Cloud, ocean Ecosystem (PACE) satellite set for launch in early 2024. OCI will have a spectral resolution of 5 nm and a spatial resolution of ∼ 1 km with global coverage in 1–2 d. At this spectral resolution, small-scale spectral structure from NO 2 absorption is still present. We use real spectra from the OMI to simulate OCI spectra that are in turn used to estimate NO 2 slant column densities (SCDs) with an artificial neural network (NN) trained on target OMI retrievals. While we obtain good results with no noise added to the OCI simulated spectra, we find that the expected instrumental noise substantially degrades the OCI NO 2 retrievals. Nevertheless, the NO 2 information from OCI may be of value for ocean color retrievals. OCI retrievals can also be temporally averaged over timescales of the order of months to reduce noise and provide higher-spatial-resolution maps that may be useful for downscaling lower-spatial-resolution data provided by instruments such as OMI and TROPOMI; this downscaling could potentially enable higher-resolution emissions estimates and be useful for other applications. In addition, we show that NNs that use coefficients of leading modes of a principal component analysis of radiance spectra as inputs appear to enable noise reduction in NO 2 retrievals. Once trained, NNs can also substantially speed up NO 2 spectral fitting algorithms as applied to OMI, TROPOMI, and similar instruments that are flying or will soon fly in geostationary orbit.

NO2↗
NASA NTRS2011

Measurement of the Noise Resulting from the Interaction of Turbulence with a Lifting Surface

An experimental study of the noise resulting from the interaction of an airfoil with incident turbulence is presented. The test models include NACA0015 airfoils of different chord lengths, a flat plate with a sharp leading edge, and an airfoil of same section as a reference Fowler flap. The airfoils are immersed in nearly isotropic turbulence. Two approaches for performing the noise measurements are used and compared. The effects that turbulence intensity and scales, airfoil geometry, velocity and angle of attack have on the incident turbulence interaction noise are examined. Detailed directivity measurements are presented. It is found that noise spectral levels beyond the peak frequency decrease more with decreasing airfoil leading edge sharpness, and that spectral peak level (at 0 deg. angle of attack) appears to be mostly controlled by the airfoil fs thickness and chord. Increase in turbulence scale and intensity are observed to lead to a uniform increase of the noise spectral levels with an LI(sup 2) dependence (where L is the turbulence longitudinal integral scale and I is the turbulence intensity). Noise levels are found to scale with the 6th power of velocity and the 2nd power of the airfoil chord. Sensitivity to changes in angle of attack appears to have a turbulence longitudinal integral scale to chord (C) ratio dependence, with large effects on noise for L/C greater than or equal to 1 and decreased effects as L/C becomes smaller than 1. For all L/C values, the directivity pattern of the noise resulting from the incident turbulence is seen to remain symmetric with respect to the direction of the mean flow until stall, at which point, the directivity becomes symmetric with respect to the airfoil chord. It is also observed that sensitivity to angle of attack changes is more pronounced on the model suction side than on the model pressure side, and in the higher frequency range of the spectra for the largest airfoils tested (L/C less than 0.24).

Hutcheson, Florence V.↗
DOE OSTI2023

Temperature Dependence of Low‐Frequency Noise Characteristics of NiO x /β‐Ga 2 O 3 p–n Heterojunction Diodes

Temperature dependence of the low-frequency electronic noise in NiO x /β-Ga 2 O 3 p–n heterojunction diodes is reported. The noise spectral density is of the 1/f-type near room temperature but shows signatures of Lorentzian components at elevated temperatures and at higher current levels (f is the frequency). It is observed that there is an intriguing non-monotonic dependence of the noise on temperature near T = 380 K. The Raman spectroscopy of the device structure suggests material changes, which results in reduced noise above this temperature. The normalized noise spectral density in such diodes is determined to be on the order of 10 −14 cm 2 Hz −1 (f = 10 Hz) at 0.1 A cm −2 current density. In terms of the noise level, NiO x /β-Ga 2 O 3 p–n diodes perform excellently for new technology and occupy an intermediate position among devices of various designs implemented with different ultra-wide-bandgap semiconductors. The obtained results are important for understanding the electronic properties of NiO x /β-Ga 2 O 3 heterojunctions and contribute to the development of noise spectroscopy as the quality assessment tool for new electronic materials and device technologies.

1/f noise↗