Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “spectral statistics”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 703 records · Page 39

MAC to VAX Connectivity: Heartrate Spectral Analysis System

The heart rate Spectral Analysis System (SAS) acquires and analyzes, in real-time, the Space Shuttle onboard electrocardiograph (EKG) experiment signals, calculates the heartrate, and applies a Fast Fourier Transformation (FFT) to the heart rate. The system also calculates other statistical parameters such as the 'mean heart rate' over specific time period and heart rate histogram. This SAS is used by NASA Principal Investigators as a research tool to determine the effects of weightlessness on the human cardiovascular system. This is also used to determine if Lower Body Negative Pressure (LBNP) is an effective countermeasure to the orthostatic intolerance experienced by astronauts upon return to normal gravity. In microgravity, astronauts perform the LBNP experiment in the mid deck of the Space Shuttle. The experiment data are downlinked by the orbiter telemetry system, then processed and analyzed in real-time by the integrated Life Sciences Data Acquisition (LSDS) - Spectral Analysis System. The data system is integrated within the framework of two different computer systems, VAX and Macintosh (Mac), using the networking infrastructure to assist the investigators in further understanding the most complex machine on Earth--the human body.

Rahman, Hasan H.↗

Statistical Hypothesis Testing in Wavelet Analysis: Theoretical Developments and Applications to Indian Rainfall

Statistical hypothesis tests in wavelet analysis are methods that assess the degree to which a wavelet quantity(e.g., power and coherence) exceeds background noise. Commonly, a point-wise approach is adopted in which a wavelet quantity at every point in a wavelet spectrum is individually compared to the critical level of the point-wise test. However, because adjacent wavelet coefficients are correlated and wavelet spectra often contain many wavelet quantities, the point-wise test can produce many false positive results that occur in clusters or patches. To circumvent the point-wise test drawbacks, it is necessary to implement the recently developed area-wise, geometric, cumulative area-wise, and topological significance tests, which are reviewed and developed in this paper. To improve the computational efficiency of the cumulative area-wise test, a simplified version of the testing procedure is created based on the idea that its output is the mean of individual estimates of statistical significance calculated from the geometric test applied at a set of point-wise significance levels. Ideal examples are used to show that the geometric and cumulative area-wise tests are unable to differentiate wavelet spectral features arising from singularity-like structures from those associated with periodicities. A cumulative arc-wise test is therefore developed to strictly test for periodicities by using normalized arc length, which is defined as the number of points composing a cross section of a patch divided by the wavelet scale in question. A previously proposed topological significance test is formalized using persistent homology profiles (PHPs) measuring the number of patches and holes corresponding to the set of all point-wise significance values. Ideal examples show that the PHPs can be used to distinguish time series containing signal components from those that are purely noise. To demonstrate the practical uses of the existing and newly developed statistical methodologies, a first comprehensive wavelet analysis of Indian rainfall is also provided. An R software package has been written by the author to implement the various testing procedures.

Wind speed↗

Seasonal Patterns and Remote Spectral Estimation of Canopy Chemistry Across the Oregon Transect

We examined seasonal changes in canopy chemical concentrations and content in conifer forests growing along a climate gradient in western Oregon, as part of the Oregon Transect Ecosystem Research (OTTER) study. The chemical variables were related to seasonal patterns of growth and production. Statistical comparisons of chemical variables with data collected from two different airborne remote-sensing platforms were also carried out. Total nitrogen (N) concentrations in foliage varied significantly both seasonally and among sites; when expressed as content in the forest canopy, nitrogen varied to a much greater extent and was significantly related to aboveground net primary production (r = 0.99). Chlorophyll and free amino acid concentrations varied more strongly than did total N and may have reflected changes in physiological demands for N. Large variations in starch concentrations were measured from pre- to post-budbreak in all conifer sites. Examination of remote-sensing data from two different airborne instruments suggests the potential for remote measurement of some canopy chemicals. Multivariate analysis of high-resolution spectral data in the near infrared region indicated significant correlations between spectral signals and N concentration and canopy N content; the correlation with canopy N content was stronger and was probably associated in part with water absorption features of the forest canopy. The spectral bands that were significantly correlated with lignin concentration and content were similar to bands selected in the other laboratory and airborne studies; starch concentrations were not significantly related to spectral reflectance data. Strong relationships between the spectral position of specific reflectance features in the visible region and chlorophyll were also found.

Matson, Pamela↗

Experimental investigation of turbulent wake flows in a helically wrapped rod bundle in presence of localized blockages

In nuclear sodium fast reactors, bundles of rods are tightly packed into a triangular lattice, enclosed in a hexagonal duct, and each pin is spirally wrapped with a thin wire. Flow blockages can potentially impact the local flow characteristics and heat transfer mechanisms in the bundle due to its small subchannel size. The effects of the blockage on the flow structures and heat transfer mechanisms are important aspects that require an accurate investigation. In this study, the flow-field characteristics in the vicinity of a blockage located in the exterior subchannel of rod bundles with helically wrapped wires were experimentally investigated. The velocity fields in the exterior subchannel were acquired by applying matched-index-of-refraction and time-resolved particle image velocimetry (TR-PIV) techniques for Reynolds numbers of Re 1 = 4000 and Re 2 = 17 000, i.e., equivalent to Rew 1 = 19 600 and Rew 2 = 83 200, respectively, based on the blockage width. The results from the TR-PIV measurements revealed an arch-shaped vortex with a large flow recirculation and a pair of counter-rotating vortices in the wake region downstream of the blockage, which is commonly observed in the wake flow of bluff bodies. The relative lateral distance and angle between the two vortices decreased when the Reynolds numbers increased. Profiles of maximum turbulence intensity along the shear layers illustrated the transition process including the growth, peak, and decay along the flow direction. From the spectral analysis of the turbulent velocities extracted at points along the shear layer, the Strouhal numbers ( St ) representing the vortex shedding frequency were found to be St = 0.25 and St = 0.56 for the left and right shear layers, respectively. Characteristics of shear layers generated by the blockage in the exterior subchannel were investigated via the two-point cross correlation of fluctuating velocities. The patiotemporal cross correlations of turbulent velocities, computed at points in the region where the left shear layer exhibited rolling effects and vortex breakdowns, were considerably wider and longer. The convection velocity U c was estimated to be ~0.82 U m to 0.93 U m . Proper orthogonal decomposition (POD) analysis was applied to the instantaneous velocity fields to extract the statistically dominant flow structures. It was found that POD modes 2–3 and 4–5 formed the pair modes when the corresponding POD temporal coefficients depicted sinusoidal shapes and exhibited nearly circular orbits in the phase space. Spectral analysis of the POD temporal coefficients confirmed the vortex shedding frequencies detected in the analysis of turbulent velocities.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

As-built design specification for PARHIS

The program is part of the CLASFYG package. It produces histograms of the greeness profile derived parameters alpha, beta, t sub o, and chi squared, which are computed by the CLASFYG program. Alpha is the approximate greeness rise time, beta is the approximate greeness decay time, t sub o is the spectral crop emergence date, and chi squared per degree of freedom is the goodness of fit of the actual data to the computed greeness profile. The program also produces statistical information concerning the parameters.

Tompkins, M. A.↗

Oregon trails revisted

Oregon State University's Environmental Remote Sensing Applications Laboratory (ERSAL) has six full-time researchers with expertise in a variety of biological, Earth, atmospheric and computer sciences as well as image interpretation and statistical techniques. The primary emphasis of the ERSAL research and demonstration program is the development and application of remote sensing technology in operational resource management programs. LANDSAT multi-spectral, multi-date digital data and imagery are utilized in concert with high altitude NASA-acquired photography, low altitude ERSAL-acquired photography, and field observations and data to provide customized, inexpensive and useful final products. Synopses are given of 9 applications projects conducted in Oregon.

Lewis, A. J.↗

Oscillations in D-region absorption at periods of one to two months

One to two month oscillations in D-region absorption are found in seven years of daily f-min data from low latitude stations at Singapore (1N, 104E) and Rarotonga (21S, 160W). Coherency (cross-spectral) analyses reveal that solar flux variations account for much of the f-min variance at these periods. Over the range of periods from 10 to 200 days, statistically significant linear correlation is found between the f-min time series and contemporaneous 10.7 cm solar flux mearurements at periods of 16 to 19 days, the 26 to 29 day solar rotation band, and a broad band covering 43 to 80 day periods.

Stanford, J. L.↗

Observations of 20-day period meridional current oscillations in the upper ocean along the Pacific Equator

Prominent oscillations of the meridional current, with a mean period of approximately 20 days, is observed in the upper ocean from May 1979 to October 1985 using moored current measurements along the Pacific equator at 95, 110, 124, 140, and 152 deg W, as well as off (but near) the equator at 110 and 140 deg W. The fluctuations are relatively narrowband in frequency. A 95 percent statistically significant peak in the power spectra of the meridional current occurs at 110, 124, and 140 deg W, but not at 95 and 152 deg W where the spectral peaks are smaller. The dominant wave period decreases by about 4 percent from 110 to 140 deg W. The wave amplitude decreases with depth, and the wave is essentially confined to the upper 80 m. The penetration depth of the oscillation is greatest at 110 deg W and least at 140 deg W.

Halpern, David↗

Oscillations in D-region absorption at periods of one to two months

One to two month oscillations in D-region absorption are found in seven years of daily f-min data from low latitude stations at Singapore (1 deg N, 104 deg E) and Rarotonga (21 deg S, 160 deg W). Coherency (cross-spectral) analyses reveal that solar flux variations account for much of the f-min variance at these periods. Over the range of periods from 10 to 200 days, statistically significant linear correlation is found between the f-min time series and contemporaneous 10.7 cm solar flux measurements at periods of 16-19 days, the 26-29 day solar rotation band, and a broad band covering 43-80 day periods.

Stanford, J. L.↗

Momentum and heat flux estimation in the planetary boundary layer (PBL) with a 10.6-micron Doppler lidar

The mean wind, its standard deviation, and the momentum fluxes in the PBL are estimated with a 10.6-micron Doppler lidar. Spectral analysis of the radial velocities was performed, from which, by examining the amplitude of the power spectrum at the inertial range, the kinetic energy dissipation was deduced. The statistical form of the Navier-Stokes equations was used to derive the surface heat flux as the residual balance between the vertical gradient of the third moment of the vertical velocity and the kinetic energy dissipation.

Gal-Chen, Tzvi↗

The amplitude and spectral index of the large angular scale anisotropy in the cosmic microwave background radiation

In many cosmological models, the large angular scale anisotropy in the cosmic microwave background is parameterized by a spectral index, n, and a quadrupolar amplitude, Q. For a Harrison-Peebles-Zel'dovich spectrum, n = 1. Using data from the Far Infrared Survey (FIRS) and a new statistical measure, a contour plot of the likelihood for cosmological models for which -1 less than n less than 3 and 0 equal to or less than Q equal to or less than 50 micro K is obtained. Depending upon the details of the analysis, the maximum likelihood occurs at n between 0.8 and 1.4 and Q between 18 and 21 micro K. Regardless of Q, the likelihood is always less than half its maximum for n less than -0.4 and for n greater than 2.2, as it is for Q less than 8 micro K and Q greater than 44 micro K.

Ganga, Ken↗

Photoemission of Single Dust Grains for Heliospheric Conditions

Initial results of an experiment to measure the photoemission of single dust grains as a function of far ultraviolet wavelengths are presented. Coulombic forces dominate the interaction of the dust grains in the heliosphere. Knowledge of the charge state of dust grains, whether in a dusty plasma (Debye length < intergrain distance) or in the diffuse interplanetary region, is key to understanding their interaction with the solar wind and other solar system constituents. The charge state of heliospheric grains is primarily determined by primary electron and ion collisions, secondary electron emission and photoemission due to ultraviolet sunlight. We have established a unique experimental technique to measure the photoemission of individual micron-sized dust grains in vacuum. This technique resolves difficulties associated with statistical measurements of dust grain ensembles and non-static dust beams. The photoemission yield of Aluminum Oxide 3-micron grains For wavelengths from 120-300 nm with a spectral resolution of 1 nm FWHM is reported. Results are compared to interplanetary conditions.

Spann, James F., Jr.↗

Detection of Northern Hemisphere Transient Baroclinic Eddies at Gale Crater Mars

The Rover Environmental Monitoring Station (REMS) on the Mars Science Laboratory’s (MSL) Curiosity rover has been operating in Gale Crater Mars (4.5°S, 137.4°E) for over 2 Mars years. Analysis of its pressure data, which have a precision of approximately 0.2 Pa (see Haberle et al., 2014; Harri et al., 2014), reveal temporal oscillations in its seasonally de-trended daily averaged pressures at some seasons with 2-5 Pa amplitudes that have periods similar to those observed at the Viking Lander 2 (VL-2) site (48.3°N, 134.0°E) several decades ago. As illustrated in Fig 1 there are clear peaks in the variance at a frequency f approximately 0.45 and 0.06 per sol for the fall season of Mars Year (MY) 31, and at f approximately 0.15 and 0.06 per sol for MY 32. These frequencies correspond to periods of 2.2, 6.7, and 16.7 sols, and are very similar to those observed at VL-2 (Fig 2, and see Barnes, 1980). Since orbital imaging data show dust frontal systems associated with eastward traveling baroclinic eddies that occasionally cross the equator (Wang et al., 2003), these findings suggest that MSL may be seeing their signature in its pressure data. To make this case we show that (a) the spectral peaks in the MSL are not only similar to those at VL-2, they have the same seasonal variation, (b) at least for some seasons the peaks are statistically significant and not likely due to random noise in the data, and (c) Global Circulation Model (GCM) results from the Ames GCM support this interpretation.

The Rover Environmental Monitoring Station (REMS)↗

Estimation of spectral emissivity in the thermal infrared

A number of algorithms are available in the literature that attempt to remove most of the effects of temperature from thermal multispectral data where the final goal is to extract emissivity differences. Early approaches include adjacent spectral band ratioing, broad band radiance normalization and the use of one band where emissivities are generally high (e.g., 11 to 12 micrometers) to determine the temperature. More recent work has produced two techniques that use data averaging to extract temperature to leave a quantity related to emissivity changes. These two techniques have been investigated and compared and appear to provide reasonable results. The analysis presented in this paper develops a thermal IR multispectral temperature/emissivity estimation procedure based on formal estimation theory, Gaussian statistics, and a stochastic radiance signal model including the effects of both temperature and emissivity. The importance of this work is that this is an optimal estimation procedure which will provide minimum variance estimates of temperature and emissivity changes directly. Section 2 discusses optimal linear spectral emissivity estimation and Section 3 is a summary.

Kryskowski, David↗

Statistical Classification of Biosignature Information using Multiple Instrument Observations

The accurate identification of biosignatures (indications of life) from data taken from remote or in situ planetary exploration is one of the most important challenges in astrobiology, the interdisciplinary field examining habitability and the potential for extraterrestrial life. This study employs machine learning algorithms to optimize the identification of biosignatures, with an emphasis on those which are agnostic to a specific biochemical basis. We exploit the wealth of terrestrial data available from biogenic and abiogenic systems to enhance efficient feature prioritization. Our dataset, pulled from public databases and laboratory recorded measurements, includes elemental abundance, isotopic fractionation, and VNIR/Raman spectra The data curation process included standardization for detection limits and ranges. Subsequent feature extraction yielded detailed inputs for machine learning, including combinations of elemental content, isotopic ratios, and parameters of spectral peaks and troughs. Feature significance was evaluated across diverse machine learning methodologies, such as k-nearest neighbors, logistic regression, Random Forest, support vector machines, and Gaussian Naïve Bayes, along with a combined voting classifier. We utilized Receiver Operating Characteristic Area Under the Curve (ROC AUC) across 2,000 50% test-train splits as a robust metric of model performance. Results revealed a promising ROC AUC of 0.853 for the combined voting classifier. Removing elemental abundance data notably reduced model accuracy (13% decrease in AUC), highlighting its critical role in biosignature detection. Several other individual data features exhibited significance within their respective data types, offering additional granularity. This research fortifies the relevance of machine learning to astrobiology, potentially enhancing life detection missions by allowing algorithmic prioritization of high-interest samples for further investigation. Future work will refine data standardization, expand the dataset to include more terrestrial systems, and incorporate convolutional neural networks for spectral feature extraction. The potential for public data sharing is also under exploration, reinforcing our commitment to collective scientific advancement.

Statistical↗

Atomic Data and Spectral Line Intensities for Ar XII

Electron impact collision strengths; energy levels; oscillator strengths and spontaneous radiative decay rates are calculated for Ar XII. The configurations used are 2s(exp 2)2p(exp 3), 2s2p(exp4), 2p(exp 5), 2s22p23s, 2s(exp 2)2p(exp 2)3p, and 2s(exp 2)2p(exp 2)3d giving rise to 72 fine-structure levels in intermediate coupling. Collision strengths are calculated at five incident energies: 35,70, 105, 140 and 175 Ry. They are complemented by Coulomb-Born limits towards infinite collision energy for forbidden transitions and line strengths for optically allowed transitions. Excitation rate coefficients are calculated as a function of electron temperature by assuming a Maxwellian electron velocity distribution. Using the excitation rate coefficients and the radiative transition rates, statistical equilibrium equations for level populations are solved at electron densities covering the range of 10(exp 8)-101(exp 14) cm(exp -3) at an electron temperature of log T(sub e)/K = 6.4, corresponding to maximum abundance of Ar XII. Relative spectral line intensities are calculated.

Eissner, W.↗

Visualization techniques to aid in the analysis of multi-spectral astrophysical data sets

The goal of this project was to support the scientific analysis of multi-spectral astrophysical data by means of scientific visualization. Scientific visualization offers its greatest value if it is not used as a method separate or alternative to other data analysis methods but rather in addition to these methods. Together with quantitative analysis of data, such as offered by statistical analysis, image or signal processing, visualization attempts to explore all information inherent in astrophysical data in the most effective way. Data visualization is one aspect of data analysis. Our taxonomy as developed in Section 2 includes identification and access to existing information, preprocessing and quantitative analysis of data, visual representation and the user interface as major components to the software environment of astrophysical data analysis. In pursuing our goal to provide methods and tools for scientific visualization of multi-spectral astrophysical data, we therefore looked at scientific data analysis as one whole process, adding visualization tools to an already existing environment and integrating the various components that define a scientific data analysis environment. As long as the software development process of each component is separate from all other components, users of data analysis software are constantly interrupted in their scientific work in order to convert from one data format to another, or to move from one storage medium to another, or to switch from one user interface to another. We also took an in-depth look at scientific visualization and its underlying concepts, current visualization systems, their contributions, and their shortcomings. The role of data visualization is to stimulate mental processes different from quantitative data analysis, such as the perception of spatial relationships or the discovery of patterns or anomalies while browsing through large data sets. Visualization often leads to an intuitive understanding of the meaning of data values and their relationships by sacrificing accuracy in interpreting the data values. In order to be accurate in the interpretation, data values need to be measured, computed on, and compared to theoretical or empirical models (quantitative analysis). If visualization software hampers quantitative analysis (which happens with some commercial visualization products), its use is greatly diminished for astrophysical data analysis. The software system STAR (Scientific Toolkit for Astrophysical Research) was developed as a prototype during the course of the project to better understand the pragmatic concerns raised in the project. STAR led to a better understanding on the importance of collaboration between astrophysicists and computer scientists.

Brugel, Edward W.↗