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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 1,207 records · Page 67
All sourcesNASA NTRSDOE OSTI
NASA NTRS1976

A survey of long-term interplanetary magnetic field variations

Interplanetary-magnetic-field data from the IMP-10, IMP-A, and Heos spacecraft have been merged into a composite data set spanning the period from 1963 to 1974. Consideration of the mutual consistency of the individual data sets reveals agrement typically to within 0.2 gamma. Analysis of the composite data set reveals the following: (1) although the yearly averaged magnitudes of all field vectors show virtually no solar-cycle variation, the yearly averaged magnitudes of positive- and negative-polarity field vectors show separate solar-cycle variations consistent with variations in the average azimuthal angles of positive- and negative-polarity field vectors; (2) there is no solar latitude dependence of long-time average field magnitudes; (3) field vectors parallel to the earth-sun line are on the average 1 gamma less in magnitude than field vectors perpendicular to this line; and (4) the solar latitude-dependent dominant polarity effect exhibits a complex sign reversal in the period from 1968 to 1971 and a measure of symmetry in 1972 through 1974 not found in earlier data.

King, J. H.↗
DOE OSTI2021

The International Soil Moisture Network: serving Earth system science for over a decade

In 2009, the International Soil Moisture Network (ISMN) was initiated as a community effort, funded by the European Space Agency, to serve as a centralised data hosting facility for globally available in situ soil moisture measurements (Dorigo et al., 2011b, a). The ISMN brings together in situ soil moisture measurements collected and freely shared by a multitude of organisations, harmonises them in terms of units and sampling rates, applies advanced quality control, and stores them in a database. Users can freely retrieve the data from this database through an online web portal (https://ismn.earth/en/, last access: 28 October 2021). Meanwhile, the ISMN has evolved into the primary in situ soil moisture reference database worldwide, as evidenced by more than 3000 active users and over 1000 scientific publications referencing the data sets provided by the network. As of July 2021, the ISMN now contains the data of 71 networks and 2842 stations located all over the globe, with a time period spanning from 1952 to the present. The number of networks and stations covered by the ISMN is still growing, and approximately 70% of the data sets contained in the database continue to be updated on a regular or irregular basis. The main scope of this paper is to inform readers about the evolution of the ISMN over the past decade, including a description of network and data set updates and quality control procedures. A comprehensive review of the existing literature making use of ISMN data is also provided in order to identify current limitations in functionality and data usage and to shape priorities for the next decade of operations of this unique community-based data repository.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Exploring the Effects of Population and Employment Characteristics on Truck Flows: An Analysis of NextGen NHTS Origin-Destination Data

Truck transportation remains the dominant mode of US freight transportation because of its advantages, such as the flexibility of accessing pickup and drop-off points and faster delivery. Because of the massive freight volume transported by trucks, understanding the effects of population and employment characteristics on truck flows is critical for better transportation planning and investment decisions. The US Federal Highway Administration published a truck travel origin-destination data set as part of the Next Generation National Household Travel Survey program. This data set contains the total number of truck trips in 2020 within and between 583 predefined zones encompassing metropolitan and nonmetropolitan statistical areas within each state and Washington, DC. In this study, origin-destination-level truck trip flow data was augmented to include zone-level population and employment characteristics from the US Census Bureau. Census population and County Business Patterns data were included. The final data set was used to train a machine learning algorithm-based model, Extreme Gradient Boosting (XGBoost), where the target variable is the number of total truck trips. Shapley Additive ExPlanation (SHAP) was adopted to explain the model results. Results showed that the distance between the zones was the most important variable and had a nonlinear relationship with truck flows.

Uddin, Majbah↗
NASA NTRS1993

Development, refinement, and testing of a short term solar flare prediction algorithm

During the period included in this report, the expenditure of time and effort, and progress toward performance of the tasks and accomplishing the goals set forth in the two year research grant proposal, consisted primarily of calibration and analysis of selected data sets. The heliographic limits of 30 degrees from central meridian were continued. As previously reported, all analyses are interactive and are performed by the Principal Investigator. It should also be noted that the analysis time involved by the Principal Investigator during this reporting period was limited, partially due to illness and partially resulting from other uncontrollable factors. The calibration technique (as developed by MSFC solar scientists), incorporates sets of constants which vary according to the wave length of the observation data set. One input constant is then varied interactively to correct for observing conditions, etc., to result in a maximum magnetic field strength (in the calibrated data), based on a separate analysis. There is some insecurity in the methodology and the selection of variables to yield the most self-consistent results for variable maximum field strengths and for variable observing/atmospheric conditions. Several data sets were analyzed using differing constant sets, and separate analyses to differing maximum field strength - toward standardizing methodology and technique for the most self-consistent results for the large number of cases. It may be necessary to recalibrate some of the analyses, but the sc analyses are retained on the optical disks and can still be used with recalibration where necessary. Only the extracted parameters will be changed.

Smith, Jesse B., Jr.↗
DOE OSTI2020

Albedo Data for Bifacial PV Systems Update

For use by the PV and financial communities to better estimate the performance and to reduce the risk of bifacial PV systems, data sets of ground albedo and associated meteorological data were developed by using existing measurement network data and data contributed by the PV industry. The data sets include time-series data as well as summary information of tabular monthly and yearly data and plots of monthly and hourly albedo values. Complete information is presented in a user’s guide and data are available for download from NREL’s DuraMAT website.

albedo↗
DOE OSTI2022

Impact of heavy quark and quarkonium data on nuclear gluon PDFs

A clear understanding of nuclear parton distribution functions (nPDFs) plays a crucial role in the interpretation of collider data taken at the Relativistic Heavy Ion Collider, the Large Hadron Collider (LHC), and in the near future at the Electron-Ion Collider. Even with the recent inclusions of vector boson and light meson production data, the uncertainty of the gluon PDF remains substantial and limits the interpretation of heavy ion collision data. To obtain new constraints on the nuclear gluon PDF, we extend our recent nCTEQ15WZ+SIH analysis to inclusive quarkonium and open heavy-flavor meson production data from the LHC. This vast new data set covers a wide kinematic range and puts strong constraints on the nuclear gluon PDF down to x ≲ 10 -5 . The theoretical predictions for these data sets are obtained from a data-driven approach, where proton-proton data are used to determine effective scattering matrix elements. This approach is validated with detailed comparisons to existing next-to-leading order calculations in nonrelativistic QCD for quarkonia and in the general-mass variable-flavor-number scheme for the open heavy-flavored mesons. In addition, the uncertainties from the data-driven approach are determined using the Hessian method and accounted for in the PDF fits. This extension of our previous analyses represents an important step toward the next generation of PDFs not only by including new data sets, but also by exploring new methods for future analyses.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
NASA NTRS1990

ATLAS: Airborne Tunable Laser Absorption Spectrometer for stratospheric trace gas measurements

The ATLAS instrument is an advanced technology diode laser based absorption spectrometer designed specifically for stratospheric tracer studies. This technique was used in the acquisition of N2O tracer data sets on the Airborne Antarctic Ozone Experiment and the Airborne Arctic Stratospheric Expedition. These data sets have proved valuable for comparison with atmospheric models, as well as in assisting in the interpretation of the entire ensemble of chemical and meteorological data acquired on these two field studies. The N2O dynamical tracer data set analysis revealed several ramifications concerning the polar atmosphere: the N2O/NO(y) correlation, which is used as a tool to study denitrification in the polar vertex; the N2O Southern Hemisphere morphology, showing subsidence in the winter polar vortex; and the value of the N2O measurements in the interpretation of ClO, O3, and NO(y) measurements and of the derived dynamical tracer, potential vorticity. Field studies also led to improved characterization of the instrument and to improved accuracy.

Loewenstein, Max↗
NASA NTRS2003

Water Ice Clouds in the Martian Atmosphere: A Comparison of Two Methods

To date, the only two data sets offer the potential to examine year-to-year changes in cloud features over an entire Martian year: the Viking Infrared Thermal Mapper (IRTM) data set and the Mars Global Surveyor (MGS) Thermal Emission Spectrometer (TES) data set. We have examined the TES data in the same way in which we examined the Viking IRTM data. This provides water-ice cloud information separated in time by 12 Martian years. Since the data are analyzed with the same method, we obtain a very accurate 'apples to apples' comparison, and can generate a historical record of the subtleties of this annual event. Consequently, it is desirable to compare their results to ours to see what differences exist.

Hale, A. S.↗
DOE OSTI2022

Heavy-Duty Vehicle Activity Updates for MOVES Using NREL Fleet DNA and CE-CERT Data

The U.S. Environmental Protection Agency's (EPA's) Motor Vehicle Emission Simulator (MOVES) is a publicly available tool used by researchers and policymakers to help understand motor vehicle emission sources at a national, county, and project level. Estimates of heavy-duty activity in the most recent version of the model at the time this work was conducted, MOVES2014, was identified as an area in need of improvement. The start activity in MOVES2014 is based on a limited and dated data set. In addition, MOVES2014 relies on drive cycles that represent on-network activity but do not account for idling activity that occurs on off-network roads, such as at a distribution center, while the truck is queuing or during loading and unloading. As a result, MOVES2014 may currently underestimate the number of starts and idle and soak time for heavy-duty trucks in real-world operation. The National Renewable Energy Laboratory (NREL) has previously leveraged its expansive Fleet DNA database of heavy-duty vehicles to idle and start activity for six of the nine heavy-duty vehicle source types of classes in the MOVES model. The data available in Fleet DNA from 416 conventional, diesel-powered vehicles provided activity estimates from more than 120,000 hours of operation throughout 14,682 vehicle days between October 2006 and January 2016. NREL calculated start fraction, starts per day, soak fraction, and idle fraction by hour of the day for each vehicle type, state, and vocation, and provided results in .CSV files that can be translated to MOVES table inputs. The idle and start activity from this initial analysis of Fleet DNA data was used to develop default idle and start data for heavy-duty vehicles in MOVES3. Satisfied with the results from the Fleet DNA data used for MOVES3, the EPA asked NREL to extend this start/soak/idle analysis using additional data from a larger number of vehicles for a potential future update to the MOVES model. Such a data set was achieved from a project led by the University of California at Riverside, College of Engineering, Center for Environmental Research & Technology (CE-CERT) and funded by California Air Resources Board. Specifically, this data set consists of 90 heavy-duty vehicles operated mainly in California, which can be separated into five of the nine heavy-duty vehicle classes in the MOVES model. In addition, the heavy-duty activity database collected by CE-CERT provided activity estimates from more than 44,000 hours of operation throughout 4,724 vehicle days between November 2014 and September 2016. This report details the analysis of the heavy-duty activity database collected from the University of California at Riverside by providing graphical analysis and context for the start, soak, and idle distributions. The comparison of the related results from both the Fleet DNA and CE-CERT data sets are documented as well.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2024

Astronomaly at scale: searching for anomalies amongst 4 million galaxies

ABSTRACT Modern astronomical surveys are producing data sets of unprecedented size and richness, increasing the potential for high-impact scientific discovery. This possibility, coupled with the challenge of exploring a large number of sources, has led to the development of novel machine-learning-based anomaly detection approaches, such as astronomaly. For the first time, we test the scalability of astronomaly by applying it to almost 4 million images of galaxies from the Dark Energy Camera Legacy Survey. We use a trained deep learning algorithm to learn useful representations of the images and pass these to the anomaly detection algorithm isolation forest, coupled with astronomaly’s active learning method, to discover interesting sources. We find that data selection criteria have a significant impact on the trade-off between finding rare sources such as strong lenses and introducing artefacts into the data set. We demonstrate that active learning is required to identify the most interesting sources and reduce artefacts, while anomaly detection methods alone are insufficient. Using astronomaly, we find 1635 anomalies among the top 2000 sources in the data set after applying active learning, including eight strong gravitational lens candidates, 1609 galaxy merger candidates, and 18 previously unidentified sources exhibiting highly unusual morphology. Our results show that by leveraging the human–machine interface, astronomaly is able to rapidly identify sources of scientific interest even in large data sets.

Astronomy & Astrophysics↗
DOE OSTI2020

PARAFAC_T1

This is a method of performing trilinear analysis on large data sets using a modification of the PARAFAC-ALS algorithm. It iteratively decomposes the data matrix into a core matrix and three loading matrices based on the Tucker1 model. The algorithm is particularly useful for data sets that are too large to upload into a computer?s main memory. While the performance advantage in utilizing our algorithm is dependent on the number of data elements and dimensions of the data array, we have seen a significant performance improvement over operating PARAFAC-ALS on the full data set. SAND2020-12649 M Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy's National Nuclear Security Administration under contract DE-NA0003525.

Van Benthem, Mark↗
NASA NTRS1983

FGGE/SBUV tape specification and shipping letter description

The FGGE/SBUV Level 2C data set consists of 12 9-track data tapes, each of which contains total ozone and ozone profile data for one calendar month grouped in files containing the data in a 6 hour synoptic time block. The data flow and quality checks in the production of this data set are described as well as the format of the data tapes and the accompanying shipping documents.

Han, D.↗
NASA NTRS1985

Process thresholds: Report of Working Group Number 3

The Process Thresholds Working Group concerned itself with whether a geomorphic process to be monitored on satellite imagery must be global, regional, or local in its effect on the landscape. It was pointed out that major changes in types and magnitudes of processes operating in an area are needed to be detectable on a global scale. It was concluded from a review of geomorphic studies which used satellite images that they do record change in landscape over time (on a time-lapse basis) as a result of one or more processes. In fact, this may be one of the most important attributes of space imagery, in that one can document land form changes in the form of a permanent historical record. The group also discussed the important subject of the acquisition of basic data sets by different satellite imaging systems. Geomorphologists already have available one near-global basis data set resulting from the early LANDSAT program, especially images acquired by LANDSATs 1 and 2. Such historic basic data sets can serve as a benchmark for comparison with landscape changes that take place in the future. They can also serve as a benchmark for comparison with landscape changes that have occurred in the past (as recorded) by images, photography and maps.

Williams, R. S., Jr.↗
NASA NTRS1990

Bioclimatic distribution of vegetation for general circulation model studies

Four global bioclimatic schemes which qualify climates on the basis of the distribution of vegetation, including the Holdridge (1947), Thornthwaite (1948), Koeppen (1936), and Troll and Paffen (1964) schemes, were applied to two global climate data sets to produce maps of global vegetation distribution: the Rand set described by Schutz and Gates (1971, 1973, and 1974) and the Shea (1986) data set. The results show that only 38 to 40 percent of the observed land surface, mapped as 31 vegetation types, could be replicated by applying the four schemes to these data sets. The simulations were significantly improved by further subdividing and regrouping the climates defined by the schemes and by regrouping the observed vegetation types. With these alterations, 77 percent of the predicted vegetative landscape coresponded with the observed distribution of vegetation.

Prentice, Katharine Culbertson↗
NASA NTRS1974

Signature extension studies

The importance of specific spectral regions to signature extension is explored. In the recent past, the signature extension task was focused on the development of new techniques. Tested techniques are now used to investigate this spectral aspect of the large area survey. Sets of channels were sought which, for a given technique, were the least affected by several sources of variation over four data sets and yet provided good object class separation on each individual data set. Using sets of channels determined as part of this study, signature extension was accomplished between data sets collected over a six-day period and over a range of about 400 kilometers.

Vincent, R. K.↗
NASA NTRS1983

Comparison of satellite and in situ data

A variety of data sets were available and analyzed. The data sets discussed here are: (1) SMMR-A: The Nimbus Project data release; (2) SMMR-D: The revised SMMR version produced by Wilheit and Milman; (3) SMMR-C: The SMMR version produced by Prabhakara; (4) Fleet Numerical Oceanography Center (PNOC): The individual ship reports; and (5) Reynolds Climatology. Data from SMMR and PNOC ships were compared in three different ways: (1) The difference between individual ship and SMMR observations which were close in space and time. (2) The difference between the 20 degree lat-lon one month averages for SMMR and ship, respectively. (3) The difference between the 20 degree averages and climatology, for both SMMR and ship.

Bernstein, R. L.↗
DOE OSTI2025

3D Continuous Forcing Dataset from 3D Constrained Variational Analysis at SGP

The continuous 3D large-scale forcing (VARANAL3D) data set derived from 3D constrained variational analysis (3DCVA) extends the conventional constrained variational analysis method by incorporating multiple sub-columns within the analysis domain. This advancement introduces spatial variability into the large-scale forcing fields, thereby enriching the data set’s applicability. The VARANAL3D data set spans from 2004 to 2018 and covers a region of 5˚×4.5˚ domain around the ARM SGP site. The analysis domain is divided into 10×9 sub-columns with 0.5˚ resolution. The 3D large-scale forcing data provides necessary variables to drive and evaluate single-column models (SCM), cloud-resolving models (CRM) ,and large-eddy simulations (LES), as well as information for testing model sensitivity to spatial variability of the large-scale forcing data, facilitating more rigorous testing and refinement of physical processes in SCM/CRM/LES.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1996

Analysis of Solar Spectral Irradiance Measurements from the SBUV/2-Series and the SSBUV Instruments

The purpose of this research is to develop a NOAA-11 SBUV/2 solar spectral irradiance data set which is free from long-term instrument drift, then perform scientific analysis using the data set. During the current period of performance, 29 February 1996 through 31 August 1996, we finalized the NOAA-11 SBUV/2 characterization using internal data. This included updating the instrument's electronic, photomultiplier tube gain, wavelength, diffuser degradation, and goniometric calibrations. We have also completed the SSBUV characterization, 1989-1994, and produced SSBUV irradiances for the first seven SSBUV flights. Both of these steps were needed before the long-term calibration of the NOAA-11 SBUV/2 solar spectral irradiance data set via SSBUV can be undertaken. A second major aspect of this work is to compare solar spectral irradiances from the SBUV/2 instruments and SSBUV with corresponding data from other instruments. In the preceding six months, SSBUV data from the ATLAS-3 (November 1994) mission were compared to coincident SUSIM ATLAS-3 data. The GOME instrument was launched by the European Space Agency in early 1995 and began making solar irradiance measurements in May 1995. Working with GOME scientists, we are using SSBUV data to validate the GOME solar irradiance data. Based in part on those findings, the GOME absolute calibration data were reanalyzed.

Cebula, Richard P.↗