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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 NTRS1990

Strategies for concurrent processing of complex algorithms in data driven architectures

The performance modeling and enhancement for periodic execution of large-grain, decision-free algorithms in data flow architectures is examined. Applications include real-time implementation of control and signal processing algorithms where performance is required to be highly predictable. The mapping of algorithms onto the specified class of data flow architectures is realized by a marked graph model called ATAMM (Algorithm To Architecture Mapping Model). Performance measures and bounds are established. Algorithm transformation techniques are identified for performance enhancement and reduction of resource (computing element) requirements. A systematic design procedure is described for generating operating conditions for predictable performance both with and without resource constraints. An ATAMM simulator is used to test and validate the performance prediction by the design procedure. Experiments on a three resource testbed provide verification of the ATAMM model and the design procedure.

Stoughton, John W.↗
NASA NTRS1990

Minimizing attitude control fuel in space manipulator systems

Techniques are presented for finding space manipulator motions which result in reduced spacecraft dynamic disturbances. Although a spacecraft's attitude control reaction jets can compensate for these disturbances, reaction jet fuel is a limited resource and excessive disturbances would limit the life of a space manipulator. A graphical tool called the Enhanced Disturbance Map (EDM) is presented and is demonstrated as an aid in developing planning and control algorithms to solve this complex problem.

Dubowsky, Steven↗
NASA NTRS2004

Retrieval of Marine Water Constituents Using Atmospherically Corrected AVIRIS Hyperspectral Data

This paper reports on the validation of bio-optical models in estuarine and nearshore (case 2) waters of New Jersey-New York to retrieve accurate water-leaving radiance spectra and chlorophyll concentration from the Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) imaging spectrometer data. MODTRAN-4 was applied to remove the effects of the atmosphere so as to infer the water-leaving radiance. The study area - Hudson/Raritan of New York and New Jersey (Figure 1) is an extremely complex estuarine system where tidal and wind-driven currents are modified by freshwater discharges from the Hudson, Raritan, Hackensack, and Passaic rivers. Over the last century, the estuarine water quality has degraded in part due to eutrophication, which has disrupted the preexisting natural balance, resulting in phytoplankton blooms of both increased frequency and intensity, increasing oxygen demand, and leading to episodes of hypoxia. As the end result, a thematic map of chlorophyll-a concentration was generated using an atmospherically corrected AVIRIS ratio image. This thematic map serves as an indication of phytoplankton concentration. Such maps are important input into the geographic information system (GIS) for use as a management tool for monitoring water resources.

Bagheri, Sima↗
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 NTRS2018

A Comparison of Satellite Data-Based Drought Indicators in Detecting the 2012 Drought in the Southeastern US

The drought of 2012 in the North America devastated agricultural crops and pastures, further damaging agriculture and livestock industries and leading to great losses in the economy. The drought maps of the United States Drought Monitor (USDM) and various drought monitoring techniques based on the data collected by the satellites orbiting in space such as the Gravity Recovery and Climate Experiment (GRACE) and the Moderate Resolution Imaging Spectroradiometer (MODIS) are inter-compared during the 2012 drought conditions in the southeastern United States. The results indicated that spatial extent of drought reported by USDM were in general agreement with those reported by the MODIS-based drought maps. GRACE-based drought maps suggested that the southeastern US experienced widespread decline in surface and root-zone soil moisture and groundwater resources. Disagreements among all drought indicators were observed over irrigated areas, especially in Lower Mississippi region where agriculture is mainly irrigated. Besides, we demonstrated that time lag of vegetation response to changes in soil moisture and groundwater partly contributed to these disagreements, as well.

drought indicators↗
NASA NTRS2024

Prithvi-EO-2.0: A Versatile Multi-Temporal Foundation Model for Earth Observation Applications

This technical report presents Prithvi-EO-2.0, a new geospatial foundation model that offers significant improvements over its predecessor, Prithvi-EO-1.0. Trained on 4.2M global time series samples from NASA’s Harmonized Landsat and Sentinel-2 data archive at 30m resolution, the new 300M and 600M parameter models incorporate temporal and location embeddings for enhanced performance across various geospatial tasks. Through extensive benchmarking with GEOBench, the 600M version outperforms the previous Prithvi-EO model by 8% across a range of tasks. It also outperforms six other geospatial foundation models when benchmarked on remote sensing tasks from different domains and resolutions (i.e. from 0.1m to 15m). The results demonstrate the versatility of the model in both classical earth observation and high-resolution applications. Early involvement of end-users and subject matter experts (SMEs) are among the key factors that contributed to the project’s success. In particular, SME involvement allowed for constant feedback on model and dataset design, as well as successful customization for diverse SME-led applications in disaster response, land use and crop mapping, and ecosystem dynamics monitoring. Prithvi-EO-2.0 is available on Hugging Face and IBM terratorch, with additional resources on GitHub. The project exemplifies the Trusted Open Science approach embraced by all involved organizations.

Daniela Szwarcman↗
DOE OSTI2024

Patch2Self2: Self-supervised Denoising on Coresets via Matrix Sketching

Diffusion MRI (dMRI) non-invasively maps brain white matter yet necessitates denoising due to low signal-to-noise ratios. Patch2Self (P2S) employing self-supervised techniques and regression on a Casorati matrix effectively denoises dMRI images and has become the new de-facto standard in this field. P2S however is resource intensive both in terms of running time and memory usage as it uses all voxels (n) from all-but-one held-in volumes (d-1) to learn a linear mapping Phi : \mathbb R ^ n x(d-1) \mapsto \mathbb R ^ n for denoising the held-out volume. The increasing size and dimensionality of higher resolution dMRI acquisitions can make P2S infeasible for large-scale analyses. This work exploits the redundancy imposed by P2S to alleviate its performance issues and inspect regions that influence the noise disproportionately. Specifically this study makes a three-fold contribution: (1) We present Patch2Self2 (P2S2) a method that uses matrix sketching to perform self-supervised denoising. By solving a sub-problem on a smaller sub-space so called coreset we show how P2S2 can yield a significant speedup in training time while using less memory. (2) We present a theoretical analysis of P2S2 focusing on determining the optimal sketch size through rank estimation a key step in achieving a balance between denoising accuracy and computational efficiency. (3) We show how the so-called statistical leverage scores can be used to interpret the denoising of dMRI data a process that was traditionally treated as a black-box. Experimental results on both simulated and real data affirm that P2S2 maintains denoising quality while significantly enhancing speed and memory efficiency achieved by training on a reduced data subset.

Fadnavis, Shreyas↗
NASA NTRS1975

ERTS applications in state land use planning

The progress made and limitations encountered in using ERTS-1 data for resource management in Ohio is surveyed. Photo-opto-electronic techniques were used with special facility equipment and resolution to 10-30 meters was required to determine strip mine features. Lake Erie's sediment patterns were detected along with flooding conditions, large scale vegetative damage caused by toxic air pollutants was identified, Ohio land use categories were tabulated and thematic map containing forested areas was derived. The experimental findings regarding utility/relevance assessment were ranked in 4 classes for all the applications involved. Preliminary recommendations for operational satellite earth resources survey data requirements are presented and data analysis and product dissemination are proposed to be centralized in conjunction with thermal IR data and an increased resolution.

Pincura, P. G.↗
NASA NTRS2022

Peru Health and Air Quality II: Leveraging Earth Observations and Health Data to Map Outbreak Risk and Inform Public Health Interventions for Zoonotic Disease Prevention

Peru's Madre de Dios region is a hotspot for dengue fever and leishmaniasis due to its tropical Amazonian climate. Though treatable, these zoonotic diseases are debilitating for under-resourced communities whose already close proximity to mosquito and sandfly vectors continues to increase via rapid urbanization and deforestation. Peru’s Ministries of Health (MINSA) and Environment (MINAM) are working to better understand the environmental factors amplifying the risk of dengue fever and leishmaniasis transmission. The first term of this project classified the land use and land cover of Madre de Dios’ 11 districts for 2010, 2015, and 2020 and identified a correlation between both diseases and urbanization. Our team expanded this analysis by creating urban-forest edge maps and incorporating climatic and topographic variables with data from Landsat 7 Enhanced Thematic Mapper Plus (ETM+), Landsat 8 Operational Land Imager (OLI), the Global Precipitation Measurement (GPM) Integrated Multi-satellitE Retrievals for GPM (IMERG), and the Shuttle Radar Topography Mission (SRTM). We determined these variables’ impacts on disease incidence by assessing existing literature and running regression models. Dengue fever correlated with urban-forest edge, urban area, slope, temperature, and precipitation. Leishmaniasis primarily correlated with forest-edge area and elevation, but lacking additional statistical significance prevented further work, a decision supported by the literature. Thus, the risk matrix and risk map which we scripted in R to visualize the risk of disease posed to districts alongside health post locations addresses only dengue fever. The results and products will inform MINSA and MINAM in public health interventions, resource distribution, and policy initiatives.

Jennifer Rogers↗
NASA NTRS2016

Drought Impacts on Agricultural Production and Land Fallowing in California's Central Valley in 2015

The ongoing drought in California substantially reduced surface water supplies for millions of acres of irrigated farmland in California's Central Valley. Rapid assessment of drought impacts on agricultural production can aid water managers in assessing mitigation options, and guide decision making with respect to mitigation of drought impacts. Satellite remote sensing offers an efficient way to provide quantitative assessments of drought impacts on agricultural production and increases in fallow acreage associated with reductions in water supply. A key advantage of satellite-based assessments is that they can provide a measure of land fallowing that is consistent across both space and time. We describe an approach for monthly and seasonal mapping of uncultivated agricultural acreage developed as part of a joint effort by USGS, USDA, NASA, and the California Department of Water Resources to provide timely assessments of land fallowing during drought events. This effort has used the Central Valley of California as a pilot region for development and testing of an operational approach. To provide quantitative measures of uncultivated agricultural acreage from satellite data early in the season, we developed a decision tree algorithm and applied it to time-series data from Landsat TM (Thematic Mapper), ETM+ (Enhanced Thematic Mapper Plus), OLI (Operational Land Imager), and MODIS (Moderate Resolution Imaging Spectroradiometer). Our effort has been focused on development of indicators of drought impacts in the March-August timeframe based on measures of crop development patterns relative to a reference period with average or above average rainfall. To assess the accuracy of the algorithms, monthly ground validation surveys were conducted across 650 fields from March-September in 2014 and 2015. We present the algorithm along with updated results from the accuracy assessment, and data and maps of land fallowing in the Central Valley in 2015.

Valleys↗
NASA NTRS2010

Lunar Reconnaissance Orbiter (LRO): Observations for Lunar Exploration and Science

The Lunar Reconnaissance Orbiter (LRO) was implemented to facilitate scientific and engineering-driven mapping of the lunar surface at new spatial scales and with new remote sensing methods, identify safe landing sites, search for in situ resources, and measure the space radiation environment. After its successful launch on June 18,2009, the LRO spacecraft and instruments were activated and calibrated in an eccentric polar lunar orbit until September 15, when LRO was moved to a circular polar orbit with a mean altitude of 50 km. LRO will operate for at least one year to support the goals of NASA's Exploration Systems Mission Directorate (ESMD), and for at least two years of extended operations for additional lunar science measurements supported by NASA's Science Mission Directorate (SMD). LRO carries six instruments with associated science and exploration investigations, and a telecommunications/radar technology demonstration. The LRO instruments are: Cosmic Ray Telescope for the Effects of Radiation (CRaTER), Diviner Lunar Radiometer Experiment (DLRE), Lyman-Alpha Mapping Project (LAMP), Lunar Exploration Neutron Detector (LEND), Lunar Orbiter Laser Altimeter (LOLA), and Lunar Reconnaissance Orbiter Camera (LROC). The technology demonstration is a compact, dual-frequency, hybrid polarity synthetic aperture radar instrument (Mini-RF). LRO observations also support the Lunar Crater Observation and Sensing Satellite (LCROSS), the lunar impact mission that was co-manifested with LRO on the Atlas V (401) launch vehicle. This paper describes the LRO objectives and measurements that support exploration of the Moon and that address the science objectives outlined by the National Academy of Science's report on the Scientific Context for Exploration of the Moon (SCEM). We also describe data accessibility by the science and exploration community.

Vondrak, Richard↗
DOE OSTI2024

Mapping use cases and dataset needs for benchmarking buildings data

A perennial challenge in buildings research is the lack of high-quality datasets that can be relied upon for a wide array of tasks, including model calibration and improving energy efficiency and load flexibility. Instrumenting a building for data collection is resource intensive, so it is important to be methodical in the approach and ensure that resulting data are flexible and useful for a broad range of analyses. This study aims to fill the gaps in characterizing potential use cases for buildings datasets and mapping them to dataset needs using a well-defined data infrastructure. Here, we have developed a systematic mapping strategy between buildings dataset needs and use cases to help streamline the processes of efficiently targeting datasets, designing building sensing systems, and determining buildings research use cases. We selected 14 prospective use cases and 11 refined buildings data categories for developing the preliminary dataset-needs-to-use-cases mapping matrix (‘DN-UC mapping matrix’) with generic ‘Tags’—a detailed sub-level of data categories extracted by justifying the needs of an aspect of the datasets to use cases. We present two example applications of the developed mapping matrix to demonstrate use of the mapping matrix and its effectiveness.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
NASA NTRS1975

CARETS: A prototype regional environmental information system. Volume 12: User evaluation of experimental land use maps and related products from the central Atlantic test site

The user interaction and evaluation phase of the USGS/NASA Central Atlantic Regional Ecological Test Site was designed to obtain the input of local, regional, State, and Federal agency users of land-resource information into the development, of a regional information system; to provide users with assistance and data resulting from CARETS research; and to have user. organizations evaluate to what extent the CARETS products meet their needs. The evaluation of CARETS land use and related products revealed that most user agencies interviewed, at all governmental levels, require more detailed data than that provided by the CARETS project. Few agencies found utility in the generalized ERTS Level I land--use maps. Level II data, though reported valuable by several users, was generally considered of secondary utility by most users. The products considered most useful by users at all levels were the high--altitude color-infrared photographs and the USGS orthophotoquads. Recommendations resulting from the evaluation reflect the need to establish a flexible and reliable system for providing more detailed raw and processed land-resource information as well as the need to improve the methods of making information available to users.

Land-use planning↗
NASA NTRS1982

Geographic Information Systems for Assessing Existing and Potential Bio-energy Resources: Their Use in Determining Land Use and Management Options which Minimize Ecological and Landscape Impacts in Rural Areas

A management construct is described which forms part of an overall landscape ecological planning model which has as a principal objective the extension of the traditional descriptive land use mapping capabilities of geographic information systems into land management realms. It is noted that geographic information systems appear to be moving to more comprehensive methods of data handling and storage, such as relational and hierarchical data management systems, and a clear need has simultaneously arisen therefore for planning assessment techniques and methodologies which can actually use such complex levels of data in a systematic, yet flexible and scenario dependent way. The descriptive of mapping method proposed broaches such issues and utilizes a current New England bioenergy scenario, stimulated by the use of hardwoods for household heating purposes established in the post oil crisis era and the increased awareness of the possible landscape and ecological ramifications of the continued increasing use of the resource.

Jackman, A. E.↗
DOE OSTI2022

Chromosome evolution and the genetic basis of agronomically important traits in greater yam

The nutrient-rich tubers of the greater yam, Dioscorea alata L., provide food and income security for millions of people around the world. Despite its global importance, however, greater yam remains an orphan crop. Here, we address this resource gap by presenting a highly contiguous chromosome-scale genome assembly of D. alata combined with a dense genetic map derived from African breeding populations. The genome sequence reveals an ancient allotetraploidization in the Dioscorea lineage, followed by extensive genome-wide reorganization. Using the genomic tools, we find quantitative trait loci for resistance to anthracnose, a damaging fungal pathogen of yam, and several tuber quality traits. Genomic analysis of breeding lines reveals both extensive inbreeding as well as regions of extensive heterozygosity that may represent interspecific introgression during domestication. These tools and insights will enable yam breeders to unlock the potential of this staple crop and take full advantage of its adaptability to varied environments.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2026

Integrated Neutronics Modeling for Inertial Fusion Energy Systems: Development and Application to LD-FIRST

Lawrence Livermore National Laboratory (LLNL) is proposing a new Laser Driven Fusion Integration Research and Science Test Facility (LD-FIRST) with the goal of providing an experimental testbed for future Inertial Fusion Energy (IFE) systems. However, IFE systems require detailed and accurate multiphysics modeling to quantify material damage, thermal loading, and tritium breeding within complex chamber environments. This article presents the first step in an integrated multiphysics framework that couples meshed CAD-based geometry within Monte Carlo neutronic simulations to enable high-fidelity analysis of IFE chamber concepts, with future coupling to external codes. The neutronics workflow utilizes OpenMC and its third-party capability to use CAD-based geometries through DAGMC and tally on unstructured meshes with Libmesh to evaluate neutron transport behavior, geometric fidelity, and material performance under reactor-relevant conditions. The use of tailored tallies on unstructured meshes in this framework allows direct transfer without interpolating to CFD simulation tools. Two IFE chambers were evaluated, both conceived by LLNL: HYLIFE-II and Laser IFE (LIFE). This work produced high-fidelity conformal surface and volumetric meshes of the HYLIFE-II and LIFE chambers with mapped spatial insight into material damage, thermal loading, and tritium breeding. The HYLIFE-II model was built utilizing available resources and used as a test case to verify that the neutronics framework can handle complex geometries. The LIFE chamber CAD was provided by LLNL and was the main focus of this work. This work analyzes multiple ternary alloy breeding materials for the LIFE chamber, across different 6 Li enrichments to produce data relevant to the LD-FIRST project. This work also investigates the level of model fidelity for the LIFE chamber, and results show that inclusion of detailed first wall and coolant structures increased the predicted tritium breeding ratio (TBR) by ~30%, highlighting the sensitivity of tritium breeding and the need for a high-fidelity simulation framework for IFE chambers. These developments provide a scalable toolset for the design and optimization of next-generation IFE chambers, forming a solid foundation for future coupled multiphysics analysis.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2023

Evaluating uncertainty-based active learning for accelerating the generalization of molecular property prediction

Deep learning models have proven to be a powerful tool for the prediction of molecular properties for applications including drug design and the development of energy storage materials. However, in order to learn accurate and robust structure–property mappings, these models require large amounts of data which can be a challenge to collect given the time and resource-intensive nature of experimental material characterization efforts. Additionally, such models fail to generalize to new types of molecular structures that were not included in the model training data. The acceleration of material development through uncertainty-guided experimental design has the promise to significantly reduce the data requirements and enable faster generalization to new types of materials. To evaluate the potential of such approaches for electrolyte design applications, we perform comprehensive evaluation of existing uncertainty quantification methods on the prediction of two relevant molecular properties - aqueous solubility and redox potential. We develop novel evaluation methods to probe the utility of the uncertainty estimates for both in-domain and out-of-domain data sets. Finally, we leverage selected uncertainty estimation methods for active learning to evaluate their capacity to support experimental design.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Hanford Site Rare Plant Monitoring Report for Calendar Year 2015

In 2015, two separate rare plant monitoring efforts occurred on the portion of the Hanford Site managed by the U.S. Department of Energy (DOE) (referred to herein as Central Hanford). 1. Upland plants of conservation concern were inventoried concurrently with efforts to map plant communities on Central Hanford. Plants were selected based on 2015 status with the Washington State Department of Natural Resources Natural Heritage Program (WNHP) listings, which are summarized in the bullets below. This effort was led by Mission Support Alliance (MSA) and subcontracted personnel from SEE Botanical Consulting.

54 ENVIRONMENTAL SCIENCES↗