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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 415 records · Page 23
All sourcesNASA NTRSDOE OSTI
NASA NTRS2016

Consistency of Vegetation Index Seasonality Across the Amazon Rainforest

Vegetation indices (VIs) calculated from remotely sensed reflectance are widely used tools for characterizing the extent and status of vegetated areas. Recently, however, their capability to monitor the Amazon forest phenology has been intensely scrutinized. In this study, we analyze the consistency of VIs seasonal patterns obtained from two MODIS products: the Collection 5 BRDF product (MCD43) and the Multi-Angle Implementation of Atmospheric Correction algorithm (MAIAC). The spatio-temporal patterns of the VIs were also compared with field measured leaf litterfall, gross ecosystem productivity and active microwave data. Our results show that significant seasonal patterns are observed in all VIs after the removal of view-illumination effects and cloud contamination. However, we demonstrate inconsistencies in the characteristics of seasonal patterns between different VIs and MODIS products. We demonstrate that differences in the original reflectance band values form a major source of discrepancy between MODIS VI products. The MAIAC atmospheric correction algorithm significantly reduces noise signals in the red and blue bands. Another important source of discrepancy is caused by differences in the availability of clear-sky data, as the MAIAC product allows increased availability of valid pixels in the equatorial Amazon. Finally, differences in VIs seasonal patterns were also caused by MODIS collection 5 calibration degradation. The correlation of remote sensing and field data also varied spatially, leading to different temporal offsets between VIs, active microwave and field measured data. We conclude that recent improvements in the MAIAC product have led to changes in the characteristics of spatio-temporal patterns of VIs seasonality across the Amazon forest, when compared to the MCD43 product. Nevertheless, despite improved quality and reduced uncertainties in the MAIAC product, a robust biophysical interpretation of VIs seasonality is still missing.

MAIAC↗
DOE OSTI2015

Analysis of calibration data for the uranium active neutron coincidence counting collar with attention to errors in the measured neutron coincidence rate

The declared linear density of 238 U and 235 U in fresh low enriched uranium light water reactor fuel assemblies can be verified for nuclear safeguards purposes using a neutron coincidence counter collar in passive and active mode, respectively. The active mode calibration of the Uranium Neutron Collar - Light water reactor fuel (UNCL) instrument is normally performed using a non-linear fitting technique. The fitting technique relates the measured neutron coincidence rate (the predictor) to the linear density of 235 U (the response) in order to estimate model parameters of the nonlinear Parte equation, which traditionally is used to model the calibration data. Alternatively, following a simple data transformation, the fitting can also be performed using standard linear fitting methods. This article compares performance of the nonlinear technique to the linear technique, using a range of possible error variance magnitudes in the measured neutron coincidence rate. We develop the required formalism and then apply the traditional (nonlinear) and alternative approaches (linear) to the same experimental and corresponding simulated representative datasets. Here, we find that, in this context, because of the magnitude of the errors in the predictor, it is preferable not to transform to a linear model, and it is preferable not to adjust for the errors in the predictor when inferring the model parameters.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2015

The Midlatitude Continental Convective Clouds Experiment (MC3E) sounding network: operations, processing and analysis

The Midlatitude Continental Convective Clouds Experiment (MC3E) took place during the spring of 2011 centered in north-central Oklahoma, USA. The main goal of this field campaign was to capture the dynamical and microphysical characteristics of precipitating convective systems in the US Central Plains. A major component of the campaign was a six-site radiosonde array designed to capture the large-scale variability of the atmospheric state with the intent of deriving model forcing data sets. Over the course of the 46-day MC3E campaign, a total of 1362 radiosondes were launched from the enhanced sonde network. This manuscript provides details on the instrumentation used as part of the sounding array, the data processing activities including quality checks and humidity bias corrections and an analysis of the impacts of bias correction and algorithm assumptions on the determination of convective levels and indices. It is found that corrections for known radiosonde humidity biases and assumptions regarding the characteristics of the surface convective parcel result in significant differences in the derived values of convective levels and indices in many soundings. In addition, the impact of including the humidity corrections and quality controls on the thermodynamic profiles that are used in the derivation of a large-scale model forcing data set are investigated. The results show a significant impact on the derived large-scale vertical velocity field illustrating the importance of addressing these humidity biases.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2017

Probing the Physics of Narrow-line Regions in Active Galaxies. IV. Full Data Release of the Siding Spring Southern Seyfert Spectroscopic Snapshot Survey (S7)

We present the second and final data release of the Siding Spring Southern Seyfert Spectroscopic Snapshot Survey (S7). Data are presented for 63 new galaxies not included in the first data release, and we provide 2D emission-line fitting products for the full S7 sample of 131 galaxies. The S7 uses the WiFeS instrument on the ANU 2.3 m telescope to obtain spectra with a spectral resolution of R = 7000 in the red (540–700 nm) and R = 3000 in the blue (350–570 nm), over an integral field of 25 × 38 arcsec{sup 2} with 1 × 1 arcsec{sup 2} spatial pixels. The S7 contains both the largest sample of active galaxies and the highest spectral resolution of any comparable integral field survey to date. The emission-line fitting products include line fluxes, velocities, and velocity dispersions across the WiFeS field of view, and an artificial neural network has been used to determine the optimal number of Gaussian kinematic components for emission-lines in each spaxel. Broad Balmer lines are subtracted from the spectra of nuclear spatial pixels in Seyfert 1 galaxies before fitting the narrow lines. We bin nuclear spectra and measure reddening-corrected nuclear fluxes of strong narrow lines for each galaxy. The nuclear spectra are classified on optical diagnostic diagrams, where the strength of the coronal line [Fe vii] λ 6087 is shown to be correlated with [O iii]/H β . Maps revealing gas excitation and kinematics are included for the entire sample, and we provide notes on the newly observed objects.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS1995

Predictions of LDEF radioactivity and comparison with measurements

As part of the program to utilize LDEF data for evaluation and improvement of current ionizing radiation environmental models and related predictive methods for future LEO missions, calculations have been carried out to compare with the induced radioactivity measured in metal samples placed on LDEF. The predicted activation is about a factor of two lower than observed, which is attributed to deficiencies in the AP8 trapped proton model. It is shown that this finding based on activation sample data is consistent with comparisons made with other LDEF activation and dose data. Plans for confirming these results utilizing additional LDEF data sets, and plans for model modifications to improve the agreement with LDEF data, are discussed.

Armstrong, T. W.↗
NASA NTRS2014

Global Inventory and Characterization of Pyroclastic Deposits on Mercury: New Insights into Pyroclastic Activity from MESSENGER Orbital Data

We present new observations of pyroclastic deposits on the surface of Mercury from data acquired during the orbital phase of the MErcury Surface, Space ENvironment, GEochemistry, and Ranging (MESSENGER) mission. The global analysis of pyroclastic deposits brings the total number of such identified features from 40 to 51. Some 90% of pyroclastic deposits are found within impact craters. The locations of most pyroclastic deposits appear to be unrelated to regional smooth plains deposits, except some deposits cluster around the margins of smooth plains, similar to the relation between many lunar pyroclastic deposits and lunar maria. A survey of the degradation state of the impact craters that host pyroclastic deposits suggests that pyroclastic activity occurred on Mercury over a prolonged interval. Measurements of surface reflectance by MESSENGER indicate that the pyroclastic deposits are spectrally distinct from their surrounding terrain, with higher reflectance values, redder (i.e., steeper) spectral slopes, and a downturn at wavelengths shorter than approximately 400nm (i.e., in the near-ultraviolet region of the spectrum). Three possible causes for these distinctive characteristics include differences in transition metal content, physical properties (e.g., grain size), or degree of space weathering from average surface material on Mercury. The strength of the near-ultraviolet downturn varies among spectra of pyroclastic deposits and is correlated with reflectance at visible wavelengths. We suggest that this interdeposit variability in reflectance spectra is the result of either variable amounts of mixing of the pyroclastic deposits with underlying material or inherent differences in chemical and physical properties among pyroclastic deposits.

Stratigraphic relationships↗
NASA NTRS1993

Dynamics Explorer 2: Continued FPI and NACS instrument data analysis and associated scientific activity at the University of Michigan

The grant entitled 'Dynamics Explorer 2 - continued FPI and NACS instrument data analysis and associated scientific activity at the University of Michigan' is a continuation of a grant that began with instrument development for the Dynamics Explorer 2 (DE 2) satellite. Over the years, many publications and presentations at scientific meetings have occurred under the aegis of this grant. This present report details the progress that has been made in the final three years of the grant. In these last 4 years of the grant 26 papers have been published or are in press and about 10 more are in preparation or have been submitted. A large number of presentations have been made in the same time span: 36 are listed in Appendix 2. Evidence of the high educational utility of this research is indicated by the list of Ph. D. and M. S. theses that have been completed in the last 3 years that have involved work connected with NAG5-465. The structure of this report is as follows: a brief synopsis of the aims of the grant NAG5-465 is given in the next section; then there is a summary of the scientific accomplishments that have occurred over the grant period; last, we make some brief concluding remarks. Reprints of articles that have recently appeared in refereed journals are appended to the end of this document.

Burns, Alan↗
NASA NTRS1990

NASA standard: Trend analysis techniques

Descriptive and analytical techniques for NASA trend analysis applications are presented in this standard. Trend analysis is applicable in all organizational elements of NASA connected with, or supporting, developmental/operational programs. This document should be consulted for any data analysis activity requiring the identification or interpretation of trends. Trend analysis is neither a precise term nor a circumscribed methodology: it generally connotes quantitative analysis of time-series data. For NASA activities, the appropriate and applicable techniques include descriptive and graphical statistics, and the fitting or modeling of data by linear, quadratic, and exponential models. Usually, but not always, the data is time-series in nature. Concepts such as autocorrelation and techniques such as Box-Jenkins time-series analysis would only rarely apply and are not included in this document. The basic ideas needed for qualitative and quantitative assessment of trends along with relevant examples are presented.

Source record↗
NASA NTRS1988

NASA standard: Trend analysis techniques

This Standard presents descriptive and analytical techniques for NASA trend analysis applications. Trend analysis is applicable in all organizational elements of NASA connected with, or supporting, developmental/operational programs. Use of this Standard is not mandatory; however, it should be consulted for any data analysis activity requiring the identification or interpretation of trends. Trend Analysis is neither a precise term nor a circumscribed methodology, but rather connotes, generally, quantitative analysis of time-series data. For NASA activities, the appropriate and applicable techniques include descriptive and graphical statistics, and the fitting or modeling of data by linear, quadratic, and exponential models. Usually, but not always, the data is time-series in nature. Concepts such as autocorrelation and techniques such as Box-Jenkins time-series analysis would only rarely apply and are not included in this Standard. The document presents the basic ideas needed for qualitative and quantitative assessment of trends, together with relevant examples. A list of references provides additional sources of information.

Source record↗
NASA NTRS2009

An Intelligent Archive Testbed Incorporating Data Mining

Many significant advances have occurred during the last two decades in remote sensing instrumentation, computation, storage, and communication technology. A series of Earth observing satellites have been launched by U.S. and international agencies and have been operating and collecting global data on a regular basis. These advances have created a data rich environment for scientific research and applications. NASA s Earth Observing System (EOS) Data and Information System (EOSDIS) has been operational since August 1994 with support for pre-EOS data. Currently, EOSDIS supports all the EOS missions including Terra (1999), Aqua (2002), ICESat (2002) and Aura (2004). EOSDIS has been effectively capturing, processing and archiving several terabytes of standard data products each day. It has also been distributing these data products at a rate of several terabytes per day to a diverse and globally distributed user community (Ramapriyan et al. 2009). There are other NASA-sponsored data system activities including measurement-based systems such as the Ocean Data Processing System and the Precipitation Processing system, and several projects under the Research, Education and Applications Solutions Network (REASoN), Making Earth Science Data Records for Use in Research Environments (MEaSUREs), and the Advancing Collaborative Connections for Earth-Sun System Science (ACCESS) programs. Together, these activities provide a rich set of resources constituting a value chain for users to obtain data at various levels ranging from raw radiances to interdisciplinary model outputs. The result has been a significant leap in our understanding of the Earth systems that all humans depend on for their enjoyment, livelihood, and survival. The trend in the community today is towards many distributed sets of providers of data and services. Despite this, visions for the future include users being able to locate, fuse and utilize data with location transparency and high degree of interoperability, and being able to convert data to information and usable knowledge in an efficient, convenient manner, aided significantly by automation (Ramapriyan et al. 2004; NASA 2005). We can look upon the distributed provider environment with capabilities to convert data to information and to knowledge as an Intelligent Archive in the Context of a Knowledge Building system (IA-KBS). Some of the key capabilities of an IA-KBS are: Virtual Product Generation, Significant Event Detection, Automated Data Quality Assessment, Large-Scale Data Mining, Dynamic Feedback Loop, and Data Discovery and Efficient Requesting (Ramapriyan et al. 2004).

Ramapriyan, H.↗
DOE OSTI2015

Effect of 50MeV Li{sup 3+} ion irradiation on structural, optical and electrical properties of amorphous Se{sub 95}Zn{sub 5} thin films

Present work focuses on the effect of swift heavy ion (SHI) irradiation of 50MeV Li{sup 3+} ions by varying the fluencies in the range of 1×10{sup 12} to 5×10{sup 13} ions/cm{sup 2} on the morphological, structural, optical and electrical properties of amorphous Se{sub 95}Zn{sub 5} thin films. Thin films of ~250nm thickness were deposited on cleaned glass substrates by thermal evaporation technique. X-ray diffraction (XRD) analysis shows the pristine thin film of Se{sub 95}Zn{sub 5} growsin hexagonal phase structure. Also it was found that the small peak observed in XRD spectra vanishes after SHI irradiation indicates the defects of the material increases. The optical parameters: absorption coefficient (α), extinction coefficient (K), refractive index (n) optical band gap (E{sub g}) and Urbach’s energy (E{sub U}) are determined from optical absorption spectra data measured from spectrophotometry in the wavelength range 200-1000nm. It was found that the values of absorption coefficient, refractive index and extinction coefficient increases while the value optical band gap decreases with the increase of ion fluence. This post irradiation change in the optical parameters was interpreted in terms of bond distribution model. Electrical properties such as dc conductivity and temperature dependent photoconductivity of investigated thin films were carried out in the temperature range 309-370 K. Analysis of data shows activation energy of dark current is greater as compared to activation energy photocurrent. The value of activation energy decreases with the increase of ion fluence indicates that the defect density of states increases.Also it was found that the value of dc conductivity and photoconductivity increases with the increase of ion fluence.

36 MATERIALS SCIENCE↗
DOE OSTI2014

Full-length structure of a monomeric histidine kinase reveals basis for sensory regulation

Although histidine kinases (HKs) are critical sensors of external stimuli in prokaryotes, the mechanisms by which their sensor domains control enzymatic activity remain unclear. In this paper, we report the full-length structure of a blue light-activated HK from Erythrobacter litoralis HTCC2594 (EL346) and the results of biochemical and biophysical studies that explain how it is activated by light. Contrary to the standard view that signaling occurs within HK dimers, EL346 functions as a monomer. Its structure reveals that the light–oxygen–voltage (LOV) sensor domain both controls kinase activity and prevents dimerization by binding one side of a dimerization/histidine phosphotransfer-like (DHpL) domain. The DHpL domain also contacts the catalytic/ATP-binding (CA) domain, keeping EL346 in an inhibited conformation in the dark. Upon light stimulation, interdomain interactions weaken to facilitate activation. Our data suggest that the LOV domain controls kinase activity by affecting the stability of the DHpL/CA interface, releasing the CA domain from an inhibited conformation upon photoactivation. Finally, we suggest parallels between EL346 and dimeric HKs, with sensor-induced movements in the DHp similarly remodeling the DHp/CA interface as part of activation.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Illinois State Geological Survey (ISGS), Illinois Basin - Decatur Project (IBDP) Seismic Data, July 7, 2021. Midwest Geological Sequestration Consortium (MGSC) Phase III Data Sets. DOE Cooperative Agreement No. DE-FC26-05NT42588.

Seismic data from the IBDP, included primarily under folders: Active_Seismic_Data and Passive_Seismic_Events_Monitoring. The data included under IBDP_Located_Microseismic_Event_Data are a subset of microseismic (Passive Seismic Events Monitoring) data acquired throughout the project from pre-injection to shut-in. These data represent the “located” microseismic events and the two datasets, located in folders Downhole_Geophone_Data and Surface_Seismometer_Data, are correlated.

3D Seismic,Carbon Sequestration,Decatur,Illinois B↗
DOE OSTI2021

Natural Systems Data Package for the Active Trenches of the Low-Level Burial Grounds, Hanford Site, Washington

This document summarizes the available information regarding the natural system (vadose zone and saturated zone) at the active trenches of the 200 West Area and 200 East Area Low-Level Burial Grounds (LLBGs). This information is relevant for developing the natural system fate and transport model for the update of the active trenches performance assessment. This document presents a description of the major features, events, and processes of the natural system at the active trenches of the 200 West Area and 200 East Area LLBGs that involves the geologic features or framework, and the vadose zone and groundwater flow and transport system. The description of the geologic features includes the following items: geologic setting, major structural features, major hydrostratigraphic units, and geologic framework. The discussion concerning vadose zone flow and transport at the active trenches of the 200 West Area and 200 East Area LLBGs includes the following topics: vadose zone features, events, and processes relevant to the development of the vadose zone conceptual model; hydrogeologic units and conditions; factors affecting moisture movement; and flow and transport properties of major units. The discussion concerning the groundwater flow and transport system in the vicinity of the active trenches of the 200 West Area and 200 East Area LLBGs includes the following topics: saturated zone features, events, and processes relevant to the saturated zone conceptual model; hydrogeologic units; groundwater flow conditions; and flow and transport properties.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗