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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 973 records · Page 54
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Automated Vehicle Feasibility Study

This study collected automated vehicle (AV) performance data on public roadways in Athens, Ohio. The route for the study contained a combination of roads with different functional classifications, conditions, annual average daily traffic, and ownership responsibilities for maintenance and repair. Preparation for the public road deployment was done in a controlled environment at Transportation Research Center’s SMARTCenter, a dedicated AV test facility in East Liberty, Ohio. Researchers analyzed data and extracted insights relevant for both AV developers and infrastructure owners and operators. The study found that rural environments offer a unique set of roadway features such as hills and curves, which can challenge the driving behavior of an AV. Rural regions can also contain a large number of low-traffic gravel roads that lack pavement markings, which appear to be a crucial infrastructure element for operation of current generation AVs. Similarly, the presence of well-maintained lane lines along curves can influence the AV’s roadway departure tendencies. The study found that curvature-related behavior of an AV is also influenced by driving speed on the roadway segment. Such findings were consistent regardless of the time of day along the route or season of data collection. However, commentary about AV performance in active adverse weather cannot be made, as this is still an area of active research.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2020

The CLAS12 Ring Imaging Cherenkov Detector

A ring imaging Cherenkov (RICH) detector has been installed in the CLAS12 spectrometer at Jefferson Laboratory (JLab) to provide kaon identification in the momentum range between 3 GeV/c and 8 GeV/c. The detector adopts a hybrid optics solution with aerogel radiator, light planar and spherical mirrors, and highly segmented photon detectors. We report here on the design, construction, and initial performance of the RICH during the commissioning of the detector and the first physics data taking period

PID detectors↗
DOE OSTI2023

Evaluating the Interplay between Trajectory Segmentation and Mode Inference Error

Travel behavior changes are essential to transportation decarbonization. Travel diaries, consisting of sequences of trips between places, are typically used to instrument human travel behavior. However, these diaries are only as accurate as the underlying methods used to construct them. Travel diary algorithms have been a popular research topic since the advent of Global Positioning System tracking surveys. These algorithms have typically been validated using prompted recall of presegmented trips, thus disregarding the continuity of mode inference. Phone operating systems have adopted battery-conserving techniques, but the resulting data collection errors have not been studied extensively. We introduce a framework to evaluate the accuracy of trip length computations and mode inference by analyzing continuous mode-segmented trajectories for groups of trips. We then use the framework to identify the input data quality and the impact of postprocessing. Our primary inputs to this evaluation are MobilityNet, a public dataset containing information from three artificial timelines covering 15 different travel modes, and sample open-source travel diary creation algorithms from the OpenPATH project. Our framework concretely shows that the variance of the distance error drops from (0.217, 0.0848) to (o.011, 0.0407) (Android, iOS) after postprocessing. Similarly, the weighted F-scores for mode inference increase from (0.25, 0.29) to (0.60, 0.74) (iOS, Android) between random forest and geographic information system-based models. We hope that this standardized method will be adapted to evaluate other, potentially proprietary, travel diary algorithms. Finally, the results can be used to understand and improve the state of the art in the travel diary creation field.

33 ADVANCED PROPULSION SYSTEMS↗
NASA NTRS1982

Use of Landsat-derived temporal profiles for corn-soybean feature extraction and classification

A physical model is presented, which has been derived from multitemporal-multispectral data acquired by Landsat satellites to describe the behavior and new features that are crop specific. A feasibility study over 40 sites was performed to classify the segment pixels into those of corn, soybeans, and others using the new features and a linear classifier. Results agree well with other existing methods, and it is shown the multitemporal-multispectral scanner data can be transformed into two parameters that are closely related to the target of interest and thus can be used in classification. The approach is less time intensive than other techniques and requires labeling of only pure pixels.

Badhwar, G. D.↗
NASA NTRS1994

The Space Communications Protocol Standards Program

In the fall of 1992 NASA and the Department of Defense chartered a technical team to explore the possibility of developing a common set of space data communications standards for potential dual-use across the U.S. national space mission support infrastructure. The team focused on the data communications needs of those activities associated with on-lined control of civil and military aircraft. A two-pronged approach was adopted: a top-down survey of representative civil and military space data communications requirements was conducted; and a bottom-up analysis of available standard data communications protocols was performed. A striking intersection of civil and military space mission requirements emerged, and an equally striking consensus on the approach towards joint civil and military space protocol development was reached. The team concluded that wide segments of the U.S. civil and military space communities have common needs for: (1) an efficient file transfer protocol; (2) various flavors of underlying data transport service; (3) an optional data protection mechanism to assure end-to-end security of message exchange; and (4) an efficient internetworking protocol. These recommendations led to initiating a program to develop a suite of protocols based on these findings. This paper describes the current status of this program.

Jeffries, Alan↗
NASA NTRS2022

Microstructure Segmentation with Deep Learning Encoders Pre-Trained on a Large Microscopy Dataset

This study examined the improvement of microscopy segmentation accuracy by transfer learning from a large dataset of microscopy images called MicroNet. Many neural network encoder architectures, including VGG, Inception, and ResNet, were trained on over 100,000 labelled microscopy images from 54 classes. These pre-trained encoders were then embedded into multiple segmentation architectures including U-Net and DeepLabV3+ to evaluate segmentation performance on newly created benchmark microscopy datasets. Compared to ImageNet pre-training, models pre-trained on MicroNet generalized better to out-of-distribution micrographs taken under different imaging and sample conditions and were more accurate with less training data. When training with only a single Ni-superalloy image, pre-training on MicroNet produced a 72.2 percent reduction in relative segmentation error. These results suggest that transfer learning from large in-domain datasets generate models with learned feature representations that are more useful for downstream tasks and will likely improve any microscopy image analysis technique that can leverage pre-trained encoders.

machine learning↗
DOE OSTI2020

Play Fairway Analysis: Structurally Controlled Geothermal Systems in the Eastern Great Basin Extensional Regime, Utah

A research team with membership from the University of Utah/Energy & Geoscience Institute, the University of Utah/Dept. of Geology & Geophysics, and the Utah Geological Survey, undertook a play fairway analysis (PFA) for geothermal resources in the Eastern Great Basin (EGB) extensional tectonic regime of western Utah. This is a high-priority region for geothermal exploration because active Basin and Range (B&R) extension with volcanism having a N-S strike is superimposed upon pre-existing E-W belts of plutonic rocks and large-scale structural lineaments. Cumulative heat flow along the N-S strike of the state totals approximately 5 GWt above background stable interior. Three electricity producing power plants currently exist with substantial potential for increase. Succinctly, our PFA approach aims to resolve potential sources of heat and permeability in the region, which are the two principal criteria for establishing a geothermal resource. An initial Phase 1 was carried out using only existing geoscientific data in the area. Criteria selected for focusing heat potential include direct heat flow measurements in boreholes, magnetotelluric (MT) low resistivity anomalies, fluid/gas geochemistry, and proximity to recent volcanic eruptions. Permeability is established through geological structures (fault density, critically stressed areas, seismicity, gravity), and MT low resistivity anomalies. In Phase II of this PFA project, additional geological, geophysical and geochemical data were acquired and analysis carried out primarily over promising composite common risk (CCR) areas initially identified in Phase I in order to focus prospectivity and prepare for drilling recommendations. These prospects are near the Twin Peaks rhyolite field, high heat flow areas north of the producing Cove Fort system, and geophysical structure beneath the Crater Knoll area off the northeast flank of the Mineral Mountains. Additional data included MT site fill-in, structural mapping and analysis using high-resolution imagery, gravity and on-ground mapping, Nodal 3C passive seismic collection, and passive 3He surveying. Heat source and permeability potential are again expressed in terms of their individual common risk segment (CRS) maps, with a color scheme using green for most favorable (low risk) and red for least favorable (high risk). Diverse data types are united through the technique of probability kriging, which establishes prospectivity thresholds for each data type and then computes probability of exceeding that threshold over the PFA area. Modified CRS and CCRS maps are compared to those of Phase I to highlight tighter prospectivity focus. In doing so, the prospectivity threshold for heat was increased significantly to narrow the targeting. In the final Phase III of this project where a recommended deep thermal gradient hole was sited, additional geophysical, geochemical and geological field collection and analysis was carried out to refine drill hole targeting. This includes prospect-scale MT, gravity, structure, passive seismic deployment (Cove Fort area), and detailed 3He isotope profiling. It was the recommendation of the DOE Technical Monitoring Team (TMT) that one or more holes be sited in the north-ern Cove Fort area where legacy TG gradient holes showed high cumulative heat flow. These were to be of moderate depth, 2000-3000 feet, to reach the geothermal fluid table expected to start in excess of 1000 feet depth. The drilling organization stipulated by the DOE/GTO was that of the USGS Research Drilling Program (RDP) centered in Las Vegas, NV. A detailed well plan, appended to this report, was developed principally by Dr. Ben Barker consulting to University of Utah, Dr. Steve Pye on the DOE TMT, Mr. Steven Crawford of the USGS-RDP, and the project PI Phil Wannamaker. However, temperature and possible H 2 S at the systems lead to cancellation of the drilling last-minute as this appeared outside the experience base of the USGS-RDP. We hope to have the opportunity to revisit the test drilling and expand the Play Fairway Analysis of this region at some point in the future.

15 GEOTHERMAL ENERGY↗
NASA NTRS2018

Online Self-Supervised Long-Range Scene Segmentation for MAVs

Recently, there have been numerous advances in the development of payload and power constrained lightweight Micro Aerial Vehicles (MAVs). As these robots aspire for high-speed autonomous flights in complex dynamic environments, robust scene understanding at long-range becomes critical. The problem is heavily characterized by either the limitations imposed by sensor capabilities for geometry-based methods, or the need for large-amounts of manually annotated training data required by data-driven methods. This motivates the need to build systems that have the capability to alleviate these problems by exploiting the complimentary strengths of both geometry and data-driven methods. In this paper, we take a step in this direction and propose a generic framework for adaptive scene segmentation using self-supervised online learning. We present this in the context of vision-based autonomous MAV flight, and demonstrate the efficacy of our proposed system through extensive experiments on benchmark datasets and real world field tests.

Matthies, Larry↗
NASA NTRS1981

Wheat cultivation: Identification and estimation of areas using LANDSAT data

The feasibility of using automatically processed multispectral data obtained from LANDSAT to identify wheat and estimate the areas planted with this grain was investigated. Three 20 km by 40 km segments in a wheat growing region of Rio Grande do Sul were aerially photographed using type 2443 Aerochrome film. Three maps corresponding to each segment were obtained from the analysis of the photographs which identified wheat, barley, fallow land, prepared soil, forests, and reforested land. Using basic information about the fields and maps made from the photographed areas, an automatic classification of wheat was made using MSS data from two different periods: July to September and July to October 1979. Results show that orbital data is not only useful in characterizing the growth of wheat, but also provides information of the intensity and extent of adverse climate which affects cultivation. The temporal and spatial characteristics of LANDSAR data are also demonstrated.

Dejesusparada, N.↗
DOE OSTI2021

Hydroxyl radical yields in the heavy ion radiolysis of water

The yields of hydroxyl radicals in the radiolysis of water with protons and carbon ions have been examined using experimental scavenging techniques coupled with Monte Carlo track simulations. Combined with previous results using helium ions, this set of data gives valuable information on the potential for radiation induced damage to biological systems for light ions with very different track structures. Carbon dioxide production from aerated formic acid solutions in concentrations ranging from 10 -3 to 1 M was used as a probe of hydroxyl radical yields from about 8 ns to 8 µs. Numerical interpolation of the results at slightly different ion energies in combination with data from gamma radiolysis allows for a systematic analysis of both track average and track segment yields. As expected, considerable track chemistry is found to occur on the nanosecond to microsecond time scales. Monte Carlo track simulations employing stochastic diffusion-kinetic calculations of product yields are found to reproduce experimental observations satisfactorily. The track simulations are used to extract hydroxyl radical kinetics in pure water at neutral conditions.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗
DOE OSTI2022

Development of Multimodal Few-Shot Analytics for Electron Micrographs

Recent advances in materials data analytics have provided new avenues for determining process-structure-property (PSP) linkages in a variety of materials. Machine learning techniques including few-shot learning have increased the efficiency of classifying microscopy images for the purposes of material characterization. Attempts at creating a multimodal approach can provide further improvements to current models and help extract more salient features from data. In this vein, raw spectrum data was taken to provide an additional modality to our current pyCHIP classifier. Modifications in segmentation also show potential in improving the accuracy of the pyCHIP classifier. Classifier output was analyzed using network graphs and unsupervised clustering algorithms such as spectral clustering to detect better segmentation methods than the current “chipping” approach. We suggest that the chip selection process can be automated in the future using a combination of these techniques to enable high-throughput analyses.

36 MATERIALS SCIENCE↗
NASA NTRS1972

Considerations for the design of an onboard air traffic situation display

The basic concept of remoting information to the cockpit is used to design and develop a computerized airborne traffic situation display device that automatically selects and presents segments of a controller's scope to the aircraft pilot via a narrow band digital data link. These data are integrated with aircraft heading and navigation information to provide a display useful in congested air space. The display can include alphanumerical symbols, air route maps, and controller instructions.

Anderson, R. E.↗
NASA NTRS1979

A brief summary of verification results for the spectral ocean wave model /SOWM/ by means of wave height measurements obtained by Geos 3

Significant wave heights calculated using a computer-based spectral ocean wave model (Pierson et al., 1966; Salfi, 1974; Lazanoff and Stevenson, 1975) from meteorological data have been compared with significant wave heights measured by Geos 3 for 44 orbit segments obtained during 1975 and 1976. The model specifications were found to be biased too low. Discrepancies between calculated and measured wave heights are also attributable to the poor specifications of the winds over the northern hemisphere oceans.

Pierson, W. J.↗
NASA NTRS1984

Landsat - An unmanned space platform

Landsats 4 and 5, the latest in the series of unmanned earth observation satellites, are used as the space platform for two remote sensing, mechanical scanning instruments: the multispectral scanner (MSS) and the recently developed thematic mapper (TM). The primary objective of the experimental portion of the Landsat 4 and 5 missions is to assess the capability of the TM to provide improved information relative to the MSS.The higher spatial resolution of the TM over the MSS requires a higher degree of flight segment attitude stability than the earlier Landsats; therefore, a more stable, low-orbit space platform must be provided. This paper describes the orbital, electrical, mechanical, and thermal characteristics of Landsat 4 and 5 flight segment with special emphasis on the TM and MSS interfaces. Also described are flight segment disturbances caused by the TM and MSS scanning mirrors, motion from the Tracking and Data Relay Satellite (TDRS) antenna, solar array, and the attitude control system (ACS).

Schulman, J. R.↗
NASA NTRS1991

Performance analysis of LAN bridges and routers

Bridges and routers are used to interconnect Local Area Networks (LANs). The performance of these devices is important since they can become bottlenecks in large multi-segment networks. Performance metrics and test methodology for bridges and routers were not standardized. Performance data reported by vendors is not applicable to the actual scenarios encountered in an operational network. However, vendor-provided data can be used to calibrate models of bridges and routers that, along with other models, yield performance data for a network. Several tools are available for modeling bridges and routers - Network II.5 was used. The results of the analysis of some bridges and routers are presented.

Hajare, Ankur R.↗
NASA NTRS2008

Recent Ice Sheet and Glacier Elevation Changes in Greenland from Aircraft Laser Altimetry

The Arctic Ice Mapping group (Project AIM) at the NASA Goddard Space Flight Center Wallops Flight Facility has been conducting systematic topographic surveys of the Greenland Ice Sheet (GIS) since 1993, using scanning airborne laser altimeters combined with Global Positioning System (UPS) technology. Earlier surveys showed the ice sheet above 2000-rn elevation to be in balance, but with localized regions of thickening or thinning. Thinning predominates at lower elevations and thinning rates have recently increased, resulting in a negative mass balance for the entire ice sheet. Recently, critical segments of near-coastal flight lines in Greenland were resurveyed. Results from the new data will be presented.

Krabill, William B.↗
NASA NTRS2009

Software Development to Assist in the Processing and Analysis of Data Obtained Using Fiber Bragg Grating Interrogation Systems

A fiber Bragg grating is a portion of a core of a fiber optic strand that has been treated to affect the way light travels through the strand. Light within a certain narrow range of wavelengths will be reflected along the fiber by the grating, while light outside that range will pass through the grating mostly undisturbed. Since the range of wavelengths that can penetrate the grating depends on the grating itself as well as temperature and mechanical strain, fiber Bragg gratings can be used as temperature and strain sensors. This capability, along with the light-weight nature of the fiber optic strands in which the gratings reside, make fiber optic sensors an ideal candidate for flight testing and monitoring in which temperature and wing strain are factors. The purpose of this project is to research the availability of software capable of processing massive amounts of data in both real-time and post-flight settings, and to produce software segments that can be integrated to assist in the task as well.

Hicks, Rebecca↗
NASA NTRSDate not supplied

Expanding NeMO-Net Machine Learning Capabilities for Citizen Science

NASA NeMO-Net, the neural multi-modal observation and training network for global coral reef assessment, is an open-source deep convolutional neural network and interactive active learning training software aiming to accurately assess the present and past dynamics of coral reef ecosystems through determination of percent living cover and morphology as well as mapping of spatial distribution. We present an interactive citizen science video game, released this April, for desktop and iOS devices where users interactively label morphology classifications over mm-scale 3D coral reef imagery captured using diver photomosaic imagery, the UAV enabled NASA FluidCam instrument, and satellite datasets. To date, the application has had over 40,000 downloads and over 60,000 unique coral reef classifications, each filtered through a user-based rating and expert evaluation system. We also present results from NeMO-Net’s convolutional neural network (CNN) models used to semantically segment 2D satellite imagery as well as projections of 3D coral reconstructions using user input data as training datasets. Fusing datasets using machine learning from multiple remote sensing platforms presents novel methodologies for assessing the health of coral ecosystems, which are critically endangered by a changing climate. In partnering with Mission Blue, the National Oceanic and Atmospheric Administration (NOAA), and the Living Oceans Foundation (LOF), NeMO-Net leverages an international consortium of subject matter experts to provide both proper training for citizen scientists and the generation of a labeled datasets to ingest into machine learning algorithms for global coral reef identification.

NeMO-Net↗