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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 325 records · Page 18
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Measurements of Argon-39 from locations near historic underground nuclear explosions

Measurement of radioactive gas seepage from an underground nuclear explosion is one of the primary methods to confirm whether an event was nuclear in nature. Radioactive noble gas indicators that are commonly targeted by such measurements (e.g. 133Xe, 37Ar) have half-lives of 35 days or less. Argon-39, an activation product similar to 37Ar, is produced by the interaction between neutrons and potassium in the surrounding geology and has a half-life of 269 years. Measurements taken at three sites near three historic underground nuclear test locations at the Nevada National Security Site have all shown highly elevated levels of 39Ar in subsurface air decades after the test events. Elevated levels of 39Ar (30-50 times background) were also detected in atmospheric air collected roughly 30 cm above ground level near two of these sites, and outside the entrance of the one tunnel site. These measurements demonstrate that 39Ar has the potential to be a long-term signature of an underground nuclear event which can be reliably detected at the surface or in the shallow subsurface. This radionuclide detection of an underground nuclear event decades after the event takes place is in contrast to the commonly held assumption that detecting underground nuclear events via radionuclides at the surface needs to be done in a matter of months. Depending upon what further studies show about the robustness of this signature in a variety of geological settings, it may in fact be easy to detect underground nuclear events at the surface for a very long time post-detonation.

Johnson, Christine M.↗
DOE OSTI2018

Vertical characterization of highly oxygenated molecules (HOMs) below and above a boreal forest canopy

While the role of highly oxygenated molecules (HOMs) in new particle formation (NPF) and secondary organic aerosol (SOA) formation is not in dispute, the interplay between HOM chemistry and atmospheric conditions continues to draw significant research attention. During the Influence of Biosphere-Atmosphere Interactions on the Reactive Nitrogen budget (IBAIRN) campaign in September 2016, profile measurements of neutral HOMs below and above the forest canopy were performed for the first time at the boreal forest SMEAR II station. The HOM concentrations and composition distributions below and above the canopy were similar during daytime, supporting a well-mixed boundary layer approximation. However, much lower nighttime HOM concentrations were frequently observed at ground level, which was likely due to the formation of a shallow decoupled layer below the canopy. Near the ground HOMs were influenced by the changes in the precursors and oxidants and enhancement of the loss on surfaces in this layer, while the HOMs above the canopy top were not significantly affected. Our findings clearly illustrate that near-ground HOM measurements conducted under stably stratified conditions at this site might only be representative of a small fraction of the entire nocturnal boundary layer. This could, in turn, influence the growth of newly formed particles and SOA formation below the canopy where the large majority of measurements are typically conducted.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Experimental Study of a Novel Semi-Transparent Bi-Facial Agri-Voltaic System: Initial Results

Solar (photovoltaic)-agriculture practices have experienced notable progress across several countries over the past few decades, creating a field widely known as agrivoltaics. This co-location practice has proved effective for certain crops that prefer partial shade like tomatoes, lettuce, and peppers, although it is less effective for crops needing more sun. Availability of natural sunlight with a specific spectral signature is necessary for agricultural practices as many plant species require an optimum-level and quality of sunlight for photosynthesis. The goal of this work is to model and validate ground-level irradiance for a semi-transparent bifacial solar collector equipped with a custom spectral reflector. By introducing intentional gaps between opaque solar cells, we hope to allow 50% of visible light to pass through the module. Additionally, this technology could reduce the soil temperature by 2° C, improve moisture retention, and enhance yield by providing partial solar radiation. In our model, we can calculate the total solar irradiance for the plants as a function of the cell distribution, material absorption, height of the panel and time of year with a spatial resolution of 0.0625 m2. When comparing theoretical estimates to experimental measurements of photosynthetically active radiation (PAR), we find a discrepancy of 32-48%, and a discrepancy of 19-38% after correction with TMY data.

McGraw, Duncan (ORCID:0000000256388118)↗
NASA NTRS1975

Pi2 pulsations in the magnetosphere

Several substorms were observed at Explorer 45 in November and December 1971, and January and February 1972, while the satellite was in the evening quadrant near L = 5. These same substorms were identified in ground level magnetograms from auroral zone and low latitude stations. The satellite vector magnetic field records and rapid run ground magnetograms were examined for evidence of simultaneous occurrence of Pi2 magnetic pulsations. Pulsations which began abruptly were observed at the satellite during 7 of the 13 substorms studied and the pulsations occurred near the estimated time of substorm onset. These 7 pulsation events were also observed on the ground and 6 were identified in station comments as Pi2. All of the events observed were principally compressional waves, that is, pulsations in field magnitude. There were also transverse components elliptically polarized counter-clockwise looking along the field line. Periods observed ranged from 40 to 200 sec with 80 sec often the dominant period.

Lin, C. C.↗
NASA NTRS1983

Theoretical studies of solar-pumped lasers

Metallic vapor lasers of Na2 and Li2 are examined as solar energy converters. The absorbed photons cause transitions to vibrational-rotational levels in an upper electronic state. With broad band absorption the resultant levels can have quantum numbers considerably higher than the upper lasing level. The excited molecule then relaxes to the upper lasing level which is one of the lower vibrational levels in the upper electronic state. The relaxation occurs from collisions, provided the molecule is not quenched into the ground level electronic state. Lasing occurs with a transition to a vibrational level in the lower electronic state. Rough estimates of solar power efficiencies are 1 percent for Na2 and probably a similar figure for Li2. The nondissociative lasers from a family distinct from materials which dissociate to yield an excited atom.

Harries, W. L.↗
NASA NTRS2023

Anisotropic Mach Cone Aligned Mesh Adaptation for Low Boom Simulations

An automated off-body Mach cone aligned structured curvilinear grid generation procedure is presented for near-field computational fluid dynamics simulations. This procedure combines output-based indicators and mesh redistribution to perform anisotropic mesh adaptation while maintaining Mach cone alignment. Automation is achieved through a novel direction-based adaptation indicator formulation. The adaptation procedure is demonstrated on the JAXA Wing Body geometry and X-59 C608 demonstrator model from the Second and Third AIAA Sonic Boom Prediction Workshops, respectively. It is demonstrated that anisotropic mesh adaptation may result in a greater than fifty percent reduction in resource usage required to achieve the same level of accuracy as uniform and user constructed Mach cone aligned grids for near-field pressure signatures, ground-level overpressure signatures, and loudness metrics.

CST↗
NASA NTRS2023

Anisotropic Mach Cone Aligned Mesh Adaptation for Low Boom Simulations

An automated off-body Mach cone aligned structured curvilinear grid generation procedure is presented for near-field computational fluid dynamics simulations. This procedure combines output-based indicators and mesh redistribution to perform anisotropic mesh adaptation while maintaining Mach cone alignment. Automation is achieved through a novel direction-based adaptation indicator formulation. The adaptation procedure is demonstrated on the JAXA Wing Body geometry and X-59 C608 demonstrator model from the Second and Third AIAA Sonic Boom Prediction Workshops, respectively. It is demonstrated that anisotropic mesh adaptation may result in a greater than fifty percent reduction in resource usage required to achieve the same level of accuracy as uniform and user constructed Mach cone aligned grids for near-field pressure signatures, ground-level overpressure signatures, and loudness metrics.

CST↗
NASA NTRS1972

Airborne measurements of air pollution chemistry and transport. 1: Initial survey of major air basins in California

An instrumented aircraft has been used to study photochemical air pollution in the State of California. Simultaneous measurements of the most important chemical constituents (ozone, total oxidant, hydrocarbons, and nitrogen oxides, as well as several meteorological variables) were made. State-of-the-art measurement techniques and sampling procedures are discussed. Data from flights over the South Coast Air Basin, the San Francisco Bay Area, the San Joaquin Valley, the Santa Clara and Salinas Valleys, and the Pacific Ocean within 200 miles of the California coast are presented. Pollutants were found to be concentrated in distant layers up to at least 18,000 feet. In many of these layers, the pollutant concentrations were much higher than at ground level. These findings bring into serious question the validity of the present practice of depending solely on data from ground-based monitoring stations for predictive models.

Gloria, H. R.↗
NASA NTRS1979

Measured and predicted noise of the Avco-Lycoming YF-102 turbofan noise

Acoustic testing of the AVCO-Lycoming YF-102 turbofan engine was done on a static test stand in support of the quiet short-haul research aircraft acoustic design. Overall noise levels were dominated by the fan noise emanating from the exhaust duct, except at high power settings when combination tones were generated in the fan inlet. Component noise levels, calculated by noise prediction methods were in reasonable agreement with the measured results. Far-field microphones placed at ground level were found superior to those at engine centerline height, even at high frequencies.

Clark, B. J.↗
NASA NTRSDate not supplied

Evaluating Diurnal Ozone Emissions: A Comparative Analysis of DSCOVR EPIC, PANDORA, and TOLNet Data for Space-Based Monitoring Assessment: A Case Study by ASDC

Stratospheric ozone occurs naturally in the upper atmosphere, forming a protective layer that shields us from the sun's harmful ultraviolet rays. Tropospheric ozone is not emitted directly into the air but is created by chemical reactions between nitrogen oxides (NOx) and volatile organic compounds (VOC). This reaction happens when pollutants emitted by cars, power plants, industrial boilers, refineries, chemical plants, and other sources chemically react in sunlight [1]. Therefore, increased levels of tropospheric ozone indicate the presence of pollutants in the air. While daily anthropogenic activity causes an increase of ground-level ozone, variation of stratospheric ozone changes happens much slower, so that variation of the total ozone column reflects the variation of the tropospheric column due to natural, e.g., wildfires and anthropogenic air pollution. Both total and tropospheric ozone column products are used in this study. The reflectance spectra measured by the Earth Polychromatic Imaging Camera (EPIC) instrument aboard the Deep Space Climate Observatory (DSCOVR) spacecraft are compared with a set of radiative transfer-derived lookup tables for the EPIC filter transmission functions and a wide range of ozone values to retrieve ozone with a maximum resolution of 18 km at the sub-satellite point [2]. EPIC provides total column ozone in level 2 and level 4 products and tropospheric column ozone in level 4 products. Both EPIC Ozone products [2] are available at the Atmospheric Science Data Center (ASDC) at NASA Langley Research Center [3, 4]. Pandora spectrometer instrument measures columnar amounts of trace gases in the atmosphere. These gases (O3, NO2, CH2O) absorb light from the sun at specific wavelengths in the ultraviolet-visible spectrum [5]. Using the theoretical solar spectrum as a reference, Pandora determines trace gas amounts using differential optical absorption spectroscopy (DOAS). Pandora ozone retrievals are available from the Pandonia Global Network [6]. Pandora data from North American major metropolitan areas, New York, NY, Washington DC, Los Angeles, CA, and Mexico City. Tropospheric Ozone Lidar Network (TOLNet) was established in 2012 to provide high spatiotemporal observations of tropospheric ozone to (1) better understand physical processes driving the ozone budget in various meteorological and environmental conditions and (2) validate the tropospheric ozone measurements of space-borne missions [7]. TOLNet data are available at ASDC [8]. While EPIC provides global coverage of ozone retrievals several times daily, temporal resolution may miss some features in daily ozone variations. Ground-based sensors such as Pandora spectrometers and TOLNet lidars provide better temporal resolution while missing continuous spatial coverage. The forthcoming ozone retrieval from the TEMPO mission [9] will provide better spatial and temporal coverage of air quality (including ozone) over North America. This study investigates whether EPIC ozone products can detect diurnal air quality variations and compare ozone temporal development with retrieval by ground-based instruments.

diurnal ozone emissions, DSCOVR EPIC, PANDORA, spa↗
NASA NTRS1988

Isoprene over the Amazon Basin

Data obtained during the 1985 ABLE expedition to the Amazon are used to describe the diurnal and vertical variations of isoprene. Isoprene is a natural hydrocarbon emitted by many species of trees, particularly those in tropical forests. The concentrations of isoprene at lower levels in the atmosphere undergo large diurnal variations, with the highest concentrations during midday and the lowest during the night. At ground level, outside the forest, peak concentrations of about 3-parts per billion by volume (ppbv) of isoprene were observed around midday. Concentrations were nearly zero before sunrise, increased to their maximum values during the day, and declined after sunset. Concentrations of 1-2 ppbv of isoprene were observed up to 300 m. Near the canopy level, up to 8 ppbv of isoprene were observed. In the forest, concentrations are generally quite low below the canopy and are highest at the level of the canopy. Since the reaction of isoprene with OH radicals is extremely fast, its concentrations fall off rapidly with altitude, so that practically none of it was seen above the boundary layer. During nighttime, however, concentrations comparable to daytime values were observed at altitudes of 300 m and above.

Rasmussen, R. A.↗
NASA NTRS1981

Calculations of lightning return stroke electric and magnetic fields above ground

Lin et al., (1980) presented a lightning return stroke model with which return stroke electric and magnetic fields measured at ground level could be reproduced. This model and a modified version of it, in which the initial current peak decays with height above ground, are used to compute waveforms for altitudes from 0-10 km and at ranges of 20 m to 10 km. Both the original and modified models gave accurate predictions of measured ground-based fields. The use of the calculated fields in calibrating airborne field measurements from simultaneous ground and airborne data is discussed.

Master, M. J.↗
DOE OSTI2022

Aboveground biomass density models for NASA’s Global Ecosystem Dynamics Investigation (GEDI) lidar mission

NASA's Global Ecosystem Dynamics Investigation (GEDI) is collecting spaceborne full waveform lidar data with a primary science goal of producing accurate estimates of forest aboveground biomass density (AGBD). This paper presents the development of the models used to create GEDI's footprint-level (~25 m) AGBD (GEDI04_A) product, including a description of the datasets used and the procedure for final model selection. The data used to fit our models are from a compilation of globally distributed spatially and temporally coincident field and airborne lidar datasets, whereby we simulated GEDI-like waveforms from airborne lidar to build a calibration database. We used this database to expand the geographic extent of past waveform lidar studies, and divided the globe into four broad strata by Plant Functional Type (PFT) and six geographic regions. GEDI's waveform-to-biomass models take the form of parametric Ordinary Least Squares (OLS) models with simulated Relative Height (RH) metrics as predictor variables. From an exhaustive set of candidate models, we selected the best input predictor variables, and data transformations for each geographic stratum in the GEDI domain to produce a set of comprehensive predictive footprint-level models. We found that model selection frequently favored combinations of RH metrics at the 98th, 90th, 50th, and 10th height above ground-level percentiles (RH98, RH90, RH50, and RH10, respectively), but that inclusion of lower RH metrics (e.g. RH10) did not markedly improve model performance. Second, forced inclusion of RH98 in all models was important and did not degrade model performance, and the best performing models were parsimonious, typically having only 1-3 predictors. Third, stratification by geographic domain (PFT, geographic region) improved model performance in comparison to global models without stratification. Fourth, for the vast majority of strata, the best performing models were fit using square root transformation of field AGBD and/or height metrics. There was considerable variability in model performance across geographic strata, and areas with sparse training data and/or high AGBD values had the poorest performance. These models are used to produce global predictions of AGBD, but will be improved in the future as more and better training data become available.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2022

Aboveground biomass density models for NASA’s Global Ecosystem Dynamics Investigation (GEDI) lidar mission

NASA’s Global Ecosystem Dynamics Investigation (GEDI) is collecting spaceborne full waveform lidar data with a primary science goal of producing accurate estimates of forest aboveground biomass density (AGBD). This paper presents the development of the models used to create GEDI’s footprint-level (~25 m) AGBD (GEDI04_A) product, including a description of the datasets used and the procedure for final model selection. The data used to fit our models are from a compilation of globally distributed spatially and temporally coincident field and airborne lidar datasets, whereby we simulated GEDI-like waveforms from airborne lidar to build a calibration database. We used this database to expand the geographic extent of past waveform lidar studies, and divided the globe into four broad strata by Plant Functional Type (PFT) and six geographic regions. GEDI’s waveform-to-biomass models take the form of parametric Ordinary Least Squares (OLS) models with simulated Relative Height (RH) metrics as predictor variables. From an exhaustive set of candidate models, we selected the best input predictor variables, and data transformations for each geographic stratum in the GEDI domain to produce a set of comprehensive predictive footprint-level models. We found that model selection frequently favored combinations of RH metrics at the 98th, 90th, 50th, and 10th height above ground-level percentiles (RH98, RH90, RH50, and RH10, respectively), but that inclusion of lower RH metrics (e.g. RH10) did not markedly improve model performance. Second, forced inclusion of RH98 in all models was important and did not degrade model performance, and the best performing models were parsimonious, typically having only 1-3 predictors. Third, stratification by geographic domain (PFT, geographic region) improved model performance in comparison to global models without stratification. Fourth, for the vast majority of strata, the best performing models were fit using square root transformation of field AGBD and/or height metrics. There was considerable variability in model performance across geographic strata, and areas with sparse training data and/or high AGBD values had the poorest performance. These models are used to produce global predictions of AGBD, but will be improved in the future as more and better training data become available.

Laura Duncanson↗
DOE OSTI2014

Ecosystem Response to Elevated Tropospheric Carbon Dioxide and Ozone is Regulated by Plant-­Microbe Interactions in Soil

Human activity has increased the concentration of carbon dioxide (CO 2 ) and ozone O 3 ) in the Earth’s lower atmosphere, and each of these trace gases has the potential to modify photosynthesis and plant growth across broad geographic regions, albeit in diametrically opposing ways. For example, higher-than-ambient concentrations of atmospheric stimulate photosynthesis and plant growth (Curtis & Wang 1998), whereas elevated O 3 generally has the opposite effect (Krupa et al. 2000; Felzer et al. 2004). By the end of this century, nearly one-half of the Earth’s forests will be growing in an atmosphere with elevated concentrations of these trace gases (Albritton et al. 2001; Fowler et al. 1998, 1999). Nonetheless, we presently do not have the ability to predict the interactive effects of CO 2 and O 3 on a wide array of biological processes from the molecular to ecosystem level. Our DoE-supported research has focused on developing and testing a conceptual model that is focused on understanding the mechanisms by which elevated ground-level CO 2 and O 3 will alter the flow of energy and nutrients through soil food webs as well as entire terrestrial ecosystems. Our approach spans a hierarchy of biological organization from the molecular to the ecosystem level, and we argue that biochemical responses can be scaled to predict ecosystem-level patterns of C and N cycling in an atmosphere enriched with anthropogenic CO 2 and O 3 .

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2008

Exploiting Satellite Remote-Sensing Data in Fine Particulate Matter Characterization for Serving the Environmental Public Health Tracking Network (EPHTN): The HELIX-Atlanta Experience and NPOESS Implications

As part of the U.S. National Environmental Public Health Tracking Network (EPHTN), the National Center for Environmental Health (NCEH) at the U.S. Centers for Disease Control and Prevention (CDC) led a project in collaboration with the National Aeronautics and Space Administration (NASA) Marshall Space Flight Center (MSFC) called Health and Environment Linked for Information Exchange (HELIX-Atlanta). Under HELIX-Atlanta, pilot projects were conducted to develop methods to better characterize exposure; link health and environmental datasets; and analyze spatial/temporal relationships. This paper describes and demonstrates different techniques for surfacing daily environmental hazards data of particulate matter with aerodynamic diameter less than or equal to 2.5 micrometers (PM(sub 2.5) for the purpose of integrating respiratory health and environmental data for the CDC's pilot study of HELIX-Atlanta. It describes a methodology for estimating ground-level continuous PM(sub 2.5) concentrations using spatial surfacing techniques and leveraging NASA Moderate Resolution Imaging Spectrometer (MODIS) data to complement the U.S. Environmental Protection Agency (EPA) ground observation data. The study used measurements of ambient PM(sub 2.5) from the EPA database for the year 2003 as well as PM(sub 2.5) estimates derived from NASA's MODIS data. Hazard data have been processed to derive the surrogate exposure PM(sub 2.5) estimates. The paper has shown that merging MODIS remote sensing data with surface observations of PM(sub 2.5), may provide a more complete daily representation of PM(sub 2.5), than either data set alone would allow, and can reduce the errors in the PM(sub 2.5) estimated surfaces. Future work in this area should focus on combining MODIS column measurements with profile information provided by satellites like the National Polar-orbiting Operational Environmental Satellite System (NPOESS). The Visible Infrared Imager/Radiometer Suite (VIIRS) and the Aerosol Polarimeter Sensor (APS) NPOESS sensors will provide first-order information on aerosol particle size and are anticipated to provide information on aerosol products at higher resolution and accuracy than MODIS. Use of the NPOESS remote sensing data should result in more robust remotely sensed data that can be coupled with the methods discussed in this paper to generate surface concentrations of PM(2.5) for linkage with health data in Environmental Public Health Tracking.

Al-Hamdan, Mohammad Z.↗
DOE OSTI2023

Intra-hour Solar Irradiance Forecast in Multiple Locations using Deep Transfer Learning

In recent years, solar power system installation imposes several challenges on the operations of local and regional power grids due to the inherent variability of ground-level solar irradiance. This work proposes a novel real-time solar forecast methodology for intra-hour solar irradiance based on deep transfer learning from ground-based sky imager for time horizons ranging from 5-15 min. There are three unique aspects of the proposed methodology: (1) a Deep Learning based algorithm development which is modeled as a classification approach rather than a traditional regression approach; (2) the use of the Transfer Learning technique to show generalization capability, robustness, and portability of baseline model in the newly deployed location where availability of enough data for training is typically scarce, and (3) redefinition of point-based irradiation forecast error estimation technique with a window-based one that is more intuitive and user-friendly. The system is developed using multiple years of irradiance and sky image recording in New Jersey and one-year data from Colorado, USA. The method is validated against ground telemetry from these two locations of diverse geographic and climatic conditions. Results show that the forecasting method proposed in this work is robust and highly accurate (8% MAPE error) for multiple locations deployment.

Deep Learning, Convolution Neural Networks, transf↗
DOE OSTI2023

Viewfactor and Raytracing for AgriPV Modeling

View factor models are used in due diligence software to calculate rear irradiance for bifacial modules. An intermediate step in this calculation is the irradiance at the ground level, which can be leveraged for evaluating the Photo Active Radiation available for crops in Agrivoltaic setups. This paper presents the metrics and modifications to the model for ground irradiance study with the view factor approach, compares it to the raytracing method, and validates it with field measurements of ground irradiance. It is found that for the clearances, row-to-row setups, and tilts studied, the view factor method matches with raytracing results within 2% MBD. The comparison is performed for the nine most common agriPV configurations using high-performance computing and the NSRDB database for the whole US, with results and data made available open-source on the InSPIRE AgriPV website.

AgriPV↗