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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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387 records · Page 3

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

Thermal Data-driven Model Reduction for Enhanced Battery Health Monitoring

Electric aviation faces a major challenge of avoiding potentially catastrophic consequences of the battery’s thermal runaway while keeping the weight of the battery low. Detection of early warning signals of battery failures requires accurate monitoring of the battery’s health throughout its lifespan. However, identifying the parameters of the battery from field data is notoriously difficult. We investigate this problem within the framework of modeling the temperature dynamics of a Li-ion cell during tests simulating loading in electric aircraft flights. It is found that the parameters of a higher-fidelity physics-based thermal model cannot be identified from the simulated flight data. To resolve this issue, we reduce the higher-fidelity thermal model to a model with fewer parameters. The resulting reduced-order model can predict temperature dynamics accurately and is identifiable throughout the cell’s lifespan which allows using the model’s parameters to monitor the state-of-health of the aging cell and detect anomalies in thermal behavior.

Li ion batteries

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

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

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

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

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

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

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

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.

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.

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

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

Introduction to Flight Test Engineering [Introduction Aux Techniques Des Essais En Vol]

Flight test is at the core of what organizations must do in order to validate the operation and systems on an aircraft. While the AGARDograph series 300 and 160 series deal with aspects of this testing, this volume pulls it all together as an introduction to the process required to do effective flight test engineering. This volume was originally published in 1995. Its utility has been proven in that many flight test organizations and universities have requested copies for their engineers and students. It was felt that re-issuing it in a new format designed for electronic publication would be valuable to the community. This second printing changes none of the text, but rather reformats it. All the original references to AGARD (instead of RTO) are left in place so that none of the flavor of the original publication is lost. This is the Introductory Volume to the Flight Test Techniques Series. It is a general introduction to the various activities and aspects of Flight Test Engineering that must be considered when planning, conducting, and reporting a flight test program. Its main intent is to provide a broad overview to the novice engineer or to other people who have a need to interface with specialists within the flight test community. The first two Sections provide some insight into the question of why flight test and give a short history of flight test engineering. Sections 3 through 10 deal with the preparation for flight testing. They provide guidance on the preliminary factors that must be considered; the composition of the test team; the logistic support requirements; the instrumentation and data processing requirements; the flight test plan; the associated preliminary ground tests; and last, but by no means least, discuss safety aspects. Sections 11 through 27 describe the various types of flight tests that are usually conducted during the development and certification of a new or modified aircraft type. Each Section offers a brief introduction to the topic under consideration, and the nature and the objectives of the tests to be conducted. It lists the test instrumentation (and, where appropriate, other test equipment and facilities) required, describes the test maneuvers to be executed, and indicates the way in which the test data is selected, analyzed, and presented. The various activities that should take place between test flights are presented next. Items that are covered are: who to debrief; what type of reports to send where: types of data analysis required for next flight; review of test data to make a comparison to predicted data and some courses of action if there is not good agreement; and comments on selecting the next test flight. The activities that must take place upon completion of the test program are presented. The types of reports and briefings that should take place and a discussion of some of the uses of the flight test data are covered. A brief forecast is presented of where present trends may be leading.

Test facilities

Battery test expert systems

The characteristics of NIHBES (nickel-hydrogen battery expert system) are described, with attention also given to NICBES-2 (nickel-cadmium battery expert system-2). The nickel-hydrogen battery testbed is set up almost identically to the nickel-cadmium battery testbed, with the exceptions of no battery protection and reconditioning circuits (BPRCs) and the frequency of transmission of data. The Ni-H2 testbed has no BPRCs and the data are transmitted every 30 s instead of every minute. An expert system shell was chosen to develop this particular expert system. The GoldWorks expert system shell from Gold Hill Computers was chosen for the task. NIHBES will extract the desired data and return fault diagnosis, status and advice, and decision support. Expert systems have been proven to be viable tools in the control and monitoring of space power systems. Presently, the DDAS (digital data acquisition system) monitors and controls the orbit time, and is responsible for limit checking, data acquisition, and data summaries. It is concluded that in the future control of the Hubble Space Telescope breadboard will be passed to NIHBES. NIHBES will be more beneficial to the testbed than the DDAS alone due to the limitations of the DDAS. The DDAS cannot provide long-term trend analysis, plotting capability, fault diagnosis, or advice.

Johnson, Yvette B.

Ni-cd Battery Life Expectancy in Geosynchronous Orbit

The feasibility of using nickel cadmium batteries as an alternate if flight qualified NiH2 batteries are not available is explored. Battery life expectancy data being a key element of power system design, an attempt is made to review the literature, life test data and in orbit performance data to develop an up to date estimate of life expectancy for NiCd batteries in a geosynchronous orbit.

Broderick, R. J.

Performance of AEA 80 Ah Battery Under GEO Profile

To date completed three Solar Dynamic Observatory SDO real-time eclipse seasons. Sony 18650HC has a low rate of capacity fade under GEO cycling regime. Real time test results correlate with accelerated GEO lifetest data and AEA capacity fade prediction tool. This data, together with other AEA test data, justify the SDO Project decision to baseline Lithium-Ion chemistry for the spacecraft battery.

Russel, N.