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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 91 records · Page 5
All sourcesNASA NTRSDOE OSTI
NASA NTRS1989

The heliocentric evolution of cometary infrared spectra - Results from an organic grain model

An emission feature peaking near 3.4 microns that is typical of C-H stretching in hydrocarbons and which fits a simple, two-component thermal emission model for dust in the cometary coma, has been noted in observations of Comets Halley and Wilson. A noteworthy consequence of this modeling is that, at about 1 AU, emission features at wavelengths longer than 3.4 microns come to be 'diluted' by continuum emission. A quantitative development of the model shows it to agree with observational data for Comet Halley for certain, plausible values of the optical constants; the observed heliocentric evolution of the 3.4-micron feature thereby furnishes information on the composition of the comet's organic grains.

Chyba, Christopher F.↗
DOE OSTI2021

GLEAM: Galaxy Line Emission & Absorption Modeling

We present Galaxy Line Emission & Absorption Modeling (gleam), a Python tool for fitting Gaussian models to emission and absorption lines in large samples of 1D extragalactic spectra. gleam is tailored to work well in batch mode without much human interaction. With gleam, users can uniformly process a variety of spectra, including galaxies and active galactic nuclei, in a wide range of instrument setups and signal-to-noise regimes. gleam also takes advantage of multiprocessing capabilities to process spectra in parallel. With the goal of enabling reproducible workflows for its users, gleam employs a small number of input files, including a central, user-friendly configuration in which fitting constraints can be defined for groups of spectra and overrides can be specified for edge cases. For each spectrum, gleam produces a table containing measurements and error bars for the detected spectral lines and continuum and upper limits for nondetections. For visual inspection and publishing, gleam can also produce plots of the data with fitted lines overlaid. In the present paper, we describe gleam’s main features, the necessary inputs, expected outputs, and some example applications, including thorough tests on a large sample of optical/infrared multi-object spectroscopic observations and integral field spectroscopic data. gleam is developed as an open-source project hosted at https://github.com/multiwavelength/gleam and welcomes community contributions.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS1994

The 8-13 micron spectra of comets and the composition of silicate grains

We have analyzed the existing spectra of seven comets which show an emission feature at 7.8-13 micrometers. Most have been converted to a common calibration, taking into account the SiO feature in late-type standard stars. The spectra are compared with spectra of the Trapezium, interplanetary dust particles (IDPs), laboratory mineral samples, and small particle emission models. The emission spectra show a variety of shapes; there is no unique 'cometary silicate'. A peak at 11.20-11.25 micrometers, indicative of small crystalline olivine particles, is seen in only three comets of this sample, P/Halley, Bradfield 1987 XXIX, and Levy 1990 XX. The widths of the emission features range from 2.6 to 4.1 micrometers (FWHM). To explain the differing widths and the broad 9.8 micrometers maximum, glassy silicate particles, including both pyroxene and olivine compositions, are the most plausible candidates. Calculations of emission models confirm that small grains of glassy silicate well mixed with carbonaceous material are plausible cometary constituents. No single class of chondritic aggregate IDPs exhibits spectra closely matching the comet spectra. A mixture of IDP spectra, particularly the glass-rich aggregates, approximately matches the spectra of comets P/Halley, Levy, and Bradfield 1987 XXIX. Yet, if comets are simply a mix of IDP types, it is puzzling that the classes of IDPs are so distinct. None of the comet spectra match the spectrum of the Trapezium. Thus, the mineralogy of the cometary silicates is not the same as that of the interstellar medium. The presence of a component of crystalline silicates in comets may be evidence of mixing between high- and low-temperature regions in the solar nebula.

Hanner, Martha S.↗
DOE OSTI2021

A systematic comparison of machine learning methods for modeling of dynamic processes applied to combustion emission rate modeling

Ten established, data-driven dynamic algorithms are surveyed and a practical guide for understanding these methods generated. Existing Python programming packages for implementing each algorithm are acknowledged, and the model equations necessary for prediction are presented. A case study on a coal-fired power plant’s NO x emission rates is performed, directly comparing each modeling method’s performance on a mutual system. Each model is evaluated by its root mean squared error (RMSE) on out-of-sample future horizon predictions. Optimal hyperparameters are identified using either an exhaustive search or genetic algorithm. The top five model structures of each method are used to recursively predict future NO x emission rates over a 60-step time horizon. The RMSE at each future timestep is determined, and the recursive output prediction trends compared against measurements in time. The GRU neural network is identified as the best candidate for representing the system, demonstrating accurate and stable predictions across the future horizon by all considered models, while satisfactory performance was observed in several of the ARX/NARX formulations. Finally, these efforts have contributed 1) a concise resource of multiple proven dynamic machine learning methods, 2) a practical guide explaining the use of these methods, effectively lowering the “barrier-to-entry” of deploying such models in control systems, 3) a comparison study evaluating each method’s performance on a mutual system, 4) demonstration of accurate multi-timestep emissions modeling suitable for systems-level control, and 5) generalizable results demonstrating the suitability of each method for prediction over a multi-step future horizon to other complex dynamic systems.

42 ENGINEERING↗
NASA NTRS1981

A model describing the microwave emission from a multi-layer snowpack at 37 GHz

A multilayer emission model is described and applied to emission measurements obtained at 37 GHz and H polarization using a microwave radiometer attached to a truck-mounted boom in Steamboat Springs, Colorado in 1977. Estimated absorption and scattering coefficients and their dependence on wetness were obtained using calculated values of the dielectric constant at 37 GHz along with the model. It was found that the scattering coefficient is comparable in value to the absorption coefficient for dry snow however, the absorption coefficient increases linearly with increasing snow wetness while the scattering coefficient decreases linearly with increasing wetness. The emission from each layer of the snowpack was also calculated using the estimated coefficients. It is shown that for dry snow, the ground underneath the snowpack contributes about 45% of all measured emission while the rest is due to emission from all the layers within the snowpack. When the wetness of the top 5 cm layer of snowpack increases to about 2% by volume, this top 5 cm snowlayer contributes more than 90% of all the measured emission.

Abdelrazik, M.↗
DOE OSTI2026

Greenhouse Gas Life Cycle Emissions Assessment Model (GLEAM) Model Documentation

The Greenhouse gas Life cycle Emissions Assessment Model (GLEAM) estimates life cycle greenhouse gas emissions from future scenarios of electricity generation considering a wide range of generation technologies. Building on the National Laboratory of the Rockies longstanding effort to quantify life cycle emissions by electricity generation technology under the LCA Harmonization Project, GLEAM streamlines the process of estimating cumulative greenhouse gas emissions on a life cycle basis. Given a set of inputs regarding annual installed and decommissioned generation capacity, as well as generation, GLEAM estimates the carbon dioxide equivalent emissions by year. The model also offers optional modules to decompose carbon dioxide equivalent emissions into constituent greenhouse gases (e.g., carbon dioxide, methane, and nitrous oxide) as well as estimate hydrogen leakage from relevant technologies. The results from GLEAM can be used to inform future electricity planning scenarios as well as investment or regulatory decisions.

24 POWER TRANSMISSION AND DISTRIBUTION↗
NASA NTRS2001

Combining TOPEX and SeaWinds Data to Refine Models for Ocean Surface Emissivity: Wind Vector Signatures at 18, 21 and 37 GHz

TOPEX Microwave Radiometer (TMR) brightness temperature observations at 18, 21, and 37 GHz have been collocated with near-simultaneous SeaWinds wind vector data as well as with a monthly SST climatological product. The combined data set allows us to study the dependence of ocean surface emissivity (at each frequency) upon both wind speed. Results show clear two-branch wind speed dependence; weak and linear below 6 m/s with an abrupt increase in sensitivity above that point. The analysis also shows that the zenith-directed ocean surface emissivity is polarization dependent above wind speeds of 5-6 m/s with an azimuthal variation related to the wind direction. This last result accords with recent polarimetric radiometer observations collected from aircraft. Implications of these observations to water vapor retrieval algorithms, nadir-viewing polarimetry, and ocean emission modeling will be discussed.

Vandemark, D.↗
NASA NTRS1976

Helium emission from model flare layers

The emission of visible and UV He I and He II line radiation from a plane-parallel model flare layer characterized by electron temperatures of 10,000 to 50,000 K and electron densities of 10 to the 10th power to 10 to the 15th power per cu cm is analyzed by solving the statistical-equilibrium equations for a 30-level He I-II-III system, using parametric representations of the line and continuum radiation fields. The atomic model was chosen to provide accurate solutions for the first two resonance lines of He I and He II as well as for the D3 and 10,830-A lines of He I. Reaction rates are discussed, and sample solutions to the steady-state population equations are given for a generally optically thin gas assumed to be irradiated over 2pi sr by a blackbody spectrum at 6000 K. Specific results are examined for ionization equilibrium, level populations, approximate optical depths of a 1000-km-thick flare layer, line intensities, and upper-level population rates.

Kulander, J. I.↗
DOE OSTI2020

Zonal-Based Emission Source Term Model for Predicting Particulate Emission Factors in Wildfire Simulations

A physics/chemistry-based numerical model for predicting the emission of fine particles from wildfires is proposed. This model implements the fundamental mechanisms of soot formation in a combustion environment: soot nucleation, surface growth, agglomeration, oxidation, and particle fragmentation. These mechanisms occur on a scale too fine for the discretization of most wildfire models, which need to simulate landscape-scale dynamics. As a result this model implements a zonal approach, where the computed soot particle distribution is partitioned into process zones within a single resolved grid cell. These process zones include: an inception zone (for nucleation), a heating zone (for coagulation, surface growth, and fragmentation), a reaction zone (for oxidation), and a quenched zone (for atmospheric processes). Governing mechanisms are applied to the appropriate zones to predict total particle growth and emission. Additionally, the proposed model is implemented into HIGRAD/FIRETEC, a physics-based wildfire simulation code which couples interactions between fire, fuels, atmosphere, and topography on a landscape scale. Fire simulations among grasslands and conifer forests are performed and compared against experimental data for emission factors.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Modeling Isoprene Emission Response to Drought and Heatwaves Within MEGAN Using Evapotranspiration Data and by Coupling With the Community Land Model

We introduce two new drought stress algorithms designed to simulate isoprene emission with the Model of Emissions of Gases and Aerosols from Nature (MEGAN) model. The two approaches include the representation of the impact of drought on isoprene emission with a simple empirical approach for offline MEGAN applications and a more process-based approach for online MEGAN in Community Land Model (CLM) simulations. The two versions differ in their implementation of leaf-temperature impacts of mild drought. For the online version of MEGAN that is coupled to CLM, the impact of drought on leaf temperature is simulated directly and the calculated leaf temperature is considered for the estimation of isoprene emission. For the offline version, we apply an empirical algorithm derived from whole-canopy flux measurements for simulating the impact of drought ranging from mild to severe stage. In addition, the offline approach adopts the ratio ($f$ PET ) of actual evapotranspiration to potential evapotranspiration to quantify the severity of drought instead of using soil moisture. We applied the two algorithms in the CLM-CAM-chem (the Community Atmosphere Model with Chemistry) model to simulate the impact of drought on isoprene emission and found that drought can decrease isoprene emission globally by 11% in 2012. We further compared the formaldehyde (HCHO) vertical column density simulated by CAM-chem to satellite HCHO observations. We found that the proposed drought algorithm can improve the match with the HCHO observations during droughts, but the performance of the drought algorithm is limited by the capacity of the model to capture the severity of drought.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2001

Modeling Modern Methane Emissions from Natural Wetlands: Model Description and Results - 1

Methane is an important greenhouse gas which contributes about 22 percent to the present greenhouse effect. Natural wetlands currently constitute the biggest methane source and were the major source in preindustrial times. Wetland emissions depend highly on the climate, i.e., on soil temperature and water table. To investigate the response of methane emissions from natural wetlands to climate variations, a process-based model that derives methane emissions from natural wetlands as a function of soil temperature, water table, and net primary productivity is used. For its application on the global scale, global data sets for all model parameters are generated. In addition, a simple hydrologic model is developed in order to simulate the position of the water table in wetlands. The hydrologic model is tested against data from different wetland sites, and the sensitivity of the hydrologic model to changes in precipitation is examined. The global methane­ hydrology model constitutes a tool to study temporal and spatial variations in methane emissions from natural wetlands. The model is applied using high-frequency atmospheric forcing fields from European Center for Medium-range Weather Forecasts (ECMWF) re-analyses of the period from 1982 to 1993. We calculate global annual methane emissions from wetlands to be 260 teragrams per year. Twenty-five percent of these methane emissions originate from wetlands north of 30 degrees North Latitude. Only 60 percent of the produced methane is emitted, while the rest is re-oxidized. A comparison of zonal integrals of simulated global wetland emissions and results obtained by an inverse modeling approach shows good agreement. In a test with data from two wetlands the seasonality of simulated and observed methane emissions agrees well.

Biogeochemical processes↗
DOE OSTI2024

Constraining Present‐Day Anthropogenic Total Iron Emissions Using Model and Observations

Abstract Iron emissions from human activities, such as oil combustion and smelting, affect the Earth's climate and marine ecosystems. These emissions are difficult to quantify accurately due to a lack of observations, particularly in remote ocean regions. In this study, we used long‐term, near‐source observations in areas with a dominance of anthropogenic iron emissions in various parts of the world to better estimate the total amount of anthropogenic iron emissions. We also used a statistical source apportionment method to identify the anthropogenic components and their sub‐sources from bulk aerosol observations in the United States. We find that the estimates of anthropogenic iron emissions are within a factor of 3 in most regions compared to previous inventory estimates. Under‐ or overestimation varied by region and depended on the number of sites, interannual variability, and the statistical filter choice. Smelting‐related iron emissions are overestimated by a factor of 1.5 in East Asia compared to previous estimates. More long‐term iron observations and the consideration of the influence of dust and wildfires could help reduce the uncertainty in anthropogenic iron emissions estimates.

Meteorology & Atmospheric Sciences↗
NASA NTRS1989

Neutrinos from SN 1987A - Implications for cooling of the nascent neutron star and the mass of the electron antineutrino

Data on neutrinos from SN 1987A are compared here with parameterized models of the neutrino emission using a consistent and straightforward statistical methodology. The empirically measured detector background spectra are included in the analysis, and the data are compared with a much wider variety of neutrino emission models than was explored previously. It is shown that the inferred neutrino emission model parameters are strongly correlated. The analysis confirms that simple models of the neutrino cooling of the nascent neutron star formed by the SN adequately explain the data. The inferred radius and binding energy of the neutron star are in excellent agreement with model calculations based on a wide range of equations of state. The results also raise the upper limit of the electron antineutrino rest mass to roughly 25 eV at the 95 percent confidence level, roughly 1.5-5 times higher than found previously.

Loredo, Thomas J.↗
DOE OSTI2020

The Completed SDSS-IV extended Baryon Oscillation Spectroscopic Survey: exploring the halo occupation distribution model for emission line galaxies

We study the modelling of the halo occupation distribution (HOD) for the eBOSS DR16 emission line galaxies (ELGs). Motivated by previous theoretical and observational studies, we consider different physical effects that can change how ELGs populate haloes. We explore the shape of the average HOD, the fraction of satellite galaxies, their probability distribution function (PDF), and their density and velocity profiles. Our baseline HOD shape was fitted to a semi-analytical model of galaxy formation and evolution, with a decaying occupation of central ELGs at high halo masses. We consider Poisson and sub/super-Poissonian PDFs for satellite assignment. We model both Navarro–Frenk–White and particle profiles for satellite positions, also allowing for decreased concentrations. We model velocities with the virial theorem and particle velocity distributions. Additionally, we introduce a velocity bias and a net infall velocity. We study how these choices impact the clustering statistics while keeping the number density and bias fixed to that from eBOSS ELGs. The projected correlation function, w p , captures most of the effects from the PDF and satellites profile. The quadrupole, ξ 2 , captures most of the effects coming from the velocity profile. We find that the impact of the mean HOD shape is subdominant relative to the rest of choices. Here, we fit the clustering of the eBOSS DR16 ELG data under different combinations of the above assumptions. The catalogues presented here have been analysed in companion papers, showing that eBOSS RSD+BAO measurements are insensitive to the details of galaxy physics considered here. These catalogues are made publicly available.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS2000

Modeling Ultraviolet Emissions Near Io

In this report, we describe work awarded to Science Applications International Corporation, for the period 6/l/99 to 5/31/00. During this time period, we have investigated the interaction of Io, Jupiter's innermost Galilean satellite, with the Io plasma torus, and the role this interaction plays in producing ultraviolet (UV) emissions from neutral oxygen and sulfur. Io, the innermost of Jupiter's Galilean satellites, plays a unique role in the jovian magnetosphere. Neutral material that escapes from Io is ionized to form the lo torus, a dense, heavy-ion plasma that corotates with Jupiter and interacts with Io. Io supplies not only the torus, but is a major source of plasma for the entire magnetosphere. Ionization and charge-exchange of neutrals near lo strongly influences the plasma interaction, and Io's neutral atmosphere plays an important role in the generation of currents that couple Io to Jupiter. There have been no in situ measurements of the neutral density near Io, but remote observations of neutrals near lo have been performed for many years. Recent observations from the Hubble Space Telescope (HST) have shown detailed structure in UV emissions from neutral species near Io. Electron-impact of the neutrals by the Io torus plasma is the primary mechanism responsible for exciting these emissions. Previously, we have modeled the Io plasma environment using three-dimensional magnetohydrodynamic (MHD) simulations, and we have shown that the interaction between Io and the plasma torus plays an important role in producing the morphology of the observed emissions. In the past year, we have extended these studies to use both UV observations and Galileo particle and field measurements to investigate the Io interaction.

Linker, Jon A.↗
DOE OSTI2026

Excited states in semi-magic 82 Ge populated in the βn-decay of 83 Ga

For this work, the βn and β-decay of the neutron-rich 83 Ga isotopes produced in proton-induced fission of 238 U were studied at the Holifield Radioactive Ion Beam Facility (HRIBF) at Oak Ridge National Laboratory using on-line mass separation and the hybrid-3Hen neutron-γ detector array. Excited states in semi-magic 82 Ge populated in βn decay of 83 Ga were identified using neutron-γ coincidences. The measured relative population of excited states in 82 Ge is compared with a βn emission model, where the neutron emission model combines the strength distribution obtained from the shell-model calculations with the statistical Hauser-Feshbach model.

3HEN↗
DOE OSTI2022

Mobility and Energy Improvements Realized through Prediction-based Vehicle Powertrain Control and Traffic Management (Research Performance Final Report)

The goal of this project was to utilize individual vehicle and systems-level transportation big data to develop real-world implementable techniques for energy efficiency. We collected a real world dataset in Fort Collins, CO using technology that is currently available. This dataset was used to (1) create individual vehicle prediction models and emissions models using cutting-edge artificial intelligence (AI) techniques, (2) create traffic prediction models, (3) create boundary condition constraints for optimal trajectory derivation, and (4) develop a novel Mobility Energy Productivity (MEP) model for Fort Collins, CO at a fidelity and flexibility which did not previously exist. Each of these techniques is novel but the most interesting results occurred from the intersection of all techniques. It was found that when optimal vehicle control is combined with optimal traffic light control, that significant energy efficiency improvements that do not compromise travel time are available.

42 ENGINEERING↗