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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 883 records · Page 49
All sourcesNASA NTRSDOE OSTI
NASA NTRS1975

Pioneer 7 observations of plasma flow and field reversal regions in the distant geomagnetic tail

The present paper gives the results of an extensive analysis of plasma and magnetic-field data from Pioneer 7 taken in the geomagnetic tail approximately 1000 earth radii downstream from earth. The principal observations are: (1) measurable fluxes of protons in the tail, flowing away from earth, sometimes with a double-peaked velocity distribution; (2) field reversal regions in which the field changes from radial to antiradial by a vector rotation in the north-south plane; and (3) general characteristics of the tail similar to those observed near earth with good correlation between taillike magnetic fields and plasma.

Walker, R. C.↗
NASA NTRS1984

Particle and field characteristics of the high-latitude plasma sheet boundary layer

Particle and field data obtained by eight ISEE spacecraft experiments are used to define more precisely the characteristics of the high-latitude boundary region of the plasma sheet. A region immediately adjacent to the high-latitude plasma sheet boundary has particle and field characteristics distinctly different from those observed in the lobe and deeper in the central plasma sheet. Electrons over a broad energy interval are 'field-aligned' and bidirectional, whereas in the plasma sheet the distributions are more isotropic. The region supports intense ion flows, large-amplitude electric fields, and enhanced broad-band electrostatic noise.

Parks, G. K.↗
NASA NTRS1993

A relationship between potential vorticity and zonal wind on Jupiter

We present evidence from analysis of Voyager data and numerical experiments that in Jupiter's troposphere at midlatitudes the potential vorticity is given simply by the reciprocal of the streamfunction. This relationship agrees with the results of a vortex-tube stretching analysis of the Voyager wind-field data of the Great Red Spot and White Oval BC, whereas other published models do not. The derivative of streamfunction with respect to potential vorticity is negative definite, and in the quasigeostrophic limit the relationship is neutrally stable with respect to Arnold's second stability theorem. Numerical experiments indicate that the relationship is also neutrally stable in the primitive shallow-water system. This resolves a long-standing question as to how Jupiter's cloud-top winds are able to violate the Rayleigh-Kuo stability criterion, and constrains the two-layer model to a single free parameter.

Dowling, Timothy E.↗
NASA NTRS2007

Short-Term Forecasting of Radiation Belt and Ring Current

A computer program implements a mathematical model of the radiation-belt and ring-current plasmas resulting from interactions between the solar wind and the Earth s magnetic field, for the purpose of predicting fluxes of energetic electrons (10 keV to 5 MeV) and protons (10 keV to 1 MeV), which are hazardous to humans and spacecraft. Given solar-wind and interplanetary-magnetic-field data as inputs, the program solves the convection-diffusion equations of plasma distribution functions in the range of 2 to 10 Earth radii. Phenomena represented in the model include particle drifts resulting from the gradient and curvature of the magnetic field; electric fields associated with the rotation of the Earth, convection, and temporal variation of the magnetic field; and losses along particle-drift paths. The model can readily accommodate new magnetic- and electric-field submodels and new information regarding physical processes that drive the radiation-belt and ring-current plasmas. Despite the complexity of the model, the program can be run in real time on ordinary computers. At present, the program can calculate present electron and proton fluxes; after further development, it should be able to predict the fluxes 24 hours in advance

Fok, Mei-Ching↗
NASA NTRS2022

Revisiting the Ground Magnetic Field Perturbations Challenge: A Machine Learning Perspective

Forecasting ground magnetic field perturbations has been a long-standing goal of the space weather community. The availability of ground magnetic field data and its potential to be used in geomagnetically induced current studies, such as risk assessment, have resulted in several forecasting efforts over the past few decades. One particular community effort was the Geospace Environment Modeling (GEM) challenge of ground magnetic field perturbations that evaluated the predictive capacity of several empirical and first principles models at both mid- and high-latitudes in order to choose an operative model. In this work, we use three different deep learning models-a feed-forward neural network, a long short-term memory recurrent network and a convolutional neural network-to forecast the horizontal component of the ground magnetic field rate of change (dB H /dt) over 6 different ground magnetometer stations and to compare as directly as possible with the original GEM challenge. We find that, in general, the models are able to perform at similar levels to those obtained in the original challenge, although the performance depends heavily on the particular storm being evaluated. We then discuss the limitations of such a comparison on the basis that the original challenge was not designed with machine learning algorithms in mind.

Victor A. Pinto↗
NASA NTRS1982

Plasma and magnetic field characteristics of magnetic flux transfer events

Plasma and magnetic field data from ISEE 1 and 2 are examined for 5 passes of the magnetopause region at 20 and 40 deg northern latitudes, and are presented in terms of moments of the distribution function, calculated from two-dimensional or three-dimensional data. Flux transfer events are characterized by a mixture of magnetosheath and magnetospheric particles, which supports the hypothesis that flux transfer events represent encounters of reconnected flux tubes. An excess pressure appears to be balanced by the tension of the ambient magnetic field lines as they are draped around the reconnected flux tube, and the different observed magnetic field signatures are consistent with expectations for encounters of the flux tubes at different relative locations. It is suggested that increased flow speeds are caused by continued reconnection at the low-latitude boundaries of the flux tubes.

Paschmann, G.↗
NASA NTRS1982

Interplanetary magnetic field control of high-latitude activity on July 29, 1977

Multisatellite particle and magnetic field data for the substorms of July 29, 1977, show auroral-like activity above 80 deg invariant latitude during the recovery period. The movement of auroral zone activity to high latitudes followed the substorm sequence, at which time the inferred interplanetary magnetic field (IMF) was strongly northward. Electron energy spectra indicative of a field-aligned potential drop, and the absence of supporting precipitating ions, are found at latitudes greater than 80 deg. The north-south symmetry of these observations suggests that the events are on closed field lines. It is noted the very strong northward IMF connected to the sunward tilted geomagnetic dipole field plays a role in the driving of strong Birkeland and ionospheric current systems in the northern polar regions, while eliminating them from the southern polar regions.

Zanetti, L. J.↗
NASA NTRSDate not supplied

Thermal Data-driven Model Reduction for Enhanced Battery Health Monitoring

Electric aviation faces a major challenge of avoiding potentially catastrophic consequences of the battery’s thermal runaway while keeping the weight of the battery low. Detection of early warning signals of battery failures requires accurate monitoring of the battery’s health throughout its lifespan. However, identifying the parameters of the battery from field data is notoriously difficult. We investigate this problem within the framework of modeling the temperature dynamics of a Li-ion cell during tests simulating loading in electric aircraft flights. It is found that the parameters of a higher-fidelity physics-based thermal model cannot be identified from the simulated flight data. To resolve this issue, we reduce the higher-fidelity thermal model to a model with fewer parameters. The resulting reduced-order model can predict temperature dynamics accurately and is identifiable throughout the cell’s lifespan which allows using the model’s parameters to monitor the state-of-health of the aging cell and detect anomalies in thermal behavior.

Li ion batteries↗
NASA NTRS1992

The dynamic cusp

Results of a study of satellite and ground-based data acquired near the dayside cusp during a period when the IMF was inferred to have a strong northward component are presented. The presence of Pc 1 bursts, Pc 4-5 pulsations, and a tailward traveling twin vortex pattern of ionospheric convection suggests that the magnetosphere may have been temporarily compressed. Magnetic field data acquired at a synchronous altitude from GOES 5 and on the ground from Huanacayo support this suggestion. Plasma with ion dispersion characteristics associated with a cusp during southward IMF was detected by Viking over a 3.5-deg range of latitude. The presence of standing Alfven waves and ring current ions suggests that this 'cusplike' plasma was observed on closed geomagnetic field lines. It is suggested that the magnetosphere, during a northward IMF, is temporarily compressed by a solar wind pressure enhancement that produces the Pc 1 bursts, Pc 4-5 pulsations, and ionospheric vortices.

Potemra, T. A.↗
DOE OSTI2020

Methane Emissions from Gathering Compressor Stations in the U.S.

Using results from a nationally representative measurement campaign at 180 gathering compressor stations conducted with nine industry partners, this study estimated emissions for the U.S. gathering sector, where sector-specific emission factors have not been previously available. The study drew from a partner station population of 1705 stations—a significantly larger pool than was available for prior studies. Data indicated that whole gas emission rates from components on gathering stations were comparable to or higher than emission factors utilized by the EPA’s greenhouse gas reporting program (GHGRP) but less than emission factors used for similar components on transmission compressor stations. Field data also indicated that the national population of stations likely has a higher fraction of smaller stations, operating at lower throughput per station, than the data used to develop the per-station emission factor used in EPA’s greenhouse gas inventory (GHGI). This was the first national study to incorporate extensive activity data reported to the GHGRP, including 319 basin-level reports, covering 15,895 reported compressors. Further, combining study emission data with 2017 GHGRP activity data, the study indicated statistically lower national emissions of 1290 [1246–1342] Gg methane per year or 66% [64–69%] of current GHGI estimates, despite estimating 17% [12–22%] more stations than the 2017 GHGI (95% confidence interval). Finally, we propose a replicable method that uses GHGRP activity data to annually update GHGI gathering and boost sector emissions.

03 NATURAL GAS↗
NASA NTRS1989

ARCS 3 ionospheric artificial argon ion beam injections - Waves near the heavy ion gyrofrequencies

Low-frequency electric field data below the proton gyrofrequency are presented for the duration of the argon ion beam experiment conducted as part of the Argon Release for Controlled Studies (ARCS) program. An argon ion beam was injected from the subpayload antiparallel or perpendicular to the magnetic field at altitudes from 250 to 405 km. During the injections, the wave spectra were broadband near the subpayload and narrow-band near heavy ion gyrofrequencies at perpendicular separation distances between 42 and 254 m. It is suggested that the narrow-band waves are associated with both the perpendicular argon ion beam and an unexpected flux of low-energy ions which peaked in energy near 15 eV and pitch angle near 90 deg with respect to the magnetic field.

Erlandson, R. E.↗
NASA NTRS1994

The relationship between the magnetic field in the Martian magnetotail and upstream solar wind parameters

Magnetic field data measured by the MAGMA instrument in the Martian magnetotail lobes are compared with the ram pressure of the upstream solar wind observed by the TAUS instrument in the circular orbits of the Phobos 2 spacecraft. High correlation was found between the magnetic field intensity in the Martian magnetotail lobes and the solar wind ram pressure. From this relationship the average flaring angle of the Martian magnetotail was determined as approximately 13 deg, and the average magnetosonic Mach number was estimated as approximately 5. The observed relationship between the Martian magnetotail magnetic field intensity and the solar wind magnetic field reflects the correlation of the solar wind magnetic field to the ram pressure providing a value of approximately 7 for the average Alfvenic Mach number. The flaring angle obtained for the Martian magnetotail was found to be an intermediate value between the flaring angle of the magnetotail of the Earth and that of Venus at comparable distances.

Rosenbauer, H.↗
NASA NTRS1979

Bumblebee program: Aerodynamic data. Part 3: Pressure fields at Mach numbers 1.5 and 2.0

A large amount of fundamental aerodynamic missile data, which were stored for a number of years at the Applied Physics Laboratory, are reported. Data that supplements the M = 2.0 flow field data are provided. The Mach number effect by means of pressure fields only, at M = 1.5 and 2.0, and at angles of attack up to 23 deg at a mid-body station where a wing might be located is described.

Barnes, G. A.↗
DOE OSTI2024

Efficient data-driven models for prediction and optimization of geothermal power plant operations

Increasing the capacity of geothermal energy as a renewable resource calls for development and deployment of efficient control and optimization technologies for geothermal power plants. A data-driven prediction and optimization model is presented as a cost-effective and efficient alternative to physics-based approach. The model predicts power output and operational cost by propagating the influence of control and disturbance variables within an artificial neural network (ANN). Numerical experiments with simulated and field data from a real geothermal power plant are first used to demonstrate the prediction performance of the ANN model. The model is then adopted to maximize the net predicted power production by automatically adjusting the working fluid circulation rate. The optimization performance of the model in evaluated using a thermodynamic flowsheet simulation model. The workflow is applied to model and control the effect of ambient temperature on an air-cooled binary cycle power plant, which is complex and costly to perform using a physics-based predictive model. As a result, the performance of the method is demonstrated by applying it to both simulated and field datasets from a binary cycle geothermal power plant.

15 GEOTHERMAL ENERGY↗
DOE OSTI2023

Rapid, Approximate Multi-Axis Vibration Testing [Thesis]

The aerospace industry uses vibration shaker tables to perform component durability testing. In these tests a component, piece of equipment, or entire system is attached to a shaker table where it is subjected to dynamic excitation. The goal is to understand how the article under test will perform in its service environment without having to run it through its entire service life via field testing. In a vibration test, an aerospace system or component is qualified if it is shown to survive a test meant to replicate its lifetime service conditions. The test is designed based on recorded field data. To develop a test, a system is taken through all of its intended environments, e.g., transportation, launch, and reentry. Acceleration data measured from these environments is then brought back to the lab and imported into a shaker table controller. The controller then drives a vibration test intended to mimic the acceleration conditions experienced by the system or specific components of the system in the field. However, it is often difficult to match the measured field response in a lab test. This is largely due to the test’s boundary conditions and excitation methods. In a lab test, a shaker table is the excitation source. The two most common shaker table types, differentiated by their number of independent degrees of freedom, are single-axis and multi-axis shaker tables. Multi-axis shakers have the ability to reproduce service environments more realistically, as real accelerations inevitably produce multiple degrees of freedom of excitation simultaneously. Figure 1 depicts a generic multi-axis testing setup on a three-axis shaker table. Often multi-axis tests use six-degree-of-freedom (6DOF) shaker tables. Yet multi-axis shakers are not yet common in the aerospace industry due in part to their high cost and the difficulty for shaker controllers to handle the added complexity. Single-axis shaker tables are much more common. They are not as expensive to purchase and have a wide range of control software options.

42 ENGINEERING↗
DOE OSTI2025

Reliable and Efficient Machine Learning (Final Technical Report)

Modern scientific experiments generate massive amounts of data at a pace much faster than humans can manually analyze. While machine learning has revolutionized commercial data analysis (such as recommending movies or recognizing faces), applying these tools to complex scientific discovery is challenging because scientific answers must be precise, interpretable, and adhere to physical laws. The research under this project aims to develop new mathematical tools and computer algorithms specifically designed for scientific applications. Major progress has been made in automatically cleaning and deconstructing messy experimental data, analyzing the visual information of physical phenomena, determining the underlying physical variables, and providing rig orous mathematical analysis of interesting algorithms and concepts widely used in machine learning. This project addressed the critical gap between our ability to generate massive scientific data and our ability to extract interpretable information from it. We established mathematical foundations for Scientific Machine Learning (SciML) aimed at effective data analytics and automated discovery. Our work focused on three core objectives: (1) developing reliable feature extraction methods for dynamic high-dimensional data, (2) establishing mathematical foundations for discovering dynamics via neural networks, and (3) creating rigorous optimization techniques for these models. Key outcomes come from two fronts. On the practical side, they include the development of algorithms that significantly enhance the extraction of signals from field data, as well as the capability to handle situations that exhibit smooth variations or physical stretching due to temperature changes. They also include the creation of an automated framework for discovering fundamental state variables from raw experimental data, demonstrating the ability to identify intrinsic physical dimensions without prior knowledge of the governing laws. On the theoretical front, the research results in theoretical advances in Optimal Transport, a widely used notion in SciML, specifically regarding functions with fixed-size nodal sets, provide sharp bounds relevant to uncertainty quantification. Meanwhile, the outcomes also include the establishment of convergence theories for nonlocal gradient descent methods, enabling robust optimization with noisy data in high-dimensional settings commonly encountered in scientific modeling. The project also helps creating opportunities to train the next generation of researchers, equipping them with the necessary technical skills for today’s workplace and preparing them for future advances.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1974

Average high latitude magnetic field - Variation with interplanetary sector and with season. II

Average high-latitude magnetic-field data from northern observatories are examined for three ranges of magnetic disturbance level, Kp = 1- to 1+, 2- to 3+ and greater than or equal to 4-. Except for 0 to 0800 hr MLT, 55 to 78 deg invariant latitude, during away interplanetary magnetic field sectors, the variations between season and sector have the same characteristics at all Kp ranges. Because the amplitude of sector differences is much larger at sunlit local times than in the midnight sector, it is concluded that the current system of Svalgaard (1973) is not adequate to describe the sector variations in magnetic disturbance. Other current systems are discussed briefly. The disturbance morphology and seasonal variation at all Kp levels confirms the results of previous studies which indicate that latitudinally broad current systems and nonionospheric sources are present in addition to latitudinally narrow electrojet currents.

Langel, R.↗
NASA NTRS1975

Applications of Landsat imagery to geological research in Minnesota

A large part of northeastern Minnesota north of Lake Superior was studied using Landsat images. The area is being studied for its intercontinental rift and for large, low grade, copper-nickel deposits. By using Landsat imagery in conjunction with field data, it is possible to develop a much higher level of continuity and structural resolution in interpretations of the bedrock geology. Preliminary results indicate that it is possible to distinguish various surficial morphological features such as the Vermilion and Highland moraines, the Toimi drumlin field, and an unnamed drumlin field apparently associated with the Highland moraine.

Weiblen, P. W.↗