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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 289 records · Page 16
All sourcesNASA NTRSDOE OSTI
NASA NTRS1994

Seasonal Patterns and Remote Spectral Estimation of Canopy Chemistry Across the Oregon Transect

We examined seasonal changes in canopy chemical concentrations and content in conifer forests growing along a climate gradient in western Oregon, as part of the Oregon Transect Ecosystem Research (OTTER) study. The chemical variables were related to seasonal patterns of growth and production. Statistical comparisons of chemical variables with data collected from two different airborne remote-sensing platforms were also carried out. Total nitrogen (N) concentrations in foliage varied significantly both seasonally and among sites; when expressed as content in the forest canopy, nitrogen varied to a much greater extent and was significantly related to aboveground net primary production (r = 0.99). Chlorophyll and free amino acid concentrations varied more strongly than did total N and may have reflected changes in physiological demands for N. Large variations in starch concentrations were measured from pre- to post-budbreak in all conifer sites. Examination of remote-sensing data from two different airborne instruments suggests the potential for remote measurement of some canopy chemicals. Multivariate analysis of high-resolution spectral data in the near infrared region indicated significant correlations between spectral signals and N concentration and canopy N content; the correlation with canopy N content was stronger and was probably associated in part with water absorption features of the forest canopy. The spectral bands that were significantly correlated with lignin concentration and content were similar to bands selected in the other laboratory and airborne studies; starch concentrations were not significantly related to spectral reflectance data. Strong relationships between the spectral position of specific reflectance features in the visible region and chlorophyll were also found.

Matson, Pamela↗
NASA NTRS1989

Vascular Responsiveness in Adrenalectomized Rats with Corticosterone Replacement

To determine under resting, unstressed conditions the circulating glucocorticoid concentrations that best maintain sensitivity of the vascular smooth muscle and baroreceptor responses to vasoactive agents, rats with vascular cannulas were sham-adrenalectomized (sham) or adrenalectomized (ADRX) and provided with four levels of corticosterone replacement (-100 mg fused pellets of corticosterone: cholesterol 0, 20, 40, and 80% implanted subcutaneously at the time of adrenal surgery). Changes in vascular and baroreflex responses were determined after intravenous injection of varying doses of phenylephrine and nitroglycerin with measurement of arterial blood pressure and heart rate in the conscious, chronically cannulated rats. Vascular sensitivity was decreased, and resting arterial blood pressure tended to be decreased in the adrenalectomized rats; both were restored to normal with levels of corticosterone (40%), which also maintained body weight gain, thymus weight, and plasma corticosteroid binding globulin concentrations at normal values. The baroreflex curve generated from the sham group was different from the curves generated from the ADRX+O, 20, and 40% groups, but not different from that of the ADRX+80% group, suggesting that the baroreflex is maintained by higher levels of corticosterone than are necessary for the maintenance of the other variables. These data demonstrate that physiological levels of corticosterone (40% pellet) restore vascular responsiveness, body weight, thymus weight, and transcortin levels to normal in ADRX rats, whereas higher levels (80% pellet) are necessary for restoration of the baroreflex.

Darlington, Daniel N.↗
NASA NTRS2000

BOREAS RSS-8 BIOME-BGC SSA Simulation of Annual Water and Carbon Fluxes

The BOREAS RSS-8 team performed research to evaluate the effect of seasonal weather and landcover heterogeneity on boreal forest regional water and carbon fluxes using a process-level ecosystem model, BIOME-BGC, coupled with remote sensing-derived parameter maps of key state variables. This data set contains derived maps of landcover type and crown and stem biomass as model inputs to determine annual evapotranspiration, gross primary production, autotrophic respiration, and net primary productivity within the BOREAS SSA-MSA, at a 30-m spatial resolution. Model runs were conducted over a 3-year period from 1994-1996; images are provided for each of those years. The data are stored in binary image format. The data files are available on a CD-ROM (see document number 20010000884), or from the Oak Ridge National Laboratory (ORNL) Distributed Active Archive Center (DAAC).

Hall, Forrest G.↗
NASA NTRS2003

The Livingstone Model of a Main Propulsion System

Livingstone is a discrete, propositional logic-based inference engine that has been used for diagnosis of physical systems. We present a component-based model of a Main Propulsion System (MPS) and say how it is used with Livingstone (L2) in order to implement a diagnostic system for integrated vehicle health management (IVHM) for the Propulsion IVHM Technology Experiment (PITEX). We start by discussing the process of conceptualizing such a model. We describe graphical tools that facilitated the generation of the model. The model is composed of components (which map onto physical components), connections between components and constraints. A component is specified by variables, with a set of discrete, qualitative values for each variable in its local nominal and failure modes. For each mode, the model specifies the component's behavior and transitions. We describe the MPS components' nominal and fault modes and associated Livingstone variables and data structures. Given this model, and observed external commands and observations from the system, Livingstone tracks the state of the MPS over discrete time-steps by choosing trajectories that are consistent with observations. We briefly discuss how the compiled model fits into the overall PITEX architecture. Finally we summarize our modeling experience, discuss advantages and disadvantages of our approach, and suggest enhancements to the modeling process.

Bajwa, Anupa↗
NASA NTRS2003

Global Lightning Activity

Our knowledge of the global distribution of lightning has improved dramatically since the 1995 launch of the Optical Transient Detector (OTD) followed in 1997 by the launch of the Lightning Imaging Sensor (LIS). Together, these instruments have generated a continuous seven-year record of global lightning activity. These lightning observations have provided a new global perspective on total lightning activity. For the first time, total lightning activity (CG and IC) has been observed over large regions with high detection efficiencies and accurate geographic location. This has produced new insights into lightning distributions, times of occurrence and variability. It has produced a revised global flash rate estimate (46 flashes per second) and has lead to a new realization of the significance of total lightning activity in severe weather. Accurate flash rate estimates are now available for large areas of the earth (+/- 72deg latitude) Ocean-land contrasts as a function of season are clearly revealed, as are orographic effects and seasonal and interannual variability. The data set indicates that air mass thunderstorms, not large storm systems dominate global activity. The ability of LIS and OTD to detect total lightning has lead to improved insight into the correlation between lightning and storm development. The relationship between updraft development and lightning activity is now well established and presents an opportunity for providing a new mechanism for remotely monitoring storm development. In this concept, lightning would serve as a surrogate for updraft velocity. It is anticipated hat this capability could lead to significantly improved severe weather warning times and reduced false warning rates.

Christian, Hugh↗
NASA NTRS2003

Polarization Evolution of the Afterglow of GRB 030329

The association of a supernova with GRB 030329l strongly supports the collapsar model of gamma-ray bursts (GRBs), where a relativistic jet forms after the progenitor star collapses. Such jets cannot be spatially resolved because of their cosmological distances. Their existence is conjectured based on breaks in GRB afterglow light curves and the theoretical desire to reduce the GRB energy requirements. Temporal evolution of polarization may provide independent evidence for the jet structure of the relativistic outflow. Small-level polarization (approx. 1-3%) has been reported for a few bursts, but the temporal evolution of polarization properties could not be established. Here, we report polarimetric observations of the afterglow of GRB 030329 with high signal-to-noise and high sampling frequency. We establish the polarization light curve, detect sustained polarization at the percent level, and find significant variability. The data imply that the afterglow magnetic field has small coherence length and is mostly random, probably generated by turbulence, in contrast with the high polarization detected in the prompt gamma-rays from GRB 02120618. Our results suggest a different structure and origin of the magnetic field in the prompt vs. afterglow emission regions.

Greiner, Jochen↗
NASA NTRS2004

Total Lightning Activity as Observed from Space

Our knowledge of the global distribution of lightning has improved dramatically since the 1995 launch of the Optical Transient Detector (OTD), followed in 1997 by the launch of the Lightning Imaging Sensor (LIS). Together, these instruments have generated a continuous seven-year record of global lightning activity. These lightning observations have provided a new global perspective on total lightning activity. For the first time, total lightning activity (CG and IC) has been observed over large regions with high detection efficiencies and accurate geographic location. This has produced new insights into lightning distributions, times of occurrence and variability. It has produced a revised global flash rate estimate (44 flashes per second) and has lead to a new realization of the significance of total ligh&g activity in severe weather. Accurate flash rate estimates are now available for areas of the earth (+/- 72 deg. latitude). Ocean-land contrasts as a function of season are clearly reveled, as are orographic effects and seasonal and interannual variability. The data set indicates that air mass thunderstorms, not large storm system dominate global activity. The ability of LIS and OTD to detect total lightning has lead to improved insight into the correlation between lightning and storm development. The relationship between updraft development and lightning activity is now well established and presents an opportunity for providing a new mechanism for remotely monitoring storm development. In this concept, lightning would serve as a surrogate for updraft velocity. It is anticipated that this capability could lead to significantly improved severe weather warning times and reduced false warning rates.

Christian, Hugh J.↗
NASA NTRS2004

Total Lightning Activity as Observed from Space

ABSTRACT: Our knowledge of the global distribution of lightning has improved dramatically since the 1995 launch of the Optical Transient Detector (OTD), followed in 1997 by the launch of the Lightning Imaging Sensor (LIS). Together, these instruments have generated a continuous seven-year record of global lightning activity. These lightning observations have provided a new global perspective on total lightning activity. For the first time, total lightning activity (CG and IC) has been observed over large regions with high detection efficiencies and accurate geographic location. This has produced new insights into lightning distributions, times of occurrence and variability. It has produced a revised global flash rate estimate (44 flashes per second) and has lead to a new realization of the significance of total ligh&g activity in severe weather. Accurate flash rate estimates are now available for areas of the earth (+/- 72 deg. latitude). Ocean-land contrasts as a function of season are clearly reveled, as are orographic effects and seasonal and interannual variability. The data set indicates that air mass thunderstorms, not large storm system dominate global activity. The ability of LIS and OTD to detect total lightning has lead to improved insight into the correlation between lightning and storm development. The relationship between updraft development and lightning activity is now well established and presents an opportunity for providing a new mechanism for remotely monitoring storm development. In this concept, lightning would serve as a surrogate for updraft velocity. It is anticipated that this capability could lead to significantly improved severe weather warning times and reduced false warning rates.

Christian, Hugh J.↗
NASA NTRS2005

Mechanical Impact Testing: A Statistical Measurement

In the decades since the 1950s, when NASA first developed mechanical impact testing of materials, researchers have continued efforts to gain a better understanding of the chemical, mechanical, and thermodynamic nature of the phenomenon. The impact mechanism is a real combustion ignition mechanism that needs understanding in the design of an oxygen system. The use of test data from this test method has been questioned due to lack of a clear method of application of the data and variability found between tests, material batches, and facilities. This effort explores a large database that has accumulated over a number of years and explores its overall nature. Moreover, testing was performed to determine the statistical nature of the test procedure to help establish sample size guidelines for material characterization. The current method of determining a pass/fail criterion based on either light emission or sound report or material charring is questioned.

Engel, Carl D.↗
NASA NTRS2007

The DaveMLTranslator: An Interface for DAVE-ML Aerodynamic Models

It can take weeks or months to incorporate a new aerodynamic model into a vehicle simulation and validate the performance of the model. The Dynamic Aerospace Vehicle Exchange Markup Language (DAVE-ML) has been proposed as a means to reduce the time required to accomplish this task by defining a standard format for typical components of a flight dynamic model. The purpose of this paper is to describe an object-oriented C++ implementation of a class that interfaces a vehicle subsystem model specified in DAVE-ML and a vehicle simulation. Using the DaveMLTranslator class, aerodynamic or other subsystem models can be automatically imported and verified at run-time, significantly reducing the elapsed time between receipt of a DAVE-ML model and its integration into a simulation environment. The translator performs variable initializations, data table lookups, and mathematical calculations for the aerodynamic build-up, and executes any embedded static check-cases for verification. The implementation is efficient, enabling real-time execution. Simple interface code for the model inputs and outputs is the only requirement to integrate the DaveMLTranslator as a vehicle aerodynamic model. The translator makes use of existing table-lookup utilities from the Langley Standard Real-Time Simulation in C++ (LaSRS++). The design and operation of the translator class is described and comparisons with existing, conventional, C++ aerodynamic models of the same vehicle are given.

Hill, Melissa A.↗
NASA NTRS2012

Using NASA Environmental Data to Enhance Public Health Decision Making

The Universities Space Research Association at the NASA Marshall Space Flight Center is collaborating with the University of Alabama at Birmingham (UAB) School of Public Health and the Centers for Disease Control and Prevention (CDC) to address issues of environmental health and enhance public health decision making by utilizing NASA remotely sensed data and products. The objectives of this collaboration are to develop high-quality spatial data sets of environmental variables, and deliver the data sets and associated analyses to local, state and federal end-user groups. These data can be linked spatially and temporally to public health data, such as mortality and disease morbidity, for further analysis and decision making. Three daily environmental data sets have been developed for the conterminous U.S. on different spatial resolutions for the time period 2003-2008: (1) spatial surfaces of estimated fine particulate matter (PM2.5) exposures on a 10-km grid utilizing the US Environmental Protection Agency (EPA) ground observations and NASA s MODerate-resolution Imaging Spectroradiometer (MODIS) data; (2) a 1-km grid of Land Surface Temperature (LST) using MODIS data; and (3) a 12-km grid of daily Solar Insolation (SI) and maximum and minimum air temperature using the North American Land Data Assimilation System (NLDAS) forcing data. These environmental data sets will be linked with public health data from the UAB REasons for Geographic And Racial Differences in Stroke (REGARDS) national cohort study to determine whether exposures to these environmental risk factors are related to cognitive decline and other health outcomes. These environmental datasets and public health linkage analyses will be made available to public health professionals, researchers and the general public through the CDC Wide-ranging Online Data for Epidemiologic Research (WONDER) system and through peer reviewed publications. To date, two of the data sets have been released to the public in CDC WONDER, Daily Air Temperature and Heat Index for years 1979-2010, and Daily Fine Particulate Matter (PM2.5) air quality measures for years 2003-2008. These data in CDC WONDER can be aggregated to the county-level, state-level, or regional-level as per users need and downloaded in tabular, graphical, and map formats. The summary statistical output are available to web and app developers via the WONDER Application Programming Interface (API). The linkage of these data with the CDC WONDER system provides a significant addition to CDC WONDER, allowing public health researchers and policy makers to better include environmental exposure data in the context of other health data available in CDC WONDER online system. It also substantially expands public access to NASA environmental data, making their use by a wide range of decision makers feasible.

Al-Hamdan, Mohammad↗
NASA NTRS2015

Climate-Induced Larch Growth Response Within the Central Siberian Permafrost Zone

Aim: estimation of larch (Larix gmelinii) growth response to current climate changes. Location: permafrost area within the northern part of Central Siberia (approximately 65.8 deg N, 98.5 deg E). Method: analysis of dendrochronological data, climate variables, drought index SPEI, GPP (gross primary production) and EVI vegetation index (both Aqua/MODIS satellite derived), and soil water content anomalies (GRACE satellite measurements of equivalent water thickness anomalies, EWTA). Results: larch tree ring width (TRW) correlated with previous year August precipitation (r = 0.63), snow accumulation (r = 0.61), soil water anomalies (r = 0.79), early summer temperatures and water vapor pressure (r = 0.73 and r = 0.69, respectively), May and June drought index (r = 0.68-0.82). There are significant positive trends of TRW since late 1980s and GPP since the year 2000. Mean TRW increased by about 50%, which is similar to post-Little Ice Age warming. TRW correlated with GPP and EVI of larch stands (r = 0.68-0.69). Main conclusions: within the permafrost zone of central Siberia larch TRW growth is limited by early summer temperatures, available water from snowmelt, water accumulated within soil in the previous year, and permafrost thaw water. Water stress is one of the limiting factors of larch growth. Larch TRW growth and GPP increased during recent decades.

permafrost thaw↗
NASA NTRS2015

Groundwater Storage Changes: Present Status from GRACE Observations

Satellite gravity measurements from the Gravity Recovery and Climate Experiment (GRACE) provide quantitative measurement of terrestrial water storage (TWS) changes with unprecedented accuracy. Combining GRACE-observed TWS changes and independent estimates of water change in soil and snow and surface reservoirs offers a means for estimating groundwater storage change. Since its launch in March 2002, GRACE time-variable gravity data have been successfully used to quantify long-term groundwater storage changes in different regions over the world, including northwest India, the High Plains Aquifer and the Central Valley in the USA, the North China Plain, Middle East, and southern Murray-Darling Basin in Australia, where groundwater storage has been significantly depleted in recent years (or decades). It is difficult to rely on in situ groundwater measurements for accurate quantification of large, regional-scale groundwater storage changes, especially at long timescales due to inadequate spatial and temporal coverage of in situ data and uncertainties in storage coefficients. The now nearly 13 years of GRACE gravity data provide a successful and unique complementary tool for monitoring and measuring groundwater changes on a global and regional basis. Despite the successful applications of GRACE in studying global groundwater storage change, there are still some major challenges limiting the application and interpretation of GRACE data. In this paper, we present an overview of GRACE applications in groundwater studies and discuss if and how the main challenges to using GRACE data can be addressed.

Australia↗
NASA NTRS1997

The Galileo Spacecraft: A Communications Legacy for Future Space Flight

The Galileo mission to Jupiter has implemented a wide range of telecommunication improvements in response to the loss of it's high gain antenna. Among the communications enhancements that have been made are the use of advanced compression techniques, packetized telemetry, new error correcting codes and algorithms, more efficient modulation, variable transmission data rates, routine ground antenna arraying (even between continents,) extremely sensitive ground receivers, and non-real-time automated data reconstruction. This telecommunications legacy of Galileo will aid in our abillity to conduct a meaningful exploration of the solar system, and beyond, at a reasonable cost.

Galileo↗
NASA NTRS2021

Revisiting the Global Patterns of Seasonal Cycle in Sea Surface Salinity

Argo profiling floats and L-band passive microwave remote sensing have significantly improved the global sampling of sea surface salinity (SSS) in the past 15 years, allowing the study of the range of SSS seasonal variability using concurrent satellite and in situ platforms. Here, harmonic analysis was applied to four 0.25° satellite products and two 1° in situ products between 2016 and 2018 to determine seasonal harmonic patterns. The 0.25° World Ocean Atlas (WOA) version 2018 was referenced to help assess the harmonic patterns from a long-term perspective based on the 3-year period. The results show that annual harmonic is the most characteristic signal of the seasonal cycle, and semiannual harmonic is important in regions influenced by monsoon and major rivers. The percentage of the observed variance that can be explained by harmonic modes varies with products, with values ranging between 50% and 72% for annual harmonic and between 15% and 19% for semiannual harmonic. The large spread in the explained variance by the annual harmonic reflects the large disparity in nonseasonal variance (or noise) in the different products. Satellite products are capable of capturing sharp SSS features on meso- and frontal scales and the patterns agree well with the WOA 2018. These products are, however, subject to the impacts of radiometric noises and are algorithm dependent. The coarser-resolution in situ products may underrepresent the full range of high-frequency small scale SSS variability when data record is short, which may have enlarged the explained SSS variance by the annual harmonic.

L-band↗
NASA NTRSDate not supplied

Improved Air Quality Forecasts using NASA’s Pandora and GEOS CF at International and Domestic Sites for SNWG Stakeholders

Air pollution prediction is complex due to the dynamic nature of atmospheric processes and the variability in data resolutions and availability. This project addresses these challenges by integrating and analyzing high-resolution ground-based measurements with global air quality models. Through this integration, we have gained a deeper understanding of how these processes interact under various conditions, which we then use to model and enhance the accuracy of forecasts.

Noussair Lazrak↗