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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 883 records · Page 49
All sourcesNASA NTRSDOE OSTI
NASA NTRS1991

Use of high spectral resolution airborne visible/infrared imaging spectrometer data for geologic mapping: An overview

Specific examples of the use of AVIRIS (Airborne Visible/Infrared Imaging Spectrometer) high spectral resolution data for mapping, alteration related to ore deposition and to hydrocarbon seepage, and alluvial fans are presented. Correction for atmospheric effects was performed using flat field correction, log residuals, and radiative transfer modeling. Minerals of interest (alunite, kaolinite, gypsum, carbonate iron oxides, etc.) were mapped based upon the wavelength position, depth and width of characteristic absorption features. Results were checked by comparing to existing maps, results from other sensors (Thematic Mapper (TM) and TIMS (Thermal Infrared Multispectral Scanner)), and laboratory spectra of samples collected in the field. Alteration minerals were identified and mapped. The signal to noise ratio of acquired AVIRIS data, long to 2.0 microns, was insufficient to map minerals of interest.

Carrere, Veronique↗
NASA NTRS1996

Far-Infrared Spectroscopy of Planetary Nebulae with the KAO

We present new far-infrared line observations of the planetary nebulae (PNs) NGC 7027, NGC 7009, and NGC 6210 obtained with the Kuiper Airborne Observatory (KAO). The bulk of our data are for NGC 7027 and NGC 7009, including [Ne(V)] 24 micrometers, [O(IV)] 26 micrometers, [O(III)] (52, 88) micrometers, and [N(III)] 57 micrometers. Our data for [O(III)] (52, 88) and [N(III)] 57 in NGC 7027 represent the first measurements of these lines in this source. The large [O(III)] 52/88-micrometer flux ratio implies an electron density (cubic cm) of log N(sub e)[O(III)] = 4.19, the largest Ne ever inferred from these lines. We derive N(++)/O(++) = 0.394 +/- 0.062 for NGC 7027 and 0.179 +/- 0.043 for NGC 6210. We are able to infer the O(+3)/O(++) ionic ratio from our data. As gauged by this ionic ratio, NGC 7027 is substantially higher ionization than is NGC 7009 - consistent with our observation that the former produces copious [Ne(V)] emission while the latter does not. These data help characterize the stellar ionizing radiation field. From our [O(IV)] and [O(III)] fluxes, we are able to show that O(++) is by far the dominant oxygen ion in NGC 7009. As a result, the O/H abundance inferred using these data tends to corroborate the value found from UV/optical, collisionally excited lines. We determined accurate rest wavelengths for the [Ne(V)] 2s(2)2p(2)P(sub 1) to 2s(2)2p(2)3P(sub 0) (lambda(sub rest) = 24.316 +/- 0.008 micrometers) and [O(IV)] 2s(2)2p(2)P(sup 0, sub 3/2) to 2s(2)2p(2)P(sup 0, sub 1/2) (lambda(sub rest) = 25.887 +/- 0.007 micrometers) transitions from observations of one or both of the bright PNs NGC 7027 and NGC 7009. Our [O(IV)] value, to the best of our knowledge, is the most accurate direct determination of this lambda(sub rest). These new KAO data will be beneficial for comparison with ISO observations of these PNs.

Rubin, Robert H.↗
DOE OSTI2022

High-Mileage Courier Fleet Vehicle On-road Logger Data

This dataset describes the performance and fuel efficiency of AVTA test vehicles operating in commercial courier fleets the Phoenix, AZ metro area between 2010 and 2016. Aftermarket data loggers were installed in two to four vehicles of each of 30+ distinct year/make/models (see reference ["INL Advanced Vehicle Testing Activity: On-road Logger and Laboratory Battery Pack Testing Vehicle List"](https://avt.inl.gov/sites/default/files/pdf/reports/DatasetVehicleList.pdf) for full list of vehicles). Loggers recorded vehicle operation as they were driven up to 160,000 miles in up to three years of fleet testing. Parameters were logged at 1-second intervals, including - vehicle speed, - engine and/or electric motor speed, - fuel and/or electricity consumption, and - ambient temperature. This dataset includes both raw second-by-second data and trip-level metrics. (This dataset will be shared by API; a small sample of the vehicle and logger data has been extracted and is available for download while the API is being developed.)

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2026

High-Mileage Courier Fleet Vehicle On-Road Logger Data

This dataset describes the performance and fuel efficiency of AVTA test vehicles operating in commercial courier fleets the Phoenix, AZ metro area between 2010 and 2016. Aftermarket data loggers were installed in two to four vehicles of each of 30+ distinct year/make/models (see reference ["INL Advanced Vehicle Testing Activity: On-road Logger and Laboratory Battery Pack Testing Vehicle List"](https://avt.inl.gov/sites/default/files/pdf/reports/DatasetVehicleList.pdf) for full list of vehicles). Loggers recorded vehicle operation as they were driven up to 160,000 miles in up to three years of fleet testing. Parameters were logged at 1-second intervals, including - vehicle speed, - engine and/or electric motor speed, - fuel and/or electricity consumption, and - ambient temperature. This dataset includes both raw second-by-second data and trip-level metrics. This dataset is shared by API; a small sample of the vehicle and logger data has been extracted and is also available for download.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2020

Damped Ly α absorbers and atomic hydrogen in galaxies: the view of the GAEA model

ABSTRACT Using the GAEA semi-analytic model, we analyse the connection between Damped Ly α systems (DLAs) and H i in galaxies. Our state-of-the-art semi-analytic model is tuned to reproduce the local galaxy H i mass function, and that also reproduces other important galaxy properties, including the galaxy mass–gas metallicity relation. To produce catalogues of simulated DLAs we throw 105 random lines of sight in a composite simulated volume: dark matter haloes with log$(\frac{M_{200}}{ {\rm M}_{\odot }}) \ge 11.5$ are extracted from the Millennium Simulation, while for $9.2 \le \log (\frac{M_{200}}{ \mathrm{M}_{\odot }})\lt 11.5$ we use the Millennium II, and for $8 \le \log (\frac{M_{200}}{\mathrm{M}_{\odot }}) \lt 9.2$ a halo occupation distribution model. At 2 < z < 3, where observational data are more accurate, our fiducial model predicts the correct shape of the column density distribution function, but its normalization falls short of the observations, with the discrepancy increasing at higher redshift. The agreement with observations is significantly improved increasing both the H i masses and the disc radii of model galaxies by a factor of 2, as implemented ‘a posteriori’ in our 2M−2R model. In the redshift range of interest, haloes with $M_{200} \ge {10}^{11} \, \mathrm{M}_{\odot }$ give the major contribution to ΩDLA, and the typical DLA host halo mass is $\sim \!{10}^{11} \, \mathrm{M}_{\odot }$. The simulated DLA metallicity distribution is in relatively good agreement with observations, but our model predicts an excess of DLAs at low metallicities. Our results suggest possible improvements for the adopted modelling of the filtering mass and metal ejection in low-mass haloes.

Di Gioia, Serafina↗
DOE OSTI2025

BLOC site - NREL Scanning Lidar / Derived Data

This dataset contains daily csv files summarizing data from 10-min wind statistics from ground-based Doppler lidar at the BLOC site for the WFIP3 event log. See https://a2e.energy.gov/ds/wfip3/bloc.lidar.10min.z01.c1/summary. This lidar was Halo XR #216 through February 24, 2025, Halo XR #217 from February 24, 2025, through April 17, 2025, and again Halo XR #216 after that.

17 WIND ENERGY↗
DOE OSTI2025

RHOD site - NREL Scanning Lidar / Derived Data

This dataset contains daily csv files summarizing data from 10-min wind statistics from ground-based Doppler lidar at the RHOD site for the WFIP3 event log. See https://a2e.energy.gov/ds/wfip3/rhod.lidar.10min.z01.c1/summary

17 WIND ENERGY↗
DOE OSTI2025

NANT site - Doppler Lidar / Derived Data

This dataset contains daily csv files summarizing data from 10-min wind statistics from ground-based Doppler lidar at the NANT site for the WFIP3 event log. See https://a2e.energy.gov/ds/wfip3/nant.lidar.10min.z02.c1/summary

17 WIND ENERGY↗
DOE OSTI2025

NANT site - Doppler Lidar / Derived Data

This dataset contains daily csv files summarizing data from 10-min wind statistics from ground-based Doppler lidar at the NANT site for the WFIP3 event log. See https://a2e.energy.gov/ds/wfip3/nant.lidar.10min.z01.c1/summary

17 WIND ENERGY↗
NASA NTRS1981

The high-excitation planetary nebulae: NGC 3918 and IC 2448

International Ultraviolet Exploration observations of NGC 3918 and IC 2448 are presented. Combining these observations with data in the optical range and computed model structure, the chemical composition for these objects is derived. For NGC 3918 log C = -3.02, log N = -3.61 and log 0 = -3.22; while for IC 2448 log C = -3.44, log N = -81 and log 0 = 3.54.

Torres-Peimbert, S.↗
NASA NTRS1986

Instantaneous velocity profile measurements in a turbulent boundary layer

Instantaneous wall shear stress and streamwise velocities have been measured simultaneously in a flat-plate, turbulent boundary layer at moderate Reynolds number in an effort to provide experimental support for large eddy simulations. Data were obtained using a buried-wire, wall shear gage and a hot-wire rake positioned in the log region of the flow. Fluctuations of the instantaneous U(+) versus Y(+) profiles about a mean law of the wall are shown to be significant and complex. Peak cross-correlation values between wall shear stress and the velocities are high, and reflect the passage of a large structure inclined at a small angle to the wall. Estimates of this angle are consistent with those made by other investigators. Conditional sampling techniques were used to detect the passage of various sizes and types of flow disturbances (events), and to estimate their mean frequency of occurrence. Events characterized by large aand sudden streamwise accelerations were found to be highly coherent throughout the log region and were strongly correlated with large fluctuations in wall shear stress. Phase randomness between the near-wall quantities and the outer velocities was small. The results suggest that the flow events detected by conditional sampling applied to velocities in the log region may be related to the bursting process.

Robinson, S. K.↗
NASA NTRS1988

The IUE data bank: Statistics and future aspects

The data exchange policy between Goddard Space Flight Center and ESA's Villafranca (Spain) station is described. The IUE data banks and their uses are outlined. Statistical information on objects observed, the quantity of data distributed and retrieved from the archives, together with a detailed design of the final format of the IUE merged log are also given.

Schmitz, Marion↗
NASA NTRS2003

A Massive X-ray Outflow From The Quasar PDS 456

We report on XMM-Newton spectroscopic observations of the luminous, radio-quiet quasar PDS 456. The hard X-ray spectrum of PDS 456 shows a deep absorption trough (constituting 50% of the continuum) at energies above 7 keV in the quasar rest frame, which can be attributed to a series of blue-shifted K-shell absorption edges due to highly ionized iron. The higher resolution soft X-ray grating RGS spectrum exhibits a broad absorption line feature near 1 keV, which can be modeled by a blend of L-shell transitions from highly ionized iron (Fe XVII - XXIV). An extreme outflow velocity of approx. 50000 km/s is required to model the K and L shell iron absorption present in the XMM-Newton data. Overall, a large column density (N(sub H) = 5 x 10(exp 23)/sq cm) of highly ionized gas (log xi = 2.5) is required in PDS 456. A large mass outflow rate of approx. 10 solar mass/year (assuming a conservative outflow covering factor of 0.1 steradian) is derived, which is of the same order as the overall mass accretion rate in PDS 456. This represents a substantial fraction (approx. 10%) of the quasar energy budget, whilst the large column and outflow velocity place PDS 456 towards the extreme end of the broad absorption line quasar population.

Reeves, J. N.↗
NASA NTRS2011

Sptrace

Sptrace is a general-purpose space utilization tracing system that is conceptually similar to the commercial Purify product used to detect leaks and other memory usage errors. It is designed to monitor space utilization in any sort of heap, i.e., a region of data storage on some device (nominally memory; possibly shared and possibly persistent) with a flat address space. This software can trace usage of shared and/or non-volatile storage in addition to private RAM (random access memory). Sptrace is implemented as a set of C function calls that are invoked from within the software that is being examined. The function calls fall into two broad classes: (1) functions that are embedded within the heap management software [e.g., JPL's SDR (Simple Data Recorder) and PSM (Personal Space Management) systems] to enable heap usage analysis by populating a virtual time-sequenced log of usage activity, and (2) reporting functions that are embedded within the application program whose behavior is suspect. For ease of use, these functions may be wrapped privately inside public functions offered by the heap management software. Sptrace can be used for VxWorks or RTEMS realtime systems as easily as for Linux or OS/X systems.

Burleigh, Scott C.↗
NASA NTRS2022

Universal Scaling Laws for Solar and Stellar Atmospheric Heating: Catalog of Power-law Index between Solar Activity Proxies and Various Spectral Irradiances

The formation of extremely hot outer atmospheres is one of the most prominent manifestations of magnetic activity common to late-type dwarf stars, including the Sun. It is widely believed that these atmospheric layers, the corona, transition region, and chromosphere, are heated by the dissipation of energy transported upwards from the stellar surface by the magnetic field. This is signified by the spectral line fluxes at various wavelengths, scaled with power-law relationships against the surface magnetic flux over a wide range of formation temperatures, which are universal to the Sun and Sunlike stars of different ages and activity levels. This study describes a catalog of power-law indices between solar activity proxies and various spectral line fluxes. Compared to previous studies, we expanded the number of proxies, which now includes the total magnetic flux, total sunspot number, total sunspot area, and the F10.7 cm radio flux, and further enhanced the number of spectral lines by a factor of 2. This provides the data to study in detail the flux–flux scaling laws from the regions specified by the temperatures of the corona (log(T/K) = 6–7) to those of the chromosphere (log(T/K) ∼ 4), as well as the reconstruction of various spectral line fluxes of the Sun in the past, F-, G-, and K-type dwarfs, and the modeled stars.

Stellar coronae↗
NASA NTRS2022

Comparison of U.S. and Russian Slow Crack Growth Data and Models

Both the US and Russian space programs use similar predictive models for design of fused silica windows on the International space station. The Russian model can be derived from the power expression for slow crack growth (SCG) or “static fatigue.” The US uses both power and exponential models. Despite the similarity of models and data fitting approach (linear regression and right censoring), different SCG parameters have been derived by US and Russian parties for the same material (Russian fused silica) tested in a similar manner. The difference appears to be related to the use of short-term strength data along with the longer-term static fatigue data, with the power law parameter n being very sensitive to the conversion of strength data into equivalent static data. This hybrid approach is feasible if strength data is measured with a constant stress rate and is appropriately converted to a static equivalent. More research into the approach is needed. However, because of the nonlinear behavior of fused silica in log(v) – log(K(I) ) space and the sensitivity of parameter estimation to fit range, the exponential model is a better choice regardless of test method. Functions are given to convert parameters from the Russian model to those in the US model. However, accurate conversion is hampered by the lack of inert strength data. When the same test technique is used, US and Russian materials exhibit very similar parameters.

Silica, strength, impact, crack growth, windows, I↗
NASA NTRS1994

The Orion OB1 association. 1: Stellar content

Walfraven photometry of established and probable members of the Orion OB1 association is presented. Effective temperature, surface gravity, luminosity and mass are derived for all stars, using atmosphere model by Kurucz (1979). Absolute magnitudes are calculated using the Straizys and Kuriliene (1981) tables. Distance moduli and visual extinctions are determined. A comparison of the visual extinctions to IRAS 100 micrometers data shows that the near edge of the Orion A and B clouds lies at a distance of approximately 320 pc, while the far edge is at approximately 500 pc. A method for deriving the ages of the subgroups by comparing theoretical isochrones to the observations in the log g, log T(sub eff) plane is presented. The derived ages suggest, contrary to earlier studies, that subgroup 1b is younger than 1c, which can possibly be explained by past geometries of the system of stars and gas. The initial mass function for Orion OB1 is derived with the aid of the Kolmogorov-Smirnoff test. Through extensive simulations, we show that it is very difficult to derive accurately the Initial Mass Function (IMF) from the available data. To within somewhat weak limits the IMF is found to be of the form xi(log M) = AM(exp -1.7 +/- 0.2) for all subgroups. The energy output of the subgroups in the form of stellar winds and supernovae is calculated and compared to the observed size and expansion velocity of the Orion-Eridanus bubble. It is shown that the energy output of the association can account for the morphology and kinematics of the interstellar medium (ISM).

Brown, A. G. A.↗