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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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All sourcesNASA NTRSDOE OSTI
NASA NTRS2013

Plasmaspheric H+, He+, O+, He++, and O++ Densities and Temperatures

Thermal plasmaspheric densities and temperatures for five ion species have recently become available, even though these quantities were derived some time ago from the Retarding Ion Mass Spectrometer onboard the Dynamics Explorer 1 satellite over the years 1981-1984. The quantitative properties will be presented. Densities are found to have one behavior with lessor statistical variation below about L=2 and another with much greater variability above that Lshell. Temperatures also have a behavior difference between low and higher L-values. The density ratio He++/H+ is the best behaved with values of about 0.2% that slightly increase with increasing L. Unlike the He+/H+ density ratio that on average decreases with increasing Lvalue, the O+/H+ and O++/H+ density ratios have decreasing values below about L=2 and increasing average ratios at higher L-values. Hydrogen ion temperatures range from about 0.2 eV to several 10s of eV for a few measurements, although the bulk of the observations are of temperatures below 3 eV, again increasing with L-value. The temperature ratios of He+/H+ are tightly ordered around 1.0 except for the middle plasmasphere between L=3.5 and 4.5 where He+ temperatures can be significantly higher. The temperatures of He++, O+, and O++ are consistently higher than H+.

Gallagher, D. L.↗
NASA NTRS2013

Plasmaspheric H+, He+, He++, O+, and O++ Densities and Temperatures

Thermal plasmaspheric densities and temperatures for five ion species have recently become available, even though these quantities were derived some time ago from the Retarding Ion Mass Spectrometer onboard the Dynamics Explorer 1 satellite over the years 1981-1984. The quantitative properties will be presented. Densities are found to have one behavior with lessor statistical variation below about L=2 and another with much greater variability above that Lshell. Temperatures also have a behavior difference between low and higher L-values. The density ratio He++/H+ is the best behaved with values of about 0.2% that slightly increase with increasing L. Unlike the He+/H+ density ratio that on average decreases with increasing Lvalue, the O+/H+ and O++/H+ density ratios have decreasing values below about L=2 and increasing average ratios at higher L-values. Hydrogen ion temperatures range from about 0.2 eV to several 10s of eV for a few measurements, although the bulk of the observations are of temperatures below 3 eV, again increasing with L-value. The temperature ratios of He+/H+ are tightly ordered around 1.0 except for the middle plasmasphere between L=3.5 and 4.5 where He+ temperatures can be significantly higher. The temperatures of He++, O+, and O++ are consistently higher than H+.

Gallagher, G. L.↗
NASA NTRS2012

Continental-scale Validation of MODIS-based and LEDAPS Landsat ETM+ Atmospheric Correction Methods

The potential of Landsat data processing to provide systematic continental scale products has been demonstrated by several projects including the NASA Web-enabled Landsat Data (WELD) project. The recent free availability of Landsat data increases the need for robust and efficient atmospheric correction algorithms applicable to large volume Landsat data sets. This paper compares the accuracy of two Landsat atmospheric correction methods: a MODIS-based method and the Landsat Ecosystem Disturbance Adaptive Processing System (LEDAPS) method. Both methods are based on the 6SV radiative transfer code but have different atmospheric characterization approaches. The MODIS-based method uses the MODIS Terra derived dynamic aerosol type, aerosol optical thickness, and water vapor to atmospherically correct ETM+ acquisitions in each coincident orbit. The LEDAPS method uses aerosol characterizations derived independently from each Landsat acquisition and assumes a fixed continental aerosol type and uses ancillary water vapor. Validation results are presented comparing ETM+ atmospherically corrected data generated using these two methods with AERONET corrected ETM+ data for 95 10 km×10 km 30 m subsets, a total of nearly 8 million 30 m pixels, located across the conterminous United States. The results indicate that the MODIS-based method has better accuracy than the LEDAPS method for the ETM+ red and longer wavelength bands.

Landsat↗
NASA NTRS2014

Development of a Water Recovery System Resource Tracking Model

A simulation model has been developed to track water resources in an exploration vehicle using regenerative life support (RLS) systems. The model integrates the functions of all the vehicle components that affect the processing and recovery of water during simulated missions. The approach used in developing the model results in the RTM being a part of of a complete vehicle simulation that can be used in real time mission studies. Performance data for the variety of components in the RTM is focused on water processing and has been defined based on the most recent information available for the technology of the component. This paper will describe the process of defining the RLS system to be modeled and then the way the modeling environment was selected and how the model has been implemented. Results showing how the variety of RLS components exchange water are provided in a set of test cases.

Chambliss, Joe↗
NASA NTRS2015

Development of a Water Recovery System Resource Tracking Model

A simulation model has been developed to track water resources in an exploration vehicle using Regenerative Life Support (RLS) systems. The Resource Tracking Model (RTM) integrates the functions of all the vehicle components that affect the processing and recovery of water during simulated missions. The approach used in developing the RTM enables its use as part of a complete vehicle simulation for real time mission studies. Performance data for the components in the RTM is focused on water processing. The data provided to the model has been based on the most recent information available regarding the technology of the component. This paper will describe the process of defining the RLS system to be modeled, the way the modeling environment was selected, and how the model has been implemented. Results showing how the RLS components exchange water are provided in a set of test cases.

Chambliss, Joe↗
NASA NTRS2015

Jovian plasma modeling for mission design

The purpose of this report is to address uncertainties in the plasma models at Jupiter responsible for surface charging and to update the jovian plasma models using the most recent data available. The updated plasma environment models were then used to evaluate two proposed Europa mission designs for spacecraft charging effects using the Nascap-2k code. The original Divine/Garrett jovian plasma model (or "DG1", T. N. Divine and H. B. Garrett, "Charged particle distributions in Jupiter's magnetosphere," J. Geophys. Res., vol. 88, pp. 6889-6903,1983) has not been updated in 30 years, and there are known errors in the model. As an example, the cold ion plasma temperatures between approx.5 and 10 Jupiter radii (Rj) were found by the experimenters who originally published the data to have been underestimated by approx.2 shortly after publication of the original DG1 model. As knowledge of the plasma environment is critical to any evaluation of the surface charging at Jupiter, the original DG1 model needed to be updated to correct for this and other changes in our interpretation of the data so that charging levels could beproperly estimated using the Nascap-2k charging code. As an additional task, the Nascap-2k spacecraft charging tool has been adapted to incorporate the so-called Kappa plasma distribution function--an important component of the plasma model necessary to compute the particle fluxes between approx.5 keV and 100 keV (at the outset of this study,Nascap-2k did not directly incorporate this common representation of the plasma thus limiting the accuracy of our charging estimates). The updating of the DG1 model and its integration into the Nascap-2k design tool means that charging concerns can now be more efficiently evaluated and mitigated. (We note that, given the subsequent decision by the Europa project to utilize solar arrays for its baseline design, surface charging effects have becomeeven more of an issue for its mission design). The modifications and results of those modifications to the DG1 model to produce the new DG2 model presented here and the steps taken to integrate the DG2 predictions into Nascap-2k are described in this report.

Voyager 2↗
NASA NTRS2015

Jovian Plasma Modeling for Mission Design

The purpose of this report is to address uncertainties in the plasma models at Jupiter responsible for surface charging and to update the jovian plasma models using the most recent data available. The updated plasma environment models were then used to evaluate two proposed Europa mission designs for spacecraft charging effects using the Nascap-2k code. The original Divine/Garrett jovian plasma model (or "DG1", T. N. Divine and H. B. Garrett, "Charged particle distributions in Jupiter's magnetosphere," J. Geophys. Res., vol. 88, pp. 6889-6903,1983) has not been updated in 30 years, and there are known errors in the model. As an example, the cold ion plasma temperatures between approx.5 and 10 Jupiter radii (Rj) were found by the experimenters who originally published the data to have been underestimated by approx.2 shortly after publication of the original DG1 model. As knowledge of the plasma environment is critical to any evaluation of the surface charging at Jupiter, the original DG1 model needed to be updated to correct for this and other changes in our interpretation of the data so that charging levels could beproperly estimated using the Nascap-2k charging code. As an additional task, the Nascap-2k spacecraft charging tool has been adapted to incorporate the so-called Kappa plasma distribution function--an important component of the plasma model necessary to compute the particle fluxes between approx.5 keV and 100 keV (at the outset of this study,Nascap-2k did not directly incorporate this common representation of the plasma thus limiting the accuracy of our charging estimates). The updating of the DG1 model and its integration into the Nascap-2k design tool means that charging concerns can now be more efficiently evaluated and mitigated. (We note that, given the subsequent decision by the Europa project to utilize solar arrays for its baseline design, surface charging effects have becomeeven more of an issue for its mission design). The modifications and results of those modifications to the DG1 model to produce the new DG2 model presented here and the steps taken to integrate the DG2 predictions into Nascap-2k are described in this report

Garrett, Henry B.↗
NASA NTRS2016

Estimation of Daily PM(sub 10) Concentrations in Italy (2006-2012) Using Finely Resolved Satellite Data, Land Use Variables and Meteorology

Health effects of air pollution, especially particulate matter (PM), have been widely investigated. However, most of the studies rely on few monitors located in urban areas for short-term assessments, or land use/dispersion modelling for long-term evaluations, again mostly in cities. Recently, the availability of finely resolved satellite data provides an opportunity to estimate daily concentrations of air pollutants over wide spatio-temporal domains. Italy lacks a robust and validated high resolution spatio-temporally resolved model of particulate matter. The complex topography and the air mixture from both natural and anthropogenic sources are great challenges difficult to be addressed. We combined finely resolved data on Aerosol Optical Depth (AOD) from the Multi-Angle Implementation of Atmospheric Correction (MAIAC) algorithm, ground-level PM10measurements, land-use variables and meteorological parameters into a four-stage mixed model framework to derive estimates of daily PM10concentrations at 1-km2 grid over Italy, for the years 2006-2012. We checked performance of our models by applying 10-fold cross-validation (CV) for each year. Our models displayed good fitting, with mean CV-R2=0.65 and little bias (average slope of predicted VS observed PM10=0.99). Out-of-sample predictions were more accurate in Northern Italy (Po valley) and large conurbations (e.g. Rome), for background monitoring stations, and in the winter season. Resulting concentration maps showed highest average PM10levels in specific areas (Po river valley, main industrial and metropolitan areas) with decreasing trends over time. Our daily predictions of PM10concentrations across the whole Italy will allow, for the first time, estimation of long-term and short-term effects of air pollution nationwide, even in areas lacking monitoring data. Copyright © 2016 Elsevier Ltd. All rights reserved.

Particulate Matter/analysis↗
NASA NTRS2019

Physical Models for Accreting Pulsars at High Luminosity

A new window for better understanding the accretion onto strongly magnetized neutron stars in X-ray binaries is opening. In these systems the accreted material follows the magnetic field lines as it approaches the neutron star, forming accretion columns above the magnetic poles. The plasma falls toward the neutron star surface at near-relativistic speeds, losing energy by emitting X-rays. The X-ray spectral continua are commonly described using phenomenological models, i.e., power laws with different types of curved cut-offs at higher energies. Here we consider high luminosity pulsars. In these systems the mass transfer rate is high enough that the accreting plasma is thought to be decelerated in a radiation-dominated radiative shock in the accretion columns. While the theory of the emission from such shocks had already been developed by 2007, a model for direct comparison with X-ray continuum spectra in xspec or isis has only recently become available. Here we analyze the broadband X-ray spectra of the accreting pulsars Centaurus X-3 and 4U1626-67 obtained withNuSTAR. We present results from traditional empirical modeling as well as successfully apply the radiation-dominated radiative shock model. We also fit the energy-dependent pulse profiles of 4U 1626-67 using a new relativistic light bending model.

Pottschmidt, Katja↗
NASA NTRSDate not supplied

The Oxidation State of Sulfur in Apollo Samples 71035 and 71055

Lunar apatites contain 100s-1000s ppm sulfur [1-3]. This was initially puzzling because lunar basalts are thought to form, including at the time of apatite crystallization, in low oxygen fugacity (fO2) conditions where sulfur exists in its reduced form (S2-), a substitution not previously observed in natural apatite. It has been recently shown, using S-XANES measurements of the oxidation state of sulfur in apatites and proximal mesostasis in the lunar basalts 12039 and 10044, that sulfur is indeed present as S2- in both the mesostasis glass and apatite when measurements were performed far from cracks or pits in the thin section [4]. This observation is consistent with other mineralogical indications of the low fO2 during formation of these samples (~IW-1) such as the presence of Fe-metal, ulvöspinel, ilmenite, fayalite, and silica in the thin sections. In the same study, in addition to clear spectral evidence for the dominance of S2-, analyses of apatite grains in both samples that occurred near cracks or pits in the thin section sometimes revealed non-negligible spectral evidence (e.g., S6+/ΣS > 0.03; [4]) for the presence of S6+. Because S6+ was not observed in the mesostasis glass near the apatite grains measured, or in any phase far from cracks or pits in the studied thin sections, this S6+ was interpreted as either primary S2- in the sulfide altered to S6+ in the thin section, or S6+ of secondary origin, deposited in the fractures of the samples [4, 5]. Whether this is of lunar or terrestrial origin is unknown but has implications for lunar petrogenesis if lunar [e.g., 5], or sample handling and curation if terrestrial. To test between lunar and terrestrial origins for observed S6+ in Apollo-era thin sections, we will measure the oxidation state of sulfur in apatite and associated phases in a specially frozen sample from a boulder sampled at Station 1A during the Apollo 17 mission as part of the NASA Apollo Next Generation Sample Analysis (ANGSA) program. Here, we present “control” measurements of samples 71035 and 71055, using Apollo era thin sections of aliquots of these rocks that were processed upon return to Earth and since stored under N2 atmospheres at room temperature. These will be compared to measurements using newly made thin sections of aliquots of the same rocks (71035 and 71055). In addition, 71036, which has been in cold storage (-20℃) since the return of the Apollo 17 mission to Earth, has been recently made available through the ANGSA program. With 71036 we can test the effect of storage temperature on potential oxidation of S2- to S6+ in the relatively oxidizing and warm conditions of Earth’s surface.

apollo↗
NASA NTRS2020

Machine Learning Algorithm Performance on the Lucata Computer

A new parallel computing paradigm (processor in memory, or PIM) has recently become available, one that uses many lightweight threads, and where each thread migrates automatically to the memory used by that thread. Our effort focuses on understanding how suitable this architecture is for our application, and whether the hardware can sustain speedups as high as the system size permits. In particular we explore the kind of code optimizations needed, and how well optimized code scales. This paper describes some of the those optimizations, and the payoff in terms of scaling.

Kogge, Peter↗
NASA NTRS2013

Near Real Time Tools for ISS Plasma Science and Engineering Applications

The International Space Station (ISS) program utilizes a plasma environment forecast for estimating electrical charging hazards for crews during extravehicular activity (EVA). The process uses ionospheric electron density and temperature measurements from the ISS Floating Potential Measurement Unit (FPMU) instrument suite with the assumption that the plasma conditions will remain constant for one to fourteen days with a low probability for a space weather event which would significantly change the environment before an EVA. FPMU data is typically not available during EVA's, therefore, the most recent FPMU data available for characterizing the state of the ionosphere during EVA is typically a day or two before the start of an EVA or after the EVA has been completed. In addition to EVA support, information on ionospheric plasma densities is often needed for support of ISS science payloads and anomaly investigations during periods when the FPMU is not operating. This presentation describes the application of space weather tools developed by MSFC using data from near real time satellite radio occultation and ground based ionosonde measurements of ionospheric electron density and a first principle ionosphere model providing electron density and temperature run in a real time mode by GSFC. These applications are used to characterize the space environment during EVA periods when FPMU data is not available, monitor for large charges in ionosphere density that could render the ionosphere forecast and plasma hazard assessment invalid, and validate the assumption of "persistence of conditions" used in deriving the hazard forecast. In addition, the tools are used to provide space environment input to science payloads on ISS and anomaly investigations during periods the FPMU is not operating.

Minow, Joseph I.↗
NASA NTRS2013

Near Real Time Tools for ISS Plasma Science and Engineering Applications

The International Space Station (ISS) program utilizes a plasma environment forecast for estimating electrical charging hazards for crews during extravehicular activity (EVA). The process uses ionospheric electron density (Ne) and temperature (Te) measurements from the ISS Floating Potential Measurement Unit (FPMU) instrument suite with the assumption that the plasma conditions will remain constant for one to fourteen days with a low probability for a space weather event which would significantly change the environment before an EVA. FPMU data is typically not available during EVA's, therefore, the most recent FPMU data available for characterizing the state of the ionosphere during EVA is typically a day or two before the start of an EVA or after the EVA has been completed. Three near real time space weather tools under development for ISS applications are described here including: (a) Ne from ground based ionosonde measurements of foF2 (b) Ne from near real time satellite radio occultation measurements of electron density profiles (c) Ne, Te from a physics based ionosphere model These applications are used to characterize the ISS space plasma environment during EVA periods when FPMU data is not available, monitor for large changes in ionosphere density that could render the ionosphere forecast and plasma hazard assessment invalid, and validate the "persistence of conditions" forecast assumption. In addition, the tools are useful for providing space environment input to science payloads on ISS and anomaly investigations during periods the FPMU is not operating.

Minow, Joseph I.↗
DOE OSTI2020

Coupled-cluster techniques for computational chemistry: The CFOUR program package

An up-to-date overview of the CFOUR program system is given. After providing a brief outline of the evolution of the program since its inception in 1989, a comprehensive presentation is given of its well-known capabilities for high-level coupled-cluster theory and its application to molecular properties. Subsequent to this generally well-known background information, much of the remaining content focuses on lesser-known capabilities of CFOUR, most of which have become available to the public only recently or will become available in the near future. Each of these new features is illustrated by a representative example, with additional discussion targeted to educating users as to classes of applications that are now enabled by these capabilities. Lastly, some speculation about future directions is given, and the mode of distribution and support for CFOUR are outlined in the appendix.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗