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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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All sourcesNASA NTRSDOE OSTI
NASA NTRS1992

Analysis of LDEF micrometeoroid/debris data and damage to composite laminates

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.

R. C. Tennyson↗
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↗
NASA NTRS2008

An Investigation of State-Space Model Fidelity for SSME Data

In previous studies, a variety of unsupervised anomaly detection techniques for anomaly detection were applied to SSME (Space Shuttle Main Engine) data. The observed results indicated that the identification of certain anomalies were specific to the algorithmic method under consideration. This is the reason why one of the follow-on goals of these previous investigations was to build an architecture to support the best capabilities of all algorithms. We appeal to that goal here by investigating a cascade, serial architecture for the best performing and most suitable candidates from previous studies. As a precursor to a formal ROC (Receiver Operating Characteristic) curve analysis for validation of resulting anomaly detection algorithms, our primary focus here is to investigate the model fidelity as measured by variants of the AIC (Akaike Information Criterion) for state-space based models. We show that placing constraints on a state-space model during or after the training of the model introduces a modest level of suboptimality. Furthermore, we compare the fidelity of all candidate models including those embodying the cascade, serial architecture. We make recommendations on the most suitable candidates for application to subsequent anomaly detection studies as measured by AIC-based criteria.

Space Shuttles↗
NASA NTRSDate not supplied

Introduction to the JPSS-2 Advanced Technology Microwave Sounder (ATMS) Government Calibration Data Book (GCDB)

The third Advanced Technology Microwave Sounder (ATMS) is an instrument onboard the Joint Polar Satellite System (JPSS), JPSS-2 (renamed NOAA-21 in orbit) mission. This report is to introduce the JPSS-2 Government Calibration Data Book (J2 GCDB) for ATMS, SN 304. This J2 GCDB document contains key information generated during the calibration testing campaign that is driving parameters for radiometric performance. This document also contains supporting data that augments the calibration results. The values in this document are utilized by ATMS’s calibration packet which is, in turn, an integral component in the interpretation of science data. The calibration data in this report was collected from tests such as shelf-level testing, antenna testing, instrument thermal vacuum (TVAC) testing; satellite TVAC testing; and JPSS-2 post-launch tests. JPSS-2 was launched on November 10, 2022. In the subsequent years, the Government will release an ATMS GCDB for each JPSS mission. We expect that all public users can download these ATMS GCDBs from the NOAA operational Integrated Calibration and Validation System (ICVS) website, see more discussions below. The goal of this GCDB is to demonstrate how to characterize ATMS measurements using JPSS-2 ATMS on-orbit operational data and to provide relevant explanations. This document serves as a primary public domain reference for calibrating operational ATMS Raw Data Records (RDR) science data, as used in the current operational Interface Data Processing Segment (IDPS) system. This same RDR science data is distributed through direct broadcast (DB) to DB users for use in their ground processing systems. This J2 GCDB provides the results of the ATMS system radiometric calibration, the antenna flat reflector emissivity [1], the antenna pattern measurements, the antenna pattern corrected brightness temperature [2], the brightness temperature of the lunar disk [3], Lunar Intrusion (LI) correction algorithm [4], receiver spectral parameters, and mechanical alignment on-orbit pointing results, and the striping effect appeared significantly in S-NPP on-orbit radiance data when the data are compared to the Radiative Transfer Model (RTM) simulation in numerical weather prediction (NWP) system [5]. It also provides the parameters required for conversion of telemetry counts to engineering units, for radiometric calibration, and for antenna beam geo-location. Moreover, it provides JPSS-2 ATMS Spectral Response Functions data, some additional information related to ATMS on-orbit performance, on-orbit lunar intrusion correction parameters and Earth contamination bias, and on how to derive ATMS RDR, antenna Temperature Data Records (TDR), and Sensor Data Records (SDR). Furthermore, an introduction of NOAA operational Integrated Calibration and Validation System (ICVS) website and services is added in this J2 GCDB. This ICVS hosts a long-term monitoring system which allows to visualization and comparison of data from JPSS missions, NOAA legacy Polar Operational Environmental Satellites (POES), and Geostationary Operational Environmental Satellites (GOES). From NOAA Comprehensive Large Array-data Stewardship System (CLASS), the public users can download all JPSS ATMS data products for all JPSS missions.

Microwave Sounder↗
NASA NTRS1988

Space Station battery system design and development

The Space Station Electric Power System will rely on nickel-hydrogen batteries in its photovoltaic power subsystem for energy storage to support eclipse and contingency operations. These 81-Ah batteries will be designed for a 5-year life capability and are configured as orbital replaceable units (ORUs), permitting replacement of worn-out batteries over the anticipated 30-year Station life. This paper describes the baseline design and the development plans for the battery assemblies, the battery ORUs and the battery system. Key elements reviewed are the cells, mechanical and thermal design of the assembly, the ORU approach and interfaces, and the electrical design of the battery system. The anticipated operational approach is discussed, covering expected performance as well as the processor-controlled charge management and discharge load allocation techniques. Development plans cover verification of materials, cells, assemblies and ORUs, as well as system-level test and analyses.

Haas, R. J.↗
NASA NTRS1996

Space Electrochemical Research and Technology

Individual papers presented at the conference address the following topics: development of a micro-fiber nickel electrode for nickel-hydrogen cell, high performance nickel electrodes for space power application, bending properties of nickel electrodes for nickel-hydrogen batteries, effect of KOH concentration and anions on the performance of a Ni-H2 battery positive plate, advanced dependent pressure vessel nickel hydrogen spacecraft cell and battery design, electrolyte management considerations in modern nickel hydrogen and nickel cadmium cell and battery design, a novel unitized regenerative proton exchange membrane fuel cell, fuel cell systems for first lunar outpost - reactant storage options, the TMI regenerable solid oxide fuel cell, engineering development program of a closed aluminum-oxygen semi-cell system for an unmanned underwater vehicle, SPE OBOGS on-board oxygen generating system, hermetically sealed aluminum electrolytic capacitor, sol-gel technology and advanced electrochemical energy storage materials, development of electrochemical supercapacitors for EMA applications, and high energy density electrolytic capacitor.

Richard M Wilson↗
NASA NTRS2026

Updated global and regional trends of stratospheric ozone profiles

We present updated evaluation of stratospheric ozone profile trends in the 60° S–60°N latitude range using long-term ground-based and satellite climate data records, as well as simulations by chemistry-climate models. The trends are evaluated using the LOTUS (Long-term Ozone Trends and Uncertainties in the Stratosphere) regression model. Analyses of satellite data confirm the statistically significant positive ozone trends in the period 2000–2024 in the upper stratosphere of ~1–3% per decade, with larger trends at mid-latitudes compared to the tropics. The trends are slightly positive or close to zero in the middle stratosphere, and mostly negative, -1 to -2% per decade, in the lower stratosphere, but they are not statistically significant. The morphology and magnitude of ozone trends are similar to previous analyses (2000–2020 trends). Ozone trends in 2000–2024 predicted by chemistry-climate model simulations are in good agreement with combined satellite trends. In the upper stratosphere, models predict a slightly stronger ozone recovery than observations. In the lower stratosphere, both models and satellite observations report negative trends in the tropics, while modelled ozone trends are slightly positive at mid-latitudes. Ozone profile trends over several stations estimated from ground-based records capture the same overall vertical pattern of ozone trends as merged gridded satellite datasets. Analyses of regional ozone profile trends in 2003–2024 using merged satellite datasets confirmed the previous observations of a longitudinal structure in ozone trends in the NH mid-latitude stratosphere, with positive trends over Scandinavia and negative trends over Siberia. However, the magnitude of this dipole-like structure is reduced compared to previous analyses.

trends↗
NASA NTRS1998

Change Detection Analysis in Urban and Suburban Areas Using Landsat Thematic Mapper data: Case of Huntsville, Alabama

Two Landsat Thematic Mapper (TM) images, from July 1984 and July 1992, were used to identify land use/cover changes in the urban and suburban fringe of the city of Huntsville, Alabama. Image difference was the technique used to quantify the change between the two dates. The eight-year period showed a 16% change, mainly from agricultural lands to urban areas generated by the settlement of industrial, commercial, and residential areas. Visual analysis of the change map (i.e., difference image) supported this phenomenon by showing that most changes were occurring in the vicinity of the major roads and highways across the city.

Dana Kuan↗
NASA NTRS1993

Data Analysis for GOPEX Image Frames

This article describes the data analysis based on the image frames received at the Solid State Imaging (SSI) camera of the Galileo Optical Experiment (GOPEX) demonstration conducted between December 9 and 16, 1992. Laser uplink was successfully established between the ground and the Galileo spacecraft during its second Earth-gravity-assist phase in December 1992. SSI camera frames were acquired which contained images of detected laser pulses transmitted from the Table Mountain Facility (TMF), Wrightwood, California, and the Starfire Optical Range (SOR), Albuquerque, New Mex/co. Laser pulse data were processed using standard image-processing techniques at the Multimission Image Processing Laboratory (MIPL) for preliminary pulse identification and to produce public re/ease images. Subsequent image analysis corrected for background noise to measure received pulse intensities. Data were plotted to obtain histograms on a dmly basis and were then compared with theoretical results derived from applicable weak-turbulence and strong-turbulence considerations. This article describes processing steps and compares the theories with the experimented results. Quantitative agreement was found in both turbulence regimes, and better agreement would have been found, given more received laser pulses. Future experiments should consider methods to reliably measure low-intensity pulses, and through experimented planning to geometrically locate pulse positions with greater certainty.

B M Levine↗
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 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 NTRS2026

Fuel Heating System Design and Thermal Modeling for Aviation Combustion Research

Aviation fuels offer substantial heat-sink capability that can be applied to aircraft thermal-management strategies and advanced propulsion-system concepts. Accurate control of fuel temperature is critical for understanding combustion behavior and supporting high temperature fuel experimental studies. This work describes the modeling and experimental validation of a portable, high temperature fuel-conditioning system designed for multiple NASA Glenn Research Center’s combustion facilities. The system utilizes a circulating-oil heating unit and modular tube-in-tube heat exchangers capable of conditioning Jet-A to temperatures approaching 600 K. A Thermal Desktop model was created to analyze heat exchanger configurations and predict performance across a range of operating conditions. Model predictions were compared with measurements collected in the CE-13C test facility, showing good agreement across the tested flow range except at low fuel flow rate around 2 kg/hr. Results provide guidance for sizing future fuel heating system for combustion research applications.

Jet fuel heating system↗
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

NASA Talks: Space Shuttle Columbia - Lessons Learned: Columbia Launch and Recovery

On February 25, 2026, this NASA Talk was held regarding the Space Shuttle Columbia (Columbia Launch & Recovery). Crew & Thermal System Division (EC) partnered with Kennedy Space Center (KSC) and Engineering Directorate (EA) to bring this talk to Johnson Space Center (JSC) centering on what led up to and transpired after the Space Shuttle Columbia accident. Some recovered debris was on exhibit during the talk. Retired NASA Columbia Vehicle Manager Scott Thurston presented this talk. Mr. Thurston brings a wealth of knowledge from his mission experience. This talk was timely and a solemn reminder of the critical importance of diligence, safety, and excellence in our work. EA Director Julie Kramer White welcomed the 400+ center-wide in-person audience, and EC Division Chief Rubik Sheth introduced the speakers. This event was held in the JSC Teague Auditorium, recorded, and executed by the EC in-house STAR Productions team. This record includes an mp4 video presentation with a run time of 36 min. 20 sec.; in color; with sound.

NASA Talks↗
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 NTRS1963

The NERVA Engine Program

The objective of the NERVA engine program is the development of a nuclear rocket engine for use in space missions. The letters N E R V A mean Nuclear Engine for Rocket Vehicle Application. NERVA is a long-range program that had its beginning in about 1955 when the Los Alamos Scientific Laboratory began preliminary studies on the feasibility of thermal reactors for rocket application. At about the same time, the Livermore Laboratory began parallel studies, but this dual effort was discontinued about a year later. In 1961 an industrial contractor team, the Aerojet-General Corporation and the Westinghouse Electric Corporation, was selected to carry out the development of the NERVA engine, and their activity began in mid-1961. Aerojet was made the prime contractor with responsibility for the complete engine development program, and Westinghouse was made a principal subcontractor with responsibility for the development of the reactor. A government field office, the Cleveland Extension of the Space Nuclear Propulsion Office, was set up to manage this development program. This office is located in Cleveland because of the availability of technical backup at the Lewis Research Center.

Lester C Corrington↗