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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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NASA NTRSDate not supplied

Using Earth Observations to Analyze Vegetation Phenology and Climatology in Bhutan to Identify Forest Disturbance

Changes in climate in the Himalayan region cause variability in temperature, precipitation, and phenology. It can also impact the health of coniferous forest ecosystems including increased damage due to aggressive forest pests. Forest disturbance from bark beetle is a major concern in Bhutan, sometimes causing extensive tree mortality to pine and spruce forests. Climatological trends and changes in vegetation phenology were analyzed and incorporated into a tool in Google Earth Engine that identified patches of forest disturbance in Bhutan. Preprocessed phenology and meteorological data from the Advanced Very High-Resolution Radiometer (AVHRR) and Terra and Aqua Moderate Resolution Imaging Spectroradiometer (MODIS), along with Climate Hazards Center Infrared Precipitation with Station (CHIRPS), Famine Early Warning System Network Land Data Assimilation System (FLDAS), Sentinel-2 Multispectral Instrument (MSI), and Landsat 5 Thematic Mapper (TM), Landsat 7 Enhanced Thematic Mapper (ETM)+, and Landsat 8 Operational Land Imager (OLI) were used within the tool. Changes in temperature, precipitation, and phenology were analyzed throughout Bhutan, and forest disturbance caused by bark beetle was investigated in two districts of the country

Tashi Choden↗
NASA NTRS2023

Considering Soil Moisture in Models of Climate Impacts on Child Health in Farming-Centric Countries

Soil moisture reflects the amount of water available to crops in the top layer of soil. As such, considering soil moisture provides important insight into water availability and ultimately crop yields in agricultural settings. In studies of climate change, food security, and health, however, soil moisture is rarely empirically considered despite its connection to crop health and yields. In this project, we aim to advance understanding of climate impacts on food security by incorporating soil moisture into quantitative models of child health. Combining spatially referenced health survey data from the Demographic and Health Surveys for 2005 and 2010 in Senegal and 2007, 2011, and 2014 in Bangladesh, with soil moisture data from the Famine Early Warning System Network Land Data Assimilation System, we explore the linkages between sub-annual and sub-seasonal climate conditions and child malnutrition in two rainfed agriculture dependent countries—Bangladesh and Senegal. Results suggest that soil moisture, measured on very short time scales, may be associated with reductions in anthropometric weight-for-height z-scores, but the relationship is highly dependent upon geographic context.

Child health↗
NASA NTRS2016

Towards Autonomous Aviation Operations: What Can We Learn from Other Areas of Automation?

Rapid advances in automation has disrupted and transformed several industries in the past 25 years. Automation has evolved from regulation and control of simple systems like controlling the temperature in a room to the autonomous control of complex systems involving network of systems. The reason for automation varies from industry to industry depending on the complexity and benefits resulting from increased levels of automation. Automation may be needed to either reduce costs or deal with hazardous environment or make real-time decisions without the availability of humans. Space autonomy, Internet, robotic vehicles, intelligent systems, wireless networks and power systems provide successful examples of various levels of automation. NASA is conducting research in autonomy and developing plans to increase the levels of automation in aviation operations. This paper provides a brief review of levels of automation, previous efforts to increase levels of automation in aviation operations and current level of automation in the various tasks involved in aviation operations. It develops a methodology to assess the research and development in modeling, sensing and actuation needed to advance the level of automation and the benefits associated with higher levels of automation. Section II describes provides an overview of automation and previous attempts at automation in aviation. Section III provides the role of automation and lessons learned in Space Autonomy. Section IV describes the success of automation in Intelligent Transportation Systems. Section V provides a comparison between the development of automation in other areas and the needs of aviation. Section VI provides an approach to achieve increased automation in aviation operations based on the progress in other areas. The final paper will provide a detailed analysis of the benefits of increased automation for the Traffic Flow Management (TFM) function in aviation operations.

Sridhar, Banavar↗
NASA NTRS1981

The DSN VLBI system Mark 4-85

The DSN VLBI System was established as a network system in 1978. The evolution of the VLBI System from Mark 1-79 to Mark 4-85 is described, and the system functional requirements for Mark 4-85 are discussed.

Chaney, W. D.↗
NASA NTRS1991

A cost-effective intelligent robotic system with dual-arm dexterous coordination and real-time vision

Dexterous coordination of manipulators based on the use of redundant degrees of freedom, multiple sensors, and built-in robot intelligence represents a critical breakthrough in development of advanced manufacturing technology. A cost-effective approach for achieving this new generation of robotics has been made possible by the unprecedented growth of the latest microcomputer and network systems. The resulting flexible automation offers the opportunity to improve the product quality, increase the reliability of the manufacturing process, and augment the production procedures for optimizing the utilization of the robotic system. Moreover, the Advanced Robotic System (ARS) is modular in design and can be upgraded by closely following technological advancements as they occur in various fields. This approach to manufacturing automation enhances the financial justification and ensures the long-term profitability and most efficient implementation of robotic technology. The new system also addresses a broad spectrum of manufacturing demand and has the potential to address both complex jobs as well as highly labor-intensive tasks. The ARS prototype employs the decomposed optimization technique in spatial planning. This technique is implemented to the framework of the sensor-actuator network to establish the general-purpose geometric reasoning system. The development computer system is a multiple microcomputer network system, which provides the architecture for executing the modular network computing algorithms. The knowledge-based approach used in both the robot vision subsystem and the manipulation control subsystems results in the real-time image processing vision-based capability. The vision-based task environment analysis capability and the responsive motion capability are under the command of the local intelligence centers. An array of ultrasonic, proximity, and optoelectronic sensors is used for path planning. The ARS currently has 18 degrees of freedom made up by two articulated arms, one movable robot head, and two charged coupled device (CCD) cameras for producing the stereoscopic views, and articulated cylindrical-type lower body, and an optional mobile base. A functional prototype is demonstrated.

Marzwell, Neville I.↗
NASA NTRS1991

Neural networks for aircraft system identification

Artificial neural networks offer some interesting possibilities for use in control. Our current research is on the use of neural networks on an aircraft model. The model can then be used in a nonlinear control scheme. The effectiveness of network training is demonstrated.

Linse, Dennis J.↗
NASA NTRS1982

Short-Circuited Power Networks

NASA computer program automatically analyzes power-system networks under faulted conditions. Program is general enough to calculate single-line to ground faults and three-phase-to-ground faults. Several novel programing techniques automate analysis while reducing computing time and storage requirements. Program is written in FORTRAN IV for batch execution.

Oepomo, T. S.↗
NASA NTRS1991

Real-time expert system and neural network for the classification of remotely sensed data

The paper examines software techniques for classifying remotely sensed data such that the number of computational steps and the amount of resources are bounded. The combination of both neural network and expert system methodology for classifying these data based on land use/land cover categories is examined. The method involves pipelining images through a neural net for initial classification and then through the expert system which resolves the ambiguous classifications. As with any pipeline, every component must have approximately equivalent run-times or otherwise a bottleneck will occur. If real-time is a requirement, each of the components must execute within a bounded number of steps. Attention is focused on the real-time system technique, which is argued to prevent a bottleneck for this data classification application.

Short, Nicholas, Jr.↗
NASA NTRS2009

IEEE 1394 Hub With Fault Containment

This innovation is designed to prevent a single end system communication node from negatively influencing the whole system s behavior so that the network system can still operate if an end node is faulty. Placing a hub (star) in the middle of the system prevents propagation of critical control information that other end systems would react to, like block reset messages.

Paulitsch, Michael↗
NASA NTRS2017

Data Descriptor: A Land Data Assimilation System for Sub-Saharan Africa Food and Water Security Applications

Seasonal agricultural drought monitoring systems, which rely on satellite remote sensing and land surface models (LSMs), are important for disaster risk reduction and famine early warning. These systems require the best available weather inputs, as well as a long-term historical record to contextualize current observations. This article introduces the Famine Early Warning Systems Network (FEWS NET) Land Data Assimilation System (FLDAS), a custom instance of the NASA Land Information System (LIS) framework. The FLDAS is routinely used to produce multi-model and multi-forcing estimates of hydro-climate states and fluxes over semi-arid, food insecure regions of Africa. These modeled data and derived products, like soil moisture percentiles and water availability, were designed and are currently used to complement FEWSNETs operational remotely sensed rainfall, evapotranspiration, and vegetation observations. The 30+ years of monthly outputs from the FLDAS simulations are publicly available from the NASA Goddard Earth Science Data and Information Services Center (GES DISC) and recommended for use in hydroclimate studies, early warning applications, and by agro-meteorological scientists in Eastern, Southern, and Western Africa.

albedo↗
NASA NTRS2017

Upper Blue Nile Basin Water Budget from a Multi-Model Perspective

Improved understanding of the water balance in the Blue Nile is of critical importance because of increasingly frequent hydroclimatic extremes under a changing climate. The intercomparison and evaluation of multiple land surface models (LSMs) associated with different meteorological forcing and precipitation datasets can offer a moderate range of water budget variable estimates. In this context, two LSMs, Noah version 3.3 (Noah3.3) and Catchment LSM version Fortuna 2.5 (CLSMF2.5) coupled with the Hydrological Modeling and Analysis Platform (HyMAP) river routing scheme are used to produce hydrological estimates over the region. The two LSMs were forced with different combinations of two reanalysis-based meteorological datasets from the Modern-Era Retrospective analysis for Research and Applications datasets (i.e., MERRA-Land and MERRA-2) and three observation-based precipitation datasets, generating a total of 16 experiments. Modeled evapotranspiration (ET), streamflow, and terrestrial water storage estimates were evaluated against the Atmosphere-Land Exchange Inverse (ALEXI) ET, in-situ streamflow observations, and NASA Gravity Recovery and Climate Experiment (GRACE) products, respectively. Results show that CLSMF2.5 provided better representation of the water budget variables than Noah3.3 in terms of Nash-Sutcliffe coefficient when considering all meteorological forcing datasets and precipitation datasets. The model experiments forced with observation-based products, the Climate Hazards group Infrared Precipitation with Stations (CHIRPS) and the Tropical Rainfall Measuring Mission (TRMM) Multi-Satellite Precipitation Analysis (TMPA), outperform those run with MERRA-Land and MERRA-2 precipitation. The results presented in this paper would suggest that the Famine Early Warning Systems Network (FEWS NET) Land Data Assimilation System incorporate CLSMF2.5 and HyMAP routing scheme to better represent the water balance in this region.

Rainfall↗
NASA NTRS2020

Towards a Soil Moisture Drought Monitoring System for South Korea

The Korea Land Data Assimilation System (KLDAS) has been established for agricultural drought (i.e. soil moisture deficit) monitoring in South Korea, running the Noah-MP land surface model within the NASA Land Information System (LIS) framework with the added value of local precipitation forcing dataset and soil texture maps. KLDAS soil moisture is benchmarked against three global products: the Global Land Data Assimilation System (GLDAS), the Famine Early Warning Systems Network (FEWS NET) Land Data Assimilation System (FLDAS), and the European Space Agency Climate Change Initiative (ESA CCI) satellite product. The evaluation is performed using in situ measurements for 2013–2015 and one month standardized precipitation index (SPI-1) for 1982–2016, focusing on four major river basins in South Korea. The KLDAS outperforms all benchmark products in capturing soil moisture states and variability at a basin scale. Compared to GLDAS and FLDAS products, the EAS CCI product is not feasible for long term agricultural monitoring due to lower data quality for early periods (1979–1991) of soil moisture estimates. KLDAS shows that the most recent 2015 drought event leads to highest drought areas in the Han and Geum River basins in the past 35 years. This work supports KLDAS as an effective agricultural drought monitoring system to provide continuous regional high-resolution soil moisture estimates in South Korea.

Agricultural drought↗
NASA NTRS2022

A Central Asia Hydrologic Monitoring Dataset for Food and Water Security Applications in Afghanistan

From the Hindu Kush mountains to the Registan Desert, Afghanistan is a diverse landscape where droughts, floods, conflict, and economic market accessibility pose challenges for agricultural livelihoods and food security. The ability to remotely monitor environmental conditions is critical to support decision making for humanitarian assistance. The Famine Early Warning Systems Network (FEWS NET) Land Data Assimilation System (FLDAS) global and Central Asia data streams provide information on hydrologic states for routine integrated food security analysis. While developed for a specific project, these data are publicly available and useful for other applications that require hydrologic estimates of the water and energy balance. These two data streams are unique because of their suitability for routine monitoring, as well as for being a historical record for computing relative indicators of water availability. The global stream is available at ∼ 1-month latency, and monthly average outputs are on a 10 km grid from 1982–present. The second data stream, Central Asia (21–56°N, 30–100°E), at ∼ 1 d latency, provides daily average outputs on a 1 km grid from 2000–present. This paper describes the configuration of the two FLDAS data streams, background on the software modeling framework, selected meteorological inputs and parameters, and results from previous evaluation studies. We also provide additional analysis of precipitation and snow cover over Afghanistan. We conclude with an example of how these data are used in integrated food security analysis. For use in new and innovative studies that will improve understanding of this region, these data are hosted by U.S. Geological Survey data portals and the National Aeronautics and Space Administration (NASA). The Central Asia data described in this paper can be accessed via the NASA repository at https://doi.org/10.5067/VQ4CD3Y9YC0R (Jacob and Slinski, 2021), and the global data described in this paper can be accessed via the NASA repository at https://doi.org/10.5067/5NHC22T9375G (McNally, 2018).

Amy McNally↗
NASA NTRSDate not supplied

An Update on the Hydrological Land Surface Data and Services at NASA GES DISC

"The NASA Goddard Earth Sciences Data and Information Services Center (GES DISC) is one of twelve NASA Earth Observing System data centers that document, process, archive and distribute data from Earth science missions and related projects. The GES DISC hosts many hydrological land surface data products including North American Land Data Assimilation System (NLDAS), Global Land Data Assimilation System (GLDAS), the Famine Early Warning Systems Network (FEWS NET) Land Data Assimilation System (FLDAS), and assimilated-Gravity Recovery and Climate Experiment (GRACE). The Land Surface Model (LSM) products contain model output, including heat fluxes, rain, snow, soil temperature, soil moisture and runoff; and observational forcing data, including surface pressure, temperature, precipitation, downward shortwave and longwave radiation, humidity, and wind. The temporal resolution of the hydrology data at the GES DISC ranges from hourly to monthly and the spatial resolution 0.1 degree to 1.0 degree. The variability of Earth’s water and energy cycles can be characterized with these spatially and temporally consistent, and quality controlled hydrological land surface data. These data could support ongoing modeling activities, and help improve our understanding of land-surface-atmosphere interactions and their impact on climate. Over the years, new data is added, and older data is reprocessed and updated. This presentation provides a summary table of the hydrological data and discusses recent updates to the data and data services at the GES DISC. New data products include (1) GRACE Global Version 3.0 drought indicators and (2) FLDAS monthly global and Central Asia daily data. Reprocessed and updated products include (1) NLDAS Version 2.0 and (2) GRACE United States Version 4.0 drought indicators. Lastly, this presentation will discuss the opportunities for accessing some of our hydrology data from the cloud. As the hydrology land surface data is moved to the cloud, users can expect faster service for longer time series, notably the hydrology data rods time series service."

Ashley Heath↗
NASA NTRS1994

The network data delivery service: A real-time data connectivity system

A network data-sharing system, the Network Data Delivery Service (NDDS), is discussed. The NDDS system relies on a bipartite model consisting of the following: information producers (sources) and information consumers (sinks). The example provided by a dual-arm robotic system is examined.

Pardo-Castellote, Gerardo↗
NASA NTRS1981

The NASA Tracking and Data Relay Satellite System and its impact on spacecraft support in the space transportation system era

The space tracking, data acquisition and communication network systems and capabilities available to NASA are discussed, with emphasis on the Tracking and Data Relay Satellite System (TDRSS). Scheduled to come into operation in 1983, TDRSS will be the prime support system for communication with the Space Shuttle, Spacelab, and the automated spacecraft to be launched into earth orbit by the Space Transportation System. TDRSS will consist of two specialized data relay satellites in geosynchronous orbit, about 130 deg apart; each TDRSS spacecraft has a three-axis stabilized configuration, with sun-oriented solar panels, and will weigh about 2200 kg at launch. The NASA Spaceflight Tracking and Data Network, currently used to support 30-40 spacecraft per day, is described, and plans for changes in the network are discussed. The 26 antennas of the network will be consolidated into an expanded Deep Space Network, after TDRSS is in operation.

Smylie, R. E.↗