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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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NASA NTRS1991

Telescience - Distributed science planning and processing in the 1990's and beyond

The paper discusses the technology and the architecture design concepts of the Telescience, a system for near-time distributing and processing data obtained aboard the Columbus and Space Station Freedom missions. Particular attention is given to the Flight Projects Office Information Systems Testbed (FIST) for prototype systems and to the proposals made by FIST to study technology for future applications. One such proposal is for a high speed, high volume network testbed that will test the ability of a system to receive and transmit data at high rates, and the technology for interfacing between the networks, the workstations, and other peripheral devices.

Liggett, Patricia K.↗

NASA NTRS1974

Frequency standards requirements of the NASA deep space network to support outer planet missions

Navigation of Mariner spacecraft to Jupiter and beyond will require greater accuracy of positional determination than heretofore obtained if the full experimental capabilities of this type of spacecraft are to be utilized. Advanced navigational techniques which will be available by 1977 include Very Long Baseline Interferometry (VLBI), three-way Doppler tracking (sometimes called quasi-VLBI), and two-way Doppler tracking. It is shown that VLBI and quasi-VLBI methods depend on the same basic concept, and that they impose nearly the same requirements on the stability of frequency standards at the tracking stations. It is also shown how a realistic modelling of spacecraft navigational errors prevents overspecifying the requirements to frequency stability.

Fliegel, H. F.↗

DOE OSTI2022

End-to-End Optimization for Battery Materials and Molecules by Combining Graph Neural Networks and Reinforcement Learning

The National Renewable Energy Laboratory (NREL), together with the Colorado School of Mines (CSM) and Colorado State University (CSU), has developed a machine learning-enhanced approach to the design of new battery materials. Currently, such materials are designed in part via numerous expensive high-fidelity computational simulations that predict the performance of a given composition. Even with computational screening tools, the vast landscape of possible molecular or crystal structures exceeds current and future computational capacity. Improving the efficiency by which new materials can be optimized will therefore disrupt the cost, risk, and time required to bring new energy solutions to the marketplace. Predicting the properties of an organic molecule or periodic crystalline material given its structure has grown increasingly common. These approaches leverage large-scale computational and experimental databases and ML approaches such as graph neural networks. The inverse design problem of finding a material that possesses desired properties is substantially more challenging, since enumerating all valid material structures is not feasible. In this project, we leveraged recent success in reinforcement learning to efficiently navigate this high-dimensional search space. Just as algorithms can find the optimal chess moves from nearly limitless options, we train an approach to evolve a simple starting structure into a complex structure that possess the desired properties. Our solution has been demonstrated by applying it to two related design application tasks for short- and long-term energy storage, respectively: (1) the design of solid-state ion conductors and (2) the design of organic redox-active materials. The project has resulted an open-source software library for material design, documented examples of applying the library to both organic and inorganic material optimization, and peer-reviewed publications detailing the data, computational models, and resulting candidate materials.

25 ENERGY STORAGE↗

NASA NTRS1972

Large-scale solar magnetic fields and H-alpha patterns

Coronal and interplanetary magnetic fields computed from measurements of large-scale photospheric magnetic fields suffer from interruptions in day-to-day observations and the limitation of using only measurements made near the solar central meridian. Procedures were devised for inferring the lines of polarity reversal from H-alpha solar patrol photographs that map the same large-scale features found on Mt. Wilson magnetograms. These features may be monitored without interruption by combining observations from the global network of observatories associated with NOAA's Space Environment Services Center. The patterns of inferred magnetic fields may be followed accurately as far as 60 deg from central meridian. Such patterns will be used to improve predictions of coronal features during the next solar eclipse.

Mcintosh, P. S.↗

NASA NTRS1984

GSFC network operations with Tracking and Data Relay Satellites

The Tracking and Data Relay Satellite System (TDRSS) Network (TN) has been developed to provide services to all NASA User spacecraft in near-earth orbits. Three inter-relating entities will provide these services. The TN has been transformed from a network continuously changing to meet User specific requirements to a network which is flexible to meet future needs without significant changes in operational concepts. Attention is given to the evolution of the TN network, the TN capabilities-space segment, forward link services, tracking services, return link services, the three basic capabilities, single access services, multiple access services, simulation services, the White Sands Ground Terminal, the NASA communications network, and the network control center.

Spearing, R.↗

NASA NTRS2003

NASA GPM GV Science Requirements

An important scientific objective of the NASA portion of the GPM Mission is to generate quantitatively-based error characterization information along with the rainrate retrievals emanating from the GPM constellation of satellites. These data must serve four main purposes: (1) they must be of sufficient quality, uniformity, and timeliness to govern the observation weighting schemes used in the data assimilation modules of numerical weather prediction models; (2) they must extend over that portion of the globe accessible by the GPM core satellite to which the NASA GV program is focused - (approx.65 degree inclination); (3) they must have sufficient specificity to enable detection of physically-formulated microphysical and meteorological weaknesses in the standard physical level 2 rainrate algorithms to be used in the GPM Precipitation Processing System (PPS), i.e., algorithms which will have evolved from the TRMM standard physical level 2 algorithms; and (4) they must support the use of physical error modeling as a primary validation tool and as the eventual replacement of the conventional GV approach of statistically intercomparing surface rainrates fiom ground and satellite measurements. This approach to ground validation research represents a paradigm shift vis-&-vis the program developed for the TRMM mission, which conducted ground validation largely as a statistical intercomparison process between raingauge-derived or radar-derived rainrates and the TRMM satellite rainrate retrievals -- long after the original satellite retrievals were archived. This approach has been able to quantify averaged rainrate differences between the satellite algorithms and the ground instruments, but has not been able to explain causes of algorithm failures or produce error information directly compatible with the cost functions of data assimilation schemes. These schemes require periodic and near-realtime bias uncertainty (i.e., global space-time distributed conditional accuracy of the retrieved rainrates) and local error covariance structure (i.e., global space-time distributed error correlation information for the local 4-dimensional space-time domain -- or in simpler terms, the matrix form of precision error). This can only be accomplished by establishing a network of high quality-heavily instrumented supersites selectively distributed at a few oceanic, continental, and coastal sites. Economics and pragmatics dictate that the network must be made up of a relatively small number of sites (6-8) created through international cooperation. This presentation will address some of the details of the methodology behind the error characterization approach, some proposed solutions for expanding site-developed error properties to regional scales, a data processing and communications concept that would enable rapid implementation of algorithm improvement by the algorithm developers, and the likely available options for developing the supersite network.

Smith, E.↗

NASA NTRS1992

Mechanisms of nascent fiber formation during avian skeletal muscle hypertrophy

This study examined two putative mechanisms of new fiber formation in postnatal skeletal muscle, namely longitudinal fragmentation of existing fibers and de novo formation. The relative contributions of these two mechanisms to fiber formation in hypertrophying anterior latissimus dorsi (ALD) muscle were assessed by quantitative analysis of their nuclear populations. Muscle hypertrophy was induced by wing-weighting for 1 week. All nuclei formed during the weighting period were labeled by continuous infusion of 5-bromo-2'-deoxyuridine (BrdU), a thymidine analog, and embryonic-like fibers were identified using an antibody to ventricular-like embryonic (V-EMB) myosin. The number of BrdU-labeled and unlabeled nuclei in V-EMB-positive fibers were counted. Wing-weighting resulted in significant muscle enlargement and the appearance of many V-EMB+ fibers. The majority of V-EMB+ fibers were completely independent of mature fibers and had a nuclear density characteristics of developing fibers. Furthermore, nearly 100% of the nuclei in independent V-EMB+ fibers were labeled. These findings strongly suggest that most V-EMB+ fibers were nascent fibers formed de novo during the weighting period by satellite cell activation and fusion. Nascent fibers were found primarily in the space between fascicles where they formed a complex anastomosing network of fibers running at angles to one another. Although wing-weighting induced an increase in the number of branched fibers, there was no evidence that V-EMB+ fibers were formed by longitudinal fragmentation. The location of newly formed fibers in wing-weighted and regenerating ALD muscle was compared to determine whether satellite cells in the ALD muscle were unusual in that, if stimulated to divide, they would form fibers in the inter- and intrafascicular space. In contrast to wing-weighted muscle, nascent fibers were always found closely associated with necrotic fibers. These results suggest that wing-weighting is not simply another model of regeneration, but rather produces a unique environment which induces satellite cell migration and subsequent fiber formation in the interfascicular space. De novo fiber formation is apparently the principal mechanism for the hyperplasia reported to occur in the ALD muscle undergoing hypertrophy induced by wing-weighting.

Non-NASA Center↗

NASA NTRS2012

Compliance with High-Intensity Radiated Fields Regulations - Emitter's Perspective

NASA's Deep Space Network (DSN) uses high-power transmitters on its large antennas to communicate with spacecraft of NASA and its partner agencies. The prime reflectors of the DSN antennas are parabolic, at 34m and 70m in diameter. The DSN transmitters radiate Continuous Wave (CW) signals at 20 kW - 500 kW at X-band and S-band frequencies. The combination of antenna reflector size and high frequency results in a very narrow beam with extensive oscillating near-field pattern. Another unique feature of the DSN antennas is that they (and the radiated beam) move mostly at very slow sidereal rate, essentially identical in magnitude and at the opposite direction of Earth rotation.The DSN is in the process of revamping its documentation to provide analysis of the High Intensity Radiation Fields (HIRF) environment resulting from radio frequency radiation from DSN antennas for comparison to FAA regulations regarding certification of HIRF protection as outlined in the FAA regulations on HIRF protection for aircraft electrical and electronic systems (Title 14, Code of Federal Regulations (14 CFR) [section sign][section sign] 23.1308, 25.1317, 27.1317, and 29.1317).This paper presents work done at JPL, in consultation with the FAA. The work includes analysis of the radiated field structure created by the unique DSN emitters (combination of transmitters and antennas) and comparing it to the fields defined in the environments in the FAA regulations. The paper identifies areas that required special attention, including the implications of the very narrow beam of the DSN emitters and the sidereal rate motion. The paper derives the maximum emitter power allowed without mitigation and the mitigation zones, where required.Finally, the paper presents summary of the results of the analyses of the DSN emitters and the resulting DSN process documentation.

DSN emitters↗

DOE OSTI2025

Orbital-Selective Instabilities and Spin Fluctuations at the Verge of Superconductivity in Interlayer-Expanded Iron Selenide

Understanding electron correlation-driven instabilities and their coupling to structural phases is essential for deciphering multiorbital pairing in unconventional superconductors. We investigate Li x (C 5 H 5 N) y Fe 2 Se 2 (x ∼ 0.6; y ∼ 0.7−0.9), a tetragonal β-FeSe intercalate with a superconducting transition temperature (T c = 39 K) closely tied to an expanded Fe-layer spacing (∼11.4 Å). High-resolution synchrotron Xray diffraction and core-level absorption spectroscopy reveal subtle lattice distortions on cooling without a symmetry-breaking transition. Instead, the material exhibits negative thermal expansion (NTE) in the two-dimensional Fe network below T S ∼ 70 K, and stiffening of local Se−Fe−Se bond dynamics near T c . The spatially incoherent rearrangement of FeSe 4 tetrahedra and the site-local fluctuations, signal reduced electron correlations compared to those of parent β-FeSe (T c = 8 K). Complementary X-ray emission spectroscopy, a fast local probe of Fe 3d valence states, detects persistent local Fe spin moments below T S , unlike quenching in related systems. These findings indicate that decoupling of Fe planes leads to an electronically driven lattice instability. The latter emerges as NTE induced from weak, orbital-selective localization of in-plane Fe 3d states rather than conventional transverse vibrations. Governed by Hund’s coupling, this selectivity permits coexistence of local spin fluctuations with itinerant d-electrons critical for enhancing T c . These results suggest that intercalation-driven d-orbital differentiation moderates electron correlations, providing a pathway to optimize the superconductivity in low-dimensional quantum materials.

36 MATERIALS SCIENCE↗

DOE OSTI2025

Electronic structure prediction of medium and high entropy alloys across composition space

We propose machine learning (ML) models to predict the electron density — the fundamental unknown of a material’s ground state — across the composition space of concentrated alloys. From this, other physical properties can be inferred, enabling accelerated exploration. A significant challenge is that the number of descriptors and sampled compositions required for accurate prediction grows rapidly with species. To address this, we employ Bayesian Active Learning (AL), which minimizes training data requirements by leveraging uncertainty quantification capabilities of Bayesian Neural Networks. Compared to the strategic tessellation of the composition space, Bayesian-AL reduces the number of training data points by a factor of 2.5 for ternary (SiGeSn) and 1.7 for quaternary (CrFeCoNi) systems. We also introduce easy-to-optimize, body-attached-frame descriptors, which respect physical symmetries while keeping descriptor-vector size nearly constant as alloy complexity increases. Our ML models demonstrate high accuracy and generalizability in predicting both electron density and energy across composition space.

materials science↗

NASA NTRS1991

Extreme Ultraviolet Explorer (EUVE): Emergency support

The Extreme Ultraviolet Explorer (EUVE) will conduct a survey of the entire celestial sphere in the extreme ultraviolet (UV) spectrum, 100 to 1000 angstrom units. This survey will be accomplished using four grazing incidence telescopes mounted on a spinning spacecraft whose spin axis is along the Sun line. Data is taken only when the spacecraft is in the Earth's shadow. The EUVE will be placed in a near circular orbit by a Delta expendable launch vehicle. The design orbit is circular at an altitude of 550 km by 28.5 degrees for a period of 96 minutes. The EUVE will be flown on a standardized Explorer Platform (EP) which will be reused for followup Explorer missions. Coverage will be provided by the Deep Space Network (DSN) for EUVE emergencies that would prevent communications via the normal channels of the Tracking and Data Relay Satellite System (TDRSS). Emergency support will be provided by the 26-meter subnet. Data is presented in tabular form for DSN support, frequency assignments, telemetry, and command.

Zayas, H.↗

DOE OSTI2023

Fast and accurate simulations of calorimeter showers with normalizing flows

In this study, we introduce caloflow, a fast detector simulation framework based on normalizing flows. For the first time, we demonstrate that normalizing flows can reproduce many-channel calorimeter showers with extremely high fidelity, providing a fresh alternative to computationally expensive geant4 simulations, as well as other state-of-the-art fast simulation frameworks based on generative adversarial networks (GANs) or variational autoencoders (VAEs). In addition to the usual histograms of physical features and images of calorimeter showers, we introduce a new metric for judging the quality of generative modeling: the performance of a classifier trained to differentiate real from generated images. We show that GAN-generated images can be identified by the classifier with nearly 100% accuracy, while images generated from caloflow are better able to fool the classifier. More broadly, normalizing flows offer several advantages compared to other state-of-the-art approaches (GANs and VAEs), including tractable likelihoods, stable and convergent training, and principled model selection. Normalizing flows also provide a bijective mapping between data and the latent space, which could have other applications beyond simulation, for example, to detector unfolding.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

NASA NTRS1980

Planetary radar

The radar astronomy activities supported by the Deep Space Network are reported. The high power S- and X-band radar transmitters at the Goldstone 64 meter station were used for a radar probe of Mars during January, February, and March 1980, which was designed to provide range and Doppler data derived from signals reflected from the Martian surface, taking advantage of the planet's nearness during opposition.

Taylor, R. M.↗

NASA NTRS2007

Decision Support Systems for Launch and Range Operations Using Jess

The virtual test bed for launch and range operations developed at NASA Ames Research Center consists of various independent expert systems advising on weather effects, toxic gas dispersions and human health risk assessment during space-flight operations. An individual dedicated server supports each expert system and the master system gather information from the dedicated servers to support the launch decision-making process. Since the test bed is based on the web system, reducing network traffic and optimizing the knowledge base is critical to its success of real-time or near real-time operations. Jess, a fast rule engine and powerful scripting environment developed at Sandia National Laboratory has been adopted to build the expert systems providing robustness and scalability. Jess also supports XML representation of knowledge base with forward and backward chaining inference mechanism. Facts added - to working memory during run-time operations facilitates analyses of multiple scenarios. Knowledge base can be distributed with one inference engine performing the inference process. This paper discusses details of the knowledge base and inference engine using Jess for a launch and range virtual test bed.

Thirumalainambi, Rajkumar↗

NASA NTRS2021

Thunderstorm and Fair-weather Quasi-Static Electric Fields Over Land and Ocean

Natural lightning and the associated clouds are known to behave differently over land and ocean, but many questions remain. We expand the related observational datasets by obtaining simultaneous quasi-static electric field observations over coastal land, near-shore water, and deep ocean regions during both fair-weather and thunderstorm periods. Oceanic observations were obtained using two 3-m NOAA buoys that were instrumented with Campbell Scientific electric field mills to measure the quasi-static electric fields. These data were compared to selected electric field records from the existing on-shore electric field mill suite of 31 sensors at Kennedy Space Center (KSC). Lightning occurrence times, locations and peak current estimates for both onshore and ocean were provided by the U.S. National Lightning Detection Network. The buoy instruments were first evaluated on-shore at the Florida coast, and the first system was calibrated for field enhancements and to confirm proper behavior of the system in elevated-field environments. The buoys were then moored 20 mi and 120 mi off the coast of KSC in February (20 mi) and August (120 mi) 2014. Diurnal fair-weather fields at both ocean sites matched will with each other and with those found during the Carnegie cruise, but mean values were 33% smaller, due at least in-part to constraints on the calibration procedure. Diurnal fair-weather fields variations at coastal and inland sites were a poorer match than offshore, likely because the offshore environment is “cleaner” with limited variations in local space charge, lower surface aerosol densities, little surface heating to disturb the surface charge layer during fair weather, and fewer local radioactive sources to modulate the near-surface electrical conductivity. Storm-related static fields were 4-5× larger at both oceanic sites than over land, likely due to decreased screening by near-surface space charge produced by corona current. The time-evolution of the electric field and field changes during storm approach are sufficiently different over land and ocean to warrant further study. This work shows the quality, accuracy, and reliability of these data, and has demonstrated the practicality of off-shore electric field measurements for safety- and launch-related decision making at KSC.

Lightning↗

NASA NTRS1988

Data system overview

The data system architecture design philosophy for 'SFOC', which is a large-scale distributed system for support of current and future space missions at the JPL, stresses 'design for change' standardization that will permit software-reuse, periodic hardware-changeout, and network-configuration evolution. Multimission capabilities are supported through a buildup of the baseline system with a minimum of special-purpose adaptations. SFOC can accommodate multiple users representing multiple disciplines, and is capable of furnishing near-real time and nonrealtime support to end-users for downlink (telemetry) and uplink (command) functions.

Kahr, Joseph R.↗

NASA NTRS2007

Advances in Ground Transmitters for the NASA Deep Space Network

The Deep Space Network (DSN), managed by the Jet Propulsion Laboratory for NASA, is equipped with multiple microwave transmitters ranging in average radiated power from 200 W to 400 kW. The transmitters are used for routine or emergency communication with spacecraft, for navigation, and for radio science tasks. The latest advances in transmitter engineering were implemented in a new generation of 20-kW dual-band transmitters developed for the DSN 34-m beam waveguide antennas. Innovations include additional X-band communication capability for near Earth missions, new control algorithms, automated calibration, improved and expanded computerized monitoring and diagnostics, reduced cabling, and improved maintainability. The innovations were very beneficial for the DSN 'overload' during the Mars 2003/2004 missions and will benefit other missions throughout the next decade. This paper describes the current design of the new transmitters and possible future developments.

microwaves↗

NASA NTRS2018

NASA Kennedy Space Center: Contributions to Sea Turtle Science and Conservation

The National Aeronautics and Space Administration (NASA) is a United States (US) federal agency that oversees US space exploration and aeronautical research. NASA's primary launch site, Kennedy Space Center (KSC) is located along the east coast of Florida, on Cape Canaveral and the western Atlantic Ocean. The natural environment within KSC's large land boundaries, not only functions as an extensive safety buffer-area, it performs simultaneously as a wildlife refuge and a national seashore. In the early 1960s, NASA was developing KSC for rocket launches and the US was establishing an awareness of, and commitment to protecting the environment. The US began creating regulations that required the consideration of the environment when taking action on federal land or with federal funds. The timing of the US Endangered Species Act (1973), the US National Environmental Policy Act (1972), coincided with the planning and implementation of the US Space Shuttle Program. This resulted in the first efforts to evaluate the impacts of space launch operation operations on waterways, air quality, habitats, and wildlife. The first KSC fauna and flora baseline studies were predominantly performed by University of Central Florida (then Florida Technological University). Numerous species of relative importance were observed and sea turtles were receiving regulatory review and protection as surveys by Dr. L Ehrhart (UCF) from 1973-1978 described turtles nesting along the KSC beaches and foraging in the KSC lagoon systems. These data were used in the first NASA Environmental Impact Statement for the Space Transportation System (shuttle program) in 1980. In 1982, NASA began a long term ecological monitoring program with contracted scientists on site. This included efforts to track sea turtle status and trends at KSC and maintain protective measures for these species. Many studies and collaborations have occurred on KSC over these last 45 years with agencies (USFWS, NOAA, NAVY), students, and universities (UCF, University of Toronto, Texas A&M, UF). This presentation will review the various studies and collaborations on sea turtles at KSC that include: nest distributions and success, stranding network development, aerial survey testing for nest counts, predator control assessments, the earliest baseline blood chemistry health determinations on nesting females, stress hormones in nesting females, multi-year study of hatchling sex ratios, genetics, species composition, abundance and distribution of in-water juveniles, turtle cold stun response, exterior lighting impacts and control, and satellite tag tracking of post-nesting turtles in the vicinity of near shore shoals and sand mining sites. Through these studies, monitoring, and recommendations, KSC has provided excellent stewardship and protection of the local environment. While conducting its space program mission, KSC has also made significant contributions of information for agencies charged with the conservation and management of these species

Provancha, Jane A.↗