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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 487 records · Page 27
All sourcesNASA NTRSDOE OSTI
NASA NTRS1979

Mapping of electrical potential distribution with charged particle beams

Potentials were measured using a beam of soft X-rays in air at 2 x 10 to the -5 power Torr. Ions were detected by a continuous-dynode electron multiplier after they passed through a retarding field. Ultimate resolution depends upon the diameter of the X-ray beam which was 3 mm. When the fields in the region of interest were such to disperse the ions, only a small fraction were detected and the method of measurement was not very reliable. Yet reasonable data could be collected if the ions traveled in parallel paths toward the detector. Development should concentrate on increasing the aperture of the detector from the pinhole which was used to something measured in centimeters. Also increasing the strength of the source would provide a stronger signal and more reliable data. Measurements were made at an estimated ion current to 10 to the -15 power A from a 10 cm length of the X-ray beam, this current being several orders of magnitude below what would have a perturbing effect on the region to be measured. Consequently, the source strength can be increased and prospects for this method of measurement are good.

Robinson, J. W.↗
DOE OSTI2021

HydrogenAR: Interactive Data-Driven Presentation of Dispenser Reliability: Preprint

When delivering presentations to a co-located audience, we typically use slides with text and 2D graphics to complement the spoken narrative. Though presentations have largely been explored on 2D media, augmented reality (AR) allows presentation designers to add data and augmentations to existing physical infrastructure on display. This could provide a more engaging experience to the audience and support comprehension. With HydrogenAR, we present a novel application that leverages the benefits of data-driven storytelling with those of AR to explain the unique challenges of hydrogen dis- penser reliability. Utilizing physical props, situated data, and virtual augmentations and animations, HydrogenAR serves as a unique presentation tool, particularly critical for stakeholders, tour groups, and VIPs. HydrogenAR is a product of multiple collaborative de- sign iterations with a local Hydrogen Fuel research team and is evaluated through interviews with team members and a user study with end-users to evaluate the usability and quality of the interactive AR experience. Through this work, we provide design considera- tions for AR data-driven presentations and discuss how AR could be used for innovative content delivery beyond traditional slide-based presentations.

augmented reality↗
NASA NTRS1975

Manipulator system performance measurement

Free-flying teleoperator technology for satellite servicing is reported. The rationale for a series of manipulator system tests is presented. Data are reported on movement time in a fine positioning task using two different manipulator systems. The movement time data showed reliable effects of movement direction and index of difficulty. These data were considered to be baseline performance measures for the manipulator system used and modifications to the control and visual systems were suggested for future testing.

Kirkpatrick, M., III↗
NASA NTRS1995

NH3, H2S, and the Radio Brightness Temperature Spectra of the Giant Planets

Recent radio interferometer observations of Neptune enable comparisons of the radio brightness temperature (T(sub B)) spectra of all four giant planets. This comparison reveals evidence for fundamental differences in the compositions of Uranus' and Neptune's upper tropospheres, particularly in their ammonia (NH3) and hydrogen sulfide (H2S) mixing ratios, despite those planets' outward similarities. The tropospheric abundances of these constituents yield information about their deep abundances, and ultimately about the formation of the planets from the presolar nebula (Atreya et al.). Figures 1, 2, 3, and 4 show the T(sub B) spectra of Jupiter, Saturn, Uranus, and Neptune, respectively, from 0.1 to tens of cm wavelength. The data shown are collected from many observers. Data for Jupiter, Saturn, and Uranus are those cataloged by de Pater and Massie (1985), plus the Saturn Very Large Array (VLA) data by Grossman et al. Figure 3, Uranus, shows only data acquired since 1973. Before 1973 Uranus' T(sub B) increased steadily as its pole moved into view, causing significant scatter in those data. Neptune data at greater than 1 cm, all taken at the VLA, are collected from de Pater and Richmond, de Pater et al., and Hofstadter. For a variety of reasons, such as susceptibility to source confusion, single-dish data at those wavelengths are much noisier than the more reliable VLA data and have been ignored. Single-dish data by Griffin and Orton shortward of 0.4 cm are shown, along with the Owens Valley Radio Observatory (interferometer) datum at 0.266 cm by Muhleman and Berge. Spectra of Jupiter, Saturn, and Neptune share certain gross characteristics. In each spectrum, T(sub B) at 1.3 cm is approximately 120-140 K, less than approximately 30 K different from that at 0.1 cm. All three spectra show a break in slope at or near 1.3 cm, with T(sub B) increasing fairly rapidly with wavelength longward of 1.3 cm. Visible and IR spectroscopy show that NH3, whose strong inversion spectrum peaks at appropximately 1.3 cm, is an important tropospheric species at Jupiter and Saturn. Its signature on the Jovian radio spectrum is obvious, causing the prominent "hole" at 1.3 cm. At Saturn it is more subdued but is the source of that spectrum's change in slope at 1.3 cm. Radiative transfer models of Jupiter and Saturn with near-solar deep NH3 abundances agree well with the data (e.g., de Pater).

Spilker, Thomas R.↗
NASA NTRS2000

Data Oscillation Resolution of Propellant Flowmeter Used in FASTRAC Engine Testing

The Stennis Space Centers' horizontal test facility, Marshall Space Flight Centers' propulsion test article and the X-34 flight vehicle are designed with V-cone flowmeters for measurement of both RP-1 and LOX flow-rates for Fastrac engine testing. Delta pressure transducer data from these flowmeters are used to calibrate the RP-1 and LOX mixture ratio in the Fastrac engine. Data from the V-Cone flowmeter delta pressure transducers have excessive oscillation. The delta pressure oscillations have caused flowrate data fluctuations that interfered with making the accurate readings necessary to calibrate the RP-1 and LOX mixture ratio required for Fastrac engine operation. The objective of this report is to document the flowmeter data oscillation problem and the method used to obtain more reliable flowmeter data.

Heflin, J.↗
NASA NTRS2014

NASA Glenn Research Center Support of the ASRG Project

A high efficiency radioisotope power system is being developed for long-duration NASA space science missions. The U.S. Department of Energy (DOE) managed a flight contract with Lockheed Martin Space Systems Company (LMSSC) to build Advanced Stirling Radioisotope Generators (ASRGs), with support from NASA Glenn Research Center (GRC). Sunpower Inc. held two parallel contracts to produce Advanced Stirling Convertors (ASCs), one with DOELockheed Martin to produce ASC-F flight units, and one with GRC for the production of ASC-E3 engineering unit pathfinders that are built to the flight design. In support of those contracts, GRC provided testing, materials expertise, government furnished equipment, inspections, and related data products to DOELockheed Martin and Sunpower. The technical support includes material evaluations, component tests, convertor characterization, and technology transfer. Material evaluations and component tests have been performed on various ASC components in order to assess potential life-limiting mechanisms and provide data for reliability models. Convertor level tests have been used to characterize performance under operating conditions that are representative of various mission conditions. Technology transfers enhanced contractor capabilities for specialized production processes and tests. Despite termination of flight ASRG contract, NASA continues to develop the high efficiency ASC conversion technology under the ASC-E3 contract. This paper describes key government furnished services performed for ASRG and future tests used to provide data for ongoing reliability assessments.

Technology Transfer↗
NASA NTRS2015

NASA Glenn Research Center Support of the Advanced Stirling Radioisotope Generator Project

A high-efficiency radioisotope power system was being developed for long-duration NASA space science missions. The U.S. Department of Energy (DOE) managed a flight contract with Lockheed Martin Space Systems Company to build Advanced Stirling Radioisotope Generators (ASRGs), with support from NASA Glenn Research Center. DOE initiated termination of that contract in late 2013, primarily due to budget constraints. Sunpower, Inc., held two parallel contracts to produce Advanced Stirling Convertors (ASCs), one with Lockheed Martin to produce ASC-F flight units, and one with Glenn for the production of ASC-E3 engineering unit "pathfinders" that are built to the flight design. In support of those contracts, Glenn provided testing, materials expertise, Government-furnished equipment, inspection capabilities, and related data products to Lockheed Martin and Sunpower. The technical support included material evaluations, component tests, convertor characterization, and technology transfer. Material evaluations and component tests were performed on various ASC components in order to assess potential life-limiting mechanisms and provide data for reliability models. Convertor level tests were conducted to characterize performance under operating conditions that are representative of various mission conditions. Despite termination of the ASRG flight development contract, NASA continues to recognize the importance of high-efficiency ASC power conversion for Radioisotope Power Systems (RPS) and continues investment in the technology, including the continuation of the ASC-E3 contract. This paper describes key Government support for the ASRG project and future tests to be used to provide data for ongoing reliability assessments.

Technology Transfer↗
DOE OSTI2024

2024 Photovoltaic Inverter Reliability Workshop Summary Report & Proceedings

The National Renewable Energy Laboratory (NREL) organized the 2024 Photovoltaic Inverter Reliability Workshop on April 11-12, 2024, hosted at NREL's South Table Mountain campus in Golden, Colorado. The workshop was organized around seven key topics, including the present state of inverter reliability; solutions for reliability challenges; life cycle cost and ownership issues; testing, standards, performance, and reliability metrics; data reporting, analytics, and sharing; and the future of PV inverter reliability research. Participants included inverter manufacturers, national laboratory researchers, academics, independent testing laboratories, and more. Over the course of the two-day workshop, attendees arrived at several key priorities and conclusions. This report summarizes these conclusions and then collects presentations from the workshop into a record of the workshop's proceedings.

14 SOLAR ENERGY↗
DOE OSTI2022

Separating Sensor Anomalies From Process Anomalies in Data-Driven Anomaly Detection

Data-driven anomaly detection over time series data is studied from the perspective of separating data anomalies—corresponding to sensor failures—from process anomalies—that arise from equipment or operational failures. Herein, a semi-supervised approach is proposed that utilizes two predictive models trained on non-anomalous data using two different sensor groups as inputs, and a nested hypothesis test to reliably classify data or process anomalies. Conditions are derived on choice of sensor groups to guarantee reliable detection, and a case study is presented to demonstrate the proposed classification approach.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
NASA NTRS1999

Sensitivity Analysis of ProSEDS (Propulsive Small Expendable Deployer System) Data Communication System

This paper discusses analytical approaches to evaluating performance of Spacecraft On-Board Computing systems, thereby ultimately achieving a reliable spacecraft data communications systems. The sensitivity analysis approach of memory system on the ProSEDS (Propulsive Small Expendable Deployer System) as a part of its data communication system will be investigated. Also, general issues and possible approaches to reliable Spacecraft On-Board Interconnection Network and Processor Array will be shown. The performance issues of a spacecraft on-board computing systems such as sensitivity, throughput, delay and reliability will be introduced and discussed.

Park, Nohpill↗
DOE OSTI2025

2025 Large Load Literature Review

This literature review catalogs more than 90 publications focused on large loads, and groups the documents and resources thematically into 12 categories, (listed below). The 2026 Large Load Literature Review and Data Sources summary reports are available here: https://emp.lbl.gov/publications/2026-large-load-literature-review -Load forecasting -Data sources -Reliability and resource adequacy -Large load interconnection -Demand flexibility -Generation -Co-location -Data center location/infrastructure -Large load tariffs -Policy options -Maps and tools -Design and operations

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Lockdown impacts on residential electricity demand in India: A data-driven and non-intrusive load monitoring study using Gaussian mixture models

This study evaluates the effect of complete nationwide lockdown in 2020 on residential electricity demand across 13 Indian cities and the role of digitalisation using a public smart meter dataset. We undertake a data-driven approach to explore the energy impacts of work-from-home norms across five dwelling typologies. Our methodology includes climate correction, dimensionality reduction and machine learning-based clustering using Gaussian Mixture Models of daily load curves. Results show that during the lockdown, maximum daily peak demand increased by 150-200% as compared to 2018 and 2019 levels for one room-units (RM1), one bedroom-units (BR1) and two bedroom-units (BR2) which are typical for low- and middle-income families. While the upper-middle- and higher-income dwelling units (i.e., three (3BR) and more-than-three bedroom-units (M3BR)) saw night-time demand rise by almost 44% in 2020, as compared to 2018 and 2019 levels. Our results also showed that new peak demand emerged for the lockdown period for RM1, BR1 and BR2 dwelling typologies. We found that the lack of supporting socioeconomic and climatic data can restrict a comprehensive analysis of demand shocks using similar public datasets, which informed policy implications for India's digitalisation. We further emphasised improving the data quality and reliability for effective data-centric policymaking.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2022

Synthetic data generation for machine learning model training for energy theft scenarios using cosimulation

Abstract Technical and non‐technical losses in distribution circuits result in significant economic costs to power utilities. One type of non‐technical loss is energy theft by various means including illegal tapping of feeders, bypassing the meter, and billing fraud. These losses are usually hard to detect, and can remain undetected for long periods of time. Machine learning models have been proven effective in detecting these conditions, but rely on the availability of large, good‐quality training data sets. The problem is exacerbated by the imbalanced nature of data related to these conditions—energy theft, though costly, is very rare. The available data sets generally have very few samples of theft with most of the data pertaining to normal operation. Such data sets are generally not suitable to train machine learning models. In this paper, an overview of energy theft detection techniques, the challenges with their data needs, and the limitations of current techniques to bridge such data limitations is presented. A co‐simulation framework is proposed to generate reliable training data for machine learning algorithms for theft detection. An example scenario is presented and a machine learning model is built to detect certain kinds of energy theft.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2019

Wireless Sensor Networks for Improved Snow Water Equivalent and Runoff Estimates

We leverage the frontiers of the Internet of Things technology in a recently developed end-to-end wireless sensor network (WSN) system that samples, collects, stores, and displays mountain hydrology measurements in near real-time. At the core of the system lies an ultra-low power, radio channel-hoping, and self-organizing mesh that allows for remote autonomous sampling of snow. Such properties, combined with a rugged weather-sealed design of the devices and multi-level data replication, provides reliable real-time data at spatial and temporal scales previously impractical to achieve in mountain environments. The system was deployed at three 1 km 2 sites across the North Fork of the Feather River basin with a cluster of 12 sensor nodes for each location. Measurements show that existing operational autonomous systems are non-representative spatially, with biases that can reach up to 50%. A comparison between a wet and dry year showed that snow depths exhibit strong multi-scale inter-year spatial stationarity with major rank conservation. Temporally dense analysis using elastic net regression shows that dominant features at the sub-km 2 scale are site-dependent and differ from the watershed scale. Newly introduced explanatory variables, based on the nearest neighbor with a Landsat assimilated historical product, consistently explained up to 90% of the variance in the watershed-scale SWE for both years. At two WSN sites, lagged cross-correlation of snowmelt with stream flow measurements showed a significant improvement of up to 100% compared with existing systems, suggesting that WSNs can be instrumental in improving runoff forecasting and water management.

47 OTHER INSTRUMENTATION↗
NASA NTRSDate not supplied

Evaluation of the Accuracy of the Load Prediction Equations of Low-Load Balance Calibration Data

Accuracy and reliability of the load prediction equations of a low-load calibration data set of a force balance were investigated. First, independent load prediction equations were generated from the data of a full-load and low-load machine calibration. Then, the low- load data set was processed as a set of precision check loads for the load prediction equations that were obtained from the full-load and low-load calibrations. Finally, the load prediction equations of the two calibrations were applied to four manual check load data sets that were recorded between 2009 and 2022. The residuals of the predicted calibration and check loads were compared in all cases. No systematic improvement of the load prediction accuracy was observed when the load prediction equations of the low-load calibration were applied to the check load data sets. Therefore, it is recommended to apply a full-load calibration to a six-component balance even if the balance is not used across its entire design envelope. This approach has the advantage that the resulting load prediction equations are less likely to be applied outside of the calibration load ranges. In addition, it is expected that the numerical estimates of the gage sensitivities are more reliable assuming that the uncertainties of the applied loads and measured outputs of the calibration data are more or less constant across the load range of the balance.

strain-gage balance↗
NASA NTRSDate not supplied

Evaluation of the Accuracy of the Load Prediction Equations of Low-Load Balance Calibration Data

Accuracy and reliability of the load prediction equations of a low-load calibration data set of a force balance were investigated. First, independent load prediction equations were generated from the data of a full-load and low-load machine calibration. Then, the low-load data set was processed as a set of precision check loads for the load prediction equations that were obtained from the full-load and low-load calibrations. Finally, the load prediction equations of the two calibrations were applied to four manual check load data sets that were recorded between 2009 and 2022. The residuals of the predicted calibration and check loads were compared in all cases. No systematic improvement of the load prediction accuracy was observed when the load prediction equations of the low-load calibration were applied to the check load data sets. Therefore, it is recommended to apply a full-load calibration to a six-component balance even if the balance is not used across its entire design envelope. This approach has the advantage that the resulting load prediction equations are less likely to be applied outside of the calibration load ranges. In addition, it is expected that the numerical estimates of the bridge sensitivities are more reliable assuming that the uncertainties of the applied loads and measured outputs of the calibration data are more or less constant across the load range of the balance.

strain-gage balance↗
NASA NTRS1998

Remote Observing with the Keck Telescope Using the ACTS Satellite

As a technical demonstration project for the NASA Advanced Communications Technology Satellite (ACTS), we have implemented remote observing on the 10-meter Keck II telescope on Mauna Kea in Hawaii from the California Institute of Technology campus in Pasadena. The data connection consists of optical fiber networks in Hawaii and California, connecting the end-points to high data rate (HDR) ACTS satellite antennae at JPL in Pasadena and at the Tripler Army Medical Center in Honolulu. The terrestrial fiber networks run the asynchronous transfer mode (ATM) protocol at DS-3 (45 Mbit/sec) speeds, providing ample bandwidth to enable remote observing with a software environment identical to that used for on-site observing in Hawaii. This experiment has explored the data requirements of remote observing with a modern research telescope and large-format detector arrays. While the maximum burst data rates are lower than those required for many other applications (e.g., HDTV), the network reliability and data integrity requirements are critical. As we show in this report, the former issue particularly may be the greatest challenge for satellite networks for this class of application. We have also experimented with the portability of standard TCP/IP applications to satellite networks, demonstrating the need for alternative TCP congestion algorithms and minimization of bit error rates (BER). Reliability issues aside, we have demonstrated that true remote observing over high-speed networks provides several important advantages over standard observing paradigms. Technical advantages of the high-speed network access include more rapid download of data to a user's home institution and the opportunity for alternative communication facilities between members of an observing team, such as audio- and videoconferencing.

SATELLITE COMMUNICATIONS↗