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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 145 records · Page 8
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Quantum computation solves a half-century-old enigma: Elusive vibrational states of magnesium dimer found

The high-lying vibrational states of the magnesium dimer (Mg 2 ), which has been recognized as an important system in studies of ultracold and collisional phenomena, have eluded experimental characterization for half a century. Until now, only the first 14 vibrational states of Mg 2 have been experimentally resolved, although it has been suggested that the ground-state potential may support five additional levels. Here, we present highly accurate ab initio potential energy curves based on state-of-the-art coupled-cluster and full configuration interaction computations for the ground and excited electronic states involved in the experimental investigations of Mg 2 . Our ground-state potential unambiguously confirms the existence of 19 vibrational levels, with ~1 cm -1 root mean square deviation between the calculated rovibrational term values and the available experimental and experimentally derived data. Our computations reproduce the latest laser-induced fluorescence spectrum and provide guidance for the experimental detection of the previously unresolved vibrational levels.

74 ATOMIC AND MOLECULAR PHYSICS↗
NASA NTRS1977

Spatially resolved excitation temperature measurements in a hypersonic flow using the hook method

Following an analysis of the hook equations for variation of refractivity along a spectrograph slit a series of experiments is reported, in which CO2 was used as the test gas, and the flow variations were spatially resolved. The hooked spectra were used to measure the ground state number densities of the impurity atom of CrI present in the flow. The excitation temperature of the CrI 1-eV level was obtained from the separation of the hooks of the CrI 425.4-nm transition resonance line and simultaneously the 434.4-nm CrI eV lower level line, from the shock to the body of the hypersonic shock tunnel flow. This excitation temperature is compared with theoretical calculations of the CO2 gas temperature. Some further applications of the hook type methods to gas diagnostics are discussed.

Sandeman, R. J.↗
NASA NTRS1977

Resolution of grass canopy biomass classes

Analysis of variance methods has been applied to in situ grassland spectral reflectance data in order to determine the classes or levels of total wet biomass that can be resolved spectrally by a single narrow band measurement. Ground-truth clipping of blue grama grass plots was performed immediately following spectral reflectance measurements at 91 wavelength intervals which were 0.005 microns apart over the spectral range from 0.350 to 0.800 microns. It was found that the photographic infrared region of 0.750 to 0.800 microns could be used to distinguish three classes or levels of total wet biomass. Four or five classes, particularly at higher biomass levels, could not be distinguished by this technique.

Tucker, C. J.↗
NASA NTRS1995

A hybrid genetic algorithm for resolving closely spaced objects

A hybrid genetic algorithm is described for performing the difficult optimization task of resolving closely spaced objects appearing in space based and ground based surveillance data. This application of genetic algorithms is unusual in that it uses a powerful domain-specific operation as a genetic operator. Results of applying the algorithm to real data from telescopic observations of a star field are presented.

Abbott, R. J.↗
NASA NTRS2012

Interpretation of Variations in Modis-Measured Greenness Levels of Amazon Forests During 2000 to 2009

This work investigates variations in satellite-measured greenness of Amazon forests using ten years of NASA Moderate Resolution Imaging Spectroradiometer (MODIS) enhanced vegetation index (EVI) data. Corruption of optical remote sensing data with clouds and aerosols is prevalent in this region; filtering corrupted data causes spatial sampling constraints, as well as reducing the record length, which introduces large biases in estimates of greenness anomalies. The EVI data, analyzed in multiple ways and taking into account EVI accuracy, consistently show a pattern of negligible changes in the greenness levels of forests both in the area affected by drought in 2005 and outside it. Small random patches of anomalous greening and browning-especially prominent in 2009-appear in all ten years, irrespective of contemporaneous variations in precipitation, but with no persistence over time. The fact that over 90% of the EVI anomalies are insignificantly small-within the envelope of error (95% confidence interval) in EVI-warrants cautious interpretation of these results: there were no changes in the greenness of these forests, or if there were changes, the EVI data failed to capture these either because the constituent reflectances were saturated or the moderate resolution precluded viewing small-scale variations. This suggests a need for more accurate and spatially resolved synoptic views from satellite data and corroborating comprehensive ground sampling to understand the greenness dynamics of these forests.

MODIS↗
DOE OSTI2020

Meter-Based Assessment of the Time and Locational Benefits of a Large Utility’s DSM Portfolio

As decarbonization goals drive increasing levels of renewable generation, there is a need to understand the time- and location-based savings benefits of demand-side management (DSM) programs. The challenges of the 'duck curve' are driving the utility industry to consider how programs can be optimized to match demand profiles with low carbon generation resources. From an infrastructure standpoint, time- and location-targeted DSM could serve as a ‘non-wires alternative’ (NWA) to defer equipment upgrades. Additional DSM value streams are motivating innovation in savings evaluation, providing more resolved insights beyond the total annual program impact. Methods grounded in the principles of billing analysis, leveraging hourly metering at the distribution grid, can provide new visibility into the spatial and temporal savings achieved through DSM. A large body of work has investigated related topics including interval meter-based savings analysis, the time- varying nature of efficiency measures, and NWA. A less studied topic concerns the impact of DSM on the grid, based on metered consumption. This paper presents an analysis of interval data across more than 25,000 customers and twelve substations, from the Sacramento Municipal Utility District. The results show for different locations on the grid: achieved savings and the impact on grid consumption; hourly savings shapes for DSM program participants and non-participants, and how those shapes vary with season; and the impact of the programs on peak demand. These findings show the current impact of DSM, with implications for future, more intentional targeting as the utility continues to pursue aggressive electrification, efficiency, load flexibility, and reliable NWA.

Granderson, Jessica↗
NASA NTRS2000

High-Resolution Optical and Near-Infrared Imaging of Young Circumstellar Disks

In the past five years, observations at optical and near-infrared wavelengths obtained with the Hubble Space Telescope and ground-based adaptive optics have provided the first well-resolved images of young circumstellar disks which may form planetary systems. We review these two observational techniques and highlight their results by presenting prototype examples of disks imaged in the Taurus-Auriga and Orion star-forming regions. As appropriate, we discuss the disk parameters that may be typically derived from the observations, as well as the implications that the observations may have on our understanding of, for example, the role of the ambient environment in shaping the disk evolution. We end with a brief summary of the prospects for future improvements in space- and ground-based optical/IR imaging techniques, and how they may impact disk studies.

McCaughrean, Mark↗
NASA NTRS2020

Data Accountability and Uncertainty Analysis for the Mars Science Laboratory

This paper presents machine learning-based approaches to automate and optimize the detection of volume loss for the downlink process of telemetry data from the Mars Curiosity Rover. The Curiosity observes volume loss and data corruption, requiring re-transmits from the rover and Ground Data System Analysts (GDSA) to monitor the data flow. To resolve this issue, we created a data pipeline to accumulate data from various data sources in the downlink process and detect where the data is missed. In this paper, we benchmarked different methodologies based on the accuracy and excitability of them to identify whether a downlink data that is received to the ground system is complete or incomplete. Our results show that machine learning methods can improve the performance of the GDSA by 55% while the user can diagnose why data is missed and provide an explanation for the data accountability problem.

Chowdhury, Ameera↗
NASA NTRS1990

Discovery of hotspots on Io using disk-resolved infrared imaging

First results are presented using two new techniques for ground-based observation of Io's hotspots. An IR array camera was used to obtain direct IR images of Io with resolution better than 0.5 arcsec, so that more than one hotspot is seen on Io in Jupiter eclipse. The camera was also used to make the first observations of the Jupiter occultation of the hotspots. These new techniques have revealed and located at least three hotspots and will now permit routine ground-based monitoring of the locations, temperatures, and sizes of multiple hotspots on Io.

Spencer, J. R.↗
DOE OSTI2020

The Cloud-resolving model Radar SIMulator (CR-SIM) Version 3.3: description and applications of a virtual observatory

Ground-based observatories use multi-sensor observations to characterize cloud and precipitation properties. One of the challenges is how to design strategies to best use these observations to understand these properties and evaluate weather and climate models. This paper introduces the Cloud resolving model Radar SIMulator (CR-SIM), which uses output from high-resolution cloud resolving models (CRMs) to emulate multi-wavelength, zenith-pointing, and scanning radar observables and multi-sensor (radar and lidar) products. CR-SIM allows direct comparison between an atmospheric model simulation and remote-sensing products using a forward-modeling framework consistent with the microphysical assumptions used in the atmospheric model. CR-SIM has the flexibility to easily incorporate additional microphysical modules, such as microphysical schemes and scattering calculations, and expand the applications to simulate multi-sensor retrieval products. In this paper, we present several applications of CR-SIM for evaluating the representativeness of cloud microphysics and dynamics in a CRM, quantifying uncertainties in radar-lidar integrated cloud products and multi-Doppler wind retrievals, and optimizing radar sampling strategy using observing system simulation experiments. These applications demonstrate the application of CR-SIM as a virtual observatory operator on high-resolution model output for a consistent comparison between model results and observations to aid interpretation of the differences and improve understanding of the representativeness errors due to the sampling limitations of the ground-based measurements. CR-SIM is licensed under the GNU GPL package and both the software and the user guide are publicly available to the scientific community.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Probing the electronic structure and spectroscopy of pyrrolyl and imidazolyl radicals using high-resolution photoelectron imaging of cryogenically cooled anions

High-resolution photoelectron imaging and photodetachment spectroscopy of cryogenically cooled pyrrolide and imidazolide anions are used to probe the electronic structure and spectroscopy of pyrrolyl and imidazolyl radicals. The high-resolution data allow the ground state vibronic structures of the two radicals to be completely resolved, yielding accurate electron affinities of 2.1433 ± 0.0008 eV and 2.6046 ± 0.0006 eV for pyrrolyl and imidazolyl radicals, respectively. Fundamental frequencies for eight vibrational modes of pyrrolyl and ten vibrational modes of imidazolyl are measured, including several nonsymmetric Franck–Condon-forbidden modes. Two electronic excited states are also observed for the two radicals, displaying diffuse spectral features in both systems. The observations of nonsymmetric vibrational modes in the ground states and the diffuse excited state features provide strong evidence for vibronic couplings between the ground state and the two close-by excited states. The 2-pyrrolide isomer is also observed as a minor species from the electrospray ionization source and the electron affinity of 2-pyrrolyl is measured to be 1.6690 ± 0.0030 eV along with five vibrational frequencies. Even though the HOMOs of both pyrrolide and imidazolide anions are p orbitals, photodetachment spectroscopy reveals completely different threshold behaviors for the two anions: a d-wave-dominated spectrum for pyrrolide and an s-wave-dominated spectrum for imidazolide. Furthermore, the current study provides a wealth of electronic and spectroscopic information, which is ideal to compare with more accurate vibronic coupling calculations for these two important radicals, as well as interesting information about the photodetachment dynamics of the two anions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRSDate not supplied

ArcjetCV: A New Machine Learning Application for Extracting Time-Resolved Recession Measurements From Arc Jet Test Videos

Arc jet Computer Vision (ArcjetCV) is a software application built to automate analysis of arc jet ground test video footage. This includes tracking material recession and the shock-material standoff distance. This provides a new capability to resolve and validate new physics associated with non-linear processes. This is an essential step to reduce testing, modeling, and validation uncertainties for heatshield material performance. ArcjetCV uses several types of machine learning (convolutional neural net: CNN, decision tree: DT, k-means unsupervised clustering: KM) to automate the video processing pipeline. These include inferring the start/stop of time segments of interest (1D CNN), measuring the time-dependent 2D recession of the material samples (2D CNN, DT), measuring the time-dependent shock standoff distance (2D CNN, DT), and post-processing cleaning of the recession data (KM). The software also provides a graphical user interface for ease of use. The results of using this tool on arc jet videos show non-linear time-dependent effects can be important for certain materials and characterizing certain failure modes.

machine learning↗
NASA NTRSDate not supplied

arcjetCV: A New Machine Learning Application for Extracting Time-Resolved Recession Measurements From Arc Jet Test Videos

Arc jet Computer Vision (ArcjetCV) is a software application built to automate analysis of arc jet ground test video footage. This includes tracking material recession and the shock-material standoff distance. This provides a new capability to resolve and validate new physics associated with non-linear processes. This is an essential step to reduce testing, modeling, and validation uncertainties for heatshield material performance. ArcjetCV uses several types of machine learning (convolutional neural net: CNN, decision tree: DT, k-means unsupervised clustering: KM) to automate the video processing pipeline. These include inferring the start/stop of time segments of interest (1D CNN), measuring the time-dependent 2D recession of the material samples (2D CNN, DT), measuring the time-dependent shock standoff distance (2D CNN, DT), and post-processing cleaning of the recession data (KM). The software also provides a graphical user interface for ease of use. The results of using this tool on arc jet videos show non-linear time-dependent effects can be important for certain materials and characterizing certain failure modes.

machine learning↗
NASA NTRS2020

Spectroscopy of the first resolved strongly lensed Type Ia supernova iPTF16geu

We report the results from spectroscopic observations of the multiple images of the strongly lensed Type Ia supernova (SN Ia), iPTF16geu, obtained with ground-based telescopes and the Hubble Space Telescope (HST). From a single epoch of slitless spectroscopy with HST, we resolve spectra of individual lensed supernova images for the first time. This allows us to perform an independent measurement of the time-delay between the two brightest images, Δt = 1.4 ± 5.0 d, which is consistent with the time-delay measured from the light curves. We also present measurements of narrow emission and absorption lines characterizing the interstellar medium in the SN Ia host galaxy at z = 0.4087, as well as in the foreground lensing galaxy at z = 0.2163. We detect strong Na ID absorption in the host galaxy, indicating that iPTF16geu belongs to a subclass of SNe Ia displaying ‘anomalously’ large Na ID column densities compared to dust extinction derived from light curves. For the lens galaxy, we refine the measurement of the velocity dispersion, σ = 129 ± 4 km/s, which significantly constrains the lens model. We use ground-based spectroscopy, boosted by a factor ∼70 from lensing magnification, to study the properties of a high-z SN Ia with unprecedented signal-to-noise ratio. The spectral properties of the supernova, such as pseudo-Equivalent widths of several absorption features and velocities of the Si II-line, indicate that iPTF16geu is a normal SN Ia. We do not detect any significant deviations of the SN spectral energy distribution from microlensing of the SN photosphere by stars and compact objects in the lensing galaxy.

J Johansson↗
DOE OSTI2024

The Collaborative Seismic Earth Model: Generation 2

Geological interpretations, earthquake source inversions and ground motion modeling, among other applications, require models that jointly resolve crustal and mantle structure. With the second generation of the Collaborative Seismic Earth Model (CSEM2), we present a global multi-resolution tomographic Earth model that serves this purpose. The model evolves through successive regional- and global-scale refinements. While the first generation aggregated regional models, with this study, we ensure consistency between all individual submodels, resulting in a model that accurately explains wave propagation across scales. Recent regional tomographic models were incorporated, comprising continental-scale inversions for Asia and Africa, as well as regional inversions for the Western US, Central Andes, Iran, and Southeast Asia. Across all regional refinements, over 793,000 source-receiver pairs contributed. Moreover, the long-wavelength Earth model (LOWE) introduces large-scale structures outside of pre-existing local refinements. A full-waveform inversion for global anisotropic P-and S-wave speed structure over a total of 194 iterations with a minimum period of 50 s on a large data set of 1 hr of waveform data from 2,423 earthquakes and over 6 million source-receiver pairs ensures that regional updates in the crust and uppermost mantle translate into updates of deeper, global-scale structure. To test the performance of CSEM2, we evaluate waveform fits between observed and synthetic seismograms at 50 s for an independent data set on the global scale, and on the regional scale for lower periods. We accurately simulate waveforms within and across regional refinements, maintaining the original resolution of the submodels embedded in the global framework.

58 GEOSCIENCES↗
DOE OSTI2021

Dipole response in Te 128 , 130 below the neutron threshold

Numerous studies of the ground-state decay of the pygmy dipole resonance (PDR) have been carried out in the past. However, data on the decay of the PDR to low-lying excited states is still very scarce due to limitations of the sensitivity to weak branching transitions of experimental setups. Here, we present a detailed examination of the low-energy dipole response of 128 Te and 130 Te below their neutron separation thresholds of 8.8 and 8.5 MeV, respectively. Photonuclear reactions with the subsequent γ-ray spectroscopy of the decay channel with continuous-energy bremsstrahlung at varying endpoint energies and linearly polarized quasimonochromatic γ-ray beams with energies ranging from 2.7 to 8.9 MeV in steps of roughly 250 keV were used for probing the decay behavior of the low-energy dipole response in 128Te and 130Te. In addition, (γ,γ' γ") reactions were used to study the population of low-lying states of 128 Te. Spin-parity quantum numbers and reduced transition probabilities are determined for individual photo-excited states. The analysis of average decay properties for nuclear levels in narrow excitation-energy bins enable the extraction of photoabsorption cross sections, average branching ratios to the $2$$^{+}_{1}$ state, and the distinction between E1 and M1 transitions to the ground state and to the $2$$^{+}_{1}$ state accounting for resolved and unresolved transitions.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2020

Vanadium spin qubits as telecom quantum emitters in silicon carbide

Solid-state quantum emitters with spin registers are promising platforms for quantum communication, yet few emit in the narrow telecom band necessary for low-loss fiber networks. Here, we create and isolate near-surface single vanadium dopants in silicon carbide (SiC) with stable and narrow emission in the O band, with brightness allowing cavity-free detection in a wafer-scale material. In vanadium ensembles, we characterize the complex d 1 orbital physics in all five available sites in 4H-SiC and 6H-SiC. The optical transitions are sensitive to mass shifts from local silicon and carbon isotopes, enabling optically resolved nuclear spin registers. Optically detected magnetic resonance in the ground and excited orbital states reveals a variety of hyperfine interactions with the vanadium nuclear spin and clock transitions for quantum memories. Last, we demonstrate coherent quantum control of the spin state. These results provide a path for telecom emitters in the solid state for quantum applications.

74 ATOMIC AND MOLECULAR PHYSICS↗
NASA NTRS1973

Water quality determinations in the Virgin Islands from ERTS-A data.

The characterization of water quality in terms of absolute color values, using imagery from the ERTS-A satellite, imagery from aircraft, and ground truth measurements is discussed. The establishment of photometric standards resolvable by the ERTS-A sensors, as a means of determining atmospheric effects (which generally vary on sequential overpasses) is examined. The application of these techniques is demonstrated for the harbor of Charlotte Amalie on St. Thomas, Virgin Islands, which is characterized by the presence of many poluting factors.-

Egan, W. G.↗