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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 775 records · Page 43
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Deploying Automation Technology Supporting Packaging and Transportation Operations

Various United States Department of Energy (DOE) sites are investigating the deployment of robotics to provide safer, effective, and more efficient operations. By implementing robotics in packaging and transportation operations, improvements toward production efficiency, worker ergonomics, radiological dose reduction, and security assurance can be realized. Robotic Systems must be designed and implemented in concert with a facility’s safety basis, classification, and security constraints, while improving overall operational effectiveness. The desired robotic implementation should provide a path to potential long-term cost savings, reduce/eliminate hazardous conditions and radiological exposure, while improving quality and reliability of an operation process. The Savannah River Site (SRS), a DOE Site located in Aiken South Carolina, has initiated several large scale projects supporting future nuclear material disposition activities. Incorporation of automation and robotic equipment in system designs will support effective and efficient material handling operations, including container movements and packaging activities. Robotic systems will execute tasks that are precise, procedural and integrated with control systems to verify and record data for material inventory and historical archiving. An overview of the current robotic system development to perform receipt inspection, packaging, storage and shipment preparation activities of designated Type A and B shipping packages will be presented.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
NASA NTRS1983

The structure of a separating turbulent boundary layer. IV - Effects of periodic free-stream unsteadiness

Measurements were obtained of the sinusoidal unsteadiness of the free stream velocity during the separation of the turbulent boundary layer. Data were gathered by single wire and cross-wire, anemometry upstream of flow detachment, by laser Doppler velocimetry to detect the movement of the flow in small increments, and by a laser anemometer in the detached zone to measure turbulence and velocities. The study was restricted to a sinusoidal instability frequency of 0.61 and a ratio of oscillation amplitude to mean velocity of 0.3. Large amplitude and phase variations were found after the detachment, with unsteady effects producing hysteresis in the relationships between flow parameters. The detached shear layer decreased in thickness with increasing free-stream velocity and increases in the Reynolds shear stress. Deceleration of the free stream velocity caused thickening in the shear layer and upstream movement of the flow reversal location. The results are useful for studies of compressor blade and helicopter rotors in transition.

Simpson, R. L.↗
NASA NTRS1990

A continuous proportional low-thrust propulsion system

Helium gas flows continuously from a low-temperature dewar supplying propellant for satellite thrusters. Thrust is obtained by movement of a spool located between two opposing nozzles, thus differentially restricting the helium flow. The design procedure and test results of a high bandwidth, low power, linear electromagnetic actuator for the pool movement are presented. Two mathematical models are used to describe the helium flow through the thruster under different flow conditions. The experimental data measured in the vacuum chamber and the computational results from the mathematical models are compared. The models agree with the experiment to 3 percent except near a Knudsen number of 1.

Chen, J.-H.↗
NASA NTRS1955

Effect of surface roughness on characteristics of spherical shock waves

An investigation has been conducted on a small-scale test layout in which direct observation of the shock wave movement with time could be made in order to determine the effects of surface roughness on the characteristics of spherical shock waves. Data were obtained with 15-gram pentolite charges at four heights of burst, both for a smooth surface and for a surface completely covered with pyramid-shaped roughness elements. The observations resulted in determinations of shock peak overpressure and Mach stem height as a function of distance for each test. Comparison of the smooth-surface data with those obtained for the extremely rough condition showed a small net effort of roughness on the shock peak overpressures at the surface for all burst heights, the effect being to lower the overpressures. The effect of surface roughness on the Mach stem formation and growth was to delay the formation at the greatest charge height and to lower the height of the Mach stem for all heights.Comparison of the free-air shock peak overpressures with larger scale data showed good similarity of the overpressure-distance relationships. The data did not fit a geometrical similarity parameter for the path of the triple point at different heights of burst suggested by other investigators. A simple similarity parameter (relating the horizontal distance to the theoretical point of Mach formation) was found which showed only a small influence of burst height on the path of the triple point. While the data presented provide knowledge of the effect of many surface-roughness elements on the overall shock characteristics, the data do not provide insight into the details of the air-flow characteristics along the surface, nor the relative contribution of individual roughness elements to the results obtained.

Huber, Paul W↗
NASA NTRS2019

Cognitive Communications for NASA Space Systems

The growing complexity of spacecraft constellations, communication relay offerings, and mission architectures drives the need for the development of autonomous communication systems. NASA has traditionally launched single spacecraft missions that are served by the Space Communication and Navigation (SCaN) program. Operations on SCaN networks are typically scheduled weeks in advance, and often each asset serves a single user spacecraft at a time. Recent movement towards swarm missions could make the current approach unsustainable. Additionally, the integration of commercial communication service providers will substantially increase the data transfer options available to new missions. NASA science missions have found benefit in launching swarms of spacecraft, allowing coordinated simultaneous observations from different perspectives. Inter-spacecraft communication (mesh networking) is an enabler for this architecture, as are CubeSats that allow cost-effective provisioning of distributed mission assets. As more complex swarm missions launch, one challenge is coordinating communication within the swarm and choosing the appropriate mechanism for telemetry, tracking, control, and data services to and from Earth. Cognitive communications research conducted by SCaN aims to mitigate the increasing communication complexity for mission users by increasing the autonomy of links, networks, and service scheduling. By considering automation techniques including recent advances in artificial intelligence and machine learning, cognitive algorithms and related approaches enable increased mission science return, improved resource utilization for service provider networks, and resiliency in unpredictable or unplanned environments. The Cognitive Communications Project at the NASA Glenn Research Center develops applications of data-driven, non-deterministic methods to improve the autonomy of space communication. The project emphasizes development of decentralized space networks with artificial intelligence agents optimizing communication link throughput, data routing, and system-wide asset management. This paper discusses the objectives, approaches, and opportunities of the research to address growing needs of the space communications community.

Chelmins, David↗
NASA NTRSDate not supplied

Climatic drivers of continental-scale bird migration in spring

Avian migration studies conventionally divide North America into three or four primary flyways.This strategy has been adopted for convenience or determined by the time-averaged movement patterns, so it may not adequately reflect the real temporal variability of bird migration phenology. Using a unique radar-based data set (NEXRAD) covering the contiguous U.S. (CONUS), and an objective regionalization approach, we have identified two regions with distinct interannual variability of spring migration. This two-region approach helped us to distinguish the climatic drivers of year-to-year variability specific to the western and eastern CONUS. For example, we identified an east-west dipole pattern in migratory behavior linked to atmospheric Rossby waves that appeared to be triggered by oceanic forcing in the tropical Pacific. Our results offer a new geographic framework that would facilitate exploring the climatic cues affecting the interannual variability of migration phenology at the continental scale.

Amin Dezfuli↗
DOE OSTI2022

Accurate and Rapid Forecasts for Geologic Carbon Storage via Learning-Based Inversion-Free Prediction

Carbon capture and storage (CCS) is one approach being studied by the U.S. Department of Energy to help mitigate global warming. The process involves capturing CO 2 emissions from industrial sources and permanently storing them in deep geologic formations (storage reservoirs). However, CCS projects generally target “green field sites,” where there is often little characterization data and therefore large uncertainty about the petrophysical properties and other geologic attributes of the storage reservoir. Consequently, ensemble-based approaches are often used to forecast multiple realizations prior to CO 2 injection to visualize a range of potential outcomes. In addition, monitoring data during injection operations are used to update the pre-injection forecasts and thereby improve agreement between forecasted and observed behavior. Thus, a system for generating accurate, timely forecasts of pressure buildup and CO 2 movement and distribution within the storage reservoir and for updating those forecasts via monitoring measurements becomes crucial. This study proposes a learning-based prediction method that can accurately and rapidly forecast spatial distribution of CO 2 concentration and pressure with uncertainty quantification without relying on traditional inverse modeling. The machine learning techniques include dimension reduction, multivariate data analysis, and Bayesian learning. The outcome is expected to provide CO 2 storage site operators with an effective tool for timely and informative decision making based on limited simulation and monitoring data.

58 GEOSCIENCES↗
DOE OSTI2025

Adoption of AI in the Utility T&D Sector: Use Cases, Consequence, Assessment and Benefits

Digital transformation and utilization of artificial intelligence (AI) in the electric grid are fundamentally changing the industry’s approach to common problems and enabling a broader paradigm shift in grid planning and operations. The change in approach is circularly both enabling and driving modernization, with load growth and reliable management of data center and AI infrastructure shifting away from planning approaches with relatively predictable behaviors and toward a mix of consumer and industrial choices that surpass human cognitive abilities to process. This movement has potential to condition humans to not understand the system on which the AI depends, while requiring it for development of the necessary infrastructure. Approaches which would address most likely grid conditions and events, such as faults, aging of equipment, and weather, now must also account for large loads which shift not based upon weather or time of day, but the computational load. Quantifying computational load is independent of the traditional grid forecasting variables, where a data center’s aggregate load is determined by user and AI system behavior and decoupled from normal grid planning and operations. AI is both the cause and solution for these challenges, with new grid planning tools integrating massive amounts of decisions into frameworks.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2023

Long-term sinking of nuclear waste canisters in salt formations by low-stress creep at high temperature

Abstract Rock salt has a self-sealing capacity, low permeability, and high thermal conductivity, making it a potential host for heat-generating nuclear waste. The feasibility of nuclear waste disposal within salt formations has been investigated mostly for small-sized canisters. Geologic disposal of larger-sized canisters originally designed for spent fuel storage and transportation has lately been examined as a cost-effective alternative. This raises questions about their long-term vertical movement due to their weight and high decay heat. Low-stress creep governs this movement; however, most salt constitutive models do not incorporate it. In this paper, the Norton and the WIPP creep models are compared with the Lux/Wolters/Lerche (LWL) model and a simpler model that combines linear and Norton creep laws (named combined creep model). The LWL and combined creep models consider pressure solution creep, though all incorporate dislocation creep. The models are first applied to creep tests under various stress levels. The LWL and the combined creep models results fit the experimental data well in both high and low stress ranges, whereas the Norton and WIPP models results only fit in higher-stress ranges. The different models are further applied for analyzing long-term canister movement. A sinking rate of $$-4.4\times 10^{-7}$$ - 4.4 × 10 - 7 mm/year was predicted using the Norton and WIPP models versus $$-2.1\times 10^{-2}$$ - 2.1 × 10 - 2 mm/year and $$-3.1\times 10^{-2}$$ - 3.1 × 10 - 2 mm/year using the LWL and the combined creep models, respectively. This comparative study confirms that creep models calibrated exclusively against high-deviatoric stress data might result in an inaccurate estimation of waste packages sinking rate in salt formations.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
NASA NTRS2016

An Integrated Gate Turnaround Management Concept Leveraging Big Data Analytics for NAS Performance Improvements

"Gate Turnaround" plays a key role in the National Air Space (NAS) gate-to-gate performance by receiving aircraft when they reach their destination airport, and delivering aircraft into the NAS upon departing from the gate and subsequent takeoff. The time spent at the gate in meeting the planned departure time is influenced by many factors and often with considerable uncertainties. Uncertainties such as weather, early or late arrivals, disembarking and boarding passengers, unloading/reloading cargo, aircraft logistics/maintenance services and ground handling, traffic in ramp and movement areas for taxi-in and taxi-out, and departure queue management for takeoff are likely encountered on the daily basis. The Integrated Gate Turnaround Management (IGTM) concept is leveraging relevant historical data to support optimization of the gate operations, which include arrival, at the gate, departure based on constraints (e.g., available gates at the arrival, ground crew and equipment for the gate turnaround, and over capacity demand upon departure), and collaborative decision-making. The IGTM concept provides effective information services and decision tools to the stakeholders, such as airline dispatchers, gate agents, airport operators, ramp controllers, and air traffic control (ATC) traffic managers and ground controllers to mitigate uncertainties arising from both nominal and off-nominal airport gate operations. IGTM will provide NAS stakeholders customized decision making tools through a User Interface (UI) by leveraging historical data (Big Data), net-enabled Air Traffic Management (ATM) live data, and analytics according to dependencies among NAS parameters for the stakeholders to manage and optimize the NAS performance in the gate turnaround domain. The application will give stakeholders predictable results based on the past and current NAS performance according to selected decision trees through the UI. The predictable results are generated based on analysis of the unique airport attributes (e.g., runway, taxiway, terminal, and gate configurations and tenants), and combined statistics from past data and live data based on a specific set of ATM concept-of-operations (ConOps) and operational parameters via systems analysis using an analytic network learning model. The IGTM tool will then bound the uncertainties that arise from nominal and off-nominal operational conditions with direct assessment of the gate turnaround status and the impact of a certain operational decision on the NAS performance, and provide a set of recommended actions to optimize the NAS performance by allowing stakeholders to take mitigation actions to reduce uncertainty and time deviation of planned operational events. An IGTM prototype was developed at NASA Ames Simulation Laboratories (SimLabs) to demonstrate the benefits and applicability of the concept. A data network, using the System Wide Information Management (SWIM)-like messaging application using the ActiveMQ message service, was connected to the simulated data warehouse, scheduled flight plans, a fast-time airport simulator, and a graphic UI. A fast-time simulation was integrated with the data warehouse or Big Data/Analytics (BAI), scheduled flight plans from Aeronautical Operational Control AOC, IGTM Controller, and a UI via a SWIM-like data messaging network using the ActiveMQ message service, illustrated in Figure 1, to demonstrate selected use-cases showing the benefits of the IGTM concept on the NAS performance.

Efficent ATM systems↗
NASA NTRS1993

Study of bubble behavior in weightlessness (effects of thermal gradient and acoustic stationary wave) (M-16)

The aim of this experiment is to understand how bubbles behave in a thermal gradient and acoustic stationary wave under microgravity. In microgravity, bubble or bubbles in a liquid will not rise upward as they do on Earth but will rest where they are formed because there exists no gravity-induced buoyancy. We are interested in how bubbles move and in the mechanisms which support the movement. We will try two ways to make bubbles migrate. The first experiment concerns behavior of bubbles in a thermal gradient. It is well known than an effect of surface tension which is masked by gravity on the ground becomes dominant in microgravity. The surface tension on the side of the bubble at a lower temperature is stronger than at a higher temperature. The bubble migrates toward the higher temperature side due to the surface tension difference. The migration speed depends on the so-called Marangoni number, which is a function of the temperature difference, the bubble diameter, liquid viscosity, and thermal diffusivity. At present, some experimental data about migration speeds in liquids with very small Marangoni numbers were obtained in space experiments, but cases of large Marangoni number are rarely obtained. In our experiment a couple of bubbles are to be injected into a cell filled with silicon oil, and the temperature gradient is to be made gradually in the cell by a heater and a cooler. We will be able to determine migration speeds in a very wide range of Marangoni numbers, as well as study interactions between the bubbles. We will observe bubble movements affected by hydrodynamical and thermal interactions, the two kinds of interactions which occur simultaneously. These observation data will be useful for analyzing the interactions as well as understanding the behavior of particles or drops in materials processing. The second experiment concerns bubble movement in an acoustic stationary wave. It is known that a bubble in a stationary wave moves toward the node or the loop according to whether its diameter is larger or smaller than that of the main resonant radius. In our experiment fine bubbles will be observed to move according to an acoustic field formed in a cylindrical cell. The existence of bubbles varies the acoustic speed, and the interactive force between bubbles will make the bubble behavior collective and complicated. This experiment will be very useful to development of bubble removable technology as well as to the understanding of bubble behavior.

Azuma, H.↗
NASA NTRS1993

The drift of Saturn's north polar spot observed by the Hubble Space Telescope

Polar projections of 50 images of Saturn at 889 nanometers and 25 images at 718 nanometers taken by the HST in November 1990, as well as three images at each wavelength taken in June 1991, have been examined. Among them, 31 show the north polar spot, which is associated with Saturn's polar hexagon, in locations suitable for measurement. The movement of the spot with respect to Saturn's system III rotation rate was studied. During the period of observation, the polar spot had first a short-term westward movement and then a long-term eastward drift. The rate of the long-term drift was -0.060 +/- 0.008 deg/day with respect to system III, approximately 50 percent greater than previously determined from Voyager. The original 1980 and 1981 Voyager data were combined with the new Hubble images to form an 11-yr baseline. The eastward drift over the longer period was -0.0569 degrees per day. The long-term drift could be due to uncertainty in the standard value of the internal rotation period. The short-term movement in November 1990 has a rate that is greater in magnitude but opposite in sign and probably represents a real, transient motion of the spot relative to the internal rotation system.

Caldwell, John↗
DOE OSTI2021

Improving Medication Regimen Recommendation for Parkinson’s Disease Using Sensor Technology

Parkinson’s disease medication treatment planning is generally based on subjective data obtained through clinical, physician-patient interactions. The Personal KinetiGraph™ (PKG) and similar wearable sensors have shown promise in enabling objective, continuous remote health monitoring for Parkinson’s patients. In this proof-of-concept study, we propose to use objective sensor data from the PKG and apply machine learning to cluster patients based on levodopa regimens and response. The resulting clusters are then used to enhance treatment planning by providing improved initial treatment estimates to supplement a physician’s initial assessment. We apply k-means clustering to a dataset of within-subject Parkinson’s medication changes—clinically assessed by the MDS-Unified Parkinson’s Disease Rating Scale-III (MDS-UPDRS-III) and the PKG sensor for movement staging. A random forest classification model was then used to predict patients’ cluster allocation based on their respective demographic information, MDS-UPDRS-III scores, and PKG time-series data. Clinically relevant clusters were partitioned by levodopa dose, medication administration frequency, and total levodopa equivalent daily dose—with the PKG providing similar symptomatic assessments to physician MDS-UPDRS-III scores. A random forest classifier trained on demographic information, MDS-UPDRS-III scores, and PKG time-series data was able to accurately classify subjects of the two most demographically similar clusters with an accuracy of 86.9%, an F1 score of 90.7%, and an AUC of 0.871. A model that relied solely on demographic information and PKG time-series data provided the next best performance with an accuracy of 83.8%, an F1 score of 88.5%, and an AUC of 0.831, hence further enabling fully remote assessments. These computational methods demonstrate the feasibility of using sensor-based data to cluster patients based on their medication responses with further potential to assist with medication recommendations.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS1985

Contributions on the Subject of Longitudinal Movements of Aircraft in Wind Shears

The effect of downburst-type wind shears on the longitudinal dynamic behavior of an unguided aircraft is simulated numerically on the basis of published meteorological data and the flight characteristics of an A300-B passenger jet. The nonlinear differential equations of the aircraft motion are linearized by conventional methods, and the wind effects are introduced via the linear derivatives of the wind components referred to the wind gradients to obtain simplified technical models of the longitudinal response to all possible types of constant-gradient wind shears during the first 20-60 sec. Graphs, maps, and diagrams are provided, and a number of accidents presumed to have involved wind shears are analyzed in detail.

Krauspe, P.↗
NASA NTRS1999

Interferometric Propagation Delay

Radar interferometry based on (near) exact repeat passes has lately been used by many groups of scientists, worldwide, to achieve state of the art measurements of topography, glacier and ice stream motion, earthquake displacements, oil field subsidence, lava flows, crop-induced surface decorrelation, and other effects. Variations of tropospheric and ionospheric propagation delays limit the accuracy of all such measurements. We are investigating the extent of this limitation, using data from the Shuttle radar flight, SIR-C, which is sensitive to the troposphere, and the Earth Resources Satellites, ERS-1/2, which are sensitive to both the troposphere and the ionosphere. We are presently gathering statistics of the delay variations over selected, diverse areas to determine the best accuracy possible for repeat track interferometry. The phases of an interferogram depend on both the topography of the scene and variations in propagation delay. The delay variations can be caused by movement of elements in the scene, by changes in tropospheric water vapor and by changes of the charge concentrations in the ionosphere. We plan to separate these causes by using the data from a third satellite visit (three-pass interferometry). The figure gives the geometry of the three-pass observations. The page of the figure is taken to be perpendicular to the spacecraft orbits. The three observational locations are marked on the figure, giving baselines B-12 and B-13, separated by the angle alpha. These parameters are almost constant over the whole scene. However, each pixel has an individual look angle, theta, which is related to the topography, rho is the slant range. A possible spurious time delay is shown. Additional information is contained in the original.

Goldstein, Richard↗
DOE OSTI2025

Using Temporal Information from Human Mobility Data to Detect Anchor Points

Spatiotemporal mobility data are available in massive quantities, but large quantities of data typically include fewer variables or data fields. Often, the only available fields are User ID, Longitude, Latitude, Timestamp (ULLT). This raises an important question: how much can we infer about human mobility patterns using only these four fields? With ULLT data, we do not know individuals' socioeconomic status information or when they are visiting their anchor points (AP) or locations (such as homes, places of employment, or schools), and it is a modern challenge to use this data to infer these characteristics. When detecting anchor locations with limited input information, verification and validation (VV) are significant challenges. This paper addresses the problem of identifying individuals' anchor locations using only temporal information from spatiotemporal datasets with limited attributes. Our approach does not explicitly use latitude and longitude during analysis. Locationbased information is only employed in the preprocessing stage to identify periods of movement (trips) and stops (dwelling). Beyond this step, all analysis is based on temporal patterns. In theory, if stops and dwell times could be detected through alternative means, our method could function entirely without location-based input. We demonstrate this methodology on the 2017 National Household Travel Survey (NHTS) data, because it includes a carefully designed and collected time use survey with representative sampling and labeled ground truth. The high-quality survey data allows us to test the accuracy of our methods because NHTS contains intended place labels and agent/user characteristics. We have also applied our validated AP identification algorithm on very large-scale GPS based trajectory data for Patterns-of-Life (PoL) assessment and other applications, but due to space limit that could not be presented here.

McBride, Liz [ORNL] (ORCID:0000000286925869)↗
DOE OSTI2021

Microstructural and infiltration properties of woven preforms during chemical vapor infiltration

Interface-resolved direct numerical simulations (DNSs) of chemical vapor infiltration (CVI) have been performed over a range of furnace-operating conditions (Thiele moduli) and for practical woven preform geometries. A level-set method is used to resolve the geometry of the initial preform at tow scale. The interface between the vapor and solid phase is then evolved in time through the entire CVI densification cycle, fully resolving the time-varying topology between the two phases. In contrast to previous level-set methods for CVI simulation, the physical reaction and diffusion processes govern the level-set movement in the current approach. The surface deposition kinetics is described by the usual one-step model. In this paper, the DNS data are used to study the evolving porosity, surface-to-volume ratio, and flow infiltration properties (permeability and effective diffusivities). Additionally, comparisons are made to popularly-assumed structure functions and the standard, Kozeny–Carmen porous media model commonly employed in modeled CFD simulations of CVI. The virtual DNS experiments reveal a Thiele modulus and preform geometry (fabric layup) dependence which the existing microstructural and infiltration models are not able to describe throughout the entire densification process. The DNS-based, woven geometry-specific correlations can be applied directly to mean-field, furnace-scale CFD simulations.

36 MATERIALS SCIENCE↗
NASA NTRS1973

Application of ERTS-1 imagery in coastal studies

The basic ERTS output is four black-and-white photographs presenting the same scene recorded in each multispectral scanner band. Mosaics covering large regions at a 1:250,000 scale can be compiled from these photographs. Office study of the image of each band separately, in combination with other bands, and in conjunction with other available data (navigation charts, tide tables, etc.) permits extraction of data useful in coastal engineering planning and coastal processes studies. Specific examples in which significant information on regional shoreline configuration or nearshore water movements has been obtained from unenhanced ERTS imagery are: (1) tidal inlet configuration; (2) navigation information; and (3) nearshore water movements.

Magoon, O. T.↗