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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 NTRS2010

Aerosol Observability and Predictability: From Research to Operations for Chemical Weather Forecasting. Lagrangian Displacement Ensembles for Aerosol Data Assimilation

A challenge common to many constituent data assimilation applications is the fact that one observes a much smaller fraction of the phase space that one wishes to estimate. For example, remotely sensed estimates of the column average concentrations are available, while one is faced with the problem of estimating 3D concentrations for initializing a prognostic model. This problem is exacerbated in the case of aerosols because the observable Aerosol Optical Depth (AOD) is not only a column integrated quantity, but it also sums over a large number of species (dust, sea-salt, carbonaceous and sulfate aerosols. An aerosol transport model when driven by high-resolution, state-of-the-art analysis of meteorological fields and realistic emissions can produce skillful forecasts even when no aerosol data is assimilated. The main task of aerosol data assimilation is to address the bias arising from inaccurate emissions, and Lagrangian misplacement of plumes induced by errors in the driving meteorological fields. As long as one decouples the meteorological and aerosol assimilation as we do here, the classic baroclinic growth of error is no longer the main order of business. We will describe an aerosol data assimilation scheme in which the analysis update step is conducted in observation space, using an adaptive maximum-likelihood scheme for estimating background errors in AOD space. This scheme includes e explicit sequential bias estimation as in Dee and da Silva. Unlikely existing aerosol data assimilation schemes we do not obtain analysis increments of the 3D concentrations by scaling the background profiles. Instead we explore the Lagrangian characteristics of the problem for generating local displacement ensembles. These high-resolution state-dependent ensembles are then used to parameterize the background errors and generate 3D aerosol increments. The algorithm has computational complexity running at a resolution of 1/4 degree, globally. We will present the result of assimilating AOD retrievals from MODIS (on both Aqua and TERRA satellites) from AERONET for validation. The impact on the GEOS-5 Aerosol Forecasting will be fully documented.

da Silva, Arlindo↗
NASA NTRS1994

(H2)2 mole-fraction altitude profile in the atmosphere of Jupiter: A computational study

The mole fraction x(sub 2) of (H2)2 in equilibrium mixture with H2 under the atmospheric conditions of Jupiter is evaluated from the dimerization equilibrium constant calculated by quantum-chemical treatments and also from the Lennard-Jones potential. The treatments are of an ab initio type with the second and fourth order Moller-Plesset perturbation techniques and a basis set superposition error evaluation. The computed dimerization equilibrium constant is combined with observed height profiles of temperature and pressure. In six treatments considered it is found that the mole fraction decreases with increasing height. Various approximations suggest the dimeric mole fraction at the Jupiter 1 atm pressure level between 0.04 and 1.06%.

Slanina, Zdenek↗
NASA NTRSDate not supplied

A window on the composition of the early solar nebula: 2014MU69, Pluto, and Phoebe

The initial chemical composition of any solar nebula will depend upon the degree to which 1) organic and ice components form on dust grains, 2) organic and molecular species form in the gas phase, 3) organics and ices are exchanged between the gas and solid state, and 4) the precursor and newly formed (more complex) materials survive and are modified in the developing planetary system. Infrared and radio observations of star-forming regions reveal that complex chemistry occurs on icy grains, sometimes before stars even form. Additional processing, through the protosolar disk and within the solar nebula further modifies most, but probably not all, of the initial materials. In fact, the modern Solar System still carries a fraction of its interstellar inheritance [Alexander et al., 2017]. Here we focus on three examples of small bodies in our Solar System, each containing chemical and dynamical clues to its origin and evolution: the small, cold-classical Kuiper Belt object (KBO) 2014MU69 , Pluto and Saturn’s moon, Phoebe. The New Horizons flyby of 2014 MU69 has given the first view of an unaltered body composed of material originally in the solar nebula at ~45 AU. The spectrum reveals methanol ice (not commonly found), a possible detection of water ice (Stern et al. 2019). Pluto’s internal and surface inventory of volatiles and complex organics, together with active geological processes including cryo-volcanism, indicate a surprising level of activity on a body in the outermost region of the Solar System, and the fluid that emerges from subsurface reservoirs may contain material inherited from the solar nebula (Cruikshank et al. 2019). Meanwhile, Saturn's captured moon, Phoebe, carries high D/H in H2O [Clark et al. 2018)], and complex organics (Cruikshank et al. 2008), both consistent with its formation in, and inheritance from, the outer solar nebula. Together, these objects provide windows on the origin and evolution of our Solar System and constraints to be considered in future chemical and physical models of PPDs. The Spitzer Space telescope discovered the ring of dust around Saturn that emanated from the bombardment of Phoebe in the recent past, dislodging primitive Solar System material from deep within that satellite. In addition, Spitzer has provided detailed studies of the chemistry of star forming regions where methanol and other ices are readily observed. As a result of these and other observations, protoplanetary disk models are beginning to combine both dynamical and chemical complexities into their codes, resulting in new insights for exoplanetary systems.

Yvonne J. Pendleton↗
NASA NTRS1978

Satellite formation. II

A satellite formation model is extended to include evolution of planetary ring material and elliptic orbital motion. In this model the formation of the moon begins at a later time in the growth of the earth, and a significant fraction of the lunar material is processed through a circumterrestrial debris cloud where volatiles might have been lost. Thus, the chemical differences between the earth and moon are more plausibly accounted for. Satellites of the outer planets probably formed in large numbers throughout the growth of those planets. Because of rapid inward evolution of the orbits of small satellites, the present satellite systems represent only satellites formed in the last few percent of the growths of their primaries. The rings of Saturn and Uranus are most plausibly explained as the debris of satellites disrupted within the Roche limit. Because such a ring would collapse onto the planet in the course of any significant further accretion by the planet, the rings must have formed very near or even after the conclusion of accretion.

Harris, A. W.↗
NASA NTRS1980

User's guide for vectorized code EQUIL for calculating equilibrium chemistry on Control Data STAR-100 computer

A vectorized code, EQUIL, was developed for calculating the equilibrium chemistry of a reacting gas mixture on the Control Data STAR-100 computer. The code provides species mole fractions, mass fractions, and thermodynamic and transport properties of the mixture for given temperature, pressure, and elemental mass fractions. The code is set up for the electrons H, He, C, O, N system of elements. In all, 24 chemical species are included.

Kumar, A.↗
NASA NTRS2003

Transmission Electron Microscopy of Non-Etched Presolar Silicon Carbide

Our solar system formed from nuclei produced in earlier generations of stars. Mixing in the proto-solar nebula isotopically homogenized most of this material, but some grains, called presolar grains, retain their original isotopic composition. The isotopic properties of presolar SiC grains indicate that most of the grains formed in the outflows of carbon-rich Asymptotic Giant Branch (AGB) stars. The microstructure of these presolar grains reflects the conditions of the dust formation and subsequent alteration. Early microstructural studies of SiC grains obtained by acid dissolution from meteorites show that most isotopically anomalous SiC grains have the face-centered cubic b- SiC structure. However, Daulton et al. have shown that a small fraction of sub-micron presolar SiC grains are of the hexagonal 2H polytype (a-SiC). Although the harsh chemical treatments of these grains does not alter their crystal structure, significant alteration of the surface morphology of the grains due to the acid treatments has been observed. In addition, the acid treatments may preferentially remove cracked or fissured grains, and possible sub-grains, such as graphite. By studying SiC grains isolated by physical separation and found in situ, we attempt to obtain a more complete analysis of presolar SiC microstructures, including the surface morphology, in order to address the formation and processing history of the grains. In our prior work, we reported on one in situ SiC grain (hereafter CBIS1). Here we present results from two additional grains, one in situ, and one prepared as a physical separate.

Stroud, Rhonda M.↗
NASA NTRS2002

M-FISH Analysis of Chromosome Aberrations in Human Fibroblast Cells After In Vitro Exposure to Low- and High-LET Radiation

The recently commercialized multiplex fluorescence in situ hybridization (m-FISH) technique, which allows human chromosomes to be painted in 24 different colors, was used to analyze chromosome aberrations in diploid human fibroblast cells after in vitro radiation exposure. Confluent flasks of a normal primary fibroblast cell line (AG 1522) were irradiated at high dose rates with either gamma rays or 200 MeV/nucleon Fe ions (LET = 440 keV/micron), incubated at 37 C for 24 hours after exposure, and subsequently subcultured. A chemically induced premature chromosome condensation technique was used to collect chromosome samples 32 hours after subculture. Results showed that the fraction of exchanges which were identified as complex, i.e. involving misrejoining of three or more DSB, were higher in the Fe-irradiated samples compared with the gamma-irradiated samples, as has been shown previously using FISH with one or two painted chromosomes . The ratios of complex/simple type exchanges were similar for samples irradiated with 0.7 Gy and 3 Gy of Fe ions, although exchanges involving five or more breaks were found only in 3 Gy irradiated samples. The fraction of incomplete exchanges was also higher in Fe- than gamma-irradiated samples. Data on the distribution of individual chromosome involvement in interchromosomal exchanges will be presented.

Wu, Honglu↗
NASA NTRS2020

Sierra Gorda 009: A New Member of the Metal-Rich G Chondrites Grouplet

We investigated the metal-rich chondrite Sierra Gorda (SG) 009, a member of the new G chondrite grouplet (also including NWA 5492, GRO 95551). G chondrites contain 23% metal, very reduced silicates, and rare oxidized mineral phases (Mg-chromite, FeO-rich pyroxene). G chondrites are not related to CH-CB chondrites, based on bulk O, C and N isotopic compositions, mineralogy and geochemistry. G chondrites have no fine-grained matrix or matrix lumps enclosing hydrated material typical for CH-CB chondrites. G chondrites’ average metal compositions are similar to H chondrites. Siderophile and lithophile geochemistry indicate sulfidization and fractionation of the SG 009 metal and silicates, unlike NWA 5492 and GRO 05551. The G chondrites have average O isotopic compositions DELTA 17O >0 ‰ ranging between bulk enstatite (E) and ordinary (O) chondrites. An Al-rich chondrule from SG 009 has DELTA 17O <0 ‰ indicating some heterogeneity in oxygen isotopic composition of G chondrite components. SG 009’s bulk carbon and nitrogen isotopic compositions correspond to E and O chondrites. Neon isotopic composition reflects a mixture of cosmogenic and solar components, and cosmic ray exposure age of SG 009 is typical for O, E, and R chondrites. G chondrites are closely related to O, E, and R chondrites and may represent a unique metal-rich parent asteroid containing primitive and fractionated material from the inner Solar System. Oxidizing and reducing conditions during SG 009 formation may be connected with a chemical micro-environment and possibly could indicate that G chondrites may have formed by a planetesimal collision resulting in the lack of matrix.

chondrite↗
NASA NTRS2018

Atmospheric Chemistry Modeling Using a Regression Forest Model

Atmospheric chemistry is central to many environmental issues such as air pollution, climate change, and stratospheric ozone loss. Chemistry Transport Models (CTM) are a central tool for understanding these issues, whether for research or for forecasting. These models split the atmosphere in a large number of grid-boxes and consider the emission of compounds into these boxes and their subsequent transport, deposition, and chemical processing. The chemistry is represented through a series of simultaneous ordinary differential equations, one for each compound. Given the difference in life-times between the chemical compounds (milli-seconds for O1D to years for CH4) these equations are numerically stiff and solving them consists of a significant fraction of the computational burden of a CTM. We have investigated a machine learning approach to solving the differential equations instead of solving them numerically. From an annual simulation of the GEOS-Chem model we have produced a training dataset consisting of the concentration of compounds before and after the differential equations are solved, together with some key physical parameters for every grid-box and time-step. From this dataset we have trained a machine learning algorithm (regression forest) to be able to predict the concentration of the compounds after the integration step based on the concentrations and physical state at the beginning of the time step. We have then included this algorithm back into the GEOS-Chem model, bypassing the need to integrate the chemistry. This machine learning approach shows many of the characteristics of the full simulation and has the potential to be substantially faster. There are a wide range of application for such an approach - generating boundary conditions, for use in air quality forecasts, chemical data assimilation systems, centennial scale climate simulations etc. We discuss our approches' speed and accuracy, and highlight some potential future directions for improving this approach.

Keller, Christoph A.↗
NASA NTRS2019

Atmospheric Chemistry Modeling and Air Quality Forecasting Using Machine Learning

Atmospheric chemistry models are a central tool to study the impact of chemical constituents on the environment, vegetation and human health. These models split the atmosphere in a large number of grid-boxes and consider the emission of compounds into these boxes and their subsequent transport, deposition, and chemical processing. The chemistry is represented through a series of simultaneous ordinary differential equations, one for each compound. Given the difference in life-times between the chemical compounds (milli-seconds for O1D to years for CH4) these equations are numerically stiff and solving them consists of a significant fraction of the computational burden of a chemistry model.We have investigated a machine learning approach to emulate the chemistry instead of solving the differential equations numerically. From a one-month simulation of the GEOS-Chem model we have produced a training dataset consisting of the concentration of compounds before and after the differential equations are solved, together with some key physical parameters for every grid-box and time-step. From this dataset we have trained a machine learning algorithm (regression forest) to be able to predict the concentration of the compounds after the integration step based on the concentrations and physical state at the beginning of the time step. We have then included this algorithm back into the GEOS-Chem model, bypassing the need to integrate the chemistry.This machine learning approach shows many of the characteristics of the full simulation and has the potential to be substantially faster. There are a wide range of application for such an approach - generating boundary conditions, for use in air quality forecasts, chemical data assimilation systems, etc. We discuss speed and accuracy of our approach, and highlight some potential future directions for improving it.

Keller, Christoph A.↗
NASA NTRS1974

Lunar Science Conference, 5th, Houston, Tex., March 18-22, 1974, Proceedings. Volume 1 - Mineralogy and petrology. Volume 2 Chemical and isotope analyses. Organic chemistry. Volume 3 - Physical properties

Numerous studies on the properties of the moon based on Apollo findings and samples are presented. Topics treated include ages of the lunar nearside light plains and maria, orange material in the Sulpicius Gallus formation at the southwestern edge of Mare Serenitatis, impact-induced fractionation in the lunar highlands, igneous rocks from Apollo 16 rake samples, experimental liquid line of descent and liquid immiscibility for basalt 70017, ion microprobe mass analysis of plagioclase from 'non-mare' lunar samples, grain size and the evolution of lunar soils, chemical composition of rocks and soils at Taurus-Littrow, the geochemical evolution of the moon, U-Th-Pb systematics of some Apollo 17 lunar samples and implications for a lunar basin excavation chronology, volatile-element systematics and green glass in Apollo 15 lunar soils, solar wind nitrogen and indigenous nitrogen in Apollo 17 lunar samples, lunar trapped xenon, solar flare and lunar surface process characterization at the Apollo 17 site, and the permanent and induced magnetic dipole moment of the moon. Individual items are announced in this issue.

Gose, W. A.↗
NASA NTRS2019

Atmospheric Chemistry Modeling Using Machine Learning

Atmospheric chemistry models are a central tool to study the impact of chemical constituents on the environment, vegetation and human health. These models split the atmosphere in a large number of grid-boxes and consider the emission of compounds into these boxes and their subsequent transport, deposition, and chemical processing. The chemistry is represented through a series of simultaneous ordinary differential equations, one for each compound. Given the difference in life-times between the chemical compounds (milli-seconds for O1D to years for CH4) these equations are numerically stiff and solving them consists of a significant fraction of the computational burden of a chemistry model. We have investigated a machine learning approach to emulate the chemistry instead of solving the differential equations numerically. From a one-month simulation of the GEOS-Chem model we have produced a training dataset consisting of the concentration of compounds before and after the differential equations are solved, together with some key physical parameters for every grid-box and time-step. From this dataset we have trained a machine learning algorithm (regression forest) to be able to predict the concentration of the compounds after the integration step based on the concentrations and physical state at the beginning of the time step. We have then included this algorithm back into the GEOS-Chem model, bypassing the need to integrate the chemistry. This machine learning approach shows many of the characteristics of the full simulation and has the potential to be substantially faster. There are a wide range of application for such an approach - generating boundary conditions, for use in air quality forecasts, chemical data assimilation systems, etc. We discuss speed and accuracy of our approach, and highlight some potential future directions for improving it.

Keller, Christoph A.↗
NASA NTRS2013

Petrologic and Chemical Characterization of a Suite of Antarctic Diogenites

The origin of diogenites, ultramafic cumulates related to eucrites, is an unresolved problem [1]. Most diogenites are orthopyroxenites, a few are harzburgites [2], and some are transitional to cumulate eucrites [1, 3]. Cumulate eucrites are gabbros formed by crystal fractionation from basaltic eucrites [4]. The consensus view is that basaltic eucrites are residual melts from global-magma-ocean crystallization on their parent asteroid [4] which is plausibly Vesta [5]. However, the petrologic and compositional characteristics of diogenites seem to preclude a magma ocean origin [1, 4]. We are doing a petrologic and chemical study of new or unusual diogenites with the ultimate goals of constraining their genesis, and the geologic evolution of Vesta.

Mittlefehldt, D. W.↗
NASA NTRS1999

Classification of ion mobility spectra by functional groups using neural networks

Neural networks were trained using whole ion mobility spectra from a standardized database of 3137 spectra for 204 chemicals at various concentrations. Performance of the network was measured by the success of classification into ten chemical classes. Eleven stages for evaluation of spectra and of spectral pre-processing were employed and minimums established for response thresholds and spectral purity. After optimization of the database, network, and pre-processing routines, the fraction of successful classifications by functional group was 0.91 throughout a range of concentrations. Network classification relied on a combination of features, including drift times, number of peaks, relative intensities, and other factors apparently including peak shape. The network was opportunistic, exploiting different features within different chemical classes. Application of neural networks in a two-tier design where chemicals were first identified by class and then individually eliminated all but one false positive out of 161 test spectra. These findings establish that ion mobility spectra, even with low resolution instrumentation, contain sufficient detail to permit the development of automated identification systems.

Non-NASA Center↗
NASA NTRS1997

Effects of Gravity on Sheared and Nonsheared Turbulent Nonpremixed Flames

The present numerical study is concerned with the fundamental physics of the multi-way interaction between turbulence, chemical reaction and buoyancy in a nonpremixed flame. The method of direct numerical simulation (DNS) is used to solve the instantaneous three-dimensional governing equations (continuity, Navier-Stokes, species mass fractions and energy) under the zero-Mach number assumption. Because of the present supercomputer limitations, we consider two simple flow geometries, namely an initially uniform flow without shear (equivalent to grid-generated turbulence) and an initially uniform shear flow. In each flow, the fuel and oxidant initially exist as two separate streams. As the reactants mix, chemical reaction takes place and exothermic energy is released causing variations in density. In the presence of a gravity field, the spatial and temporal distributions of the induced buoyancy forces depend on the local density gradients and the direction of the gravitational acceleration.

Elghobashi, Said↗
NASA NTRS1994

Interplanetary dust particles collected from the stratosphere: Physical, chemical, and mineralogical properties and implications for their sources

The suggestion that significant quantities of interplanetary dust are produced by both main-belt asteroids and comets is based on the Infrared Astronomical Satellite (IRAS) detection of dust trails or bands associated with these objects. Gravitational focusing strongly biases all near-Earth collections of interplanetary dust in favor of particles with the lowest geocentric velocities, that is the dust from main-belt asteroids spiraling into the Sun under the influence of Poynting-Robertson radiation drag. The major dust bands in the main-belt appear to be associated with the catastrophic disruptions which produced the Eos, Themis and Koronis families of asteroids. If dust particles are produced in the catastrophic collision process, then Poynting-Robertson radiation drag is such an efficient transport mechanism from the main-belt to 1 AU that near-Earth collections of interplanetary dust should include, and perhaps be dominated by, this material. Interplanetary dust particles from 5 to 100 micrometers in diameter have been recovered from the stratosphere of the Earth by NASA sampling aircraft since the mid-1970s. The densities of a large fraction of these interplanetary dust particles are significantly lower than the densities of their constituent silicate mineral phases, indicating significant porosites. The majority of the particles are chemically and mineralogically similar to, but not identical to, the carbonaceous chondrite meteorites. Most stony interplanetary dust particles have carbon contents exceeding those of Allende, a carbonaceous chondrite meteorite having a low albedo. Higher albedo particles corresponding to S-type asteroids are underrepresented or absent from the stratospheric collections, and primitive carbonaceous particles seem to be overrepresented in the stratospheric collections compared to the fraction of main-belt asteroids classified as primitive. This suggests that much of the interplanetary dust may be generated by a stochastic process, probably preferentially sampling a few most recent collisional events.

Flynn, George J.↗
NASA NTRS1973

Chemical analysis of outgassing contaminants on spacecraft surfaces

Methods for analyzing and characterizing outgassing contaminants from such materials as RTV 501 potting compound and S 13 G paint are presented. Fractional distillation of a gross distillate from RTV 501 rubber was carried out and the distilled fractions examined as to their ultraviolet and infrared spectra by gas liquid chromatography. A sensitive technique for structural analysis and molecular identification was found to consist of a gas chromatography-mass spectroscopy system, which was determined to be economically unfeasible at present.

Mcnutt, R. C.↗
NASA NTRS1982

Effects of cobalt on the microstructure of Udimet 700

Cobalt, a critical and "strategic" alloying element in many superalloys, was systematically substituted by nickel in experimental alloys Udimet 700 containing 0.1, 4.3, 8.6, 12.8 and the standard 17.0 wt.% cobalt. Electrolytic and chemical extraction techniques, X-ray diffraction, scanning electron and optical microscopy were used for the microstructural studies. The total weight fraction of gamma' was not significantly affected by the cobalt content, although a difference in the size and quantities of the primary and secondary gamma' phases was apparent. The lattice parameters of the gamma' were found to increase with increasing cobalt content while the lattice mismatch between the gamma matrix and gamma' phases decreased. Other significant effects of cobalt on the weight fraction, distribution and formation of the carbide and boride phases as well as the relative stability of the experimental alloys during long-time aging are also discussed.

Engel, M. A.↗