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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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At least 19 records
All sourcesNASA NTRSDOE OSTI
NASA NTRS1971

Facsimile bandwidth compression using nonlinear analog processing.

A system is presented for reducing the number of picture elements in a scanned image by an order of magnitude while preserving the detail contrast. Starting with high-resolution data a 3 x 3 matrix of input elements is compressed into a single output element using a nonlinear algorithm. Optimum results are obtained by including the data on the outer periphery of the input sample in the processing algorithm thus requiring a 5 x 5 input matrix. Experimental results are presented using weather satellite photographs. This system has application in those cases where the sensor has higher resolution capability than the communication link can support.

Macovski, A.↗
NASA NTRS1971

In-situ measurement of objective lens data of a high-resolution electron microscope.

Bragg-reflex images of small individual crystallites in the size range of 20-100 A diameter with known crystallographic orientation were used in a transmission electron microscope to determine in-situ: (a) the relationship between objective lens current (or accelerating voltage) changes in discrete steps and corresponding defocus, (b) the spherical aberration coefficient, and (c) the axial chromatic aberration coefficient of the objective lens. The accuracy of the described method is better than 5%. The same specimen can advantageously be used to properly aline the illuminating beam with respect to the optical axis.

Heinemann, K.↗
NASA NTRS1985

Satellite remote sensing for ice sheet research

Potential research applications of satellite data over the terrestrial ice sheets of Greenland and Antarctica are assessed and actions required to ensure acquisition of relevant data and appropriate processing to a form suitable for research purposes are recommended. Relevant data include high-resolution visible and SAR imagery, infrared, passive-microwave and scatterometer measurements, and surface topography information from laser and radar altimeters.

Thomas, R. H.↗
NASA NTRS1971

Automated cloud tracking using precisely aligned digital ATS pictures.

An interactive man-computer system, termed WINDCO, which was developed to measure cloud motions from pictures obtained by the ATS-I and ATS-III satellites, is described. The system will measure motions to at least three knots at moderate cost in a real-time environment. Accuracy could be improved by a factor of 4 by incorporating high-resolution visible SMS data.

Smith, E. A.↗
NASA NTRS1972

Spectrophotometry of the 1.5-micron window of Jupiter.

The limb darkening of the 1.5-micron region and the variations of ammonia and methane absorptions over the Jovian belts, zones, and spots are studied on the basis of high-resolution infrared spectrometric data obtained for 86 areas on the Jovian surface. It is shown that the absorptions increase with increasing air mass between the equator and the poles, that they decrease linearly with increasing air mass between the central meridian and the limbs, and that the absorptions over the South Tropical Zone are greater and those over the Great Red Spot are smaller than the absorptions for other features. An ammonia absorption map of the planet is plotted for the period April-June, 1970.

Binder, A. B.↗
NASA NTRSDate not supplied

NASA POWER: Providing Analysis-Ready, Cloud-Optimized Data for AI /ML Training and Applications in Earth Science

As global demand for sustainable development grows, the integration of Earth Observation (EO) data into decision making frameworks has become a primary objective for the scientific community. The NASA Prediction of Worldwide Energy Resources (POWER) project serves as a bridge between NASA EO data and the specialized needs of the renewable energy, sustainable infrastructure and agroclimatology communities. In this poster presentation we will present an overview of POWER data products and services along with its use in diverse research to decision-making workflows. By providing over 40 years of high-resolution historical, hourly and daily solar and meteorological data, POWER transforms satellite observations and global model reanalysis into actionable, Analysis-Ready Dataset (ARD). Currently, the project delivers over 250 industry-friendly parameters to the users from different NASA datasets like CERES SYN1Deg, MERRA-2, and IMERG alongside downscaled CMIP6 climate model data, fulfilling over 16 million requests from 50,000 unique users monthly. To ensure data quality and traceability, these parameters are rigorously validated against the ground-based observations from the Baseline Surface Radiation Network (BSRN) and the Global Surface Summary of the Day (GSOD) – these results will be discussed in the presentation. A newly introduced web-based PaRameter Uncertainty ViEwer (PRUVE) tool will be presented that provides an online validation platform to the users that benchmarks satellite-based and assimilation data products against these surface measurements. To reduce technical barriers to data adoption, POWER data is accessible through RESTful APIs, ESRI ArcGIS Image Services, a web-based Data Access Viewer tool, allowing users to visualize, validate and apply the dataset. For efficient data delivery POWER data is cloud-optimized into Zarr datastore accessible through NASA managed Amazon S3 ensures high-performance allowing users to integrate EO directly into operational pipelines. These customized services will be presented. Use cases from application will be presented from the energy sector - such as for design of generation systems, performance monitoring of solar power plants, in infrastructure sector- optimizing building energy efficiency and thermal comfort, in agriculture – such as driving crop simulation and yield forecasting models to enable climate resilient farming. Furthermore, the shift toward machine learning (ML) in EO research that has positioned POWER as a key provider for training datasets which will be discussed. Use-cases will be presented to showcase how NASA data is enabling the development of predictive tools for climate variability and resource management. The poster will present POWER’s future plans including technology development to enhance data traceability and reproducibility and improving I/O performance to support the rapid integration of new EO products, ensuring that POWER remains a robust scalable backend for the evolving landscape of AI-driven Earth Science. Additionally, POWER is developing an AI Agent and an MCP-Server to enable industry AI-Agentic workflows.

Neha Khadka↗
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

Proactive Wildfire Management: A Remote Sensing and Multimodal CNN-MLP Architecture for Ignition Risk Forecasting

As the frequency and intensity of wildfires increase, with fire seasons now starting earlier and ending later than they have over the past decades, current monitoring systems, such as lookout towers and satellites, are hindered by cloud cover, low-resolution imagery, and static data gaps that fail to track vegetation moisture levels fast enough to catch rapid pre-ignition changes. This report proposes a Machine Learning-enabled Wildfire Ignition Prediction framework that combines satellite monitoring with dynamic and high-resolution remote sensing from Unmanned Aerial Vehicle (UAV) swarms. The method would use multispectral and thermal data from the Landsat program to create a baseline for vegetation health, calculating a two-band Enhanced Vegetation Index (EVI2) and the moisture content of the vegetation. These inputs will later be fused with microscale UAV weather data, including thermal hotspots found through thick canopies, hyperspectral chemical signatures of pre-visual combustion, and local weather streams. The multispectral satellite, multispectral Light Detection and Ranging (LiDAR), and thermal data would then be processed through a Convolutional Neural Network (CNN), alongside a Multilayer Perceptron (MLP) for the micro-weather telemetry. The outputs of these networks would be fused into a single feature representation and passed through a final prediction network to generate real-time ignition risk scores and hotspot alerts. Model performance would be assessed using standard classification metrics, including a Receiver Operating Characteristic - Area Under the Curve (ROC AUC) and F1 score. This system would allow first responders to identify high-risk zones and intervene before ignition occurs, improving emergency response time compared to current approaches.

machine learning↗
NASA NTRS1972

Ogo 5 magnetic-field data near the earth's bow shock - A correlation with theory.

Magnetic-field data obtained in the earth's bow-shock region with a high-resolution triaxial fluxgate magnetometer aboard the Ogo 5 satellite have been correlated with a theory of Tidman and Northrop (1968). These authors have shown that either of two hypotheses about the nature of low-frequency magnetic waves could be invoked to explain previous observations. We have observed exponentially decaying upstream waves that are consistent with only one of these hypotheses. This observation allows use of the theory to infer the local shock velocity and frequency of driving currents within the shock. This method of finding the shock velocity is less sensitive to errors in the plasma parameters than is the method based on the Rankine-Hugoniot relations.

Guha, J. K.↗
NASA NTRS1971

Rocket measurement of OH in the mesosphere.

A volume density profile of the OH radical throughout the 45- to 70-km region of the earth's upper atmosphere is presented. A high-resolution polarized Ebert-Fastie spectrometer flown aboard a sounding rocket was used to obtain the data. The molecule was found to have a scale height significantly greater than that of the atmosphere, with local densities of 4.4 million/cu cm at 50 km, 5.5 million/cu cm at 60 km, and 3.5 million/cu cm at 70 km.

Anderson, J. G.↗
NASA NTRS1971

Electron microscopy and diffraction of layered, superconducting intercalation complexes.

Several layered, transition metal dichalcogenide intercalation complexes with unique superconducting properties have been examined by high-resolution electron microscopy and electron diffraction. Details of the crystalline lattice and of the lattice imperfections have been directly resolved. The results can be correlated with the available X-ray diffraction and chemical data, and they confirm and extend the postulated models.

Fernandez-Moran, H.↗
NASA NTRS1972

Photographic summary

The photographic objectives of the Apollo 15 mission were designed to support a wide variety of scientific and operational experiments, to provide high-resolution panoramic photographs and precisely oriented metric photographs of the lunar surface, and to document operational tasks on the lunar surface and in flight. Detailed premission planning integrated the photographic tasks with the other mission objectives to produce a balanced mission that has returned more data than any previous space voyage. The return of photographic data was enhanced by new equipment, the high latitude of the landing site, and greater time in lunar orbit. New camera systems that were mounted in the scientific instrument module (SIM) bay of the service module provided a major photographic capability that was not available on any previous lunar mission, manned or unmanned.

Dietrich, J. W.↗
NASA NTRS1971

The Jimsonde - A high resolution temperature sensor.

The Jimsonde, a high-resolution lightweight temperature sensor developed for use with the FPS-16 Radar/Jimsphere wind system, and its related systems are discussed; and an error analysis that shows the sonde to have an rms error of 0.41 C at sea level and 0.56 C at 18 km is presented. Five flight tests, a sequence of four tests and one individual test, of the Jimsonde were made. For comparative purposes, radiosonde temperature data are presented along with the Jimsonde data.

Camp, D. W.↗
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 NTRS2004

Ejecta Generation and Redistribution on 433 Eros: Modeling Ejecta Launch Conditions

The NEAR-Shoemaker mission to asteroid 433 Eros presents an unprecedented opportunity to gain fundamental new knowledge about the processes governing regolith formation and redistribution on small bodies. NEAR-Shoemaker’s high-resolution imaging of the surface of Eros makes the asteroid a valuable and heretofore unparalleled laboratory for the detailed study of impact ejecta reaccretion and regolith redistribution on low-gravity (of order 10 -3 g) objects. Regolith is produced on asteroids by impact cratering, and the existence of regolith on the smallest solar system bodies supports the view that some of the ejecta from impact events on such objects may be retained. Impact craters and retained ejecta on low-gravity objects like Eros represent valuable natural laboratories for evaluating various models of impact cratering processes, since they may present crater structures or ejecta features that either do not form or are hidden on higher-gravity bodies like the Moon. Further, quantifying the extent to which impact processes generate and redistribute regoliths on small body surfaces (excavation depths, retained fraction, turnover timescales, etc.) is pivotal to the issue of how to relate meteoritical samples to their asteroidal parent bodies when surficial processes ( i.e., “space weathering”) may disguise or cover up underlying material and confound the ability of remote sensing techniques to provide reliable mineralogical assays of the parent objects. The rich variety of data on Eros’ regolith properties and distribution returned by NEAR-Shoemaker now require detailed analysis in order to take full advantage of the clues these observations offer for elucidating details of the impact cratering process on small bodies. Complicating simple interpretations of crater and ejecta morphology are dynamical effects on ejecta emplacement resulting from Eros’ irregular shape, rapid (5.27 hr) rotation, and low gravity. Figure 1 shows the very different ejecta deposit morphology that can result if the effects of rotation alone are neglected. Considering the additional complicating factors of Eros’ irregular shape and complex gravitational field, simple calculations of the extent and thickness of ejecta blankets and the spatial distribution of ejecta blocks from basic crater scaling laws or numerical hydrocodes alone do not suffice. In order to fully interpret the suite of NEAR-Shoemaker observations of regolith features across the surface of Eros and to evaluate various impact models for specific craters on the asteroid, detailed dynamical modeling of the deposition of crater ejecta from those craters is required . Here, I describe some modifications and improvements to the dynamical model being used for these studies.

D D Durda↗
NASA NTRS2026

Petermann Glacier on the Brink: Progress, Challenges and Insights

Petermann Glacier, the largest marine-terminating glacier in northern Greenland based on catchment area and ice discharge, plays a key role in regulating ice discharge from the Greenland Ice Sheet into the Arctic Ocean. With an upstream catchment connected to the ice sheet interior via a deep subglacial canyon, its future stability has major implications for sea level rise. In this review, we synthesize recent advances in understanding Petermann’s dynamics across three critical interfaces: the ice–ocean, ice–atmosphere, and ice–bed boundaries. At the surface, observations show that reanalysis products underestimate air temperatures and melt, while regional climate models diverge significantly in their estimates of surface mass balance, underscoring the need for improved in situ data and models. At the ocean boundary, enhanced basal melting driven by both subglacial runoff and Atlantic water intrusions is identified as the dominant driver of recent mass loss of Petermann Glacier, with continued warming posing a serious threat to the stability of the floating tongue. At the bed, new geophysical synthesis reveals complex geology, likely spatial variability in geothermal heat flux, and the influence of the megacanyon on seasonal hydrology and velocity fluctuations. Petermann’s mass balance has been negative in recent decades without corresponding flow acceleration. However, the glacier has undergone significant calving events, and the current rifting that began in September 2025 highlights its vulnerability. This upcoming calving event underscores the timeliness of this review, as it will put Petermann Glacier’s terminus at its most retreated position since records began in 1923. The anticipated retreat of the ice tongue also reduces buttressing and brings the terminus closer to the grounding zone, and modeling studies suggest that calving within 12 km of the grounding zone could potentially trigger dynamic retreat, accelerating ice discharge, and a doubling of flow speeds. We conclude that improved observations, sustained monitoring of oceanographic and atmospheric properties, and high-resolution modeling are critical to constraining projections of Petermann Glacier’s future and its role in the stability of the Greenland Ice Sheet.

Dominik Fahrner↗