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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 271 records · Page 15
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

COLUMBUS─An Efficient and General Program Package for Ground and Excited State Computations Including Spin–Orbit Couplings and Dynamics

The COLUMBUS program system provides the tools for performing high-level multireference (MR) computations, including the multireference configuration interaction (MRCI) method and its multireference averaged quadratic coupled cluster (MR-AQCC) extension, allowing computations on a wide range of fascinating atomic and molecular systems, including the treatment of open-shells and complicated excited state phenomena. The inclusion of spin−orbit coupling (SOC) directly within the MRCI step enables the description of systems containing heavy elements, such as lanthanides and actinides, whose properties are strongly influenced by SOC. Analytic energy gradients and nonadiabatic couplings at the correlated MRCI level provide the foundation for a variety of dynamics studies, giving insight into ultrafast photochemistry. New and ongoing method developments in COLUMBUS include the computation of spin densities, improved descriptions of ionic states, enhancements to the AQCC method, and the porting of COLUMBUS to graphical processing units (GPUs). New external interfaces enable an enhanced description of electronic resonances and molecules in strong laser fields. This work highlights these new developments while providing a detailed account of the diverse applications of COLUMBUS in recent years.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS2013

Flight Test Results of an Angle of Attack and Angle of Sideslip Calibration Method Using Output-Error Optimization

As part of a joint partnership between the NASA Aviation Safety Program (AvSP) and the University of Tennessee Space Institute (UTSI), research on advanced air data calibration methods has been in progress. This research was initiated to expand a novel pitot-static calibration method that was developed to allow rapid in-flight calibration for the NASA Airborne Subscale Transport Aircraft Research (AirSTAR) facility. This approach uses Global Positioning System (GPS) technology coupled with modern system identification methods that rapidly computes optimal pressure error models over a range of airspeed with defined confidence bounds. Subscale flight tests demonstrated small 2-σ error bounds with significant reduction in test time compared to other methods. Recent UTSI full scale flight tests have shown airspeed calibrations with the same accuracy or better as the Federal Aviation Administration (FAA) accepted GPS 'four-leg' method in a smaller test area and in less time. The current research was motivated by the desire to extend this method for inflight calibration of angle of attack (AOA) and angle of sideslip (AOS) flow vanes. An instrumented Piper Saratoga research aircraft from the UTSI was used to collect the flight test data and evaluate flight test maneuvers. Results showed that the output-error approach produces good results for flow vane calibration. In addition, maneuvers for pitot-static and flow vane calibration can be integrated to enable simultaneous and efficient testing of each system.

Siu, Marie-Michele↗
NASA NTRS2014

Cultivating an Emergent Earth Observation Analytics Ecosystem in the Cloud

A diverse set of data analytics systems for Earth Observations are sprouting up in the Earth Science community, with a wealth of processing algorithms and analysis methods. There is a similar wealth of data resources available via myriad data providers and clearinghouses, including large institutional systems like the Earth Observing System Data and Information System, Comprehensive Large Scale Array-data Stewardship System, and Federated Earth Observation Missions gateway. With Earth system science driving a need to work with more datasets together, and the community developing more analysis tools (some of them dataset-specific), how can we develop analysis workflows that incorporate far-flung datasets and leverage analysis resources from multiple organizations? Cloud computing points the way toward a solution in two different respects. Firstly, the access to and abstraction of virtually unlimited storage and computing power provides an environment that enables more straightforward means of pulling datasets and analysis resources together. Just as importantly, however, cloud computing serves as an example of an "ecosystem" of interoperating services, since the essence of cloud computing is the presentation of all resources as a service, from hardware to infrastructure to platform to software. This enables the combination of off-the-shelf, diverse services to construct entire systems that emerge out of an equally diverse community of architects and developers. This approach can be similarly applied to the data and analysis resources in the Earth Observation community. By exposing these resources via well understood services, and consuming resources in the same way, different organizations can construct bespoke analysis workflows and systems for their own purposes. The key leap the community needs to make is to develop analysis systems in components that interact with other components via services. The result would be a rich ecosystem of analytics components that can be combined to analyze datasets at scale and in conjunction with other datasets from other sources.

chaos↗
DOE OSTI2022

A Computational Framework for Energy Storage Participation in Transmission Planning with Electricity Market Participation

Energy storage technologies—including pumped storage hydropower (PSH), batteries, and other technologies—have been technically proven to be capable of providing transmission services by regulating power flows and providing voltage support. These technologies will potentially increase the flexibility of transmission infrastructure and may defer (or eliminate) the need for transmission upgrades or new investments. On the regulatory side, Congress and the Federal Energy Regulatory Commission (FERC) have issued several orders over decades that have established energy storage’s (ES) eligibility as a transmission asset. The orders have required transmission planning entities to provide a level playing field where ES can participate in the transmission planning process (TPP) without undue discrimination and preference of technology. These developments pave the way for ES to participate in transmission planning as a transmission asset. On the other hand, as a flexible resource, ES can play an important role in the electricity market to enable more renewable energy integration by providing energy and grid reliability services. This could bring more revenue in return.

25 ENERGY STORAGE↗
NASA NTRS1980

Study of the cerrado vegetation in the Federal District area from orbital data

The physiognomic units of cerrado in the area of Distrito Federal (DF) were studied through the visual and automatic analysis of products provided by Multispectral Scanning System (MSS) of LANDSAT. The visual analysis of the multispectral images in black and white, at the 1:250,000 scale, was made based on the texture and tonal patterns. The automatic analysis of the compatible computer tapes (CCT) was made by means of IMAGE-100 system. The following conclusions were obtained: (1) the delimitation of cerrado vegetation forms can be made by the visual and automatic analysis; (2) in the visual analysis, the principal parameter used to discriminate the cerrado forms was the tonal pattern, independently of the year's seasons, and the channel 5 gave better information; (3) in the automatic analysis, the data of the four channels of MSS can be used in the discrimination of the cerrado forms; and (4) in the automatic analysis, the four channels combination possibilities gave more information in the separation of cerrado units when soil types were considered.

Dejesusparada, N.↗
NASA NTRSDate not supplied

Biological Research and Space Health Enabled by Machine Learning to Support Deep Space Missions

A key science goal of the NASA “Moon to Mars” campaign is to understand how biology responds to the Lunar, Martian, and deep space environments in order to advance fundamental knowledge, reduce risk, and support safe, productive human space missions. Through the powerful emerging computer science approaches of artificial intelligence (AI) and machine learning (ML), a paradigm shift has begun in biomedical science and engineered astronaut health systems, to enable Earth-independence and autonomy of mission operations. We present a decadal view of AI/ML architecture to support deep space mission goals, developed in concert with leaders in the field. We describe current AI/ML methods to support 1) fundamental biology, 2) in situ analytics, 3) high performance computing hardware, 4) automated science, 5) self-driving labs, 6) remote data management, 7) integrated real-time mission biomonitoring, and 8) a Precision Space Health system. Cutting-edge AI/ML approaches that can be integrated to support these domains include active learning, explainable AI, adaptive learning, causal inference, knowledge graphs, federated learning, transfer learning, and large language models. Finally, we present results from several current ML projects that are underway in the field to address key challenges of small sample n, high feature count, heterogeneity, and sparse data. These include 1) connecting omics data to phenotypic data using an ensemble model to infer causality of spaceflight rodent liver health disruption, 2) usage of explainable ML to interrogate the muscular underpinnings of spaceflight muscle atrophy, 3) ML models analyzing and determining directed acyclic graphs of human space health risk leveraging rodent bone datasets, 4) usage of large pre-trained models connecting biomedical knowledgebases with small spaceflight datasets to understand gene-to-gene interaction networks, and 5) a suite of benchmarked open science datasets (spaceflight mouse liver; radiation DNA damage) enabling programmers to identify the best ML algorithms to answer space biological science questions.

space biology↗
NASA NTRSDate not supplied

Biological Research and Space Health Enabled by Machine Learning to Support Deep Space Missions

A key science goal of the NASA “Moon to Mars” campaign is to understand how biology responds to the Lunar, Martian, and deep space environments in order to advance fundamental knowledge, reduce risk, and support safe, productive human space missions. Through the powerful emerging computer science approaches of artificial intelligence (AI) and machine learning (ML), a paradigm shift has begun in biomedical science and engineered astronaut health systems, to enable Earth-independence and autonomy of mission operations. We present a decadal view of AI/ML architecture to support deep space mission goals, developed in concert with leaders in the field. We describe current AI/ML methods to support 1) fundamental biology, 2) in situ analytics, 3) high performance computing hardware, 4) automated science, 5) self-driving labs, 6) remote data management, 7) integrated real-time mission biomonitoring, and 8) a Precision Space Health system. Cutting-edge AI/ML approaches that can be integrated to support these domains include active learning, explainable AI, adaptive learning, causal inference, knowledge graphs, federated learning, transfer learning, and large language models. Finally, we present results from several current ML projects that are underway in the field to address key challenges of small sample n, high feature count, heterogeneity, and sparse data. These include 1) connecting omics data to phenotypic data using an ensemble model to infer causality of spaceflight rodent liver health disruption, 2) usage of explainable ML to interrogate the muscular underpinnings of spaceflight muscle atrophy, 3) ML models analyzing and determining directed acyclic graphs of human space health risk leveraging rodent bone datasets, 4) usage of large pre-trained models connecting biomedical knowledgebases with small spaceflight datasets to understand gene-to-gene interaction networks, and 5) a suite of benchmarked open science datasets (spaceflight mouse liver; radiation DNA damage) enabling programmers to identify the best ML algorithms to answer space biological science questions.

space biology↗
DOE OSTI2025

Procurement Analysis Tool (PAT)

This a poster on PAT for the CESA National Energy Summit for States: Navigating Energy Trends and Federal Programs Conference.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
NASA NTRS1996

A Conservation Strategy for the Florida Scrub-Jay on John F. Kennedy Space Center/Merritt Island National Wildlife Refuge: An Initial Scientific Basis for Recovery

The Florida Scrub-Jay (Aphelocoma coerulescens) is an indicator of ecosystem integrity of Florida scrub, an endangered ecosystem that requires frequent fire. One of the largest populations of this federally threatened species occurs on John F. Kennedy Space Center/Merritt Island National Wildlife Refuge. Population trends were predicted using population modeling and field data on reproduction and survival of Florida Scrub-Jays collected from 1988 - 1995. Analyses of historical photography indicated that habitat suitability has been declining for 30 years. Field data and computer simulations suggested that the population declined by at least 40% and will decline by another 40% in 1 0 years, if habitat management is not greatly intensified. Data and computer simulations suggest that habitat suitability cannot deviate greatly from optimal for the jay population to persist. Landscape trajectories of vegetation structure, responsible for declining habitat suitability, are associated with the disruption of natural fire regimes. Prescribed fire alone can not reverse the trajectories. A recovery strategy was developed, based on studies of Florida Scrub-Jays and scrub vegetation. A reserve design was formulated based on conservation science principles for scrub ecosystems. The strategy emphasizes frequent fire to restore habitat, but includes mechanical tree cutting for severely degraded areas. Pine thinning across large areas can produce rapid increases in habitat quality. Site-specific strategies will need to be developed, monitored, and modified to achieve conditions suitable for population persistence.

Breininger, D. R.↗
NASA NTRS2018

Improving NASA Earth Science Data and Information Access Through Natural Language Processing Based Data Analysis and Visualization

NASA: The Research Access initiative is part of the agency's framework for increasing public access to scientific publications and digital scientific data. The initiative follows the release of White House Office of Science and Technology Policy's (OSTP) memorandum "Increasing Access to the Results of Federally Funded Research," to ensure federally funded research is available to the public within one year of publication. NASA answered the mandate by creating an agency plan entitled "NASA Plan for Increasing Access to the Results of Scientific Research" and associated policy, NPD 2230.1, Research Data and Publication Access. Principles in NASA SMD Strategic Plan for Scientific Data and Computing: Continued free and open access to scientific data for any use. Improved ease of use and discoverability. Enhanced science applications and new use cases. Incorporates best practices and "state of the art" through partnerships. Earth Data and Systems are Evolving: Increasing archive and file sizes. More complicated data structures. More user-friendly and data services. What is the future direction?

Liu, Zhong↗
NASA NTRS1987

Ranger's Legacy

With its Landsat satellites, development of sensors, and advancement of processing techniques, NASA provided the initial technology base for another Earth-benefit application of image processing, Earth resources survey by means of remote sensing. Since each object has its own unique "signature," it is possible to distinguish among surface features and to generate computer-processed imagery identifying specific features of importance to resource managers. This capability, commercialized by Perceptive Scientific Instruments, Inc., offers practical application in such areas as agricultural crop forecasting, rangeland and forest management, land use planning, mineral and petroleum exploration, map making, water quality evaluation and disaster assessment. Major users of the technology have been federal, state, and local governments, but it is making its way into commercial operations, for example, resource exploration companies looking for oil, gas and mineral sources, and timber production firms seeking more efficient treeland management. Supporting both government and private users is a small industry composed of companies producing the processing hardware software. As is the case in the medical application, many of these companies are direct offspring of NASA's work.

Source record↗
NASA NTRS2013

Neutron Characterization for Additive Manufacturing

Oak Ridge National Laboratory (ORNL) is leveraging decades of experience in neutron characterization of advanced materials together with resources such as the Spallation Neutron Source (SNS) and the High Flux Isotope Reactor (HFIR) shown in Fig. 1 to solve challenging problems in additive manufacturing (AM). Additive manufacturing, or three-dimensional (3-D) printing, is a rapidly maturing technology wherein components are built by selectively adding feedstock material at locations specified by a computer model. The majority of these technologies use thermally driven phase change mechanisms to convert the feedstock into functioning material. As the molten material cools and solidifies, the component is subjected to significant thermal gradients, generating significant internal stresses throughout the part (Fig. 2). As layers are added, inherent residual stresses cause warping and distortions that lead to geometrical differences between the final part and the original computer generated design. This effect also limits geometries that can be fabricated using AM, such as thin-walled, high-aspect- ratio, and overhanging structures. Distortion may be minimized by intelligent toolpath planning or strategic placement of support structures, but these approaches are not well understood and often "Edisonian" in nature. Residual stresses can also impact component performance during operation. For example, in a thermally cycled environment such as a high-pressure turbine engine, residual stresses can cause components to distort unpredictably. Different thermal treatments on as-fabricated AM components have been used to minimize residual stress, but components still retain a nonhomogeneous stress state and/or demonstrate a relaxation-derived geometric distortion. Industry, federal laboratory, and university collaboration is needed to address these challenges and enable the U.S. to compete in the global market. Work is currently being conducted on AM technologies at the ORNL Manufacturing Demonstration Facility (MDF) sponsored by the DOE's Advanced Manufacturing Office. The MDF is focusing on R&D of both metal and polymer AM pertaining to in-situ process monitoring and closed-loop controls; implementation of advanced materials in AM technologies; and demonstration, characterization, and optimization of next-generation technologies. ORNL is working directly with industry partners to leverage world-leading facilities in fields such as high performance computing, advanced materials characterization, and neutron sciences to solve fundamental challenges in advanced manufacturing. Specifically, MDF is leveraging two of the world's most advanced neutron facilities, the HFIR and SNS, to characterize additive manufactured components.

Watkins, Thomas↗
NASA NTRS1997

Propulsion Flight Research at NASA Dryden From 1967 to 1997

From 1967 to 1997, pioneering propulsion flight research activities have been conceived and conducted at the NASA Dryden Flight Research Center. Many of these programs have been flown jointly with the United States Department of Defense, industry, or the Federal Aviation Administration. Propulsion research has been conducted on the XB-70, F-111 A, F-111E, YF-12, JetStar, B-720, MD-11, F-15, F- 104, Highly Maneuverable Aircraft Technology, F-14, F/A-18, SR-71, and the hypersonic X-15 airplanes. Research studies have included inlet dynamics and control, in-flight thrust computation, integrated propulsion controls, inlet and boattail drag, wind tunnel-to-flight comparisons, digital engine controls, advanced engine control optimization algorithms, acoustics, antimisting kerosene, in-flight lift and drag, throttle response criteria, and thrust-vectoring vanes. A computer-controlled thrust system has been developed to land the F-15 and MD-11 airplanes without using any of the normal flight controls. An F-15 airplane has flown tests of axisymmetric thrust-vectoring nozzles. A linear aerospike rocket experiment has been developed and tested on the SR-71 airplane. This paper discusses some of the more unique flight programs, the results, lessons learned, and their impact on current technology.

Burcham, Frank W., Jr.↗
NASA NTRS1995

Investigation of wing upper surface flow-field disturbance due to NASA DC-8-72 in-flight inboard thrust-reverser deployment

An investigation of the wing upper surface flow-field disturbance due to in-flight inboard thrust reverser deployment on the NASA DC-8-72, which was conducted cooperatively by NASA Ames, the Federal Aviation Administration (FAA), McDonnell Douglas, and the Aerospace Industry Association (AIA), is outlined and discussed in detail. The purpose of this flight test was to obtain tufted flow visualization data which demonstrates the effect of thrust reverser deployment on the wing upper surface flow field to determine if the disturbed flow regions could be modeled by computational methods. A total of six symmetric thrust reversals of the two inboard engines were performed to monitor tuft and flow cone patterns as well as the character of their movement at the nominal Mach numbers of 0.55, 0.70, and 0.85. The tufts and flow cones were photographed and video-taped to determine the type of flow field that occurs with and without the thrust reversers deployed. In addition, the normal NASA DC-8 onboard Data Acquisition Distribution System (DADS) was used to synchronize the cameras. Results of this flight test will be presented in two parts. First, three distinct flow patterns associated with the above Mach numbers were sketched from the motion videos and discussed in detail. Second, other relevant aircraft parameters, such as aircraft's angular orientation, altitude, Mach number, and vertical descent, are discussed. The flight test participants' comments were recorded on the videos and the interested reader is referred to the video supplement section of this report for that information.

Hamid, Hedayat U.↗
NASA NTRS2000

Web Exploration Tools for a Fast Federated Optical Survey Database

We implemented several new web-based tools to improve the efficiency and versatility of access to the APS Catalog of the POSS I (Palomar Observatory-National Geographic Sky Survey) and its associated image database. The most important addition was a federated database system to link the APS Catalog and image database into one Internet-accessible database. With the FDBS, the queries and transactions on the integrated database are performed as if it were a single database. We installed Myriad the FDBS developed by Professor Jaideep Srivastava and members of his group in the University of Minnesota Computer Science Department. It is the first system to provide schema integration, query processing and optimization, and transaction management capabilities in a single framework. The attached figure illustrates the Myriad architecture. The FDBS permits horizontal access to the data, not just vertical. For example, for the APS, queries can be made not only by sky position, but also by any parameter present in either of the databases. APS users will be able to produce an image of all the blue galaxies and stellar sources for comparison with x-ray source error ellipses from AXAF (X Ray Astrophysics Facility) (Chandra) for example. The FDBS is now available as a beta release with the appropriate query forms at our web site. While much of our time was occupied with adapting Myriad to the APS environment, we also made major changes in Star Base, our DBMS for the Catalog, at the web interface to improve its efficiency for issuing and processing queries. Star Base is now three times faster for large queries. Improvements were also made at the web end of the image database for faster access; although work still needs to be done to the image database itself for more efficient return with the FDBS. During the past few years, we made several improvements to the database pipeline that creates the individual plate databases queries by StarBase. The changes include improved positions especially for galaxies, using a new median centroider and integrated magnitudes for galaxies with an improved density-to-intensity calibration with a "sky" background subtraction. In the original version of StarBase the object classification fainter than 19.5-20.0 mag., was an extrapolation of the networks trained on brighter objects. We have used a new catalog of galaxies at the NGP to train a neural network on objects fainter than 20th mag. This improved classification is used in the new version of StarBase. We have also added a FITS table option for the returned data from queries on the object catalog. The APS image database includes images in both colors so we have added a tool for querying the image database in both colors simultaneously. The images can be displayed in parallel or blinked for comparison.

Humphreys, Roberta M.↗
NASA NTRS1995

An Improved Ionospheric Correction Method for Wide-Area Augmentation Systems

A powerful approach for generating ionospheric corrections in wide area differential GPS applications has been developed, that can be applied to the Federal Aviation Administration's Wide Area Augmentation System (WAAS). This approach has been used to support ionospheric calibration for NASA's Deep Space Network and will be supporting real-time operations for global ionospheric specification and, possibly, single-frequency satellite altimeter calibration. It is a real-time, grid-based technique relying on a computationally efficient Kalman-type filter to produce accurate, smoothly varying ionospheric correction maps over the coverage area. Formal error maps are also computed, providing vertical delay errors over the WAAS grid, which are useful in integrity monitoring. This solution to the ionospheric correction problem is self-calibrating, since GPS transmitter inter-frequency biases are obtained as a by-product of the mapping procedure. This contrasts with other techniques in which bias values must be provided from some additional source.

Wide-Area↗
DOE OSTI2023

The deal.II Library, Version 9.5

Here, this paper provides an overview of the new features of the finite element library deal.II, version 9.5.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Scaling HPC Education

Throughout the cyberinfrastructure community there are a large range of resources available to train faculty and young scholars about successful utilization of computational resources for research. The challenge that the community faces is that training materials abound, but they can be difficult to find, and often have little information about the quality or relevance of offerings. Building on existing software technology, we propose to build a way for the community to better share and find training and education materials through a federated training repository. In this scenario, organizations and authors retain physical and legal ownership of their materials by sharing only catalog information, organizations can refine local portals to use the best and most appropriate materials from both local and remote sources, and learners can take advantage of materials that are reviewed and described more clearly. In this paper, we introduce the HPC ED pilot project, a federated training repository that is designed to allow resource providers, campus portals, schools, and other institutions to both incorporate training from multiple sources into their own familiar interfaces and to publish their local training materials.

community engagement↗