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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 109 records · Page 6
All sourcesNASA NTRSDOE OSTI
NASA NTRS1992

Accelerated cometary ions observed downstream of the Comet Halley bow shock

Results are presented of fluxes of energetic ions with energies exceeding 100 keV that were detected upstream of the bow shock of Comet Halley by the Tuende instrument on board the VEGA 1 spacecraft. Downstream of the shock, ion fluxes in the energy range 100 to 180 keV were observed. The measured ion fluxes were transformed into distribution functions in the solar wind frame using a variety of assumptions concerning the energy dependence of the distribution function and the identity of the ion species. The derived distribution function upstream of the shock falls off steeply with energy between 100 and 150 keV, with an effective temperature of about 7 keV or spectral index of about -15. The distribution function increases with decreasing cometocentric distance, on average, reaching a maximum at the bow shock. The measured distribution functions are compared with those obtained by similar instruments on Giotto and ICE as well as with the predictions of several theoretical models that employ different acceleration mechanisms.

Kecskemety, K.↗
NASA NTRS1993

Dynamics of the atmospheres of the outer planets - Post-Voyager measurement objectives

Current knowledge about dynamics and thermal structure on the outer planets is reviewed with the aim of identifying important measurements which should be made in the post-Voyager era. The existence of jets and cloud bands is the puzzle that underlies all others. Discussion focuses on the particular case of Jupiter because documentation is most complete. Recent dynamical work has successfully reproduced much of the behavior of jets and spots with simple models that contain few parameters. It is argued that the gross dynamical parameters, such as density stratification and rotation rate, are the keys to their behaviors, rather than the particular specifics of radiative forcing, cloud distributions, thermodynamic transformations. Voyager data have shown that the jet systems decay with height in the region above the visible clouds. Therefore the highest priority must be given to establishing dynamical parameters that characterize levels within and beneath the clouds. These require determination of the deep structure of the jets, of the density stratification, and of the horizontal density contrasts. The deep regions are not easily accessible, and these measurements present challenging opportunities. Indirect inferences about the controlling processes may sometimes be possible by observing waves and other activity in the more easily accessible stratosphere, and some of these issues are also discussed.

Gierasch, Peter J.↗
NASA NTRS1993

EOS ground data systems: A description and interface overview

The Earth Observing System (EOS) is planned as a space-based measurement system, earth-science research program, and data and information system (EOSDIS). It will consist of several high data rate spacecraft with multiple earth sensing instruments which provide investigators with a thorough, longterm view of the earth's environment. Up to seven spacecraft may be supported at once, either in operational, checkout, or testing phases; and the average data rate from the EOS satellites in orbit at any one time is expected to be from 18 to 60 Mbps. Providing the data processing and flight operations support for EOS will be the EOSDIS Core System (ECS). The ECS will command and control the spacecraft; process and store the EOS data; provide access to the data for years; and support researchers. The data processing aspects of the ECS consist of a collection of Distributed Active Archive Centers (DAAC's) which perform the product generation, data archive and distribution, and information management services. Flight operations aspects will be provided by the EOS Operations Center, by instrument control centers, and by widely distributed instrument support terminals. The communications and system management aspects will be provided by the EOSDIS Science Network and the System Management Center. In addition to the EOS satellite data, other data sets from earlier earth science missions are also to be added to designated DAAC's. Other ground data systems which will provide support to EOS for acquiring, transporting, processing, and distributing the transformed spacecraft data are currently being defined or are being upgraded for the EOS era. These systems include the Space Network consisting of the Tracking and Data Relay Satellite System (TDRSS), the TDRSS Ground Terminals, and the Network Control Center as well as the night Dynamics Facility, the EOS Data and Operations System, and EOS Communications. This paper briefly describes data handling by the ECS, the support data systems, their interfaces, and their roles.

Smith, Gene↗
DOE OSTI2024

Game Theoretic Orchestration for Cooperation among Power Distribution System Applications

The evolving transformation with the proliferation of distributed energy resources and advanced metering, necessitates advanced distribution systems to integrate and orchestrate a large number of grid-edge devices while also serving multiple system-level objectives such as resilience, decarbonization, equity and other system mandates. The parallel deployment and control of resources towards achieving diverse objectives may lead to conflicts between applications that want to control overlapping sets of device setpoints, potentially leading to oscillatory behavior and suboptimal performance. This work aims at leveraging game theoretic framework to drive cooperative behavior among competitive applications. The work proposes a weighted-consensus based game design to facilitate conflict resolution through consensus-building iterations for modular platform. Simulation-based evaluation on a sample test system demonstrates the performance the proposed deconfliction strategy in resolving operational conflicts and achieving close-to-optimal trade off among the applications. Results also compare the proposed strategy with a distribution optimization approach and illustrate it effectiveness in diverse apps regardless of their design while also incentivizing apps with flexible design.

Advanced distribution operations, cooperation, app↗
NASA NTRS1990

The Cortex Transform as an image preprocessor for sparse distributed memory: An initial study

An experiment is described which was designed to evaluate the use of the Cortex Transform as an image processor for Sparse Distributed Memory (SDM). In the experiment, a set of images were injected with Gaussian noise, preprocessed with the Cortex Transform, and then encoded into bit patterns. The various spatial frequency bands of the Cortex Transform were encoded separately so that they could be evaluated based on their ability to properly cluster patterns belonging to the same class. The results of this study indicate that by simply encoding the low pass band of the Cortex Transform, a very suitable input representation for the SDM can be achieved.

Olshausen, Bruno↗
NASA NTRS1993

Wave generation by contaminant ions

Investigations dealing with the generation of waves by contaminant ions are reported. The studies included the properties of the velocity distribution function of such ions. It was found that it takes about one ion-cyclotron period for the distribution function to transform from a beam to a ring distribution. A linear instability analysis was performed to examine the possibility of wave excitation by an ion beam streaming perpendicular to the ambient magnetic field in an ionospheric type of plasma. A simulation code was developed to study the nonlinear behavior of the waves excited by beam and ring types of ion distributions. The code treats both electrons and ions as particles kinetically to also factor in the possible involvement of lower-hybrid waves.

Singh, N.↗
DOE OSTI2020

Dynamic re-equilibration controlled multi-step transformations in (Mn, Fe) 2 (P, Si) alloys

In (Mn, Fe) 2 (P, Si) alloys crystallographic first-order phase transformations enable strong coupling of magnetic and entropic properties, potentially leading to high-efficiency energy generation and refrigeration applications. Although hysteresis losses that limit these applications can be reduced through careful control of alloy composition, compositional tuning can also unfavorably influence transformation temperatures and magnetocaloric coupling strength. Hence, exploration of additional processing variables enabling independent control of transformation properties is crucial. In this work, we investigate the role of thermal history as an additional processing variable, exploiting thermally-activated mechanisms to control properties of non-diffusive transformations in (Mn, Fe) 2 (P, Si) alloys. In so doing, we report an unusual transformation-splitting phenomenon following annealing at intermediate times, where a single well-defined magneto-structural transformation evolves towards a multi-step transformation with individual steps occurring at multiple distinct temperatures. Here, on longer annealing at the same temperatures, single-step transformation behavior is recovered. Through additional magnetic and crystallographic characterization, we show that the thermal history-controlled multi-step behavior results from sluggish thermally-activated diffusion. The two-step transformation corresponds to non-equilibrium bimodal composition distributions in the transforming phase, and these develop through a dynamic re-equilibration process as the alloy passes relatively slowly between different thermal equilibria. Together, these results suggest that thermal history primarily controls the transformation properties of (Mn, Fe) 2 (P, Si) alloys indirectly through the composition of one or more transforming phases. Additional investigations are needed to develop thermal history processing for decoupling hysteresis control from other transformation properties.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
NASA NTRS1987

Particle field holography data reduction by Fourier transform analysis

The size distribution of a particle field hologram is obtained with a Fourier transformation of the Fraunhofer diffraction pattern of the reconstructed hologram. Off-axis absorption holograms of particle fields with known characteristics were obtained and analyzed with a commercially available instrument. The mean particle size of the reconstructed hologram was measured with an error of + or - 5 percent, while the distribution broadening was estimated within + or - 15 percent. Small sections of a pulsed laser hologram of a synthetic fuel spray were analyzed with this method thus yielding a spatially resolved size distribution. The method yields fast and accurate automated analysis of particle field holograms.

Hess, Cecil F.↗
DOE OSTI2020

Generation of waves in magnetized plasma [PowerPoint]

The presentation goes through assumptions made for the study, sections on plasma dispersion, whistler modes for RBR, excitation of plane waves with antenna, dipole vs loop antenna, verification of results, excitation of whistler waves with electron beams, assumptions for the model, distribution of current in space in general case, Fourier transform of current distribution, resonant excitation of waves, and ending with a discussion of generic debunching.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
NASA NTRS1985

Second-order Compton-Getting effect on arbitrary intensity distribution

Theoretical studies of energetic particles in space are often referred to a special frame of reference. To compare theory with experiment, one has to transform the particle distribution from the special frame to the observer's frame, or vice versa. Various methods have been derived to obtain the directional distribution in the comoving frame from the directional fluxes measured on a spacecraft. These methods have become progressively complicated as increasingly detailed directional particle data become available. A set of 2nd order correct formulae for the transformation of an arbitrary differential intensity distribution, expressed as a series of spherical harmonics, between any two frames in constant relative motion is presented. These formulae greatly simplify the complicated procedures currently in use for the determination of the differential intensity distribution in a comoving frame.

Ng, C. K.↗
DOE OSTI2021

OpenDSS-wrapper (Distribution System Co-simulator with Distributed Energy Resource Controls)

Electric grid transformation with the proliferation of distributed energy resources (DER), such as solar photovoltaic (PV), wind, advanced energy storage technologies, and electric vehicles, and the growing use of communication technologies in both transmission and distribution systems are increasing the need to capture the interactions among these systems. Advanced modeling, control, and simulation tools that can perform co-simulation of electric power systems with other domains become indispensable to accurately model these interactions. To address this need, we have developed a codebase that integrates an electric power distribution system simulator, DER models, and DER controls. The codebase is based on OpenDSS, a distribution system simulator, and an existing open source co-simulation framework called HELICS. The contribution and uniqueness of the proposed codebase is that it tailors the generic HELICS framework specifically for distribution grid-related applications. The codebase includes an OpenDSS wrapper that controls the simulation, implements advanced DER controls, and extracts power flows, voltages, and other power system element information from the the distribution network modeled in OpenDSS. Sample HELICS federates, including a federate for OpenDSS, are provided that can communicate messages through the HELICS interface. Sample federates can be modified and additional HELICS federates can be added by the user depending on their use case requirements. SEE ALSO: https://github.com/NREL/dss-cosim

Blonsky, Michael↗
DOE OSTI2025

Architectural Approaches for Integrating ADMS and DERMS: Challenges, Comparisons, and Real-World Use Cases

The electrical distribution landscape is rapidly transforming due to the proliferation of distributed energy resources (DERs) such as solar panels, wind turbines, battery storage systems, combined heat and power units, and electric vehicles, introducing variability and uncontrollability that traditional grid operators are ill-equipped to manage. This transformation is further accelerated by advancements in Information and Communication Technology infrastructure that connects control centers with end devices, demanding automation and a deeper understanding of new technologies by utility personnel. Advanced grid control techniques using system-level optimization, Artificial Intelligence, and Machine Learning at the enterprise level and distributed level are evolving to address these issues. There is also an opportunity to utilize the enormous data created by these new DER technologies in the grid. Advanced Distribution Management Systems (ADMS) and Distributed Energy Resource Management Systems (DERMS) are critical in addressing these challenges by automating grid operations and enhancing reliability. Given the relatively recent development of ADMS and DERMS, and the still relatively low level of ADMS and DERMS deployment in the industry, there is a notable deficiency in the comprehensive understanding of the challenges and benefits associated with these new technologies, especially with their complementary natures and integration architectures. This paper aims to bridge the knowledge gap in ADMS and DERMS integration, presenting three distinct integration architectures currently available, and discussing the challenges and benefits of each architecture to guide utilities, industry professionals, and researchers in optimizing grid management and decision-making processes for a resilient and efficient energy future.

24 POWER TRANSMISSION AND DISTRIBUTION↗
NASA NTRS2022

Seasonal Updraft Speeds Change Cloud Droplet Number Concentrations in Low Level Clouds Over the Western North Atlantic

To determine the impact of dynamic and aerosol processes on marine low clouds, we examine the seasonal impact of updraft speed w and cloud condensation nuclei concentration at 0.43 % supersaturation () on the cloud droplet number concentration (N(C)) of low-level clouds over the western North Atlantic Ocean. Aerosol and cloud properties were measured with instruments on board the NASA LaRC Falcon HU-25 during the ACTIVATE (Aerosol Cloud meTeorology Interactions oVer the western ATlantic Experiment) mission in summer (August) and winter (February–March) 2020. The data are grouped into different loadings, and the density functions of NC and w near the cloud bases are compared. For low updrafts (w < 1.3 m s−1), NC in winter is mainly limited by the updraft speed and in summer additionally by aerosols. At larger updrafts (w > 3 m s−1), NC is impacted by the aerosol population, while at clean marine conditions cloud nucleation is aerosol-limited, and for high it is influenced by aerosols and updraft. The aerosol size distribution in winter shows a bimodal distribution in clean marine environments, which transforms to a unimodal distribution in high due to chemical and physical aerosol processes, whereas unimodal distributions prevail in summer, with a significant difference in their aerosol concentration and composition. The increase of is accompanied with an increase of organic aerosol and sulfate compounds in both seasons. We demonstrate that NC can be explained by cloud condensation nuclei activation through upwards processed air masses with varying fractions of activated aerosols. The activation highly depends on w and thus supersaturation between the different seasons, while the aerosol size distribution additionally affects NC within a season. Our results quantify the seasonal influence of w and on NC and can be used to improve the representation of low marine clouds in models.

Simon Kirschler↗
NASA NTRS1988

Determination Of Grain-Size Distributions

Images of microstructures analyzed by transform methods. Report discusses determination of distributions of grain sizes by analysis of images of microstructures.

Generazio, Edward R.↗
DOE OSTI2020

Apparatus, method and system for imaging and utilization of SEM charged particles

A scanning electron microscope (SEM) system includes an SEM objective that emits an electron beam toward a sample, causing emission of charged particles including secondary electrons, Auger electrons, backscattered electrons, anions and cations. The SEM system includes electron optics elements that are configured to establish electric fields around the sample that accelerate charged particles toward a detector. A two-dimensional distribution of locations of incidence of the charged particles on the detector is indicative of energies of the charged particles and their emission angles from the sample. A three-dimensional spatial distribution of charged particles emitted from the sample is recovered by performing an Abel transform over the distribution on the detector. The energies and emission angles of the charged particles are then determined from the three-dimensional spatial distribution.

42 ENGINEERING↗
DOE OSTI2024

Normalizing flows for domain adaptation when identifying Λ hyperon events

Here this study focuses on the application of a normalizing flow as a method of domain adaptation when classifying physics data. Normalizing flows offer a way to transform data points between two different distributions. The present study investigates a novel method of transforming latent representations of physics data to a normal distribution and then to a physics distribution again. The final distribution models a simulated distribution. After being transformed, the data can be classified by a neural network trained on labeled simulation data. The present study succeeds in training two normalizing flows that can transform between data (or simulation) and a Gaussian distribution.

47 OTHER INSTRUMENTATION↗
DOE OSTI2023

Ensemble models for circuit topology estimation, fault detection and classification in distribution systems

This paper presents a methodology for simultaneous fault detection, classification, and topology estimation for adaptive protection of distribution systems. The methodology estimates the probability of the occurrence of each one of these events by using a hybrid structure that combines three sub-systems, a convolutional neural network for topology estimation, a fault detection based on predictive residual analysis, and a standard support vector machine with probabilistic output for fault classification. The input to all these sub-systems is the local voltage and current measurements. A convolutional neural network uses these local measurements in the form of sequential data to extract features and estimate the topology conditions. The fault detector is constructed with a Bayesian stage (a multitask Gaussian process) that computes a predictive distribution (assumed to be Gaussian) of the residuals using the input. Since the distribution is known, these residuals can be transformed into a Standard distribution, whose values are then introduced into a one-class support vector machine. The structure allows using a one-class support vector machine without parameter cross-validation, so the fault detector is fully unsupervised. Finally, a support vector machine uses the input to perform the classification of the fault types. All three sub-systems can work in a parallel setup for both performance and computation efficiency. In conclusion, we test all three sub-systems included in the structure on a modified IEEE123 bus system, and we compare and evaluate the results with standard approaches.

24 POWER TRANSMISSION AND DISTRIBUTION↗