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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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To date completed three Solar Dynamic Observatory SDO real-time eclipse seasons. Sony 18650HC has a low rate of capacity fade under GEO cycling regime. Real time test results correlate with accelerated GEO lifetest data and AEA capacity fade prediction tool. This data, together with other AEA test data, justify the SDO Project decision to baseline Lithium-Ion chemistry for the spacecraft battery.
Human thermal analysis and model development inform NASA’s space suit development, vehicle/habitat design, and survivability studies. Historically, human thermal models such as the 41-node metabolic man (METMAN) and the Wissler model have been standalone software tools developed with FORTRAN, a programming language known for its high performance in computationally intensive applications. Though efficient, these standalone programs pose challenges to coupled human-system analysis with detailed life support and thermal control subsystem models in other commercial software. This paper describes the conversion of the METMAN human thermal model from a standalone FORTRAN program to a model in Thermal Desktop (Ansys), a commonly used CAD-based simulation software for engineering that specializes in heat transfer, thermal radiation, and fluid flow analysis. This format was chosen to best facilitate model sharing and compatibility, enabling the direct integration of METMAN human thermal analysis with subsystem models across NASA programs and commercial partners.
The lunar surface presents unfavorable constraints and harsh living conditions. To address these challenges, autonomous habitats will require complex integrated systems that combine advanced software, high-performance hardware, and cutting-edge sensors to ensure sustainability, safety, and operational efficiency. Consequently, maintaining a sustainable presence on the Moon requires reliable infrastructure and efficient development, precise monitoring, and utilization of resources within a lunar installation. These elements are essential not only to ensure that lunar settlement can be long-term, self-sustaining, and resource-efficient, but also to serve as a foundation for future missions and eventual human habitation on Mars. Humans are not native to the Moon; therefore, our survival and ability to thrive will depend on autonomous systems that can foster safety and resilience through high-availability architectures, graceful degradation, and highly fault-tolerant spaceflight hardware capable of continuing operation during failures. This requires advanced human-rated distributed systems architectures with specialized electronics, scalable capabilities, and an integrated design approach. Unlike current practices focused on short-term missions and regularly maintained components, permanent lunar compute systems must be designed for extended operations beyond mission durations. This paper explores the necessity of transitioning toward fault- tolerant, highly autonomous hardware systems designed for multi-year missions. It also identifies critical subsystems that require high levels of autonomy, supported by radiation-hardened processors and extreme thermal loads, which are essential to mitigate long-term degradation and ensure sustainable lunar habitation. Finally, the paper aligns with NASA’s identified Civil Space Shortfalls, particularly in high-performance onboard computing, advanced data acquisition, extreme-environment avionics, radiation monitoring and countermeasures, and autonomous health management. It proposes NASA’s new High-Performance Spaceflight Computing (HPSC) processor as a turnkey solution, delivering 100 times the performance-per-watt of legacy rad-hard CPUs and enabling onboard AI, edge computing, and fault-tolerant features essential for sustained lunar autonomy and beyond.
This work presents an application of Model Predictive Control to maintain long-term stability for a three-satellite formation around the asteroid Apophis via remote guidance. The mothership and two daughterships perform tomographic characterization with a bistatic radar. The mothership estimates the states of all three spacecraft and determines the necessary control to maintain the desired antipodal daughtership states. An Extended Kalman Filter estimates the mothership states. A Batch Least Squares algorithm estimates the daughtership states and performs maneuver reconstruction for the mothership-administered thrust commands under thruster and gravitational uncertainty. The formulation maintains the antipodal angle with growing instability amidst these uncertainties.
The objectives of this research are to: 1) Investigate the oxidation/ablation behavior of HfB2/SiC materials in simulated re-entry environments; 2) Use the arc jet test results to define appropriate use environments for these materials for use in vehicle design. The parameters to be investigated include: surface temperature, stagnation pressure, duration, number of cycles, and thermal stresses.
Development of the Moon Base will enable a home away from home for astronauts who will live and work at humanity’s first lunar outpost. In this effort, NASA’s Moon Transportation Office is responsible for enabling the transformational missions required to deliver habitats, supplies, science payloads, and all other elements needed to cultivate a permanent presence on the Lunar Surface. The Mission Concept (MC) is characterized through evaluation of an end-to-end architecture that can successfully deliver a generalized heavy large-volume payload, in excess of 4000 kg, to a precision landing and touchdown on the lunar surface. The mission architecture utilizes a single launch configuration of a Lunar Lander (LL) with a unique propellant system. The LL has an integral orbital transfer capability and features jettisonable elements. The design circumvents the need for prop transfer on orbit and multiple launch configurations. The launch vehicle (LV) for this work will assume the capability to deliver a payload in excess of 40,000 kg to orbit, affording multiple LV solutions. Considerations for the LL and payload deployment from the fairing are assumed to be handled through compliance with a launch providers’ Interface Requirements Document (IRD). The MC will span from launch at Kennedy Space Center (KSC) to terminal descent and touchdown on the lunar surface, requiring a total ΔV on the order of 6 km/s beyond what is required to get the vehicle stack to a 200 km circular Low Earth Orbit (LEO). Major mission phases include: launch and launch vehicle separation, transfer operations, pre-landing navigation, and lunar descent and touchdown. A Concept of Operations (ConOps) is used as the primary design driver for defining architecture of the vehicles necessary to achieve final payload delivery. Numerous ground rules and assumptions will be provided for each phase of the mission. Concept designs for the LL is presented. An emphasis of the design maximizes a feasible path for maturation, manufacturing, and operation. A self-imposed practical consideration for this effort is the incorporation of legacy designed hardware to minimize expensive, time-intensive, and high-risk hardware development cycles. The propulsion system of the LL adopts a conventional storable bipropellant configuration of monomethyl hydrazine (MMH) and mixed oxides of nitrogen (MON3). This effort will showcase a unique propellant delivery system to minimize the reliance on propellant management devices (PMDs) during descent. Numerous key constraints have been considered, across the multiple segments of the mission. These include the unique aspects of center of gravity (CG) management, thruster plume effects including self-impingement, propulsion system hardware limitations, navigation during multiple mission phases, and landing gear geometry for uneven terrain. These constraints shape the trades necessary for precision landing of heavy cargo and ensure compatibility with broader Moon Base Transportation concepts. The resulting insights inform future transportation strategies for the Moon and beyond; directly contributing to the development of cargo‑delivery standards that will support the long‑term buildup of a sustainable, continuously inhabited Moon Base.
Batteries are used in a wide variety of applications. In recent years, they have become popular as a source of power for electric vehicles such as cars, unmanned aerial vehicles, and commericial passenger aircraft. In such application domains, it becomes crucial to both monitor battery health and performance and to predict end of discharge (EOD) and end of useful life (EOL) events. To implement such technologies, it is crucial to understand how batteries work and to capture that knowledge in the form of models that can be used by monitoring, diagnosis, and prognosis algorithms. In this work, we develop electrochemistry-based models of lithium-ion batteries that capture the significant electrochemical processes, are computationally efficient, capture the effects of aging, and are of suitable accuracy for reliable EOD prediction in a variety of usage profiles. This paper reports on the progress of such a model, with results demonstrating the model validity and accurate EOD predictions.
NASA seeks a sustained human presence on the lunar surface. High-efficiency and resilient energy systems are critical to supporting habitats, scientific outposts, and lunar surface operations. Photovoltaics have long been the backbone of space power systems, transitioning from silicon solar cells to multi-junction III-V solar cells, which now dominate state-of-the-art (SOA) technology. Multi-junction cells achieve high efficiency by layering semiconductors, each absorbing a specific portion of the solar spectrum. However, efficiency gains are increasingly constrained by device physics and manufacturing complexity. Additionally, higher-order junctions pose challenges for accurate modelling and performance characterization due to difficulties in replicating the AM0 spectrum.
A cryogenically cooled Ka-band (33.6-GHz), seven-element front-end array for the DSN was built and tested. This system uses seven high electron mobility transistor (HEMT) low-noise amplifiers cooled by a two-stage closed-cycle refrigerator. All system components from the polarizers to the output isolators are cooled to a physical temperature between 18 and 35 K. The noise temperatures of the individual elements range from 64 to 84 K over a 2.75-GHz bandwidth.
In 2007, the NASA Engineering Safety Center (NESC) chartered the NASA Aerospace Flight Battery Systems Working Group to bring forth and address critical battery-related performance/manufacturing issues for NASA and the aerospace community. A suite of tasks identifying and addressing issues related to Ni-H2 and Li-ion battery chemistries was submitted and selected for implementation. The current NESC funded are: (1) Wet Life of Ni-H2 Batteries (2) Binding Procurement (3) NASA Lithium-Ion Battery Guidelines (3a) Li-Ion Performance Assessment (3b) Li-Ion Guidelines Document (3b-i) Assessment of Applicability of Pouch Cells for Aerospace Missions (3b-ii) High Voltage Risk Assessment (3b-iii) Safe Charge Rates for Li-Ion Cells (4) Availability of Source Material for Li-Ion Cells (5) NASA Aerospace Battery Workshop This presentation provides a brief overview of the tasks in the 2007 plan and serves as an introduction to more detailed discussions on each of the specific tasks.
Rechargeable nickel-hydrogen systems are described that more closely resemble a fuel cell system than a traditional nickel-cadmium battery pack. This was stimulated by the currently emerging requirements related to large manned and unmanned low Earth orbit applications. The resultant nickel-hydrogen battery system should have a number of features that would lead to improved reliability, reduced costs as well as superior energy density and cycle lives as compared to battery systems constructed from the current state-of-the-art nickel-hydrogen individual pressure vessel cells.
Silver-zinc (Ag-Zn) battery technology has been baselined as the energy storage system for the MESUR mission. The mission profile will require the operation of this battery in a manner not usually seen for this technology. In particular, the combination of storage time followed by multiple cycles as a function of fluctuating temperatures and charge/discharge rates, and limited available time for charging has not been previously demonstrated.
Americium-241 is used as the fuel of choice in European Radioisotope Power Systems. The University of Leicester have developed a number of systems using this fuel type, including a 200 Wth heat source. To maximise the electrical output that can be generated from the heat source, the University of Leicester and NASA Glenn Research Center have collaborated on a radioisotope Stirling generator concept, building on the long heritage of dynamic power conversion developments at NASA GRC. Here we present the design of a technology demonstrator of the Americium-fuelled Radioisotope Stirling Generator (Am-RSG).
Team functioning is integral to success in future long term space exploration missions. Proactively detecting declines in team functioning can mitigate conflict and ensure mission success. This project developed a speech-based artificial intelligence (AI) system that unobtrusively predicts degradation in team functioning, including performance and cohesion, in the Human Exploration Research Analog (HERA) Campaigns 4 and 5. The AI system conducted automated analysis of the prosodic (tone of voice) and linguistic (language content) components of speech, modeling interpersonal dynamics at both the turn-taking and day-wide levels. We investigated team functioning via observing structured interactions (i.e., multi-mission space exploration vehicle-extra vehicular activity [MMSEV-EVA], team interaction battery [TIB]) and unstructured interactions before the MMSEV-EVA task. We developed machine learning models to predict team functioning (objective task accuracy, self reported team efficacy and self reported team cohesion) by analyzing OpenSmile acoustic features, linguistic descriptors extracted via the linguistic inquiry and word count (LIWC) dictionary, and semantic embeddings. In the TIB, static models using logistic regression and random forests were not able to predict task accuracy, but predicted team efficacy and cohesion during both the decision making and relational tasks to a moderate level (60-70%). Majority voting on the individual turns to predict day long team efficacy further increased accuracies (70-80%). Finally, long short-term memory (LSTM) models showed the best performance across all variables (80-91%), including task performance. In the MMSEV-EVA, static models achieved an accuracy of 60% with majority voting, which increased to 80% through the incorporation of mission day as a variable, accounting for the learning effect. A key finding across both tasks was the "team-dependent" nature of these interactions; models achieved much higher accuracy when trained on prior days of the same team's data rather than attempting to generalize across entirely different teams, with even 1-2 days of prior data per team achieving 5-15% improvement over team-independent models. In addition, the incorporation of pre-task data from the same team also improves model performance, e.g., incorporating data from the decision-making task of the TIB, which preceded the relational task, improved the prediction of team efficacy and cohesion during the latter. We compared model performance when trained on machine-generated data compared to data that had been further corrected by human annotators. Overall, models trained on human-corrected data exhibited a modest improvement in performance, particularly when acoustic features were used. We found no significant correlation between word error rate (WER) and model accuracy (r(55) = -0.08, p = 0.51), but model’s accuracy was significantly higher for medium/high quality transcription (0.74 (SD = 0.48)) compared to the low-quality group (0.64 (SD = 0.36)) (t(63)=2.82, p = 0.006). Based on these, several design recommendation emerge, that could inform Standards at NASA. Models predicting team functioning should incorporate at least one to two days of historical interaction data, include brief pre-task discussions, and explicitly model temporal learning effects, especially for longer operational tasks. Minimum quality standards for automated speech-processing pipelines are needed, given the performance gains observed with manually corrected acoustic data. Finally, systems should leverage both acoustic features and language embeddings in complementary ways, with modality choices and fusion strategies tailored to mission context, task demands, and data quality requirements.
Fatigue analysis tools can vary across industries. For example, automotive engineers often use the Wöhler (S-N) approach to design for safe-life, while aerospace engineers prioritize damage tolerance and inspection intervals, relying instead on crack growth models such as Paris’ law. Although both approaches may deal with the control of cracks in similar materials, their analysis tools and material characterizations are fundamentally distinct. This divide mirrors the classic split between stress-based strength analysis and linear elastic fracture mechanics. However, modern nonlinear models that incorporate material softening, such as cohesive laws, blur this boundary and capture fracture behaviors across scales. This presentation describes the CF23 fatigue model, which uses cohesive softening to link S-N crack initiation with crack propagation rates. CF23 spans the full fatigue spectrum, from initial propagation transients to steady-state growth and threshold conditions, offering a unified framework that bridges Wöhler and Paris-based methodologies. Example applications include fatigue crack propagation transients in adhesive interfaces and skin/stiffener separation.
Nickel-hydrogen cells are currently being manufactured on a semi-experimental basis. Rechargeable nickel-hydrogen systems are described that more closely resemble a fuel cell system than a traditional nickel-cadmium battery pack. This has been stimulated by the currently emerging requirements related to large manned and unmanned low earth orbit applications. The resultant nickel-hydrogen battery system should have a number of features that would lead to improved reliability, reduced costs as well as superior energy density and cycle lives as compared to battery systems constructed from the current state-of-the-art nickel-hydrogen individual pressure vessel cells.
A nomogram based on the number/distribution of micrometeoroid/debris hits recorded on the Long Duration Exposure Facility (LDEF) is presented. The nomogram permits the user to estimate the total number of impacts that a space structure would encounter as a function of time in orbit, exposed area, and angular location associated with the LDEF. Examples are presented on the application of the nomogram to satellites and space structures of different cross-sections to that of the LDEF. The effects of altitude and orbit inclination are also discussed. To further demonstrate the usefulness of this nomogram, results are compared to impact data measured on the UTIAS polymer matrix composite experiment (AO180). The impact damage occurring on these composite materials is examined, and data on hole size, penetration depth, and delamination area are presented.
A full-charge indicator for battery chargers, includes a transistor which is in a conductive state as long as charging current to the battery is not less than a level which indicates that the battery did not reach full charge. When the battery reaches full charge, a voltage drop in a resistor in the charging current path is not sufficient to maintain the transistor in a conducting state, and therefore it is switched off. When this occurs an LED is turned on, to indicate a full charge state of the battery. A photocoupler together with a photocoupler transistor are included. When the transistor is off, the photocoupler activates the photocoupler transistor to shunt out a resistor, thereby reducing the charging current to the battery to a float charging current and prevent the battery from being overcharged and damaged.