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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 NTRS2026

Long-Term Evaluation of Landsat 9 Oli Data Product Uniformity at Focal Plane Module-Boundaries Using Earth Scenes

The uniformity performance characteristic in remote sensing data products is a metric that helps evaluate how an image accurately represents radiometric responses to geophysical variability at the Earth’s surface or within the atmosphere. These uniformity attributes are used in Earth remote sensing science applications such as investigating water quality, land-cover/land-use classifications, and crop health assessments. To ensure these applications perform effectively, it is crucial to maintain and regularly assess the uniformity of calibrated remote sensing data products. In the Landsat missions, data from the onboard radiometric reference Solar diffuser device are used as the standard approach to derive the calibration parameters, ensuring the maintenance of both absolute radiance and radiometric uniformity through quarterly updates. This publication presents an alternative approach that leverages Earth scene data to assess the on-orbit uniformity performance of the Landsat 9 (L9) mission. The analysis characterizes uniformity at a specific set of spatial positions (the focal-plane boundary zones) that are intrinsic to the Operational Land Imager (OLI) focal plane design. By employing these Earth data statistics, the article further explores the temporal trends in the radiometric uniformity results. The results shown in this article demonstrate that for pushbroom imaging design systems with staggered sensor chip focal plane architectures, the co-registered pixels, i.e., overlapping measurements of the same ground target viewed by different detectors, offer a self-contained mechanism for assessing product uniformity. Remarkably, this alternative approach achieves a level of radiometric quality comparable to that delivered by a stable, well-characterized onboard Solar diffuser calibration device. The findings demonstrate the potential and capability of such Earth scene statistics in maintaining radiometric uniformity in calibrated data products to better than 1% (1-sigma) throughout the mission’s operational lifetime.

trend↗
NASA NTRSDate not supplied

Bosch Carbon Catalyst Regeneration in Water III: Experiments for and Related to Thermal Shock

Bosch technology has the potential to close the atmospheric revitalization loop by providing theoretically 100% regeneration of metabolic carbon dioxide into oxygen. The main obstacle to using Bosch technology is over-pressurization issues in the carbon formation reactor. Prior work on Bosch catalyst regeneration established that agitating carbon coated beads in water broke up pressure causing clogs and regenerated the catalyst surface. This process proved to be time consuming with experiments taking at least one hour to regenerate ten grams of carbon coated beads. In an attempt to shorten the processing time, thermally shocking the carbon coated beads prior to mechanical agitation was tested. Agitating the carbon coated beads after exposure to a saturated steam environment was also tested to ensure that the steam generated by thermally shocking the carbon coated beads would not cause adverse effects. The rationale behind thermally shocking the carbon coated beads is that the bead would pull away from the carbon shell due to a difference in the thermal expansion coefficients. The results of this project show that the processing time can be cut in half when compared to previous work, and that saturated steam has little to no effect on regeneration.

Bosch Process↗
NASA NTRS2026

PERSIANN-Unet: A Global Deep Learning Framework for Near-Real-Time Precipitation Estimation Using Infrared Data

Access to high-quality, high-resolution, near-real-time precipitation data is essential for hydrological and meteorological research and disaster mitigation. Traditional tools such as rain gauges and radar networks, though effective, have limitations, including sparse coverage in remote areas and high operational costs. Satellite data, with its global coverage and high spatial and temporal resolutions, mitigates limitations in coverage. Satellite precipitation products like Hydro Estimator (HE), Integrated Multi-satellitE Retrievals for Global Precipitation Measurement (IMERG), and Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks (PERSIANN) utilize both geosynchronous thermal infrared (IR) and passive microwave (PMW) data in their operation. PMW sensors offer detailed atmospheric profiles but suffer from higher latency, whereas IR sensors provide lower latency but only capture cloud-top information. Despite this constraint, IR data remains attractive for low-latency precipitation estimation. Recent advances in deep learning, particularly convolutional neural networks (CNNs), have further improved satellite precipitation retrievals. This study introduces PERSIANN-Unet (PUnet or PERSIANN V3), a quasi-global algorithm covering 60°N–60°S that combines IR data, monthly climatology, and the UNet architecture to produce half-hourly precipitation estimates at 0.04° resolution. The product is evaluated against HE, IMERG, and PDIR-Now for 2022–2023. Results show that PUnet closely matches its training target, IMERG V07 Final, at the global scale, and performance is further evaluated against Stage IV as a reference over CONUS. Training PUnet on IMERG (2016–2021) leverages a high-quality, integrated PMW IR-gauge precipitation product while developing an IR-based framework not reliant on PMW availability. By operating on a single global image, PUnet avoids tile partitioning and blending steps, reducing edge discontinuities, and produces more spatially consistent precipitation fields across hemispheres.

Phu Nguyen↗
NASA NTRS1993

The Telecommunications and Data Acquisition Report

This quarterly publication provides archival reports on developments in programs managed by JPL's Office of Telecommunications and Data Acquisition (TDA). In space communications, radio navigation, radio science, and ground-based radio and radar astronomy, it reports on activities of the Deep Space Network (DSN) in planning, supporting research and technology, implementation, and operations. Also included are standards activity at JPL for space data and information systems and reimbursable DSN work performed for other space agencies through NASA. The preceding work is all performed for NASA's Office of Space Communications (OSC). The TDA Office also performs work funded by another NASA program office through and with the cooperation of OSC. This is the Orbital Debris Radar Program with tile Office of Space Systems Development. The TDA Office is directly involved in several tasks that directly support the Office of Space Science (OSS), with OSC funding DSN operational support. In radio science, The TDA Progress Report describes the spacecraft radio science program conducted using tile DSN. For the High-Resolution Microwave Survey (HRMS), the report covers implementation and operations for searching the microwave spectrum. In solar system radar, it reports on the uses of the Goldstone Solar System Radar for scientific exploration of the planets, their rings and satellites, asteroids, and comets. In radio astronomy, the areas off support include spectroscopy, very long baseline interferometry, and astrometry.

Edward C Posner↗
NASA NTRSDate not supplied

Bosch Carbon Catalyst Regeneration in Water I: Bosch Carbon Removal from Reacted Beads Utilizing Mechanical Agitation

The ability to recover oxygen from metabolic carbon dioxide is crucial for crewed long duration missions in which the atmosphere must be recycled. Two physiochemical methods are primarily employed for this purpose: the Bosch process and the Sabatier reaction. This paper focuses on the Bosch process. It utilizes hydrogen in the presence of a catalyst to form water and solid carbon out of metabolic carbon dioxide. The solid carbon product deposits onto the catalyst and eventually causes reactor over pressurization issues. Multiple methods are currently being investigated to regenerate the catalyst’s surface and break up the pressure causing carbon clogs. This paper explores whether water and mechanical abrasion would work to remove Bosch carbon by testing multiple washing conditions. The different washing conditions involved agitation intensity, heating, duration, and volume of water. It was found that it is possible to break up the clumps of carbon formed in the reactor through agitation with room temperature water in one hour and shows promise for completely cleaning the carbon off the beads’ surface.

Agitation↗
NASA NTRS2022

Test Data Analysis of the Thermodynamic Vent System-Augmented Top Spray Injector Liquid Nitrogen Transfer Experiments

Traditionally, a cryogenic tank must be pre-chilled to some “target” temperature before the main vent valve can be closed to attempt a non-vented fill (NVF) of cryogenic liquid propellant. This methodology is particularly attractive for performing in-space transfer of cryogens due to the unknown location of the liquid/vapor interface in microgravity and the high likelihood of venting liquid if the vent valve is opened during transfer. This paper presents in-depth test data analysis of a Thermodynamic Vent System (TVS) augmented injector used for cryogenic tank chilldown and fill experiments of a thin-walled Titanium tank. Eight tests were conducted using liquid nitrogen across a range of inlet conditions and boundary conditions, and three different chilldown/fill methods. For four of the tests, the injector sprays liquid into the tank as normal, but also uses a TVS heat exchanger to cool the metallic injector itself as well as the main incoming liquid stream. Results show that using the TVS augmented injector simplifies transfer operation via enhanced condensation at the injector surface at the cost of sacrificing only a small amount of propellant.

Thermodynamic Vent System↗
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 NTRS2026

Remote Sensing-Driven Hydrodynamic Modeling in Data-Scarce Regions: Integrating ICESat-2, Sentinel-2, SWOT and Re-analysis Models for Coastal Monitoring

Hydrodynamic models in coastal and estuarine systems are typically constrained by sparse bathymetry, boundary, and validation data, especially in regions where field campaigns are costly or impractical. Here we develop and test a fully satellite-driven framework for hydrodynamic modeling in South Africa’s Langebaan Lagoon without using any local in situ measurements. Bathymetry is derived by training multispectral Sentinel-2 reflectance against ICESat-2 ATL24 photon-derived depths using an XGBoost model optimized with Bayesian search. The final satellite-derived bathymetry reproduces independent ATL24 points with RMSE = 0.45 m and R 2 = 0.97. This bathymetry was used in a depth-averaged Delft3D Flexible Mesh model driven at the open boundary by TPXO tidal harmonics and by ERA5 winds. We validate modeled water surface elevation against 16 SWOT low-rate (250 m, unsmoothed) passes in 2023. SWOT–model comparisons yield an overall RMSE of 0.11 m and R 2 = 0.61, with typical point differences <0.10 m (∼7% of the 1.5 m tidal range), and showed consistent spatial gradients in water level from the offshore boundary, through Saldanha Bay, and into the lagoon. At the offshore boundary, TPXO and SWOT sea surface heights agree closely (R 2 = 0.86). A simple phase adjustment of ∼26,min between TPXO and SWOT lowers the RMSE from 0.18,m to 0.11,m, showing that phase offset accounts for some of the discrepancy, with additional errors likely linked to non-tidal signals. Our results demonstrate that combining passive optical, photon-counting LiDAR, radar interferometry, and global tidal/atmospheric models enables robust, transferrable hydrodynamic modeling in data-scarce coastal systems, offering a cost-effective pathway for monitoring.

ICESat-2↗
NASA NTRSDate not supplied

The Future of Oaks in the Santa Monica Mountains: A Case Study in Using Remote Sensing Data for Species Distributions Models

The Woolsey Fire began on November 8, 2018, and lasted for almost two weeks, during which it burned almost 100,000 acres of valuable landscape and habitat, including a vast area of woodland. The persistence of key woodland species provides aesthetic, monetary, and ecological value to the landscape through carbon sequestration, air temperature moderation, and erosion mitigation, among other ecosystem services. This study investigated the impact of the Woolsey Fire on native woodland species distributions and identified areas suitable for restoration within the Santa Monica Mountains National Recreation Area. The team partnered with the Resource Conservation District of the Santa Monica Mountains; National Park Service, Santa Monica Mountains National Recreation Area; California Department of Parks and Recreation, Los Angeles County Division; County of Los Angeles Fire Department, Prevention Services Bureau, Forestry Division; County of Los Angeles Department of Regional Planning; and the University of Montana. The Earth observations used include data from Landsat 8 Operational Land Imager, NASA ER-2 Jet Airborne Visible InfraRed Imaging Spectrometer, Shuttle Radar Topography Mission, and RapidEye. The team produced maps of burn severity from the Woolsey Fire, its impact on plant species distributions, and habitat suitability projections for 2050 and 2099 to assist partners in prioritizing areas for restoration. A plant community classification was successfully created using Multiple Endmember Spectral Mixture Analysis (MESMA). Overall accuracy was assessed at 90.54% by comparing the classification to validation pixels derived from ground truth information provided by our partners.

Roger Ly↗
NASA NTRSDate not supplied

A Machine Learning Framework for Error Compensation in Radiative Transfer Calculations

Radiative heat transfer influences the amount of heat flux transferred to the surface of the hypersonic vehicle, which is essential to evaluate the performance of thermal protection systems. The radiative heat flux is found to be computationally prohibitive while accounting for the variation in spatial, angular, and spectral domains. A new methodology has been recently developed to alleviate the cost of computation in the spectral domain by constructing flow-agnostic reduced-order models (ROMs). The developed spectral ROM databases provide grouping strategies that account for non-equilibrium absorption and emission as well as interaction between disparate species due to spectral overlap in associated radiative processes. However, the developed ROMs need to be optimized for a specific combination of interacting gas species and would need to re-calibrated in case individual species are added/omitted. In this work, we use various machine learning (ML) techniques to approximate the radiative intensities determined by a ROM optimized for a specific gas mixture. The ML model relies on the ROM databases developed for a single species which ignores any spectral overlap. Thus, radiation evaluation starts with a simple summation of radiative intensities predicted using these non-calibrated ROMs for the contributing species. The ML framework then provides a correction to account for the interplay in the frequency, i.e., emission of photons by one species and absorption by another, and yields mixture-specific radiation fields. Once trained on the individual ROM databases, the ML framework offers instantaneous corrections that serves as a time/cost effective alternative to the optimization of ROMs for a specific gas mixture. The ML framework is trained on both the high fidelity and ROM evaluated line of sight (LOS) data from Orion, Stardust, and FIRE II cases to obtain a general purpose correction model for earth re-entry scenarios when radiation contributions from both atomic nitrogen and atomic oxygen are considered. A geometric length scale parameter is used in the training process to account for errors introduced in the ROM databases as a consequence of high optical thickness. The efficacy of the ML framework is underscored through extensive analysis of train and test errors with respect to all the re-entry scenarios. The applicability of such an ML framework was further corroborated by embedding it in a state-of-the-art US3D - NERO system for determining the radiative heat flux transferred to the hypersonic vehicle surface.

Radiation↗
NASA NTRS1992

A computerized aircraft battery servicing facility

The latest upgrade to the Aerospace Energy Systems Laboratory (AESL) is described. The AESL is a distributed digital system consisting of a central system and battery servicing stations connected by a high-speed serial data bus. The entire system is located in two adjoining rooms; the bus length is approximately 100 ft. Each battery station contains a digital processor, data acquisition, floppy diskette data storage, and operator interfaces. The operator initiates a servicing task and thereafter the battery station monitors the progress of the task and terminates it at the appropriate time. The central system provides data archives, manages the data bus, and provides a timeshare interface for multiple users. The system also hosts software production tools for the battery stations and the central system.

Glover, Richard D.↗
NASA NTRS1980

Update of the IUE battery in-flight performance

The in-flight performance data of two 17-cell, 6-ampere-hour nickel cadmium spacecraft batteries are presented covering 22 months of operation. Fluctuations in the battery voltage and the battery temperature are presented for spacecraft movement throughout a beta range of 0 to 130 deg. The battery discharge voltages during the peak eclipse seasons, daily seasons, and daily eclipse periods are noted. Finally, the spacecraft data are compared to data from a 6-ampere-hour test pack and test flight data.

Tiller, S. E.↗
NASA NTRSDate not supplied

Enabling Mission Flexibility to Battery Driven Deep Space Endeavors With Generalized Battery-Health-Monitoring Using Physics-Based and Data-Driven Reduced-Order Models

The needs and requirements for an electrochemical energy storage for deep space exploration is well explored. It is often understood that different mission sites and environmental conditions require different battery chemistries or technologies. Additionally, various engineering solutions are deployed to overcome specific chemical challenges. One often overlooked need is the “health” monitoring of an electrochemical storage system. The term generalized health monitoring, as envisioned in this work, refers to the monitoring of various aspects such as electrode health, electrolyte health, reaction pathway health, cooling system health, sensor health, and BMS health [1]. Generalized health monitoring allows mission leads, engineers, and scientists to incorporate flexibility in mission designs, make on-the-fly mission changes, and extend the duration of science missions. Moreover, it enables automation and data-driven decision-making without compromising safety and performance. Recently, our group developed a hierarchy of thermal reduced-order models (TROM) by combining a physics-based modeling approach and data-driven model reduction techniques applied to flight data [2]. The resulting TROMs were found to be not only accurate but also identifiable from the flight data. Consequently, the coefficient of variance of the model parameters is small over the course of hundreds of flights, allowing for monitoring the parameter evolution trajectories as the battery ages and degrades. These parameters constitute the metrics of the generalized health of a battery. Monitoring their evolution allows such models to be used for anomaly detection and prognostics, improving early detection of abnormal behavior and thus enabling timely maintenance, longer battery life, and enhanced battery safety. For this presentation, the practicality of the thermal model will be validated on a pack of 14cells under various topology configurations such as 1S14P, 2P7S, 7S2P, and 1P14S. It is well known that manufacturing and non-uniform aging lead to variability in the performance of a cell, which is exacerbated by cell balancing during active load. Additionally, in extreme scenarios, the paramount objective is to complete the mission, regardless of the stresses on the battery. Topology-induced balancing issues further stress the battery. The goal of this study is to determine if the noise (identifiability) in the reduced-order thermal model parameters is sensitive to topology, cell spacing, cooling strategy, and manufacturing or age variability. The variability in cells is considered by assuming a multimodal distribution for microscopic parameters of a cell (such as porosity, tortuosity, reaction kinetics, volumetric thermal conductivity, and volumetric heat capacity). The compounded effect of manufacturing variability, topological selection, cooling strategies, and cell balancing ages each cell in a battery differently. The study aims to clarify whether the challenge in extracting maximum information depends on the minimum number of sensors or models used for data extraction.

Automation↗
NASA NTRS2026

The Future of in-Situ Sequencing-Based Microbial Monitoring: Development of a Shelf-Stable Method for Artemis and Beyond

Microbial monitoring onboard the International Space Station (ISS) is essential for assessing the efficiency of the Environmental Control and Life Support Systems (ECLSS) and providing insight into potential risk to both crew and spacecraft. Historically, this monitoring required the need to culture organisms onboard, return these cultures to Earth, and then complete the identifications, a process that would take months. Over the past decade, and through numerous payloads, advances in molecular biology have enabled in-flight microbial identifications using nanopore sequencing. The swab-to-sequencer method resulting from these efforts was transitioned from research to operations for microbial monitoring under the Crew Health Care Systems (CHeCS) BioMole. Collectively, these accomplishments have propelled the swab-to-sequencer method to be selected as the Microbial Surface Monitor (MSM) for Gateway, as well as a payload on Artemis IV. However, the lack of cold stowage availability for Artemis requires modifications to the entire method due to the thermal instability of the reagents required for sample preparation. To achieve this, new development, optimization, and validations were undertaken. Key considerations included enzyme concentration, buffer compatibility, and equal or enhanced sensitivity and specificity. At each step, thorough side-by-side comparisons with the current ISS method were performed. The development of a robust shelf-stable method will ensure continued sequencing-based microbial monitoring for Artemis and beyond, providing data in near real-time, enhancing risk response time, and yielding clear insight into the microbiome of spacecraft.

Christian G Mena↗
NASA NTRS1988

Bipolar-Battery Construction

Bipolar batteries fabricated in continuous quasi-automated process. Components of battery configured so processing steps run sequentially. Key components of battery, bipolar plate and bipolar separator, fabricated separately and later joined together.

Rippel, Wally E.↗
NASA NTRS1994

Orbital Processing of High-Quality CdTe Compound Semiconductors

CdZnTe crystals were grown in one-g and in micro-g for comparative analysis. The two micro-g crystals were grown in the Crystal Growth Furnace during the First United States Microgravity Laboratory mission (USML-1). The samples were analyzed for chemical homogeneity, structural perfection, and optoelectronic performance (infrared transmission). Fourier Transform Infrared (FTIR) transmission of both ground and flight materials showed that the infrared transmission was close to theoretical, 63% versus 66%, suggesting that the material was close to the stochiometric composition during both the ground and flight experiments. Infrared microscopy confirmed that the principal precipitates were Te and their size (1-10 microns) and density suggested that the primary flight and ground base samples experienced similar cooling rates. Macrosegregation was predicted, using scaling analysis, to be low even in one-g crystals and this was confirmed experimentally, with nearly diffusion controlled growth achieved even in the partial mixing regime on the ground. Radial segregation was monitored in the flight samples and was found to vary with fraction solidified, but was disturbed due to the asymmetric grvitational and thermal fields experienced by the flight samples. The flight samples, however, were found to be much higher in structural perfection than the ground samples produced in the same furnace under identical growth conditions except for the gravitational level. Rocking curve widths were found to be substantially reduced, from 20/35 (one-g) to 9/20 (micro-g) for the best regions of the crystals. The full width at half maximum (FWHM) of 9 arc seconds is as good as the best reported terrestrially for this material. The ground samples were found to have a fully developed mosaic structure consisting of subgrains, whereas the flight sample dislocations were discrete and no mosaic substructure was evident. The defect density was reduced from 50-100,000 (one-g) to 500-25000 EPD (micro-g). These results were confirmed using rocking curve analysis, synchrotron topography, and etch pit analysis. The low dislocation density is thought to have resulted from the near-absence of hydrostatic pressure which allowed the melt to solidify with minimum or no wall contact, resulting in very low stress being exerted on the crystal during growth or during post-solidification cooling.

D J Larson, Jr.↗
NASA NTRS1992

LDEF experiment M0003 meteoroid and debris survey

A survey of the meteoroid and space debris impacts on LDEF experiment M0003 was performed. The purpose was to document impact phenomenology and to obtain impact crater data for comparison to current debris and micrometeoroid models. The survey consists of photomicrographs of significant impacts in a variety of material types, accurate measurements of impact crater coordinates and dimensions for selected experiment surfaces and data basing of the crater data for reduction, manipulation, and comparison models. Large area surfaces which were studied include the experiment power and data system sunshields, environment exposure control canister sunshields, and the M0003 signal conditioning unit covers. Crater diameters down to 25 microns were measured and catalogued. Both leading and trailing edge surfaces were studied and compared. The results shows the different response of materials to hypervelocity impacts. Comparison of the data to curves derived from the Kessler debris model and the Cour-Palais micrometeoroid model indicates a marked tendency for overprediction of small impacts and underprediction of large impacts with there being better agreement for the medium sized impacts. Representative impact data is presented.

M. J. Meshishnek↗