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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 793 records · Page 44
All sourcesNASA NTRSDOE OSTI
NASA NTRS1989

Average areal water equivalent of snow in a mountain basin using microwave and visible satellite data

Satellite microwave data were used to evaluate the average areal water equivalent of snow cover in the mountainous Rio Grande basin of Colorado. Areal water equivalent data for the basin were obtained from contoured values of point measurements and from zonal water volume values generated by a snowmelt runoff model. Comparison of these snow water equivalent values shows the model values to consistently exceed the contoured values, probably because of the narrow elevation range in the lower part of the basin where the point measurements are concentrated. A significant relationship between the difference in microwave brightness temperatures at two different wavelengths and a basin-wide average snow water equivalent value is obtained. The average water equivalent of the snow cover in the basin was derived from differences of the microwave brightness temperatures.

Rango, Albert↗
NASA NTRS1990

The sunrise and sunset variation of ClO in the lower stratosphere

The abundances of ClO have been measured, in situ, in the lower stratosphere during sunrise and sunset. Measurements were made with an instrument mounted on the NASA ER-2 aircraft, which was flown at an altitude of 20 km and latitudes between 35 and 47 deg N during a morning and an evening flight. The abundances of ClO were observed over a dynamic range of 20 from a detection threshold of 1 part per trillion volume (pptv). These data confirm the sunrise variation of the photolysis of chlorine nitrate that is predicted by a zero-dimensional photochemical model. They also suggest that the absolute photolysis and termolecular formation of chlorine nitrate occur at rates consistent with nominal ClONO2 and NO2 concentrations.

Brune, W. H.↗
NASA NTRS2004

Ozone Measurements and a 3D Chemical Transport Model

We have used our three-dimensional chemical transport model (CTM) to calculate the expected reponse of stratospheric composition over the past 30 years to forcing by chlorine and bromine compounds, solar ultraviolet, and volcanic aerosols. The CTM uses off-line winds and temperatures fiom a 50-year run of the finite volume general circulation model (FVGCM). We compare the total column ozone and the ozone profile fiom the CTM output to a variety of data sources. These include a merged total ozone data set from TOMS and SBUV using the new version 8 algorithm. Total ozone fiom the CTM are compared to ground-station measurements of total ozone at specific locations. Ozone profiles are compared to satellite meausrements fiom SBUV, SAGE, and HALOE. Profiles are also compared to ozonesondes over several locations. The results of the comparisons are quantified by using a time-series statistical analysis to determine trends, solar cycle, and volcanic reponse in both the model and in the data. Initial results indicate that the model responds to forcings in a way that is similar to the observed atmospheric response. The model does seem to be more sensitive to the chlorine and bromine perturbation ihan is the data. Further details and comparisons wiii be discussed.

Stolarski, Richard S.↗
NASA NTRSDate not supplied

TPSAS-NF1676L-33992-DND

The CERES Science Team integrates and fuses observations from 6 CERES instruments aboard the Terra, Aqua, S-NPP, and NOAA-20 missions with data from more than 20 other unique data sources. Following the November 2017 launch of CERES Flight Model 6 (FM6) onboard NOAA20, CERES has now amassed over 80 instrument-years of valuable Earth radiation budget data. The rapidly growing volume of CERES data coupled with the introduction of new data products alongside improvements to existing science algorithms fosters the requirement for faster, more flexible, and scalable data production and orchestration. New virtualized, cloud-centric compute hardware hosted by the NASA Langley Research Center’s (LaRC) Atmospheric Sciences Data Center (ASDC) provides an ideal environment for these ever-increasing data production demands for CERES. This poster discusses updates to the implementation of the CERES Data Management Team’s (DMT) CERES AuTomAted job Loading sYSTem (CATALYST), a custom data processing workflow engine for CERES, to use on-demand computing resources to perform automated CERES data production processing in a Linux-based container environment. Linux containers provide CERES the flexibility to build multiple production environments in containers tailored for specific workloads and allow effortless provisioning of resources based on the CERES Science Team’s data production requirements.

Thomas N. Hillyer↗
DOE OSTI2020

Ordovician-Cambrian Units: Hierarchical Evaluation of Geologic Carbon Storage Resource Estimates

The Indiana Geological and Water Survey (IGWS) led subtask 1.1 to assess the regional distribution and estimate the storage capacity of Ordovician-Cambrian stratigraphic units located within the partnership region. A comprehensive data set of wireline logs and petrophysical information was used to generate these interpretations. These data include core analysis for porosity and permeability, mercury injection capillary pressure (MICP), and existing well data including location and stratigraphic information. This report includes storage resource estimates (SREs) for three potential storage reservoirs(limestone and dolostone from the Upper Ordovician Trenton Limestone/Black River Group and equivalent units, the Middle Ordovician St. Peter Sandstone, and primary target reservoir rocks of the Lower Ordovician and Upper Cambrian Knox Supergroup and equivalent units) calculated using six methodologies: (1) a fixed value of porosity of 10 percent in all units evaluated; (2) a unique average porosity (per well) from wireline-derived porosity (neutron, sonic, and/or density porosity for each unit); (3) porosity values from core analysis; (4) a depth-dependent porosity model (Knox Supergroup only); (5) porosity based on a model based on petrophysical facies; and (6) SREs using National Energy Technology Laboratory’s CO2 Storage prospeCtive Resource Estimation Excel aNalysis (CO2-SCREEN beta V2). All methods used the same values for thickness for each unit. However, the areal extent of each assessment was limited by the data available for each method. Estimated volumes were calculated in 1-by-1 kilometer grid cells and summarized as county and total stratigraphic unit volumes. The resultant SREs mass are displayed using boxplots, which allow for comparing data statistics (mean values and variability) between methods. Differences observed in SRE results from the six methods are mainly attributable to differences in the data and conceptual models used to interpret or estimate porosity in each method. Based on this systematic variability between methods, it is inferred that methods 1, 4, and 6 are best used for regional-scale reconnaissance estimates of storage capacity while methods 2, 3, and 5 are more appropriate for local scales where more data is required. All estimates are data-density dependent and different methods require different amounts of data for reasonable assessments. ArcMap 10.5.1 software was used to portray SREs to help visualize spatial variance of estimates for each methodology, and more importantly, to highlight those areas having the greatest total storage potential estimates.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2022

Development of lean, efficient, and fast physics-framed deep-learning-based proxy models for subsurface carbon storage

In this work, we present deep-learning-based surrogate models for CCUS developed with four different algorithms and a physics-framed two-phase flow problem involving displacement of water by CO 2 . The deep-learning models were trained using 3D datasets describing the pressure plume, CO 2 saturation plume, and water extraction rate generated by numerical simulation. The hyperparameters defining the architecture of the neural networks were optimized to determine the slimmest network size and training parameters that give the most efficient performance at the least training cost. To develop a robust model that closely mimics the governing physical laws, the discretized form of the two-phase fluid transport equation was used to formulate the supervised deep-learning task. The algorithms investigated in this study predicted the data to above 95% accuracy, with the multi-layer perceptron model demonstrating the best performance by balancing training speed, prediction time, and prediction accuracy with lean network capacity. Furthermore, the surrogate models simultaneously predict reservoir pressure and CO 2 saturation in every grid block, including the surface well extraction rate and bottomhole pressure, at all simulation times for a given static model realization in just a few seconds on a standard desktop computer. A key outcome of this study is that limits can be placed on network design parameters to avoid over designing neural networks, with associated efficiencies in training and prediction times. This is very useful because large volumes of data may be generated in CCUS projects and over-design of neural network architectures imposes penalties that are antithetical to the goal of near-real time forecasting.

58 GEOSCIENCES↗
NASA NTRS1973

Results of Tests OA12 and IA9 in the Ames Research Center unitary plan wind tunnels on an 0.030-scale model of the Space Shuttle Vehicle 2A to determine aerodynamic loads, volume 4

Tests were conducted in wind tunnels during April and May 1973, on an 0.030-scale replica of the Space Shuttle Vehicle Configuration 2A. Aerodynamic loads data were obtained at Mach numbers from 0.6 to 3.5. The investigation included tests on the integrated (launch) configuration and on the isolated orbiter (entry configuration). The integrated vehicle was tested at angles of attack and sideslip from minus 8 degrees to +8 degrees. The isolated orbiter was tested at angles of attack from minus 15 degrees to +40 degrees and angles of sideslip from minus 10 degrees to +10 degrees as dictated by trajectory considerations. The effects of orbiter/external tank incidence angle and deflected control surfaces on aerodynamic loads were also investigated.

Spangler, R. H.↗
NASA NTRS1973

Results of tests OA12 and IA9 in the Ames Research Center unitary plan wind tunnels on an 0.030 scale model of the space shuttle vehicle 2A to determine aerodynamic loads, volume 7

Tests were conducted in wind tunnels during April and May 1973, on an 0.030-scale replica of the Space Shuttle Vehicle Configuration 2A. Aerodynamic loads data were obtained at Mach numbers from 0.6 to 3.5. The investigation included tests on the integrated (launch) configuration and on the isolated orbiter (entry configuration). The integrated vehicle was tested at angles of attack and sideslip from -8 deg. The isolated orbiter was tested at angles of attack from -15 deg to +40 deg and angles of sideslip from -10 deg to +10 deg as dictated by trajectory considerations. The effects of orbiter/external tank incidence angle and deflected control surfaces on aerodynamic loads were also investigated.

Spangler, R. H.↗
NASA NTRS1973

Results of tests OA12 and IA9 in the Ames Research Center unitary plan wind tunnels on an 0.030-scale model of the Space Shuttle Vehicle 2A to determine aerodynamic loads, volume 11

Tests were conducted in wind tunnels during April and May 1973, on an 0.030-scale replica of the Space Shuttle Vehicle Configuration 2A. Aerodynamic loads data were obtained at Mach numbers from 0.6 to 3.5. The investigation included tests on the integrated (launch) configuration and on the isolated orbiter (entry configuration). The integrated vehicle was tested at angles of attack from -15 degrees to +40 degrees and angles of sideslip from -10 degrees to +10 degrees as dictated by trajectory considerations. The effects of orbiter/external tank incidence angle and deflected control surfaces on aerodynamic loads were also investigated. Tabulated pressure data are presented for: orbiter fuselage and base, upper MPS nozzle, OMS nozzle, body flap, OMS pod outside, and lower wing surface.

Spangler, R. H.↗
NASA NTRS1974

Results of tests OA12 and IA9 in the Ames Research Center unitary plan wind tunnels on an 0.030-scale model of the space shuttle vehicle 2A to determine aerodynamic loads, volume 13

Tests were conducted in wind tunnels during April and May 1973, on a 0.030-scale replica of the Space Shuttle Vehicle Configuration 2A. Aerodynamic loads data were obtained at Mach numbers from 0.6 to 3.5. The investigation included tests on the integrated (launch) configuration and on the isolated orbiter (entry configuration). The integrated vehicle was tested at angles of attack and sideslip from -8 deg to +8 deg. The isolated orbiter was tested at angles of attack from -15 deg to +40 deg and angles of sideslip from -10 deg to +10 deg as dictated by trajectory considerations. The effects of orbiter/external tank incidence angle and deflected control surfaces on aerodynamic loads were also investigated. Tabulated pressure data are given for the following components: orbiter fuselage and base; OMS and upper MPS nozzles; body flap; and OMS pod outside.

Spangler, R. H.↗
NASA NTRS1974

Results of tests OA12 and IA9 in the Ames Research Center unitary plan wind tunnels on an 0.030-scale model of the space shuttle vehicle 2A to determine aerodynamic loads, volume 14

Tests were conducted in wind tunnels during April and May 1973, on a 0.030-scale replica of the Space Shuttle Vehicle Configuration 2A. Aerodynamic loads data were obtained at Mach numbers from 0.6 to 3.5. The investigation included tests on the integrated (launch) configuration and the isolated orbiter (entry configuration). The integrated vehicle was tested at angles of attack and sideslip from -8 degrees to +8 degrees. The isolated orbiter was tested at angles of attack from -15 degrees to +40 degrees and angles of sideslip from -10 degrees to +10 degrees as dictated by trajectory considerations. The effects of orbiter/external tank incidence angle and deflected control surfaces on aerodynamic loads were also investigated. Tabulated pressure data were obtained for upper and lower wing surfaces and left and right vertical tail surfaces.

Spangler, R. H.↗
NASA NTRS2006

Sensor Management for Applied Research Technologies (SMART)-On Demand Modeling (ODM) Project

NASA requires timely on-demand data and analysis capabilities to enable practical benefits of Earth science observations. However, a significant challenge exists in accessing and integrating data from multiple sensors or platforms to address Earth science problems because of the large data volumes, varying sensor scan characteristics, unique orbital coverage, and the steep learning curve associated with each sensor and data type. The development of sensor web capabilities to autonomously process these data streams (whether real-time or archived) provides an opportunity to overcome these obstacles and facilitate the integration and synthesis of Earth science data and weather model output. A three year project, entitled Sensor Management for Applied Research Technologies (SMART) - On Demand Modeling (ODM), will develop and demonstrate the readiness of Open Geospatial Consortium (OGC) Sensor Web Enablement (SWE) capabilities that integrate both Earth observations and forecast model output into new data acquisition and assimilation strategies. The advancement of SWE-enabled systems (i.e., use of SensorML, sensor planning services - SPS, sensor observation services - SOS, sensor alert services - SAS and common observation model protocols) will have practical and efficient uses in the Earth science community for enhanced data set generation, real-time data assimilation with operational applications, and for autonomous sensor tasking for unique data collection.

Goodman, M.↗
DOE OSTI2023

Spectral Energy Distributions for 258 Local Volume Galaxies

We present model spectral energy distribution (SED) fits to ultraviolet/optical/infrared observations for the 258 nearby galaxies in the Local Volume Legacy survey, a sample dominated by lower-luminosity dwarf irregular systems. The data for each galaxy include up to 26 spatially-integrated broadband and narrowband fluxes from the Galaxy Evolution Explorer, Spitzer Space Telescope, and Infrared Astronomical Satellite space-based platforms, and from the Sloan Digital Sky Survey, Two Micron All Sky Survey, and other ground-based efforts. The CIGALE SED fitting package is employed using a delayed star-formation history with an optional late burst or quenching episode to constrain 11 different free parameters that characterize the properties of each galaxy's stellar and dust emission, with the overriding constraint that the ultraviolet/optical emission absorbed by interstellar dust grains is emitted in equal energy portions at infrared wavelengths. The main results are: (i) 94% of the SED fits yield reduced χ 2 values less than 3; (ii) the modeled stellar masses agree with those derived from 3.6 μm-based measures with a scatter of 0.07 dex; (iii) for a typical galaxy in the sample the SED-derived star-formation rate averaged over the past 100 Myr is about 88% of the value derived from standard hybrid indicators on similar timescales; and (iv) there is a statistically significant inverse relation between the stellar mass fraction appearing in the late burst and the total stellar mass. These results build upon prior SED modeling efforts in the local volume and lay the groundwork for future studies of more distant low-metallicity galaxies with JWST.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS2005

NASA Earth Sciences Data Support System and Services for the Northern Eurasia Earth Science Partnership Initiative

The presentation describes data management of NASA remote sensing data for Northern Eurasia Earth Science Partnership Initiative (NEESPI). Many types of ground and integrative (e.g., satellite, GIs) data will be needed and many models must be applied, adapted or developed for properly understanding the functioning of Northern Eurasia cold and diverse regional system. Mechanisms for obtaining the requisite data sets and models and sharing them among the participating scientists are essential. The proposed project targets integration of remote sensing data from AVHRR, MODIS, and other NASA instruments on board US- satellites (with potential expansion to data from non-US satellites), customized data products from climatology data sets (e.g., ISCCP, ISLSCP) and model data (e.g., NCEPNCAR) into a single, well-architected data management system. It will utilize two existing components developed by the Goddard Earth Sciences Data & Information Services Center (GES DISC) at the NASA Goddard Space Flight Center: (1) online archiving and distribution system, that allows collection, processing and ingest of data from various sources into the online archive, and (2) user-friendly intelligent web-based online visualization and analysis system, also known as Giovanni. The former includes various kinds of data preparation for seamless interoperability between measurements by different instruments. The latter provides convenient access to various geophysical parameters measured in the Northern Eurasia region without any need to learn complicated remote sensing data formats, or retrieve and process large volumes of NASA data. Initial implementation of this data management system will concentrate on atmospheric data and surface data aggregated to coarse resolution to support collaborative environment and climate change studies and modeling, while at later stages, data from NASA and non-NASA satellites at higher resolution will be integrated into the system.

Leptoukh, Gregory↗
NASA NTRS2006

NASA Earth Sciences Data Support System and Services for the Northern Eurasia Earth Science Partnership Initiative

The presentation describes the recently awarded ACCESS project to provide data management of NASA remote sensing data for the Northern Eurasia Earth Science Partnership Initiative (NEESPI). The project targets integration of remote sensing data from MODIS, and other NASA instruments on board US-satellites (with potential expansion to data from non-US satellites), customized data products from climatology data sets (e.g., ISCCP, ISLSCP) and model data (e.g., NCEP/NCAR) into a single, well-architected data management system. It will utilize two existing components developed by the Goddard Earth Sciences Data & Information Services Center (GES DISC) at the NASA Goddard Space Flight Center: (1) online archiving and distribution system, that allows collection, processing and ingest of data from various sources into the online archive, and (2) user-friendly intelligent web-based online visualization and analysis system, also known as Giovanni. The former includes various kinds of data preparation for seamless interoperability between measurements by different instruments. The latter provides convenient access to various geophysical parameters measured in the Northern Eurasia region without any need to learn complicated remote sensing data formats, or retrieve and process large volumes of NASA data. Initial implementation of this data management system will concentrate on atmospheric data and surface data aggregated to coarse resolution to support collaborative environment and climate change studies and modeling, while at later stages, data from NASA and non-NASA satellites at higher resolution will be integrated into the system.

Leptoukh, Gregory↗
NASA NTRS2016

SpIES: The Spitzer IRAC Equatorial Survey

We describe the first data release from the Spitzer-IRAC Equatorial Survey (SpIES); a large-area survey of approx.115 sq deg in the Equatorial SDSS Stripe 82 field using Spitzer during its "warm" mission phase. SpIES was designed to probe sufficient volume to perform measurements of quasar clustering and the luminosity function at z > or = 3 to test various models for "feedback" from active galactic nuclei (AGNs). Additionally, the wide range of available multi-wavelength, multi-epoch ancillary data enables SpIES to identify both high-redshift (z > or = 5) quasars as well as obscured quasars missed by optical surveys. SpIES achieves 5 sigma depths of 6.13 μJy (21.93 AB magnitude) and 5.75 μJy (22.0 AB magnitude) at 3.6 and 4.5 microns, respectively-depths significantly fainter than the Wide-field Infrared Survey Explorer (WISE). We show that the SpIES survey recovers a much larger fraction of spectroscopically confirmed quasars (approx.98%) in Stripe 82 than are recovered by WISE (∼55%). This depth is especially powerful at high-redshift (z > or = 3.5), where SpIES recovers 94% of confirmed quasars, whereas WISE only recovers 25%. Here we define the SpIES survey parameters and describe the image processing, source extraction, and catalog production methods used to analyze the SpIES data. In addition to this survey paper, we release 234 images created by the SpIES team and three detection catalogs: a 3.6 microns only detection catalog containing approx. 6.1 million sources, a 4.5 microns only detection catalog containing approx. 6.5 million sources, and a dual-band detection catalog containing approx. 5.4 million sources.

quasar clustering↗
DOE OSTI2025

Towards an Introspective Dynamic Model of Globally Distributed Computing Infrastructures

Large-scale scientific collaborations like ATLAS, Belle II, CMS, DUNE, and others involve hundreds of research institutes and thousands of researchers spread across the globe. These experiments generate petabytes of data, with volumes soon expected to reach exabytes. Consequently, there is a growing need for computation, including structured data processing from raw data to consumer-ready derived data, extensive Monte Carlo simulation campaigns, and a wide range of end-user analysis. To manage these computational and storage demands, centralized workflow and data management systems are implemented. However, decisions regarding data placement and payload allocation are often made disjointly and via heuristic means. A significant obstacle in adopting more effective heuristic or AI-driven solutions is the absence of a quick and reliable introspective dynamic model to evaluate and refine alternative approaches. In this study, we aim to develop such an interactive system using real-world data. By examining job execution records from the PanDA workflow management system, we have pinpointed key performance indicators such as queuing time, error rate, and the extent of remote data access. The dataset includes five months of activity. Additionally, we are creating a generative AI model to simulate time series of payloads, which incorporate visible features like category, event count, and submitting group, as well as hidden features like the total computational load—derived from existing PanDA records and computing site capabilities. These hidden features, which are not visible to job allocators, whether heuristic or AI-driven, influence factors such as queuing times and data movement.

kilic, Ozgur Ozan [Brookhaven National Laboratory ↗
NASA NTRS2019

Preliminary Soot Computations Based on a Model Aircraft Combustor With OpenNCC

In a preliminary effort to extend our current capabilities used in the design & testing of aero-engine combustors to particulate emissions, we incorporated several existing 2- equation soot models into the Open National Combustion Code (OpenNCC). The paper presents results from a validation study based on a well-characterized, swirl-stabilized, turbulent sooting flame generated by a model aero-engine combustor developed at DLR, Germany. The calculations are based on a Reynolds-Averaged Navier Stokes (RANS) simulation with standard k-e turbulence model & a finite-rate chemical kinetic mechanism. A separate transport equation is solved for all individual species involved in ethylene/air combustion. The predicted velocity and temperature are mostly in good agreement with the measured data and reasonable agreement was found for soot. While the calculated SVF (Soot Volume Fraction) behavior is similar to some other predicted results reported in literature, the measured soot lasts farther downstream than the calculated soot indicating a need for further improvement in the soot models employed.

Raju, Manthena↗