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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 1,603 records · Page 89

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NASA NTRS1971

Aerodynamic characteristics of Lockheed delta-body orbiter and stage-and-one-half launch vehicle

An experimental wind tunnel test program was conducted to investigate the subsonic through high supersonic aerodynamic characteristics of the Lockheed delta lifting body orbiter and stage-and-one-half launch vehicle. Analyses and results of these data are presented. A 0.01-scale model of the LS 200-5 system was designed and fabricated for testing in wind tunnels. Orbiter and launch configurations were tested over a speed range of Mach 0.6 to 2.0, whereas only the orbiter was tested over a speed range of Mach 2.3 to 4.6. Six-component force and moment data, base pressures, and schlieren photos were obtained at various angles-of-attack and sideslip. A 0.03-scale model of the orbiter was also designed, fabricated, and tested in a wind tunnel. Six-component force and moment data, base pressure, and a limited amount of tuft flow visualization data were obtained on a variety of configuration combinations.

Velligan, F. A.↗

NASA NTRS1994

Cosmic microwave background anisotropies in cold dark matter models with cosmological constant: The intermediate versus large angular scales

We obtain predictions for cosmic microwave background anisotropies at angular scales near 1 deg in the context of cold dark matter models with a nonzero cosmological constant, normalized to the Cosmic Background Explorer (COBE) Differential Microwave Radiometer (DMR) detection. The results are compared to those computed in the matter-dominated models. We show that the coherence length of the Cosmic Microwave Background (CMB) anisotropy is almost insensitive to cosmological parameters, and the rms amplitude of the anisotropy increases moderately with decreasing total matter density, while being most sensitive to the baryon abundance. We apply these results in the statistical analysis of the published data from the UCSB South Pole (SP) experiment (Gaier et al. 1992; Schuster et al. 1993). We reject most of the Cold Dark Matter (CDM)-Lambda models at the 95% confidence level when both SP scans are simulated together (although the combined data set renders less stringent limits than the Gaier et al. data alone). However, the Schuster et al. data considered alone as well as the results of some other recent experiments (MAX, MSAM, Saskatoon), suggest that typical temperature fluctuations on degree scales may be larger than is indicated by the Gaier et al. scan. If so, CDM-Lambda models may indeed provide, from a point of view of CMB anisotropies, an acceptable alternative to flat CDM models.

Stompor, Radoslaw↗

NASA NTRS2001

Radarsat Antarctic Mapping Project: Antarctic Imaging Campaign 2

The Radarsat Antarctic Mapping Project is a collaboration between NASA and the Canadian Space Agency to map Antarctica using synthetic aperture radar (SAR). The first Antarctic Mapping Mission (AMM-1) was successfully completed in October 1997. Data from the acquisition phase of the 1997 campaign have been used to achieve the primary goal of producing the first, high-resolution SAR image map of Antarctica. The limited amount of data suitable for interferometric analysis have also been used to produce remarkably detailed maps of surface velocity for a few selected regions. Most importantly, the results from AMM-1 are now available to the general science community in the form of various resolution, radiometrically calibrated and geometrically accurate image mosaics. The second Antarctic imaging campaign occurred during the fall of 2000. Modified from AMM-1, the satellite remained in north looking mode during AMM-2 restricting coverage to regions north of about -80 degrees latitude. But AMM-2 utilized for the first time RADARSAT-1 fine beams providing an unprecedented opportunity to image many of Antarctica's fast glaciers whose extent was revealed through AMM-1 data. AMM-2 also captured extensive data suitable for interferometric analysis of the surface velocity field. This report summarizes the science goals, mission objectives, and project status through the acquisition phase and the start of the processing phase. The reports describes the efforts of team members including Alaska SAR Facility, Jet Propulsion Laboratory, Vexcel Corporation, Goddard Space Flight Center, Wallops Flight Facility, Ohio State University, Environmental Research Institute of Michigan, White Sands Facility, Canadian Space Agency Mission Planning and Operations Groups, and the Antarctic Mapping Planning Group.

Source record↗

NASA NTRS2004

MARIE Dose and Flux Measurements in Mars Orbit

We present results from the Martian Radiation Environment Experiment (MARIE), aboard the 2001 Mars Odyssey spacecraft in orbit around Mars. MARIE operated successfully from March 2002 through October 2003. At the time of this writing, the instrument is off due to a loss of communications during an extremely intense Solar Particle Event. Efforts to revive MARIE are planned for Spring 2004, when Odyssey's role as a communications relay for the MER rovers is completed. During the period of successful operation, MARIE returned the first detailed energetic charged particle data from Mars. Due to limitations of the instrument, normalizing MARIE data to flux or dose is not straightforward - several large corrections are needed. Thus normalized results (like dose or flux) have large uncertainties and/or significant model-dependence. The problems in normalization are mainly due to inefficiency in detecting high-energy protons (signal-to-noise problems force the trigger threshold to be higher than optimal), to the excessively high gains employed in the signal processing electronics (many ions deposit energy sufficient to saturate the electronics, and dE/dx information is lost), and to artifacts associated with the two trigger detectors (incomplete registration of dE/dx). Despite these problems, MARIE is efficient for detecting helium ions with kinetic energies above about 30 MeV/nucleon, and for detecting high-energy ions (energies above about 400 MeV/nucleon) with charges from 5 to 10. Fluxes of these heavier ions can be compared to fluxes obtained from the ACE/CRIS instrument, providing at least one area of direct comparison between data obtained at Earth and at Mars; this analysis will be presented as a work in progress. We will also present dose-rate data, with a detailed explanation of the many sources of uncertainty in normalization. The results for both flux and dose will be compared to predictions of the HZETRN model of the GCR.

Zeitlin, C.↗

NASA NTRS2014

GPU Lossless Hyperspectral Data Compression System

Hyperspectral imaging systems onboard aircraft or spacecraft can acquire large amounts of data, putting a strain on limited downlink and storage resources. Onboard data compression can mitigate this problem but may require a system capable of a high throughput. In order to achieve a high throughput with a software compressor, a graphics processing unit (GPU) implementation of a compressor was developed targeting the current state-of-the-art GPUs from NVIDIA(R). The implementation is based on the fast lossless (FL) compression algorithm reported in "Fast Lossless Compression of Multispectral-Image Data" (NPO- 42517), NASA Tech Briefs, Vol. 30, No. 8 (August 2006), page 26, which operates on hyperspectral data and achieves excellent compression performance while having low complexity. The FL compressor uses an adaptive filtering method and achieves state-of-the-art performance in both compression effectiveness and low complexity. The new Consultative Committee for Space Data Systems (CCSDS) Standard for Lossless Multispectral & Hyperspectral image compression (CCSDS 123) is based on the FL compressor. The software makes use of the highly-parallel processing capability of GPUs to achieve a throughput at least six times higher than that of a software implementation running on a single-core CPU. This implementation provides a practical real-time solution for compression of data from airborne hyperspectral instruments.

Aranki, Nazeeh I.↗

NASA NTRSDate not supplied

NASA R&M Efficiency through Findable, Accessible, Interoperable, and Reusable (FAIR) Digital Assets

At the intersection of mission, technology, and place is NASA’s need to modernize for a digital-forward future. Digitalization, the process of moving toward digital business, is occurring everywhere and remains an ongoing process across the federal government.”[1] Whereas, Digital Transformation is “employing digitization/digital technologies (e.g., Artificial Intelligence (AI), mobile, cloud, data) to change a process, product, or capability so dramatically (e.g., real-time, intelligent, personalized, anywhere, anytime) that it is unrecognizable compared to its traditional form.” [2] In order to facilitate a digital transformation it is essential for NASA to understand and identify where data exists today and which data are value-needed in the future, understand where there are unfulfilled data needs that limit the advancement of NASA work, and ensure NASA efficiency through Findable, Accessible, Interoperable, and Reusable (FAIR) digital assets in the future. Therefore, NASA’s Reliability & Maintainability (R&M) Enterprise Data Sharing team is working to leverage both Digitization and Digital Transformation to achieve their vision of developing an R&M data discovery framework that enables our community, our partners, and our stakeholders with the ability to efficiently, robustly, and seamlessly access information that enables real-time knowledge and model-based, analytics driven, decision-making impacting R&M. As a result the R&M Enterprise Data Sharing team has conducted a survey of its Reliability, Maintainability, and Availability (RMA) community members to identify data existence (created or used) and where there are corresponding barriers to data acquisition and/or R&M or other issues as shown within this presentation.

Digital Transformation↗

NASA NTRSDate not supplied

Trilateral Task Force – Reliability Analysis Supporting Mission Extension/Post Mission Disposal

Digital Transformation, Reliability Engineering↗

NASA NTRSDate not supplied

Building access and community standards for opacity data at the onset of next-generation atmosphere observations

The characterization of a diverse set of exoplanet atmosphere observations, ranging from hot gas giants to small temperate rocky worlds, will be one of the legacies of upcoming facilities such as the James Webb Space Telescope (JWST). Our understanding and interpretation of such observations will hinge on our ability to link observations with atmospheric theoretical studies that critically rely on fundamental molecular and atomic opacities. Computing such opacities is a highly non-trivial and inaccessible process which requires several terabytes of available disk space, hours of CPU time per pressure-temperature combination, and requires users to carefully aggregate line lists data from various sources, which limits access and intercomparison of opacity data in the exoplanet community. Here we present MAESTRO (Molecules and Atoms in Exoplanet Science: Tools and Resources for Opacities) an opacity database that can be accessed by the community via a web interface and python API. MAESTRO was built with community input to create a version-controlled opacity database that is easily queryable, includes informative metadata to ensure reproducibility, and exports relevant citations for inclusion in publications. Scheduled for community release in 2022, MAESTRO will prove to be an invaluable community resource in the era of JWST and beyond.

Natasha Batalha↗

DOE OSTI2021

Improving the Accessibility and Usability of Geothermal Information with Data Lakes and Data Pipelines on the Geothermal Data Repository: Preprint

The Geothermal Data Repository (GDR) provides universal access to data and information resulting from research and development activities funded by the Department of Energy (DOE). The GDR has extended this universal access to big data through integration with data lakes developed by the Open Energy Data Initiative (OEDI). Previously, large datasets such as seismic waveform or distributed acoustic sensing (DAS) data could only be accessed by institutions with high performance data storage and compute capabilities, effectively limiting the accessibility of big data to national labs, larger universities, and major corporations. Moreover, the time and resources needed to transport big data and configure them can produce additional barriers to use. Many of the standard formats used for structured data models (also known as content models) are incapable of handling big data and can introduce additional usability problems, often requiring data to be reformatted prior to use. This paper will explore how recent integrations between the GDR and the OEDI data lake have improved the accessibility and usability of geothermal data in a big way, making the data available to a broader audience, and enabling collaborative analysis and innovation across the greater geothermal industry.

access↗

DOE OSTI2021

Improving the Accessibility and Usability of Geothermal Information with Data Lakes and Data Pipelines on the Geothermal Data Repository

access↗

DOE OSTI2026

Reconstruction of Six-Dimensional Phase Space

A phase space is a mathematical representation of all possible physical states of a system. Particle beams at Fermilab exist within a six-dimensional (6D) phase space defined by three positional components, (x, y, z) and three momentum components, (px, py, pz). To reconstruct this space implies taking measurement data from detectors and mapping out particle behavior using computational methods. The beam detectors, however, are only able to detect spatial distribution among the events of the beam, therefore being limited to positional data. Also, due to the vast number of events in a particle beam, it is extremely difficult to analyze and differentiate every single one’s behavior. However, with Machine Learning (ML), which can distinguish between patterns and map out particle behavior more efficiently. We first used the particle beam software, G4beamline, to simulate a 10,000-event muon beam, adjusting parameters such as initial momentum magnitude (p¬0) and virtual detector position. Using ten virtual detectors, we analyzed p0 values such that minimum 9,990 events were analyzed by every detector. We then input the data from these beam simulations to a C++ program, that randomly selects 100 events, and creates a 2D histogram based on spatial distribution, detector position, and event intensity. This process is repeated 100 times to create 100 histograms per p0 value. These images were then input to a modified ResNet18 Convolutional Neural Network (CNN) for training, and to predict p0 from some unseen set of histograms. The model was accurate when trained on momentum increments of 5 MeV/c and provided with denser training samples around highly variable test values. These results displayed machine learning being able to accurately predict p0 from being trained on different particle behaviors.

Shirlee, Jermain [Fermilab]↗

DOE OSTI2023

A novel transfer learning framework for sorghum biomass prediction using UAV-based remote sensing data and genetic markers

Yield for biofuel crops is measured in terms of biomass, so measurements throughout the growing season are crucial in breeding programs, yet traditionally time- and labor-consuming since they involve destructive sampling. Modern remote sensing platforms, such as unmanned aerial vehicles (UAVs), can carry multiple sensors and collect numerous phenotypic traits with efficient, non-invasive field surveys. However, modeling the complex relationships between the observed phenotypic traits and biomass remains a challenging task, as the ground reference data are very limited for each genotype in the breeding experiment. In this study, a Long Short-Term Memory (LSTM) based Recurrent Neural Network (RNN) model is proposed for sorghum biomass prediction. The architecture is designed to exploit the time series remote sensing and weather data, as well as static genotypic information. As a large number of features have been derived from the remote sensing data, feature importance analysis is conducted to identify and remove redundant features. A strategy to extract representative information from high-dimensional genetic markers is proposed. To enhance generalization and minimize the need for ground reference data, transfer learning strategies are proposed for selecting the most informative training samples from the target domain. Consequently, a pre-trained model can be refined with limited training samples. Field experiments were conducted over a sorghum breeding trial planted in multiple years with more than 600 testcross hybrids. The results show that the proposed LSTM-based RNN model can achieve high accuracies for single year prediction. Further, with the proposed transfer learning strategies, a pre-trained model can be refined with limited training samples from the target domain and predict biomass with an accuracy comparable to that from a trained-from-scratch model for both multiple experiments within a given year and across multiple years.

36 MATERIALS SCIENCE↗

DOE OSTI2026

Development of physics-consistent conditional diffusion model to overcome data scarcity in critical heat flux

Deep generative modeling provides a powerful pathway to overcome data scarcity in energy-related applications where experimental data are often limited. By learning the underlying probability distribution of the training dataset, deep generative models, such as the diffusion model, can generate high-fidelity synthetic samples that statistically resemble the training data. Such synthetic data generation can significantly enrich the size and diversity of the available training data, and more importantly, improve the robustness of downstream machine learning models in predictive tasks. The objective of this paper is to investigate the effectiveness of diffusion models for overcoming data scarcity in nuclear energy applications. By leveraging a public dataset on critical heat flux which covers a wide range of commercial nuclear reactor operational conditions, we developed a diffusion model that can generate an arbitrary amount of synthetic samples. Since a vanilla diffusion model can only generate samples randomly, we also developed a conditional diffusion model capable of generating targeted critical heat flux data under user-specified thermal-hydraulic conditions. The performance of the diffusion model was evaluated based on its ability to capture empirical feature distributions and pair-wise correlations, as well as to maintain physical consistency. The results showed that both the diffusion model and conditional diffusion model can successfully generate realistic and physics-consistent critical heat flux data. Furthermore, uncertainty quantification results demonstrate that the conditional diffusion model is highly effective in augmenting critical heat flux data while maintaining acceptable levels of uncertainty.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2022

Iraq/Afghanistan war lung injury reflects burn pits exposure

This descriptive case series retrospectively reviewed medical records from thirty-one previously healthy, war-fighting veterans who self-reported exposure to airborne hazards while serving in Iraq and Afghanistan between 2003 and the present. They all noted new-onset dyspnea, which began during deployment or as a military contractor. Twenty-one subjects underwent non-invasive pulmonary diagnostic testing, including maximum expiratory pressure (MEP) and impulse oscillometry (IOS). In addition, five soldiers received a lung biopsy; tissue results were compared to a previously published sample from a soldier in our Iraq Afghanistan War Lung Injury database and others in our database with similar exposures, including burn pits. We also reviewed civilian control samples (5) from the Stony Brook University database. Military personnel were referred to our International Center of Excellence in Deployment Health and Medical Geosciences, Donald and Barbara Zucker School of Medicine at Hofstra/Northwell under the auspices of Northwell IRB: 17-0140-FIMR Feinstein Institution for Medical Research “Clinicopathologic characteristics of Iraq Afghanistan War Lung Injury.” We retrospectively examined medical records, including exposure data, radiologic imaging, and non-invasive pulmonary function testing (MGC Diagnostic Platinum Elite Plethysmograph) using the American Thoracic Society (ATS) standard interpretation based on Morgan et al., and for a limited cohort, biopsy data. Lung tissue, when available, was examined for carbonaceous particles, polycyclic aromatic hydrocarbons (Raman spectroscopy), metals, titanium connected to iron (Brookhaven National Laboratory, National Synchrotron Light Source II, Beamline 5-ID), oxidized metals, combustion temperature, inflammatory cell accumulation and fibrosis, neutrophil extracellular traps, Sirius red, Prussian Blue, as well as polarizable crystals/particulate matter/dust. Among twenty-one previously healthy, deployable soldiers with non-invasive pulmonary diagnostic tests, post-deployment, all had severely decreased MEP values, averaging 42% predicted. These same patients concurrently demonstrated abnormal airways reactance (X5Hz) and peripheral/distal airways resistance (D5–D20%) via IOS, averaging – 1369% and 23% predicted, respectively. These tests support the concept of airways hyperresponsiveness and distal airways narrowing, respectively. Among the five soldiers biopsied, all had constrictive bronchiolitis. We detected the presence of polycyclic aromatic hydrocarbons (PAH)—which are products of incomplete combustion—in the lung tissue of all five warfighters. All also had detectable titanium and iron in the lungs. Metals were all oxidized, supporting the concept of inhaling burned metals. Combustion temperature was consistent with that of burned petrol rather than higher temperatures noted with cigarettes. All were nonsmokers. Neutrophil extracellular traps were reported in two biopsies. Compared to our prior biopsies in our Middle East deployment database, these histopathologic results are similar, since all database biopsies have constrictive bronchiolitis, one has lung fibrosis with titanium bound to iron in fixed mathematical ratios of 1:7 and demonstrated polarizable crystals. These results, particularly constrictive bronchiolitis and polarizable crystals, support the prior data of King et al. (N. Engl. J. Med. 365:222–230, 2011) Soldiers in this cohort deployed to Iraq and Afghanistan since 2003, with exposure to airborne hazards, including sandstorms, burn pits, and improvised explosive devices, are at high risk for developing chronic clinical respiratory problems, including: (1) reduction in respiratory muscle strength; (2) airways hyperresponsiveness; and (3) distal airway narrowing, which may be associated with histopathologic evidence of lung damage, reflecting inhalation of burned particles from burn pits along with particulate matter/dust. Non-invasive pulmonary diagnostic tests are a predictor of burn pit-induced lung injury

36 MATERIALS SCIENCE↗

NASA NTRS1985

A study of depletions within the RHO Ophiuchi cloud based on IUE observations of HD 147889

Archival IUE data on the deeply embedded Rho Oph cloud star HD 147889 have been used to derive column densities for several species. The poor data quality and limited useful spectral coverage made unambiguous abundances very difficult to deduce, but firm limits could be set. Absolute depletions have been estimated, based on an assumed value of the total hydrogen column density, but they are uncertain due to uncertainty in N(H). The data appear to indicate that depletions are generally very large in this line of sight. There is also some indication that the relative depletions are enhanced in the densest portions of the cloud.

Snow, T. P.↗

NASA NTRS1994

X-ray color analysis of the spectra of active galactic nuclei

The identification and detection of X-ray absorption and emission features depends on the resolution and the signal-to-noise ratio (S/N) of the observation, the understanding of the instrument response, and the Galactic line-of-sight absorption. Since many of the active galactic nucleus (AGN) data sets are limited in their S/N and full modeling of the physical conditions is rather complicated, we suggest a new analysis method based on 'X-ray colors.' The two sets of X-ray colors, defined for low (ROSAT Position Sensitive Proportional Counter (PSPC)) and medium (Broad Band X-Ray Telescope (BBXRT)) and ASCA Solid-State Imaging Spectrometers (SIS) resolution experiments, are used to separate regions of different physical conditions in a two-dimensional color-color plane. They are similar but superior to previous methods using the X-ray 'hardness ratio' in being able to reveal more of the physical properties of the source. We illustrate the use of such diagrams by studying a number of AGNs suspected of showing absorption features. A sample of 14 AGNs observed by the ROSAT PSPC is presented which includes several objects with suspected 'warm absorbers' along the line-of-sight to the nucleus, several others exhibiting intrinsic continuum variations, and a number of control objects thought to be featureless. Our new observations show, for the first time, the color variation as a function of time for three of the Seyfert 1 sources: NGC 4051, Mrk 335, and Mrk 766. The variations suggest that in two sources we are witnessing real changes in continuum shape, while one (NGC 4051) is consistent with having a warm absorber. Four of the objects observed by BBXRT are reanalyzed using our X-ray colors. Out of these, we discuss in detail the case of NGC 4151 and show that the color-color analysis agrees very well with previous, detailed spectral fitting methods. In particular, we confirm that the observed BBXRT observation of this source is not consistent with the warm absorber explanation and must be interpreted as a combination of a variable hard component and another component. We explain the limitations in measuring low-energy emission features in ASCA SIS observations and present color-color diagrams which can be used as a powerful diagnostic tool in the analysis of data collected by this experiment.

Netzer, Hagai↗

NASA NTRS1998

Of mice and genes: evolution of vertebrate brain development

In this review the current understanding of genetic and molecular evolution of development, in particular the formation of the major axis of bilateral animals, is critically evaluated, and the early pattern formation in the hindbrain is related as much as possible to these processes. On the genetic level it is proposed that the exuberant multiplication of regulatory genes compared to that of structural genes relates to the increased flexibility of early vertebrate development. In comparisons to fruit flies, many conserved genes are found to be expressed very differently, while many others seem to reflect a comparable pattern and thus suggest a conservation of function. Even genes with a largely conserved pattern of expression may change the level at which they are expressed and the mechanisms by which they are regulated in their expression. Evolution and development of hindbrain motoneurons is reviewed, and it is concluded that both comparative data as well as more recent experimental data suggest a limited importance for the rhombomeres. Clearly, many cell fate-specifying processes work below the level of rhombomeres or in the absence of rhombomeres. It is suggested that more comparative developmental data are needed to establish firmly the relationship between homeobox genes and rhombomere specification in vertebrates other than a few model species.

NASA Discipline Developmental Biology↗

NASA NTRS2018

In-Flight Calibration of Hitomi Soft X-Ray Spectrometer. (1) Background

The X-Ray Spectrometer (XRS) instrument of Suzaku provided the first measurement of the non-X-ray background (NXB) of an X-ray calorimeter spectrometer, but the data set was limited. The Soft X-ray Spectrometer (SXS) instrument of Hitomi was able to provide a more detailed picture of X-ray calorimeter background, with more than 360 ks of data while pointed at the Earth, and a comparable amount of blank-sky data. These data are important not only for analyzing SXS science data, but also for categorizing the contributions to the NXB in X-ray calorimeters as a class. In this paper, we present the contributions to the SXS NXB, the types and effectiveness of the screening, the interaction of the screening with the broad-band redistribution, and the residual background spectrum as a function of magnetic cut-off rigidity. The orbit-averaged SXS NXB in the range 0.3-12 keV was 4 × 10(exp −2) counts s(exp −1) -sq cm. This very low background in combination with groundbreaking spectral resolution gave SXS unprecedented sensitivity to weak spectral lines.

Kilbourne, Caroline A.↗