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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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Use spectrometers to monitor high explosive (HE) events in infrared region: Spectrometers measure radiance in many (100s) of spectral bands; Sensors give information on the fireball such as temperature, size, soot quantity and gas species concentrations (CO, CO₂, H₂O, etc.).
Recent breakthroughs in remote sensing technology have led to the development of a spaceborne high spectral resolution imaging sensor, HIRIS, to be launched in the mid-1990s for observation of earth surface features. The effects of organic carbon content on soil reflectance over the spectral range of HIRIS, and to examine the contributions of humic and fulvic acid fractions to soil reflectance was evaluated. Organic matter from four Indiana agricultural soils was extracted, fractionated, and purified, and six individual components of each soil were isolated and prepared for spectral analysis. The four soils, ranging in organic carbon content from 0.99 percent, represented various combinations of genetic parameters such as parent material, age, drainage, and native vegetation. An experimental procedure was developed to measure reflectance of very small soil and organic component samples in the laboratory, simulating the spectral coverage and resolution of the HIRIS sensor. Reflectance in 210 narrow (10 nm) bands was measured using the CARY 17D spectrophotometer over the 400 to 2500 nm wavelength range. Reflectance data were analyzed statistically to determine the regions of the reflective spectrum which provided useful information about soil organic matter content and composition. Wavebands providing significant information about soil organic carbon content were located in all three major regions of the reflective spectrum: visible, near infrared, and middle infrared. The purified humic acid fractions of the four soils were separable in six bands in the 1600 to 2400 nm range, suggesting that longwave middle infrared reflectance may be useful as a non-destructive laboratory technique for humic acid characterization.
The paper describes an improved method for calculating gamma-ray spectra of gamma-ray bursts. This method is independent of any assumed model for the incident spectrum. In many cases it makes it possible to perform chi-squared model fitting without detailed knowledge of the instrument response functions. The results of extensive calculations using simulated data and realistic response functions are presented; the Backus-Gilbert technique produces model-independent spectral estimates that are quantitatively accurate and easy to calculate.
Simultaneous acquisition of emission intensity from two channels in dual-color fluorescence measurements can be used to determine the spectral properties of an emitter. We detail a method to extract quantitative information from dual-color measurements by considering two models: a single spectral component model for peak wavelength determination and a dual spectral component model for relative strength determination. The former model is useful for spectral characterization and establishing heterogeneity within an emitter species, while the latter model is useful for analyzing energy transfer efficiency. Both models are formalized to yield probability distributions that reflect uncertainties due to shot noise. We applied these analysis tools to single-particle measurements of CdSe/CdS quantum dots. Isolated emitters had narrow spectral-intensity distributions that reflected their static emission profiles and fluorescence stability. Small assemblies of mixed donor/acceptor particles exhibited dynamic behavior where emission configuration changes reveal different spectral characteristics due to energy transfer.
This paper updates recent work to populate spectral databases for (near-) infrared sensing of solids in different modalities including passive and active sensing of minerals, ores and other mining chemicals and minerals.
The characteristics and extent of data which is obtainable by electromagnetic spectrum sensing and the application to earth resources survey are discussed. The wavelength and frequency ranges of operation for various remote sensors are tabulated. The spectral sensitivities of various sensing instruments are diagrammed. Examples of aerial photography to show the effects of lighting and seasonal variations on earth resources data are provided. Specific examples of multiband photography and multispectral imagery to crop analysis are included.
Stress in sunflowers was assessed in western and northwestern Minnesota. Weekly ground observations (acquired in 1980 and 1981) were analyzed in concert with large scale aerial photography and concurrent LANDSAT data. Using multidate supervised and unsupervised classification procedures, it was found that all crops grown in association with sunflowers in the study area are spectrally separable from one another. Under conditions of extreme drought, severely stressed plants were differentiable from those not severely stressed, but between-crop separation was not possible. Initial regression analyses to estimate sunflower seed yield showed a sensitivity to environmental stress during the flowering and seed development stages. One of the most important biological factors related to sunflower production in the Red River Valley area was found to be the extent and severity of insect infestations.
Recent observations of the photosphere using high spatial and temporal resolution show small dynamic features at or below the current resolving limits. A new pixel dynamics method has been developed to analyze spectral profiles and quantify changes in line displacement, width, asymmetry, and peakedness of photospheric absorption lines. The algorithm evaluates variations of line profile properties in each pixel and determines the statistics of such fluctuations averaged over all pixels in a given region. The method has been used to derive statistical characteristics of pixel fluctuations in observed quiet-Sun regions, an active region with no eruption, and an active region with an ongoing eruption. Using Stokes I images from the Vector Spectromagnetograph (VSM) of the Synoptic Optical Long-term Investigations of the Sun (SOLIS) telescope on 2012 March 13, variations in line width and peakedness of Fe i 6301.5 Å are shown to have a distinct spatial and temporal relationship with an M7.9 X-ray flare in NOAA 11429. This relationship is observed as stationary and contiguous patches of pixels adjacent to a sunspot exhibiting intense flattening in the line profile and line-center displacement as the X-ray flare approaches peak intensity, which is not present in area scans of the non-eruptive active region. The analysis of pixel dynamics allows one to extract quantitative information on differences in plasma dynamics on sub-pixel scales in these photospheric regions. The analysis can be extended to include the Stokes parameters and study signatures of vector components of magnetic fields and coupled plasma properties.
Estimating the emergence of a given crop, such as wheat or barley, is proposed using an analytic method which relies on the hypothesis that in the region (lambda = 0.70-1.35 microns) a given crop, after emergence, has a unique spectral profile in time. If the crop emerges early or late, relative to a reference standard determined for a given segment, the profile is displaced but has the same shape. Therefore, given the crop specific constants of the reference profile and a sufficient number of Landsat observations of reflectivity at specific times, the emergence date of a field can be determined.
The Optical Plume Anomaly Detection (OPAD) system is under development to provide early-warning failure detection in support of ground-level testing of the Space Shuttle Main Engine (SSME). Failure detection is to be achieved through the acquisition of spectrally resolved plume emissions and subsequent identification of abnormal levels indicative of engine corrosion or component failure. Two computer codes (one linear and the other non-linear) are used by the OPAD system to iteratively determine specific element concentrations in the SSME plume, given emission intensity and wavelength information. Since this analysis is extremely labor intensive, a study was initiated to develop neural networks that would model the 'inverse' of these computer codes. Optimally connected feed-forward networks with imperceptible prediction error have been developed for each element modeled by the linear code, SPECTRA4. Radial basis function networks were developed for the non-linear code, SPECTRA5, and predict combustion temperature in addition to element concentrations.
The use of polyvinyl alcohol as a binder for barium sulphate does not allow the intrinsically high reflectance of this material in the near vacuum ultraviolet to be optimally employed. In an effort to better utilize this property, completely inorganic coatings systems are described, where from the intrinsically high reflectance of barium sulphate in this spectral region can be gotten. Potassium sulphate turns out to be the preferred binder. Compositions, formulating procedures, and application techniques are included. For completeness, absolute and relative reflectance data are included for intra- and intersystem comparisons.
Elliptical patterns on emission lines of argon plasma jets attributed to antihalation backing during hypersensitization of film
Data collected on November 2, 1982 by the Landsat 4 Thematic Mapper (TM) over 72 forested sites in the Ridge and Valley province in Pennsylvania were compared with corresponding botanical and site variable field data. The analysis revealed that both the TM and the botanical data sets can be divided into four groups based on lithology and aspect. Lithology, which is clearly the dominant controlling factor in both sets of data, determines elevation and slope. The aspect (essentially north- and south-facing slope) determines the intensity of solar illumination which affects both the moisture available to the vegetation and the intensity of reflected radiance. Each of the four lithologic/aspect units support unique forest associations, clearly separable both on the basis of ground-based 1/10-acre forest association surveys and on the basis of their TM spectral signatures.
Intra-ply microcracking in unlined composite pressure vessels can be very troublesome to detect and when linked through the thickness can provide leak paths that may hinder mission success. The leaks may lead to loss of pressure/propellant, increased risk of explosion and possible cryo-pumping into air pockets within the laminate. Ultrasonic techniques have been shown capable of detecting the presence of microcracking and in this work they are used to quantify the level of microcracking. Resonance ultrasound methods are utilized with artificial neural networks to build a microcrack prediction/measurement tool. Two networks are presented, one unsupervised to provide a qualitative measure of microcracking and one supervised which provides a quantitative assessment of the level of microcracking. The resonant ultrasound spectroscopic method is made sensitive to microcracking by tuning the input spectrum to the higher frequency (shorter wavelength) components allowing more significant interaction with the defects. This interaction causes the spectral characteristics to shift toward lower amplitudes at the higher frequencies. As the density of the defects increases more interactions occur and more drastic amplitude changes are observed. Preliminary experiments to quantify the level of microcracking induced in graphite/epoxy composite samples through a combination of tensile loading and cryogenic temperatures are presented. Both unsupervised (Kohonen) and supervised (radial basis function) artificial neural networks are presented to determine the measurable effect on the resonance spectrum of the ultrasonic data taken from the samples.
Analysis of bacterial biofilms is particularly challenging and important with diverse applications from systems biology to biotechnology. Among the variety of techniques that have been applied, time-of-flight secondary ion mass spectrometry (ToF-SIMS) has many promising features in studying the surface characteristics of biofilms. ToF-SIMS offers high spatial resolution and high mass accuracy, which permit surface sensitive analysis of biofilm components. Thus, ToF-SIMS provides a powerful solution to addressing the challenge of bacterial biofilm analysis. This dataset covers ToF-SIMS analysis of Paenibacillus sp. 300A (300A) isolated from the Hanford site in Richland, WA. The strain is known to have metal and sulfur reducing properties and can be used for bioremediation, wastewater treatment, bioengineering and technology development. There is a current need to identify small molecules and fragments produced from bacterial biofilms. Static ToF-SIMS spectra of 300A were obtained using an IONTOF TOF-SIMS V instrument equipped with a 25 keV Bi 3 + metal ion gun. Identified molecules and molecular fragments are compared against known biological databases and the reported peaks have at least 65 ppm mass accuracy. These molecules range from lipids and fatty acids to flavonoids, quinolones, and other naturally occurring organic compounds. It is anticipated that the spectral identification of key peaks will assist detection of metabolites, extracellular polymeric substance molecules like polysaccharides, and biologically relevant small molecules using ToF-SIMS in future surface and interface research of bacterial biofilms.
In many practical applications, the accuracy of neutron transport calculations depends on an estimate of the energy distribution provided in the source definition. While the energy distribution of neutrons emitted by spontaneous fission sources is well-defined, the spectra of neutrons produced in (α,n) reactions in compound mixtures, such as americium-beryllium (AmBe), depend on the microstructural properties of the source material, which may vary. Although the energy of neutrons produced in nuclear reactions can be calculated from first principles, such computations require detailed knowledge of the key characteristics of the source material, which are often unknown. Here, this study focuses on deriving the at-birth neutron energy distribution for an AmBe source by applying reverse transport calculations to the externally measured high-precision spectrum recommended in the latest revision of the international standard. The derived at-birth spectrum was validated through indirect energy-sensitive neutron emission rate measurements of AmBe sources calibrated at national primary metrology institutions. The resulting at-birth neutron energy distribution serves as essential input data for radiation transport modeling, providing a validated spectrum for broader experimental and computational applications.
Various studies have shown associations between molecular features and phenotypes of biological samples. These studies, however, focus on a single phenotype per study and are not applicable to repository scale metabolomics data. Here we report MetSummarizer, a method for predicting (i) the biological phenotypes of environmental and host-oriented samples, and (ii) the raw ingredient composition of complex mixtures. We show that the aggregation of various metabolomic datasets can improve the accuracy of predictions. Since these datasets have been collected using different standards at various laboratories, in order to get unbiased results it is crucial to detect and discard standard-specific features during the classification step. We further report high accuracy in prediction of the raw ingredient composition of complex foods from the Global Foodomics Project.
Spectra – the lifeblood of photochemistry – have been very difficult to find in the literature. Chatbots, remarkably, may enable their more efficient acquisition and prove to be generally powerful tools for searching the scientific literature.