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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 NTRS2017

The Detection of 6.9 µm Emission Features in the Infrared Spectra of IRAS 04296+3429, IRAS 05341+0852, IRAS 22272+5435: Evidence for the Presence of Hn-PAHs in Post AGB Stars

Polycyclic aromatic hydrocarbons (PAHs) are generally believed to be ubiquitous in space and responsible for numerous telltale interstellar infrared emission bands. In Sandford et al., (2013), we suggested that polycyclic aromatic hydrocarbons with excess hydrogenation at their periphery (Hn-PAHs) may be an important subclass of these molecules in some astrophysical environments. These molecules are candidates to explain objects with anomalously large 3.4 μm features, which are presumed to be associated with the aliphatic C—H stretching vibrations of the excess hydrogen. In that work, we suggest that for Hn-PAHs to be a viable candidate as the source for this 3.4 μm feature, we must also expect to observe methylene scissoring modes at 6.9 μm. In this work, we continue to develop the Hn-PAH hypothesis with a focus on the 6.9 μm feature. We also present some new observations of three post-asymptotic giant branch (post- AGB) objects with abnormally large 3.4 μm features, IRAS 04296+3429, IRAS 05341+0852, IRAS 22272+5435, in addition to one post-AGB object with normal PAH emissions, IRAS 20000+3239. These observations were made using the FORCAST instrument in grism mode on the Stratospheric Observatory for Infrared Astronomy (SOFIA) aircraft (Adams et al. 2010) and demonstrate the presence of a 6.9 μm feature for the three objects with abnormally large 3.4 μm features and no detectable 6.9 μm feature for the normal PAH emitter. These results are consistent with the hypothesis that Hn-PAHs are a possible source of these infrared emission bands.

ISM↗
NASA NTRS1977

Feature discrimination and detection probability in synthetic aperture radar imaging system

Images obtained using synthetic aperture radar (SAR) systems can only represent the intensities of resolution cells in the scene of interest probabilistically since radar receiver noise and Rayleigh scattering of the transmitted radiation are always present. Consequently, when features to be identified differ only by their contribution to the mean power of the radar return, discrimination can be treated by detection theory. In this paper, we develop a 'sufficient statistic' for discriminating between competing features and compare it with some suboptimal methods frequently used. Discrimination is measured by probability of detection error and depends on number of samples or 'looks', signal-to-noise ratio (SNR), and ratio of mean power returns from the competing features. Our results show discrimination and image quality rapidly saturate with SNR (very small improvement for SNR not less than 10 dB) but continue to improve with increasing number of looks.

Lipes, R. G.↗
NASA NTRS1984

Detection of subsurface features in Seasat radar images of Means Valley, Mojave Desert, California

Igneous dikes buried beneath as much as 2 m of alluvium in the Mojave Desert of California were detected by the Seasat L-band (23.5-cm wavelength) synthetic-aperture radar (SAR) in 1978. The roughness and dihedral configuration of the dikes are favorable to generation of strong radar echos. The soil-moisture levels in 1978 were likely below the critical 1 percent level. The other permissive conditions for radar penetration of a fine-grained and thin alluvial cover are present. Our findings suggest that subsurface features with potential tectonic or geomorphic significance may be revealed in other orbital radar images of semiarid terrains.

Blom, R. G.↗
DOE OSTI2021

Control-Theory-Informed Feature Selection for Detecting Malicious Tampering in Additive Layer Manufacturing Processes

Additive layer manufacturing (ALM) is rapidly becoming an appealing solution to the low-volume manufacturing of metal, polymer, or composite parts. However, ALM’s reliance on digital part specifications, microcontrollers, and modern networking makes these devices vulnerable to malicious tampering by cyber attackers, which can negatively affect part performance and even result in catastrophic failure. We present a hybrid analytic approach to feature discovery using control theoretic techniques and linear modelling on input-output data collected from a representative controller system. Employing this approach, we design, train, and test an anomaly detection system. The preliminary results show that the proposed approach effectively discovers useful input-output relationships for anomaly detection in a simulated ALM process. Application to larger and more complex systems are discussed.

Dawson, Joel↗
NASA NTRS2018

Detection of Reflection Features in the Neutron Star Low-mass X-Ray Binary Serpens X-1 with NICER

We present Neutron Star Interior Composition Explorer (NICER) observations of the neutron star (NS) low-mass X-ray binary Serpens X-1 during the early mission phase in 2017. With the high spectral sensitivity and low-energy X-ray passband of NICER, we are able to detect the Fe L line complex in addition to the signature broad, asymmetric Fe K line. We confirm the presence of these lines by comparing the NICER data to archival observations with XMM-Newton/Reflection Grating Spectrometer (RGS) and NuSTAR. Both features originate close to the innermost stable circular orbit (ISCO). When modeling the lines with the relativistic line model RELLINE, we find that the Fe L blend requires an inner disk radius of 1.4(sup 0.2, sub -0.1)R(sub ISCO) and Fe K is at 1.03(sup 0.13, sub -0.03)R(sub ISCO) (errors quoted at 90%). This corresponds to a position of 17(sup 2.5, sub -1.2)km and 12(sup 1.6, sub -0.4)km for a canonical NS mass (M(sub NS)=1.4 solar mass) and dimensionless spin value of a = 0. Additionally, we employ a new version of the RELXILL model tailored for NS(sub s) and determine that these features arise from a dense disk and supersolar Fe abundance.

Ludlam, R. M.↗
NASA NTRS2018

Detection of Photospheric Features in the Near-Infrared Spectrum of a Class 0 Protostar

We present a near-infrared K-band R ≃ 1500 Keck spectrum of S68N, a Class 0 protostar in the Serpens molecular cloud. The spectrum shows a very red continuum, CO absorption bands, weak or non-existent atomic metal absorptions, and H2 emission lines. The near-IR H2 emission is consistent with excitation in shocks or by X-rays but not by UV radiation. We model the absorption component as a stellar photosphere plus circumstellar continuum emission with wavelength-dependent extinction. A Markov Chain Monte Carlo analysis shows that the most likely model parameters are consistent with a low-temperature, low-gravity photosphere with signifi cant extinction and no more than modest continuum veiling. Its T(eff) ≃ 3260 K effective temperature is similar to that of older, more evolved pre-main-sequence stars, but its surface gravity log g ≃ 2:4 cm/sq.s is approximately 1 dex lower. This implies that the radius of this protostar is a factor of ~ 3 larger than that of 106 yr old T Tauri stars. Its low veiling is consistent with a circumstellar disk having intrinsic near-IR emission that is less than or equal to that of more evolved Class I protostars. Along with the high extinction, this suggests that most of the circumstellar material is in a cold envelope, as expected for a Class 0 protostar. This is the first known detection and analysis of a Class 0 protostar absorption spectrum.

Thomas P Greene↗
DOE OSTI2025

Automated Scoring of Morphological Changes in Images of Pentaerythritol Tetranitrate

Recent advances in characterization techniques that generate large datasets of material microstructure images require robust, automated image-processing. We applied an unsupervised anomaly detection method called feature anomaly detection system (FADS) to automatically detect and quantify microstructure changes in images of the explosive pentaerythritol tetranitrate (PETN) aged at various temperatures. We demonstrated the FADS approach on two-dimensional images extracted from computed tomography scans, but the same technique can be readily applied to other imaging modalities. FADS calculates anomaly scores on the basis of differences in filter activations of nominal and test data in pretrained convolutional neural networks. The FADS scores successfully differentiated between pristine PETN and PETN aged at a temperature where material coarsening occurred. Morphological metric analysis of segmented images verified observed trends in FADS scores as a function of aging temperature and aging time, specifically by calculating volume fractions, specific boundary lengths, two-point correlation functions, and local thicknesses. Here, the FADS technique has two important advantages compared to traditional morphological analysis: First, it uses grayscale images as input, rather than images that are segmented to separate the appropriate phases; and second, FADS scores capture any type of changes among image sets, rather than requiring prior knowledge or selection of a relevant set of metrics.

Accelerated aging↗
DOE OSTI2023

Machine learning for detection of 3D features using sparse x-ray tomographic reconstruction

In many inertial confinement fusion (ICF) experiments, the neutron yield and other parameters cannot be completely accounted for with one and two dimensional models. This discrepancy suggests that there are three dimensional effects that may be significant. Sources of these effects include defects in the shells and defects in shell interfaces, the fill tube of the capsule, and the joint feature in double shell targets. Due to their ability to penetrate materials, x rays are used to capture the internal structure of objects. Methods such as computational tomography use x-ray radiographs from hundreds of projections, in order to reconstruct a three dimensional model of the object. In experimental environments, such as the National Ignition Facility and Omega-60, the availability of these views is scarce, and in many cases only consists of a single line of sight. Mathematical reconstruction of a 3D object from sparse views is an ill-posed inverse problem. These types of problems are typically solved by utilizing prior information. Neural networks have been used for the task of 3D reconstruction as they are capable of encoding and leveraging this prior information. We utilize half a dozen, different convolutional neural networks to produce different 3D representations of ICF implosions from the experimental data. Deep supervision is utilized to train a neural network to produce high-resolution reconstructions. These representations are used to track 3D features of the capsules, such as the ablator, inner shell, and the joint between shell hemispheres. Machine learning, supplemented by different priors, is a promising method for 3D reconstructions in ICF and x-ray radiography, in general.

Wolfe, Bradley T. (ORCID:0000000268301614)↗
DOE OSTI2022

Neural net detection of seismic features related to gas hydrates and free gas accumulations on the northern U.S. Atlantic margin

Bottom-simulating reflections (BSRs) that sometimes mark the base of the gas hydrate stability zone in marine sediments are often identified based on the reverse polarity reflections that cut across stratigraphic layering in seismic amplitude data. On the northern U.S. Atlantic margin (USAM) between Cape Hatteras and Hudson Canyon, legacy seismic data have revealed pronounced BSRs south of the deepwater extension of Hudson Canyon and more subtle ones from offshore Delaware south to Cape Hatteras, where the reflections sometimes follow stratigraphic layering. Using high-resolution seismic data acquired during the 2018 Mid-Atlantic Resource Imaging Experiment and a supervised neural net, we identify seismic features associated with gas hydrates and/or the top of gas between Hudson Canyon and Cape Hatteras. Using seismic attributes especially sensitive to the presence of gas, we train a neural network algorithm on seismic data from an area with strong BSRs and then apply the model to the rest of the data set. The results indicate that gas hydrate and/or shallow free gas are significantly more widespread on the northern part of the USAM than previously known. Seismic indicators of gas extend landward from the 2000 m isobath to the upper continental slope in sectors with (offshore Virginia) and, to a lesser extent, without (offshore New Jersey) pervasive upper slope methane seeps. Higher sand content and intermediate sediment thickness, factors related to the container size and gas charge in a petroleum systems framework, are associated with more robust gas indicators.

Geochemistry & Geophysics↗
NASA NTRS1974

Remote detection of ocean features in the Lesser Antilles using ERTS-1 data

The author has identified the following significant results. Photographic data received from the ERTS-1 satellite over the Lesser Antilles Islands shows distinct ocean features on the leeward side of each island. Attempts to relate these features to ocean eddy formations with the aid of ground truth data proved unsuccessful. However, analysis of surface and upper air wind data correlate extremely well with the size, shape, and downwind extent of the ocean features. Studies to date indicate strongly that these features result from horizontal differences in sea surface roughness due to the wind shadow effect of the islands. The results suggest that horizontal variations in the reflectance of the sea surface will make remote sensing of the ocean mixed layer more difficult than previously anticipated. The surface reflection seems to be large enough to mask the smaller variations in backscattered energy from the mixed layer. Efforts to limit the effect of surface reflectance by photographic differencing of two MSS bands were unsuccessful. A supplementary study to enhance the energy reflected from the mixed layer through numerical differencing of ERTS-1 digital data is planned.

Hanson, K. J.↗
NASA NTRS1974

Remote detection of ocean features in the Lesser Antilles using ERTS-1 data

The author has identified the following significant results. Photographic data received from the ERTS-1 satellite over the Lesser Antilles Islands show distinct ocean features on the leeward side of each island. Attempts to relate these features to ocean eddy formations with the aid of ground truth data proved unsuccessful. However, surface and upper air wind data indicate a good correlation with the size, shape, and downwind extent of the ocean features. Studies to date indicate strongly that these features result from horizontal differences in sea surface roughness due to the wind shadow effect of the islands. The results suggest that horizontal variations in the reflectance of the sea surface will make remote sensing of the ocean mixed layer more difficult than previously anticipated. The surface reflection seems to be large enough to mask the smaller horizontal variations in backscattered energy from the mixed layer.

Hanson, K. J.↗
NASA NTRS1982

Detection of pedestal features in dark clouds - Evidence for formation of low mass stars

To assess whether B335 is unique among dark clouds or whether CO-12 pedestal features are quite common, 180 opacity class 5 and 6 Lynds clouds were surveyed. From this set of data, three additional sources were found to have pedestal features. These suggest the presence of embedded low-mass stars, though a hot differentially rotating disk cannot be excluded for B335. Estimates of the mass-loss rate required to produce stellar winds consistent with observations are comparable with mass-loss rates for T Tauri stars. Further, the pedestal feature formation rate is similar to the local low-mass star formation rate.

Frerking, M. A.↗
NASA NTRS1989

Neptune cloud structure at visible wavelengths

Digital images of Neptune showing cloud structure at visible wavelengths were obtained in July 1988. A discrete bright feature was detected both at 6190 A (a weak methane absorption band in the visible) and at 8900 A (a stronger methane band in the near infrared). The images also revealed that Neptune's southern pole was bright relative to planetary mid-latitudes at 6190 A but not 8900 A. The implications of these findings for atmospheric rotation and structure are discussed. The detection of discrete features at visible wavelengths is of special importance to the upcoming Voyager encounter with Neptune: the wide-angle camera has a 6190 A filter similar to that used for these observations.

Hammel, H. B.↗