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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 NTRS1992

Constraints on the power spectrum of the primordial density field from large-scale data - Microwave background and predictions of inflation

It is shown here that, by using galaxy catalog correlation data as input, measurements of microwave background radiation (MBR) anisotropies should soon be able to test two of the inflationary scenario's most basic predictions: (1) that the primordial density fluctuations produced were scale-invariant and (2) that the universe is flat. They should also be able to detect anisotropies of large-scale structure formed by gravitational evolution of density fluctuations present at the last scattering epoch. Computations of MBR anisotropies corresponding to the minimum of the large-scale variance of the MBR anisotropy are presented which favor an open universe with P(k) significantly different from the Harrison-Zeldovich spectrum predicted by most inflationary models.

Kashlinsky, A.↗
NASA NTRS2018

NeMO-Net & Fluid Lensing: The Neural Multi-Modal Observation & Training Network for Global Coral Reef Assessment Using Fluid Lensing Augmentation of NASA EOS Data

We present preliminary results from NASA NeMO-Net, the first neural multi-modal observation and training network for global coral reef assessment. NeMO-Net is an open-source deep convolutional neural network (CNN) and interactive active learning training software in development which will assess the present and past dynamics of coral reef ecosystems. NeMO-Net exploits active learning and data fusion of mm-scale remotely sensed 3D images of coral reefs captured using fluid lensing with the NASA FluidCam instrument, presently the highest-resolution remote sensing benthic imaging technology capable of removing ocean wave distortion, as well as hyperspectral airborne remote sensing data from the ongoing NASA CORAL mission and lower-resolution satellite data to determine coral reef ecosystem makeup globally at unprecedented spatial and temporal scales. Aquatic ecosystems, particularly coral reefs, remain quantitatively misrepresented by low-resolution remote sensing as a result of refractive distortion from ocean waves, optical attenuation, and remoteness. Machine learning classification of coral reefs using FluidCam mm-scale 3D data show that present satellite and airborne remote sensing techniques poorly characterize coral reef percent living cover, morphology type, and species breakdown at the mm, cm, and meter scales. Indeed, current global assessments of coral reef cover and morphology classification based on km-scale satellite data alone can suffer from segmentation errors greater than 40%, capable of change detection only on yearly temporal scales and decameter spatial scales, significantly hindering our understanding of patterns and processes in marine biodiversity at a time when these ecosystems are experiencing unprecedented anthropogenic pressures, ocean acidification, and sea surface temperature rise. NeMO-Net leverages our augmented machine learning algorithm that demonstrates data fusion of regional FluidCam (mm, cm-scale) airborne remote sensing with global low-resolution (m, km-scale) airborne and spaceborne imagery to reduce classification errors up to 80% over regional scales. Such technologies can substantially enhance our ability to assess coral reef ecosystems dynamics.

satellite data↗
NASA NTRS2018

NASA NeMO-Net

We present preliminary results from NASA NeMO-Net, the first neural multi-modal observation and training network for global coral reef assessment. NeMO-Net is an open-source deep convolutional neural network (CNN) and interactive active learning training software in development which will assess the present and past dynamics of coral reef ecosystems. NeMO-Net exploits active learning and data fusion of mm-scale remotely sensed 3D images of coral reefs captured using fluid lensing with the NASA FluidCam instrument, presently the highest-resolution remote sensing benthic imaging technology capable of removing ocean wave distortion, as well as hyperspectral airborne remote sensing data from the ongoing NASA CORAL mission and lower-resolution satellite data to determine coral reef ecosystem makeup globally at unprecedented spatial and temporal scales. Aquatic ecosystems, particularly coral reefs, remain quantitatively misrepresented by low- resolution remote sensing as a result of refractive distortion from ocean waves, optical attenuation, and remoteness. Machine learning classification of coral reefs using FluidCam mm-scale 3D data show that present satellite and airborne remote sensing techniques poorly characterize coral reef percent living cover, morphology type, and species breakdown at the mm, cm, and meter scales. Indeed, current global assessments of coral reef cover and morphology classification based on km-scale satellite data alone can suffer from segmentation errors greater than 40%, capable of change detection only on yearly temporal scales and decameter spatial scales, significantly hindering our understanding of patterns and processes in marine biodiversity at a time when these ecosystems are experiencing unprecedented anthropogenic pressures, ocean acidification, and sea surface temperature rise. NeMO-Net leverages our augmented machine learning algorithm that demonstrates data fusion of regional FluidCam (mm, cm-scale) airborne remote sensing with global low-resolution (m, km-scale) airborne and spaceborne imagery to reduce classification errors up to 80% over regional scales. Such technologies can substantially enhance our ability to assess coral reef ecosystems dynamics.

NASA↗
DOE OSTI2026

First Detection of the Baryon Acoustic Oscillation (BAO) Feature in the 3-Point Correlation Function of DESI DR1 Luminous Red Galaxies

We present the first detection of the 3-Point Correlation Function (3PCF) Baryon Acoustic Oscillation (BAO) signal from the DESI Data Release 1 (DR1) sample of Luminous Red Galaxies (LRGs), which contains over 2.1 million galaxies. Our analysis is based on a tree-level redshift-space bispectrum template, which is then transformed to position space using the Fast Fourier Transform on Logarithmic scales (FFTLog) algorithm. We detect the BAO feature with a significance of approximately $8.1σ$ using the EZmock covariance matrix and $8.5σ$ using the analytical covariance matrix, for the full LRG redshift range ($0.4

Kamalinejad, Farshad [Florida U.] (ORCID:000000017↗
NASA NTRS1971

Detection and Characterization of Stress Symptoms in Forest Vegetation

Techniques used at the Pacific Southwest Forest and Range Experiment Station to detect advanced and previsual symptoms of vegetative stress are discussed. Stresses caused by bark beetles in coniferous stands of timber are emphasized because beetles induce stress more rapidly than most other destructive agents. Bark beetles are also the most damaging forest insects in the United States. In the work on stress symptoms, there are two primary objectives: (1) to learn the best combination of films, scales, and filters to detect and locate injured trees from aircraft and spacecraft, and (2) to learn if stressed trees can be detected before visual symptoms of decline occur. Equipment and techniques used in a study of the epidemic of the Black Hills bark beetle are described.

Heller, R. C.↗
DOE OSTI2025

Searching for MeV-mass neutrinophilic dark matter with large scale dark matter detectors

The indirect detection of dark matter (DM) through its annihilation products is one of the primary strategies for DM detection. One of the least constrained classes of models is neutrinophilic DM, because the annihilation products, weakly interacting neutrinos, are challenging to observe. Here, we consider a scenario where MeV-mass DM exclusively annihilates to the third neutrino mass eigenstate, which is predominantly of tau and muon flavor. In such a scenario, the potential detection rate of the neutrinos originating from the DM annihilation in our Galaxy in the conventional detectors would be suppressed by up to approximately two orders of magnitude. This is because the best sensitivity of such detectors for neutrinos with energies below approximately 100 MeV is for electron neutrino flavor. In this work, we highlight the potential of large-scale DM detectors in uncovering such signals in the tens of MeV range of DM masses. In addition, we discuss how coincident signals in direct detection DM experiments and upcoming neutrino detectors such as DUNE, Hyper-Kamiokande, and JUNO could provide new perspectives on the DM problem. Published by the American Physical Society 2025

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
NASA NTRS1980

Diffuse X-ray emission from the jets of SS 433

The detection of large-scale diffuse X-ray jets from the variable-emission-line object SS 433 is reported. Observations were made with the high resolution imager and imaging proportional counter on board the Einstein X-ray Observatory. The two diffuse X-ray features discovered are found to be aligned with both the central source of SS 433 and with the bulges of the shell of the huge supernova remnant W 50 associated with SS 433, thus confirming the detection of jets related to SS 433 and the link between SS 433 and W 50, establishing a minimum age of 1000 years for the jet phenomenon and offering an explanation of the size of W 50. Processes by which two oppositely directed beams of material from the SS 433 source region may emit the diffuse X-rays are then considered, including shock heating by interactions with the ambient medium and synchrotron radiation. Similarities between the morphologies of the diffuse X-ray emission and those of radio galaxies are also noted.

Seward, F.↗
NASA NTRS2019

The Lyα Luminosity Function and Cosmic Reionization at z ~ 7.0: A Tale of Two LAGER Fields

We present the largest-ever sample of 79 Lyα emitters (LAEs) at z ~ 7.0 selected in the COSMOS and CDFS fields of the LAGER project (the Lyman Alpha Galaxies in the Epoch of Reionization). Our newly amassed ultradeep narrowband exposure and deeper/wider broadband images have more than doubled the number of LAEs in COSMOS, and we have selected 30 LAEs in the second field CDFS. We detect two large-scale LAE-overdense regions in the COSMOS that are likely protoclusters at the highest redshift to date. We perform injection and recovery simulations to derive the sample incompleteness. We show that significant incompleteness comes from blending with foreground sources, which, however, has not been corrected in LAE luminosity functions (LFs) in the literature. The bright-end bump in the Lyα LF in COSMOS is confirmed with six (two newly selected) luminous LAEs (LLyα > 1043.3 erg s−1). Interestingly, the bump is absent in CDFS, in which only one luminous LAE is detected. Meanwhile, the faint-end LFs from the two fields agree well with each other. The six luminous LAEs in COSMOS coincide with two LAE-overdense regions, while such regions are not seen in CDFS. The bright-end LF bump could be attributed to ionized bubbles in a patchy reionization. It appears associated with cosmic overdensities and thus supports an inside-out reionization topology at z ~ 7.0, i.e., the high-density peaks were ionized earlier compared to the voids. An average neutral hydrogen fraction of xH I ~ 0.2–0.4 is derived at z ~ 7.0 based on the cosmic evolution of the Lyα LF.

cosmology: observations↗
NASA NTRS2004

Nuclear Microprobe using Elastic Recoil Detection (ERD) for Hydrogen Profiling in High Temperature Protonic Conductors

The interaction between hydrogen and various high temperature protonic conductors (HTPC) has not been clearly understood due to poor densification and unreacted secondary phases. the melt-processing technique is used in producing fully dense simple SrCe(0.9)Y (0.10) O(3-delta) and complex Sr3Ca(1+x)Nb(2+x)O(9-delta) perovskites that can not be achieved by solid-state sintering. the possibilities of ion beam analysis have been investigated to quantify hydrogen distribution in HTPC perovskites subjected to water heat treatment. Nuclear microprobe technique is based on the interactions of a focused ion beam of MeV light ions (H-1, H-2, He-3, He-4,.) with the sample to be analyzed to determine local elemental concentrations at the cubic micrometer scale, the elastic recoil detection analysis technique (ERDA) has been carried out using He-4(+) microbeams and detecting the resulting recoil protons. Mappings of longitudinal sections of water treated SrCeO3 and Sr(Ca(1/3)Nb(2/3))O3 perovskites have been achieved, the water treatment strongly alters the surface of simple SrCe(0.9)Y(0.10)O(3-delta) perovskite. From Rutherford Back Scattering measurements (RBS), both Ce depletion and surface re-deposition is evidenced. the ERDA investigations on water treated Sr3Ca(1+x)Nb(2+x)O(9-delta) perovskite did not exhibit any spatial difference for the hydrogen incorporation from the surface to the centre. the amount of hydrogen incorporation for Sr3Ca(1+x)Nb(2+x)O(9-delta) was low and required further development of two less conventional techniques, ERDA in forward geometry and forward elastic diffusion H-1(p,p) H-1 with coincidence detection.

Berger, Pascal↗
NASA NTRS2018

Field Exploration and Life Detection Sampling for Planetary Analogue Research (FELDSPAR): Variability and Correlation in Biomarker and Mineralogy Measurements from Icelandic Mars Analogues

In situ exploration of planetary environments allows biochemical analysis of sub-centimeter-scale samples; however, landing sites are selected a priori based on measurable meter- to kilometer-scale geological features. Optimizing life detection mission science return requires both understanding the expected biomarker distributions across sample sites at different scales and efficiently using first-stage in situ geochemical instruments to justify later-stage biological or chemical analysis. Icelandic volcanic regions have an extensive history as Mars analogue sites due to desiccation, low nutrient availability, and temperature extremes, in addition to the advantages of geological youth and isolation from anthropogenic contamination. Many Icelandic analogue sites are also rugged and remote enough to create the same type of instrumentation and sampling constraints typically faced by robotic exploration.

Planetary↗
DOE OSTI2024

Computed Tomography Scanning and Geophysical Measurements of UW Enterprises LP 1-250512-129 Well in Southwestern Indiana

The computed tomography (CT) facilities and the Multi-Sensor Core Logger (MSCL) at the National Energy Technology Laboratory (NETL) in Morgantown, West Virginia, were used to characterize Illinois Basin core of the Upper Devonian-Early Mississippian New Albany Shale Formation from Posey County, Indiana. The primary impetus of this work is a collaboration between Indiana Geological and Water Survey at Indiana University Bloomington, NETL, and Woolsey Operating Company LLC to characterize and make publicly available core information from the New Albany Shale of the Illinois Basin. Core characterization of this unconventional oil/gas well will aid in understanding the lithology changes and the fracture complexity of the New Albany Shale. There is a potential for this formation to be developed in the future for critical mineral and rare earth element (CM/REE) extraction. The resultant datasets are presented in this report and can be accessed from NETL's Energy Data eXchange (EDX) online system using the following link: https://edx.netl.doe.gov/dataset/uw-enterprises. All equipment and techniques used were non-destructive, enabling future examinations and analyses to be performed on this core. None of the equipment used was suitable for direct visualization of the pore space in the fine-grained structures studied; however, fractures, discontinuities, and millimeter-scale features were readily detectable with the methods tested. Imaging with the NETL medical CT scanner was performed on the entire core. Targeted higher resolution CT scanning of select sections was performed with NETL’s industrial and micro-CT scanner. Qualitative analysis of the medical CT images, coupled with X-ray fluorescence (XRF), P-wave, and magnetic susceptibility measurements from the MSCL were useful in identifying zones of interest for more detailed analysis. The ability to quickly identify key areas for more detailed study with higher resolution will save time and resources in future studies. The combination of methods used provides a multi-scale analysis of the core; the resulting macro and micro descriptions are relevant to many subsurface energy related examinations traditionally performed at NETL.

58 GEOSCIENCES↗
NASA NTRS2003

Evidence for Filamentary Jet Structure: The Light Curve of GRB 011211

We report on the discovery of the optical afterglow of the X-ray rich, long-duration gamma-ray burst GRB 011211, and the oscillatory behavior present in its optical and X-ray afterglow light curve. The time scale of the fluctuations, -1 hour, is much smaller than the time of the observations, -12 hours from the onset of the gamma-ray burst. The character and strength of the fluctuations visible in the optical data are unprecedented, and are inconsistent with causally connected variations in the emission of a symmetric, relativistic blast wave. Moreover, the differential time lag between the short-term variations in X-ray and optical energies suggests they do not arise from the same emitting region. Such variability may imply that local spherical symmetry is broken because the energy content across the jet-emitting surface is not uniform, indicating the detection of a small scale substructure within the jet itself.

Jakobsson, P.↗
DOE OSTI2024

Computed Tomography Scanning and Petrophysical Measurements of Eastern Williston Basin Twin Buttes and Hagel Formations

The computed tomography (CT) facilities and the Multi-Sensor Core Logger (MSCL) at the U.S. Department of Energy’s (DOE) National Energy Technology Laboratory (NETL) in Morgantown, West Virginia, were used to characterize core from two wells that represent coal resources across North Dakota. These include the MC23080C Well in Mercer County and the 23-B001 Well in Oliver County. The primary impetus of this work was to capture a detailed digital representation of the core from the MC23080C and 23-B001 Wells. The collaboration between the NETL and the Energy and Environment Research Center (EERC) enables other research entities to access information about this potential carbon ore, rare earth, and critical mineral resource plays in the Williston Basin. All equipment and techniques used were non-destructive, enabling future examinations and analyses to be performed on these cores. Fractures, discontinuities, and millimeter-scale features were readily detectable with the medical CT scanner acquired images. Imaging with the NETL medical CT scanner was performed on entire cores. Qualitative analysis of the medical CT images, coupled with X-ray fluorescence (XRF), gamma density, and magnetic susceptibility measurements from the MSCL were useful in identifying zones of interest for potential future analysis. Higher-resolution industrial and micro-CT images were acquired from selected zones along the depth of the core to visualize the structure in higher detail. The ability to quickly identify key areas for more detailed study with higher resolution will save time and resources in future studies. The combination of methods used provides a multi-scale analysis of the core, with the resulting macro- and micro-descriptions relevant to many subsurface energy-related examinations traditionally performed at NETL.

01 COAL, LIGNITE, AND PEAT↗
NASA NTRSDate not supplied

ISS Lightning Imaging Sensor and STP-H8/ASAP Observations

What is ISS LIS? - ISS Lightning Imaging Sensor (LIS) is the flight spare for the Tropical Rainfall Measuring Mission (TRMM) LIS instrument - Modified to work on ISS and launched as part of STP-H5 in February 2017 - Detects lightning (via near-IR 777-nm channel) during both day and night, with storm-scale resolution and globally uniform detection efficiency - Relocated on ISS July 2022, expected to operate thru at least December 2023

Timothy Lang↗
NASA NTRS2007

Benchtop Detection of Proteins

A process, and a benchtop-scale apparatus for implementing the process, have been developed to detect proteins associated with specific microbes in water. The process and apparatus may also be useful for detection of proteins in other, more complex liquids. There may be numerous potential applications, including monitoring lakes and streams for contamination, testing of blood and other bodily fluids in medical laboratories, and testing for microbial contamination of liquids in restaurants and industrial food-processing facilities. A sample can be prepared and analyzed by use of this process and apparatus within minutes, whereas an equivalent analysis performed by use of other processes and equipment can often take hours to days. The process begins with the conjugation of near-infrared-fluorescent dyes to antibodies that are specific to a particular protein. Initially, the research has focused on using near-infrared dyes to detect antigens or associated proteins in solution, which has proven successful vs. microbial cells, and streamlining the technique in use for surface protein detection on microbes would theoretically render similar results. However, it is noted that additional work is needed to transition protein-based techniques to microbial cell detection. Consequently, multiple such dye/antibody pairs could be prepared to enable detection of multiple selected microbial species, using a different dye for each species. When excited by near-infrared light of a suitable wavelength, each dye fluoresces at a unique longer wavelength that differs from those of the other dyes, enabling discrimination among the various species. In initial tests, the dye/antibody pairs are mixed into a solution suspected of containing the selected proteins, causing the binding of the dye/antibody pairs to such suspect proteins that may be present. The solution is then run through a microcentrifuge that includes a membrane that acts as a filter in that it retains the dye/antibody/protein complexes while allowing any remaining unbound dye/antibody pairs to flow away. The retained dye/antibody/protein complexes are transferred to a cuvette, wherein they are irradiated with light from a miniature near-infrared laser delivered via a fiber-optic cable. The resulting fluorescence from the dye(s) is measured by use of a miniature spectrometer, the output of which is digitized, then analyzed by laptop computer. The software running in the computer identifies the protein species by the wavelengths of their spectral peaks and determines the amounts of the proteins, and thus, one day, microbes of the various species from the intensities of the peaks. The abovementioned removal of the unbound dye/antibody pairs during centrifugation prevents false positive readings. The process proves successful in detecting proteins in solution and thus can now be employed for use in microbe detection.

Scardelletti, Maximilian C.↗
NASA NTRS2023

The First X-Ray Polarimetric Observation of the Black Hole Binary LMC X-1

We report on an X-ray polarimetric observation of the high-mass X-ray binary LMC X-1 in the high/soft state, obtained by the Imaging X-ray Polarimetry Explorer ( IXPE ) in 2022 October. The measured polarization is below the minimum detectable polarization of 1.1 per cent (at the 99 per cent confidence level). Simultaneously, the source was observed with the Neutron Star Interior Composition Explorer (NICER), Nuclear Spectroscopic Telescope Array ( NuSTAR ), and Spectrum-Rontgen-Gamma ( SRG )/Astronomical Roentgen Telescope – X-ray Concentrator (ART-XC) instruments, which enabled spectral decomposition into a dominant thermal component and a Comptonized one. The low 2–8 keV polarization of the source did not allow for strong constraints on the black hole spin and inclination of the accretion disc. However, if the orbital inclination of about 36◦ is assumed, then the upper limit is consistent with predictions for pure thermal emission from geometrically thin and optically thick discs. Assuming the polarization degree of the Comptonization component to be 0, 4, or 10 per cent, and oriented perpendicular to the polarization of the disc emission (in turn assumed to be perpendicular to the large-scale ionization cone orientation detected in the optical band), an upper limit to the polarization of the disc emission of 1.0, 0.9, or 0.9 per cent, respectively, is found (at the 99 per cent confidence level).

LMC X-1↗
NASA NTRS2000

BOREAS AFM-12 1-km AVHRR Seasonal Land Cover Classification

The Boreal Ecosystem-Atmosphere Study (BOREAS) Airborne Fluxes and Meteorology (AFM)-12 team's efforts focused on regional scale Surface Vegetation and Atmosphere (SVAT) modeling to improve parameterization of the heterogeneous BOREAS landscape for use in larger scale Global Circulation Models (GCMs). This regional land cover data set was developed as part of a multitemporal one-kilometer Advanced Very High Resolution Radiometer (AVHRR) land cover analysis approach that was used as the basis for regional land cover mapping, fire disturbance-regeneration, and multiresolution land cover scaling studies in the boreal forest ecosystem of central Canada. This land cover classification was derived by using regional field observations from ground and low-level aircraft transits to analyze spectral-temporal clusters that were derived from an unsupervised cluster analysis of monthly Normalized Difference Vegetation Index (NDVI) image composites (April-September 1992). This regional data set was developed for use by BOREAS investigators, especially those involved in simulation modeling, remote sensing algorithm development, and aircraft flux studies. Based on regional field data verification, this multitemporal one-kilometer AVHRR land cover mapping approach was effective in characterizing the biome-level land cover structure, embedded spatially heterogeneous landscape patterns, and other types of key land cover information of interest to BOREAS modelers.The land cover mosaics in this classification include: (1) wet conifer mosaic (low, medium, and high tree stand density), (2) mixed coniferous-deciduous forest (80% coniferous, codominant, and 80% deciduous), (3) recent visible bum, vegetation regeneration, or rock outcrops-bare ground-sparsely vegetated slow regeneration bum (four classes), (4) open water and grassland marshes, and (5) general agricultural land use/ grasslands (three classes). This land cover mapping approach did not detect small subpixel-scale landscape features such as fens, bogs, and small water bodies. Field observations and comparisons with Landsat Thematic Mapper (TM) suggest a minimum effective resolution of these land cover classes in the range of three to four kilometers, in part, because of the daily to monthly compositing process. In general, potential accuracy limitations are mitigated by the use of conservative parameterization rules such as aggregation of predominant land cover classes within minimum horizontal grid cell sizes of ten kilometers. The AFM-12 one-kilometer AVHRR seasonal land cover classification data are available from the Earth Observing System Data and Information System (EOSDIS) Oak Ridge National Laboratory (ORNL) Distributed Active Archive Center (DAAC). The data files are available on a CD-ROM (see document number 20010000884).

Steyaert, Lou↗
NASA NTRS2019

Pixel Based Model for High Latitude Dust Detection

High Latitude Dust (HLD, ≥ 50°𝑁 𝑎𝑛𝑑 ≥ 40°𝑆 ) load has implications on the energy budget, ocean biodiversity and economy on a regional and global scale. Current methods of dust detection rely on spectral sensitivity at visible (RGB) and infrared wavelengths. The characteristics of HLD vary according to the sediments and sedimentary processes operating on the land surface that are the source of the dust particles. Leveraging machine learning (ML) methods, we propose a new detection method based on convolutional neural network (CNN) using true color images.

Priftis, Georgios↗