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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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NASA NTRS2008

Characterization of a New Phase and Its Effect on the Work Characteristics of a Near-Stoichiometric Ni30Pt20Ti50 High-Temperature Shape Memory Alloy (HTSMA)

A new phase observed in a nominal Ni 30 Pt 20 Ti 50 (at.%) high temperature shape memory alloy has been characterized using transmission electron microscopy and 3-D atom probe tomography. This phase forms homogenously in the B2 austenite matrix by a nucleation and growth mechanism and results in a concomitant increase in the martensitic transformation temperature of the base alloy. Although the structure of this phase typically contains a high density of faults making characterization difficult, it appears to be trigonal (-3m point group) with a o ~1.28 nm and c o ~1.4 nm. Precipitation of this phase increases the microhardness of the alloy substantially over that of the solution treated and quenched single-phase material. The effect of precipitation strengthening on the work characteristics of the alloy has been explored through load-biased strain-temperature testing in the solution-treated condition and after aging at 500 ºC for times ranging from 1 to 256 hours. Work output was found to increase in the aged alloy as a result of an increase in transformation strain, but was not very sensitive to aging time. The amount of permanent deformation that occurred during thermal cycling under load was small but increased with increasing aging time and stress. Nevertheless, the dimensional stability of the alloy at short aging times (1-4 hours) was still very good making it a potentially useful material for high-temperature actuator applications.

A Garg↗
NASA NTRSDate not supplied

A Simplified Model of VIPER Thermal Management System. Part II: Integrated Vehicle

NASA’s Volatiles Investigating Polar Exploration Rover (VIPER) thermal management system (TMS) relies on four loop heat pipes (LHPs) to transport electronic waste heat to the vehicle cooling radiative surface and avoid overheating. The TMS has also ten constant conductance heat pipes (CCHPs) dedicated to balance the thermal load within the internal environment where the avionics boxes are mounted, also called warm electronic box (WEB), and to transport the heat from two of the science payload instruments. The TMS also uses two thermal straps to thermally link the batteries to the WEB. These thermal components, in addition to heaters, thermostat, multi-layer insulation (MLIs), and isolators forms the core of the VIPER TMS. The complex heat transport balance managed by the TMS is challenging to characterize and model. The more fidelity and granularity of a model, the more costly the computational resources needed and the longer the simulation and modeling time. When the priority is to provide quick but reliable assessments of the thermal performance or real time thermal feedback for training of console operators, simplified modeling tools are needed. To satisfy that need, this paper describes the effort to develop and correlate a model of VIPER TMS based on control volume approach. The correlation effort in particular focuses on hibernation, cold thermal balance, and hot thermal balance data from the integrated vehicle thermal vacuum (TVAC) test. Thus, the correlated model captures the heat leaks during hibernations and the performance at two extremes, bounding, operating scenarios.

Loop Heat Pipe↗
NASA NTRSDate not supplied

A Simplified Model of VIPER Thermal Management System. Part II: Integrated Vehicle

NASA’s Volatiles Investigating Polar Exploration Rover (VIPER) thermal management system (TMS) relies on four loop heat pipes (LHPs) to transport electronic waste heat to the vehicle cooling radiative surface and avoid overheating. The TMS has also ten constant conductance heat pipes (CCHPs) dedicated to balance the thermal load within the internal environment where the avionics boxes are mounted, also called warm electronic box (WEB), and to transport the heat from two of the science payload instruments. The TMS also uses two thermal straps to thermally link the batteries to the WEB. These thermal components, in addition to heaters, thermostat, multi-layer insulation (MLIs), and isolators forms the core of the VIPER TMS. The complex heat transport balance managed by the TMS is challenging to characterize and model. The more fidelity and granularity of a model, the more costly the computational resources needed and the longer the simulation and modeling time. When the priority is to provide quick but reliable assessments of the thermal performance or real time thermal feedback for training of console operators, simplified modeling tools are needed. To satisfy that need, this paper describes the effort to develop and correlate a model of VIPER TMS based on control volume approach. The correlation effort in particular focuses on hibernation, cold thermal balance, and hot thermal balance data from the integrated vehicle thermal vacuum (TVAC) test. Thus, the correlated model captures the heat leaks during hibernations and the performance at two extremes, bounding, operating scenarios.

Thermal Modeling↗
NASA NTRS2010

Ares I-X Ground Diagnostic Prototype

Automating prelaunch diagnostics for launch vehicles offers three potential benefits. First, it potentially improves safety by detecting faults that might otherwise have been missed so that they can be corrected before launch. Second, it potentially reduces launch delays by more quickly diagnosing the cause of anomalies that occur during prelaunch processing. Reducing launch delays will be critical to the success of NASA's planned future missions that require in-orbit rendezvous. Third, it potentially reduces costs by reducing both launch delays and the number of people needed to monitor the prelaunch process. NASA is currently developing the Ares I launch vehicle to bring the Orion capsule and its crew of four astronauts to low-earth orbit on their way to the moon. Ares I-X will be the first unmanned test flight of Ares I. It is scheduled to launch on October 27, 2009. The Ares I-X Ground Diagnostic Prototype is a prototype ground diagnostic system that will provide anomaly detection, fault detection, fault isolation, and diagnostics for the Ares I-X first-stage thrust vector control (TVC) and for the associated ground hydraulics while it is in the Vehicle Assembly Building (VAB) at John F. Kennedy Space Center (KSC) and on the launch pad. It will serve as a prototype for a future operational ground diagnostic system for Ares I. The prototype combines three existing diagnostic tools. The first tool, TEAMS (Testability Engineering and Maintenance System), is a model-based tool that is commercially produced by Qualtech Systems, Inc. It uses a qualitative model of failure propagation to perform fault isolation and diagnostics. We adapted an existing TEAMS model of the TVC to use for diagnostics and developed a TEAMS model of the ground hydraulics. The second tool, Spacecraft Health Inference Engine (SHINE), is a rule-based expert system developed at the NASA Jet Propulsion Laboratory. We developed SHINE rules for fault detection and mode identification. The prototype uses the outputs of SHINE as inputs to TEAMS. The third tool, the Inductive Monitoring System (IMS), is an anomaly detection tool developed at NASA Ames Research Center and is currently used to monitor the International Space Station Control Moment Gyroscopes. IMS automatically "learns" a model of historical nominal data in the form of a set of clusters and signals an alarm when new data fails to match this model. IMS offers the potential to detect faults that have not been modeled. The three tools have been integrated and deployed to Hangar AE at KSC where they interface with live data from the Ares I-X vehicle and from the ground hydraulics. The outputs of the tools are displayed on a console in Hangar AE, one of the locations from which the Ares I-X launch will be monitored. In a previous publication, we discussed how we selected the three tools based primarily on their ability to be certified for human spaceflight and described our plans for the prototype. This abstract is due October 23, 2009, and the Ares I-X launch is currently scheduled for October 27, 2009. If this abstract is accepted, then the full paper will describe how the prototype performed before the launch. It will include an analysis of the prototype's accuracy, including false-positive rates, false-negative rates, and receiver operating characteristics (ROC) curves. It will also include a description of the prototype's computational requirements, including CPU usage, main memory usage, and disk usage. If the prototype detects any faults during the prelaunch period then the paper will include a description of those faults. Similarly, if the prototype has any false alarms then the paper will describe them and will attempt to explain their causes. Also, the paper will describe the three tools and how they are used in the prototype. It will include a description of the TEAMS models of the Ares I-X first-stage TVC and associated ground hydraulics and how we adapted the TVC model for use in real-time diagnostics. It will describe the SHINE rules used for fault detection and mode identification and the software architecture that interfaces the various pieces of existing software that are part of the prototype to one another. It will describe how we selected the sensor values and commands that were used to train the IMS model and how we optimized the number of clusters in the IMS model. It will include screen shots of the graphical display that we developed in Java to display the outputs of the three tools. Because Ares I-X data was not yet available to us while we were developing the prototype, we used historical data from the Space Shuttle's Solid Rocket Booster (SRB) TVCs and the associated ground hydraulics to train IMS and to test the entire prototype. Because most of the failure modes that we modeled have never occurred in the Shuttle we inserted simulated failures into the Shuttle data. The Ares I-X first-stage TVC is very similar to the SRB TVC and we expect the data will be very similar. After the launch, we will determine how similar the data actually is and report how any differences in the data affected the diagnostic accuracy of the prototype. Finally, although we did not get the prototype certified, we designed it in a way that it could be certified and wrote a preliminary certification plan. The paper will include a brief summary of how we considered the need for certification in the design of the prototype, how we tested the prototype before deploying it to Hangar AE, and how we would propose to get it certified if it were deployed as an operational system. The paper will conclude with a description of some of the challenges we faced and some of the lessons learned in developing and deploying the prototype.

International Space Station↗
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

The NASA Turbulent Heat Flux (THX) Experiments: Summary and Lessons Learned

The Turbulent Heat Flux (THX) experiments were conducted at NASA Glenn Research Center (GRC) in order to collect measurements of velocities and temperatures for computational fluid dynamics (CFD) validation of heated flows, with a focus on propulsion system components. The experiments spanned 5 phases; four of which were conducted in the GRC AeroAcoustic Propulsion Laboratory (AAPL) using the Small Hot Jet Flow Rig (SHJAR). In addition to making velocity measurements with Particle Image Velocimetry (PIV), the THX experiments introduced a new Raman-scattering based capability to measure temperatures. Computational studies were also conducted for each of the experimental configurations, in order to provide a baseline of expected CFD results and conduct an assessment of the capability of various CFD approaches for calculating flows where the turbulent transport of heat was important. Two of the collected sets of data were used for American Institute of Aeronautics and Astronautics (AIAA) Propulsion Aerodynamic Workshops (PAWs). The data set from the 5th phase, collected for heated supersonic jets, was also used to construct new validation cases for the NASA Turbulence Model Resource (TMR). This paper provides an overview of the experiments and associated computations for each of the 5 test phases. Key experimental findings are presented. Lessons learned are provided concerning the effect of computational modeling choice on accuracy of predicting turbulent flows where thermal transport is important. Emphasis is placed on comparing Reynolds-averaged Navier-Stokes approaches with large-eddy simulation approaches. The benefits of utilizing a conjugate heat transfer method in conjunction with CFD solver for film cooling is demonstrated.

RANS↗
NASA NTRS2026

Influence of Processing Parameters on the Mechanical Properties of 3D Printed Borosilicate Particulate Reinforced Polymer Composites

Emerging composite materials are expanding the potential of additive manufacturing and enabling applications previously restricted by traditional manufacturing methods. The multi-phase nature of these composite materials combined with the complex in-ternal geometry of additively manufactured parts have enabled unique behavior, and potentially new applications. Additionally, these materials can be pyrolyzed to create dense metal, ceramic, and glass parts with geometries typically not achievable by tra-ditional processes. Additive manufacturing of borosilicate glass-based systems can open new applications in nuclear engineering, astronomy, and bone regrowth therapy. To elucidate the process-parameter relationship of borosilicate-polylactic acid (PLA) composites, mechanical testing was conducted and compared with a pure polylactic acid polymer baseline. Test specimens were fabricated by fused-filament fabrication with minimal post-processing. Yield strength, ultimate strength, and elastic modulus were calculated from stress-strain curves. Optical and scanning electron microscopy were conducted to observe the specimen microstructure before and after testing. The highest compressive yield strength for the composite was 28.22 MPa, and the highest compressive yield strength for PLA was 49.30 MPa. Print orientation was found to benefit the composite material but have a detrimental effect on the pure matrix material. An elastic modulus of 2.66 GPa was recorded for the borosilicate-PLA composite at 100% infill, 1 shell wall, and layer lines parallel to compression axis. Microscopy revealed that lower modulus composite specimens had the particulates re-distributed within the matrix. Tensile testing was done according to a polymer testing standard, which caused difficulties obtaining consistent fracture within the gauge length.

mechanical testing↗
NASA NTRS2026

Modeling Study of Hatch Spacing’s Effect on Grain Morphology in Repairing Damaged Metal Parts with Welding and Hatch Spacing’s Potential Use in Lunar Exploration

The welding process is a potential way of repairing a damaged metal component, especially cavity damage caused by a harsh environment like the lunar environment, which is characterized by large temperature differences and reduced gravity. The adjustment of welding parameter (e.g., hatch spacing) can improve production efficiency in the repair process. Seen from the microstructural level, hatch spacing sensitivity affects the metallic grain evolution and morphology in the welding process, which can further influence a repaired part’s mechanical properties; however, the study of hatch spacing’s effect on microstructure is challenging. Traditional experimental procedures are costly and time-consuming, and any change in hatch spacing value needs roll-back of experimental procedure. A modeling study can address the above challenges in experimental observation. In this research, a modeling approach based on the Kinetic Monte Carlo (KMC) Potts theory was used to simulate grain evolution and morphology with three hatch spacings. Through quantifying and analyzing the predicted grain morphologies, the effect of hatch spacing on microstructure in a welding-fabricated part was investigated. The predicted grain morphologies were validated with an EBSD image of welding microstructure, which has been published before. The primary grain morphologies were columnar grains with a small amount of fine equiaxed grains formed in the scanning path centerline. When increasing the hatch spacing, the columnar grains become larger and more lengthy, while the effect of hatch spacing on the equiaxed grains is not obvious.

Welding for repairing↗
NASA NTRSDate not supplied

The NASA Turbulent Heat Flux Experiments: Summary and Lessons Learned

The Turbulent Heat Flux (THX) experiments were conducted at NASA Glenn Research Center (GRC) in order to collect measurements of velocities and temperatures for computational fluid dynamics (CFD) validation of heated flows, with a focus on propulsion system components. The experiments spanned 5 phases; four of which were conducted in the GRC AeroAcoustic Propulsion Laboratory (AAPL) using the Small Hot Jet Flow Rig (SHJAR). In addition to making velocity measurements with Particle Image Velocimetry (PIV), the THX experiments introduced a new Raman-scattering based capability to measure temperatures. Computational studies were also conducted for each of the experimental configurations, in order to provide a baseline of expected CFD results and conduct an assessment of the capability of various CFD approaches for calculating flows where the turbulent transport of heat was important. Two of the collected sets of data were used for American Institute of Aeronautics and Astronautics (AIAA) Propulsion Aerodynamic Workshops (PAWs). The data set from the 5th phase, collected for heated supersonic jets, was also used to construct new validation cases for the NASA Turbulence Model Resource (TMR). This paper provides an overview of the experiments and associated computations for each of the 5 test phases. Key experimental findings are presented. Lessons learned are provided concerning the effect of computational modeling choice on accuracy of predicting turbulent flows where thermal transport is important. Emphasis is placed on comparing Reynolds- averaged Navier-Stokes approaches with large-eddy simulation approaches. The benefits of utilizing a conjugate heat transfer method in conjunction with CFD solver for film cooling is demonstrated.

RANS↗
NASA NTRS2026

Incremental Learning for Passive Microwave Precipitation Retrievals using Advanced Technology Microwave Sounder

Spaceborne passive microwave (PMW) radiometry is central to global precipitation monitoring, yet retrieval uncertainties remain substantial, particularly for cross-track sounders whose variable footprints and channel configurations are optimized for atmospheric temperature and moisture profiling rather than precipitation. Consequently, existing operational products often exhibit angular-dependent biases, limited effective swath utilization, unrealistic rainfall probability distributions, and systematic misclassification of precipitation phase. These limitations are further compounded by the scarcity of globally accurate and representative precipitation observations, as training data from the Dual-frequency Precipitation Radar (DPR) and the Cloud Profiling Radar (CPR) are spatially sparse, lack uniform global coverage, and exhibit heterogeneous error characteristics across precipitation regimes. To address these challenges, this study presents a supervised retrieval algorithm that incrementally trains an ensemble of extreme gradient-boosted decision trees by augmenting base learners with pre-training on reanalysis data and post-training on coincident DPR and CPR observations matched with the Advanced Technology Microwave Sounder (ATMS). By transferring prior information from reanalysis to posterior constraints from radar observations and adopting a sequential detection–estimation strategy for precipitation phase and rate retrieval, the proposed approach yields retrievals across the full ATMS swath that are largely free from persistent deficiencies in current Global Precipitation Measurement (GPM) passive microwave operational products. In particular, the method resolves bimodal artifacts in rainfall retrievals and mitigates systematic high-latitude snowfall biases, including overestimation across the Arctic and underestimation across the Antarctic. Validation against independent Multi-Radar Multi-Sensor (MRMS) data over the Contiguous United States (CONUS) further demonstrates improved performance in precipitation phase detection and rate estimation relative to both reanalysis and current GPM PMW products.

Mahyar Garshasbi↗
NASA NTRSDate not supplied

Phosphate Textural Diversity in CI Chondrites and C-Type Asteroids

Introduction: Apatite, Ca 5 (PO 4 ) 3 (CL/F/OH-), is a ubiquitous phosphate found throughout the solar system, including the most primitive solids, CI-chondrites [1,2] and related samples of carbonaceous asteroids Ryugu [3] and Bennu [4], returned by JAXA’s Hayabusa2 and NASA’s OSIRIS-REx missions, respectively. Apatite in these primitive solids is found as individual grains or mineral clusters and has been inferred to form from the hydrothermal sequence during cooling of their respective parent body or bodies. To better understand the formation history and reworking of these early phosphates we have undertaken a highly coordinated study of phosphate microstructures, geochemistry and U/Pb geochronology from a suite of CI meteorites and carbonaceous asteroid samples. These data have identified novel phosphate microstructures and complex relationships across a suite of apatite grains from the early solar system, indicating multiple episodes of growth and modification on the CI parent body(ies). Methods: Samples of CI chondrites, Alais, Ivuna, Orgueil, Oued Chebeika 002, Yamato (Y) 82162, Y980115, Y980134, and two chips of Hayabusa2 Ryugu particles (A0262 and C0263) have been acquired for analysis. The bulk texture of the samples were first scanned by X-ray Computed Tomography (XCT) using the Nikon XT H 320 within the XFACT facility at NASA JSC or the Xradia 620 Versa at the UTCT facility. Based on the identification of petrofabrics or features of interest from the XCT data, samples were chipped, oriented, potted in epoxy and thick sections were prepared. After anhydrously polishing the samples with silicon carbide and dry diamond powder down to 1 µm, the samples were ion polished using a Hitachi ArBlade. Energy dispersive Xray spectrometry (EDS) maps were collected to ID phosphates of interest using a JEOL 7900F SEM. The internal microstructures of identified phosphates were then mapped by electron backscatter diffraction (EBSD) using the JEOL 7900F. Based on the EDS and EBSD data, domains of interest were targeted for quantitative chemical analyses using a JEOL 8530 EPMA. Subsequently, in situ U-Pb and 207 Pb/ 206 Pb ages will be collected using a Cameca ims1290 secondary ion mass spectrometer at UCLA across a range of microstructures. Results: Apatite grains are ubiquitous throughout the CI chondrites and carbonaceous asteroid materials, found as individual grains, disseminated clusters or grain aggregates. Apatite grains are associated with serpentine, magnet-ite, and/or carbonate. Of particular interest, we have identified individual and aggregate polycrystalline grains ex-hibiting an internal ‘honeycomb’ texture (Fig. 1). Some of these grains appear overprinted by subsequent alteration while others remain unaltered. Apatite halogen sites are dominated by the missing component, assumed to be OH, and F, comparable to published values from Bennu, Ryugu and CM-chondrites [3-5]. However, the Yamato CI-like meteorites show a broader range of Cl values, and one grain from Alais is dominated by CL. Summary: Apatite growth features indicate a protracted and complex growth history, consistent with precipitation from an evolving fluid system. The ‘honeycomb’ texture identified in some CI meteorites is, to the best of our knowledge, the first report of such a microstructure in meteoritic phosphate. The microtextures and zoning will guide subsequent age analyses, to better constrain the formation and reworking of phosphate in CI(-like) materials. Acknowledgments: We thank the National Institute of Polar Research, Japan for samples of Y82162, 980115 and 980134 meteorites, ASU’s Buseck Center for Meteorite Studies for samples of Ivuna and Alais meteorites, and JAXA curation for chips of Ryugu material. This work was funded by NASA ROSES LARS grant 24-LARS24-0014. References: [1] Morlok et al., 2016, GCA 70:5371-5394. [2] Alfin g et al., 2019, Geochemistry 79:125532. [3] Nakamura et al. (2022) Science 379:1-15. [4] Seifert et al. (2026) MAPS 61:504-521. [5] Piralla et al. (2021) MAPS 56:809-828.

CI chondrites↗
NASA NTRS2026

Micromechanical Design of Carbon Nanotube Ribbon Reinforced Polymer Composite Materials

Lightweight materials are an important component of the design of aerospace structures. Carbon nanotube materials have been considered for this purpose due to the strength and stiffness of individual nanotubes, and the commercial availability of bulk formats such as fibers. These fibers can have a ribbon cross section which results in a different design space for their composites relative to traditional reinforcements which have a round cross section. This work applies brick-and-mortar micromechanical models and classical lamination theory with an inverse approach to investigate the design space of these composites. Using this approach, the influences of fiber geometry and axial and transverse mechanical properties are mapped. Finally, a sensitivity study is performed and the relative impacts of ±10% variations in the constituent material and geometric properties are ranked. Lamina axial moduli were found to range from a maximum of 3x to 1x minimum relative to a target quasi-isotropic laminate modulus depending on the anisotropy and shear modulus of the lamina. The fiber targets depended strongly on the fiber volume fraction in the lamina and the fiber axial modulus target was found to range from 4.8x to 3.2x the quasi-isotropic laminate target. The sensitivity analysis found that the largest driver of performance was the volume fraction, followed by the fiber axial modulus. While bio-based brick-and-mortar composites, such as nacre, can benefit from reinforcement aspect ratios above 10, for carbon nanotube ribbon (or carbon fiber)/polymer composites the sensitivity study indicated that the optimal cross-sectional aspect ratio was relatively smaller, potentially less than three.

Micromechanics↗
NASA NTRS2026

Towards an Improved Understanding of the Antarctic Coastal Zone and Its Contribution to Future Global Sea Level

Understanding the coastal zone of the Antarctic Ice Sheet (AIS), where it interacts with the Southern Ocean and warmer air masses, is crucial for predicting Antarctica's influence on the global climate and sea level. This region has multiple tipping mechanisms that could trigger large, rapid, and potentially irreversible changes in the AIS, the Southern Ocean and their global connections in the coming centuries. The AIS remains the largest source of uncertainty in future sea-level projections. Bed topography beneath the ice shelves and the coastal ice sheet is not yet well documented, and is a major source of this uncertainty. This review assesses current knowledge of the coastal zone and highlights methods to investigate it, including aerogeophysical surveys, ground- and ship-based measurements, satellite observations, and computer modeling. An ensemble analysis of published bed topography data sets identifies significant data gaps and their regional distribution, framed in the context of current ice-sheet behavior and potential instability. We propose scientific priorities and guidelines for future aerogeophysical surveys, advocating for a comprehensive, coordinated international effort to build a next-generation data set of Antarctic bed properties. Such an initiative would significantly advance understanding of the role of coastal processes in ice-sheet dynamics, reducing uncertainties in sea-level rise projections and improving predictions of future ocean and climate changes.

Kenichi Matsuoka↗
NASA NTRS1960

Ranger Spacecraft

The thermal-control philosophy of the spacecraft currently under development by the Jet Propulsion Laboratory is design by passive means to maintain all components within the tolerances specified by cognizant engineers. Due to the complexity of the configurations, calculations are) of necessity, fairly generalized and final design is based upon tests in an environmental chamber. The Ranger series spacecraft is designed with a basic structure which is common to all models, with additional hardware to suit the individual mission. This basic structure of Rangers A-1 and A-2 is seen as the hexagonal instrument section, the erectable solar panels, the movable antenna, and the omniantenna. The Ranger A-1 and A-2 configuration is for engineering tests and space-exploration, with the scientific instrumentation isolation requirement dictating the spread-out design. The spacecraft stands 12 feet high, weighs 700 to 800 pounds, and has an internal power of 150 watts. Rangers A-3, A-4, and A-5 are designed to rough land a capsule on the moon. For these, a capsule and retrorocket replace the scientific instruments, occupying the space inside the tower structure. The spacecraft must survive many environments. Chronologically they are: 1) Folded configuration inside an aerodynamic shroud on the pad. 2) Thermal flux from shroud aerodynamically heated during boost phase. 3) Coasting up to 30 minutes attached to Agena stage after booster and shroud are separated. 4) Agena stage burning. 5) Coasting and tumbling after separation from Agena until it passes from earth's shadow. 6) Upon reaching sunlight, panels open and begin sun acquisition. 7) Antenna seeks earth after spacecraft locks onto sun. 8) Space phase- "steady state" with vehicle's vertical axis locked on sun, communicating with earth. The philosophy is to design for the sun-acquired mode, making allowances for the transient conditions.

T. O. Thostesen↗
NASA NTRS2024

Wave Rotor Enhanced Nuclear (WREN) Propulsion: NASA Innovative Advanced Concepts (NIAC) - Phase I Final Report

Nuclear Thermal Propulsion (NTP) is identified as one of the preferred propulsion technologies for manned missions throughout the solar system (NASA MSFC).[1, 2] The state-ofthe-art NTP cycle is based on a solid core Nuclear Engine for Rocket Vehicle Application (NERVA)[3] class technology (Fig. 1) that is envisioned to provide a specific impulse of 900 seconds doubling chemical rocket performance (450 seconds). Even with this impressive increase, the NTP NERVA designs still have issues providing adequate initial to final mass fractions for high ΔV missions.[4] Nuclear Electric Propulsion (NEP) can provide extremely high Isp (2,000 to over 10,000 seconds) but with only low thrust and limits on mass to power ratios. The need for an electric power source also adds the issue of heat rejection in space where thermal energy conversion is at best 30-40% under ideal conditions. NASA Space Technology Mission Directorate (STMD) has recently expressed interest in finding advanced nuclear propulsion technology through the NASA Go:Thrust RFI.[5, 6] A novel Wave Rotor (WR) topping cycle has been proposed for our NASA NIAC concept. It promises to deliver similar thrust as NERVA class NTP propulsion, but with Isp in the 1,200-2,000 second range. Coupled with an NEP cycle, the duty cycle Isp can further be increased (1,800-4,000 seconds) with minimal addition of dry mass. This bimodal design enables fast transit trajectories for manned missions to Mars and revolutionizes the deep space exploration of our solar system.

Nuclear Thermal Propulsion↗
NASA NTRS2026

Towards an improved understanding of the Antarctic coastal zone and its contribution to future global sea level

Understanding the coastal zone of the Antarctic Ice Sheet, where it interacts with the Southern Ocean and warmer air masses, is crucial for predicting Antarctica's influence on the global climate. This region has multiple tipping mechanisms that could trigger large, rapid, and potentially irreversible changes in the coming centuries. The Antarctic Ice Sheet remains the largest source of uncertainty in future sea-level projections. Insufficient knowledge of bed topography beneath the ice shelves and the coastal ice sheet is not yet well documented, but is a major source of this uncertainty. This review assesses current knowledge of the coastal zone and highlights methods to investigate it, including aerogeophysical surveys, ground- and ship-based measurements, satellite observations, and computer modeling. An ensemble analysis of published bed topography datasets identifies significant data gaps and their regional distribution, framed in the context of current ice-sheet behavior and potential instability. We propose scientific priorities and guidelines for future aerogeophysical surveys, advocating for a comprehensive, coordinated international effort to build a next-generation dataset of Antarctic bed properties. Such an initiative would significantly advance understanding of the role of coastal processes in ice-sheet dynamics, reducing uncertainties in sea-level rise projections and enhancing predictions of future ocean and climate changes.

Kenichi Matsuoka↗
NASA NTRSDate not supplied

A Parametric Battery Model for the Conceptual Design of Electric Aircraft

Electric aircraft conceptual designs usually have an assumed specific power and specific energy for the aircraft’s energy storage system that dictates the total capacity and the peak power available. The specific energy and power are inherently linked to the state-of-charge and discharge rate from which they were derived; therefore, they will not directly correspond to the diverse circumstances encountered in various aircraft missions and flight segments. These parameters turn the battery system into a black box, disregard potential electrical restrictions, and disallow the aircraft and battery to be optimized as a system. Peering into this box, this study highlights the importance of incorporating a parametric battery model into the conceptual design workflow by splitting high-level terms such as power into voltage and current and investigating their variability during the discharge process. Through the modeling of these more detailed parameters, this methodology shows the feasibility of using low states-of-charge for contingency operations, including the end of the reserve mission, expanding the amount of usable capacity for electric aircraft. Stark differences in aircraft capabilities can arise between varying fidelity battery models due to late-mission, high-power flight operations. This parametric battery model effectively captures these differences by evaluating the limitations that arise within the individual battery cells and the aircraft powertrain. This paper shows that the unusable charge of a battery is set by the balked landing power requirement and can realistically range from 5% to 44% based on assumptions. This sets the analog to unusable fuel capacity in aircraft with liquid fuel systems. Needing only aircraft- and mission-level inputs and only seconds of run time, this model is a prime fit for the fast, accurate exploration of the electric aircraft conceptual design space.

Battery↗
NASA NTRS2026

Hydrology Copilot: A Cloud-Native Ai System for Hydrological Data Analysis

The emergence of AI-driven Earth observation systems promises to broaden access to petabyte-scale geospatial data beyond domain specialists. However, translating this vision into operational scientific infrastructure requires addressing fundamental challenges in data virtualization, code transparency, and domain-specific reasoning. We present Hydrology Copilot, a cloud-native AI framework for natural-language-driven analysis of Earth observation data. To demonstrate operational capabilities at scale, we implement the system using NASA's North American Land Data Assimilation System version 3 (NLDAS-3), which provides surface meteorological forcing and land-surface model output across North and Central America at 1-km resolution, from which drought diagnostics are derived. The system integrates five core contributions: (1) scalable data virtualization using Kerchunk-based cloud optimized access, achieving a 1.5 to 4.6 times improvement in I/O latency across benchmark queries spanning regional single-day extractions (4.6 times speedup) to continental monthly aggregations (1.5 times speedup); (2) transparent code generation through Microsoft Azure AI Foundry agents that expose executable Python workflows for scientific verification; (3) persistent conversational memory enabling multi-turn analytical discourse across sessions; (4) intelligent query validation that enforces dataset boundaries and resolves ambiguous requests before execution; and (5) a multi-agent architecture coordinating query parsing, code generation, and visualization. We evaluate the system through drought-monitoring workflows, demonstrating reliable code generation, accurate results validated against reference computations and the operational U.S. Drought Monitor, and efficient operation across increasingly complex tasks. By bridging natural-language interfaces with rigorous hydrological analysis, Hydrology Copilot advances beyond proof-of-concept demonstrations to provide a deployable framework for operational Earth science applications.

Data virtualization↗