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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 181 records · Page 10
All sourcesNASA NTRSDOE OSTI
NASA NTRS2015

Research-Based Monitoring, Prediction, and Analysis Tools of the Spacecraft Charging Environment for Spacecraft Users

The Space Weather Research Center (http://swrc. gsfc.nasa.gov) at NASA Goddard, part of the Community Coordinated Modeling Center (http://ccmc.gsfc.nasa.gov), is committed to providing research-based forecasts and notifications to address NASA's space weather needs, in addition to its critical role in space weather education. It provides a host of services including spacecraft anomaly resolution, historical impact analysis, real-time monitoring and forecasting, tailored space weather alerts and products, and weekly summaries and reports. In this paper, we focus on how (near) real-time data (both in space and on ground), in combination with modeling capabilities and an innovative dissemination system called the integrated Space Weather Analysis system (http://iswa.gsfc.nasa.gov), enable monitoring, analyzing, and predicting the spacecraft charging environment for spacecraft users. Relevant tools and resources are discussed.

space weather↗
NASA NTRS2013

Toward Global Drought Early Warning Capability - Expanding International Cooperation for the Development of a Framework for Monitoring and Forecasting

Drought has had a significant impact on civilization throughout history in terms of reductions in agricultural productivity, potable water supply, and economic activity, and in extreme cases this has led to famine. Every continent has semiarid areas, which are especially vulnerable to drought. The Intergovernmental Panel on Climate Change has noted that average annual river runoff and water availability are projected to decrease by 10 percent-13 percent over some dry and semiarid regions in mid and low latitudes, increasing the frequency, intensity, and duration of drought, along with its associated impacts. The sheer magnitude of the problem demands efforts to reduce vulnerability to drought by moving away from the reactive, crisis management approach of the past toward a more proactive, risk management approach that is centered on reducing vulnerability to drought as much as possible while providing early warning of evolving drought conditions and possible impacts. Many countries, unfortunately, do not have adequate resources to provide early warning, but require outside support to provide the necessary early warning information for risk management. Furthermore, in an interconnected world, the need for information on a global scale is crucial for understanding the prospect of declines in agricultural productivity and associated impacts on food prices, food security, and potential for civil conflict. This paper highlights the recent progress made toward a Global Drought Early Warning Monitoring Framework (GDEWF), an underlying partnership and framework, along with its Global Drought Early Warning System (GDEWS), which is its interoperable information system, and the organizations that have begun working together to make it a reality. The GDEWF aims to improve existing regional and national drought monitoring and forecasting capabilities by adding a global component, facilitating continental monitoring and forecasting (where lacking), and improving these tools at various scales, thereby increasing the capacity of national and regional institutions that lack drought early warning systems or complementing existing ones. A further goal is to improve coordination of information delivery for drought-related activities and relief efforts across the world. This is especially relevant for regions and nations with low capacity for drought early warning. To do this requires a global partnership that leverages the resources necessary and develops capabilities at the global level, such as global drought forecasting combined with early warning tools, global real-time monitoring, and harmonized methods to identify critical areas vulnerable to drought. Although the path to a fully functional GDEWS is challenging, multiple partners and organizations within the drought, forecasting, agricultural, and water-cycle communities are committed to working toward its success.

GDEWS↗
NASA NTRS2014

Impacts of Light Use Efficiency and fPAR Parameterization on Gross Primary Production Modeling

This study examines the impact of parameterization of two variables, light use efficiency (LUE) and the fraction of absorbed photosynthetically active radiation (fPAR or fAPAR), on gross primary production(GPP) modeling. Carbon sequestration by terrestrial plants is a key factor to a comprehensive under-standing of the carbon budget at global scale. In this context, accurate measurements and estimates of GPP will allow us to achieve improved carbon monitoring and to quantitatively assess impacts from cli-mate changes and human activities. Spaceborne remote sensing observations can provide a variety of land surface parameterizations for modeling photosynthetic activities at various spatial and temporal scales. This study utilizes a simple GPP model based on LUE concept and different land surface parameterizations to evaluate the model and monitor GPP. Two maize-soybean rotation fields in Nebraska, USA and the Bartlett Experimental Forest in New Hampshire, USA were selected for study. Tower-based eddy-covariance carbon exchange and PAR measurements were collected from the FLUXNET Synthesis Dataset. For the model parameterization, we utilized different values of LUE and the fPAR derived from various algorithms. We adapted the approach and parameters from the MODIS MOD17 Biome Properties Look-Up Table (BPLUT) to derive LUE. We also used a site-specific analytic approach with tower-based Net Ecosystem Exchange (NEE) and PAR to estimate maximum potential LUE (LUEmax) to derive LUE. For the fPAR parameter, the MODIS MOD15A2 fPAR product was used. We also utilized fAPAR chl, a parameter accounting for the fAPAR linked to the chlorophyll-containing canopy fraction. fAPAR chl was obtained by inversion of a radiative transfer model, which used the MODIS-based reflectances in bands 1-7 produced by Multi-Angle Implementation of Atmospheric Correction (MAIAC) algorithm. fAPAR chl exhibited seasonal dynamics more similar with the flux tower based GPP than MOD15A2 fPAR, especially in the spring and fall at the agricultural sites. When using the MODIS MOD17-based parameters to estimate LUE, fAPAR chl generated better agreements with GPP (r2= 0.79-0.91) than MOD15A2 fPAR (r2= 0.57-0.84).However, underestimations of GPP were also observed, especially for the crop fields. When applying the site-specific LUE max value to estimate in situ LUE, the magnitude of estimated GPP was closer to in situ GPP; this method produced a slight overestimation for the MOD15A2 fPAR at the Bartlett forest. This study highlights the importance of accurate land surface parameterizations to achieve reliable carbon monitoring capabilities from remote sensing information.

grossprimary↗
NASA NTRS2021

Advances in Land Surface Models and Indicators for Drought Monitoring and Prediction

Millions of people across the globe are affected by droughts every year, and recent droughts have highlighted the considerable agricultural impacts and economic costs of these events. Monitoring the state of droughts depends on integrating multiple indicators that each capture particular aspects of hydrologic impact and various types and phases of drought. As the capabilities of land surface models and remote sensing have improved, important physical processes such as dynamic, interactive vegetation phenology, groundwater, and snowpack evolution now support a range of drought indicators that better reflect coupled water, energy, and carbon cycle processes. In this work, we discuss these advances, including newer classes of indicators that can be applied to improve the characterization of drought onset, severity, and duration. We utilize a new model-based drought reconstruction to illustrate the role of dynamic phenology and groundwater in drought assessment. Further, through case studies on flash droughts, snow droughts, and drought recovery, we illustrate the potential advantages of advanced model physics and observational capabilities, especially from remote sensing, in characterizing droughts.

Christa D Peters-lidard↗
NASA NTRS2021

Advances in Land Surface Models and Indicators for Drought Monitoring and Prediction

Millions of people across the globe are affected by droughts every year, and recent droughts have highlighted the considerable agricultural impacts and economic costs of these events. Monitoring the state of droughts depends on integrating multiple indicators that each capture particular aspects of hydrologic impact and various types and phases of drought. As the capabilities of land-surface models and remote sensing have improved, important physical processes such as dynamic, interactive vegetation phenology, groundwater, and snow pack evolution now support a range of drought indicators that better reflect coupled water, energy and carbon cycle processes. In this work, we discuss these advances, including newer classes of indicators that can be applied to improve the characterization of drought onset, severity and duration. We utilize a new model-based drought reconstruction to illustrate the role of dynamic phenology and groundwater in drought assessment. Further, through case studies on flash droughts, snow droughts, and drought recovery, we illustrate the potential advantages of advanced model physics and observational capabilities, especially from remote sensing, in characterizing droughts.

Drought↗
NASA NTRSDate not supplied

Advances in Land Surface Models and Indicators for Drought Monitoring and Prediction

Millions of people across the globe are affected by droughts every year, and recent droughts have highlighted the considerable agricultural impacts and economic costs of these events. Monitoring the state of droughts depends on integrating multiple indicators that each capture particular aspects of hydrologic impact and various types and phases of drought. As the capabilities of land surface models and remote sensing have improved, important physical processes such as dynamic, interactive vegetation phenology, groundwater, and snowpack evolution now support a range of drought indicators that better reflect coupled water, energy, and carbon cycle processes. In this work, we discuss these advances, including newer classes of indicators that can be applied to improve the characterization of drought onset, severity, and duration. We utilize a new model-based drought reconstruction to illustrate the role of dynamic phenology and groundwater in drought assessment. Further, through case studies on flash droughts, snow droughts, and drought recovery, we illustrate the potential advantages of advanced model physics and observational capabilities, especially from remote sensing, in characterizing droughts.

Christa D Peters-lidard↗
NASA NTRS2021

Vegetation Monitoring Optimization with Normalized Difference Vegetation Index and Evapotranspiration Using Remote Sensing Measurements and Land Surface Models Over East Africa

The majority of people in East Africa rely on the agro-pastoral system for their livelihood, which is highly vulnerable to droughts and flooding. Agro-pastoral droughts are endemic to the region and are considered the main natural hazard that contributes to food insecurity. Drought begins with rainfall deficit, gradually leading to soil moisture deficit, higher land surface temperature, and finally impacts to vegetation growth. Therefore, monitoring vegetation conditions is essential in understanding the progression of drought, potential effects on food security, and providing early warning information needed for drought mitigation decisions. Because vegetation processes couple the land and atmosphere, monitoring of vegetation conditions requires consideration of both water provision and demand. While there is consensus in using either the Normalized Difference Vegetation Index (NDVI) or evapotranspiration(ET) for vegetation monitoring, a comprehensive assessment optimizing the use of both has not yet been done. Moreover, the evaluation methods for understanding the relationships between NDVI and ET for vegetation monitoring are also limited. Taking these gaps into account we have developed a framework to optimize vegetation monitoring using both NDVI and ET by identifying where they perform the best by using triple collocation and cross-correlation methods. We estimated the random error structure in Moderate Resolution Imaging Spectroradiometer (MODIS) NDVI; ET from the Operational Simplified Surface Energy Balance (SSEBop) model; and ET from land surface models (LSMs). LSM ET and SSEBop ET have been found to be better indicators for vegetation monitoring during extreme drought events, while NDVI could provide better information on vegetation condition during wetter than normal conditions. The random error structures of these variables suggest that LSM ET is most likely to provide important information for vegetation monitoring over low and high ends of the vegetation fraction areas. Over moderate vegetative areas, any of these variables could provide important vegetation information for drought characterization and food security assessments. While this study provides a framework for optimizing vegetation monitoring for drought and food security assessments over East Africa, the framework can be adopted to optimize vegetation monitoring over any other drought and food insecure region of the world.

triple collocation↗
NASA NTRS1974

Application of ERTS imagery in estimating the environmental impact of a freeway through the Knysna area of South Africa

In the coastal areas north-east and south-west of Knysna, South Africa lie natural forests, lakes and lagoons highly regarded by many for their aesthetic and ecological richness. A freeway construction project has given rise to fears of the degradation or destruction of these natural features. The possibility was investigated of using ERTS imagery to estimate the environmental impact of the freeway and found that: (1) All threatened features could readily be identified on the imagery. (2) It was possible within a short time to provide an area estimate of damage to indigenous forest. (3) In several important respects the imagery has advantages over maps and aerial photos for this type of work. (4) The imagery will enable monitoring of the actual environmental impact of the freeway when completed.

Williamson, D. T.↗
NASA NTRSDate not supplied

Culture-Independent Microbial Air Profiling using a Spaceflight-Compatible Nanopore Sequencing Method

Microbial monitoring of spacecraft air is critical toward assessing the efficacy of microbial controls within the environmental control and life support systems to protect the crew and vehicle environment. Currently, onboard the International Space Station (ISS), the air is monitored every quarter using an impaction air sampler. With this method, microbial cells and spores are pulled onto plates containing a growth medium. Following onboard incubation, the crew reports approximate microbial levels to the ground, but sample return is required for identification. Upon return of the plates, the isolates present are identified for crew health risk assessments. As NASA moves beyond low-Earth orbit, sample return will be impractical, and a near real-time monitoring capability is essential. Significant strides have been made in recent years to utilize a molecular-based method for microbial profiling of ISS surfaces. The developed method is independent of microbial culture, thus removing the bias toward detecting only culturable organisms, eliminating the need for sample return, and reducing the risk to crew health from exposure to high microbial levels. The work described here details the evaluation of three different air sampling platforms whose product is amenable to downstream molecular processing. The three samplers were compared in terms of mass and power requirements, ease of use, and the resulting data. For the two highest-ranking samplers, a basic concept of operations was developed to transfer the sample into the already established preparation and sequencing process. Using these concepts of operations, an in-depth comparison of the molecular data generated was compared to the historical culture-based method. Data from both methods detailed similar microbial profiles, while the molecular method detailed microbial identifications that were lacking from the culture data. The developed method will enable the generation of near real-time microbial profiles of the spacecraft atmosphere.

Brandon Dunbar↗
NASA NTRS2010

Spectral Indices to Monitor Nitrogen-Driven Carbon Uptake in Field Corn

Climate change is heavily impacted by changing vegetation cover and productivity with large scale monitoring of vegetation only possible with remote sensing techniques. The goal of this effort was to evaluate existing reflectance (R) spectroscopic methods for determining vegetation parameters related to photosynthetic function and carbon (C) dynamics in plants. Since nitrogen (N) is a key constituent of photosynthetic pigments and C fixing enzymes, biological C sequestration is regulated in part by N availability. Spectral R information was obtained from field corn grown at four N application rates (0, 70, 140, 280 kg N/ha). A hierarchy of spectral observations were obtained: leaf and canopy with a spectral radiometer; aircraft with the AISA sensor; and satellite with EO-1 Hyperion. A number of spectral R indices were calculated from these hyperspectral observations and compared to geo-located biophysical measures of plant growth and physiological condition. Top performing indices included the R derivative index D730/D705 and the normalized difference of R750 vs. R705 (ND705), both of which differentiated three of the four N fertilization rates at multiple observation levels and yielded high correlations to these carbon parameters: light use efficiency (LUE); C:N ratio; and crop grain yield. These results advocate the use of hyperspectral sensors for remotely monitoring carbon cycle dynamics in managed terrestrial ecosystems.

Corp, Lawrence A.↗
NASA NTRS1991

Considerations for human-machine interfaces in tele-operations

Numerous factors impact on the efficiency of tele-operative manipulative work. Generally, these are related to the physical environment of the tele-operator and how he interfaces with robotic control consoles. The capabilities of the operator can be influenced by considerations such as temperature, eye strain, body fatigue, and boredom created by repetitive work tasks. In addition, the successful combination of man and machine will, in part, be determined by the configuration of the visual and physical interfaces available to the teleoperator. The design and operation of system components such as full-scale and mini-master manipulator controllers, servo joysticks, and video monitors will have a direct impact on operational efficiency. As a result, the local environment and the interaction of the operator with the robotic control console have a substantial effect on mission productivity.

Newport, Curt↗
NASA NTRS2016

Assessing Impact of Dual Sensor Enhanced Flight Vision Systems on Departure Performance

Synthetic Vision (SV) and Enhanced Flight Vision Systems (EFVS) may serve as game-changing technologies to meet the challenges of the Next Generation Air Transportation System and the envisioned Equivalent Visual Operations (EVO) concept - that is, the ability to achieve the safety and operational tempos of current-day Visual Flight Rules operations irrespective of the weather and visibility conditions. One significant obstacle lies in the definition of required equipage on the aircraft and on the airport to enable the EVO concept objective. A motion-base simulator experiment was conducted to evaluate the operational feasibility and pilot workload of conducting departures and approaches on runways without centerline lighting in visibility as low as 300 feet runway visual range (RVR) by use of onboard vision system technologies on a Head-Up Display (HUD) without need or reliance on natural vision. Twelve crews evaluated two methods of combining dual sensor (millimeter wave radar and forward looking infrared) EFVS imagery on pilot-flying and pilot-monitoring HUDs. In addition, the impact of adding SV to the dual sensor EFVS imagery on crew flight performance and workload was assessed. Using EFVS concepts during 300 RVR terminal operations on runways without centerline lighting appears feasible as all EFVS concepts had equivalent (or better) departure performance and landing rollout performance, without any workload penalty, than those flown with a conventional HUD to runways having centerline lighting. Adding SV imagery to EFVS concepts provided situation awareness improvements but no discernible improvements in flight path maintenance.

Kramer, Lynda J.↗
NASA NTRS2017

Characterizing Agricultural Impacts of Recent Large-Scale US Droughts and Changing Technology and Management

Process-based agricultural models, applied in novel ways, can reproduce historical crop yield anomalies in the US, with median absolute deviation from observations of 6.7% at national-level and 11% at state-level. In seasons for which drought is the overriding factor, performance is further improved. Historical counterfactual scenarios for the 1988 and 2012 droughts show that changes in agricultural technologies and management have reduced system-level drought sensitivity in US maize production by about 25% in the intervening years. Finally, we estimate the economic costs of the two droughts in terms of insured and uninsured crop losses in each US county (for a total, adjusted for inflation, of $9 billion in 1988 and $21.6 billion in 2012). We compare these with cost estimates from the counterfactual scenarios and with crop indemnity data where available. Model based measures are capable of accurately reproducing the direct agro-economic losses associated with extreme drought and can be used to characterize and compare events that occurred under very different conditions. This work suggests new approaches to modeling, monitoring, forecasting, and evaluating drought impacts on agriculture, as well as evaluating technological changes to inform adaptation strategies for future climate change and extreme events.

Climate extremes; Drought impacts; Agriculture; Se↗
NASA NTRS1972

Determination of impact sensitivity of materials at high pressures

Compact device is used to determine impact sensitivity of material in static, high pressure, gaseous environment. It can also be instrumented to monitor and record pressure, temperature, and striker impact force. Device is used in conjunction with commercially available liquid oxygen impact tester which provides impact energy.

Davis, L.↗
NASA NTRS1990

Trends and individual differences in response to short-haul flight operations

A survey of airline pilots was undertaken to determine normative patterns and individual differences in mood and sleep during short-haul flight operations. The results revealed that over the course of a typical 2-d trip, pilots experience a decline in positive mood, or activity, and an increase in negative mood, or tension. On layovers, pilots report experiencing sleep of shorter duration and poorer quality than at home. These patterns are very similar to those reported by Gander and Graeber (1987) and by Gander et al. (1988), using high-fidelity sleep and activity monitoring equipment. Examination of the impact of two personality dimensions extracted from the Jenkins Activity Survey measure of the Type A personality, Achievement Striving and Impatience/Irritability, suggested that Impatience/Irritability may serve as a marker of individuals most likely to experience health-related problems on trips. Achievement Striving may serve as a predictor of performance in crew settings.

Chidester, Thomas R.↗
NASA NTRS1990

Trends and individual differences in response to short-haul fight operations

A survey of airline pilots was undertaken to determine normative patterns and individual differences in mood and sleep during short-haul flight operations. The results revealed that over the course of a typical 2-d trip, pilots experience a decline in positive mood, or activity, and an increase in negative mood, or tension. On layovers, pilots report experiencing sleep of shorter duration and poorer quality than at home. These patterns are very similar to those reported by Gander and Graeber and by Gander et al. using high-fidelity sleep and activity monitoring equipment. Examination of the impact of two personality dimensions extracted from the Jenkins Activity Survey measure of the Type A personality, Achievement Striving and Impatience/Irritability, suggested that Impatience/Irritability may serve as a marker of individuals most likely to experience health-related problems on trips. Achievement Striving may serve as a predictor of performance in crew settings.

Aircraft↗
NASA NTRS2005

BEAM Technology Flight Demonstration

As technologies advance, their growing complexity makes them harder to maintain. Detection methods for isolating and identifying impending problems are needed to balance this complexity. Through comparison of signal pairs from onboard sensors, the Beacon-based Exception Analysis For Multimissions (BEAM) algorithm can identify and help classify deviations in system operation from a data-trained statistical model. The goal of this task is to mature BEAM and validate its performance on a flying test bed. A series of F-18 flight demonstrations with BEAM monitoring engine parameters in real time was used to demonstrate in-the-field readiness. Captured F-18 and simulated F-18 engine data were used in model creation and training. The algorithm was then ported to the embedded system with a data buffering, file writing, and data-time-stamp monitoring shell to reduce the impact of embedded system faults on BEAM'S ability to correctly identify engine faults. Embedded system testing identified hardware related restrictions and contributed to iterative improvements in the code's runtime performance. The system was flown with forced engine flameouts and other pilot induced faults to simulate operation out of the norm. Successful detection of these faults, confirmed through post-flight data analysis, helped BEAM achieve TRL6.

Wang, David↗
NASA NTRS1994

(abstract) Atmospheric Transmission Model Through Autonomous Visibility Measurement

Performance of deep space optical communications is impacted by atmospheric outages. By monitoring known stellar objects with calibrated telescopes, atmospheric attenuation statistics can be recorded. This paper describes a program to develop an atmospheric transmission model for optical communications by making automous visibility measurements of known stellar objects from three locations in the southwestern US. The data will be correlated and infused with weather data to establish the atmospheric transmission model. This model will be sent in link margin analysis for optical communications channels. The statistics will be updated on a quarterly basis and calibrated using data taken over a long period of time. This calibration is expected to allow extrapolation to other ground-based locations through use of global weather databases.

attenuation model↗