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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 199 records · Page 11
All sourcesNASA NTRSDOE OSTI
NASA NTRS1998

Empirical Mode Decomposition and Hilbert Spectral Analysis

The difficult facing data analysis is the lack of method to handle nonlinear and nonstationary time series. Traditional Fourier-based analyses simply could not be applied here. A new method for analyzing nonlinear and nonstationary data has been developed. The key part is the Empirical Mode Decomposition (EMD) method with which any complicated data set can be decomposed into a finite and often small number of Intrinsic Mode Functions (IMF) that serve as the basis of the representation of the data. This decomposition method is adaptive, and, therefore, highly efficient. The IMFs admit well-behaved Hilbert transforms, and yield instantaneous energy and frequency as functions of time that give sharp identifications of imbedded structures. The final presentation of the results is an energy-frequency-time distribution, designated as the Hilbert Spectrum. Among the main conceptual innovations is the introduction of the instantaneous frequencies for complicated data sets, which eliminate the need of spurious harmonics to represent nonlinear and nonstationary signals. Examples from the numerical results of the classical nonlinear equation systems and data representing natural phenomena are given to demonstrate the power of this new method. The classical nonlinear system data are especially interesting, for they serve to illustrate the roles played by the nonlinear and nonstationary effects in the energy-frequency-time distribution.

Huang, Norden E.↗
NASA NTRS1999

Spectral Analysis of Vibrational Harmonic Motion by use of a Continuous-Wave CO2 Doppler Lidar

Vibrational motion of a harmonic oscillator was investigated using a focused continuous wave CO2 Doppler lidar at 9.1 microns wavelength. A continuum of frequencies along with many discrete, equally spaced, resonant frequency modes was observed. The frequency modes are similar in structure to the oscillatory longitudinal modes of a laser cavity and arise because of interference of the natural resonant frequency of the oscillator with specific frequencies within the continuum. The spectra revealed departures from linear motion for vigorous vibrations of the oscillator. Each consecutive resonant frequency mode occurred for a movement of the oscillator much less than the wavelength of incident lidar radiation.

Jarzembski, Maurice A.↗
NASA NTRS2003

Applications of Hilbert Spectral Analysis for Speech and Sound Signals

A new method for analyzing nonlinear and nonstationary data has been developed, and the natural applications are to speech and sound signals. The key part of the method is the Empirical Mode Decomposition method with which any complicated data set can be decomposed into a finite and often small number of Intrinsic Mode Functions (IMF). An IMF is defined as any function having the same numbers of zero-crossing and extrema, and also having symmetric envelopes defined by the local maxima and minima respectively. The IMF also admits well-behaved Hilbert transform. This decomposition method is adaptive, and, therefore, highly efficient. Since the decomposition is based on the local characteristic time scale of the data, it is applicable to nonlinear and nonstationary processes. With the Hilbert transform, the Intrinsic Mode Functions yield instantaneous frequencies as functions of time, which give sharp identifications of imbedded structures. This method invention can be used to process all acoustic signals. Specifically, it can process the speech signals for Speech synthesis, Speaker identification and verification, Speech recognition, and Sound signal enhancement and filtering. Additionally, as the acoustical signals from machinery are essentially the way the machines are talking to us. Therefore, the acoustical signals, from the machines, either from sound through air or vibration on the machines, can tell us the operating conditions of the machines. Thus, we can use the acoustic signal to diagnosis the problems of machines.

Huang, Norden E.↗
NASA NTRS2004

A Spectral Analysis Approach for Acoustic Radiation from Composite Panels

A method is developed to predict the vibration response of a composite panel and the resulting far-field acoustic radiation due to acoustic excitation. The acoustic excitation is assumed to consist of obliquely incident plane waves. The panel is modeled by a finite element analysis and the radiated field is predicted using Rayleigh's integral. The approach can easily include other effects such as shape memory alloy (SMA) ber reinforcement, large detection thermal postbuckling, and non-symmetric SMA distribution or lamination. Transmission loss predictions for the case of an aluminum panel excited by a harmonic acoustic pressure are shown to compare very well with a classical analysis. Results for a composite panel with and without shape memory alloy reinforcement are also presented. The preliminary results demonstrate that the transmission loss can be significantly increased with shape memory alloy reinforcement. The mechanisms for further transmission loss improvement are identified and discussed.

Turner, Travis L.↗
NASA NTRS2006

Thickness of the Magnetic Crust of Mars from Magneto-Spectral Analysis

Previous analysis of the magnetic spectrum of Mars showed only a crustal source field. The observational spectrum was fairly well fitted by the spectrum expected from random dipolar sources scattered on a spherical shell about 46 plus or minus 10 km below Mars' 3389.5 km mean radius. This de-correlation depth overestimates the typical depth of extended magnetized structures, and so was judged closer to mean source layer thickness than twice its value. To better estimate the thickness of the magnetic crust of Mars, six different magnetic spectra were fitted with the theoretical spectrum expected from a novel, bimodal distribution of magnetic sources. This theoretical spectrum represents both compact and extended, laterally correlated sources, so source shell depth is doubled to obtain layer thickness. The typical magnetic crustal thickness is put at 47.8 plus or minus 8.2 km. The extended sources are enormous, typically 650 km across, and account for over half the magnetic energy at low degrees. How did such vast regions form?

Voorhies, Coerte V.↗
NASA NTRS2010

Regional Mapping and Spectral Analysis of Mounds in Acidalia Planitia, Mars

Acidalia Planitia is a approx.3000 km diameter planum located in the northern plains of Mars. It is believed to be a sedimentary basin containing an accumulation of sediments brought by Hesperian outflow channels that drained the Highlands. A large number of high-albedo mounds have been identified across this basin [1-2] and understanding the process that formed them should help us understand the history of this region. Farrand et al. [2] showed that the mounds are dark in THEMIS (Thermal Emission Imaging System) nighttime IR (infrared) image data. This implies that the mounds have a lower thermal inertia than the surrounding plains (Fig. 1), suggesting that the material of the mounds is fine-grained or unconsolidated. Farrand et al. [2] also reviewed potential analogs for the mounds and concluded that a combination of mud volcanoes with evaporites around geysers or springs is most consistent with all the data. We have built on this work by creating regional maps of the features and analyzing CRISM (Compact Reconnaissance Imaging Spectrometer for Mars) data to see if there are mineralogical differences between the mounds and surrounding plains.

Amador, E. S.↗
NASA NTRS2009

A Comprehensive Spectral Analysis of the X-Ray Pulsar 4U 1907+09 from Two Observations with the Suzaku X-Ray Observatory

We present results from two observations of the wind-accreting X-ray pulsar 4U 1907+09 using the Suzaku observatory, The broadband time-averaged spectrum allows us to examine the continuum emission of the source and the cyclotron resonance scattering feature at approx. 19 keV. Additionally, using the narrow CCD response of Suzaku near 6 ke V allows us to study in detail the Fe K bandpass and to quantify the Fe Kp line for this source for the first time. The source is absorbed by fully-covering material along the line of sight with a column density of N(sub H) approx. 2 x 10(exp 22)/sq cm, consistent with a wind accreting geometry, and a high Fe abundance (approx. 3 - 4 x solar). Time and phase-resolved analyses allow us to study variations in the source spectrum. In particular, dips found in the 2006 observation which are consistent with earlier observations occur in the hard X-ray bandpass, implying a variation of the whole continuum rather than occultation by intervening material, while a dip near the end of the 2007 observation occurs mainly in the lower energies implying an increase in NH along the line of sight, perhaps indicating clumpiness in the stellar wind

Rivers, Elizabeth↗
NASA NTRS2013

Application of Spectral Analysis Techniques in the Intercomparison of Aerosol Data: 1. an EOF Approach to the Spatial-Temporal Variability of Aerosol Optical Depth Using Multiple Remote Sensing Data Sets

Many remote sensing techniques and passive sensors have been developed to measure global aerosol properties. While instantaneous comparisons between pixel-level data often reveal quantitative differences, here we use Empirical Orthogonal Function (EOF) analysis, also known as Principal Component Analysis, to demonstrate that satellite-derived aerosol optical depth (AOD) data sets exhibit essentially the same spatial and temporal variability and are thus suitable for large-scale studies. Analysis results show that the first four EOF modes of AOD account for the bulk of the variance and agree well across the four data sets used in this study (i.e., Aqua MODIS, Terra MODIS, MISR, and SeaWiFS). Only SeaWiFS data over land have slightly different EOF patterns. Globally, the first two EOF modes show annual cycles and are mainly related to Sahara dust in the northern hemisphere and biomass burning in the southern hemisphere, respectively. After removing the mean seasonal cycle from the data, major aerosol sources, including biomass burning in South America and dust in West Africa, are revealed in the dominant modes due to the different interannual variability of aerosol emissions. The enhancement of biomass burning associated with El Niño over Indonesia and central South America is also captured with the EOF technique.

variability↗
NASA NTRS2014

Application of Spectral Analysis Techniques in the Intercomparison of Aerosol Data: Part III. Using Combined PCA to Compare Spatiotemporal Variability of MODIS, MISR and OMI Aerosol Optical Depth

Satellite measurements of global aerosol properties are very useful in constraining aerosol parameterization in climate models. The reliability of different data sets in representing global and regional aerosol variability becomes an essential question. In this study, we present the results of a comparison using combined principal component analysis (CPCA), applied to monthly mean, mapped (Level 3) aerosol optical depth (AOD) product from Moderate Resolution Imaging Spectroradiometer (MODIS), Multiangle Imaging Spectroradiometer (MISR), and Ozone Monitoring Instrument (OMI). This technique effectively finds the common space-time variability in the multiple data sets by decomposing the combined AOD field. The results suggest that all of the sensors capture the globally important aerosol regimes, including dust, biomass burning, pollution, and mixed aerosol types. Nonetheless, differences are also noted. Specifically, compared with MISR and OMI, MODIS variability is significantly higher over South America, India, and the Sahel. MODIS deep blue AOD has a lower seasonal variability in North Africa, accompanied by a decreasing trend that is not found in either MISR or OMI AOD data. The narrow swath of MISR results in an underestimation of dust variability over the Taklamakan Desert. The MISR AOD data also exhibit overall lower variability in South America and the Sahel. OMI does not capture the Russian wild fire in 2010 nor the phase shift in biomass burning over East South America compared to Central South America, likely due to cloud contamination and the OMI row anomaly. OMI also indicates a much stronger (boreal) winter peak in South Africa compared with MODIS and MISR.

satellite observation↗
NASA NTRS2015

Spectral Analysis of Forecast Error Investigated with an Observing System Simulation Experiment

The spectra of analysis and forecast error are examined using the observing system simulation experiment (OSSE) framework developed at the National Aeronautics and Space Administration Global Modeling and Assimilation Office (NASAGMAO). A global numerical weather prediction model, the Global Earth Observing System version 5 (GEOS-5) with Gridpoint Statistical Interpolation (GSI) data assimilation, is cycled for two months with once-daily forecasts to 336 hours to generate a control case. Verification of forecast errors using the Nature Run as truth is compared with verification of forecast errors using self-analysis; significant underestimation of forecast errors is seen using self-analysis verification for up to 48 hours. Likewise, self analysis verification significantly overestimates the error growth rates of the early forecast, as well as mischaracterizing the spatial scales at which the strongest growth occurs. The Nature Run-verified error variances exhibit a complicated progression of growth, particularly for low wave number errors. In a second experiment, cycling of the model and data assimilation over the same period is repeated, but using synthetic observations with different explicitly added observation errors having the same error variances as the control experiment, thus creating a different realization of the control. The forecast errors of the two experiments become more correlated during the early forecast period, with correlations increasing for up to 72 hours before beginning to decrease.

OSSE↗
NASA NTRS2019

Spectral Properties of Hydrated Poorly Crystalline Materials for Spectral Analysis of the Moon and Mars

Visible/near-infrared (VNIR) reflectance spectra of both Mars [1] and the Moon [2] include hydration bands that vary across the planet and are not well explained in some cases. Poorly crystalline phases have been found at ~30-70 wt.% by CheMin in Gale crater, Mars in all samples measured to date [3]. Here we report on VNIR reflectance spectra of a large collection of amorphous and poorly crystalline materials. These include opal, allophane, imogolite, iron hydroxides/ oxyhydroxides (FeOx), and several synthetic materials containing Si, Al and/or Fe. All of these contain hydration bands due to water and OH that can be used to identify these materials remotely on planetary bodies.

Bishop, J. L.↗