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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 253 records · Page 14
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Immediate effects of acute Mars mission equivalent doses of SEP and GCR radiation on the murine gastrointestinal system-protective effects of curcumin-loaded nanolipoprotein particles (cNLPs)

Introduction: Missions beyond low Earth orbit (LEO) will expose astronauts to ionizing radiation (IR) in the form of solar energetic particles (SEP) and galactic cosmic rays (GCR) including high atomic number and energy (HZE) nuclei. The gastrointestinal (GI) system is documented to be highly radiosensitive with even relatively low dose IR exposures capable of inducing mucosal lesions and disrupting epithelial barrier function. IR is also an established risk factor for colorectal cancer (CRC) with several studies examining long-term GI effects of SEP/GCR exposure using tumor-prone APC mouse models. Studies of acute short-term effects of modeled space radiation exposures in wildtype mouse models are more limited and necessary to better define charged particle- induced GI pathologies and test novel medical countermeasures (MCMs) to promote astronaut safety. Methods: In this study, we performed ground-based studies where male and female C57BL/6J mice were exposed to γ-rays, 50 MeV protons, or 1 GeV/n Fe-56 ions at the NASA Space Radiation Laboratory (NSRL) with histology and immunohistochemistry endpoints measured in the first 24 h post-irradiation to define immediate SEP/GCR-induced GI alterations. Results: Our data show that unlike matched γ-ray controls, acute exposures to protons and iron ions disrupts intestinal function and induces mucosal lesions, vascular congestion, epithelial barrier breakdown, and marked enlargement of mucosa-associated lymphoid tissue. We also measured kinetics of DNA double-strand break (DSB) repair using gamma-H2AX- specific antibodies and apoptosis via TUNEL labeling, noting the induction and disappearance of extranuclear cytoplasmic DNA marked by gamma-H2AX only in the charged particle-irradiated samples. We show that 18 h pre-treatment with curcumin-loaded nanolipoprotein particles (cNLPs) delivered via IV injection reduces DSB-associated foci levels and apoptosis and restore crypt villi lengths. Discussion: These data improve our understanding of physiological alterations in the GI tract immediately following exposures to modeled space radiations and demonstrates effectiveness of a promising space radiation MCM.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS2000

Proposal Drafted for Allocating Space-to-Space Frequencies in the GPS Spectrum Bands

Radionavigation Satellite Service (RNSS) systems such as the U.S. Global Positioning System (GPS) and the Russian Global Navigation Satellite System (GLONASS) are primarily being used today in the space-to-Earth direction (i.e., from GPS satellite to Earth user) for a broad range of applications such as geological surveying; aircraft, automobile, and maritime navigation; hiking and mountain climbing; and precision farming and mining. However, these navigation systems are being used increasingly in space. Beginning with the launch of the TOPEX/Poseidon remote-sensing mission in 1992, over 90 GPS receivers have flown onboard spacecraft for such applications as real-time spacecraft navigation, three-axis attitude control, precise time synchronization, precision orbit determination, and atmospheric profiling. In addition to use onboard many science spacecraft, GPS has been used or is planned to be used onboard the shuttles, the International Space Station, the International Space Station Emergency Crew Return Vehicle, and many commercial satellite systems such as Orbcomm, Globalstar, and Teledesic. From a frequency spectrum standpoint, however, one important difference between the space and terrestrial uses of GPS is that it is being used in space with no interference protection. This is because there is no frequency allocation for the space-to-space use of GPS (i.e., from GPS satellite to user spacecraft) in the International Telecommunications Union (ITU) regulatory table of frequency allocations. If another space-based or groundbased radio system interferes with a spaceborne GPS user, the spaceborne user presently has no recourse other than to accept the interference. Consequently, for the past year and a half, the NASA Glenn Research Center at Lewis Field and other Government agencies have been working within ITU toward obtaining a GPS space-to-space allocation at the next World Radio Conference in the year 2000 (WRC 2000). Numerous interference studies have been conducted in support of a primary space-tospace allocation in the 1215- to 1260-MHz and 1559- to 1610-MHz RNSS bands. Most of these studies and analyses were performed by Glenn and submitted as U.S. input documents to the international Working Party 8D meetings in Geneva, Switzerland. In the structure of the ITU, Working Party 8D is responsible for frequency spectrum issues in the RNSS and the mobile satellite service (MSS). The full texts of the studies are available from the ITU web site under Working Party 8D contributions. Note that because spaceborne RNSS receivers operate in a receive-only mode with navigation signals already being broadcast toward the Earth, the addition of a space-tospace allocation will not result in interference with other systems. A space-based RNSS receiver, however, could experience interference from systems of other services, including intraservice interference from other RNSS systems. The interference scenarios examined in the studies can be inferred from the following frequency allocation charts. In these charts, services labeled in all capital letters (e.g., "ARNS") have primary status, whereas those labeled with sentence-style capitalization (e.g., "Amateur radio") have secondary status (i.e., a service with secondary status cannot claim interference protection from or cause harmful interference to a service with primary status). Charts showing the ITU frequency allocations in the 960 to 1350 MHZ range and the 1525-1660 MHZ range are discussed and presented.

Spence, Rodney L.↗
NASA NTRS2007

Risk Reduction for Use of Complex Devices in Space Projects

We present guidel!nes to reduce risk to an acceptable level when using complex devices in space applications. Application to Virtex 4 Field Programmable Gate Array (FPGA) on Express Logistic Carrier (ELC) project is presented.

Berg, Melanie↗
DOE OSTI2026

Data for Selected Ion Monitoring for Orbitrap-Based Metabolomics

Orbitrap mass spectrometry in full scan mode enables the simultaneous detection of hundreds of metabolites and their isotope-labeled forms. Yet, sensitivity remains limiting for many metabolites, including low-concentration species, poor ionizers, and low-fractional-abundance isotope-labeled forms in isotope-tracing studies. Here, we explore selected ion monitoring (SIM) as a means of sensitivity enhancement. The analytes of interest are enriched in the orbitrap analyzer by using the quadrupole as a mass filter to select particular ions. In tissue extracts, SIM significantly enhances the detection of ions of low intensity, as indicated by improved signal-to-noise (S/N) ratios and measurement precision. In addition, SIM improves the accuracy of isotope-ratio measurements. SIM, however, must be deployed with care, as excessive accumulation in the orbitrap of similar m/z ions can lead, via space-charge effects, to decreased performance (signal loss, mass shift, and ion coalescence). Ion accumulation can be controlled by adjusting settings including injection time and target ion quantity. Overall, we suggest using a full scan to ensure broad metabolic coverage, in tandem with SIM, for the accurate quantitation of targeted low-intensity ions, and provide methods deploying this approach to enhance metabolome coverage.f

Mass Spectrometry↗
NASA NTRS1989

The diageotropica mutant of tomato lacks high specific activity auxin binding sites

Tomato plants homozygous for the diageotropica (dgt) mutation exhibit morphological and physiological abnormalities which suggest that they are unable to respond to the plant growth hormone auxin (indole-3-acetic acid). The photoaffinity auxin analog [3H]5N3-IAA specifically labels a polypeptide doublet of 40 and 42 kilodaltons in membrane preparations from stems of the parental variety, VFN8, but not from stems of plants containing the dgt mutation. In roots of the mutant plants, however, labeling is indistinguishable from that in VFN8. These data suggest that the two polypeptides are part of a physiologically important auxin receptor system, which is altered in a tissue-specific manner in the mutant.

NASA Discipline Number 29-20↗
DOE OSTI2022

Photometric redshift estimation with convolutional neural networks and galaxy images: Case study of resolving biases in data-driven methods

Deep-learning models have been increasingly exploited in astrophysical studies, but these data-driven algorithms are prone to producing biased outputs that are detrimental for subsequent analyses. In this work, we investigate two main forms of biases: class-dependent residuals, and mode collapse. We do this in a case study, in which we estimate photometric redshift as a classification problem using convolutional neural networks (CNNs) trained with galaxy images and associated spectroscopic redshifts. We focus on point estimates and propose a set of consecutive steps for resolving the two biases based on CNN models, involving representation learning with multichannel outputs, balancing the training data, and leveraging soft labels. The residuals can be viewed as a function of spectroscopic redshift or photometric redshift, and the biases with respect to these two definitions are incompatible and should be treated individually. We suggest that a prerequisite for resolving biases in photometric space is resolving biases in spectroscopic space. Experiments show that our methods can better control biases than benchmark methods, and they are robust in various implementing and training conditions with high-quality data. Our methods hold promises for future cosmological surveys that require a good constraint of biases, and they may be applied to regression problems and other studies that make use of data-driven models. Nonetheless, the bias-variance tradeoff and the requirement of sufficient statistics suggest that we need better methods and optimized data usage strategies.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

Sharing the Sun Community Solar Project Data

This database represents a list of community solar projects, complete and pending, identified through various sources. The dataset is updated multiple times per year. The current version is the first file located below. Previous versions of the dataset published before June of 2024 can be found in the dataset below labeled “ARCHIVE_Sharing the Sun Community Solar Project Data_Before 06.24.“ The list has been reviewed but errors may exist, and the list may not be comprehensive. Errors in the sources e.g. press releases may be duplicated in the list. Blank spaces represent missing information. NLR invites input to improve the database including, to correct erroneous information, add missing projects, fill in missing information, and remove inactive projects. Updated information can be submitted to Sudha Kannan ( sudha.kannan@nlr.gov ).

14 SOLAR ENERGY↗
NASA NTRS2024

The NASA Radiation Hardness Assurance (RHA) Process Standard

This paper presents status on the upcoming NASA Agency-level RHA Process Standard. Based on recommendations provided by the NASA Engineering and Safety Center (NESC), the NASA Electronic Parts and Packaging (NEPP) Program has led development of an agency-level standard for space flight avionics and electronics RHA. The standard introduces a novel RHA taxonomy and prescribes the process required by NASA programs and projects to baseline their RHA programs consistent with the MEAL (Mission, Environment, Application, and Lifetime) criteria including the risk tolerance posture. The standard also provides requirements for the RHA schedule integration in the program or project lifecycle and requirements for data deliverables content. Additional non-prescriptive technical content is provided in the standard appendices to guide development of RHA programs for NASA missions.

Avionics↗
NASA NTRS2016

Radiation Failures in Intel 14nm Microprocessors

In this study the 14 nm Intel Broadwell 5th generation core series 5005U-i3 and 5200U-i5 was mounted on Dell Inspiron laptops, MSI Cubi and Gigabyte Brix barebones and tested with Windows 8 and CentOS7 at idle. Heavy-ion-induced hard- and catastrophic failures do not appear to be related to the Intel 14nm Tri-Gate FinFET process. They originate from a small (9 m 140 m) area on the 32nm planar PCH die (not the CPU) as initially speculated. The hard failures seem to be due to a SEE but the exact physical mechanism has yet to be identified. Some possibilities include latch-ups, charge ion trapping or implantation, ion channels, or a combination of those (in biased conditions). The mechanism of the catastrophic failures seems related to the presence of electric power (1.05V core voltage). The 1064 nm laser mimics ionization radiation and induces soft- and hard failures as a direct result of electron-hole pair production, not heat. The 14nm FinFET processes continue to look promising for space radiation environments.

Microprocessors↗
NASA NTRSDate not supplied

Revolutionizing Earth Science with Generalized AI Models

Foundation Models (FM) are generalized Artificial Intelligence (AI) models that are designed to replace a task or an application-specific model and can be used for many downstream applications. These FM can be built on any sequence data and are trained utilizing self-supervised approaches. The obstacle of creating a sizable labeled dataset for training is removed by using self-supervised learning. Most FM employ transformer design that takes advantage of the idea of self-attention, allowing the network to represent the impact of distant data points on one another in space and time. The FM models show emergent qualities that are induced from the data. FM can become a valuable tool for Earth science researchers. Due to the size of these models, downstream applications built fine-tuning these FM perform better and exhibit greater accuracy than models created from scratch. FM significantly lowers the entry barrier in terms of both the time and effort required to develop various downstream applications. For some scientific datasets, such as optical remote sensing data, FM can speed up processes like classification, object detection and prediction. By eliminating the training data bottleneck and maximizing the usage of science data, FM can make it simpler to integrate AI into scientific research. Initial results for three different FMs will be presented.

Rahul Ramachandran↗
NASA NTRS2019

Carbon Nanostructures in Biological Sensors for Space and Terrestrial Applications

Biosensing devices comprised of carbon nanotubes and nanofibers have been developed for astronaut crew point-of-care. Their inherent nanometer scale, high conductivity, wide potential window, good biocompatibility and well-defined surface chemistry make them ideal candidates as biosensor electrodes. Here, we report two studies using carbon nanotube and carbon nanofiber electrodes for biomedical applications. First, a 3x3 electrode device, with each electrode containing 40,000 carbon nanofiber nanoelectrodes was fabricated on silicon using traditional microfabrication processing. The device was demonstrated as a multiplexed immunosensor for simultaneous, label-free detection of cardiac troponin-I, C-reactive protein and myoglobin. Antibodies specific to cardiac troponin-I, C-reactive protein and myoglobin were covalently bound to the CNF surface and were characterized using electrochemical impedance spectroscopy and differential pulse voltammetry. Each step of the modification process resulted in changes in resistance to charge transfer due to the changes at the electrode surface upon antibody immobilization and binding to the specific cardiac protein. The real-time label free detection of the three cardiac markers from pure components and mixtures was demonstrated with high sensitivity, down to 0.2 ng/mL, and good selectivity. Detection in human blood serum did not present false positives from non-specific protein adsorption. More recently, this detection scheme has been applied to inkjet printed carbon nanotube electrodes on Kapton and paper. Printed devices have several unique advantages including simple and inexpensive fabrication. The results demonstrate that these sensors can serve a miniaturized, low cost device for detection of proteins in complex mixtures making this platform a good candidate for early stage diagnosis of myocardial infarction. Future inkjet printed devices can be fabricated have the added advantage in their suitability to be manufactured in an in-space, microgravity environment.

carbon nanotubes↗
DOE OSTI2025

Physics-guided dual implicit neural representations for source separation

Significant challenges exist in efficient data analysis of most advanced experimental and observational techniques because the collected signals often include unwanted contributions, such as background and signal distortions, that can obscure the physically relevant information of interest. To address this, we have developed a self-supervised machine-learning approach for source separation using a dual implicit neural representation framework that jointly trains two neural networks: one for approximating distortions of the physical signal of interest and the other for learning the effective background contribution. Our method learns directly from the raw data by minimizing a reconstruction-based loss function without requiring labeled data or pre-defined dictionaries. We demonstrate the effectiveness of our framework by considering a challenging case study involving large-scale simulated, as well as experimental, momentum-energy-dependent inelastic neutron scattering data in a four-dimensional parameter space, characterized by heterogeneous background contributions and unknown distortions to the target signal. The method is found to successfully separate physically meaningful signals from a complex or structured background even when the signal characteristics vary across all four dimensions of the parameter space. An analytical approach that informs the choice of the regularization parameter is presented. Our method offers a versatile framework for addressing source separation problems across diverse domains, ranging from superimposed signals in astronomical measurements to structural features in biomedical image reconstructions.

47 OTHER INSTRUMENTATION↗
NASA NTRS2017

Interactive Visualization of High-Dimensional Petascale Ocean Data

We describe an application for interactive visualization of 5 petabytes of time-varying multivariate data from a high-resolution global ocean circulation model. The input data are 10311 hourly (ocean time) time steps of various 2D and 3D fields from a 22-billion point 1/48- degree “lat-lon cap” configuration of the MIT General Circulation Model (MITgcm). We map the global horizontal model domain onto our 128-screen (8x16) tiled display wall to produce a canonical tiling with approximately one MITgcm grid point per display pixel, and using this tiling we encode the entire time series for multiple native and computed scalar quantities at a collection of ocean depths. We reduce disk bandwidth requirements by converting the model’s floating point data to 16-bit fixed point values, and compressing those values with a lossless video encoder, which together allow synchronized playback at 24 time steps per second across all 128 displays. The application allows dynamic assignment of any two encoded tiles to any display, and has multiple interfaces for quickly specifying various orderly arrangements of tiles. All subsequent rendering is done on the fly, with run time control of colormaps, transfer functions, histogram equalization, and labeling. The two data streams on each screen can be rendered independently and combined in various ways, including blending, differencing, horizontal/ vertical wipes, and checkerboarding. The two data streams on any screen can optionally be displayed as a scatterplot in their joint attribute space. All scatterplots and map-view plots from the same x/y location and depth are linked so they all show the current brushable selection. Ocean scientists have used the system, and have found previously unidentified features in the data.

Interactive↗
NASA NTRS2019

State Predictor of Classification Cognitive Engine Applied to Channel Fading

This study presents the application of machine learning (ML) to a space-to-ground communication link, showing how ML can be used to detect the presence of detrimental channel fading. Using this channel state information, the communication link can be used more efficiently by reducing the amount of lost data during fading. The motivation for this work is based on channel fading observed during on-orbit operations with NASA's Space Communication and Navigation (SCaN) testbed on the International Space Station (ISS). This paper presents the process to extract a target concept (fading and not-fading) from the raw data. The pre-processing and data exploration effort is explained in detail, with a list of assumptions made for parsing and labelling the dataset. The model selection process is explained, specifically emphasizing the benefits of using an ensemble of algorithms with majority voting for binary classification of the channel state. Experimental results are shown, highlighting how an end-to-end communication system can utilize knowledge of the channel fading status to identity fading and take appropriate action. With a laboratory testbed to emulate channel fading, the overall performance is compared to standard adaptive methods without fading knowledge, such as adaptive coding and modulation.

Fading↗
DOE OSTI2026

Quantum Computing for AI-based Design and Optimization of Electric Motors

Knowledge-based artificial intelligence and hierarchical fuzzy logic offer an interpretable framework for electricvehicle motor preliminary design, but their computational burden grows with linguistic granularity and coupled design-space size. This paper presents a reduced quantum reformulation of the hierarchical fuzzy inference of air-gap flux density, a representative level-one motor-design parameter. Starting from the published electric-vehicle motor-design framework, a three-term fuzzy prototype is constructed from the original inference structure. The reduced model is then reformulated as a modular quantum register-oracle system, in which each hierarchical subrelation is encoded as a block oracle and evaluated through superpositionbased candidate-label testing. The proposed modular quantum formulation reproduces the reduced classical prototype after block fusion. A resource analysis shows that the reduced modular system requires seven qubits per block and twenty-two qubits in a straightforward four-block implementation. Finally, a crossovercomplexity model is derived to identify the regime in which quantum candidate search may become favorable relative to hierarchical fuzzy inference. The results show that no quantum advantage should be claimed for the present one-output reduced benchmark, but that a plausible crossover emerges for larger joint candidate spaces and higher linguistic granularity. The work therefore establishes a technically consistent starting point for future quantum-assisted electric-vehicle motor-design optimization.

Kumar, Praveen [ORNL] (ORCID:0000000291877857)↗