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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 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Detection of Thermal Emission at Millimeter Wavelengths from Low-Earth Orbit Satellites

The detection of satellite thermal emission at millimeter wavelengths is presented using data from the 3rd-Generation receiver on the South Pole Telescope (SPT-3G). This represents the first reported detection of thermal emission from artificial satellites at millimeter wavelengths. Satellite thermal emission is shown to be detectable at high signal-to-noise on timescales as short as a few tens of milliseconds. An algorithm for downloading orbital information and tracking known satellites given observer constraints and time-ordered observatory pointing is described. Consequences for cosmological surveys and short-duration transient searches are discussed, revealing that the integrated thermal emission from all large satellites does not contribute significantly to the SPT-3G survey intensity map. Measured satellite positions are found to be discrepant from their two-line element (TLE) derived ephemerides up to several arcminutes which may present a difficulty in cross-checking or masking satellites from short-duration transient searches.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2025

Outer Radiation Belt Dynamics During the October 2012 Storm Revisited: Rapid Inward Radial Transport From a Dynamic Outer Boundary

Earth's outer radiation belt electron flux is highly variable and can be enhanced by over an order of magnitude over timescales less than one day, as observed during the October 2012 storm. Previous studies of this storm (e.g., Reeves et al., 2013, https://doi.org/10.1126/science.1237743) have invoked local acceleration to explain this. However, here, we argue that the observations can instead be explained by fast inward radial transport. One method often invoked to distinguish between these two acceleration processes is the existence of local peaks in electron phase space density (PSD) as a function of L* at fixed first, M, and second, K, adiabatic invariants. However, this method relies on the assumption that the evolution of the PSD as a function of L* occurs over timescales slower than the satellite orbital period. Here, high spatiotemporal resolution data from the Global Positioning System (GPS) spacecraft constellation is used to show that enhancements in the PSD occur during the October 2012 storm over short timescales not resolvable by the Van Allen Probes. In addition, Geostationary Operational Environmental Satellite spacecraft data also indicate that these enhancements are consistent with relativistic electron injections. A radial diffusion model is shown to reproduce the PSD dynamics observed by the Van Allen Probes, once rapid variations at the simulation outer boundary are included, consistent with GPS data. This verifies that apparently “locally growing” peaks in PSD along high apogee satellite orbits can be produced by fast inward radial transport without requiring the action of any local acceleration processes.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2024

Extensive Secondary Cratering From the InSight Sol 1034a Impact Event

Abstract Impact cratering is one of the fundamental processes throughout the history of the Solar System. The formation of new impact craters on planetary bodies has been observed with repeat images from orbiting satellites. However, the time gap between images is often large enough to preclude detailed analysis of smaller‐scale features such as secondary impact craters, which are often removed or buried over a short time period. Here we use a seismic event detected on Mars by the NASA InSight mission to investigate secondary cratering at a new impact crater. We strengthen the case that the seismic event that occurred on Sol 1034 (S1034a) is the result of a new impact cratering event. Using the exact timing of this event from InSight, we investigated the resulting new impact crater in orbital image data. The S1034a impact crater is approximately 9 m in diameter but is responsible for over 900 secondary impact events in the form of low albedo spots that are located at distances of up to almost 7 km from the primary crater. We suggest that the low albedo spots formed from relatively low energy ejecta, with individual ejecta block velocities less than 200 m s −1 . We estimate that the low albedo spots, the main evidence of secondary impact processes at this new impact event, fade within 200–300 days after formation.

Grindrod, P. M. [Natural History Museum London UK]↗
DOE OSTI2025

Effect of the space weather conditions on the Earth magnetosphere soft X-ray emissivity

The aim of the study is to model and characterize the soft X-ray emissivity on the Earth magnetosphere for different space weather conditions (SWC), providing information to interpret the soft X-ray measurements of the Solar wind Magnetosphere Ionosphere Link Explorer space mission. The MHD code pluto in spherical coordinates is used to perform parametric studies with respect to the solar wind (SW) dynamic pressure (considering density and velocity effects independently) as well as the IMF intensity and orientation, predicting the soft X-ray emissivity for different SWC. The integrated soft X-ray emissivity inside the magnetosheath is calculated as a proxy of the soft X-ray emission dependencies with the SWC independently of the satellite orbit and camera line of sight. The analysis indicates fluctuations of the interplanetary magnetic field (IMF) orientation and magnitude may significantly affect the measured soft X-ray emission although changes in the SW dynamic pressure should be the main source of variability. The southward IMF orientation leads to the configuration with the largest soft X-ray emissivity and northward to the lowest. Strongly distorted magnetospheres explored in configurations showing SW and IMF parameters comparable to the impact of interplanetary coronal mass ejections may show a decrease of the soft X-ray emissivity as the IMF magnitude increases, explained by the strong magnetosphere compression and constriction of the magnetosheath region where the soft X-ray emissivity maximum is located. The simulations also indicate large excursions of the soft X-ray emissivity maximum inside the magnetosheath as the IMF magnitude and SW dynamic pressure fluctuate particularly for radial and ecliptic IMF orientations.

Earth↗
DOE OSTI2025

Monthly Quality-filtered Aggregation of NOAA Climate Data Record (CDR) of AVHRR Leaf Area Index (LAI) and Fraction of Absorbed Photosynthetically Active Radiation (FAPAR), Version 5

This dataset contains gridded monthly Leaf Area Index (LAI) derived from the daily NOAA Climate Data Record (CDR) of AVHRR Leaf Area Index (LAI) and Fraction of Absorbed Photosynthetically Active Radiation (FAPAR), Version 5. This data record spans from 1981 to 2018 using data from eight NOAA polar orbiting satellites: NOAA-7, -9, -11, -14, -16, -17, -18 and -19. The data are projected on a 0.05 degree x 0.05 degree global grid, as in the original CDR. The original CDR is one of the Land Surface CDR Version 5 products produced by the NASA Goddard Space Flight Center (GSFC) and the University of Maryland (UMD), which is accompanied by algorithm documentation, data flow diagram and source code for the NOAA CDR Program. This dataset is in the netCDF-4 file format following ACDD and CF Conventions. This dataset has applied quality assurance information to only include "OK" data from the original CDR in the monthly aggregation.

Vermote, Eric [NASA Goddard Space Flight Center (G↗
DOE OSTI2026

Monthly Quality-filtered Aggregation of NOAA Climate Data Record (CDR) of AVHRR (Version 5) and VIIRS (Version 1) Leaf Area Index (LAI) and Fraction of Absorbed Photosynthetically Active Radiation (FAPAR)

This dataset contains gridded monthly Leaf Area Index (LAI) derived from the daily NOAA Climate Data Record (CDR) of AVHRR (Version 5) and VIIRS (Version 1) Leaf Area Index (LAI) and Fraction of Absorbed Photosynthetically Active Radiation (FAPAR). This data record spans from 1981 to 2024 using data from NOAA polar orbiting satellites: NOAA-7, -9, -11, -14, -16, -17, -18, -19 and S-NPP. The data are projected on a 0.05 degree x 0.05 degree global grid, as in the original CDR. The original CDR is one of the Land Surface CDR products produced by the NASA Goddard Space Flight Center (GSFC) and the University of Maryland (UMD), which is accompanied by algorithm documentation, data flow diagram and source code for the NOAA CDR Program. This dataset is in the netCDF-4 file format following ACDD and CF Conventions. This dataset has applied quality assurance information to only include "OK" data from the original CDR in the monthly aggregation.

Vermote, Eric [NASA Goddard Space Flight Center (G↗
DOE OSTI2024

Probabilistic inference of the structure and orbit of Milky Way satellites with semi-analytic modelling

Semi-analytic modelling furnishes an efficient avenue for characterizing dark matter haloes associated with satellites of Milky Way-like systems, as it easily accounts for uncertainties arising from halo-to-halo variance, the orbital disruption of satellites, baryonic feedback, and the stellar-to-halo mass (SMHM) relation. We use the SatGen semi-analytic satellite generator, which incorporates both empirical models of the galaxy–halo connection as well as analytic prescriptions for the orbital evolution of these satellites after accretion onto a host to create large samples of Milky Way-like systems and their satellites. By selecting satellites in the sample that match observed properties of a particular dwarf galaxy, we can infer arbitrary properties of the satellite galaxy within the cold dark matter paradigm. For the Milky Way’s classical dwarfs, we provide inferred values (with associated uncertainties) for the maximum circular velocity v max and the radius r max at which it occurs, varying over two choices of baryonic feedback model and two prescriptions for the SMHM relation. While simple empirical scaling relations can recover the median inferred value for v max and r max , this approach provides realistic correlated uncertainties and aids interpretability. We also demonstrate how the internal properties of a satellite’s dark matter profile correlate with its orbit, and we show that it is difficult to reproduce observations of the Fornax dwarf without strong baryonic feedback. Furthermore, the technique developed in this work is flexible in its application of observational data and can leverage arbitrary information about the satellite galaxies to make inferences about their dark matter haloes and population statistics.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2025

slewpy

slewpy is a Python package that allows the simulation of the science operations of an astrophysics space satellite mission. slewpy allows users to specify an astronomical target list with observing priorities and a satellite configuration (i.e., orbit and various satellite parameters). Taking these inputs, slewpy can be used to run a time-resolved simulation of an astrophysics mission and outputs simulated target observations given constraints such as satellite slewing rates between targets, observing time on a given target, and Sun-, Earth-, and Moon-limb observing constraints. slewpy provides the tools to test astrophysics space satellite mission designs against observing requirements for a given science case.

Geringer-Sameth, Alex [Lawrence Livermore National↗
DOE OSTI2025

Link Scheduling in Satellite Networks via Machine Learning Over Riemannian Manifolds

Low Earth Orbit (LEO) satellites play a crucial role in enhancing global connectivity, serving a complementary solution to existing terrestrial systems. In wireless networks, scheduling is a vital process that allocates time-frequency resources to users for interference management. However, LEO satellite networks face significant challenges in scheduling their links towards ground users due to the satellites’ mobility and overlapping coverage. This paper addresses the dynamic link scheduling problem in LEO satellite networks by considering spatio-temporal correlations introduced by the satellites’ movements. The first step in the proposed solution involves modeling the network over Riemannian manifolds, thanks to their representation as symmetric positive definite matrices. We introduce two machine learning (ML)-based link scheduling techniques that model the dynamic evolution of satellite positions and link conditions over time and space. To accurately predict satellite link states, we present a recurrent neural network (RNN) over Riemannian manifolds, which captures spatio-temporal characteristics over time. Furthermore, we introduce a separate model, the convolutional neural network (CNN) over Riemannian manifolds, which captures geometric relationships between satellites and users by extracting spatial features from the network topology across all links. Simulation results demonstrate that both RNN and CNN over Riemannian manifolds deliver comparable performance to the fractional programming-based link scheduling (FPLinQ) benchmark. Remarkably, unlike other ML-based models that require extensive training data, both models only need 30 training samples to achieve over 99% of the sum rate while maintaining similar computational complexity relative to the benchmark.

42 ENGINEERING↗
DOE OSTI2024

Anticipating Optical Availability in Hybrid RF/FSO Links Using RF Beacons and Deep Learning

Radiofrequency (RF) communications offer reliable but low data rates and energy-inefficient satellite links, while free-space optical (FSO) promises high bandwidth but struggles with disturbances imposed by atmospheric effects. A hybrid RF/FSO architecture aims to achieve optimal reliability along with high data rates for space communications. Accurate prediction of dynamic ground-to-satellite FSO link availability is critical for routing decisions in low-earth orbit constellations. In this paper, we propose a system leveraging ubiquitous RF links to proactively forecast FSO link degradation prior to signal drops below threshold levels. This enables pre-calculation of rerouting to maximally maintain high data rate FSO links throughout the duration of weather effects. We implement a supervised learning model to anticipate FSO attenuation based on the analysis of RF patterns. Through the simulation of a dense lower earth orbit (LEO) satellite constellation, we demonstrate the efficacy of our approach in a simulated satellite network, highlighting the balance between predictive accuracy and prediction duration. An emulated cloud attenuation model is proposed to provide insight into the temporal profiles of RF signals and their correlation to FSO channel dynamics. Our investigation sheds light on the trade-offs between prediction horizon and accuracy arising from RF beacon numbers and proximity.

FSO availability↗
DOE OSTI2026

Predictive Model for Starlink Maritime Performance Using Multi-Horizon RandomForest

Low Earth orbit (LEO) satellite systems have become a crucial enabler of broadband access for maritime industries, where traditional networks are unavailable. However, the high mobility of LEO constellations and constantly changing weather conditions result in unpredictable link fluctuations, limiting the ability of maritime platforms to plan bandwidth usage proactively. To the best of our knowledge, no prior work has developed a short-term predictive model for maritime LEO connectivity using real experimental field measurements. This paper proposes a data-driven forecasting model that predicts future downlink throughput using multi-horizon RandomForest regression. The model is trained using real experimental coastal measurement data incorporating recent throughput history, network-layer indicators, and environmental variables. The proposed approach reduces mean absolute error by approximately 31% compared to a persistence baseline for 15-minute horizons. It maintains a measurable improvement at 30 minutes, despite increased stochasticity. These findings confirm that proactive bandwidth awareness is feasible on maritime platforms and can effectively support operational decisions such as adaptive streaming, routing, and resource scheduling. The performance gap between forecasting horizons also highlights the need for expanded offshore datasets to improve prediction robustness under harsher maritime environments.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Optimizing Non-Terrestrial Hybrid RF/FSO Links With Reinforcement Learning: Navigating Through Clouds

In the pursuit of ubiquitous broadband connectivity, there has been a significant shift towards the vertical expansion of communication networks into space, particularly through the exploitation of low Earth orbit (LEO) satellite constellations, which are favored for their relatively low latency. However, this approach faces many challenges that need to be addressed, including atmospheric turbulence, high path loss, and dynamic cloud formations. High-altitude pseudo-satellites (HAPS) have emerged as promising relaying layers between LEO satellites and ground stations, enhancing coverage, latency, and direct terrestrial user connectivity. While radio frequency (RF) bands suffer from congestion and limited bandwidth, free space optical (FSO) communications offer higher data rates, but are susceptible to misalignment and weather-induced signal degradation. To address these challenges, a hybrid RF/FSO approach has been proposed to take advantage of both technologies by dynamic switching between RF and FSO based on propagation channel conditions. This paper introduces a reinforcement learning-based algorithm designed to optimize the trajectory of HAPS, maneuver around cloudy areas, and seamlessly switch between the RF and FSO communication modes to maximize the achievable capacity. The proposed approach aims to maximize system performance by intelligently adapting to environmental conditions and offering a promising solution for next-generation space communication networks.

actor-critic algorithm↗
DOE OSTI2024

Estimating Carbon Dioxide Emissions in Two California Cities Using Bayesian Inversion and Satellite Measurements

NASA's Orbiting Carbon Observatories (OCO-2 and OCO-3) provide measurements of column-averaged carbon dioxide concentrations (XCO 2 ) with sufficient spatial resolution and precision to constrain bottom-up estimates of CO 2 fluxes at regional scales. We use Bayesian inversion methods assimilating satellite retrievals to improve estimates of CO 2 fluxes in the South Coast Air Basin (SoCAB) which surrounds Los Angeles, and in the San Francisco Bay Area Air Basin (SFBA). We study 2020 to understand the impact of the COVID-19 lockdowns and an active wildfire season. Our results indicated that a 50% (30%) reduction in CO 2 emissions relative to 2015 during the COVID-19 lockdown period was consistent with OCO measurements for SFBA (SoCAB). We find that posterior wildfire emissions differed significantly from the prior at the scale of individual wildfires, though with large uncertainties, and that wildfire emissions in SFBA are significant, attributing 72% of the region's CO 2 emissions during August 2020 to wildfires.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Optimization of X-ray event screening using ground and in-orbit data for the Resolve instrument onboard the XRISM satellite

The X-Ray Imaging and Spectroscopy Mission (XRISM) satellite was successfully launched and put into a low-Earth orbit on September 6, 2023 (UT). The Resolve instrument onboard XRISM hosts an X-ray microcalorimeter detector, which was designed to achieve a high-resolution ( ≤ 7 eV FWHM at 6 keV), high-throughput, and non-dispersive spectroscopy over a wide energy range. It also excels in a low background with a requirement of < 2 × 10 -3 s -1 keV -1 (0.3 to 12.0 keV), which is equivalent to only one background event per spectral bin per 100-ks exposure. Event screening to discriminate X-ray events from background is a key to meeting the requirement. We present the result of the Resolve event screening using data sets recorded on the ground and in orbit based on the heritage of the preceding X-ray microcalorimeter missions, in particular, the Soft X-ray Spectrometer onboard ASTRO-H. We optimize and evaluate 19 screening items of three types based on (1) the event pulse shape, (2) relative arrival times among multiple events, and (3) good time intervals. We show that the initial screening, which is applied for science data products in the performance verification phase, reduces the background rate to 1.8 × 10 -3 s -1 keV -1 meeting the requirement. We further evaluate the additional screening utilizing the correlation among some pulse shape properties of X-ray events and show that it further reduces the background rate, particularly in the < 2 keV band. Over 0.3 to 12 keV, the background rate becomes 1.0 × 10 -3 s -1 keV -1 .

47 OTHER INSTRUMENTATION↗
DOE OSTI2026

Atmospheric pion, kaon, and muon fluxes for sub-orbital experiments

Cosmic rays interacting with the Earth's atmosphere generate extensive air showers, which produce Cherenkov, fluorescence and radio emissions. These emissions are key signatures for detection by ground-based, sub-orbital, and satellite-based telescopes aiming to study high energy cosmic ray and neutrino events. However, detectors operating at ground and balloon altitudes are also exposed to a background of atmospheric charged particles, primarily pions, kaons, and muons, that can mimic or obscure the signals from astrophysical sources. In this work, we use coupled cascade equations to calculate the atmospheric pion, kaon and muon fluxes reaching detectors at various altitudes. Our analysis focuses on energies above 10 GeV, where the influence of the Earth's magnetic field on particle trajectories is minimal. We provide angular and energy-resolved flux estimates and discuss their relevance as background for extensive air shower detection. Furthermore, our results are potentially relevant for interpreting data from current and future balloon-borne experiments such as EUSO-SPB2 and for refining trigger and veto strategies in Cherenkov and fluorescence telescopes.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2025

Multiple Hypothesis Tracking for Opportunistic Transmitter Identification

The exploitation of radio frequency (RF) signals from Low Earth Orbit (LEO) communication satellites for the purposes of navigation is an active field of research. In this alternative navigation system, navigation observables are passively extracted from existing RF signals. Because these signals are not designed for navigation purposes and often have proprietary signal structures that are unknown to the receiver, they lack much of the information required for navigation systems or such information is unavailable to the receiver.

42 ENGINEERING↗
DOE OSTI2025

Orbiting Lunar Ground Penetrating Radar SAR Feasibility

This report aims to answer the question: “Will ground penetrating radar (GPR) be able to measure lunar subsurface resources from a 10km or above orbit?” Similarly, “Could a reasonable satellite-based system achieve the radar parameters required for lunar orbital GPR?” This report is not proposing a system but exploring if one is possible.

47 OTHER INSTRUMENTATION↗
DOE OSTI2024

DarkNESS: developing a skipper-CCD instrument to search for Dark Matter from Low Earth Orbit

The DarkNESS (Dark Matter Nano-satellite Equipped with Skipper Sensors) mission aims to deploy a skipper-CCD CubeSat Observatory to search for dark matter (DM) from Low Earth Orbit. This mission will employ novel skipper-CCDs to investigate O(keV) X-rays from decaying DM, as well as electron recoils from strongly-interacting sub-GeV DM. The DarkNESS mission will be the first space deployment of skipper-CCDs, and the DarkNESS team is developing a skipper-CCD instrument that is compatible with the CubeSat platform. DarkNESS has recently progressed from laboratory validation to a Critical Design Review (CDR) phase, with a launch opportunity anticipated in late 2025. The implementation of the DarkNESS skipper-CCD payload on the CubeSat platform will pave the way for future demonstrators of space-based imagers for X-ray and single-electron counting applications.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗