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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 109 records · Page 6
All sourcesNASA NTRSDOE OSTI
NASA NTRS1975

Saturn radio emission near 1 MHz

Emission from the direction of the planet Saturn was observed by the IMP-6 spacecraft at 15 frequencies between 375 and 2200 kHz during the period April 1971 to October 1972. The Saturnian radio bursts were identified in the IMP-6 data through an analysis of the phase of the observed modulated signal detected from the spinning dipole antenna. Initial data reduction has isolated approximately 12 storms whose occurrence corresponded to times in which the spacecraft had an unobstructed view in the direction of Saturn. These events persisted over periods between one and ten minutes. Over the span of 500 days of data another 10 to 20 Saturnian events may exist, but positive identification is confused by the presence of terrestrial noise as well as a geometric ambiguity with Jupiter. A power spectral analysis of the storm occurrence times indicates a weak periodicity at 10h 30m + or - 5m at some of the observing frequencies. The spectral character of the radiation was found analogous to that of Jupiter.

Brown, L. W.↗
NASA NTRS1983

EGRET - The high energy gamma ray telescope for NASA's Gamma Ray Observatory

The EGRET high energy gamma-ray telescope under development for NASA's Gamma Ray Observatory will have an energy range of approximately 12 to 30,000 MeV, energy resolution of about 15 percent FWHM over most of that range, an effective area of about 2000 sq cm at high energies, and single photon angular accuracy of approximately 2 deg at 100 MeV, less than 0.1 deg above 5 GeV. This instrument can locate strong sources to an accuracy of about 5 arc min. The instrument utilizes a set of digital spark chambers interleaved with tantalum foils for detection and identification of gamma-ray events, and a large NaI(Tl) scintillator for energy determination. The system is triggered by a coincidence matrix using two arrays of plastic scintillation counters and a large plastic scintillator anticoincidence dome that rejects incident charged particles.

Fichtel, C. E.↗
NASA NTRS2001

Wireless Subsurface Microsensors for Health Monitoring of Thermal Protection Systems on Hypersonic Vehicles

Health diagnostics is an area where major improvements have been identified for potential implementation into the design of new reusable launch vehicles in order to reduce life cycle costs, to increase safety margins, and to improve mission reliability. NASA Ames is leading the effort to develop inspection and health management technologies for thermal protection systems. This paper summarizes a joint project between NASA Ames and SRI International to develop 'SensorTags,' radio frequency identification devices coupled with event-recording sensors, that can be embedded in the thermal protection system to monitor temperature or other quantities of interest. Two prototype SensorTag designs containing thermal fuses to indicate a temperature overlimit are presented and discussed.

Milos, Frank S.↗
NASA NTRS2005

Crop Surveillance Demonstration Using a Near-Daily MODIS Derived Vegetation Index Time Series

Effective response to crop disease outbreaks requires rapid identification and diagnosis of an event. A near-daily vegetation index product, such as a Normalized Difference Vegetation Index (NDVI), at moderate spatial resolution may serve as a good method for monitoring quick-acting diseases. NASA s Moderate Resolution Imaging Spectroradiometer (MODIS) instrument flown on the Terra and Aqua satellites has the temporal, spatial, and spectral properties to make it an excellent coarse-resolution data source for rapid, comprehensive surveillance of agricultural areas. A proof-of-concept wide area crop surveillance system using daily MODIS imagery was developed and tested on a set of San Joaquin cotton fields over a growing season. This area was chosen in part because excellent ground truth data were readily available. Preliminary results indicate that, at least in the southwestern part of the United States, near-daily NDVI products can be generated that show the natural variations in the crops as well as specific crop practices. Various filtering methods were evaluated and compared with standard MOD13 NDVI MODIS products. We observed that specific chemical applications that produce defoliation, which would have been missed using the standard 16-day product, were easily detectable with the filtered daily NDVI products.

McKellip, Rodney↗
NASA NTRS2007

Transport in the Subtropical Lowermost Stratosphere during CRYSTAL-FACE

We use in situ measurements of water vapor (H2O), ozone (O3), carbon dioxide (CO2), carbon monoxide (CO), nitric oxide (NO), and total reactive nitrogen (NO(y)) obtained during the CRYSTAL-FACE campaign in July 2002 to study summertime transport in the subtropical lowermost stratosphere. We use an objective methodology to distinguish the latitudinal origin of the sampled air masses despite the influence of convection, and we calculate backward trajectories to elucidate their recent geographical history. The methodology consists of exploring the statistical behavior of the data by performing multivariate clustering and agglomerative hierarchical clustering calculations, and projecting cluster groups onto principal component space to identify air masses of like composition and hence presumed origin. The statistically derived cluster groups are then examined in physical space using tracer-tracer correlation plots. Interpretation of the principal component analysis suggests that the variability in the data is accounted for primarily by the mean age of air in the stratosphere, followed by the age of the convective influence, and lastly by the extent of convective influence, potentially related to the latitude of convective injection [Dessler and Sherwuud, 2004]. We find that high-latitude stratospheric air is the dominant source region during the beginning of the campaign while tropical air is the dominant source region during the rest of the campaign. Influence of convection from both local and non-local events is frequently observed. The identification of air mass origin is confirmed with backward trajectories, and the behavior of the trajectories is associated with the North American monsoon circulation.

Pittman, Jasna V.↗
NASA NTRS2007

Transport in the Subtropical Lowermost Stratosphere during the Cirrus Regional Study of Tropical Anvils and Cirrus Layers-Florida Area Cirrus Experiment

We use in situ measurements of water vapor (H2O), ozone (O3), carbon dioxide (CO2), carbon monoxide (CO), nitric oxide (NO), and total reactive nitrogen (NOy) obtained during the CRYSTAL-FACE campaign in July 2002 to study summertime transport in the subtropical lowermost stratosphere. We use an objective methodology to distinguish the latitudinal origin of the sampled air masses despite the influence of convection, and we calculate backward trajectories to elucidate their recent geographical history. The methodology consists of exploring the statistical behavior of the data by performing multivariate clustering and agglomerative hierarchical clustering calculations and projecting cluster groups onto principal component space to identify air masses of like composition and hence presumed origin. The statistically derived cluster groups are then examined in physical space using tracer-tracer correlation plots. Interpretation of the principal component analysis suggests that the variability in the data is accounted for primarily by the mean age of air in the stratosphere, followed by the age of the convective influence, and last by the extent of convective influence, potentially related to the latitude of convective injection (Dessler and Sherwood, 2004). We find that high-latitude stratospheric air is the dominant source region during the beginning of the campaign while tropical air is the dominant source region during the rest of the campaign. Influence of convection from both local and nonlocal events is frequently observed. The identification of air mass origin is confirmed with backward trajectories, and the behavior of the trajectories is associated with the North American monsoon circulation.

Pittman, Jasna V.↗
NASA NTRS2010

The EXIST Infra-Red Telescope System: Design and Performance

The Infra-Red Telescope is a critical element of the EXIST (Energetic X-Ray Imaging Survey Telescope) observatory. It is a passively cooled 1.lm visible/infrared telescope. The primary goal of the IRT is to obtain photometric and spectroscopic measurements of high redshift (>6) gamma ray burst afterglows to study the nature of these enigmatic events and their environments, and to use them as probes of the composition and ionization state of the intergalactic medium of the young universe. The IRT will provide a prompt follow up (within three minutes) of the transient discovered by the EXIST with exceptional NIR sensitivity (AB=24 in 100s) surpassing HST in the infrared due to its passively cooled (- 30 C) mirror. Its optical design and spectral coverage is tailored to the high redshift transient events that require prompt pointing, identification, accurate photometry and both low and high resolution spectroscopy. Here we describe the telescope, its instrument complement, and the cooling systems which provide its remarkable sensitivity

Moseley, Samuel H.↗
NASA NTRS2007

Solutions Network Formulation Report. Integrating Salinity Measurements from Aquarius into the Harmful Algal Blooms Observing System

This Candidate Solution suggests the use of Aquarius sea surface salinity measurements to improve the NOAA/NCDDC (National Oceanic and Atmospheric Administration s National Coastal Data Development Center) HABSOS (Harmful Algal Blooms Observing System) DST (decision support tool) by enhancing development and movement forecasts of HAB events as well as potential species identification. In the proposed configuration, recurring salinity measurements from the Aquarius mission would augment HABSOS sea surface temperature and in situ ocean current measurements. Thermohaline circulation observations combined with in situ measurements increase the precision of HAB event movement forecasting. These forecasts allow coastal managers and public health officials to make more accurate and timely warnings to the public and to better direct science teams to event sites for collection and further measurements.

Anderson, Daniel↗
NASA NTRS1984

Solar He-3-rich events and non-relativistic electron events: A new association

In 15 months of observation by the ISEE-e spacecraft, it was found that virtually all solar greater than or approximately equal to 1.3 MeV/nucleon He-3-rich events are associated with impulsive 2 to approximately 100 keV electron events, although many electron events were not accompanied by detectable He-3 increases. Both the He-3 and the electrons exhibit nearly scatter-free propagation in the interplanetary medium, and the times of onset and maximum for the He-3 and electron increases are closely related by velocity dispertion. The electron events and their related type III solar radio bursts provide, for the first time, identification of the flares which produce He-3-rich events. He-3 appears to be accelerated at the flash phase of solar flares along with nonrelativistic electrons.

Reames, D. V.↗
NASA NTRS2019

Episodes of Particle Ejection from the Surface of the Active Asteroid (101955) Bennu

Active asteroids are those that show evidence of ongoing mass loss. We report repeated instances of particle ejection from the surface of (101955) Bennu, demonstrating that it is an active asteroid. The ejection events were imaged by the OSIRIS-REx (Origins, Spectral Interpretation, Resource Identification, and Security–Regolith Explorer) spacecraft. For the three largest observed events, we estimated the ejected particle velocities and sizes, event times, source regions, and energies. We also determined the trajectories and photometric properties of several gravitationally bound particles that orbited temporarily in the Bennu environment. We consider multiple hypotheses for the mechanisms that lead to particle ejection for the largest events, including rotational disruption, electrostatic lofting, ice sublimation, phyllosilicate dehydration, meteoroid impacts, thermal stress fracturing, and secondary impacts.

Lauretta, D. S.↗
NASA NTRS1985

Solar He-3-rich events and nonrelativistic electron events - A new association

In 15 months of observation by the ISEE-e spacecraft, it was found that virtually all solar greater than or approximately equal to 1.3 MeV/nucleon He-3-rich events are associated with impulsive 2 to approximately 100 keV electron events, although many electron events were not accompanied by detectable He-3 increases. Both the He-3 and the electrons exhibit nearly scatter-free propagation in the interplanetary medium, and the times of onset and maximum for the He-3 and electron increases are closely related by velocity dispersion. The electron events and their related type III solar radio bursts provide, for the first time, identification of the flares which produce the He-3-rich events. He-3 appears to be accelerated at the flash phase of solar flares along with nonrelativistic electrons.

Reames, D. V.↗
NASA NTRSDate not supplied

Benchmark Problem Development for Testing Maturity of Intelligent Contingency Management Tools

This paper presents a process used to develop appropriate scenarios and metrics for evaluating the maturity of intelligent contingency management algorithms. A benchmark scenario is a reference point against which something can be measured, compared, or assessed. Creating an accurate benchmark requires considerable research and expertise. The scenario itself is an artificial representation of a real-world event, designed to achieve a set of learning objectives through experiential learning. Designing an effective benchmark simulation scenario requires careful planning, including identification of clear objectives; capability assessment of the algorithm/tool being evaluated; assessment of necessary levels of fidelity; development of a process flow map of events and event interactions; and identification of metrics that map back to objectives. Thus, a benchmark scenarios for contingency management might consist of one or several commonly used functions taken from real world applications, used for evaluation, characterization and performance measurement of a contingency management algorithm. Behavior of the contingency management algorithm under different environmental conditions should then be able to be predicted using a set of benchmark functions. The paper describes the resulting benchmark problem as an illustration of the application of this process.

Jon Holbrook↗
DOE OSTI2025

Toward Drilling the Perfect Geothermal Well: An International Research Coordination Network for Geothermal Drilling Optimization Supported by Deep Machine Learning and Cloud Based Data Aggregation

The EDGE project, supported by the U.S. Department of Energy Geothermal Technologies Office under award DE-EE0008793, established a data-driven framework for improving the efficiency, cost-effectiveness, and reliability of geothermal well drilling. The project focused on developing scalable data infrastructure, advanced machine learning and probabilistic models, and integrated analytics tools to support continuous drilling optimization. A central objective was to reduce geothermal drilling costs by up to seventy percent while minimizing the risk of well failure through predictive diagnostics and adaptive planning. Over the project period, a comprehensive data repository was designed and deployed, incorporating records from over one hundred geothermal wells across varied geological settings. This repository supported both structured and unstructured data and adhered to FAIR data principles, enabling provenance tracking, quality control, and standardized metadata. The project introduced automated ingestion pipelines and a cloud-hosted platform that facilitated access to raw, processed, and derived datasets. This infrastructure served as the foundation for model development and analysis. Machine learning workflows were developed to predict key drilling metrics including rate of penetration, non-productive time, and total drilling costs. Self-organizing maps and dimensionality reduction methods were used to uncover operational patterns and outliers, while supervised learning algorithms such as random forests and deep neural networks were applied to forecast performance outcomes. The models were validated on heterogeneous datasets from both U.S. and Icelandic fields, demonstrating variable but significant predictive accuracy. The results indicated that finer temporal resolution, inclusion of lithological data, and consistency in operational annotations could substantially improve model performance. The project also implemented process mining techniques to reconstruct state-transition models from drilling event logs. These models enabled the identification of deviations from optimal workflows and provided insights into recurring failure modes. Analysis of non-productive time highlighted the impact of equipment failures, geological challenges, and human factors, offering opportunities for targeted mitigation strategies. The EDGE Dashboard was developed as a web-based expert system integrating data visualization, model outputs, and user-driven queries. It provided an accessible interface for operators to explore historical data, evaluate predicted outcomes, and compare drilling scenarios. Initial feedback from project partners suggested that the dashboard could serve as a foundation for more advanced advisory and optimization tools. Overall, the EDGE project demonstrated the feasibility and value of applying modern data science techniques to geothermal drilling. It delivered a set of interoperable tools and models that can support more efficient, lower-risk well development. The findings point toward a viable path for transitioning from advisory analytics to semi-autonomous drilling systems, contingent on continued collaboration, expanded datasets, and field validation. The project results have immediate relevance for drilling operations, data management practices, and future geothermal R&D efforts aimed at achieving reliable, cost-competitive geothermal energy at scale.

15 GEOTHERMAL ENERGY↗
NASA NTRS1981

Observations of solar flares on 1980 April 30 and June 7 with the hard X-ray burst spectrometer

Descriptions of hard X-ray observations for solar flares occurring on 1980 April 30 and June 7 are presented. The hard X-ray light curve for the June 7 event shows complex intensity variations on time scales of 100 ms and spectral variations on time scales of seconds. The results for the 1980 April 30 flare are compared with simultaneous observations from other SMM instruments and from ground-based observatories. These comparisons have enhanced the interpretation of the hard X-ray data for this event and have permitted the tentative identification of the origin of the hard X-ray emission with a small loop structure within the flare region.

Orwig, L. E.↗
NASA NTRS1988

Pulse shaping and extraction of information from ultrasonic reflections in composite materials

The application of ultrasonic inspection to the nondestructive testing of composite materials is examined with reference to specific examples including monitoring of epoxy curing, evaluation of impact damage in a graphite/epoxy laminate, and monitoring of a repaired area in a composite wing plate. Signal processing methods are described which improve time resolution, facilitating identification of discrete echoes corresponding to events in the material.

Kishoni, Doron↗
NASA NTRS2008

Processing LiDAR Data to Predict Natural Hazards

ELF-Base and ELF-Hazards (wherein 'ELF' signifies 'Extract LiDAR Features' and 'LiDAR' signifies 'light detection and ranging') are developmental software modules for processing remote-sensing LiDAR data to identify past natural hazards (principally, landslides) and predict future ones. ELF-Base processes raw LiDAR data, including LiDAR intensity data that are often ignored in other software, to create digital terrain models (DTMs) and digital feature models (DFMs) with sub-meter accuracy. ELF-Hazards fuses raw LiDAR data, data from multispectral and hyperspectral optical images, and DTMs and DFMs generated by ELF-Base to generate hazard risk maps. Advanced algorithms in these software modules include line-enhancement and edge-detection algorithms, surface-characterization algorithms, and algorithms that implement innovative data-fusion techniques. The line-extraction and edge-detection algorithms enable users to locate such features as faults and landslide headwall scarps. Also implemented in this software are improved methodologies for identification and mapping of past landslide events by use of (1) accurate, ELF-derived surface characterizations and (2) three LiDAR/optical-data-fusion techniques: post-classification data fusion, maximum-likelihood estimation modeling, and hierarchical within-class discrimination. This software is expected to enable faster, more accurate forecasting of natural hazards than has previously been possible.

Fairweather, Ian↗
DOE OSTI2025

Modelling detector-specific reconstruction uncertainties in LAr-TPC

The Short-Baseline Neutrino (SBN) program features three Liquid Argon Time Projection Chamber (LAr-TPC) detectors positioned along the Booster Neutrino Beam (BNB) axis: the Short Baseline Neutrino Near Detector, MicroBooNE, and the ICARUS T600. As the largest operational LAr-TPC, ICARUS T600 serves as the far detector, located 600 m from the BNB target. While its primary goal is to record neutrino events, it also detects other ionizing events, including cosmic rays. This work focuses on analyzing and modeling detector-specific reconstruction uncertainties in LAr-TPC. These inefficiencies, identified during the Pattern Recognition phase handled by the PANDORA algorithm, impact subsequent Particle Fits and Offline Analysis. Specifically, inaccuracies in track reconstruction can lead to significant physical consequences, such as erroneous particle energy estimates and poor Particle Identification (PID), reducing the efficiency of neutrino event characterization. A key issue addressed is split tracks, caused by missing hits or incomplete track stitching by PANDORA. The aim of this internship is to characterize, model, and quantify the impact of split tracks on track reconstruction.

43 PARTICLE ACCELERATORS↗