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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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1,070 records · Page 6

Laser Beam Welding Advancements for In-Space Servicing, Assembly, and Manufacturing

NASA is currently working to develop in-space servicing, assembly, and manufacturing (ISAM) capabilities for low Earth orbit and the lunar surface. One crucial technology for this effort is laser beam welding. Laser systems can perform joining, cleaning, cutting, and repair activities, which will enable the construction of large in-space structures that could not fit on a single launch vehicle, such as trusses for solar panels, radiators, or communications infrastructure. Multiple projects studying laser welding for space applications are currently underway at NASA Marshall Space Flight Center. One of these, the DIsk-Shaped Configurable and Modular vAcuum uNit (DISCMAN), is a compact vacuum chamber designed to support parameter development for laser welding in microgravity. It contains a rotating platen with weld samples made from aluminum, steel, and titanium, a high-power infrared laser, and integrated pumps for pulling vacuum inside the sample cartridge. The DISCMAN payload is planned to launch to the International Space Station, where welds will be performed under sustained microgravity inside the Bishop Airlock. Another effort underway at Marshall is the Lunar Assembly and Servicing by Autonomous Robotics (LASAR) initiative. This project uses a space-rated robotic arm equipped with a laser weld head, wire feeder, and multiple cameras to perform welds in a thermal vacuum chamber simulating the lunar surface environment. Some of these welds are done on snowflake joints, which are specially designed to slot together to join segments of trussN structures, allowing for the construction of tall surface infrastructure. DISCMAN, LASAR, and other projects are being carried out to advance the technological maturity of in-space laser beam welding, collect data to inform computational models, and learn reliable processes for creating weld joints in space. This work supports NASA’s greater goals to expand humanity’s presence in low Earth orbit, establish a permanent moon base, and eventually send crewed missions to Mars and beyond.

Robotics

Data Analysis for GOPEX Image Frames

This article describes the data analysis based on the image frames received at the Solid State Imaging (SSI) camera of the Galileo Optical Experiment (GOPEX) demonstration conducted between December 9 and 16, 1992. Laser uplink was successfully established between the ground and the Galileo spacecraft during its second Earth-gravity-assist phase in December 1992. SSI camera frames were acquired which contained images of detected laser pulses transmitted from the Table Mountain Facility (TMF), Wrightwood, California, and the Starfire Optical Range (SOR), Albuquerque, New Mex/co. Laser pulse data were processed using standard image-processing techniques at the Multimission Image Processing Laboratory (MIPL) for preliminary pulse identification and to produce public re/ease images. Subsequent image analysis corrected for background noise to measure received pulse intensities. Data were plotted to obtain histograms on a dmly basis and were then compared with theoretical results derived from applicable weak-turbulence and strong-turbulence considerations. This article describes processing steps and compares the theories with the experimented results. Quantitative agreement was found in both turbulence regimes, and better agreement would have been found, given more received laser pulses. Future experiments should consider methods to reliably measure low-intensity pulses, and through experimented planning to geometrically locate pulse positions with greater certainty.

B M Levine

Laser Beam Welding Advancements for In-Space Servicing, Assembly, and Manufacturing

NASA is currently working to develop in-space servicing, assembly, and manufacturing (ISAM) capabilities for low Earth orbit and the lunar surface. One crucial technology for this effort is laser beam welding. Laser systems can perform joining, cleaning, cutting, and repair activities, which will enable the construction of large in-space structures that could not fit on a single launch vehicle, such as trusses for solar panels, radiators, or communications infrastructure. Multiple projects studying laser welding for space applications are currently underway at NASA Marshall Space Flight Center. One of these, the DIsk-Shaped Configurable and Modular vAcuum uNit (DISCMAN), is a compact vacuum chamber designed to support parameter development for laser welding in microgravity. It contains a rotating platen with weld samples made from aluminum, steel, and titanium, a high-power infrared laser, and integrated pumps for pulling vacuum inside the sample cartridge. The DISCMAN payload is planned to launch to the International Space Station, where welds will be performed under sustained microgravity inside the Bishop Airlock. Another effort underway at Marshall is the Lunar Assembly and Servicing by Autonomous Robotics (LASAR) initiative. This project uses a space-rated robotic arm equipped with a laser weld head, wire feeder, and multiple cameras to perform welds in a thermal vacuum chamber simulating the lunar surface environment. Some of these welds are done on snowflake joints, which are specially designed to slot together to join segments of trussN structures, allowing for the construction of tall surface infrastructure. DISCMAN, LASAR, and other projects are being carried out to advance the technological maturity of in-space laser beam welding, collect data to inform computational models, and learn reliable processes for creating weld joints in space. This work supports NASA’s greater goals to expand humanity’s presence in low Earth orbit, establish a permanent moon base, and eventually send crewed missions to Mars and beyond.

Manufacturing

Should I stay or should I flow? An exploration of phase‐separated metallosupramolecular liquid crystal polymers

Abstract Dynamic liquid crystalline polymers (dLCPs) incorporate both liquid crystalline mesogens and dynamic bonds into a single polymeric material. These dual functionalities impart order‐dependent thermo‐responsive mechano‐optical properties and enhanced reprocessability/programmability enabling their use as soft actuators, adaptive adhesives, and damping materials. While many previous works studying dynamic LCPs utilize dynamic covalent bonds, metallosupramolecular bonds provide a modular platform where a series of materials can be accessed from a single polymeric feedstock through the variation of the metal ion used. A series of dLCPs were prepared by the addition of metal salts to a telechelic 2,6‐bisbenzimidazolylpyridine (Bip) ligand endcapped LCP to form metallosupramolecular liquid crystal polymers (MSLCPs). The resulting MSLCPs were found to phase separate into hard and soft phases which aids in their mechanical robustness. Variations of the metal salts used to access these materials allowed for control of the thermomechanical, viscoelastic, and adhesive properties with relaxations that can be tailored independently of the mesogenic transition. This work demonstrates that by accessing phase separation through the incorporation of metallosupramolecular moieties, highly processable yet robust MSLCP materials can be realized. This class of materials opens the door to LCPs with bulk flow behavior that can also be utilized as multi‐level adhesives.

Chemistry

Artemis Suit Material Optical Property Testing of Dust Exposed Fabrics

This paper highlights one aspect of NASA’s ongoing technology-infusion effort to design, fabricate, and test a next-generation outer shell fabric for a lunar Extravehicular Activity (EVA) space suit, a critical component of sustained lunar exploration. Managing thermal loads on the Moon is essential for astronaut safety and suit performance. The suit’s exterior fabric directly influences heat gain and loss through its optical properties: low solar absorptivity minimizes sunlight absorption, while high infrared emissivity aids radiative cooling. Lunar regolith complicates this balance. Its fine, abrasive particles possess unique optical behavior that can lower reflectivity and raise emissivity when embedded in or adhered to fabric surfaces, degrading thermal control and increasing the risk of overheating or cooling inefficiency. To quantify these effects, the Artemis Suit Materials (ASM) team measured solar absorptance and infrared emissivity of clean and dust-soiled Ortho Fabric, establishing beginning-of-life (BOL) and end-of-life (EOL) benchmarks. EOL conditions were simulated with a rotary tumbler abrasion process using lunar dust simulant and ceramic media to reproduce cumulative wear expected during surface operations. Tests also included unmodified fabrics and a fabric/film laminate system containing titanium dioxide to evaluate potential improvements in dust resistance and optical performance. Results from these evaluations provide critical insight into how lunar dust alters fabric thermal behavior and inform the design of bespoke suit materials that maintain required optical properties throughout mission life, supporting safe and effective long-duration EVA on the lunar surface.

Textile

Artemis Suit Material Optical Property Testing of Dust Exposed Fabrics

This paper highlights one aspect of NASA’s ongoing technology-infusion effort to design, fabricate, and test a next-generation outer shell fabric for a lunar Extravehicular Activity (EVA) space suit, a critical component of sustained lunar exploration. Managing thermal loads on the Moon is essential for astronaut safety and suit performance. The suit’s exterior fabric directly influences heat gain and loss through its optical properties: low solar absorptivity minimizes sunlight absorption, while high infrared emissivity aids radiative cooling. Lunar regolith complicates this balance. Its fine, abrasive particles possess unique optical behavior that can lower reflectivity and raise emissivity when embedded in or adhered to fabric surfaces, degrading thermal control and increasing the risk of overheating or cooling inefficiency. To quantify these effects, the Artemis Suit Materials (ASM) team measured solar absorptance and infrared emissivity of clean and dust-soiled Ortho Fabric, establishing beginning-of-life (BOL) and end-of-life (EOL) benchmarks. EOL conditions were simulated with a rotary tumbler abrasion process using lunar dust simulant and ceramic media to reproduce cumulative wear expected during surface operations. Tests also included unmodified fabrics and a fabric/film laminate system containing titanium dioxide to evaluate potential improvements in dust resistance and optical performance. Results from these evaluations provide critical insight into how lunar dust alters fabric thermal behavior and inform the design of bespoke suit materials that maintain required optical properties throughout mission life, supporting safe and effective long-duration EVA on the lunar surface.

space

Entanglement properties of SU(2) gauge theory

Understanding how isolated quantum systems thermalize is central to both fundamental physics and the development of quantum technologies. In this Perspective, we present recent and new results on thermalization in nonabelian gauge theory from exact real-time simulations of two-dimensional lattice models. We discuss tests of the eigenstate thermalization hypothesis, entanglement entropy dynamics, the absence of persistent non-thermal states, spectral signatures, and measures of quantum complexity. Our new results include a two-step thermalization process in localized regions and the role of higher gauge field representations. These findings suggest that thermalization in gauge theories may offer a test case for quantum advantage.

information theory and computation

Energy 101 - Wind [Slides]

The Energy 101: Wind presentation, developed for the Energy Technology Innovation Partnership Project (ETIPP), provides an overview of wind energy. It covers fundamental concepts, technologies, considerations, case studies, and additional resources.

17 WIND ENERGY

Online Prediction of Battery Discharge and Estimation of Parasitic Loads for an Electric Aircraft

Predicting whether or not vehicle batteries contain sufficient charge to support operations over the remainder of a given flight plan is critical for electric aircraft. This paper describes an approach for identifying upper and lower uncertainty bounds on predictions that aircraft batteries will continue to meet output power and voltage requirements over the remainder of a flight plan. Battery discharge prediction is considered here in terms of the following components; (i) online battery state of charge estimation; (ii) prediction of future battery power demand as a function of an aircraft flight plan; (iii) online estimation of additional parasitic battery loads; and finally, (iv) estimation of flight plan safety. Substantial uncertainty is considered to be an irremovable part of the battery discharge prediction problem. However, high-confidence estimates of flight plan safety or lack of safety are shown to be generated from even highly uncertain prognostic predictions.

Battery Discharge Prediction

Shuttle-Mir [Мир-Шаттл] Supplement

This is a companion to an illustrated history book with the same title. This set of electronic files includes the full text and images in the book, as well as additional material. Interviews, photographs, and biographies of the U.S. Astronauts, cosmonauts, and team members for the Shuttle-Mir Program are available. STS Mission Summaries for each mission involved can be viewed, including launch and landing details, crew lists, and mission highlights. Photographs and videos from each mission are included, as well as diagrams of different spacecraft, and computer-generated animations of the Mir deorbit, collision, and flyaround. Additional documents include mission status reports, published documents, news releases, personal letters, and oral histories. The experiments carried out on Mir are described, highlighting combustion and fluid physics research, life in microgravity, and research of the development of the solar system. The focus on improving space technology and planning for the International Space Station is explained. The main features of the book itself include: (1) Training and Operations; (2) Long Duration Psychology; (3) Bilingual Blues; and (4) Earth Observations.

Astronautics

Refractory-based thermal energy storage for industrial process heat: one-dimensional modeling, control, and optimization

The variable and weather-dependent output of wind and solar power plants present a substantial challenge for planning and operating electricity-systems, particularly in the absence of cost-effective and dispatchable energy storage technologies. This study investigates a high-temperature, electrically heated, refractory-based thermal energy storage (RTES) system that stores electrical energy as sensible heat in dense ceramic bricks over the 950–1800 °C range. The stored heat can be discharged as a controlled hot-gas stream for industrial heating, fuel substitution in high-temperature processes, or electricity generation. The main novelty is a comprehensive modelling, control, mapping, and optimization framework that integrates one-dimensional transient gas–solid heat transfer, fan-assisted discharge, bypass-flow regulation, reheating logic, fan-power evaluation, insulation-loss assessment, and genetic-algorithm-based design optimization. The model uses feedback from outlet temperature and delivered power to regulate discharge, while a two-stage genetic algorithm optimizes brick-channel geometry, gas-flow operation, and multilayer insulation thicknesses. Storage capacities below 50 MWh and discharge powers of 5–30 MW are analyzed to evaluate hold time, thermal delivery, fan-power penalty, heat loss, state-of-charge evolution, and indicative capital cost. Results demonstrate that optimized and well-insulated refractory-based thermal energy storage units can provide stable, efficient, and repeatable heat delivery over multiple discharge cycles. The generated performance and cost maps support modular refractory thermal energy storage as a practical option for large-scale integration of wind and solar generation and for high-temperature industrial process heat.

25 ENERGY STORAGE

Boron Coordination in Multicomponent Glasses: Analytical Models and Machine Learning With Uncertainty

Borosilicate glasses are extensively used in a variety of applications from kitchenware to nuclear waste immobilization due to the strong network formed by the Si-O-B bond that makes it resistant to chemical corrosion and gives it a low thermal expansion. Boron, however, exists in both trigonal BO3 and tetrahedral BO4 bonds in glass systems, which impacts the chemical durability and thermal resistance of the glass, amongst other properties. Boron coordination (N4), or the ratio of the amount of BO4 to BO3 within a glass, may aid in predicting these properties but is difficult to derive without experimental data due to the complexity of impacts from varied glass compositions and processing factors. For this reason, compositional models have been developed to predict boron coordination, but the models typically include a limited number of glass components. To help fill this gap in the models, in this work, a diverse multicomponent glass dataset of 809 glasses is compiled from a literature search, and then a number of analytical and machine learning (ML) models are trained on the dataset. Previously developed modified Bernstein and modified Du Stebbins analytical models were fitted to update parameters with the new dataset. Then, partially Bayesian neural networks, Gaussian process regressor, and heteroskedastic deterministic neural networks were evaluated. The ML models examined all have different strategies to overcome the potential for overfitting as a result of a limited training dataset, and return results that account for model uncertainty, which can be valuable for understanding model reliability. For the first time, cooling rate is introduced as an input parameter for ML models, showing consistent improvements in performance and solidifying the importance of including parameters outside of composition alone for N4 prediction. The machine learning models examined here show promise in accurate predictions of boron coordination in borosilicate glasses, all achieving R2 values of 0.91.

boron coordination

Integration and Optimization of Loads, and Renewables for Grid-Interactive Efficient Buildings

Deploying advanced building control strategies in small- and medium-sized commercial buildings (SMBs) is critical but constrained by two major challenges: (1) the lack of sensor and control infrastructure (SCI) and (2) the significant engineering effort required for implementation and configuration. While these barriers limit large-scale adoption in SMBs, they remain underexplored in the literature, which has largely emphasized feasibility over scalability.

25 ENERGY STORAGE

Considerations for Maritime Nuclear Technologies, Economic Viability and Public Acceptance

The Maritime Nuclear Application Group (MNAG) is a working group convened by the National Reactor Innovation Center at Idaho National Laboratory (INL), the American Bureau of Shipping, and Morgan, Lewis, and Bockius LLP. This report documents an MNAG examination of considerations relevant to implementing nuclear technology in commercial maritime applications. In general, two types of use case are examined: maritime nuclear power plants and nuclear reactors used on board shipping vessels for propulsion and other ship needs. The report finds that there may be economic benefits related to maritime nuclear technologies, including the flexible deployment of maritime nuclear reactors, which would allow them to complement land-based nuclear projects, and operational differences for nuclear cargo ships that may lead to an overall increase in revenue. High-level analyses in this report show that, based on general small modular reactor and microreactor cost estimates developed by INL, maritime nuclear reactors may be economically competitive for electricity production in remote regions and for use in the propulsion of large cargo ships. Besides economic viability, public acceptance will be key to implementing maritime nuclear technologies. The report discusses the public’s current perception of nuclear technologies. Engaging with the public will be important to improving this perception. The report discusses some key benefits and risks associated with maritime nuclear technologies. Benefits include the creation of jobs, the production of reliable energy, and the potential to improve air quality. Risks that concern the public are the potential for radioactive releases during operation and decommissioning, as well as those related to waste management. Communicating the benefits and the risks of maritime nuclear technologies will be essential to improving public perception.

22 - GENERAL STUDIES OF NUCLEAR REACTORS

Parameterization of Nuclear Electric Propulsion Trajectories for Outer Solar System Science Missions Methodology

This manuscript addresses the methodology used to create a database of low thrust missions to outer planets. This database utilizes previous work modeling NEP systems to determine the maximum delivered mass to outer planets based on a range of mission parameters, such as time of flight, launch vehicle, and power system mass. Trajectories were selected which best utilized NEP benefits. Additionally, a discussion on the database outputs for missions to Saturn is included, such as time of flight based on trajectory type and maximum payload, given a specific launch vehicle. The purpose of this work was to create a basis for future mission design, and a tool to investigate general trends across mission options.

Outer Planets

Flight Testing

It is considered by the Flight Mechanics Panel of AGARD as vitally important that the NATO flight test community meet regularly so that new techniques for flight test, instrumentation and data analysis and lessons learned from past and on-going programs be disseminated to ensure that safe efficient cost-effective and timely testing is accomplished. There are many new systems being tested or planned for testing in the near future. These include programmable signal processor radars, integrated flight, fire and propulsion control systems, thrust vectoring, low observable technologies, multifunction pilot displays and multisensor integration. Acquisition and processing of large quantities of avionics multiplex data are challenges that must be met. There is a need for greater use of simulators and other hardware-in-the-loop ground test facilities.

Source record

Roadmap and Benchmarking: Privacy in Federated Load Forecasting

Data-driven techniques for energy demand forecasting continue to emerge with promising impacts on distribution grid planning. However, the development of robust and generalizable machine learning models requires that representative high quality training data are available. Distributed energy resources have begun to embed intelligence, gathering large amounts of data on customer demand, behavior, and household devices that are connected to the grid. Though utilities aggregate meter-level demand data for load shaping, demand response, outage management, reliability planning, and billing applications, there lies an inherent privacy concern in sharing consumption data that may identify individual consumer behavioral patterns. Hence, while sharing the data is crucial, the private sensitive customer data must be safeguarded from being exposed or manipulated. In this study, we propose a roadmap for implementing a based privacy preserving framework to support the advancement of data-driven analytics in data-sensitive distributed energy resources environments. The roadmap incorporates federated learning–a distributed training framework, differential privacy–a statistical framework that provides guarantees to safeguard the leakage of sensitive data, secure multiparty computation and homomorphic encryption– techniques for encrypting model gradients and applying secure aggregation on the server. Moreover, we perform baseline experiments on the federated short-term load forecasting (STLF) task using open-source residential load profile datasets, offering insights into the challenges of integrating differential privacy into federated learning.

Abebe, Waqwoya [Oak Ridge National Laboratory (ORN