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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 NTRS1992

NASA Aerospace Flight Battery Systems Program: An Update

The major objective of the NASA Aerospace Flight Battery Systems Program is to provide NASA with the policy and posture to increase and ensure the safety, performance, and reliability of batteries for space power systems. The program was initiated in 1985 to address battery problems experienced by NASA and other space battery users over the previous ten years. The original program plan was approved in May 1986 and modified in 1990 to reflect changes in the agency's approach to battery related problems that are affecting flight programs. The NASA Battery Workshop is supported by the NASA Aerospace Flight Battery Systems Program. The main objective of the discussions is to aid in defining the direction which the agency should head with respect to aerospace battery issues. Presently, primary attention in the Battery Program is being devoted to issues revolving around the future availability of nickel-cadmium batteries as a result of the proposed OSHA standards with respect to allowable cadmium levels in the workplace. The decision of whether or not to pursue the development of an advanced nickel-cadmium cell design and the qualification of vendors to produce cells for flight programs hinges on the impact of the OSHA ruling. As part of a unified Battery Program, the evaluation of a nickel-hydrogen cell design options and primary cell issues are also being pursued to provide high performance NASA Standards and space qualified state-of-the-art cells. The resolution of issues is being addressed with the full participation of the aerospace battery community.

Manzo, Michelle A.↗
NASA NTRS2025

Erosion Behavior of Ti-hBN Multifunctional Coatings in A Custom-Made Planetary Test Rig at Extreme Lunar Temperatures

Spacecraft landings and takeoffs on the lunar surface, along with extreme temperature variations between day and night (-196 to 150° C), cause high-velocity dust impacts and erosion, resulting in the premature failure of structures. Ti/2 vol% hBN coatings were deposited using atmospheric (APS) and vacuum plasma spray (VPS) using cryo-milled powder feedstock to protect the structural components. The erosion performance of coatings at extreme lunar temperature regimes (-150 to 150° C) was evaluated in a custom-made planetary erosion test rig (PETR) at low (50 mph) and high impact velocities (250 mph). The mass loss of VPS coatings was reduced by 50% compared to the APS coatings and 40% compared to the Ti6Al4V substrate. The cryogenic temperature induces brittleness in the material, rendering it susceptible to extreme conditions of material loss. The particle impact-deformation behavior was captured using a high-speed camera to study the erosion mechanism. This analysis revealed chipping in substrates and brittle APS coatings, while particles rebounding and embedding were observed in VPS coatings. Energy calculations, aided by particle trajectory tracking from the high-speed camera, have conclusively shown that VPS coatings absorb 5–10% more energy than APS coatings during erosion tests. A modified erosion index was developed incorporating the fracture toughness and temperatures. New erosion models for brittle and ductile target materials are proposed for developing erosion-resistant material systems.

Abhijith Kunneparambil Sukumaran↗
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 NTRS2004

Lunar and Planetary Science XXXV: Icy Worlds: Moving and Grooving

Reports from the conference session entitled Icy Worlds: Moving and Grooving, include:Mass Anomalies on Ganymede; Europan Chaos and Lenticulae: A Synthesis of Size, Spacing, and Areal Density Analyses; Thermal and Topographic Tests of Europa Chaos Formation Models; Flexure of Europa s Lithosphere Due to Ridge-Loading; Ridges on Europa: Origin by Incremental Ice-Wedging ; Convergent Boundaries on Europa: a Numerical Approach to Euler Pole Analysis and Its' Implications for Plate Reconstruction; Numerical Simulations of Subsolidus Convection in the Ice Shell of Europa: Implications for the Thermal Evolution and Present State; Effects of Plasticity on Convection in an Ice Shell: Implications for Europa; Non-Newtonian Convection and Compositional Buoyancy: Advances in Modeling Convection and Dome Formation on Europa; Convective Instability in Ice I: Application to Callisto and Ganymede; Crater Size Distributions on Callisto: A Galileo SSI Summary; Neutron Diffraction Studies of Planetary Ices; and H2O2 Synthesis Induced by Irradiation of H2O with Energetic H+ and Ar+ Ions at Various Temperatures.

Source record↗
NASA NTRSDate not supplied

First-Principles Investigation of Phase Transitions in RuNb, RuTa, and Ru-Nb-Ta Ultrahigh Temperature Shape Memory Alloys

Ultrahigh temperature shape memory alloys (UHT-SMAs) have transition temperatures above 600 C, and they have found applications for sensing and actuating devices in aerospace industry. Among very few such UHT-SMAs currently known are Ru-based alloys such as RuNb and RuTa, whose martensite structures and phase transitions are totally different from those of NiTi-based SMAs and were poorly understood. In this work, we carried out a systematical study of RuNb using first-principles total energy calculations and molecular dynamics (MD) simulations. The transition paths and mechanisms in cubic → tetragonal →monoclinic transitions are revealed. and the transition sequence and martensitic transition temperatures are determined (MTTs) by evaluating the Gibbs free energies using thermodynamic integration. The calculated MTTs are in very good agreement with the experimental data. We found that the monoclinic phase at the second transition has the 𝑃21/m symmetry instead of experimentally identified 𝑃2/m. Our calculations demonstrate that RuTa has very similar phase transitions to those of RuTa. Furthermore, we studied the Ru0.5Nb0.25Ta0.25 ternary. Our results can explain the measured significant drop of MTT (~ 200 C) in the second transition for Ru0.5Nb0.25Ta0.25 compared with those of RuNb and RuTa, while in the first transition its MTT is between MTTs of RuNb and RuTa. The insights gained by this study and the verified ab initio methods for accurate MTT calculations can be applied to fast screen and quantitatively design novel UHT-SMAs having similar properties with desirable MTTs and much reduced cost.

Zhigang Wu↗
NASA NTRS1992

Second LDEF Post-Retrieval Symposium Abstracts

These abstracts from the symposium represent the data analysis of the 57 experiments flown on the LDEF. The experiments include materials, coatings, thermal systems, power and propulsion, science, (cosmic ray, interstellar gas, heavy ions, micrometeoroids, etc.), electronics, optics, and life science.

Arlene S. Levine↗
NASA NTRS1980

NASA/Marshall's lithium battery applications

A general lithium battery is described and a summary of lithium battery applications is presented. Four aspects of a particular lithium battery, the inducement environmental contamination monitoring battery, are discussed-design and construction details, thermal vacuum tests, projection tests, and acceptance tests.

Paschal, L. E.↗
NASA NTRSDate not supplied

From Exploration Flight Test-1 to Artemis II--A NASA Langley's Orion Aerosciences Overview

The Orion Aerosciences program at NASA Langley has played a central role in advancing the aerodynamic and aeroheating prediction capabilities required for the Orion crew vehicle’s return from deep space. This presentation provides a technical overview of aerosciences contributions spanning Exploration Flight Test-1 (EFT-1), Artemis I, and the ongoing post-flight analysis of Artemis II. EFT-1 provided the first high-energy entry dataset for Orion, enabling critical validation of aerodynamic force and moment predictions, static and dynamic stability characteristics, and aeroheating environments at relevant flight Mach and Reynolds numbers. Flight-derived pressure data were used to refine the Flush Air Data System (FADS) methodology for atmospheric density reconstruction and to improve Best Estimated Trajectory (BET) solutions. The EFT-1 data also offered key insights into heat shield performance, including char layer recession, in-depth thermal response, and material retention behavior under flight conditions, informing updates to both thermal response models and uncertainty quantification practices. Building on EFT-1, Artemis I extended the database to true lunar-return conditions. Observations of heat shield performance, including localized char loss, bondline response, and recession variability, provided an unprecedented opportunity to reassess Thermal Protection System (TPS) and aeroheating modeling assumptions. Aerodynamic reconstruction efforts incorporated improved FADS calibration, enhanced atmospheric modeling, and refined force and moment databases to reduce trajectory and load uncertainties. Aeroheating comparisons between pre-flight predictions and flight data enabled targeted model updates, particularly in transitional flow environments and wake heating regions. For Artemis II, these lessons were systematically incorporated into the pre-flight prediction process. Updates included refined aerodynamic databases anchored to flight-validated corrections, improved density estimation and BET methodologies using enhanced database interpolation algorithm and FADS modeling, and revised aeroheating design environments informed by Artemis I material response observations. By the time of the workshop, Artemis II post-flight analysis will be underway, and preliminary findings will be presented where available, including early comparisons of aerodynamic reconstruction, atmospheric density estimation, and thermal protection system performance relative to updated predictions. Collectively, this body of work is a testament to the dedicated and multidisciplinary team whose sustained efforts have contributed to the program’s success and to the progressive maturation of Orion aerosciences modeling through numerical modeling, ground and flight data assimilation. The integrated advancement of aerodynamics, trajectory reconstruction, FADS-based density estimation, and aeroheating analysis has reduced predictive uncertainty and strengthened confidence for future crewed lunar and deep-space missions.

Orion↗
NASA NTRS2026

Spatially Refined Satellite Gravimetry Captures Human Signatures in Global Terrestrial Water Storage Trends

Human activities have directly altered the water cycle through water management, aquifer pumping, agricultural irrigation, and land use change. Although satellite gravimetry has transformed global hydrological research, its coarse resolution limits attribution of freshwater change to human activities at many management-relevant scales. Here we assessed global terrestrial water storage (TWS) trends from April 2002 to November 2025 using “stacked” regression of Level-1B intersatellite ranging data, which leverages temporal information and variability to dramatically improve effective spatial resolution relative to standard approaches. We combined this refined product with rigorous uncertainty analysis, autocorrelation-robust geostatistical methods, and literature assessment to evaluate TWS trend associations with land and water use, climate variability, and glacial mass loss. We identified TWS trend hotspots exhibiting significant spatial associations with anthropogenic 40 drivers, including groundwater and surface-water irrigation, rainfed agriculture, deforestation, and reservoir impoundment. Across these regions, cumulative TWS losses (3,122 Gt) substantially exceeded gains (2,432 Gt). Compared with traditional regression of monthly mascons, our approach yielded regional trend magnitudes that are on average 33% larger, revealing that global freshwater depletion, particularly from groundwater pumping, is considerably more acute than previously estimated. Multivariate regression models show that humans account for a significant share of the spatial variability in TWS trends on every non-polar continent except Australia. We detected localized TWS gains linked to rainfed agriculture, surface water irrigation, and reservoir filling that were unresolved in earlier gravimetric studies. The methodology provides a foundation for future gravity missions to independently track decadal freshwater change with unprecedented spatial fidelity.

groundwater↗
NASA NTRSDate not supplied

Predicting Team Functioning in Long Term Space Missions Using Acoustic and Linguistic Measures

Maintaining optimal team functioning is critical for long-duration space exploration missions, yet traditional monitoring methods, such as self-reports and wearable sensors, often impose operational burdens or suffer from bias. This paper investigates a non-intrusive speech-based artificial intelligence (AI) framework to predict degradations in team functioning using data from the Human Exploration Research Analog (HERA) of the U.S. National Aeronautics and Space Administration (NASA). Using acoustic features, linguistic descriptors, and semantic embeddings, we evaluate static non-linear and temporal machine learning models to predict both objective (task accuracy) and subjective (self-reported efficacy and cohesion) team functioning outcomes. Results indicate that temporal models outperform static approaches, with prediction of objective task accuracy in Team Interaction Battery (TIB) improving from near chance to 71%. Self-reported outcomes, including team efficacy and cohesion, are predicted more reliably than task performance, achieving balanced accuracies of up to 85.56% and 78.12%, respectively, and are found to be most strongly associated with acoustic features. In a second interdependent task, the MMSEV–EVA, accuracies of up to 78% are achieved using temporal models with acoustic features. Furthermore, incorporating just 1–2 days of team-specific historical data systematically improved performance, and acoustic markers from informal pre-task interactions provided modest predictive gains. Finally, while automated preprocessing yielded viable accuracy, humancorrected data provided moderate performance gains, though transcription error rates did not significantly correlate with model performance. These findings highlight the potential of speech as a passive, high-fidelity monitoring tool for autonomous habitats.

Temporal modeling↗
NASA NTRS1970

Development of a silver-zinc battery system

Summary report is described of historical documentation and detailed design data for development of silver-zinc battery for use on Surveyor spacecraft. Electrical and physical characteristics of battery models are included, along with data on qualification, acceptance, solar-thermal-vacuum, mission simulation testing, and actual flight performance.

Moses, A. J.↗
NASA NTRSDate not supplied

The Roman Space Telescope Optical System: Status, Test, and Verification Update

The Nancy Grace Roman Space Telescope (“Roman”) is NASA’s next flagship observatory. Launching in 2026, Roman will explore the nature of dark energy as well as expand the census of exoplanets in our galaxy via microlensing. Roman’s large field of view, agile survey capabilities, and excellent stability enable these scientific objectives, yet present unique challenges for the design, test, and verification of its optical system. Roman recently completed a comprehensive thermal vacuum test of the Spacecraft bus + Integrated Payload Assembly (SCIPA), followed by integrating the Outer Barrel Assembly (OBA), Solar Array Sunshield (SASS), and Deployable Aperture Cover (DAC) with SCIPA to complete the Observatory. This paper will present an overview of the thermal vacuum optical testing as well as a status of the optical system performance and verification.

Matthew Bolcar↗
NASA NTRS2024

Artemis I Orion ESM Propulsion System Engine Performance

NASA's Orion spacecraft transports humans and cargo into cislunar space for the Artemis program. The European Service Module (ESM), supplied by ESA and its European industry partners, provides Orion with power and in-space propulsion. The Orion-ESM propulsion system is a bipropellant hypergolic propulsion system using monomethyl hydrazine (MMH) and nitrogen tetroxide (MON-3). Primary translational propulsion is provided by the Orbital Maneuvering System Engine(OMS-E), with backup translational propulsion provided by eight Auxiliary thrusters (AUX). Attitude control and small translational maneuvers are provided by twenty four Reaction Control System (RCS) engines. The 2022 Artemis I mission was the first integrated flight test of the Orion-ESM spacecraft and its propulsion system. The OMS-E used on Artemis I was a refurbished Space Shuttle OMS-E that previously flew on nineteen missions ranging from STS-41G in 1984 to STS-112 in 2002. The Auxiliary engines are modified Aerojet Rocketdyne R4D-11 engines produced specifically for the Orion program. The RCS engines are Ariane Group engines originally used for the Automated Transfer Vehicle (ATV) program. This paper will discuss the unique operational requirements for each engine on Orion and the development and qualification effort sat both the engine and system-level that were completed to enable a successful Artemis I mission. Next the paper will evaluate the in-flight performance of the engines during the Artemis I mission showing nominal performance as expected. Additionally, comparisons to models will be presented showing very good correlation. Finally, the paper will address the plan for the engines on future Orion missions and the evolution of the system operation.

Liquid Propulsion Systems↗
NASA NTRS2024

Artemis I Orion ESM Propulsion System Engine Performance

NASA's Orion spacecraft transports humans and cargo into cislunar space for the Artemis program. The European Service Module (ESM), supplied by ESA and its European industry partners, provides Orion with power and in-space propulsion. The Orion-ESM propulsion system is a bipropellant hypergolic propulsion system using monomethyl hydrazine (MMH) and nitrogen tetroxide (MON-3). Primary translational propulsion is provided by the Orbital Maneuvering System Engine(OMS-E), with backup translational propulsion provided by eight Auxiliary thrusters (AUX). Attitude control and small translational maneuvers are provided by twenty four Reaction Control System (RCS) engines. The 2022 Artemis I mission was the first integrated flight test of the Orion-ESM spacecraft and its propulsion system. The OMS-E used on Artemis I was a refurbished Space Shuttle OMS-E that previously flew on nineteen missions ranging from STS-41G in 1984 to STS-112 in 2002. The Auxiliary engines are modified Aerojet Rocketdyne R4D-11 engines produced specifically for the Orion program. The RCS engines are Ariane Group engines originally used for the Automated Transfer Vehicle (ATV) program. This paper will discuss the unique operational requirements for each engine on Orion and the development and qualification effort sat both the engine and system-level that were completed to enable a successful Artemis I mission. Next the paper will evaluate the in-flight performance of the engines during the Artemis I mission showing nominal performance as expected. Additionally, comparisons to models will be presented showing very good correlation. Finally, the paper will address the plan for the engines on future Orion missions and the evolution of the system operation.

Reuse↗
NASA NTRS2026

Benchmarking Bayesian Optimization Frameworks and Acquisition Strategies for Materials Discovery and Autonomous Laboratories

Bayesian optimization (BO) can accelerate materials discovery by guiding expensive experiments toward the most promising processing conditions. We systematically compare five BO surrogate and framework combinations (Gaussian processes in Ax, Gaussian processes and Monte-Carlo neural networks in BayBE, random forests in Lolopy, and tree-structured Parzen (TPE) estimators in Hyperopt) on three benchmarks that mimic common materials design tasks (a discrete solid-electrolyte composition space, a hybrid discrete/continuous laminate-composite design problem solved with micromechanics modeling, and the continuous Ishigami analytic function which is a standard optimization benchmark). Each BO surrogate is paired with posterior mean, probability of improvement, and expected improvement acquisition functions and run for 100 trials from randomized initial samples with uniform random search providing a control. Across five random seeds per setting, BayBE’s Gaussian-process surrogate with expected improvement consistently reached ≥95 % of the known optimum in the fewest evaluations, while Lolopy’s random forest matched or exceeded GP performance on purely categorical or mixed spaces at a higher computational cost. Posterior mean alone often stagnated at local optima, underscoring the need for exploration, whereas probability and expected improvement balanced exploration and exploitation leading to better optimization in fewer trials. Execution times ranged from milliseconds for TPE to minutes for neural-network and random-forest surrogates. These results establish baseline expectations for BO in automated materials laboratories and highlight expected improvement with Gaussian processes as a reliable first choice, with random forests offering a strong alternative when categorical variables dominate. The benchmark suite and code are released to facilitate future surrogate, acquisition, and constraint-handling research in data-driven materials optimization.

Bayesian optimization↗
NASA NTRSDate not supplied

Numerical Investigation of Heat Transfer and Fluid Flow within Electrochemical Hydrogen Peroxide Generation Unit

Long-term manned space missions require the onboard production of disinfectants essential for maintaining crew health and supporting life systems. Currently, disinfection aboard the International Space Station (ISS) relies on disposable wetted wipes, which are regularly resupplied from Earth. This approach imposes a significant burden on resupply logistics, storage, and waste management. To address these challenges and support future missions, efforts are underway to develop an in-situ solution that electrochemically generates hydrogen peroxide disinfectant using onboard resources. In collaboration with NASA, Faraday Technology, Inc. has advanced this concept through a series of Small Business Innovation Research (SBIR) projects, resulting in the development of a Peroxide Generation Unit (PGU). The PGU can produce up to 3 wt.% hydrogen peroxide on-demand at a rate of 1 liter per day, providing a sustainable alternative to Earth-dependent supplies. The resulting aqueous hydrogen peroxide (H₂O₂) is an effective disinfectant, safe for crew use, compatible with spacecraft systems, and free from volatiles, off-gassing, or residues. This innovation offers a reliable, efficient solution for onboard disinfection, reducing dependence on Earth-based resupply while ensuring the health and safety of space crews. Generating hydrogen peroxide at the required rate needs high voltages and currents, exceeding 20V and 2A respectively, which leads to significant heat generation from Joule heating. This temperature rise poses a risk to sensitive system components, especially critical and expensive membranes that can degrade under thermal stress. To mitigate this risk, the thermal, fluid, and electrical flows within the system are modeled computationally using the commercial software COMSOL. The numerical simulations are validated against experimental data from both sub-scale and alpha-scale systems. Once verified, the model is employed to identify thermal hotspots, investigate their underlying causes, and explore solutions to prevent them.

Life Support Systems (LSS)↗