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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 1,171 records · Page 65
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Leveraging a Southern California Energy Innovation Cluster to Pilot and Validate Emerging Energy Technologies

The EPIC Pilot Program, led by the Los Angeles Cleantech Incubator (LACI), was designed to help early-stage clean technology startups accelerate technical validation, investment readiness, and market entry. The project focused on supporting startups in designing and deploying small-scale pilots with the guidance of EPIC Partners, a network of regional stakeholders in the Southern California energy ecosystem, including but not limited to: the Los Angeles Department of Water and Power (LADWP), the California Energy Commission (CEC), Los Angeles County Metropolitan Transportation Authority (LA Metro), and Edison International, among others. Through mentorship, funding, and site access for technology deployments, the program provided a structured pathway for startups to test and refine their technologies in real-world settings.

14 SOLAR ENERGY↗
DOE OSTI2022

Integrated simulation, machine learning, and experimental approach to characterizing fracture instability in indentation pillar-splitting of materials

Measuring fracture toughness of materials at small scales remains challenging due to limited experimental testing configurations. A recently developed indentation pillar-splitting method has shown promise of improved flexibility in fracture toughness measurements at the microscale, partly due to the occurrence of an unusual fracture instability, i.e., a transition from stable to unstable crack propagation. In spite of growing interest in this method, the underlying mechanism of this phenomenon is yet to be elucidated. Furthermore, we provide a comprehensive description of fracture instability in indentation pillar-splitting by combining in situ experiments with high-fidelity simulations based on cohesive zone and J-integral methods. In addition, a machine-learning-based solution for predicting the critical indentation load of fracture instability is established through Gaussian processes regression for broad use of this method by the community.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Vitrification of High-Cr Glass in Research-Scale Melter

This test report describes the experimental results from a small-scale test using the research-scale melter (RSM) at Pacific Northwest National Laboratory to demonstrate processing of a high-Cr simulated feed stream, designated HLW-HCr-16. The RSM is a small, joule-heated melter capable of processing melter feed continuously. The melter is equipped with Inconel ® 693 electrodes, Monofrax ® K-3 refractory, and an Inconel 690 pour spout. An electric kiln surrounds the melter body and minimizes heat loss from the melter body during operation. The RSM is equipped with an offgas treatment system that employs quenching, wet scrubbing, and high-efficiency mist elimination. The glass-discharge section is heated to facilitate pouring of the glass. The melter is fitted with a melt cavity that is ~25 cm (10 in.) in diameter with a nominal glass depth of 8.9 cm (3.5 in.). The melter was operated with a target glass temperature of 1150°C and target plenum temperature between 550°C and 700°C for this test. The air bubbling rate was 4.2 L/min. Overall, during the continuous operation of the melter for ~ 103 hours, ~ 141 kg of glass was produced. At the conclusion of the test, the melter and exhaust lines were visually inspected for particulate deposition and corrosion. Entrained material had adhered to the underside of the melter lid and to the exhaust piping. Enrichments in elements such as Cl, F, B, K, Li, P, Na, and S were measured in these deposits through inductively coupled plasma–optical emission spectroscopy and X-ray fluorescence analysis. When the melter electrodes and air bubbler tube were removed from the glass in the RSM, the electrodes appeared discolored, but no significant loss of metal was observed. The processing of a high-Cr simulant, HLW-HCr-16, in the RSM produced glass at an average rate of 1.36 kg/h, equaling a melter-surface-area normalized glass generation rate of 654 kg/day/m 2 . The resulting glass met the toxicity characteristic leaching procedure requirement. Test results of crystallinity, electrical conductivity, and viscosity showed good processing properties of this high-Cr high-level waste glass. RSM offgas was also sampled and analyzed at periodic intervals during steady-state operating conditions. The total decontamination factor averaged by four sampling periods was 134. The concentrations of CO and NO x in emissions were 237 to 422 and 69 to 94 parts per million by volume, respectively.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
NASA NTRS2014

Characterization and Performance of a Kilo-TES Sub-Array for ACTPol

ACTPol is a polarization-sensitive receiver upgrade to the Atacama CosmologyTelescope (ACT) which will make millimeterwavelength measurements of the small-scale polarization anisotropies of the cosmic microwave background to investigate the properties of inflation, dark energy, dark matter, and neutrinos in the early Universe. ACTPol will employ three arrays of transition edge sensor (TES) bolometer detectors. The detectors, with a target transition temperature of 150 mK, will be operated at a bath temperature of 100 mK provided by a dilution refrigerator. One array operating at a central frequency of 150 GHz and consisting of 1024 TESes achieved first light at the ACT site in July 2013. We anticipate fielding the remainder of the focal plane, consisting of a second 150 GHz array and a multi-chroic array sensitive to 90 and 150 GHz, at the end of the 2013 observing season. In these proceedings, we present characterization of key detector parameters from measurements performed on the first array both in the lab and during initial field testing. We comment on the design goals, measurements, and uniformity of the detector transition temperatures, saturation powers, and thermal conductivities while detailing measurement methods and results for the detector optical efficiencies and time constants.

neutrinos↗
DOE OSTI2025

Symmetry structure of a Riccati equation appearing in penetration mechanics

In the design of projectile penetration experiments a matter of considerable interest is scaling: that is, the potential relevance of small-scale experiments to their full-scale counterparts, in a manner analogous to that most often encountered in the context of fluid mechanics. From the theoretical standpoint, phenomena associated with scaling and scalability can be assessed using the well-established tools of dimensional analysis and the Buckingham-Pi Theorem. However, the familiar precepts of dimensional analysis are themselves a specific manifestation of the broader group invariance properties or symmetries of a mathematical model. Here, this work explores these notions – that is, dimensional analysis, the conditions for realizing complete similarity, and any additional symmetry structures – in the context of a Riccati differential equation appearing in the context of penetration mechanics. The aim of the investigation is twofold: 1) to complement existing empirical considerations with a concrete theoretical basis, and 2) to provide a deeper theoretical understanding of the projectile penetration model and its many implications.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

Hierarchical-embedding autoencoder with a predictor as efficient architecture for learning time-evolution in multi-scale turbulent flows

We introduce a scale-aware, data-driven deep learning modeling framework for accurately predicting the time evolution of multi-scale turbulent plasma and liquid flows. The approach is motivated by the idea of scale separation. Structures of vastly different length scales emerge in these systems, and interactions between these structures occur only locally. To exploit this structure, the flow state is transformed by a hierarchical, fully convolutional autoencoder, not into a single embedding layer as in conventional convolutional surrogate models, but into a series of embedding layers. A stepwise training strategy ensures that fine-scale features are encoded on a high-resolution grid, while larger structures are represented on progressively coarser layers. The time evolution predictor advances all embedding layers in sync, capturing local interactions between features at the same scale as well as between all scales. This approach enables efficient modeling of multi-scale systems since negligible interactions between distant, small-scale structures do not need to be directly modeled. Our hierarchical-embedding autoencoder with a predictor framework is evaluated on canonical examples of multi-scale turbulence: two-dimensional Kolmogorov flow and Hasegawa–Wakatani plasma turbulence. In both cases, the proposed framework significantly improves predictive accuracy relative to conventional convolutional network architectures. A significant improvement in prediction accuracy was observed for crucial statistical characteristics of the Hasegawa–Wakatani plasma as well as for individual trajectories of the Kolmogorov flow turbulence. Importantly, the model's rollout for the Hasegawa–Wakatani problem demonstrates a four-order-of-magnitude speedup compared to traditional numerical solvers.

Khrabry, Alexander I. [Princeton Univ., NJ (United↗
DOE OSTI2023

Plasmoid-mediated reconnection during nonlinear peeling–ballooning edge-localized modes

Abstract Plasmoid-mediated reconnection is investigated for nonlinear peeling–ballooning edge-localized modes (P-B ELMs). The formation of current sheets and the transition to 3D current sheet instability is demonstrated through fully nonlinear resistive MHD simulations of P-B ELMs in DIII-D discharges. Large-scale axisymmetric current sheets, as well as small-scale poloidally extended current sheets, are formed as the coherent P-B ELM filaments nonlinearly evolve. It is observed that, at high Lundquist numbers, these current sheets break during a reconnection burst, i.e. a secondary exponential growth of intermediate modes followed by relaxation due to the suppression of P-B drive.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2026

Code for the manuscript "Lagrangian Attention Tensor Networks for Velocity Gradient Statistical Mode

We disclose a python/pytorch implementation of the physics-informed machine learning algorithm described in "Lagrangian Attention Tensor Networks for Velocity Gradient Statistical Modeling", LA-UR-24-30678. Direct numerical simulation (DNS) of ubiquitous turbulence phenomena is computationally infeasible for realistic flows. As a result, reduced modeling for turbulent flows aim to reduce the number of resolved scales while retaining accurate representations of the small-scale physics. The dynamics of the velocity gradient tensor (VGT) is a key ingredient in reduced or subgrid turbulence models. The evolution equation for the VGT involves nonlocal terms, requiring closure modeling. This implementation of the novel methodology of Lagrangian Attention Tensor Networks (LATN), utilizes a structured representation of the history of the VGT to inform a physics-informed machine learning algorithm. This addition of structured memory terms is shown to outperform previous models when trained and evaluated on DNS data.

Livescu, Daniel [LANL]↗
DOE OSTI2022

GLUE Code: A framework handling communication and interfaces between scales

Many scientific applications are inherently multiscale in nature. Such complex physical phenomena often require simultaneous execution and coordination of simulations spanning multiple time and length scales. This is possible by combining expensive small-scale simulations (such as molecular dynamics simulations) with larger scale simulations (such continuum limit/hydro solvers) to allow for considerably larger systems using task and data parallelism. However, the granularity of the tasks can be very large and often leads to load imbalance. Traditionally, we use approximations to streamline the computation of the more costly interactions and this introduces trade-offs between simulation cost and accuracy. In recent years, the available computational power and the advances in machine learning have made computing these scale-bridging interactions and multiscale simulations more feasible. One driving application has been plasma modeling in inertial confinement fusion (ICF), which is fundamentally multiscale in nature. This requires deep understanding of how to extrapolate microscopic information into macroscopically relevant scales. For example, in ICF one needs an accurate understanding of the connection between experimental observables and the underlying microphysics. The properties of the larger scales are often affected by the microscale behavior incorporated usually into the equations of state and ionic and electronic transport coefficients (Liboff, 1959; Rinderknecht et al., 2014; Rosenberg et al., 2015; Ross et al., 2017). Instead of incorporating this information using reliable molecular dynamics (MD) simulations, one often needs to use theoretical models, due to the inability of MD to reach engineering scales (Glosli et al., 2007; Marinak et al., 1998). One approach to resolve this issue is by coupling two MD simulations of different scales via force interpolation, e.g., the AdResS method (Krekeler et al., 2018; Nagarajan et al., 2013). Another approach, which we will pursue in the scope of this work, is by enabling scale bridging between MD simulations and meso/macro-scale models through the development and support of application programming interfaces that these different applications can interact through.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Department of Energy’s Atmospheric System Research (ASR) Program’s Workshop on the Future of Atmospheric Large Eddy Simulation (LES): Workshop Report

Large-eddy simulation (LES) is used as a tool to understand physical processes such as turbulence, aerosols, clouds, precipitation, radiation, the interactions among all these, and their interactions with the underlying surface. Over the next 10 years, LES will drive fundamental progress in open scientific questions in these areas as LES is increasingly used to gain understanding of complex interacting physical processes involving atmospheric turbulence. This growth will be driven both by scientific demand and the expansion of computational resources needed to conduct LES, and the form that the growth takes will largely be determined by how computational resources are leveraged for scientific gain. In particular, we suggest that computational resources are likely to be leveraged in two separate but not necessarily distinct ways. On one hand, growth in computational resources will allow LES to be made more routine, that is, performed more frequently, while on the other hand, the computational expense (measured in total floating point operations) afforded to individual LES will expand dramatically, allowing simulations to increase in both domain size and resolution as well as physical detail. Current U.S. Department of Energy (DOE) projects such as LES ARM Symbiotic Simulation and Observation Activity (LASSO) are leading the way in conducting routine LES, building large, public databases that are accessible for data science, sensitivity studies, and training for machine learning. LES will also become more routine as it becomes more accessible for individual researchers to address their scientific questions of interest. Scientific questions addressed by LES over the next 10 years are likely to include cloud organization and aggregation; aerosol cloud interactions and atmospheric chemistry (including geo-engineering); urban-scale LES; atmospheric extreme events, ranging from small-scale severe weather to wildfires; and ocean-wave-atmosphere interactions. Further LES-related research will likely grow significantly in areas related to societal impact studies of air quality and extreme weather events, applications to renewable energy forecasting and resource assessment, and aid in decision-making processes. The growth in the use of LES in atmospheric science research will drive the need for better physical process representations (e.g., cloud aerosol microphysics, radiation, and atmospheric chemistry) at the scales resolved by LES. To date, many of the process representations used by LES have been taken directly from coarser-resolution models. Promising methods for LES process representations include superdroplet and quadrature methods for microphysics, 3D approaches for radiation, and better representation of chemistry and aerosol processes. At LES resolution, land-atmosphere interactions for complex terrains, land cover/types, biogeochemistry, and plant canopy models are needed as an improvement beyond traditional and widely used Monin-Obuhkov similarity theory.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Department of Energy’s Atmospheric System Research (ASR) Program’s Workshop on the Future of Atmospheric Large Eddy Simulation (LES) (Workshop Report)

Large-eddy simulation (LES) is used as a tool to understand physical processes such as turbulence, aerosols, clouds, precipitation, radiation, the interactions among all these, and their interactions with the underlying surface. Over the next 10 years, LES will drive fundamental progress in open scientific questions in these areas as LES is increasingly used to gain understanding of complex interacting physical processes involving atmospheric turbulence. This growth will be driven both by scientific demand and the expansion of computational resources needed to conduct LES, and the form that the growth takes will largely be determined by how computational resources are leveraged for scientific gain. In particular, we suggest that computational resources are likely to be leveraged in two separate but not necessarily distinct ways. On one hand, growth in computational resources will allow LES to be made more routine, that is, performed more frequently, while on the other hand, the computational expense (measured in total floating point operations) afforded to individual LES will expand dramatically, allowing simulations to increase in both domain size and resolution as well as physical detail. Current U.S. Department of Energy (DOE) projects such as LES ARM Symbiotic Simulation and Observation Activity (LASSO) are leading the way in conducting routine LES, building large, public databases that are accessible for data science, sensitivity studies, and training for machine learning. LES will also become more routine as it becomes more accessible for individual researchers to address their scientific questions of interest. Scientific questions addressed by LES over the next 10 years are likely to include cloud organization and aggregation; aerosol cloud interactions and atmospheric chemistry (including geo-engineering); urban-scale LES; atmospheric extreme events, ranging from small-scale severe weather to wildfires; and ocean-wave-atmosphere interactions. Further LES-related research will likely grow significantly in areas related to societal impact studies of air quality and extreme weather events, applications to renewable energy forecasting and resource assessment, and aid in decision-making processes.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Airfoil Computational Fluid Dynamics - 2k shapes, 25 AoA's, 3 Re numbers

This dataset contains aerodynamic quantities - including flow field values (momentum, energy, and vorticity) and summary values (coefficients of lift, drag, and momentum) - for 1,830 airfoil shapes computed using the HAM2D CFD (computational fluid dynamics) model. The airfoil shapes were designed using the separable shape tensor parameterization that encodes two-dimensional shapes as elements of the Grassmann manifold. This data-driven approach learns two independent spaces of parameter from a collection of sample airfoils. The first captures large-scale, linear perturbations, and the second defines small-scale, higher-order perturbations. For this dataset, we used the G2Aero database of over 19,000 airfoil shapes to learn a parameter space that captured a wide array of shape characteristics. We sampled airfoil designs over both parameter spaces to explore the full range of possible shape variations. The aerodynamic quantities for the generated airfoil were obtained using the HAM2D code, which is a finite-volume Reynolds-averaged Navier-Stokes (RANS) flow solver. We employ a fifth-order WENO scheme for spatial reconstruction with Roe's flux difference scheme for inviscid flux and second-order central differencing for viscous flux. A preconditioned GMRES method is applied for implicit integration. The Spalart-Allmaras 1-eq turbulence model is used for the turbulence closure, and the Medida-Baeder 2-eq transition model is applied to account for the effects of laminar turbulent transition. The airfoil grid is generated with a total of 400 points on the airfoil surface, the initial wall-normal spacing of y+ = 1, and an outer boundary located at 300 chord lengths away from the wall. The CFD simulations are performed at a freestream Mach number of 0.1, for or three different Reynolds' numbers (3M, 6M, and 9M), and for 25 angles of attack from -4 deg. to 20 deg. with 1 degree increments. Across all these various parameters, this dataset includes the results from over 250,000 CFD simulations. The simulations were performed using the Bridges-2 system at the Pittsburgh Supercomputing Center in February 2023 as part of the INTEGRATE project funded by the Advanced Research Projects Agency - Energy, in the U.S. Department of Energy. The data was collected, reformatted, and preprocessed for this OEDI submission in July 2023 under the Foundational AI for Wind Energy project funded by the U.S. Department of Energy Wind Energy Technologies Office. This dataset is intended to serve as a benchmark against which new artificial intelligence (AI) or machine learning (ML) tools may be tested. Baseline AI/ML methods for analyzing this dataset have been implemented, and a link to their repository containing those models has been provided. The .h5 data file structure can be found in the GitHub Repository resource under explore_airfoil_2k_data.ipynb.

2k↗
DOE OSTI2023

Airfoil Computational Fluid Dynamics - 9k shapes, 2 AoA's

This dataset contains aerodynamic quantities - including flow field values (momentum, energy, and vorticity) and summary values (coefficients of lift, drag, and momentum) - for 8,996 airfoil shapes, computed using the HAM2D CFD (computational fluid dynamics) model. The airfoil shapes were designed using the separable shape tensor parameterization that encodes two-dimensional shapes as elements of the Grassmann manifold. This data-driven approach learns two independent spaces of parameter from a collection of sample airfoils. The first captures large-scale, linear perturbations, and the second defines small-scale, higher-order perturbations. For this data, we used the G2Aero database of over 19,000 airfoil shapes to learn a parameter space that captured a wide array of shape characteristics. We fixed the linear deformations to be the mean over the database and sampled new shapes over a four-dimensional parameter space of higher-order perturbation. This sampling approaches allows for isolated analysis of non-linear airfoil shape deformations while holding other aspects (e.g., airfoil thickness) approximately constant. The aerodynamic quantities for the generated airfoil were obtained using the HAM2D code, which is a finite-volume Reynolds-averaged Navier-Stokes (RANS) flow solver. We employ a fifth-order WENO scheme for spatial reconstruction with Roe's flux difference scheme for inviscid flux and second-order central differencing for viscous flux. A preconditioned GMRES method is applied for implicit integration. The Spalart-Allmaras 1-eq turbulence model is used for the turbulence closure, and the Medida-Baeder 2-eq transition model is applied to account for the effects of laminar turbulent transition. The airfoil grid is generated with a total of 400 points on the airfoil surface, the initial wall-normal spacing of y+ = 1, and an outer boundary located at 300 chord lengths away from the wall. The CFD simulations are performed at a freestream Mach number of 0.1, Reynolds number of 9M, and at two angles of attack, 4 deg. and 12 deg. The simulations were performed using the Bridges-2 system at the Pittsburgh Supercomputing Center in February 2023 as part of the INTEGRATE project funded by the Advanced Research Projects Agency - Energy in the U.S. Department of Energy. The data was collected, reformatted, and preprocessed for this OEDI submission in July 2023 under the Foundational AI for Wind Energy project funded by the U.S. Department of Energy Wind Energy Technologies Office. This dataset is intended to serve as a benchmark against which new artificial intelligence (AI) or machine learning (ML) tools may be tested. Baseline AI/ML methods for analyzing this dataset have been implemented, and a link to their repository containing those models has been provided. The .h5 data file structure can be found in the GitHub Repository resource under explore_airfoil_9k_data.ipynb.

9k↗
NASA NTRS1972

Potential applications of NASA-developed technology to problems of the environment.

The life-support mission of NASA has the same broad objectives as the national imperatives toward environmental restoration: pure air, clean water, and reuse of resources. The major difference is the vast scale of the environment, compared to the very small scale of spacecraft, even including the largest space stations now projected. For this reason, the devices developed for manned spacecraft life support will be of much less interest than the techniques that have emerged from NASA-sponsored research and development. Several immediate applications in air and water purification can be cited, and several other long-term potential applications may also be considered.

Ross, L. W.↗
NASA NTRS1972

Investigation of gaseous nuclear rocket technology

The experimental and theoretical investigations conducted during the period from September 1969 through September 1972 are reported which were directed toward obtaining information necessary to determine the feasibility of the full-scale nuclear light bulb engine, and of small-scale nuclear tests involving fissioning uranium plasmas in a unit cell installed in a driver reactor, such as the Nuclear Furnace. Emphasis was placed on development of RF simulations of conditions expected in nuclear tests in the Nuclear Furnace. The work included investigations of the following: (1) the fluid mechanics and containment characteristics of one-component and two-component vortex flows, both unheated and RF-induction heated; (2) heating of particle-seeded streams by thermal radiation from a dc arc to simulate propellant heating; (3) condensation and separation phenomena for metal-vapor/heated-gas mixtures to provide information for conceptual designs of components of fuel exhaust and recycle systems; (4) the characteristics of the radiant energy spectrum emitted from the fuel region, with emphasis on definition of fuel and buffer-gas region seed systems to reduce the ultraviolet radiation emitted from the nuclear fuel; and (5) the effects of nuclear radiation on the optical transmission characteristics of transparent materials.

Kendall, J. S.↗
NASA NTRS1973

Characteristics of a gelled liquid hyprogen polyphenylene oxide (PPO) foam open-cell insulation system, phase 1

A large scale gel production and storage facility and a small scale facility, the latter used for detailed visual examination of the gel/PPO foam interface, were developed. A subcontract was given to investigate techniques for the production of gelled liquid hydrogen, develop a process design for scale-up to a 1.89 cu m (500 gallon) gel production and storage facility, determine gel transfer characteristics, determine the solubility rate of gaseous helium in the gel, and investigate the gross gel/PPO foam interfacial phenomena. An inside-tank process for scaled-up production of gelled liquid hydrogen was selected. No detectable gel structure degradation occurred during repeated shearing. The viscosity of gelled liquid hydrogen at shear rates of 300/sec and higher is 2 to 5-fold greater than that of neat liquid hydrogen. No clogging problems were encountered during the transfer of gelled liquid hydrogen through warmed transfer lines. The solubility rate of helium in liquid hydrogen was significantly reduced by the presence of gel structure. The boil-off rates from gelled liquid hydrogen were reduced from 25 to 50 percent compared to those observed for the neat liquid hydrogen under compatible conditions. The polyphenylene oxide (PPO) foam insulation was found to be compatible with liquid ethane.

Source record↗
NASA NTRS1985

The speed of wave-wave interactions in the atmosphere

Resonant wave-wave interactions are considered. Studies of the interaction coefficient show that rapid transfer of wave action can take place in the disjoined parts of the spectrum for three processes, namely: elastic scattering, parametric subharmonic instability and induced diffusion. Of the three processes, the vertical shear plays a role in two. The vertical shear of a moderate scale interacts through elastic scattering to make the spectrum vertically symmetric. On the other hand, the vertical shear of a large scale interacts through induced diffusion and is responsible for diffusion in k sub z space. When interacting with a vertical shear, it is known that the vertical shear acts as a catalyst and is not involved in energy transfer. Consequently, in both elastic scattering and induced diffusion, the vertical shear does not gain or lose energy. Through parametric subharmonic instability the more energetic large-scale waves are feeding energy into moderate and small scale waves of an elevation angle of 60 deg or larger.

Yeh, K. C.↗
NASA NTRS1988

Auroral E-fields from DE-1 and -2 at magnetically conjugate points

The results of studies of the electric field measurements from the two Dynamics Explorer satellites are reviewed. There are times at which DE-2 measured electric fields at the auroral ionosphere while DE-1 obtained nearly simultaneous measurement at a higher altitude on the same magnetic field lines. When these electric fields are mapped to a common altitude it is found that the large-scale electric fields are similar, but the small-scale electric fields have a larger amplitude at the higher altitude. Through the use of Fourier analysis it is shown that these results are evidence for a magnetic field-aligned potential drop between the two satellites. While these results were made possible by the satellites' altitude separation, it is also possible to take advantage of the fact that the satellites may pass through the same geomagnetic location with a time separation. This was useful for confirming that sinusoidal electric field oscillations which were detected near one conjunction were due to spatial rather than temporal variations, since similar oscillations were found at the same location at different times. The observed spatial oscillations can be explained by a simple model of magnetosphere-ionosphere coupling.

Weimer, D. R.↗