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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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All sourcesNASA NTRSDOE OSTI
NASA NTRSDate not supplied

Preliminary Assessment of the Impact on the V-Band Oxygen Channels From Satellite Communication Uplinks

We calculate the percentage of time that an ATMS-like instrument [1] will be illuminated by the uplink beam of one of the proposed V-band communication system and estimate the damage resulting from such exposure. Using a combination of openly available information and educated guesses about the location and characteristics of the up/down link terminals, we constructed the ground segment of a hypothetical high-speed communication network. The space segment of the network was constructed from the orbital data of the existing Starlink constellation [2] of 6223 communication satellites (comsats) which is used as strawman to represent any other possible constellation of communication satellites. It is shown that without a very delicate balance of frequency allocations (science vs telecommunications), coupled with extremely steep and deep bandpass-defining filters, and strict adherence to the agreed limits (i.e. no out-of-band transmissions) the deployment of the telecommunication network leads to almost-complete loss of some important geophysical data. For the analysis we use the spectral characteristics of the ATMS instrument with the ephemeris for the NOAA-21 satellite [3]. The analysis is conducted for the USA and the simulation covers 8 consecutive days in July 2024. Effective and accurate microwave remote sensing of the atmosphere depends on the availability of interference-free spectrum windows at frequencies which are prescribed by physical processes [e.g. 4]. The family of resonant lines of the oxygen molecule near 60 GHz provides a unique opportunity to sample the vertical distribution of temperature and density from space, and it has been exploited for weather and climate studies from polar-orbiting satellites since 1978 (MSU on TIROS-N [5]). It remains a staple in the payloads operated by Russia, China, USA, Japan, France, India, UK, Ukraine [6] which are built around a common blueprint: a few wide-band (hundreds of MHz) channels around 50 GHz to sample the atmosphere and the surface while several more channels with high spectral resolution (few MHz) sample the individual resonant lines. Accurate retrieval of the environmental parameters depends upon the data provided by both sets of channels, and the their location in frequency space is not arbitrary and cannot be altered at will [7, 8]. The introduction of 5G technology in 2019 has driven telecommunication companies to request more bandwidth to be dedicated to their devices. This additional bandwidth is only available in spectral regions traditionally reserved for environmental and astrophysical research, such as the V-band between 50 and 60 GHz for up/downlink between satellites in low-earth orbits and terminals connected to fiberoptics network for distribution to high-speed local internet services. The power broadcast by the uplink communication leg is many orders of magnitude greater than the natural thermal signal emitted from the Earth scene. If the ground antenna were to perfectly align with the passive instrument’s antenna, the spaceborne receiver would suffer permanent, irreparable damage. While a direct boresight-to-boresight conjunction is extremely unlikely (even with a large constellation of satellites the fraction of the celestial sphere occupied by the satellites remains minuscule) the finite size of the ground station’s antenna beam in the sky suggests that the ATMS will be in the near background (as seen from the ground station) of one of the communication satellites and will be illuminated by either the main lobe or the near sidelobes of the uplink antenna more often than it is desirable. For our analysis we first calculate the position of the ATMS with respect to each of the ground stations at a resolution of 0.2 sec, then calculate the position of each of the comsats which are at least 25 deg above the station’s local horizon; finally we calculate the angle between the line-of-sight of the ATMS and the line-of-sight of the comsat. We assume that the gain pattern of the ground station is circularly symmetric; the angle-off-station-boresight then provides an attenuation of the uplink power which we use to assess the likely effect upon the passive instrument’s operations. We assume that each ground station can communicate with all the comsats in its field of view; this implies that, on average, a ground station can engage with 46 comsats simultaneously. The analysis is repeated for the case when the uplink broadcast within the ATMS passive channels (in-band scenario) and for the case when the uplink is limited to frequencies adjacent to the ATMS channels (out-of-band scenario). The antenna of the ground station is modelled as having a HPBW (Half-Power Beam Width) of 0.16 deg and EIRP (Equivalent Isotropic Radiated Power) of 70 dBW. We account for the geometric dissipation of the signal caused by the satellite orbital altitude, the attenuation induced by atmospheric gasses at 51 GHz and the mismatch between the circular polarization of the ground-based transmitting antenna and the linear polarization of the satellite-borne receiving antenna. The damages on ATMS are estimated from bench-level measurement conducted at the ATMS’ manufacturer facilities [unpublished].

passive microwave↗
NASA NTRS1964

Radio Noise Problems in Arctic Regions

Three main types of radio noise should be considered when establishing noise levels for communication purposes or in experiments utilizing radio techniques in Arctic regions. These are atmospheric and man-made noise, and precipitation static. National Bureau of Standards radio noise data obtained hourly at Arctic and Antarctic stations on eight .fixed frequencies between 51 kc and 20 Mc/s are analyzed to show the characteristics of the three types. The diurnal and seasonal variations of atmospheric radio noise at high latitudes are explainable in terms of changes in propagation factors and in the distribution of world thunderstorm activity. In both northern and southern Arctic regions atmospheric noise decreases during polar cap absorption (PCA), most markedly in the h.f. band. The probable magnitude of man-made noise in the h.f. band is estimated from data taken during PCA, when atmospheric noise is absent. At Thule man-made noise on 2.5 and 5 Mc/s appears to be 57 and 49 dB above kTB (where kTB is antenna thermal noise power), respectively, while at Byrd Station the values are about 20 and 12 dB respectively. Precipitation static is generated on exposed antennas during periods of blowing snow (blizzards). The noise power magnitude can be at least 50 dB above man-made and atmospheric levels, but the maximum enhancement cannot be ascertained because of missing data. In winter and spring months at Byrd Station radio data dependent upon exposed antennas may be lost 10-30 per cent of the time due to precipitation static alone.

Radio Noise↗
NASA NTRS1993

The Flight Performance of the Galileo Orbiter USO

Results are presented from an analysis of radio metric data received by the DSN stations from the Galileo spacecraft using an Ultrastable Oscillator (USO) as a signal source. These results allow the health and performance of the Galileo USO to be evaluated, and are used to calibrate this Radio Science instrument and the data acquired for Radio Science experiments such as the Red-shift Observation, Solar Conjunction, and Jovian occultations. Estimates for the USO-referenced spacecraft-transmitted frequency and frequency stability were made for 82 data acquisition passes conducted between launch (October 1989) and November 1991. Analyses of the spacecraft-transmitted frequencies show that the USO is behaving as expected. The USO was powered off and then back on in August 1991 with no adverse effect on its performance. The frequency stabilities measured by Allan deviation are consistent with expected values due to thermal wideband noise and the USO itself at the appropriate time intervals. The Galileo USO appears to be healthy and functioning normally in a reasonable manner.

D D Morabito↗
NASA NTRSDate not supplied

Emergence of Complex Modes in Lightly Damped Structural Systems

In this short presentation format, we will provide a set of useful equations, relationships, and physical interpretations direct from the damped two-mode interaction problem. We will demonstrate that the results from the two-mode interaction problem are in direct agreement with observed test data. Practical methods for estimating the parameters driving the relations direct from modal test data are provided. We finalize with two examples demonstrating weak and strong interactions.

spaceflight hardware↗
NASA NTRS1991

Impact of Inertia, Friction, and Backlash upon Force Control in Telemanipulation

The mechanical behavior of master controllers of telemanipulators has been a concern of both designers and implementors of telerobotic systems. In general, the literature recommends that telemanipulator systems be constructed that minimize inertia, friction, and backlash in an effort to improve telemanipulative performance. For the most part, these recommendations are founded upon theoretical analysis or simply intuition. Although these recommendations are not challenged on their merit, the material results are measured of building and fielding telemanipulators that possess less than ideal mechanical behaviors. Experiments are described in which forces in a mechanical system with human input are evaluated as a function of mechanical characteristics such as inertia, friction, and backlash. Results indicate that the ability of the human to maintain gripping forces was relatively unaffected by dynamic characteristics in the range studied, suggesting that telemanipulator design in this range should be based on task level force control requirements rather than human factors.

Neil A Duffie↗
NASA NTRSDate not supplied

Evaluation of Long-Term Storage Stability and Operational Efficiency of Rapid Cycle Amine Adsorbents

With the recent incorporation of Mars Extravehicular Activity (EVA) into the 2025 NASA roadmap, Rapid Cycle Amine (RCA) technology advancement within the Exploration Extravehicular Mobility Unit (xEMU) applies to both the upcoming Lunar Artemis missions and future human exploration of Mars. The incorporation of commercial spacesuit vendors to service NASA’s crewed-space programs since 2021 has increased the demand for regenerable, RCA-based carbon dioxide (CO2) and humidity control adsorbents. The regenerable RCA subunit is the most advanced, long-term solution for CO2 removal and humidity control, enabling both lunar and Martian EVAs. The adsorbent selected for use within the RCA unit must exhibit sufficient storage stability and operational efficiency for prolonged missions. As XploSafe worked to simultaneously develop both a recirculating sub-atmospheric test rig and adsorbents for the RCA system within the xEMU, several novel adsorbents were evaluated for long-term storage stability in support of future extended-duration missions. The chosen materials were periodically evaluated by nuclear magnetic resonance (NMR) spectroscopy, thermal desorption-coupled with gas chromatography/mass spectrometry (TD-GC/MS), and CO2 adsorption to assess long-term storage efficacy across various environmental storage conditions. NMR spectroscopy was utilized by extracting the active CO2 adsorbing chemical from the solid support with deuterated solvent and comparing the spectra over time for degradation and change. The solid adsorbents were also analyzed via TD-GC/MS to reveal any potential off-gassing chemicals over time. Additionally, XploSafe’s breakthrough test rig was utilized to dose the solid adsorbents with a 585 BTU/h metabolic rate flow-equivalent CO2 stream and monitored for 0–99% CO2 breakthrough. The performance metrics from the breakthrough analysis were compared over the storage study duration for CO2 removal and humidity control. Xplo-SA9T was evaluated for 24 months, whereas two additional adsorbent variants, MMPA-Sorbent and LPEI-Sorbent, were each evaluated for 12 months.

John R Tidwell↗
NASA NTRS1982

Dynamic environments for space shuttle payloads

Payload bay dynamic data from the first two space shuttle flights are summarized and evaluated. Development of dynamic environment design and test criteria for shuttle payloads from measured flight data is discussed. Factors that must be considered are flight to flight variations, spatial variations, temporal variations, measurement bias errors and the degree of confidence desired that a predicted environment will not be exceeded in flight. Summary and conclusion reports will be published after STS-4 and at appropriate intervals thereafter. The nature of these future reports and their impact on the user community is discussed.

Dennis L Kern↗
NASA NTRS2026

Proactive Wildfire Management: A Remote Sensing and Multimodal CNN-MLP Architecture for Ignition Risk Forecasting

As the frequency and intensity of wildfires increase, with fire seasons now starting earlier and ending later than they have over the past decades, current monitoring systems, such as lookout towers and satellites, are hindered by cloud cover, low-resolution imagery, and static data gaps that fail to track vegetation moisture levels fast enough to catch rapid pre-ignition changes. This report proposes a Machine Learning-enabled Wildfire Ignition Prediction framework that combines satellite monitoring with dynamic and high-resolution remote sensing from Unmanned Aerial Vehicle (UAV) swarms. The method would use multispectral and thermal data from the Landsat program to create a baseline for vegetation health, calculating a two-band Enhanced Vegetation Index (EVI2) and the moisture content of the vegetation. These inputs will later be fused with microscale UAV weather data, including thermal hotspots found through thick canopies, hyperspectral chemical signatures of pre-visual combustion, and local weather streams. The multispectral satellite, multispectral Light Detection and Ranging (LiDAR), and thermal data would then be processed through a Convolutional Neural Network (CNN), alongside a Multilayer Perceptron (MLP) for the micro-weather telemetry. The outputs of these networks would be fused into a single feature representation and passed through a final prediction network to generate real-time ignition risk scores and hotspot alerts. Model performance would be assessed using standard classification metrics, including a Receiver Operating Characteristic - Area Under the Curve (ROC AUC) and F1 score. This system would allow first responders to identify high-risk zones and intervene before ignition occurs, improving emergency response time compared to current approaches.

machine learning↗
NASA NTRS1977

Reanalysis of the Apollo Cosmic Gamma-Ray Spectrum in the 0.3 to 10 Mev Energy Region

Additional data obtained from the Apollo 16 and 17 missions, together with collateral calculations on background radiation effects, have made possible an improved subtraction of unwanted backgrounds from the diffuse cosmic gamma ray data previously reported from Apollo 15. As a result, the 1 to 10 MeV spectrum is lowered significantly and connects smoothly with recent data at other energies. The inflection reported previously is much less pronounced and has no more than 1.5 sigma significance. Sky occultation by the Apollo 16 spacecraft shows the bulk of the 0.3 to 1 MeV radiation to be diffuse. The analysis of spurious backgrounds points to important improvements for future experiments designed for this spectral region. A light-weight satellite design can give a fourfold improvement in the signal to noise for such a measurement. Use of an anisotropic central crystal, which spins quickly compared with possible time variations in detector background, would enable sensitive limits to be set on galactic plane and point source contributions.

C S Dyer↗
NASA NTRS2026

Model Correlation and Thermal Analysis of xEMU Boot at Lunar South Pole Temperatures

The National Aeronautics and Space Administration (NASA) Artemis program plans to send astronauts to the lunar south pole, a region of the moon that is colder than previous lunar missions and low earth orbit operations. The spacesuit boots that will be used on these missions will be directly impacted by these extremely cold temperatures (down to ~50 K). To assess the performance of the Exploration Extravehicular Mobility Unit (xEMU) lunar boot in these extreme temperatures, the boot was tested at the Jet Propulsion Lab (JPL) in the Cryogenic Ice Transfer, Acquisition Development, and Excavation Laboratory (CITADEL) thermal vacuum (TVAC) chamber. This data was used to correlate thermal models to predict operational performance of the boots on the lunar south pole. This paper documents the data analysis, thermal boot model correlation, and operational predictions conducted using data from the xEMU TVAC test. Data from the test series was used to determine expected thermal conductances within the boot and between the boot and environment. These conductances were used to correlate a Thermal Desktop model of the xEMU boot across 10 different test points which varied external temperature, internal boot ventilation flowrate, and contact pressure. The correlated model was then used to predict operational performance in the lunar south pole. While the predictions indicate promising evidence for performance of the boots at the 100K test point, there is still substantial uncertainty in performance, particularly at the 48K test point. The results of this test series and model correlation stress the importance of improved testing for characterizing the expected thermal resistance between the outside of the boot and the lunar surface.

xEMU↗
NASA NTRSDate not supplied

Model Correlation and Thermal Analysis of xEMU Boot at Lunar South Pole Temperatures

The National Aeronautics and Space Administration (NASA) Artemis program plans to send astronauts to the lunar south pole, a region of the moon that is colder than previous lunar missions and low earth orbit operations. The spacesuit boots that will be used on these missions will be directly impacted by these extremely cold temperatures (down to ~50 K). To assess the performance of the Exploration Extravehicular Mobility Unit (xEMU) lunar boot in these extreme temperatures, the boot was tested at the Jet Propulsion Lab (JPL) in the Cryogenic Ice Transfer, Acquisition Development, and Excavation Laboratory (CITADEL) thermal vacuum (TVAC) chamber. This data was used to correlate thermal models to predict operational performance of the boots on the lunar south pole. This paper documents the data analysis, thermal boot model correlation, and operational predictions conducted using data from the xEMU TVAC test. Data from the test series was used to determine expected thermal conductances within the boot and between the boot and environment. These conductances were used to correlate a Thermal Desktop model of the xEMU boot across 10 different test points which varied external temperature, internal boot ventilation flowrate, and contact pressure. The correlated model was then used to predict operational performance in the lunar south pole. While the predictions indicate promising evidence for performance of the boots at the 100K test point, there is still substantial uncertainty in performance, particularly at the 48K test point. The results of this test series and model correlation stress the importance of improved testing for characterizing the expected thermal resistance between the outside of the boot and the lunar surface.

thermal analysis↗
NASA NTRS1968

Surveyor Project Final Report: Part 2 - Science Results

This two-part document constitutes the Project Final Report on the Surveyor spacecraft. Part I of this Technical Report consists of a technical description and an evaluation of engineering results of the systems used on Surveyor. Part II presents the science data derived from the lunar soft-landing missions, and the scientific analyses conducted by the Surveyor Scientific Evaluation Advisory Team, the Surveyor Investigator Teams, and the associated Working Croups. Results given in this part of this Technical Report are based on data evaluation before June 15, 1968. It is expected that future evaluations and analyses will provide additional science results.

Jet Propulsion Laboratory↗
NASA NTRS1992

Science questions for the Magellan continuing mission

Magellan has completed two mapping cycles around the planet Venus, returning high resolution synthetic aperture images and altimetry data of over 95 percent of the planet's surface. Venus is dominated by low lying volcanic plains with an impact crater population indicating an average surface age of about 500 million years. Highland regions either tend to be characterized by volcanic shield complexes and rifting or by complex ridged terrain. Successful as the primary mission of Magellan has been, significant scientific questions remain to be addressed with imaging and gravity data that will be collected over the next several years.

Saunders, R. S.↗
NASA NTRSDate not supplied

Usage-based Lifing of Lithium-Ion Battery with HybridPhysics-Informed Neural Networks

Lithium-ion batteries are commonly used to power unmanned aircraft vehicles (UAVs).The ability to model and forecast the remaining useful life of these batteries enables UAV reliability assurance. Building accurate models for battery state of charge and state of health based on first principles is challenging due to the complex electrochemistry that governs battery operations and computational complexity required to solve them. Therefore, reduced order models are often used due to their ability to capture the overall battery discharge. Un-fortunately, these simplifications lead to residual discrepancy between model predictions and observed data. In this paper, we present a hybrid modeling approach merging reduced-order models and neural networks. In this approach, while most of the input-output relationship is captured by Nernst and Butler-Volmer equations, data-driven kernels reduce the gap between predictions and observations. We validate our approach using data publicly available through the NASA Prognostics Center of Excellence repository. Results showed that our hybrid battery prognosis model can be successfully calibrated, even with a limited number of observations.

Lithium-ion Battery↗
NASA NTRS2025

Improving Adhesive Bondline Time of Flight Predictions During Autoclave Cure Utilizing Machine Learning

Composite materials are increasingly being used in aerospace applications due to their superior strength-to-weight ratio compared to commonly used metals. A current limitation to widespread adoption is the certification of adhesively bonded joints. One approach to improving adhesive bonding in composites is accurately measuring the thickness of adhesive bondlines in composite laminates. Precise bondline thickness control is essential for aerospace applications where adhesive layer thickness directly affects joint fracture properties and structural performance. This study focused on implementing machine learning techniques to determine the ultrasonic time of flight (directly correlated to thickness) in adhesive bondlines throughout autoclave cure cycles. A high-temperature (use up to 180°C) ultrasonic scanning system was deployed in an autoclave to provide time of flight data through composite panels. Three experiments were conducted on the curing of 305 mm × 305 mm unidirectional composite panels. In the first experiment, a piecewise function was fit for the temperature correction factor to account for changing autoclave temperatures. Due to deficiencies in the first calibration experiment, a second experiment was run, and the results were used to train a machine learning model. The revised experiment, in combination with the machine learning model, significantly increased the accuracy of the bondline time of flight predictions (~14% error reduced to <1%). Data was processed using the Regression Learner Application in MATLAB®, with a Support Vector Machine selected for the model. The result was a machine learning algorithm capable of reliably quantifying ultrasonic time of flight through adhesive bondlines. The third experiment provided independent test data for the machine learning model, demonstrating that the model produces accurate predictions from data beyond its training set.

Machine Learning↗
NASA NTRSDate not supplied

Exposure of Highly Reflective Far-Ultraviolet Coatings to LEO Environment for TRL Advancement for the Habitable Worlds Observatory

Over the past several years, our team at the NASA Goddard Space Flight Center (GSFC), in collaboration with the Jet Propulsion Laboratory (JPL) and the Naval Research Laboratory (NRL), have developed several new protected Al coating technologies with improved Far-Ultraviolet (FUV) reflectance performance and more robust environmental stability. These include Al protected with lithium-based fluoride (LiF) coatings such as hot deposited LiF (eLiF), XeF 2 -passivated LiF coatings (XeLiF), Li 3 AlF 6 overcoats, AlF 3 (plasma passivated), and XeF 2 passivated MgF 2 coatings (XeMgF 2 ). However, despite these developments, relatively little experimental information exists regarding the long-term stability of these coatings after simultaneous exposure to the Low Earth Orbit (LEO) environment. To evaluate their environmental durability and advance their Technology Readiness Level (TRL), representative samples of these coating technologies, Al+XeLiF, Al+eLiF, Al+Li 3 AlF 6 , Al+AlF 3 , Al+XeMgF 2 , and bare Al as reference samples, were flown onboard the International Space Station (ISS) as part of the Materials International Space Station Experiment 20 (MISSE-20). The MISSE platform is operated by Aegis Aerospace for relatively long-duration (e.g. 6 months) external exposure experiments in a space environment. The coatings were deposited on ULE and Zerodur substrates, and witness samples deposited on the same coatings runs, but on glass slides were left on Earth as control. A subset of the flight samples were fitted with MgF 2 windows to reduce direct exposure to atomic oxygen (AO) and charged particles, and still let through UV and other types of radiation on these samples. After approximately 6 months of exposure in the forward-facing (RAM) direction, the samples were returned to Earth and characterized by performing FUV/NUV/VIS/NIR reflectance measurements to quantify degradation, spectroscopic ellipsometry to evaluate coating thickness and optical constants, atomic force microscopy (AFM) to quantify surface roughness evolution during the flight in the ISS. The MgF 2 protective windows were also analyzed through FUV transmission measurements. Comparison with the witness samples left on the ground and with the flown bare Al samples (with just the naturally occurring Al 2 O 3 layer) provided a quantitative assessment of coating thickness variations, optical performance degradation, and morphological changes induced by prolonged exposure to the LEO environment.

Far Ultraviolet (FUV)↗
NASA NTRS2022

Exploration of an Adaptive Routine for Battery Modeling

The purpose of this document is to explore the use of adaptive routines in battery modeling. The adaptive routines consist of real-time state estimators combined with battery parameter model components that are adjusted in real-time as battery data becomes available. Several aspects are explored. It is shown that model parameter identification is possible for simple battery models using available input/output data measurements. The online system identification used is recursive least squares. Model identification may be combined with a state observer such as the extended Kalman filter or the unscented Kalman filter to form an adaptive model combined with state estimation. However, such a combination is found to be problematic due to uncertainty, observability and stability issues. This paper is organized as follows. Section 1 introduces adaptive routines and possible roles they play in battery modeling. In Section 2 real-time parameter identification is described with results based on battery data. Section 3 reviews various state estimators and results using a simple battery model. In Section 4 parameter identification and state estimation are combined to form an adaptive routine. Finally, in Section 5 conclusions are drawn and future work is suggested.

Adaptive↗
NASA NTRS1965

Aerodynamic Design of Axial Flow Compressors

An overview of 'Aerodynamic systems design of axial flow compressors' is presented. Numerous chapters cover topics such as compressor design, potential and viscous flow in two dimensional cascades, compressor stall and blade vibration, and compressor flow theory. Theoretical aspects of flow are also covered. This work is based substantially on a three-volume Confidential Research Memorandum f h t issued by the National Advisory Committee for Aeronautics in 1956 and declassified in .1958 for release to the general public. The material, which was of a fundamental character, has been updated for the present edition in the light of subsequent developments in the field and has been carefully reexamined for current validity by members of the staff of the NASA Lewis Research Center, Cleveland, Ohio. It is now published for the first time in a single volume to meet continuing demand for the information and to make it readily available in convenient form to the engineering community both within and outside the National Aeronautics and Space Administration.

Axial flow compressor↗