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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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All sourcesNASA NTRSDOE OSTI
NASA NTRS2008

Documenting AUTOGEN and APGEN Model Files

A computer program called "autogen hypertext map generator" satisfies a need for documenting and assisting in visualization of, and navigation through, model files used in the AUTOGEN and APGEN software mentioned in the two immediately preceding articles. This program parses autogen script files, autogen model files, PERL scripts, and apgen activity-definition files and produces a hypertext map of the files to aid in the navigation of the model. This program also provides a facility for adding notes and descriptions, beyond what is in the source model represented by the hypertext map. Further, this program provides access to a summary of the model through variable, function, sub routine, activity and resource declarations as well as providing full access to the source model and source code. The use of the tool enables easy access to the declarations and the ability to traverse routines and calls while analyzing the model.

Gladden, Roy E.↗
NASA NTRS2015

Using Science Skills to Understand Ecophysiology and Manage Resources

Presentation will be for a general audience and focus on plant science and ecosystem science in NASA. Examples from the projects involving the presenter will be used to illustrate. Specifically, the California Sacramento-San Joaquin River Delta project. This collaboration supports the goals of the Delta Plan in developing science-based, adaptive-management strategies. The mission is to improve reliability of water supply and restore a healthy Delta ecosystem while enhancing agriculture and recreation. NASA can contribute gap-filling science understanding of overall functions in the Delta ecosystem and assess and help develop management plans for specific issues. Airborne and satellite remote-sensing, ecosystem modeling, and biological studies provide underlying data needed by Delta stakeholders to assess and address water, ecosystem restoration, and environmental and economic impacts of potential actions in the Delta. The California Sacramento-San Joaquin River Delta, the hub for California's water supply, supports important ecosystem services for fisheries, supplies drinking water for millions, and distributes water from Northern California to agriculture and urban communities to the south; millions of people and businesses depend on Delta water. Decades of competing demands for Delta resources and year-to-year variability in precipitation has resulted in diminished overall health of the Delta. Declines in fish populations, threatened ecosystems, endangered species, invasive plants and animals, cuts in agricultural exports, and increased water conservation is the result. NASA and the USDA, building on previous collaborations, aide local Delta stakeholders in assessing and developing an invasive weed management approach. Aquatic, terrestrial, and riparian invasive weeds threaten aquatic and terrestrial ecosystem restoration efforts. Aquatic weeds are currently detrimental economically, environmentally, and sociologically in the Delta. They negatively impact the redistribution of water and disrupt the ecology of the Bay Delta food web. Filling current science gaps in the Delta Plan and improving management practices within the Delta are important to achieving the mission of improved Delta health. Methods developed can become routine land and water management tools. New high-resolution NASA sensor systems could be used to provide data packages specifically designed for water system The presenter will also speak about his personal experience and the role Delaware Valley College played in preparation for a professional career science.

Water↗
NASA NTRS2005

Probabilistic Reasoning for Plan Robustness

A planning system must reason about the uncertainty of continuous variables in order to accurately project the possible system state over time. A method is devised for directly reasoning about the uncertainty in continuous activity duration and resource usage for planning problems. By representing random variables as parametric distributions, computing projected system state can be simplified in some cases. Common approximation and novel methods are compared for over-constrained and lightly constrained domains. The system compares a few common approximation methods for an iterative repair planner. Results show improvements in robustness over the conventional non-probabilistic representation by reducing the number of constraint violations witnessed by execution. The improvement is more significant for larger problems and problems with higher resource subscription levels but diminishes as the system is allowed to accept higher risk levels.

autonomous planning↗
NASA NTRS2009

Computing Bounds on Resource Levels for Flexible Plans

A new algorithm efficiently computes the tightest exact bound on the levels of resources induced by a flexible activity plan (see figure). Tightness of bounds is extremely important for computations involved in planning because tight bounds can save potentially exponential amounts of search (through early backtracking and detection of solutions), relative to looser bounds. The bound computed by the new algorithm, denoted the resource-level envelope, constitutes the measure of maximum and minimum consumption of resources at any time for all fixed-time schedules in the flexible plan. At each time, the envelope guarantees that there are two fixed-time instantiations one that produces the minimum level and one that produces the maximum level. Therefore, the resource-level envelope is the tightest possible resource-level bound for a flexible plan because any tighter bound would exclude the contribution of at least one fixed-time schedule. If the resource- level envelope can be computed efficiently, one could substitute looser bounds that are currently used in the inner cores of constraint-posting scheduling algorithms, with the potential for great improvements in performance. What is needed to reduce the cost of computation is an algorithm, the measure of complexity of which is no greater than a low-degree polynomial in N (where N is the number of activities). The new algorithm satisfies this need. In this algorithm, the computation of resource-level envelopes is based on a novel combination of (1) the theory of shortest paths in the temporal-constraint network for the flexible plan and (2) the theory of maximum flows for a flow network derived from the temporal and resource constraints. The measure of asymptotic complexity of the algorithm is O(N O(maxflow(N)), where O(x) denotes an amount of computing time or a number of arithmetic operations proportional to a number of the order of x and O(maxflow(N)) is the measure of complexity (and thus of cost) of a maximumflow algorithm applied to an auxiliary flow network of 2N nodes. The algorithm is believed to be efficient in practice; experimental analysis shows the practical cost of maxflow to be as low as O(N1.5). The algorithm could be enhanced following at least two approaches. In the first approach, incremental subalgorithms for the computation of the envelope could be developed. By use of temporal scanning of the events in the temporal network, it may be possible to significantly reduce the size of the networks on which it is necessary to run the maximum-flow subalgorithm, thereby significantly reducing the time required for envelope calculation. In the second approach, the practical effectiveness of resource envelopes in the inner loops of search algorithms could be tested for multi-capacity resource scheduling. This testing would include inner-loop backtracking and termination tests and variable and value-ordering heuristics that exploit the properties of resource envelopes more directly.

Muscvettola, Nicola↗
NASA NTRS2011

Variability of African Farming Systems from Phenological Analysis of NDVI Time Series

Food security exists when people have access to sufficient, safe and nutritious food at all times to meet their dietary needs. The natural resource base is one of the many factors affecting food security. Its variability and decline creates problems for local food production. In this study we characterize for sub-Saharan Africa vegetation phenology and assess variability and trends of phenological indicators based on NDVI time series from 1982 to 2006. We focus on cumulated NDVI over the season (cumNDVI) which is a proxy for net primary productivity. Results are aggregated at the level of major farming systems, while determining also spatial variability within farming systems. High temporal variability of cumNDVI occurs in semiarid and subhumid regions. The results show a large area of positive cumNDVI trends between Senegal and South Sudan. These correspond to positive CRU rainfall trends found and relate to recovery after the 1980's droughts. We find significant negative cumNDVI trends near the south-coast of West Africa (Guinea coast) and in Tanzania. For each farming system, causes of change and variability are discussed based on available literature (Appendix A). Although food security comprises more than the local natural resource base, our results can perform an input for food security analysis by identifying zones of high variability or downward trends. Farming systems are found to be a useful level of analysis. Diversity and trends found within farming system boundaries underline that farming systems are dynamic.

Vrieling, Anton↗
NASA NTRS1977

An interactive computer approach to performing resource analysis for a multi-resource/multi-project problem

New planning techniques and supporting computer tools are needed for the optimization of resources and costs for space transportation and payload systems. Heavy emphasis on cost effective utilization of resources has caused NASA program planners to look at the impact of various independent variables that affect procurement buying. A description is presented of a category of resource planning which deals with Spacelab inventory procurement analysis. Spacelab is a joint payload project between NASA and the European Space Agency and will be flown aboard the Space Shuttle starting in 1980. In order to respond rapidly to the various procurement planning exercises, a system was built that could perform resource analysis in a quick and efficient manner. This system is known as the Interactive Resource Utilization Program (IRUP). Attention is given to aspects of problem definition, an IRUP system description, questions of data base entry, the approach used for project scheduling, and problems of resource allocation.

Schlagheck, R. A.↗
NASA NTRS2022

Midwest Water Resources: Developing an Evapotranspiration Climatology to Analyze Spatiotemporal Water Budget Patterns for Agriculture and Natural Resources Managers in the Midwest

Evapotranspiration (ET) is a climatic variable critical to the hydrologic cycle and is used to evaluate spatiotemporal trends in drought conditions. Although in-situ observations provide accurate ET information, these records are spatially sparse. The United States Department of Agriculture (USDA) Midwest Climate Hub, National Integrated Drought Information System, Minnesota Department of Agriculture, Michigan State University, and the USDA Foreign Agricultural Service have partnered with DEVELOP to gain new insights on spatiotemporal patterns of ET with NASA satellite data. This project evaluates the feasibility of using remotely sensed ET data products to understand trends from 2001 through 2020. Actual ET (aET) data were sourced from NASA’s Terra Moderate Resolution Imaging Spectroradiometer (MODIS), and reference ET (refET) and precipitation data were sourced from the Gridded Surface Meteorological Dataset (gridMET). Spatial and temporal differences in the MODIS and gridMET data sets were resolved such that gridded data could be compared. These data sets were then used to produce monthly Normals maps of mm/8-day of precipitation, aET, and refET. Using precipitation and ET Normals maps, hydrologic state maps were produced by subtracting either refET or aET from precipitation. These hydrologic state maps provide a proxy water balance by summarizing the difference between water entering and leaving the ground surface. Additionally, the ET products were compared in timeseries plots. The ET products from this project provided partners with comparable datasets to assess potential drought and flooding conditions to support Midwest agricultural and natural resource managers in decision-making.

Emma Myrick↗
NASA NTRS1973

Repetitive ERTS-1 observations of surface water variability along rivers and low-lying areas

The Earth Resources Technology Satellite, ERTS-1, provides an 18 day repetitive coverage capability and observations in the 0.8-1.1 micron spectral region where the contrast between water and adjacent surfaces is relatively large. Using these capabilities, observations in Virginia, Iowa, Missouri, and California have been acquired showing distinct patterns of flooding. Repetitive views of these areas before and after flooding have been examined, and flood mapping was performed. Sloughs in California can be seen to expand in terms of the area covered by standing water as time extends from summer to autumn. The results indicate that ERTS-1 imagery can be a valuable adjunct to conventional and aircraft survey methods for ascertaining the amount of area covered by water or affected by flooding.

Rango, A.↗
NASA NTRS1992

The experience factory: Can it make you a 5? or what is its relationship to other quality and improvement concepts?

The concepts of quality improvements have permeated many businesses. It is clear that the nineties will be the quality era for software and there is a growing need to develop or adapt quality improvement approaches to the software business. Thus we must understand software as an artifact and software as a business. Since the business we are dealing with is software, we must understand the nature of software and software development. The software discipline is evolutionary and experimental; it is a laboratory science. Software is development not production. The technologies of the discipline are human based. There is a lack of models that allow us to reason about the process and the product. All software is not the same; process is a variable, goals are variable, etc. Packaged, reusable, experiences require additional resources in the form of organization, processes, people, etc. There have been a variety of organizational frameworks proposed to improve quality for various businesses. The ones discussed in this presentation include: Plan-Do-Check-Act, a quality improvement process based upon a feedback cycle for optimizing a single process model/production line; the Experience Factory/Quality Improvement Paradigm, continuous improvements through the experimentation, packaging, and reuse of experiences based upon a business's needs; Total Quality Management, a management approach to long term success through customer satisfaction based on the participation of all members of an organization; the SEI capability maturity model, a staged process improvement based upon assessment with regard to a set of key process areas until you reach a level 5 which represents a continuous process improvement; and Lean (software) Development, a principle supporting the concentration of the production on 'value added' activities and the elimination of reduction of 'not value added' activities.

Basili, Victor R.↗
NASA NTRS1996

Optimization of Operations Resources via Discrete Event Simulation Modeling

The resource levels required for operation and support of reusable launch vehicles are typically defined through discrete event simulation modeling. Minimizing these resources constitutes an optimization problem involving discrete variables and simulation. Conventional approaches to solve such optimization problems involving integer valued decision variables are the pattern search and statistical methods. However, in a simulation environment that is characterized by search spaces of unknown topology and stochastic measures, these optimization approaches often prove inadequate. In this paper, we have explored the applicability of genetic algorithms to the simulation domain. Genetic algorithms provide a robust search strategy that does not require continuity and differentiability of the problem domain. The genetic algorithm successfully minimized the operation and support activities for a space vehicle, through a discrete event simulation model. The practical issues associated with simulation optimization, such as stochastic variables and constraints, were also taken into consideration.

Joshi, B.↗
NASA NTRS2020

Irrigation Water Demand Sensitivity to Climate Variability across the Contiguous United States

Climate variability is an important driver of irrigation water use in many regions. Efforts to anticipate climate change impacts on future water availability can benefit from understanding how irrigation water demand has responded to these drivers to date. Here we apply satellite derived data, meteorological reanalysis, an advanced land surface model, and available state level reports to quantify irrigation demand sensitivities to temperature and precipitation across the Contiguous United States, for the period of 2002-2017. As expected, strong negative correlations are found between precipitation and irrigation withdrawals, both simulated and reported. Temperature sensitivities, however, vary by region and season, as do the interactive effects of temperature and precipitation on irrigation. Climate-induced irrigation variability is largest in transitional climate zones. These transitional zones are generally separate from the regions where rates of irrigation withdrawals are greatest, such that climate-induced variability in irrigation demand represents a water resource consideration that is distinct from chronic over pumping.

Wanshu Nie↗
NASA NTRS2012

Probabilistic Requirements (Partial) Verification Methods Best Practices Improvement. Variables Acceptance Sampling Calculators: Empirical Testing

The NASA Engineering and Safety Center was requested to improve on the Best Practices document produced for the NESC assessment, Verification of Probabilistic Requirements for the Constellation Program, by giving a recommended procedure for using acceptance sampling by variables techniques as an alternative to the potentially resource-intensive acceptance sampling by attributes method given in the document. In this paper, the results of empirical tests intended to assess the accuracy of acceptance sampling plan calculators implemented for six variable distributions are presented.

Johnson, Kenneth L.↗
NASA NTRS1985

Finding relationships between effort and other variables in the SEL

Estimating the amount of effort required for a software development project is one of the major aspects of resource estimation for that project. In this study, the relationship between effort and other variables for 23 Software Engineering Laboratory (SEL) projects that were developed for NASA/Goddard Space Flight Center was examined. These variables fell into two categories: those which can be determined in the early stages of project development and may therefore be useful in a baseline equation for predicting effort in future projects, and those which can be used mainly to characterize or evaluate effort requirements and thus enhance the understanding of the software development process in this environment. Some results of the analyses are presented.

Basili, Victor R.↗
NASA NTRS2017

Multi-Objective Reinforcement Learning-Based Deep Neural Networks for Cognitive Space Communications

Future communication subsystems of space exploration missions can potentially benefit from software-defined radios (SDRs) controlled by machine learning algorithms. In this paper, we propose a novel hybrid radio resource allocation management control algorithm that integrates multi-objective reinforcement learning and deep artificial neural networks. The objective is to efficiently manage communications system resources by monitoring performance functions with common dependent variables that result in conflicting goals. The uncertainty in the performance of thousands of different possible combinations of radio parameters makes the trade-off between exploration and exploitation in reinforcement learning (RL) much more challenging for future critical space-based missions. Thus, the system should spend as little time as possible on exploring actions, and whenever it explores an action, it should perform at acceptable levels most of the time. The proposed approach enables on-line learning by interactions with the environment and restricts poor resource allocation performance through virtual environment exploration. Improvements in the multiobjective performance can be achieved via transmitter parameter adaptation on a packet-basis, with poorly predicted performance promptly resulting in rejected decisions. Simulations presented in this work considered the DVB-S2 standard adaptive transmitter parameters and additional ones expected to be present in future adaptive radio systems. Performance results are provided by analysis of the proposed hybrid algorithm when operating across a satellite communication channel from Earth to GEO orbit during clear sky conditions. The proposed approach constitutes part of the core cognitive engine proof-of-concept to be delivered to the NASA Glenn Research Center SCaN Testbed located onboard the International Space Station.

space archtiecture↗
NASA NTRS2017

Multi-Objective Reinforcement Learning-based Deep Neural Networks for Cognitive Space Communications

Future communication subsystems of space exploration missions can potentially benefit from software-defined radios (SDRs) controlled by machine learning algorithms. In this paper, we propose a novel hybrid radio resource allocation management control algorithm that integrates multi-objective reinforcement learning and deep artificial neural networks. The objective is to efficiently manage communications system resources by monitoring performance functions with common dependent variables that result in conflicting goals. The uncertainty in the performance of thousands of different possible combinations of radio parameters makes the trade-off between exploration and exploitation in reinforcement learning (RL) much more challenging for future critical space-based missions. Thus, the system should spend as little time as possible on exploring actions, and whenever it explores an action, it should perform at acceptable levels most of the time. The proposed approach enables on-line learning by interactions with the environment and restricts poor resource allocation performance through virtual environment exploration. Improvements in the multiobjective performance can be achieved via transmitter parameter adaptation on a packet-basis, with poorly predicted performance promptly resulting in rejected decisions. Simulations presented in this work considered the DVB-S2 standard adaptive transmitter parameters and additional ones expected to be present in future adaptive radio systems. Performance results are provided by analysis of the proposed hybrid algorithm when operating across a satellite communication channel from Earth to GEO orbit during clear sky conditions. The proposed approach constitutes part of the core cognitive engine proof-of-concept to be delivered to the NASA Glenn Research Center SCaN Testbed located onboard the International Space Station.

space archtiecture↗
NASA NTRS2011

NASA Water Resources Program

With increasing population pressure and water usage coupled with climate variability and change, water issues are being reported by numerous groups as the most critical environmental problems facing us in the 21st century. Competitive uses and the prevalence of river basins and aquifers that extend across boundaries engender political tensions between communities, stakeholders and countries. In addition to the numerous water availability issues, water quality related problems are seriously affecting human health and our environment. The potential crises and conflicts especially arise when water is competed among multiple uses. For example, urban areas, environmental and recreational uses, agriculture, and energy production compete for scarce resources, not only in the Western U.S. but throughout much of the U.S. and also in numerous parts of the world. Mitigating these conflicts and meeting water demands and needs requires using existing water resources more efficiently. The NASA Water Resources Program Element works to use NASA products and technology to address these critical water issues. The primary goal of the Water Resources is to facilitate application of NASA Earth science products as a routine use in integrated water resources management for the sustainable use of water. This also includes the extreme events of drought and floods and the adaptation to the impacts from climate change. NASA satellite and Earth system observations of water and related data provide a huge volume of valuable data in both near-real-time and extended back nearly 50 years about the Earth's land surface conditions such as precipitation, snow, soil moisture, water levels, land cover type, vegetation type, and health. NASA Water Resources Program works closely to use NASA and Earth science data with other U.S. government agencies, universities, and non-profit and private sector organizations both domestically and internationally. The NASA Water Resources Program organizes its projects under five functional themes. I) Streamflow and Flood Forecasting 2) Water Supply and Irrigation (includes evapotranspiration) 3) Drought 4) Water Quality 5) Climate and Water Resources. To maximize this activity NASA Water Resources Program works closely with other government agencies (e.g., the National Oceanic and Atmospheric Administration (NOAA); the U.S. Department of Agriculture (USDA); the U.S. Geological Survey (USGS); the Environmental Protection Agency (EPA), USAID, the Air Force Weather Agency (AFWA)), universities, non-profit national and international organizations, and the private sector. The NASA Water Resources program currently is funding 21 active projects under the functional themes (http://wmp.gsfc.nasa.gov & http://science.nasa.gov/earth-science/applied-sciences/).

Toll, David L.↗
NASA NTRS2002

Fractional Factorial Experiment Designs to Minimize Configuration Changes in Wind Tunnel Testing

This paper serves as a tutorial to introduce the wind tunnel research community to configuration experiment designs that can satisfy resource constraints in a configuration study involving several variables, without arbitrarily eliminating any of them from the experiment initially. The special case of a configuration study featuring variables at two levels is examined in detail. This is the type of study in which each configuration variable has two natural states - 'on or off', 'deployed or not deployed', 'low or high', and so forth. The basic principles are illustrated by results obtained in configuration studies conducted in the Langley National Transonic Facility and in the ViGYAN Low Speed Tunnel in Hampton, Virginia. The crucial role of interactions among configuration variables is highlighted with an illustration of difficulties that can be encountered when they are not properly taken into account.

DeLoach, Richard↗
NASA NTRS2018

Remote Sensing Applications for Water Resources Management, Including Droughts, Floods, and Associated Water Cycle Extremes II

Water resources management can benefit from applications of remote sensing and hydrologic models. These tools can be especially valuable during extreme events and in data-sparse regions. Observational platforms include the GPM, SMAP, Terra, Aqua, Landsat, GRACE, and Sentinel satellites, and other satellite and airborne platforms. They can support the operational water resources management community in responding to climate change, increases in climate variability and the frequency of extreme events. This session will highlight advances in the use of satellite, airborne and ground-based sensor networks to: measure the quantity/quality of hydrologic resources in the U.S. and internationally; provide information to water managers to improve water resources management; and support risk-based decision making. Topics of interest include (1) extreme events such as floods and droughts; (2) water supply and snow water resource monitoring and forecasting; (3) evapotranspiration, soil moisture, groundwater, and agricultural water management; (4) water quality and (5) global water sustainability.

Bolten, John D.↗