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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 163 records · Page 9
All sourcesNASA NTRSDOE OSTI
NASA NTRS1989

High-spectral resolution observations of the 3.29 micron emission feature: Comparison to QCC and PAHs

Two of the most promising explanations for the origin of the interstellar emission features observed at 3.29, 3.4, 6.2, 7.7, 8.6, and 11.3 microns are: quenched carbonaceous composite (QCC) and polycyclic aromatic hydrocarbons (PAHs). High resolution spectra are given of the 3.29 micron emission feature which were taken with the Cooled Grating Array Spectrometer at the NASA Infrared Telescope Facility and previously published. These spectra show that the peak wavelength of the 3.29 micron feature is located at 3.295 + or - 0.005 micron and that it is coincident with the peak absorbance of QCC. The peak wavelength of the 3.29 micron feature appears to be the same in all of the sources observed thus far. However, the width of the feature in HD 44179 and Elias 1 is only 0.023 micron, which is smaller than the 0.043 micron width in NGC 7027, IRAS 21282+5050, the Orion nebula, and BD+30 deg 3639. Spectra of NGC 7027, QCC, and PAHs is shown. QCC matches the 3.29 micron interstellar emission feature very closely in the wavelength of the peak, and it produces a single feature. On the other hand, PAHs rarely match the peak of the interstellar emission feature, and characteristically produce multiple features.

Tokunaga, Alan T.↗
NASA NTRS1993

The unusual supernova SN1993J in the galaxy M81

Supernova 1993J in the galaxy M81 is the second-brightest type II supernova observed this century, surpassed only by SN1987A in the Large Magellanic Cloud. Here we report the evolution of the photometric and spectral properties of SN1993J for the first 50 d following its discovery. The behavior of this supernova is unusual, showing features typical of type II supernovae near the initial maximum, but with the strong helium lines characteristic of type Ib supernovae at later times. This implies that the progenitor star had an unusually thin hydrogen envelope (compared to normal type II progenitors), suggesting that significant mass loss had taken place before the explosion. Application of an expanding photosphere model to our data provides an estimate of the distance to the supernova of 2.6 +/- 0.4 Mpc, broadly consistent with the distance to M81 determined using Cepheid variable stars. Supernova models that more closely match the atypical spectral features of SN1993J may change the inferred distance, and should provide better constraints on the structure of the progenitor.

Schmidt, Brian P.↗
DOE OSTI2022

Seabed bathymetry and friction modeling in MoorDyn

This paper presents the implementation and verification of a seabed bathymetry feature and seabed friction feature to the open-source, lumped-mass mooring system dynamics modeler, MoorDyn, which is part of the National Renewable Energy Laboratory’s aero-hydro-servo-elastic simulation tool, OpenFAST. Variations in seabed slope, as well as the frictional effects of mooring lines moving along the seabed, will affect the mooring line tensions of a floating platform and the consequent platform response. These new features are especially relevant for modeling mooring systems in deep-water coastal areas where seabed depth can change significantly over an entire mooring footprint. The bathymetry feature models the seabed as a rectangular grid of variable water depths in place of the existing, uniform water depth in MoorDyn. The friction force is primarily represented as a Coulombic friction force, or the product of a kinetic friction coefficient and the seabed contact normal force, with the ability to differentiate between transverse and axial motion of a line node on the seabed in any bathymetry grid. These capabilities were tested by running MoorDyn and OpenFAST simulations over a variety of seabed and environmental conditions; the resulting fairlead tensions, node tensions, and mooring line kinematics were verified against equivalent OrcaFlex simulations. The results match closely, meaning the features are verified, which will increase the overall fidelity of OpenFAST and FAST.Farm simulations.

17 WIND ENERGY↗
NASA NTRS1992

Wind interaction with falling ejecta - Origin of the parabolic features on Venus

A quantitative model in which the parabolic features are produced by the interaction of the zonal winds with material ejected ballistically from the impact crater is proposed. As the ejecta particles fall through the atmosphere, the winds transport them downwind from their entry point, smaller particles being transported a greater distance. Since the ejecta distribution is initially axially symmetric and smaller particles are thrown farther from the crater, the winds blow the particles on the upwind side back upon one another, leading to a pile-up of material. On the downwind side, the winds disperse the ejecta particles and no pile-up occurs. The resulting thickness distribution on the Venusian surface matches the observed parabolic features closely. The dual parabolic features associated with the crater Carson is also explained by this model.

Vervack, Ronald J., Jr.↗
NASA NTRSDate not supplied

Artificial Generation of 2-D Fiber Reinforced Composite Microstructures with Statistically Equivalent Features

Fiber reinforced composites are used widely for their high strength and low weight advantages in various aerospace and automotive applications. While their use may be sought after, modeling of these material requires increasing fidelity at the lower scales to capture accurate material behavior under loading. The first steps in creating statistically equivalent models to real life cases is developing a method of rapid evaluation and artificial microstructure generation. The outlined work is capable of tracking microscale fiber positions and determining regions of localized volume fraction extrema (high and low end). Groupings of high and low volume fraction regions are called clusters and their geometry is used to characterize the microstructure. These cluster features can be evaluated for both artificial models and actual scans, allowing correlation to be established which can ultimately be used to regenerate statistically equivalent models. The results of this work show that if one feature is to be correlated, a model can be generated which matches almost exactly. But once more features are equally taken into account, the regeneration loses accuracy.

micromechanics↗
NASA NTRS1995

High Accuracy In-Flight Wavelength Calibration of Imaging Spectrometry Data

Accurate wavelength calibration of imaging spectrometer data is essential if proper atmospheric transmission corrections are to be made to obtain apparent surface reflectance. Accuracies of 0.1 nm are necessary for a 10 nm-sampling instrument in order to match the slopes of the deep atmospheric water vapor features that dominate the 0.7-2.3 micrometer regions. The Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) is calibrated in the laboratory to determine the wavelength position and full-width-half-maximum (FWHM) response for each of the 224 channels. The accuracies are limited by the quality of the monochromator used as a source. The accuracies vary from plus or minus to plus or minus 1.5 nm depending on the wavelength region, in general decreasing with increasing wavelength. Green et al. make corrections to the wavelength calibrations by using the known positions of 14 atmospheric absorption features throughout the 0.4-2.5 micrometer wavelength region. These features, having varying width and intensity, were matched to the MODTRAN model with a non-linear least squares fitting algorithm. A complete calibration was developed for all 224 channels by interpolation. Instrument calibration cannot be assumed to be stable to 0.1 nm over a flight season given the rigors of thermal cycling and launch and landing loads. The upcoming sensor HYDICE will require a means for in-flight spectral calibration of each scene because the calibration is both temperature and pressure sensitive. In addition, any sensor using a two-dimensional array has the potential for systematic wavelength shifts as a function of cross-track position, commonly called 'smile'. Therefore, a rapid means for calibrating complete images will be required. The following describes a method for determining instrument wavelength calibration using atmospheric absorption features that is efficient enough to be used for entire images on workstations. This study shows the effect of the surface reflectance on the calibration accuracy and the calibration history for the AVIRIS B spectrometer over the 1992 flight season.

Goetz, Alexander F. H.↗
DOE OSTI2025

A deep learning and finite element approach for exploration of inverse structure–property designs of lightweight hybrid composites

Hybrid composites have important applications, such as high-performance and lightweight materials in aerospace and automotive industries. Hybrid composites utilize the synergy of diverse fillers to achieve desired material properties, but usually have more complicated microstructures. While topology optimization can optimize a particular property, designing hybrid composites for customized mechanical performances, e.g. full-range stress–strain curve, remains challenging. Here, a computational framework that integrated finite element analysis (FEA) and artificial intelligence (AI) methods of Conditional Generative Adversarial Networks (cGAN) deep learning and transfer learning was developed to establish inverse structure–property relationships and design tailor-made hybrid composites. Based on FEA-generated datasets of hybrid fiber-particle–matrix microstructures and their corresponding full-range stress–strain curves, a cGAN architecture was trained to generate tailored microstructures and establish structure–property relationships. Similarity in microstructural features and well-matched stress–strain curves based on the AI-generated composites were achieved. In conclusion, transfer learning was used to expand the pre-trained model for designing different materials systems.

Hybrid composites↗
DOE OSTI2020

Deep learning to generate in silico chemical property libraries and candidate molecules for small molecule identification in complex samples

Comprehensive and unambiguous identification of small molecules in complex samples will revolutionize our understanding of the role of metabolites in biological systems. Existing and emerging technologies have enabled measurement of chemical properties of molecules in complex mixtures and, in concert, are sensitive enough to resolve even stereoisomers. Despite these experimental advances, small molecule identification is inhibited by (i) chemical reference libraries (e.g. mass spectra, collision cross section, and other measurable property libraries) representing <1% of known molecules, limiting the number of possible identifications, and (ii) the lack of a method to generate candidate matches directly from experimental features (i.e. without a library). To this end, we developed a variational autoencoder (VAE) to learn a continuous numerical, or latent, representation of molecular structure to expand reference libraries for small molecule identification. We extended the VAE to include a chemical property decoder, trained as a multitask network, in order to shape the latent representation such that it assembles according to desired chemical properties. The approach is unique in its application to metabolomics and small molecule identification, with its focus on properties that can be obtained from experimental measurements (m/z, CCS) paired with its training paradigm, which involved a cascade of transfer learning iterations. First, molecular representation is learned from a large dataset of structures with m/z labels. Next, in silico property values are used to continue training, as experimental property data is limited. Finally, the network is further refined by being trained with the experimental data. This allows the network to learn as much as possible at each stage, enabling success with progressively smaller datasets without overfitting. Once trained, the network can be used to predict chemical properties directly from structure, as well as generate candidate structures with desired chemical properties. Our approach is orders of magnitude faster than first-principles simulation for CCS property prediction. Additionally, the ability to generate novel molecules along manifolds, defined by chemical property analogues, positions DarkChem as highly useful in a number of application areas, including metabolomics and small molecule identification, drug discovery and design, chemical forensics, and beyond.

Colby, Sean M.↗
DOE OSTI2020

Improved Single-Cell Proteome Coverage Using Narrow-Bore Packed NanoLC Columns and Ultrasensitive Mass Spectrometry

Single-cell proteomics can provide unique insights into biological processes by resolving heterogeneity that is obscured by bulk measurements. Gains in the overall sensitivity and proteome coverage through improvements in sample processing and analysis increase the information content obtained from each cell, particularly for less abundant proteins. Here we report on improved single-cell proteome coverage through the combination of the previously developed Nanodroplet Processing in One Pot for Trace Samples (nanoPOTS) platform with further miniaturization of liquid chromatography (LC) separations and implementation of an ultrasensitive latest-generation mass spectrometry (MS) instrument. Following nanoPOTS sample preparation, protein digest from single cells were separated using a 20-µm-i.d. in-house-packed nanoLC column. Separated peptides were ionized using an etched fused silica emitter capable of stable ionization at the ~20 nL/min flow rate provided by the LC separation. Ultrasensitive LC-MS analysis was achieved using the Orbitrap Eclipse Tribrid mass spectrometer. An average of 362 protein groups were identified by MS/MS from single HeLa cells, and 874 protein groups were identified using the Match Between Runs (MBR) feature of MaxQuant. This represents a >70% increase in label-free proteome coverage for single cells relative to previous efforts using larger-bore (30-µm-i.d.) LC columns coupled to a previous-generation MS (Orbitrap Fusion Lumos).

Cong, Yongzheng↗
DOE OSTI2021

Ultraviolet spectra of extreme nearby star-forming regions: Evidence for an overabundance of very massive stars

ABSTRACT As deep spectroscopic campaigns extend to higher redshifts and lower stellar masses, the interpretation of galaxy spectra depends increasingly upon models for very young stellar populations. Here we present new HST/COS ultraviolet spectroscopy of seven nearby (<120 Mpc) star-forming regions hosting very young stellar populations (∼4–20 Myr) with optical Wolf–Rayet stellar wind signatures, ideal laboratories in which to benchmark these stellar models. We detect nebular C iii] in all seven, but at equivalent widths uniformly <10 Å. This suggests that even for very young stellar populations, the highest equivalent width C iii] emission at ≥15 Å is reserved for inefficiently cooled gas at metallicities at or below that of the SMC. The spectra also reveal strong C iv P-Cygni profiles and broad He ii emission formed in the winds of massive stars, including some of the most prominent He ii stellar wind lines ever detected in integrated spectra. We find that the latest stellar population synthesis prescriptions with improved treatment of massive stars nearly reproduce the entire range of stellar He ii wind strengths observed here. However, we find that these models cannot simultaneously match the strongest wind features alongside the optical nebular line constraints. This discrepancy can be naturally explained by an overabundance of very massive stars produced by a high incidence of binary mass transfer and mergers occurring on short ≲10 Myr time-scales, suggesting these processes may be crucial for understanding systems dominated by young stars both nearby and in the early Universe.

Senchyna, Peter↗
DOE OSTI2021

Multiagent-Based Dynamic Voltage Support of Power Converters During Fault Ride-Through

Reference point of applicability (RPA) is a predefined point in a distribution network that performance requirements shall apply. As RPA is not directly controlled by a dedicated distributed energy resource (DER), it requires an aggregate response of multiple DERs over a complex meshed network. Here, this article presents a multiagent-based distributed dynamic voltage support (DDVS) method for coordinated aggregate response of multiple DER units to support RPA voltage profile during and after fault ride-through. DDVS implements a multiagent-based leader target tracking scheme with velocity matching and flock centering features to avoid uncoordinated current injections of cooperative DERs. The DDVS is an event-based approach based on RPA requirements. Two-dimensional voltage support objective is handled: 1) coordinated positive sequence current injection for voltage magnitude boosting and 2) coordinated negative sequence current injection for unbalance voltage mitigation. The results demonstrate that the proposed DDVS algorithm addresses emerging coordinated DVS requirement of DERs.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2023

Matrix element corrections in the PYTHIA8 parton shower in the context of matched simulations at next-to-leading order

We discuss the role of matrix element corrections (MEC) to parton showers in the context of MC@NLO-type matchings for processes that feature unstable resonances, where MEC are liable to result in double-counting issues, and are thus generally not employed. By working with PYTHIA8 , we show that disabling all MEC is actually unnecessary in computations based on the narrow-width approximation, and we propose alternative MEC settings which, while still avoiding double counting, allow one to include hard-recoil effects in the simulations of resonance decays. We illustrate our findings by considering $t\overline{t}$ production at the LHC, and by comparing MadGraph5-aMC@NLO predictions with those of POWHEG-BOX and standalone PYTHIA8 .

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2021

HSolo v.1.0

SAND2021-11023 O HSolo is a library for estimating similarity, affine, projective homographies from matches produced by image feature detectors such as SURF and SIFT. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.

Gonzales, Antonio↗
DOE OSTI2024

In situ estimation of ice crystal properties at the South Pole using LED calibration data from the IceCube Neutrino Observatory

The IceCube Neutrino Observatory instruments about 1 km 3 of deep, glacial ice at the geographic South Pole. It uses 5160 photomultipliers to detect Cherenkov light emitted by charged relativistic particles. An unexpected light propagation effect observed by the experiment is an anisotropic attenuation, which is aligned with the local flow direction of the ice. We examine birefringent light propagation through the polycrystalline ice microstructure as a possible explanation for this effect. The predictions of a first-principles model developed for this purpose, in particular curved light trajectories resulting from asymmetric diffusion, provide a qualitatively good match to the main features of the data. This in turn allows us to deduce ice crystal properties. Since the wavelength of the detected light is short compared to the crystal size, these crystal properties include not only the crystal orientation fabric, but also the average crystal size and shape, as a function of depth. By adding small empirical corrections to this first-principles model, a quantitatively accurate description of the optical properties of the IceCube glacial ice is obtained. In this paper, we present the experimental signature of ice optical anisotropy observed in IceCube light-emitting diode (LED) calibration data, the theory and parameterization of the birefringence effect, the fitting procedures of these parameterizations to experimental data, and the inferred crystal properties.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1987

The IR emission features - Emission from PAH molecules and amorphous carbon particles

Given the current understanding of polycyclic aromatic hydrocarbons (PAHs), the spectroscopic data suggest that are at least two components which contribute to the interstellar emission spectrum: (1) free molecule-sized PAHs producing the narrow features and (2) amorphous carbon particles (which are primarily composed of an irregular 'lattice' of PAHs) contributing to the broad underlying components. An exact treatment of the IR fluorescence from highly vibrationally excited large molecules demonstrates that species containing between 20 and 30 carbon atoms are responsible for the narrow features, although the spectra match more closely with the spectra of amorphous carbon particles. It is concluded that, since little is known about the spectroscopic properties of free PAHs and PAH clusters, much laboratory work is required along with an observational program focusing on the spatial characteristics of the spectra.

Allamandola, L. J.↗
NASA NTRS1990

A rough-surface thermophysical model for airless planets

A model for determining diurnal temperatures in spherical-section depressions and which encompasses both subsurface heat-flow and direct and scattered sunlight effects is presently applied to the disk-integrated thermal emission of a rough planetary surface with nonzero thermal inertia. Attention is given to the variation with roughness and thermal inertia of the beaming parameter eta, which characterizes zero-phase thermal emission by comparison with a smooth, nonrotating body and is almost independent of albedo for a given surface roughness. The thermal phase curve of Ceres is noted to be well matched by the model features of (1) prograde rotation, (2) 44-deg rms surface slope, and (3) a thermal inertia that is 30 percent of the lunar value.

Spencer, John R.↗
NASA NTRS1992

On ionized napthalene (C10H8(+)) as a carrier of diffuse interstellar bands

A recent laboratory study of ionized napthalene (C10H8(+)) has led to the suggestion that some of the unidentified diffuse interstellar bands may be formed by this molecular ion in the diffuse interstellar medium. In particular, there is a close match between a laboratory feature at 6741 A and a weak diffuse band at 6742 A, and some near-coincidences at other wavelengths. The same laboratory data show that other diffuse bands may be found, including one at 6151 A, if indeed C10H8(+) is responsible. This paper reports a search for the 6151 A feature, with negative results. The derived upper limits appear to be in conflict with the C10H8(+) hypothesis, but may not be, due to uncertainties in the expected width of the predicted interstellar feature, and due to the fact that the observations do not include data on the 6742 A band, so it is not known whether this putative C10H8(+) feature is present in the observed clouds.

Snow, Theodore P.↗
NASA NTRS1994

A HIRES analysis of the FIR emission of supernova remnants

The high resolution (HiRes) algorithm has been used to analyze the far infrared emission of shocked gas and dust in supernova remnants. In the case of supernova remnant IC 443, we find a very good match between the resolved features in the deconvolved images and the emissions of shocked gas mapped in other wavelengths (lines of H2, CO, HCO+, and HI). Dust emission is also found to be surrounding hot bubbles of supernova remnants which are seen in soft X-ray maps. Optical spectroscopy on the emission of the shocked gas suggests a close correlation between the FIR color and local shock speed, which is a strong function of the ambient (preshock) gas density. These provide a potentially effective way to identify regions of strong shock interaction, and thus facilitate studies of kinematics and energetics in the interstellar medium.

Wang, Zhong↗