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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 163 records · Page 9
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Analyzing Wildland Fire Smoke Emissions Data Using Compositional Data Techniques

By conservation of mass, the mass of wildland fuel that is pyrolyzed and combusted must equal the mass of smoke emissions, residual char and ash. For a given set of conditions, these amounts are fixed. This places a constraint on smoke emissions data which violates statistical assumptions for many of the methods currently used to analyze these data such as linear regression, analysis of variance, and t-tests. These data are inherently multivariate and non-negative parts of a whole. This paper introduces the field of compositional data analysis to the emissions community and provides examples of appropriate statistical treatment of emissions data. It is shown that modified combustion efficiency should not be used as a predictor variable for other smoke emissions because it is not an independent variable. An alternative method based on compositional linear trends to estimate trace gas composition using CO and CO2 is presented. The data used in this paper resulted from projects the DOD/DOE/EPA Strategic 586 Environmental Research and Development Program projects RC-1648 and 1649. The senior 587 author appreciates the guidance and R scripts provided by Prof. Girty at San Diego State 588 University to estimate linear trends by perturbation. J. P.-A. was supported by the Spanish 589 Ministry of Science, Innovation and Universities under the project CODAMET (RTI2018-590 095518-B-C21, 2019-2021). The data used in this study have been previously published and are 591 available in the original publications. DRW conceived the initial manuscript (70 percent) and 592 performed the bulk of the data analysis. JPA provided statistical guidance and compositional data 593 expertise and contributed 20 percent of the manuscript. TJJ and HJ were extensively involved in 594 the study that provided the data. TJJ provide smoke emissions expertise and HJ provided 595 combustion expertise. The authors declare that they have no conflict of interest. The use of trade 596 or firm names in this publication is for reader information and does not imply endorsement by 597 the U.S. Department of Agriculture of any product or service.

simplex, compositional data analysis, balance, log↗
DOE OSTI2023

Inhibition of nitrous oxide reduction in forest soil microcosms by different forms of methanobactin

Copper plays a critical role in controlling greenhouse gas emissions as it is a key component of the particulate methane monooxygenase and nitrous oxide reductase. Some methanotrophs excrete methanobactin (MB) that has an extremely high copper affinity. As a result, MB may limit the ability of other microbes to gather copper, thereby decreasing their activity as well as impacting microbial community composition. Here, we show using forest soil microcosms that multiple forms of MB; MB from Methylosinus trichosporium OB3b (MB-OB3b) and MB from Methylocystis sp. strain SB2 (MB-SB2) increased nitrous oxide (N 2 O) production as well caused significant shifts in microbial community composition. Such effects, however, were mediated by the amount of copper in the soils, with low-copper soil microcosms showing the strongest response to MB. Furthermore, MB-SB2 had a stronger effect, likely due to its higher affinity for copper. The presence of either form of MB also inhibited nitrite reduction and generally increased the presence of genes encoding for the iron-containing nitrite reductase (nirS) over the copper-dependent nitrite reductase (nirK). Lastly, these data indicate the methanotrophic-mediated production of MB can significantly impact multiple steps of denitrification, as well as have broad effects on microbial community composition of forest soils.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2011

A Real-Time MODIS Vegetation Composite for Land Surface Models and Short-Term Forecasting

The NASA Short-term Prediction Research and Transition (SPoRT) Center is producing real-time, 1- km resolution Normalized Difference Vegetation Index (NDVI) gridded composites over a Continental U.S. domain. These composites are updated daily based on swath data from the Moderate Resolution Imaging Spectroradiometer (MODIS) sensor aboard the polar orbiting NASA Aqua and Terra satellites, with a product time lag of about one day. A simple time-weighting algorithm is applied to the NDVI swath data that queries the previous 20 days of data to ensure a continuous grid of data populated at all pixels. The daily composites exhibited good continuity both spatially and temporally during June and July 2010. The composites also nicely depicted high greenness anomalies that resulted from significant rainfall over southwestern Texas, Mexico, and New Mexico during July due to early-season tropical cyclone activity. The SPoRT Center is in the process of computing greenness vegetation fraction (GVF) composites from the MODIS NDVI data at the same spatial and temporal resolution for use in the NASA Land Information System (LIS). The new daily GVF dataset would replace the monthly climatological GVF database (based on Advanced Very High Resolution Radiometer [AVHRR] observations from 1992-93) currently available to the Noah land surface model (LSM) in both LIS and the public version of the Weather Research and Forecasting (WRF) model. The much higher spatial resolution (1 km versus 0.15 degree) and daily updates based on real-time satellite observations have the capability to greatly improve the simulation of the surface energy budget in the Noah LSM within LIS and WRF. Once code is developed in LIS to incorporate the daily updated GVFs, the SPoRT Center will conduct simulation sensitivity experiments to quantify the impacts and improvements realized by the MODIS real-time GVF data. This presentation will describe the methodology used to develop the 1-km MODIS NDVI composites and show sample output from summer 2010, compare the MODIS GVF data to the AVHRR monthly climatology, and illustrate the sensitivity of the Noah LSM within LIS and/or the coupled LIS/WRF system to the new MODIS GVF dataset.

Case, Jonathan L.↗
DOE OSTI2022

Report on Data Quality Required for Modeling an MSR

Calculations were performed to assess how uncertainties in molten salt property values impact the results of behavior models of molten salt reactor systems under steady-state conditions. The thermophysical and thermochemical properties of salt mixtures being considered for use in molten salt reactors are not yet well characterized and methods used to measure property values to molten salts are not yet well established. The limited property data for salts of interest that are available in the literature are inconsistent and unreliable. Many methods used to measure property values remain developmental in the sense that not all variables affecting measured values have been identified or controlled during the measurement and not all aspects of the measurements affecting data quality are calibrated. A prior report described the repeatability of measurements made at Argonne and the reproducibility of measurements made with the same salts at several institutions is being evaluated. There is significant uncertainty in measured property values due to instrumental limitations and the effects of contaminants in the salts used to make the measurements that impacts predictions of salt behavior in a reactor. Most salts of interest are multicomponent eutectic or near-eutectic mixtures and both uncertainty in the salt composition and uncertainty in measured values. Furthermore, the salt composition evolves over time due to the uptake of impurities from the atmosphere and corrosion of containment vessels. More significantly, fission products will accumulate during operation that change the salt compositions and property values. MSR developers need to understand how this uncertainty in the basic property data of the fuel will impact modeling predictions for normal reactor operation as well was in transient scenarios that will impact the safety basis. The calculations and analyses in this report address the impact of uncertainty in measured property values under steady-state conditions through a generalized parametric study. The pooled uncertainty from contributions by a number of factors were considered and quantified, including varying composition due to impurities and fission products, imprecision in the measured values, and uncontrolled aspects of the measurement. In this way, we can begin to gain an understanding of the magnitude of the impact uncertainty will have in modeling MSR systems.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
NASA NTRS2011

Next-Generation Aura/OMI NO2 and SO2 Products

The measurement of both SO2 and NO2 gases are recognized as an essential component of atmospheric composition missions. We describe current capabilities and limitations of the operational Aura/OMI NO2 and SO2 data that have been used by a large number of researchers. Analyses of the data and validation studies have brought to light a number of areas in which these products can be expanded and improved. Major improvements for new NASA standard (SP) NO2 product include more accurate tropospheric and stratospheric column amounts, along with much improved error estimates and diagnostics. Our approach uses a monthly NO2 climatology based on the NASA Global Modeling Initiative (GMI) chemistry-transport model and takes advantage of OMI data from cloudy scenes to find clean areas where the contribution from the trap NO2 column is relatively small. We then use a new filtering, interpolation and smoothing techniques for separating the stratospheric and tropospheric components of NO2, minimizing the influence of a priori information. The new algorithm greatly improves the structure of stratospheric features relative to the original SP. For the next-generation OMI SO2 product we plan to implement operationally the offline iterative spectral fitting (ISF) algorithm and re-process the OMI Level-2 SO2 dataset using a priori SO2 and aerosol profiles, clouds, and surface reflectivity appropriate for observation conditions. This will improve the ability to detect and quantify weak tropospheric SO2 loadings. The new algorithm is validated using aircraft in-situ data during field campaigns in China (2005 and 2008) and in Maryland (Frostburg, 2010 and DISCOVER-AQ in July 2011). The height of the SO2 plumes will also be estimated for high SO2 loading cases (e.g., volcanic eruptions). The same SO2 algorithm will be applied to the data from OMPS sensor to be launched on NPP satellite later this year. The next-generation NO2 and SO2 products will provide critical information (e.g., averaging kernels) for evaluation of chemistry-transport models, for data assimilation, and to impose top-down constraints on the SO2 and NO2 emission sources.

Krotkov, Nickolay↗
DOE OSTI2024

Performance Testing of a Moving-Bed Gasifier Using Coal, Biomass, and Waste Plastic Blends with Washed and Unwashed Legacy Coals and Other Waste Fuels to Generate White Hydrogen

The objective of this effort, primarily funded by the United States Department of Energy (DOE), and led by the Electric Power Research Institute, Inc. (EPRI), with support by Hamilton Maurer International (HMI) and Sotacarbo S.p.A. (Sotacarbo), has been to qualify coal, biomass, and plastic waste blends based on performance testing of selected fuel pellet compositions in a pilot-scale updraft moving-bed (UDMB) gasifier. The testing provided relevant data to advance the commercial-scale design of the moving-bed gasifier to be able to successfully use these feedstocks to produce hydrogen. In particular, the effects of waste plastics on feedstock development (i.e., blending and pelletizing) and the resulting products (i.e., syngas compositions, organic condensate production, and ash characteristics) are the focus. The gasifier used for testing is HMI’s moving-bed gasifier, which has been proven capable of gasifying nearly all coal ranks. It has also shown the ability in prior testing work to gasify wood chips (biomass). However, mixtures of these fuels with plastic wastes have not been prepared and gasified together. The three feedstocks were densified and pelletized by California Pellet Mill (CPM) to meet the feedstock size required by Sotacarbo’s 30mm ID UDMB gasifier, under contract to HMI. The technical tasks and results from this two-year research project included: (1) Feed Procurement and Preparation: Nine different tri-fuel pellets were prepared from varying compositions of fresh mined PRB coal, corn stover biomass, and car fluff waste plastics. Tri-fuel pellets were produced by CPM and shipped to Sotacarbo’s test facility in Carbonia, Sardinia, Italy. (2) Test Plan Development: A test plan was created to define the test runs to be performed. The test plan detailed the different UDMB gasification tests to be performed in Sotacarbo’s 12-inch ID pilot scale gasifier, the process monitoring instrumentation used, and the extractive samples recovered for analysis of the total gasification process mass and energy balance. (3) Gasifier Testing: Nine different gasification runs were performed in the pilot-scale gasifier at Sotacarbo using nine different fuel feedstock compositions generated from varying mixtures of PRB coal, biomass, and plastic wastes. The testing generated performance data on gasification reaction efficiency and performance, yielding relevant data for models used to scale up the gasifier design. This task also included work to refurbish and reassemble the pilot gasifier at Sotacarbo and perform a baseline 100% PRB coal run. (4) Data Analysis and Reporting: Review of the data, determination of figures of merit, and interpretation of the results are reported in the project’s final report, published in March 2024. The results show that all tri-fuel pellets gasified well and maintained structural integrity throughout the gasification process. The syngas generated can be shifted to hydrogen by using commercial syngas shifting technologies. (5) High Fidelity computational fluid dynamics (CFD) Simulation: The National Energy Technology Laboratory (NETL) team performed CFD simulations of the UDMB gasifier for two of the tri-fuel pellets gasified in Sotacarbo’s pilot scale gasifier. The kinetic mechanisms for the pyrolysis of each constituent, PRB coal, corn stover biomass, and waste plastics are based on thermogravimetric analysis performed by Sotacarbo. The gasification model was validated by comparing the predicted syngas composition at the exit of the gasifier with the measured syngas composition. In addition, the reactor’s measured internal temperature profile agreed well with the predicted internal reactor temperature profile. These results validate that the model can be used to predict the performance of the updraft moving bed gasifier for different feedstocks and operating conditions. This paper summarizes the results of the completed work in which the pelletizing procedure was validated to ensure the viability of the tri-fuel pellets for the gasification runs performed at Sotacarbo’s 30 mm UDMB gasifier. The gasification performance data from this series of nine runs will enable modeling of a full-scale HMI industrial scale gasifier supporting both combined heat and power, and Hydrogen production from coal (both fresh mined and legacy) combined with various biomass and waste plastics. Additionally, plans and progress on a follow-up project, being executed by the same project team, will be presented. In this project, a total of twenty (20) different feedstocks are being prepared from varying compositions of biomass (both woody biomass and corn stover) with a mixture of legacy coal waste, plastic waste, and refuse-derived fuel (RDF). The testing will provide information on gasification reaction efficiency/performance, yielding relevant data for models used to scale up the gasifier design to 50 megawatt electric (MWe) (equivalent hydrogen production). Tests will also be performed on a bench-scale fluidized-bed gasifier for comparison purposes. The results of this testing will be used to specify the range of feedstock blends that can be successfully gasified as well as quantify gasifier outputs based on specific blends.

08 HYDROGEN↗
NASA NTRS2013

Layer Precipitable Water (LPW) Briefing

Microwave Integrated Retrieval System (MIRS) provides soundings of specific humidity from a variety of instruments and is combined with AIRS infrared soundings to create a Layered Precipitable Water (LPW) composite product. The LPW provides vertical moisture information in the column instead of just upper levels via WV imagery, or a single column value via TPW products. LPW is created every 3 hours using the last 12 hours worth of data and has a delivery latency of 40 minutes. Weaknesses include discontinuities in the composite. Strengths include seeing through clouds, over land usage, and greater spatial coverage of vertical moisture profiles. Applications of LPW include analysis of horizontal and vertical moisture gradients, verification of NWP moisture, and analysis of atmospheric rivers and other moisture advection. Operational testbed is ongoing to determine viability of wider distribution.

Forsythe, John↗
DOE OSTI2022

Composition Measurements and Product Consistency Test Results for the EMHQ-LBE-04-B Glass

This report provides the results from the chemical analyses of the glass composition and the Product Consistency Test leachate analyses for the EMHQ-LBE-04-B glass. These data will be used in the development, validation, and implementation of enhanced property/composition models for waste glass vitrification at Hanford.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
NASA NTRSDate not supplied

1235 Preparing for TEMPO: A Review of Planned Metadata, Data Structure, and Distribution by NASA’s Atmospheric Science Data Center

The Atmospheric Science Data Center (ASDC) is in the Science Directorate located at the NASA Langley Research Center (LaRC), in Hampton, Virginia. The ASDC is one of NASA’s Distributed Active Archive Centers (DAAC) and supports over 60 projects and provides access to more than 1,000 archived collections. These datasets were created from satellite measurements, field experiments, and modeled data products. ASDC projects focus on the following Earth science disciplines: Radiation Budget, Clouds, Aerosols, and Tropospheric Composition. The ASDC is the official Distributed Active Archive Center (DAAC) of record for the upcoming Tropospheric Emissions: Monitoring of Pollution (TEMPO) instrument.. The instrument will share a ride on a commercial satellite as a hosted payload and will be launched to an orbit about 22,000 miles above Earth's equator. The investigation will, for the first time, use a space-based instrument to make accurate observations of tropospheric pollution concentrations of ozone, nitrogen dioxide, formaldehyde, and aerosols with high resolution and frequency over the U.S, Canada, and Mexico.

Ashlee Autore↗
NASA NTRSDate not supplied

1235 Preparing for TEMPO: A Review of Planned Metadata, Data Structure, and Distribution by NASA’s Atmospheric Science Data Center

The Atmospheric Science Data Center (ASDC) is in the Science Directorate located at the NASA Langley Research Center (LaRC), in Hampton, Virginia. The ASDC is one of NASA’s Distributed Active Archive Centers (DAAC) and supports over 60 projects and provides access to more than 1,000 archived collections. These datasets were created from satellite measurements, field experiments, and modeled data products. ASDC projects focus on the following Earth science disciplines: Radiation Budget, Clouds, Aerosols, and Tropospheric Composition. The ASDC is the official Distributed Active Archive Center (DAAC) of record for the upcoming Tropospheric Emissions: Monitoring of Pollution (TEMPO) instrument.. The instrument will share a ride on a commercial satellite as a hosted payload and will be launched to an orbit about 22,000 miles above Earth's equator. The investigation will, for the first time, use a space-based instrument to make accurate observations of tropospheric pollution concentrations of ozone, nitrogen dioxide, formaldehyde, and aerosols with high resolution and frequency over the U.S, Canada, and Mexico.

Ashlee Autore↗
DOE OSTI2021

First principles reactive simulation for equation of state prediction

The high cost of density functional theory (DFT) has hitherto limited the ab initio prediction of the equation of state (EOS). In this article, we employ a combination of large scale computing, advanced simulation techniques, and smart data science strategies to provide an unprecedented ab initio performance analysis of the high explosive pentaerythritol tetranitrate (PETN). Comparison to both experiment and thermochemical predictions reveals important quantitative limitations of DFT for EOS prediction and thus the assessment of high explosives. In particular, we find that DFT predicts the energy of PETN detonation products to be systematically too high relative to the unreacted neat crystalline material, resulting in an underprediction of the detonation velocity, pressure, and temperature at the Chapman–Jouguet state. The energetic bias can be partially accounted for by high-level electronic structure calculations of the product molecules. Furthermore we demonstrate a modeling strategy for mapping chemical composition across a wide parameter space with limited numerical data, the results of which suggest additional molecular species to consider in thermochemical modeling.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS1999

Anomalous Xenon in the Precambrian Nuclear Reactor in Okelobondo (Gabon): A Possible Connection to the Fission Component in the Terrestrial Atmosphere

Some CFF-Xe (Chemically Fractionated Fission Xenon), whose isotopic composition is established by simultaneous decay and migration of radioactive fission products, is probably present in the Earth's lithosphere, a conclusion based on available Xe data from various crustal and mantle rocks . Our recent isotopic analysis of Xe in alumophosphate from zone 13 of Okelobondo (southern extension of Oklo), along with the independent estimation of the isotopic composition of atmospheric fission Xe , supports the hypothesis that CFF-Xe was produced on a planetary scale. Additional information is contained in the original extended abstract.

Meshik, A. P.↗
NASA NTRSDate not supplied

Developing a Customized Composite Drought Index for Pakistan

This study aims to identify historical agricultural droughts between 2004-2019 using 10 geophysical variables (Table 1) and determine what variables have little importance in this identification. Satellite data products or model outputs are used for all input variables. Understanding the interactions between the data will provide information on temporal and spatial patterns of how drought is presented in irrigated and rainfed areas (Fig. 2). This knowledge will assist in creating a Customized Composite Drought Index in future work

Drought↗
NASA NTRS1984

Monitoring and mapping global vegetation cover using data from meteorological satellites

The role of coarse resolution meteorological satellite data for monitoring and mapping of vegetation for global, continental and regional scales is outlined. In the NOAA products used the effects of cloud cover are reduced by the generation of temporal composites of images of the normalized difference vegetation index. Different land cover types are shown to have characteristic spectral phenological curves. Such data have the disadvantage of effectively increasing the apparent areal extent of small areas of green vegetation.

Townshend, J. R. G.↗
NASA NTRS2000

Mechanisms of Carbon Nanotube Production by Laser Ablation Process

We will present possible mechanisms for nanotube production by laser oven process. Spectral emission of excited species during laser ablation of a composite graphite target is compared with that of laser irradiated C60 vapor. The similarities in the transient and spectral data suggest that fullerenes are intermediate precursors for nanotube formation. The confinement of the ablation products by means of a 25-mm diameter tube placed upstream of the target seems to improve the production and purity of nanotubes. Repeated laser pulses vaporize the amorphous/graphitic carbon and possibly catalyst particles, and dissociate fullerenes yielding additional feedstock for SWNT growth.

Scott, Carl D.↗
NASA NTRS2009

Using LIDAR and Quickbird Data to Model Plant Production and Quantify Uncertainties Associated with Wetland Detection and Land Cover Generalizations

Spatiotemporal data from satellite remote sensing and surface meteorology networks have made it possible to continuously monitor global plant production, and to identify global trends associated with land cover/use and climate change. Gross primary production (GPP) and net primary production (NPP) are routinely derived from the MOderate Resolution Imaging Spectroradiometer (MODIS) onboard satellites Terra and Aqua, and estimates generally agree with independent measurements at validation sites across the globe. However, the accuracy of GPP and NPP estimates in some regions may be limited by the quality of model input variables and heterogeneity at fine spatial scales. We developed new methods for deriving model inputs (i.e., land cover, leaf area, and photosynthetically active radiation absorbed by plant canopies) from airborne laser altimetry (LiDAR) and Quickbird multispectral data at resolutions ranging from about 30 m to 1 km. In addition, LiDAR-derived biomass was used as a means for computing carbon-use efficiency. Spatial variables were used with temporal data from ground-based monitoring stations to compute a six-year GPP and NPP time series for a 3600 ha study site in the Great Lakes region of North America. Model results compared favorably with independent observations from a 400 m flux tower and a process-based ecosystem model (BIOME-BGC), but only after removing vapor pressure deficit as a constraint on photosynthesis from the MODIS global algorithm. Fine resolution inputs captured more of the spatial variability, but estimates were similar to coarse-resolution data when integrated across the entire vegetation structure, composition, and conversion efficiencies were similar to upland plant communities. Plant productivity estimates were noticeably improved using LiDAR-derived variables, while uncertainties associated with land cover generalizations and wetlands in this largely forested landscape were considered less important.

Cook, Bruce D.↗
DOE OSTI2023

Search for a heavy composite Majorana neutrino in events with dilepton signatures from proton-proton collisions at s = 13 TeV

Results are presented of a search for a heavy Majorana neutrino Image 1 decaying into two same-flavor leptons ℓ (electrons or muons) and a quark-pair jet. A model is considered in which the Image 1 is an excited neutrino in a compositeness scenario. The analysis is performed using a sample of proton-proton collisions at s = 13 TeV recorded by the CMS experiment at the CERN LHC, corresponding to an integrated luminosity of 138 fb − 1 . The data are found to be in agreement with the standard model prediction. For the process in which the Image 1 is produced in association with a lepton, followed by the decay of the Image 1 to a same-flavor lepton and a quark pair, an upper limit at 95% confidence level on the product of the cross section and branching fraction is obtained as a function of the Image 1 mass Image 2 and the compositeness scale Λ. For this model the data exclude the existence of Image 3 (Image 4) for Image 2 below 6.0 (6.1) TeV, at the limit where Image 2 is equal to Λ. For Image 5, values of Λ less than 20 (23) TeV are excluded. These results represent a considerable improvement in sensitivity, covering a larger parameter space than previous searches in Image 6 collisions at 13 TeV.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗