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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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642 records · Page 13
All sourcesNASA NTRSDOE OSTI
NASA NTRS1992

Effect of Microgravity on Several Visual Functions During STS Shuttle Missions

Many astronauts and cosmonauts have commented on apparent changes in their vision while on-orbit. Comments have included statements of supposed improved distance acuity to decreased near vision capability. The purpose of this study was to assess not only changes in visual acuity, but expand the assessment to several other visual functions for a comprehensive battery of tests. Vision was assessed using an innovative device, the Visual Function Tester - Model 1 (VFT-1), which presents the tests at optical infinity and includes critical flicker fusion, stereopsis to 10 seconds-of-arc, visual acuity in small steps to 20/7.7, cyclophoria, lateral and vertical phoria, and retinal rivalry. Vision was assessed 2 times prelaunch at L-14 days and L-7 days, 3-4 times while on-orbit, at landing, and 2 times postlanding at L+3 days and L+7 days. There were 26 STS astronauts that participated, with data on 20 astronauts used for analysis. There was a typical wide variability between subjects in baseline visual performance for each parameter at the prelaunch sessions. There was a slight but statistically significant decrease in visual acuity while on-orbit that was not clinically significant. For stereopsis (i.e. depth perception), there was a small improvement on-orbit that was not statistically significant. There were no changes during space flight for any of the other visual parameters tested. A few individuals showed apparent changes in acuity and stereopsis. The possibility exists that microgravity affects the visual system of some individuals differently, as with space adaptation syndrome. Repeat data on 2 astronauts showed good repeatability between the 2 flights. These results pertain to only short term space flight on the STS shuttle, and longer flights are necessary to determine if there is any relationship between mission duration and these visual functions.

Melvin R O'Neal↗
DOE OSTI2026

High-Throughput Uniformity and Defect Monitoring in Low-Temperature Electrolysis Porous Transport Layers Using X-Ray Radiography

Effective quality control (QC) for manufacturing proton exchange membrane water electrolysis (PEMWE) components is critical to enabling widespread adoption of the technology for hydrogen generation. This study investigates X-ray radiography as a novel, high-throughput, potentially in-line QC technique for detecting defects and assessing material property distributions in titanium-based porous transport layers (PTLs) which constitute a crucial component of low temperature PEMWE stacks. We obtain radiographs of a set of fifteen PTLs and model their absorbance of the broadband radiation as a second-order polynomial to account for the non-monoenergetic radiation source used in this study. The resulting model serves as a basis for predicting the areal density and porosity distributions of the PTLs. We find radiography successful in detecting multiple instances of defects, including holes/depressions, cracks, and excess material on the surface or in the pores of the material, demonstrating its potential as a robust in-line QC tool for PTL manufacturing.

08 HYDROGEN↗
NASA NTRS2026

Spacecraft Disposal Rosetta Stone: Parametric Tool for Orbital Lifetime, Disposal, and Cost Assessment

This Technical Memorandum documents a simplified, parametric method for evaluating spacecraft orbital lifetime, disposal compliance, and disposal-related cost impacts during early mission formulation and preliminary design. The method captures the dominant drivers of orbital decay—effective ballistic coefficient, operating altitude, and solar-cycle variability—using conservative bounding assumptions. Solar maximum conditions are used to bound achievable mission lifetime, while solar minimum conditions are used to bound disposal timelines and compliance with orbital debris requirements. A single tabulated dataset provides orbital lifetime under both solar-cycle extremes together with representative disposal ΔV required to ensure compliant disposal, enabling rapid assessment of disposal feasibility, cost sensitivity, and system-level impacts prior to committing to higher-fidelity analyses.

Orbital debris mitigation↗
NASA NTRS1977

Research on battery-operated electric road vehicles

Mathematical analysis of battery-operated electric vehicles is presented. Attention is focused on assessing the influence of the battery on the mechanical and dynamical characteristics of dc electric motors with series and parallel excitation, as well as on evaluating the influence of the excitation mode and speed control system on the performance of the battery. The superiority of series excitation over parallel excitation with respect to vehicle performance is demonstrated. It is also shown that pulsed control of the electric motor, as compared to potentiometric control, provides a more effective use of the battery and decreases the cost of recharging.

Varpetian, V. S.↗
DOE OSTI2025

Dimensional Evolution Guides Property Control in the A n Cu 4– n TiS 4 Semiconductor Series

Through progressive reduction of the three-dimensional (3D) covalent network of Cu 4 TiS 4 , we isolate seven new members of the A n Cu 4–n TiS 4 family (A = alkali metal; n = 0–4), spanning 3D, 2D, 1D, and 0D structural fragments. The dimensional reduction is rational, as it preserves the edge-sharing connectivity between [CuS 4 ] 7– and [TiS 4 ] 4– tetrahedra across the series. This structural evolution is driven by the stepwise substitution of Cu with alkali metals, guiding the formation of fragments with reduced dimensionality. The effects of “n” and “A” on the crystal structures, stabilities, electronic structures, and optoelectronic properties are profound, demonstrating that the manipulation of alkali metal size and A n Cu 4–n TiS 4 stoichiometry enables predictable variations in structure and properties. For example, the n = 0 and n = 4 end members of the A n Cu 4–n TiS 4 family set the range of achievable band gaps with 2.00 eV for Cu 4 TiS 4 , 2.60 eV for Na 4 TiS 4 , and intermediate values for the n = 1–3 members. Notably, CsCu 3 TiS 4 exhibits exceptional air stability and congruent melting, with density functional theory (DFT) calculating moderate hole and electron effective masses in specific crystallographic directions (mh = 1.24m 0 , me = 0.87m 0 ). Additionally, A 3 CuTiS 4 (A = Na, K, Rb) displays direct band gap behavior and long photoluminescence lifetimes of 2.3–8.6 μs, and K 3 CuTiS 4 has a PLQY of 5.19%. These findings underscore the potential of the A n Cu 4–n TiS 4 family for applications in optoelectronics and demonstrate widely applicable design concepts that unveil rational stoichiometries within a given composition space to generate a series of crystal structures related through an evolving covalent dimensionality that corresponds to a predictable electronic structure and property progression.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS2012

Analysis of Screen Channel LAD Bubble Point Tests in Liquid Methane at Elevated Temperature

This paper examines the effect of varying the liquid temperature and pressure on the bubble point pressure for screen channel Liquid Acquisition Devices in cryogenic liquid methane using gaseous helium across a wide range of elevated pressures and temperatures. Testing of a 325 x 2300 Dutch Twill screen sample was conducted in the Cryogenic Components Lab 7 facility at the NASA Glenn Research Center in Cleveland, Ohio. Test conditions ranged from 105 to 160K and 0.0965 – 1.78 MPa. Bubble point is shown to be a strong function of the liquid temperature and a weak function of the amount of subcooling at the LAD screen. The model predicts well for saturated liquid but under predicts the subcooled data.

Reaction Control System↗
NASA NTRS1990

A Laboratory Breadboard System for Dual-Arm Teleoperation

The computing architecture of a novel dual-arm teleoperation system is described. The novelty of this system is that: (1) the master arm is not a replica of the slave arm; it is unspecific to any manipulator and can be used for the control of various robot arms with software modifications; and (2) the force feedback to the general purpose master arm is derived from force-torque sensor data originating from the slave hand. The computing architecture of this breadboard system is a fully synchronized pipeline with unique methods for data handling, communication and mathematical transformations. The computing system is modular, thus inherently extendable. The local control loops at both sites operate at 100 Hz rate, and the end-to-end bilateral (force-reflecting) control loop operates at 200 Hz rate, each loop without interpolation. This provides high-fidelity control. This end-to-end system elevates teleoperation to a new level of capabilities via the use of sensors, microprocessors, novel electronics, and real-time graphics displays. A description is given of a graphic simulation system connected to the dual-arm teleoperation breadboard system. High-fidelity graphic simulation of a telerobot (called Phantom Robot) is used for preview and predictive displays for planning and for real-time control under several seconds communication time delay conditions. High fidelity graphic simulation is obtained by using appropriate calibration techniques.

A K Bejczy↗
NASA NTRSDate not supplied

Harness Thermal Heat Loss Measurement for a Lunar Surface-Deployed LEMS Artemis III Payload

The Lunar Environment Monitoring Station (LEMS) is an autonomous, survive-the-lunar-night seismic suite to be deployed on the Lunar surface by the Artemis III crew and designed to operate continuously for two years. It will see the extremes of the Lunar south pole thermal environment where surface temperatures range from -200°C to +20°C and where nighttime duration is at least 354 hours. Given power and mass constraints, the thermal system is limited to 2.5 Watts of heat during the lunar night. The electrical harnessing named the Signal and Power Passthrough (SAPP) was designed to minimize heat loss while meeting power and signal integrity requirements. To mitigate risk due to uncertainty associated with the harnessing materials, routing, and tie-downs, a flight-like thermal conductance test was performed to measure the heat loss. The test methodology, results, and model correlation are presented.

TVAC↗
NASA NTRSDate not supplied

Harness Thermal Heat Loss Measurement for A Lunar Surface-Deployed LEMS Artemis III Payload

The Lunar Environment Monitoring Station (LEMS) is an autonomous, survive-the-lunar-night seismic suite to be deployed on the Lunar surface by the Artemis III crew and designed to operate continuously for two years. It will see the extremes of the Lunar south pole thermal environment where surface temperatures range from -200°C to +20°C and where nighttime duration is at least 354 hours. Given power and mass constraints, the thermal system is limited to 2.5 Watts of heat during the lunar night. The electrical harnessing named the Signal and Power Passthrough (SAPP) was designed to minimize heat loss while meeting power and signal integrity requirements. To mitigate risk due to uncertainty associated with the harnessing materials, routing, and tie-downs, a flight-like thermal conductance test was performed to measure the heat loss. The test methodology, results, and model correlation are presented.

Thermal↗
NASA NTRSDate not supplied

Harness Thermal Heat Loss Measurement for A Lunar Surface-Deployed LEMS Artemis III Payload

The Lunar Environment Monitoring Station (LEMS) is an autonomous, survive-the-lunar-night seismic suite to be deployed on the Lunar surface by the Artemis III crew and designed to operate continuously for two years. It will see the extremes of the Lunar south pole thermal environment where surface temperatures range from -200°C to +20°C and where nighttime duration is at least 354 hours. Given power and mass constraints, the thermal system is limited to 2.5 Watts of heat during the lunar night. The electrical harnessing named the Signal and Power Passthrough (SAPP) was designed to minimize heat loss while meeting power and signal integrity requirements. To mitigate risk due to uncertainty associated with the harnessing materials, routing, and tie-downs, a flight-like thermal conductance test was performed to measure the heat loss. The test methodology, results, and model correlation are presented.

TVAC↗
DOE OSTI2026

Testing and Validation of Wireless Communication Architecture for Heliostat Fields: SIPS Final Report

This work focuses on the development and testing of a low-cost wireless communication system for heliostat fields, enabling significant capital costs reductions for concentrating solar thermal systems. Outputs of this work include a working demonstration of a multi-node communication system, clear reporting of system performance, and technical documentation of system development and architecture for reproducibility. Through this process, an open-source repository was created for manufacturing hardware at ~$30/heliostat. The system includes software for cybersecurity, achieving sub-second communication latencies and derisking of hardware for eventual scale-up to tens of thousands of heliostats. While the system is not currently off-the-shelf ready, there is now a clearly defined pathway for scaling up and completing the commercial development process.

14 SOLAR ENERGY↗
NASA NTRSDate not supplied

Physics-Guided Deep Learning for Complex System Health Management and Decision Making

The landscape of complex engineered systems is rapidly evolving, from smart manufacturing facilities to next-generation transportation vehicles. As these systems become increasingly sophisticated and interconnected, the need for advanced health management systems grows ever more critical. These systems must go beyond simple monitoring, actively predicting potential failures before they occur. This paradigm shift from fixed maintenance schedules to condition-based predictions is key to optimizing system performance, enhancing safety, and paving the way for autonomous decision-making across various industries. Whether in industrial processes, energy systems, or advanced transportation, the ability to anticipate and prevent failures is becoming a cornerstone of operational excellence. To accurately predict the future health of any complex system, knowledge of its current health state and future operational conditions is essential. Recent advancements in data-driven algorithms have generated growing interest in artificial intelligence for industrial applications. However, the limitations of pure data-driven methods, particularly in industries where data acquisition is costly and limited, have become apparent. This has led to a focus on blending physics with data-driven algorithms, mitigating the drawbacks of both approaches while emphasizing their respective advantages. This research proposes a novel framework for integrating physics-based performance models with deep learning algorithms for the prognostics of complex safety-critical systems. In this approach, physics-based models serve as a blueprint, capturing fundamental system behaviors, while deep learning algorithms, leveraging real-world sensor data, fill in gaps and identify subtle patterns indicative of potential problems. This hybrid methodology, utilizing techniques such as Physics-Informed Neural Networks (PINNs), offers a powerful solution for predicting system health. By fusing domain knowledge with data-driven insights, this approach promises more accurate, adaptable, and reliable models for health prediction. The resulting framework is versatile, applicable across various sectors including aerospace, manufacturing, and energy systems, ultimately contributing to safer, more efficient operations in our increasingly complex technological landscape.

Diagnostics↗
NASA NTRS2026

Development and Validation of a High-Vacuum Thermal Conductivity Testbed for Aerospace Interface Materials

Thermal Interface Materials (TIMs) are critical components in spacecraft thermal management systems, where thermal performance is strongly influenced by vacuum conditions, interface contact resistance, and layered metallic joint behavior. However, manufacturer-reported thermal conductivity values are often derived under idealized conditions and may not accurately represent performance within operational aerospace applications. To address this limitation, the Testbed for Advanced Interface Materials in Vacuum (TAIMV) was developed as a modular vacuum-compatible thermal conductivity characterization platform capable of evaluating aerospace-relevant TIM configurations under both ambient and high-vacuum environments. The testbed was derived from the ASTM C1044-16 guarded hot plate methodology and incorporates interchangeable layers of stainless steel coupon geometries, independently controlled main and guard heaters, embedded resistance temperature detectors (RTDs), thermocouples, multi-layer insulation (MLI), and a temperature-controlled cold plate to characterize through-thickness thermal gradients across layered interfaces. In the current configuration, interface compression is limited to the nominal contact pressure generated by the experimental stack assembly. Initial experimental campaigns were conducted at ambient pressure and below 1×10-5 torr for vacuum cases using multiple interface materials including Braycote 601EF and Krytox-based greases across a range of thermal operating conditions. In parallel, a coupled numerical Python thermal model was developed to predict temperature distribution throughout the stack while accounting for conduction, radiation, and parasitic heat transfer pathways and effective interface resistance effects. Experimental measurements and numerical predictions showed consistent thermal trends across multiple operating conditions and environmental states. Results also revealed measurable differences between ambient and vacuum thermal behavior, demonstrating the importance of interface resistance, parasitic heat transfer mechanisms, and stack geometry in determining effective thermal performance within layered thermal interfaces. The presented work establishes a foundation for future thermal model correlation efforts and expanded characterization of aerospace thermal interface materials under representative environmental conditions. Future work will focus on the integration of a load cell system to enable controlled pressure-dependent characterization of thermal interface materials under compressive loading. This capability will allow investigation of the influence of contact pressure on effective thermal conductivity, interface resistance, and thermal performance within layered aerospace thermal interfaces under representative operational conditions.

Thermal Development Testing↗
DOE OSTI2025

Carbon Utilization and Storage Partnership of the Western United States

This technical report documents research conducted under DOE Award No. DE-FE0031837 focused on evaluating the feasibility of carbon capture, utilization, and storage (CCUS) systems in the central and western United States. The project integrated geologic characterization, reservoir simulation, infrastructure modeling, and economic analysis to assess CO₂ storage potential near industrial sources and develop strategies for transport and sequestration. The work included subsurface modeling, risk assessment, monitoring and verification (MRV) planning, and evaluation of regulatory pathways such as EPA Underground Injection Control (UIC) Class VI permitting and IRS 45Q tax credit eligibility. Results demonstrate the viability of multiple storage approaches, including saline formations, enhanced coalbed methane recovery, and basalt mineralization, supported by data-driven workflows and regional analyses. The project also produced permitting templates, technology transfer activities, and stakeholder engagement efforts to support deployment readiness. These findings contribute to the development of scalable, economically viable CCUS systems and provide a repeatable framework for future carbon management projects.

20 FOSSIL-FUELED POWER PLANTS↗
NASA NTRS2001

Performance of Li-Ion Cells Under Battery Voltage Charge Control

A study consisting of electrochemical characterization and Low-Earth-Orbit (LEO) cycling of Li-Ion cells from three vendors was initiated in 1999 to determine the cycling performance and to infuse the new technology in the future NASA missions. The 8-cell batteries included in this evaluation are prismatic cells manufactured by Mine Safety Appliances Company (MSA), cylindrical cells manufactured by SAFT and prismatic cells manufactured by Yardney Technical Products, Inc. (YTP). The three batteries were cycle tested in the LEO regime at 40% depth of discharge, and under a charge control technique that consists of battery voltage clamp with a current taper. The initial testing was conducted at 20 C; however, the batteries were cycled also intermittently at low temperatures. YTP 20 Ah cells consisted of mixed-oxide (Co and Ni) positive, graphitic carbon negative, LIPF6 salt mixed with organic carbonate solvents. The battery voltage clamp was 32 V. The low temperature cycling tests started after 4575 cycles at 20 C. The cells were not capable of cycling. at low temperature since the charge acceptance at battery level was poor. There was a cell in the battery that showed too high an end-of-charge (EOC) voltage thereby limiting the ability to charge the rest of the cells in the battery. The battery has completed 6714 cycles. SAFT 12 Ah cells consisted of mixed-oxide (Co and NO positive, graphitic carbon negative, LiPF6 salt mixed with organic carbonate solvents. The battery voltage clamp was for 30.8 V. The low temperature cycling tests started after 4594 cycles at 20 C. A cell that showed low end of discharge (EOD) and EOC voltages and three other cells that showed higher EOC voltages limited the charge acceptance at the selected voltage limit during charge. The cells were capable of cycling at 10 C and 0 C but the charge voltage limit had to be increased to 34.3 V (4.3 V per cell). The low temperature cycling may have induced poor chargeability since the voltage had to be increased to achieve the required charge input. The battery has completed 6226 cycles. MSA 10 Ah cells consisted of Co oxide positive, graphitic carbon negative, LiPF6 salt mixed with organic carbonate solvents. The battery voltage clamp was 30.8 V. The low temperature cycling tests were started after 2182 cycles at 20 C. The cells were capable of cycling at 10 C and 0 C. Like SAFT, the voltage limit on charge had to be increased to 36 V (4.5 V per cell). There was a cell (cell S/N 13) in the battery that showed poor performance features such as low EOD voltage and high EOC voltage. The battery has completed 3441 cycles. A reconditioning procedure that consisted of C15 charge to a taper current of C/100 and C/20 discharge improved the voltage behavior of SAFT and MSA cells with no significant effect on YTP cells. We have demonstrated that the charge operation with VT clamp at battery rather than at cell level is feasible for onboard Li-Ion battery operation.

Rao, Gopalakrishna M.↗
DOE OSTI2026

NanoPSD: A software for automatic detection of Nano-Particle Shape Distribution in electron microscopy images

Accurate quantification of the size and morphology of nanoparticles from electron microscopy (EM) images is essential to understand growth mechanisms, surface reactivity, and functional behavior in nanoscale materials. Manual analysis remains slow, subjective, and difficult to reproduce in large datasets. We introduce NanoPSD (Nano-Particle Shape Distribution), an open-source and fully automated framework for quantitative particle detection and morphology analysis from EM images. NanoPSD integrates adaptive contrast enhancement, polarity-agnostic scale-bar detection, Optical Character Recognition (OCR)-based calibration, and classical segmentation via Otsu thresholding with morphological refinement. Particle contours are used to extract geometric descriptors, including equivalent circular diameter, aspect ratio, circularity, and solidity, enabling automated classification into spherical, rod-like, and aggregate morphologies. The framework supports both single-image and batch processing, generating publication-quality visualizations, LaTeX-ready tables, and structured comma-separated values (CSV) datasets. As a demonstration, we applied NanoPSD to plasma-synthesized nanoparticle samples diagnosed via transmission electron microscopy (TEM). The code produced statistically robust size and morphology distributions spanning a few to tens of nanometers with minimal user supervision. The pipeline demonstrates high reproducibility and scalability, processing large image collections with consistent calibration and output formatting. Its modular design enables seamless integration of future deep-learning-based segmentation models, providing a pathway toward intelligent, data-driven electron microscopy analysis.

36 MATERIALS SCIENCE↗
DOE OSTI2026

PowerModelsGAT-AI: Physics-Informed Graph Attention for Multi-System Power Flow With Continual Learning

Solving the alternating current power flow equations in real time is essential for secure grid operation, yet classical Newton–Raphson solvers can be slow under stressed conditions. Existing graph neural networks for power flow are typically trained on a single system and often degrade on different systems. We present PowerModelsGAT-AI, a physics-informed graph attention network that predicts bus voltages and generator injections. The model uses bus-type-aware masking to handle different bus types and balances multiple loss terms, including a power-mismatch penalty, using learned weights. We evaluate the model on 14 benchmark systems (4 to 6,470 buses) and train a unified model on 13 of these under contingency conditions with up to two branch outages, achieving an average normalized mean absolute error of 0.89% for voltage magnitudes and R 2 >0.99 for voltage angles. We also show continual learning: when adapting a base model to a new 1,354-bus system, standard fine-tuning causes severe forgetting with error increases exceeding 1000% on base systems, while our experience replay and elastic weight consolidation strategy keeps error increases below 2% and in some cases improves base-system performance. Interpretability analysis shows that learned attention weights correlate with physical branch parameters (susceptance: r=0.38 ; thermal limits: r=0.22 ), and feature importance analysis supports that the model captures established power flow relationships.

24 POWER TRANSMISSION AND DISTRIBUTION↗