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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 1,459 records · Page 81
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Memory-Related Frontal Brainwaves Predict Transition to Mild Cognitive Impairment in Healthy Older Individuals Five Years Before Diagnosis

Background: Early prognosis of high-risk older adults for amnestic mild cognitive impairment (aMCI), using noninvasive and sensitive neuromarkers, is key for early prevention of Alzheimer’s disease. We have developed individualized measures in electrophysiological brain signals during working memory that distinguish patients with aMCI from age-matched cognitively intact older individuals. Objective: Here we test longitudinally the prognosis of the baseline neuromarkers for aMCI risk. We hypothesized that the older individuals diagnosed with incident aMCI already have aMCI-like brain signatures years before diagnosis. Methods: Electroencephalogram (EEG) and memory performance were recorded during a working memory task at baseline. The individualized baseline neuromarkers, annual cognitive status, and longitudinal changes in memory recall scores up to 10 years were analyzed. Results: Seven of the 19 cognitively normal older adults were diagnosed with incident aMCI for a median 5.2 years later. The seven converters’ frontal brainwaves were statistically identical to those patients with diagnosed aMCI (n = 14) at baseline. Importantly, the converters’ baseline memory-related brainwaves (reduced mean frontal responses to memory targets) were significantly different from those who remained normal. Furthermore, differentiation pattern of left frontal memory-related responses (targets versus nontargets) was associated with an increased risk hazard of aMCI (HR = 1.47, 95% CI 1.03, 2.08). Conclusion: The memory-related neuromarkers detect MCI-like brain signatures about five years before diagnosis. The individualized frontal neuromarkers index increased MCI risk at baseline. These noninvasive neuromarkers during our Bluegrass memory task have great potential to be used repeatedly for individualized prognosis of MCI risk and progression before clinical diagnosis.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS1980

Measuring coal deposits by radar

Front-surface, local-oscillator radar directly compares frequency of signals reflected from front and back surfaces of coal deposits. Thickness is measured directly as frequency difference. Transmitter is frequency modulated, so thickness is computed directly from frequency difference. Because front and back reflections are detected in combination rather than separately, masking of comparatively weak back signal is less problem. Also system is not sensitive to extraneous reflections from targets between transmitting antenna and coal surface.

Barr, T. A.↗
NASA NTRS1982

Pulsed Phase Shifter Improves Doppler Radar

Ability of microwave Doppler radar to measure velocity of slow moving nearby target is enhanced by pulsed 90 degrees phase shifter in radar transmission line between circulator and antenna. Because of phase shifting, Doppler frequency is detected as modulation on carrier instead of baseband signal. Carrier is amplified and filtered before demodulation, resulting in strong, clean demodulated Doppler for measurement and display.

Kobayashi, H. S.↗
NASA NTRS1982

The recognition of extended targets - SAR images for level and hilly terrain

Radar image simulation techniques are used to determine the character of SAR images of area-extensive targets, for the cases of flat underlying terrain and of moderate relief, with a view to the severity of elevation change effects on the detection and recognition of boundaries and shapes. The experiment, which demonstrated these effects on shapes and boundaries, was performed in order to establish Seasat-A SAR performance. Attention is given to the geometry/propagation effects in range perspective imaging that must be known for information extraction.

Stiles, J. A.↗
NASA NTRS1986

Analysis of AIS radiometry with emphasis on determination of atmospheric properties and surface reflectance

Airborne Imaging Spectrometer data from Mono Lake, California, were studied in order to establish spectral radiance of test areas under solar illumination. The objective is to provide a method of atmospheric correction for major absorbers from the spectrometer data themselves. Crucial to the analysis is radiometric calibration of the instrument. Good agreement is found between calculated and measured radiances for uniform surface targets (beaches), but simulations of atmospheric properties with LOWTRAN lead to unreasonably low values of atmospheric precipitable water. Absorptions from carbon dioxide are not detected in the AIS data, but are strongly present in the LOWTRAN model. The apparent low contrast of all atmospheric absorption bands leads to a study of contamination from overlapping spectral orders in the AIS data. The suspected contamination is shown unambiguously to be present beyond approximately 1500 nm and consists of an extra radiance term including atmospheric bands from the delta/2 wavelength interval. A rigorous removal of the unwanted spectral contamination does not seem possible for any data taken in the rock mode. Rough estimates for tree-mode observations might be pieced together is a suitable after-the-fact radiometric claibration of the instrument can be formulated.

Conel, J. E.↗
NASA NTRS1992

Charged particle activation studies on the surface of LDEF spacecraft

High energy proton induced nuclear reaction products are examined using seven elements, namely: aluminum, silicon, nickel, copper, zirconium, tantalum, and tungsten. We detected activities due to Na-22 from Al, Co-56 and Co-57 from Ni, Co-58 from Cu, and Y-88 from Zr targets. No induced activity was observed in Si, Ta, and W, most probably due to the long cooling times. Only the Zr sample contained a weak Be-7 peak, although Ta and W were also located at the leading edge of the spacecraft. Gamma-rays of individual isotopes were measured using a high-resolution Ge(Li) solid state detector coupled to a 4096-multichannel analyzer. Activities were calculated for Co-56 (846 keV) and Co-57 (122 and 136 keV's) at the time of the entry of the spacecraft and found to be 0.014 +/- 0.005 c/s-g, 0.018 +/- 0.002 c/s-g, and 0.0024 +/- 0.0007 c/s-g, respectively.

Olmez, Ilhan↗
NASA NTRS2005

Single visit completeness optimization

The Terrestrial Planet Finder Coronagraph (TPF-C) is a NASA pre-phase. A orbiting telescope with the goal of detecting and characterizing visible and near-IR light refelected from terrestrial planets. We use observational completeness, defined as the fraction of potentially observable planets that are detected, to determine how well the proposed telescope meets the mission goals. Single visit completeness is optimized by slecting the length of observation per target that maximizes the completeness for the ensemble of stars. In this memo we describe the integration time calculations and two approaches to single visit optimization.

optimization↗
NASA NTRS2011

Machine Vision for Relative Spacecraft Navigation During Approach to Docking

This paper describes a machine vision system for relative spacecraft navigation during the terminal phase of approach to docking that: 1) matches high contrast image features of the target vehicle, as seen by a camera that is bore-sighted to the docking adapter on the chase vehicle, to the corresponding features in a 3d model of the docking adapter on the target vehicle and 2) is robust to on-orbit lighting. An implementation is provided for the case of the Space Shuttle Orbiter docking to the International Space Station (ISS) with quantitative test results using a full scale, medium fidelity mock-up of the ISS docking adapter mounted on a 6-DOF motion platform at the NASA Marshall Spaceflight Center Flight Robotics Laboratory and qualitative test results using recorded video from the Orbiter Docking System Camera (ODSC) during multiple orbiter to ISS docking missions. The Natural Feature Image Registration (NFIR) system consists of two modules: 1) Tracking which tracks the target object from image to image and estimates the position and orientation (pose) of the docking camera relative to the target object and 2) Acquisition which recognizes the target object if it is in the docking camera Field-of-View and provides an approximate pose that is used to initialize tracking. Detected image edges are matched to the 3d model edges whose predicted location, based on the pose estimate and its first time derivative from the previous frame, is closest to the detected edge1 . Mismatches are eliminated using a rigid motion constraint. The remaining 2d image to 3d model matches are used to make a least squares estimate of the change in relative pose from the previous image to the current image. The changes in position and in attitude are used as data for two Kalman filters whose outputs are smoothed estimate of position and velocity plus attitude and attitude rate that are then used to predict the location of the 3d model features in the next image.

Chien, Chiun-Hong↗
NASA NTRS2018

Imaging Technique for High Precision Measurement of Detector Stability for the Ocean Color Instrument

One of the new projects by NASA to explore environmental change is the Plankton, Aerosol, Cloud, ocean Ecosystem (PACE) spacecraft. The primary instrument aboard the PACE spacecraft is the Ocean Color Instrument (OCI), an advanced optical spectrometer that will measure the color of the ocean from the ultraviolet to shortwave infrared range for the purpose of observing and monitoring ocean and coastal biology. As part of the optical alignment testing that must be completed before the instrument is built, the measurement stability of the detectors at space flight operating temperatures must be determined to ensure alignment is maintained. Therefore, this project focuses on the development of an imaging technique that adheres to testing requirements and can be used to determine the stability of the OCI detector. The movements of targets affixed to a high-precision stage were analyzed through an image processing program to test the ability of the imaging technique to detect very small (under 10 micrometers) movements. It was found that movements as small as half a pixel (~6 microns) and 1 pixel (~12 microns) were able to be accurately and consistently detected with this imaging technique. This project found that the designed image analysis technique fulfills testing and measurement requirements and will be an effective metrology technique for the OCI detector stability test.

Optics↗
NASA NTRSDate not supplied

Lidar-Based Safe Site Relative Navigation

Established Safe and Precise Landing–Integrated Capability Evolution (SPLICE) project precision landing requirements necessitate a navigation filter architecture and underlying models developed specifically with these needs in mind. To date, test flights to characterize SPLICE guidance and navigation (GN) system performance have not provided a means to divert from the a priori selected landing site (LS) due to hazardous conditions. With the inclusion of a new sensor type, the Hazard Detection Lidar (HDL) coupled with safe landing site selection algorithms, GN can divert from the originally planned trajectory and navigate relative to the new targeted landing site. This discussion covers the navigation filter developments necessary to perform this estimation and process the resulting HDL measurements to meet project safe landing goals.

Navigation↗
NASA NTRSDate not supplied

P52D-1583 - Further Improvements to Constraints on Titan’s Atmospheric n-Butane, via Ground-Based Observations

We have acquired high spectral resolution ground-based observations of Titan in the mid-infrared from NASA Infrared Telescope Facility’s Texas Echelon Cross Echelle Spectrograph instrument , designed to constrain the abundances of new molecules within Titan’s atmosphere. The target molecule for this work, n-butane (n-C H ), though predicted by photochemical models of Titan’s atmosphere , has never been detected. Using the NEMESIS radiative transfer code , we retrieved a disk-averaged temperature profile for Titan by modeling CH emission in the 1248 cm region. Using this temperature profile, we then retrieved disk-averaged profiles of ethene (C H ), propane (C H ), and propene (C H ) in the 956 and 965 cm regions, which are also home to the strong and vibrational features of n-butane. We used an n-butane pseudoline list from JPL in order to systematically introduce a range of n-butane mixing ratios into the model, to constrain the molecule’s abundance based on the model’s changing fit to the data. We derive 3-confidence upper limits at an altitude of 150 km of 48 and 31 ppb for n-butane, via the and bands in the 956 and 965 cm regions, respectively. These are significantly tighter upper limits when compared to the ~300 ppb upper limit found in our recent work which used the same methodology but on much lower resolution limb data collected by the Cassini spacecraft. Upper limits on gas abundances are important for continued improvement of photochemical models of Titan’s atmosphere, which is understood to be an important analog for the prebiotic Earth atmosphere . They are also important for understanding the composition of Titan’s lakes and seas, which are likely to contain these larger hydrocarbons . Finally, as larger molecules like C ’s are thought to be able to serve as formation sites for building haze particles, constraining their abundances is important for understanding the process of haze formation at Titan and at Earth Ref: [1] J. H. Lacy, et al., PASP, 2002. [2] Y.L. Yung, et al., ApJS, 1984. [3] M. Dobrijevic, et al., Icarus, 2021. [4] P. G. J. Irwin et al., JQSRT, 2008. [5] K. Sung, et al., JQSRT, 2020. [6] B. L. Steffens, et al., PSJ, 2022. [7] Clarke & Ferris, Origins Life Evol. Biosphere, 1997. [8] D. Cordier, et al., ApJ, 2008. [9] D. B. Curtis, et al., JPCA, 2005.

Brendan Steffens↗
DOE OSTI2020

Proteomic Tissue-Based Classifier for Early Prediction of Prostate Cancer Progression

Although ~40% of screen-detected prostate cancers (PCa) are indolent, advanced-stage PCa is a lethal disease with 5-year survival rates around 29%. Identification of biomarkers for early detection of aggressive disease is a key challenge. Starting with 52 candidate biomarkers, selected from existing PCa genomics datasets and known PCa driver genes, we used targeted mass spectrometry to quantify proteins that significantly differed in primary tumors from PCa patients treated with radical prostatectomy (RP) across three study outcomes: (i) metastasis ≥1-year post-RP, (ii) biochemical recurrence ≥1-year post-RP, and (iii) no progression after ≥10 years post-RP. Sixteen proteins that differed significantly in an initial set of 105 samples were evaluated in the entire cohort (n = 338). A five-protein classifier which combined FOLH1, KLK3, TGFB1, SPARC, and CAMKK2 with existing clinical and pathological standard of care variables demonstrated significant improvement in predicting distant metastasis, achieving an area under the receiver-operating characteristic curve of 0.92 (0.86, 0.99, p = 0.001) and a negative predictive value of 92% in the training/testing analysis. This classifier has the potential to stratify patients based on risk of aggressive, metastatic PCa that will require early intervention compared to low risk patients who could be managed through active surveillance.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2026

Investigation of the isoscalar monopole response in the proton-rich nucleus 14 O

Deuteron inelastic scattering on 14 O was measured in inverse kinematics using an active-target time projection chamber and a magnetic spectrograph. The experimental technique enabled precise measurements of deuteron recoiling particles in coincidence with beam-like fragments detected in the spectrograph focal plane. The double differential cross section was reconstructed for scattering angles of 3–6 degrees and excitation energies up to 26 MeV. The monopole strength distribution was obtained from the data using a multipole decomposition analysis. The results were compared to quasiparticle random-phase approximation (QRPA) and generator coordinate method (GCM) calculations. The QRPA calculation accurately describes experimental data in the energy range of 13 to 26 MeV. GCM calculations assuming a 12 C (g . s .) + p + p cluster configuration were used to determine the 0 + strength in 14 O below 13 MeV. The monopole transition strength of these cluster states provides a good description of the experimental distribution in the 9–11 MeV region, while the 0$^{+}_{2}$ state accounts for only a small fraction of the experimental strength around 6 MeV.

Active target↗
DOE OSTI2021

Refined Telluric Absorption Correction for Low-resolution Ground-based Spectroscopy: Resolution and Radial Velocity Effects in the O{sub 2}A-band for Exoplanets and K i Emission Lines

Telluric correction of spectroscopic observations is either performed via standard stars that are observed close in time and airmass along with the science target, or recently growing in importance, by theoretical telluric absorption modeling. Both approaches work fine when the telluric lines are resolved, i.e., at a spectral resolving power larger than about 10,000, and it is sufficient to facilitate the detection of spectral features at lower resolution. However, a meaningful quantitative analysis also requires the reliable recovery of line strengths. Here, we show for the Fraunhofer A-band of molecular O{sub 2} that the standard telluric correction approach fails in this at lower spectral resolutions, as an example for the general problem. Doppler-shift-dependent errors of the restored flux may arise, which can amount to more than 50% in extreme cases, depending on the line shapes of the target spectral features. Two applications are discussed: the recovery of the O{sub 2} band in the reflected light of an Earth analog atmosphere, as facilitated potentially in the future using an orbiting starshade and a ground-based extremely large telescope; and the recovery of the intrinsic ratio of the K i lines in the post-nova V4332 Sgr tracing the optical depth of the emitting region, to exemplify the relevance using present-day instrumentation. We show how one should derive correction functions for the compensation of the error in dependence of radial velocity shift, spectral resolution, and target line-profile function by use of high-resolution atmospheric transmission modeling, which has to be solved for the individual case.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
NASA NTRSDate not supplied

Repurposing Drilling Control Diagnostics for Subsurface Edge Detection and Boundary Advisement During Planetary Drilling

Informed decision-making during lunar drilling and sampling missions will require data monitoring tools and specialized ground data systems. Accurate and updated situational awareness, with ongoing data monitoring, is critical for timely responses by to incoming science data. Traverse plans and scheduled activities may need to be flexibly changed in order to react to unexpected data or situations. Unlike (for example) Mars missions, the relative lightspeed closeness of the Moon allows for near-real-time ground processing of incoming mission and instrument data. An Apollo-class lunar regolith drill will in a sense “travel” a meter or two vertically at a given subsurface characterization site. As the drill penetrates into lunar regolith, it is likely to encounter a range of material densities, orientations, fracture toughness, and (perhaps) ice percentages. Lunar drill telemetry can provide science teams with a valuable first look into the subsurface structure, the regolith bulk properties, and constituents at each drilled site. Real-time AI-based recognition and reaction to downhole situations has been developed for automated deeper drilling on Mars and beyond. We can leverage the same knowledge bases and pattern-matching as areal-time interpreter of the subsurface, a situational awareness tool during drilling operations. We recently (Sept. 2019) demonstrated this AI drilling monitoring and analysis capability, in control of in-situ drilling and sampling operations, mounted on a KREX-2 rover in Chile’s Atacama Desert. Terrestrial automated drilling log analyses in oil exploration have used similar machine learning techniques in classifying and identifying features in drilling logs –but these typically are designed assuming a drilling fluid influencing downhole measurements and data (permeability, resistivity). Drilling models and existing AI software designed to detect and respond to drilling faults and hard materials can be repurposed, for near-real-time (ground-based) interpretation of drilling telemetry –a potentially valuable advisory tool for strata boundaries and changes in drilling parameters. On the Moon, this approach could be used to study the structure and to some extent the composition of lunar regolith vs. borehole depth, based on recognizable variations in fracture hardness, drilling energy and penetration rates while actively drilling. Since the early 2000s, a series of increasingly-capable real-time drilling telemetry interpretation and characterization software tools have been developed. These subsurface models and software tools have monitored the real-time drilling data received, and automatically identified changes in drill behavior (e.g., encountering a harder target layer, bit inclusions, drill choking due to infall downhole, and others) correlating these with subsurface structures and features. We discuss the mappings between drill borehole parameters, faults or events detected, and modeled changes in rock layer boundaries, in examples drawn from field testing at analog sites in an Arctic impact crater, Rio Tinto, and Chile’s Atacama Desert. These demonstrate how subsurface structural boundaries led to fault detections and responses by the software.

drilling advisor↗
NASA NTRSDate not supplied

Merging Analytic Collaborative Frameworks with New Observing Strategies Toward a Digital Twin: Earth – Episodic Pulse Event Impacts on Ocean Carbon Cycle as an Example

Virtual representations of the Earth will allow us to address some of the most critical environmental issues of our time. Here, we show the first steps toward representation of riverine, estuarine, and coastal carbon processes to enable scenario driven “what-if” analyses of the carbon system and human footprint. Excess sediment and nutrient runoff from land-based human activities impact water quality and can pose serious threats to coastal and marine ecosystems. Episodic pulse events, such as extreme precipitation events, can increase the amount of nutrients entering estuaries and coastal regions, potentially leading to large phytoplankton blooms followed by anoxic conditions. Consequences of coastal runoff are predicted to increase with the higher intensity and frequency of extreme events. Beyond the threat to coastal ecosystems, recent findings suggest these episodic pulses might play a significant role for biological production influencing regional and global carbon fluxes and budgets. An improved understanding of these events through optimal, dynamic observing strategies will increase our knowledge of the land-ocean continuum and how regional events and nutrient fluxes affect the carbon cycle and ocean ecosystem. This conceptual framework enables focused science investigations by pairing data analytics and artificial intelligence tools (otherwise termed an Analytic Center Framework, ACF) with targeted measurement acquisition through distributed sensing and intelligent asset tasking (or New Observing Strategies, NOS). This NOS and ACF iterative approach acquires and integrates complementary and coincident satellite, in-situ and model data to build a more complete and in-depth picture of science phenomena. Specifically, Apache Science Data Analytic Platform (SDAP) is extended to incorporate relevant datasets for data access, harmonized analysis, and anomaly detection. When conditions are met for a likely pulse event, NASA’s D-SHIELD (Distributed Spacecraft with Heuristic Intelligence to Enable Logistical Decisions) tool is triggered to optimize asset overpass frequency and schedule observations for persistent monitoring. Targeted data is ingested by SDAP for enhanced investigation via iterative analysis until the trigger criteria is no longer met - steps toward a digital twin.

Laura Rogers↗
NASA NTRS2020

Dim Prospects for Transmission Spectra of Ocean Earths Around M Stars

The search for water-rich Earth-sized exoplanets around low-mass stars is rapidly gaining attention because they represent the best opportunity to characterize habitable planets in the near future. Understanding the atmospheres of these planets and determining the optimal strategy for characterizing them through transmission spectroscopy with our upcoming instrumentation is essential in order to constrain their environments. For this study, we present simulated transmission spectra of tidally locked Earth-sized ocean-covered planets around late-M to mid-K stellar spectral types, utilizing GCM modeling results previously published by Kopparapu et al. (2017) as inputs for our radiative transfer calculations performed using NASA's Planetary Spectrum Generator (psg.gsfc.nasa.gov; Villanueva et al. (2018)). We identify trends in the depth of H2O spectral features as a function of planet surface temperature and rotation rate. These trends allow us to calculate the exposure times necessary to detect water vapor in the atmospheres of aquaplanets through transmission spectroscopy with the upcoming James Webb Space Telescope (JWST) as well as several future flagship space telescope concepts under consideration (LUVOIR and OST) for a target list constructed from the TESS Input Catalog (TIC). Our calculations reveal that transmission spectra for water-rich Earth-sized planets around low-mass stars will be dominated by clouds, with spectral features < 20 ppm, and only a small subset of TIC stars would allow for the characterization of an ocean planet in the Habitable Zone. We thus present a careful prioritization of targets that are most amenable to follow-up characterizations with next-generation instrumentation, in order to assist the community in efficiently utilizing precious telescope time.

exoplanet atmospheres↗
NASA NTRS2012

HyspIRI Cloud Mask Detection Algorithm Theoretical Basis Document

The Hyperspectral Infrared Imager (HyspIRI) satellite includes a thermal infrared (TIR) multispectral scanner with seven spectral bands in the thermal infrared (TIR) between 7 and 12 μm and one band in the mid-infrared between 3 and 5 μm designed to measure hot targets. The TIR bands have a NEΔT of <0.2 K at 300K and all bands have a spatial scale of 60 m. The two primary Level-2 products that will be generated by HyspIRI TIR data are land surface temperature and emissivity. A critical aspect of minimizing uncertainties in these products and in generating global Level-3 products is an accurate and reliable cloud mask algorithm. This document describes the methodology behind developing the HyspIRI Cloud Mask Algorithm (HyCMA), and challenges associated with cloud detection. The HyCMA will derive its heritage from previously well established cloud mask algorithms such as the Landsat ACCAA, MODIS MOD35 and AVHRR.

Hook, Simon J.↗