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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 NTRSDate not supplied

Fire-Resistant Textile Development for Exploration Vehicles With Enriched-Oxygen Cabin Environments

Material selection is a key part of the National Aeronautics and Space Administration (NASA) spacecraft fire safety management plan. Non-flammable textiles are necessary to ensure large-scale flame propagation events do not occur inside a spacecraft. An increased use of textiles and other softgood material is crucial to the pursuit of exploration spaceflight to reduce mass and volume. Exploration spaceflight missions benefit from enriched oxygen cabin environments (>21% O2) by allowing a reduced prebreathe protocol before Extravehicular Activity (EVA). However, materials become exponentially more flammable the higher the O2 levels become. Recent testing within the agency has revealed the lack of commercial-off-the-shelf (COTS) materials that can meet safety requirements in oxygen-enriched environments. Most of the fibers and textiles developed during Apollo (100% O2 cabin environment) and Skylab (>70% O2 cabin environment) are no longer commercially available due to those Programs ending and the discontinuation of raw materials or closure of the original manufacturers. As NASA returns to higher oxygen concentrations inside spacecraft, non-flammable textile development efforts have begun to meet the agency’s needs. This paper discusses those efforts including overall fire safety approach, priorities, interactions with industry, flammability testing and expected challenges.

Karim Aly↗
DOE OSTI2026

Toward an AI-Powered Software Pipeline for Real-Time Tracking and Analysis of Wildfire and Smoke

Real-time tracking of wildfires and smoke is crucial for effective response, minimizing damage, protecting lives, and efficiently managing resources during fire emergencies. We develop a web-based AI-powered pipeline that detects wildfires in aerial video and estimates deployment-relevant behavior metrics, including cumulative burned area, burned-area growth rate, fire spread direction, and smoke dispersion. The system combines a YOLO-based detector with YCbCr-based fire segmentation, HSV-based smoke segmentation, Farneback optical flow, and centroid-based spatiotemporal tracking. Using ground sampling distance (GSD), pixel-level fire masks are converted to physical burned-area measurements by correlating fire pixel counts with camera altitude and tilt angle. We benchmark YOLO variants and non-YOLO baselines (GoogLeNet, CNN, DBN, Autoencoder, U-Net, and AlexNet) on the IEEE FLAME dataset and a newly created aerial frame dataset, Wildfire-DB. Cross-dataset evaluation uses a strict threshold-transfer protocol: decision thresholds are selected on FLAME validation and transferred unchanged to Wildfire-DB to quantify generalization under domain shift. YOLOv6 achieves the strongest cross-dataset frame-level fire detection on Wildfire-DB (ROC-AUC 0.8200, PR-AUC 0.8044, and transferred-threshold F1 0.7596). For tracking-oriented deployment requiring oriented localization, YOLO11-OBB provides the most reliable cross-dataset behavior among OBB-capable models while remaining computationally feasible. To analyze the feasibility of UAV deployment, we further measure inference efficiency using synchronized GPU and CPU power logs on a fixed workload of 1569 frames. YOLO-family models process the video in 5.73–12.47 seconds with net energy of 1247.28–1775.39 J, substantially lower latency and energy than heavier classification and reconstruction baselines. Overall, model optimality depends on operational objectives: YOLOv6 is best for cross-dataset detection robustness, whereas YOL...

Color segmentation↗
DOE OSTI2026

Optical Vibrational Spectroscopic Investigation of Natural and Synthetic Analogs of Uranyl Oxyhydroxyhydrate Minerals

Uranyl oxy-hydroxy-hydrate minerals are common alteration products of uraninite (UO2+x) which is chemically and structurally analogous to uranium dioxide nuclear fuel. Therefore, structural and spectroscopic investigations of these alteration minerals and their analogous anthropogenic counterparts can provide insight into the environmental behavior of nuclear fuel cycle materials. Previously, we compiled available vibrational spectroscopic data for uranyl minerals in the Compendium of Uranium Raman and Infrared Experimental Spectra (CURIES) and found that only 37% of known uranyl oxy-hydroxy-hydrate minerals had spectra readily available in the literature and existing databases for inclusion therein. Furthermore, no available infrared spectra for this mineral group were included in CURIES. To expand our understanding of the spectroscopic features of uranyl oxy-hydroxy-hydrates and the structural origins thereof, we collected, and now include in CURIES, Raman and infrared spectra for an additional 12 uranyl hydroxide phases. To better understand the impact of structural and compositional variations of these phases on their spectroscopic features, we compare Raman spectra of different anion sheet topological groups and of analogous phases hosting different counter cations. We identify spectroscopic variations related to differences in equatorial bonding and structural changes as a result of cation substitution. We also prepare a uranyl hydroxide phase via hydrolysis of uranyl fluoride (UO2F2) as an analog of hydrolysis reactions that occur in nuclear fuel cycle materials; and we find that the alteration product of UO2F2, despite chemical and structural similarities to uranyl oxy-hydroxy-hydrate minerals, is readily distinguishable from related mineral phases using Raman spectroscopy. In this work, we provide new insights into the structural origins of spectroscopic features in uranyl oxy-hydroxy-hydrate minerals, improve the average Raman spectrum for this group of minerals, and thereby improve capabilities for identifying these mineral species and related anthropogenic phases using Raman spectroscopy.

Barth, Brodie [ORNL] (ORCID:0000000256142601)↗
NASA NTRSDate not supplied

ARCTRON: A Rapid Experimental Proving Ground for TPS Experiments and Arcjet Technology Development

Innovation in high-enthalpy facilities is fundamentally limited by the cost and risk of experimentation. New concepts for plasma control, diagnostics, facility components, and plasma-material interaction often require repeated iterations that are impractical to perform in production arcjets. As a result, promising ideas may remain unexplored or reach operational facilities only after significant development effort. ARCTRON is being developed as a rapid experimental proving ground where new ideas in plasma science, arcjet engineering, diagnostics, and material response can be conceived, tested, and quantitatively evaluated before transition to large-scale facilities. The platform combines radio-frequency (RF) and DC arc plasma generation, externally applied magnetic fields, configurable gas composition, reduced-pressure operation, laser heating, electrical biasing, and modular diagnostic access. These capabilities permit the plasma source, applied forcing, test article, and measurement configuration to be modified independently, allowing individual physical mechanisms to be isolated more readily than in a traditional test environment. One class of investigations addresses fundamental plasma-surface interaction physics. Conventional material tests often expose a specimen simultaneously to convective heating, reactive species, pressure, shear, radiation, and surface-current effects. The resulting material response may be measured accurately, while the contribution of each mechanism remains difficult to identify. ARCTRON is designed to vary these effects selectively. Plasma chemistry can be changed independently through configurable gas mixtures; magnetic fields and electrical biasing can modify charged-particle transport; laser heating can provide a non-plasma thermal input; and pressure, flow, and discharge mode can be varied over a broad operating space. This enables controlled tests of hypotheses involving surface catalycity, reactive-species transport, plasma-assisted oxidation, electromagnetic effects, shear, and the relative contributions of thermal and chemical loading. A second class of investigations enabled by this approach concerns the engineering of high-enthalpy facilities themselves. Arc-heated facilities are limited by electrode erosion, unstable arc attachment, localized heating, and damage to nozzles and other plasma-facing components. ARCTRON provides a lower-cost environment for testing concepts intended to mitigate these limitations. Candidate investigations include the use of applied magnetic fields to alter current paths and reduce plasma interaction with nozzle walls, ExB forcing to introduce controlled plasma rotation, magnetic or geometric approaches for distributing arc attachment, and alternative electrode or discharge configurations intended to reduce erosion and improve stability. Because the platform is reconfigurable, these concepts can be evaluated through repeated design--build--test cycles before they are considered for implementation in operational facilities. The platform also supports the development and validation of diagnostics that may be difficult to introduce initially into a large arcjet. Current and planned measurements include spatially resolved optical emission spectroscopy, electrostatic probes, fast imaging, pyrometry, calorimetry, laser-induced fluorescence, and absorption spectroscopy. These diagnostics are intended not merely to document a nominal operating condition, but to constrain the local plasma state and its relationship to component or material response. The modular facility geometry allows diagnostic concepts to be tested, calibrated, and compared under repeatable conditions before deployment in more demanding environments. ARCTRON is also supported by an integrated software suite. Automated control and data acquisition allow discharge parameters, gas composition, magnetic fields, diagnostic timing, and test configuration to be recorded as part of each experiment (STARDAC - Software for Testing, Analysis, Research Data, and Control). The Backend for Experiment Analysis, Storage, and Traceability (BEAST) is a database that provides the infrastructure needed to associate heterogeneous measurements with facility configuration, specimen identity, calibration state, geometry, and analysis provenance. This backend is particularly important for exploratory campaigns, in which many related configurations may be tested, and the value of an individual experiment depends on its connection to earlier and subsequent iterations. Complementary analysis capabilities, including computer-vision-based transient response measurements (arcjetCV), three-dimensional surface reconstruction (STARSCAN), and model-based Bayesian inference (SHIELD), and tomography data analysis (TOMATO, PuMA) can be incorporated when required by a specific hypothesis without becoming the focus of every campaign. The central objective of ARCTRON is therefore not to maximize heat flux or reproduce a complete flight environment. Its purpose is to reduce the cost and time required to ask consequential questions about plasma behavior, plasma-facing materials, diagnostics, and arcjet technology. By providing a controlled environment for rapid reconfiguration, mechanism isolation, quantitative measurement, and iterative engineering, ARCTRON can help mature concepts that would otherwise remain too speculative or too risky for evaluation in production facilities. The resulting knowledge can then guide the design of material models, focus test objectives in larger arcjets, reduce facility-development risk, and improve the physical basis of high-enthalpy ground testing. This work will present the ARCTRON architecture, operating modes, diagnostic suite, and digital experimental workflow. Initial experimental results from the first integrated operation of the facility will be presented, including flow characterization, power limitations, and deployment of the initial diagnostic suite. Ongoing development efforts aimed at catalycity characterization, magnetic plasma control, and advanced optical diagnostics will also be discussed, illustrating how the platform supports rapid iteration from concept to experiment.

experimental diagnostics↗
NASA NTRSDate not supplied

ARCTRON: A Rapid Experimental Proving Ground for TPS Experiments and Arcjet Technology Development

Innovation in high-enthalpy facilities is fundamentally limited by the cost and risk of experimentation. New concepts for plasma control, diagnostics, facility components, and plasma-material interaction often require repeated iterations that are impractical to perform in production arcjets. As a result, promising ideas may remain unexplored or reach operational facilities only after significant development effort. ARCTRON is being developed as a rapid experimental proving ground where new ideas in plasma science, arcjet engineering, diagnostics, and material response can be conceived, tested, and quantitatively evaluated before transition to large-scale facilities. The platform combines radio-frequency (RF) and DC arc plasma generation, externally applied magnetic fields, configurable gas composition, reduced-pressure operation, laser heating, electrical biasing, and modular diagnostic access. These capabilities permit the plasma source, applied forcing, test article, and measurement configuration to be modified independently, allowing individual physical mechanisms to be isolated more readily than in a traditional test environment. One class of investigations addresses fundamental plasma-surface interaction physics. Conventional material tests often expose a specimen simultaneously to convective heating, reactive species, pressure, shear, radiation, and surface-current effects. The resulting material response may be measured accurately, while the contribution of each mechanism remains difficult to identify. ARCTRON is designed to vary these effects selectively. Plasma chemistry can be changed independently through configurable gas mixtures; magnetic fields and electrical biasing can modify charged-particle transport; laser heating can provide a non-plasma thermal input; and pressure, flow, and discharge mode can be varied over a broad operating space. This enables controlled tests of hypotheses involving surface catalycity, reactive-species transport, plasma-assisted oxidation, electromagnetic effects, shear, and the relative contributions of thermal and chemical loading. A second class of investigations enabled by this approach concerns the engineering of high-enthalpy facilities themselves. Arc-heated facilities are limited by electrode erosion, unstable arc attachment, localized heating, and damage to nozzles and other plasma-facing components. ARCTRON provides a lower-cost environment for testing concepts intended to mitigate these limitations. Candidate investigations include the use of applied magnetic fields to alter current paths and reduce plasma interaction with nozzle walls, ExB forcing to introduce controlled plasma rotation, magnetic or geometric approaches for distributing arc attachment, and alternative electrode or discharge configurations intended to reduce erosion and improve stability. Because the platform is reconfigurable, these concepts can be evaluated through repeated design--build--test cycles before they are considered for implementation in operational facilities. The platform also supports the development and validation of diagnostics that may be difficult to introduce initially into a large arcjet. Current and planned measurements include spatially resolved optical emission spectroscopy, electrostatic probes, fast imaging, pyrometry, calorimetry, laser-induced fluorescence, and absorption spectroscopy. These diagnostics are intended not merely to document a nominal operating condition, but to constrain the local plasma state and its relationship to component or material response. The modular facility geometry allows diagnostic concepts to be tested, calibrated, and compared under repeatable conditions before deployment in more demanding environments. ARCTRON is also supported by an integrated software suite. Automated control and data acquisition allow discharge parameters, gas composition, magnetic fields, diagnostic timing, and test configuration to be recorded as part of each experiment (STARDAC - Software for Testing, Analysis, Research Data, and Control). The Backend for Experiment Analysis, Storage, and Traceability (BEAST) is a database that provides the infrastructure needed to associate heterogeneous measurements with facility configuration, specimen identity, calibration state, geometry, and analysis provenance. This backend is particularly important for exploratory campaigns, in which many related configurations may be tested, and the value of an individual experiment depends on its connection to earlier and subsequent iterations. Complementary analysis capabilities, including computer-vision-based transient response measurements (arcjetCV), three-dimensional surface reconstruction (STARSCAN), and model-based Bayesian inference (SHIELD), and tomography data analysis (TOMATO, PuMA) can be incorporated when required by a specific hypothesis without becoming the focus of every campaign. The central objective of ARCTRON is therefore not to maximize heat flux or reproduce a complete flight environment. Its purpose is to reduce the cost and time required to ask consequential questions about plasma behavior, plasma-facing materials, diagnostics, and arcjet technology. By providing a controlled environment for rapid reconfiguration, mechanism isolation, quantitative measurement, and iterative engineering, ARCTRON can help mature concepts that would otherwise remain too speculative or too risky for evaluation in production facilities. The resulting knowledge can then guide the design of material models, focus test objectives in larger arcjets, reduce facility-development risk, and improve the physical basis of high-enthalpy ground testing. This work will present the ARCTRON architecture, operating modes, diagnostic suite, and digital experimental workflow. Initial experimental results from the first integrated operation of the facility will be presented, including flow characterization, power limitations, and deployment of the initial diagnostic suite. Ongoing development efforts aimed at catalycity characterization, magnetic plasma control, and advanced optical diagnostics will also be discussed, illustrating how the platform supports rapid iteration from concept to experiment.

experimental diagnostics↗
DOE OSTI2024

Relithiation process for direct regeneration of cathode materials from spent lithium-ion batteries

A method for the regeneration of cathode material from spent lithium-ion batteries is provided. The method includes dissolving a lithium precursor in a polyhydric alcohol to form a solution. Degraded cathode material containing lithium metal oxides are dispersed into the solution under mechanical stirring, forming a mixture. The mixture is heat treated within a reactor vessel or microwave oven. During this heat treatment, lithium is intercalated into the degraded cathode material. The relithiated electrode material is collected by filtration, washing with solvents, and drying. The relithiated electrode material is then ground with a lithium precursor and thermally treated at a relatively low temperature for a predetermined time period to obtain regenerated cathode material.

Belharouak, Ilias↗
DOE OSTI2026

Review of Particle Physics

The Review summarizes much of particle physics and cosmology. Using data from previous editions, plus 3,200 new measurements from 903 papers, we list, evaluate, and average measured properties of gauge bosons and the recently discovered Higgs boson, leptons, quarks, mesons, and baryons. We summarize searches for hypothetical particles such as supersymmetric particles, heavy bosons, axions, dark photons, etc. Particle properties and search limits are listed in Summary Tables. We give numerous tables, figures, formulae, and reviews of topics such as Higgs Boson Physics, Supersymmetry, Grand Unified Theories, Neutrino Mixing, Dark Energy, Dark Matter, Cosmology, Particle Detectors, Colliders, Probability and Statistics. Most of the 118 reviews are updated, including many that are heavily revised.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2024

Method for implant and anneal for high voltage field effect transistors

In an example, the present invention provides a method of forming a semiconductor device on a gallium and nitrogen containing material. The method includes providing a substrate member comprising a surface region, the substrate member comprising a gallium and nitrogen bearing material. The method includes causing an implanted species to electrically activate the implant profile while removing one or more crystalline damage from the epitaxial material to change the amorphous state to a single crystalline state, and thereby creating a substantially electrically activated crystalline material.

Shealy, James R.↗
NASA NTRSDate not supplied

Selecting an Encapsulant for an Aerospace Superconducting Machine

Achieving larger benefits from electrified propulsion in single aisle aircraft (the largest commercial aircraft market segment) necessitates that a significant fraction of their 20 MW or greater propulsion system be electrified. These aircraft would require up to 10-20 of today’s state-of-the art machines, which have been demonstrated up to 2.5 MW for aerospace use, and could benefit further from 5 MW+ designs. However, when conventionally cooled, high power density machines still produce a significant amount of waste heat, translating into heavy thermal management and detracting from system benefits. Highly efficient fully superconducting electric machines (or those with a cryogenically cooled, high purity copper or aluminum stator) are a possible solution but have multiple barriers to overcome. One such barrier is the durability of superconducting windings. Superconductors are typically brittle, and encapsulants used to hold windings in place are a significant source of stress due to mismatches in coefficient of thermally induced contraction between ambient and operational temperatures (20 to 77 K). Lack of compliance between the materials at operational temperatures also adds significant stress. These encapsulants also form a thermal barrier that can be detrimental to cooling the superconductors. This work describes an initial study of commercially available encapsulants as it relates to superconducting machine applications, along with initial modeling of thermal stress in superconducting windings for a superconducting or cryogenically cooled stator in a 5 MW electric machine.

encapsulant↗
NASA NTRSDate not supplied

Fire-Resistant Textile Development for Exploration Vehicles With Enriched-Oxygen Cabin Environments

Material selection is a key part of the National Aeronautics and Space Administration (NASA) spacecraft fire safety management plan. Non-flammable textiles are necessary to ensure large-scale flame propagation events do not occur inside a spacecraft. An increased use of textiles and other softgood material is crucial to the pursuit of exploration spaceflight to reduce mass and volume. Exploration spaceflight missions benefit from enriched oxygen cabin environments (>21% O2) by allowing a reduced prebreathe protocol before Extravehicular Activity (EVA). However, materials become exponentially more flammable the higher the O2 levels become. Recent testing within the agency has revealed the lack of commercial-off-the-shelf (COTS) materials that can meet safety requirements in oxygen-enriched environments. Most of the fibers and textiles developed during Apollo (100% O2 cabin environment) and Skylab (>70% O2 cabin environment) are no longer commercially available due to those Programs ending and the discontinuation of raw materials or closure of the original manufacturers. As NASA returns to higher oxygen concentrations inside spacecraft, non-flammable textile development efforts have begun to meet the agency’s needs. This paper discusses those efforts including overall fire safety approach, state-of-the-art textile review and testing, an agency-wide assessment of textile needs performed by the NASA Engineering and Safety Center (NESC), the textile development strategy and expected challenges.

Mary Walker↗
DOE OSTI2024

Supervisory genset control in range-extended electric vehicle

A controls system for a range-extended electric vehicle comprising an overall system control unit, an engine control module configured to control a range extender of the range-extended electric vehicle, power electronics configured to control a generator of the range-extended electric vehicle, and a supervisory control module coupled between the overall system control unit and the engine control module and the power electronics, the supervisory control module configured to receive information from the overall system control unit and provide commands to the engine control module and the power electronics.

Li, Ke↗
DOE OSTI2026

Rapid Coal-Ash Characterization using Geophysical Methods & Machine Learning

Coal combustion products (CCP) are challenging to delineate in heterogeneous field settings. Conventional methods (test pits, coring, and laboratory analyses) are labor-intensive, slow, invasive, and provide sparse spatial coverage. This study evaluates whether rapid non-invasive geophysical screening methods—induced polarization (IP), magnetic susceptibility, and nuclear magnetic resonance (NMR) —combined with surface colorimetry (RGB_24), can discriminate CCP-soil mixtures and provide reliable estimates of CCP content. Laboratory measurements were collected on five CCP-soil mixtures (series) and modeled using (i) a linear baseline, (ii) a calibrated non-linear (power-mean) model, and (iii) a machine-learning (ML) Random Forest approach, with validation via leave-one-series-out and site-specific tests. Across the five series, individual signals—particularly IP and magnetic susceptibility—were strongly predictive of ash content but were consistently outperformed by combined models. The pooled calibrated non-linear and ML models captured the observed non-linearity and achieved high accuracy and precision, improving on linear fits. Colorimetry showed the weakest direct relationship with ash content for the tested samples but improved performance when included in multi-signal models. At pre-selected 3.5% decision threshold, calibrated and ML approaches yielded near-perfect classification (Matthews correlation coefficient ˜ 1), suggesting strong practical operability for field screening. Additionally, field-analog tests highlighted the role of endmembers—accuracy declined without access to end-member measurements but was largely recovered by collecting a minimal labeled pair for local recalibration. With end members, accuracy remained high. Globally trained models performed well on three operational unknowns; however, series-specific refits provided the most accurate predictions. Overall, these results highlight the potential of combining rapid geophysics and minimal local calibration for improved coal-ash delineation.

Peshtani, Klaudio↗
DOE OSTI2023

Overcoming the Entropy Penalty of Direct Air Capture for Efficient Gigatonne Removal of Carbon Dioxide

Atmospheric carbon poses an existential threat to civilization via global climate change. Hundreds of gigatonnes of carbon dioxide must be removed from earth’s atmosphere in the next three decades, necessitating a low-cost, energy-efficient process to extract low concentrations of carbon dioxide for conversion to a stable material permanently stored for thousands of years. In this work, the challenge of removing gigatonnes of CO 2 is described via the scale of effort and the thermodynamics of collecting and reducing this diffuse chemical, the accumulation of which imparts a substantial entropy penalty on any atmospheric carbon capture process. The methods of CO 2 reduction combined with upstream direct air capture (DAC) including absorption, membrane separation, and adsorption are compared with biomass torrefaction and permanent burial (BTB). A Monte Carlo model assesses the mass, energy, and economics of the full process of biomass torrefaction from biomass collection and transport to stable carbon burial to determine that 95% of scenarios could remove carbon for less than $200 per CO 2 -tonne-equivalent. Torrefied carbon is further discussed for its long-term stability and availability at the scale required to substantially mitigate the threat of climate change.

biomass↗
DOE OSTI2024

Intake runner for gaseous fuel engine, system, and method

A gaseous fuel engine system includes a hydrogen fuel supply, an engine housing having an intake port extending to a cylinder, and an intake runner. The intake runner includes a valve mount attached to a conduit and having a valve mounting face, and a gaseous fuel admission valve is mounted upon the valve mounting face. A hydrogen fuel passage extends from the valve mount through the conduit and is oriented angularly to at least one of a clamping face of the intake runner or the valve mounting face. Related apparatus and methodology is also disclosed.

Singh, Jaswinder↗
NASA NTRS2017

International Space Station Lithium-Ion Main Battery Thermal Runaway Propagation Test

In 2010, the ISS Program began the development of Lithium-Ion (Li-Ion) batteries to replace the aging Ni-H2 batteries on the primary Electric Power System (EPS). After the Boeing 787 Li-Ion battery fires, the NASA Engineering and Safety Center (NESC) Power Technical Discipline Team was tasked by ISS to investigate the possibility of Thermal Runaway Propagation (TRP) in all Li-Ion batteries used on the ISS. As part of that investigation, NESC funded a TRP test of an ISS EPS non-flight Li-Ion battery. The test was performed at NASA White Sands Test Facility in October 2016. This paper will discuss the work leading up to the test, the design of the test article, and the test results.

International Space Statio↗