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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 1,369 records · Page 76
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Digital Twin Technology for Safety, Security, and Training in Spent Nuclear Fuel Handling

The increasing complexity of spent nuclear fuel handling requires significant resources to ensure safety, security, and personnel training. As nuclear facilities have continued to advance in scale and technology, the integration of digital tools has become indispensable. Among these tools, digital twins, which are virtual models of physical systems, are emerging as invaluable tools for enhancing safety protocols, security measures, and training in the nuclear sector. These models were conceptualized in the Industry 4.0 revolution. Digital twins can process data from physical systems in real time (by using sensors), include multiple code packages to enable simulations of different physics applications, and even implement artificial intelligence or machine learning techniques for advanced data processing. Despite the advantages that digital twins provide, challenges still exist regarding their widespread implementation. For instance, data used by a digital twin must be accurate to ensure that the digital twin is accurately tuned. Furthermore, if insecure digital twins are targeted by hackers, then they can pose serious risks to the security and safety of nuclear facilities.

Digital twins↗
NASA NTRS2012

Acoustic Surveys of a Scaled-Model CESTOL Transport Aircraft in Static and Forward Speed Conditions

An 11% scale-model of a Cruise-Efficient Short Take-off and Landing (CESTOL) scalemodel test was recently completed. The test was conducted in the AEDC National Full-Scale Aerodynamic Complex (NFAC) 40- by 80-Foot Wind Tunnel at NASA Ames Research Center. The model included two over-wing pod-mounted turbine propulsion simulators (TPS). The hybrid blended wing-body used a circulation control wing (CCW) with leadingand trailing-edge blowing. The bulk of the test matrix included three forward velocities (40 kts, 60 kts, and 100kts), angle-of-attack variation between -5 and 25 , and CCW mass flow variation. Seven strut-mounted microphones outboard of the left wing provided source directivity. A phased microphone array was mounted outboard of the right wing for source location. The goal of this paper is to provide a preliminary look at the acoustic data acquired during the Advanced Model for Extreme Lift and Improved Aeroacoustics (AMELIA) test for 0 angle-of-attack and 0 sideslip conditions. Data presented provides a good overview of the test conditions and the signal-to-noise quality of the data. TPS height variation showed a difference of 2 dB to 3 dB due to wing shielding. Variation of slot mass flow showed increases of 12 dB to 26 dB above the airframe noise and the TPS increased the overall levels an additional 5 dB to 10 dB.

Burnside, Nathan↗
NASA NTRS1998

Variations in Atmospheric Water Vapor as Seen in Satellite Data and Model Reanalysis Fields

New data sets used to describe components of the hydrologic and energy cycles of the Earth system are currently being produced and disseminated through the NASA EOS DAACs and several data assimilation centers supported by such organizations as NASA and NOAA. These data sets incorporate hybrid data analysis schemes and portray satellite and radiosonde data combined in a diagnostic sense and in a forecast mode. There is a need to develop a better understanding of the accuracy and utility of these global, relatively long-term, datasets to describe components of the hydrologic cycle and to understand atmospheric moisture variability and its relation to climatological significant events Much progress has been made in the last ten years in the development of global atmospheric models and analysis of satellite data for global studies. The atmospheric models have improved in their ability to predict both short term and longer term weather events. This has been possible through better understanding of atmosphere dynamics and very rapid advances in computer technology. Over the same period, data assimilation methods have advanced and unconventional data sources such as aircraft and satellite data, drifting buoys, etc., can be assimilated at non-synaptic times. As a result of these improvements, comprehensive global atmospheric fields based on four-dimensional data assimilation methods now provide one of the most reliable methods for studying dynamical and physical behavior in the atmosphere.

Jedlovec, Gary J.↗
NASA NTRSDate not supplied

Development of Carbon Flux Model Using ABI Data Over the Conterminous US

The satellite-driven carbon flux estimation has been playing important role to estimate continental-scale carbon budget. One of the biggest recent advances in the satellite-driven carbon flux modeling is utilization of high-frequent geostationary satellites to estimate diurnal cycle in carbon fluxes. The satellite based carbon flux estimation used the polar orbiting satellite sensors (e.g., Moderate Resolution Imaging Spectroradiometer (MODIS)), which allow us to observe target regions only once during the day. The new generation of geostationary satellite sensors provide frequent observations, often less than every 10 minutes. Here, we use GOES Advanced Baseline Imager (ABI) data to estimate hourly NEE over the conterminous US. We used the Terrestrial Observation Prediction System (TOPS) model for estimating hourly NEE. TOPS is a diagnostic ecosystem process model that simulates the fluxes of carbon and water through vegetation in response to climate variability. For the climate input, we developed hourly climate data using the same algorithm with NASA Earth Exchange Gridded Daily Meteorology (NEX-GDM) datasets based on machine learning techniques. The hourly climate data includes precipitation, maximum temperature, minimum temperature, dew point temperature, and solar radiation were derived from the Geostationary observations. The spatial patterns of ecosystem parameters used in TOPS are optimized using satellite Solar Induced Fluorescence (SIF) data. The high frequency GPP estimations from geostationary satellite sensors make it comparable to the instantaneous SIF data than daily GPP. We also used Ameriflux data for optimization of model parameters and the validation of the output. The derived data addresses the diurnal dynamics of carbon cycling at large scales and should help in reducing the uncertainties in carbon budget studies.

geostationary satellite↗
DOE OSTI2021

Recent Advances in Machine Learning for Fiber Optic Sensor Applications

Over the last three decades, fiber optic sensors (FOS) have gained a lot of attention for their wide range of monitoring applications across many industries, including aerospace, defense, security, civil engineering, and energy. FOS technologies hold great promise to form the backbone for next‐generation intelligent sensing platforms that offer long‐distance, high‐accuracy, distributed measurement capabilities and multiparametric monitoring with resilience to harsh environmental conditions. The major limitations posed by FOS are 1) cross‐sensitivity, 2) enormous volume and large data generation, 3) low data processing speed, 4) degradation of signal‐to‐noise ratio over the fiber length, and 5) overall cost of sensor and interrogator systems. These challenges can be overcome by building advanced data analytics engines enabled by recent breakthroughs in machine learning (ML) and artificial intelligence (AI). This article presents a comprehensive review of recent studies that integrate ML and AI algorithms with FOS technologies. This review also highlights several FOS technology development directions that promise a significant impact on widespread use for several industrial applications, with an emphasis on energy systems monitoring. A perspective on future directions for further research development is also provided.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1974

Advanced processing and information extraction techniques applied to ERTS-1 MSS data

Conventional automatic data processing and information extraction techniques fall short of providing the information required by the user in some applications. For those cases, advanced techniques are needed to permit the extraction of the necessary information. Advanced techniques are described and examples of their application to ERTS-1 MSS data are provided. The techniques are designed to help overcome problems in location, mensuration, and classification accuracies which result from geometric distortions of the ERTS MSS data, the relatively coarse resolution of the sensor, and variations in atmospheric state over the region to be surveyed. It is shown that each of these factors can seriously degrade one's ability to extract necessary information. Further, it is shown that advanced techniques can alleviate the effects of these factors.

Malila, W. A.↗
NASA NTRS1976

Precipitation-attenuation studies based on measurements of ATS-6 20/30-GHz beacon signals at Clarksburg, Maryland

Radiometric sky temperature and minute precipitation measurements were intended to broaden the data base required to advance the understanding of the propagation characteristics of the earth-satellite path at frequencies over 10 GHz. Analyses of the data collected from the measurement program have established a detailed correlation between the satellite signal and the signals from auxiliary ground-based measurements. The indirectly derived statistics agreed reasonably well (or can be reconciled) with the earlier published results. The correlations may therefore be used for indirectly estimating long term cumulative attenuation statistics in the absence of direct satellite signal measurements.

Fang, D. J.↗
NASA NTRS1983

Development of aerodynamic prediction methods for irregular planform wings

A set of empirical methods was developed to predict low-speed lift, drag and pitching-moment variations with angle of attack for a class of low aspect ratio irregular planform wings suitable for application to advanced aerospace vehicles. The data base, an extensive series of wind-tunnel tests accomplished by the Langley Research Center of the National Aeronautics and Space Administration, is summarized. The approaches used to analyze the wind tunnel data, the evaluation of previously existing methods, data correlation efforts, and the development of the selected methods are presented and discussed. A summary of the methods is also presented to document the equations, computational charts and design guides which have been programmed for digital computer solution. Comparisons of predictions and test data are presented which show that the new methods provide a significant improvement in capability for evaluating the landing characteristics of advanced aerospace vehicles during the preliminary design phase of the configuration development cycle.

Benepe, D. B., Sr.↗
NASA NTRSDate not supplied

Phenomena Portal: Large- Scale Visual Exploration of Atmospheric Phenomena

The Earth science community is experiencing a high influx of remote sensing data due to recent advancements in sensor technology. This enables the community to extend their research on a larger scale than ever before. Unfortunately, traditional data processing techniques do not scale well to these new, high volume data sources. State-of-the-art machine learning (ML) pipelines have been proven to overcome these burdens in various other fields but are underexploited within the physical sciences community. Moreover, ML is reliant on labeled data, which is currently sparsely available, owing to the fact that ML adoption is still in the early stages within the Earth and atmospheric science communities. To address these issues, we developed the Phenomena Portal, a visual exploration tool that uses ML to detect various atmospheric phenomena on a global scale. This allows the Earth and atmospheric science communities to view trends of occurrences of phenomena, identify potential relationships between them, and analyze spatiotemporal patterns over time. These detections can also serve as initial labeled data for ML research pertaining to the respective phenomena. The tool also incorporates feedback from subject matter experts to further improve the model detection accuracy, thereby facilitating human-in-the-loop. This presentation will provide an overview of the ML model development and cloud deployment. We also discuss the capabilities of the user interface for displaying the detections.

Muthukumaran Ramasubramanian↗
NASA NTRS1983

Continental land cover classification using meteorological satellite data

The use of the National Oceanic and Atmospheric Administration's advanced very high resolution radiometer satellite data for classifying land cover and monitoring of vegetation dynamics over an extremely large area is demonstrated for the continent of Africa. Data from 17 imaging periods of 21 consecutive days each were composited by a technique sensitive to the in situ green-leaf biomass to provide cloud-free imagery for the whole continent. Virtually cloud-free images were obtainable even for equatorial areas. Seasonal variation in the density and extent of green leaf vegetation corresponded to the patterns of rainfall associated with the inter-tropical convergence zone. Regional variations, such as the 1982 drought in east Africa, were also observed. Integration of the weekly satellite data with respect to time produced a remotely sensed assessment of biological activity based upon density and duration of green-leaf biomass. Two of the 21-day composited data sets were used to produce a general land cover classification. The resultant land cover distributions correspond well to those of existing maps.

Tucker, C. J.↗
NASA NTRS1991

Hughes advanced nickel-cadmium batteries: An update

After delivering a significant data base on boilerplate and prototype advanced nickel cadmium (Ni/Cd) battery cells, Hughes decided to start using the Advanced Ni/Cd batteries on several of their flight programs. The advanced cell can been operated at 80 percent depth of discharge (DOD) for more than 10 years, and possibly 15 years, in geosynchronous earth orbit (GEO) applications. This cell offers an important weight saving over the standard Ni/Cd cell that is usually only operated at 50 to 60 percent DOD in GEO applications. The negative and positive electrodes are manufactured using electrochemical deposition methods which reduce the sinter corrosion problems encountered by the chemical deposition process used in the standard cells. The degradable nylon separators used in standard cells was replaced by polymer impregnated Zirconia separators.

Bogner, R. Sam↗
DOE OSTI2024

Assessment of Condition Monitoring Methods and Technologies for Inservice Inspection and Testing of Nuclear Power Plant Components

This report was prepared for the U.S. Nuclear Regulatory Commission (NRC) to explore the application of advanced technologies toward meeting the current and future regulatory requirements for maintenance and condition monitoring of structures, systems, and components. The advanced technologies considered in this work are advanced sensors and instrumentation, data analytics, machine learning and artificial intelligence (ML/AI), physics-based models, and digital twins (DT). The interest in the application of advanced technologies for condition monitoring in nuclear power plants continues to grow, and current and future licensees are expected to implement advanced technologies as part of their inservice inspection (ISI) and inservice testing (IST) programs. This report delineates the outcomes of an exploratory investigation into the implementation of advanced condition monitoring technologies to address ISI and IST requirements. A thorough review was conducted of the existing regulatory requirements for ISI and IST, along with an analysis of associated industry practices. Additionally, a state-of-the-art assessment was performed on advanced condition monitoring technologies frequently employed in non-nuclear sectors. This research incorporated two nuclear-specific case studies to illustrate the application of these technologies within the current nuclear fleet. The report provides an exhaustive discussion on the technical challenges, considerations, and opportunities associated with the deployment of advanced condition monitoring technologies. The following are key considerations in the application of advanced technologies for the ISI and IST of nuclear power plant components: • Developing adequate verification and validation procedures to confirm the functional and non-functional requirements, • Developing technical capabilities to conduct real-time asset condition monitoring, • Establishing guidance and protocol for modeling and simulation tools to continuously meet regulatory requirements, • Addressing trustworthiness, explainability, and interpretability of ML/AI methods, • Evaluating maintenance activities to maintain an adequate safety margin and avoid undesirable conditions, • Establishing cybersecure condition monitoring programs associated with a computer-based software system, and • Establishing standardized evaluation metrics for advanced condition monitoring programs. Interest in the use of advanced technologies for condition monitoring in ISI and IST programs continues to grow, and the technology is expected to experience rapid and wide industry adoption in the near future. Adoption of advanced technologies for condition monitoring could have novel and unique impacts on regulatory activities associated with ISI and IST programs. The NRC is continuing to explore the regulatory aspects of advanced technologies as part of ISI and IST programs by pursuing additional research in this technical area.

22 - GENERAL STUDIES OF NUCLEAR REACTORS↗
NASA NTRS2002

NASA planetary data: applying planetary satellite remote sensing data in the classroom

NASA supports several data archiving and distribution mechanisms that provide a means whereby scientists can participate in education and outreach through the use of technology for data and information dissemination. The Planetary Data System (PDS) is sponsored by NASA's Office of Space Science. Its purpose is to ensure the long-term usability of NASA data and to stimulate advanced research. In addition, the NASA Regional Planetary Image Facility (RPIF), an international system of planetary image libraries, maintains photographic and digital data as well as mission documentation and cartographic data.

Regional Plaentary Image Facility RPIF Planetary D↗
NASA NTRS1993

Advanced engine study program

A design and analysis study was conducted to provide advanced engine descriptions and parametric data for space transfer vehicles. The study was based on an advanced oxygen/hydrogen engine in the 7,500 to 50,000 lbf thrust range. Emphasis was placed on defining requirements for high-performance engines capable of achieving reliable and versatile operation in a space environment. Four variations on the expander cycle were compared, and the advantages and disadvantages of each were assessed. Parametric weight, envelope, and performance data were generated over a range of 7,500 to 50,000 lb thrust and a wide range of chamber pressure and nozzle expansion ratio.

Masters, A. I.↗
NASA NTRS2023

Research and Technology Challenges for Human Data Analysts in Future Safety Management Systems

Enabling new and novel concepts of operations for Advanced Air Mobility poses an important need to evolve current safety management systems (SMS) and is posited to be realized through advances in Machine Learning (ML) Data Sciences and Artificial Intelligence. The “In-time Aviation Safety Management System” (IASMS) concept of operations supports the need to evolve today’s SMS to become more tailorable, scalable, and interoperable in response to forecasted changes expected for the future airspace system. Key to IASMS is integration of proactive and predictive ML algorithms trained to provide “in time” detection and mitigation of hazards and emergent risks through new methods and novel data types. IASMS research and technology development includes human factors design considerations for these systems to include human-system teaming, innovations in human interfaces and management of complex digital data information, human-system interaction/model-based system engineering, and verification and validation for data assurance and trust.

Chad L Stephens↗
DOE OSTI2025

Position Papers for Inverse Methods for Complex Systems under Uncertainty Workshop

The ability to solve inverse problems – inferring unknown parameters, structures, or states of a system from observed data – is essential for advancing scientific discovery and innovation capabilities for the DOE mission. Basic research needs and challenges are particularly acute in emerging areas such as the interactive, data-driven, modeling and simulation of digital twins; decision support for experiments at DOE scientific user facilities; and for other complex systems and workflows. Inverse problems are at the heart of understanding and controlling complex systems due to factors such as observational data with varying modalities and fidelities, inherent uncertainties in physical measurements and numerical models, and the computational demands of rapid and high-fidelity simulations. The convergence of recent scientific computing trends – scientific machine learning, artificial intelligence, and computing advances such as exascale computing – is creating unprecedented opportunities. These advancements offer the potential to revolutionize how we approach inverse problems to extract actionable insights with the required level of accuracy and computational efficiency. This workshop and the Call for Position Papers are vital steps in bringing together experts to collectively explore and identify the new computational and mathematical directions needed in inverse methods for complex systems under uncertainty.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Photo- and Electrocouplings of Nucleon Resonances

Advances in the exploration of the spectrum and structure of the excited states of the nucleon from experiments with electromagnetic probes on proton targets are presented here. Impressive progress has been achieved in the studies of exclusive meson photoproduction in experiments with continuous electron beams and with detectors of almost 4π acceptance. The high-quality data, coupled with the advances in the amplitude analyses of exclusive photo- and hadroproduction data, allow for the observation of several long-awaited new baryon states known previously as the “missing” resonances. Studies of exclusive meson electroproduction in the resonance region with the CLAS detector at JLab have provided the dominant part of the available world information on exclusive meson electroproduction observables. These data offer unique information on the structure of most well-established excited nucleon states in the mass region up to 1.8 GeV in terms of the evolution of their electroexcitation amplitudes with momentum transfer of the virtual photon. We discuss the impact of these results on the insight into the strong interaction dynamics that underlie the generation of the full spectrum of nucleon resonances of distinctively different structure. These results shed light on the emergence of hadron mass, which is one of the most important and still open problems in the Standard Model. The extension of the nucleon resonance stud

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2021

Geophysical Retrievals in an Artificial Intelligence (AI) Framework for Illuminating Processes Controlling Water Cycle

Focal Area(s): This white paper responds to Focal Area #3: Insight gleaned from complex data (both observed and simulated) using AI, big data analytics, and other advanced methods, including explainable AI and physics- or knowledge-guided AI. Science Challenge: This white paper addresses the water-cycle and data-model integration grand challenge. It leverages data from the Atmospheric Radiation Measurement (ARM) Climate Research Facility, and Next-Generation Ecosystem Experiment (NGEE), and Science Focus Area (SFA). The white paper focuses on controlling cloud, precipitation, and radiative properties as observed and simulated by the Earth System Models (ESM). The described framework can be readily applied to any other ensemble of instruments, including satellites and other ground-based networks.

54 ENVIRONMENTAL SCIENCES↗