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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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Combining broad-beam circuit level SEU response with ion microprobe tests on single silicon germanium heterojunction bipolar transistors allows for a better understanding of the charge collection mechanisms responsible for SEU response of HBT technology.
By developing and enhancing various services and tools, the GES DISC provides users with the capability to access and visualize data, and to make comparisons of data from multiple sensor and models via a number of cross-discipline projects. Discovering Data via Faceted Web Interface Web interface to data products and services Search and Download mechanisms Dataset Landing Pages Accessing Data through Interoperable Services: GDS – GrADS Data Server OPeNDAP - Open-source Project for a Network Data Access Protocol WMS – OGC service GIS connector – allowing IS tools to access data easier (coming soon) HTTPS -- direct online access Downloading Data Basics: Subset and egridding Service – Parameter, Spatial, Time, Vertical, Mean averaging, format conversion, and regridding for L3/L4 gridded data Swath Data Subsetter – Parameter, spatial subset of L2 /L1 data. Visualizing Data Online: Giovanni –Visualization and Analysis L3/L4 gridded data AIRS NRT Viewer – AIRS near-real-time DQVis – L2 data quality visualization
We report on the linear relationship between the durations of two types of electromagnetic emissions associated with shocks driven by coronal mass ejections: sustained gamma-ray emission (SGRE) and interplanetary type II radio bursts. The relationship implies that shocks accelerate approximately 10 kiloelectronvolts electrons (for type II bursts) and more than 300 megaelectronvolts protons (for SGRE) roughly over the same duration. The SGRE events are from the Large Area Telescope (LAT) on board the Fermi satellite, while the type II bursts are from the Radio and Plasma Wave Experiment (WAVES) on board the Wind spacecraft. Here we consider five SGRE events that were not included in a previous study of events with longer duration (more than 5 hours). The five events are selected by relaxing the minimum duration to 3 hours. We found that some SGRE events had a tail that seems to last until the end of the associated type II burst. We pay special attention to the 2011 June 2 SGRE event that did not have a large solar energetic particle event at Earth or at the STEREO spacecraft that was well connected to the eruption. We suggest that the preceding CME (Coronal Mass Ejection) acted as a magnetic barrier that mirrored protons back to Sun.
We explore and elucidate physical failure mechanisms in a 4H-SiC, high voltage, superjunction (SJ) vertical DMOSFET from a single heavy ion strike using three-dimensional electro-thermal transient simulations. The single-event burnout (SEB) failure is thermal runaway from second breakdown, initiated by impact ionization and terminated with mesoplasma formation, at the center of the P-pillar/N+ substrate interface. We also demonstrate that the SEB performance of this SiC SJ DMOSFET is insensitive to the pillar width but sensitive to the strike location with ion strike at the P-pillar causing SEB at a lower blocking voltage than at the N-pillar. Compared to commercially available 1.2 kV blocking-rated non-SJ DMOSFETs, which have been demonstrated to survive SEB up to 525 V, the SJ DMOSFET increases SEB survival threshold voltage (VSEB) by a factor of 2.2, making it close to 1200 V, while the on-resistance is increased by only 11%. Using our recently developed figure of merit (FoM), which considers the trade-off between VSEB and on-state performance, we find that the SiC SJ DMOSFET achieves a FoM that is 14 times better, making it superior to conventional 1.2 kV SiC DMOSFETs for long-term radiation-tolerant operation in space applications.
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Beam-induced backgrounds at high-luminosity $e^+e^-$ colliders, such as the FCC-ee, are dominated by incoherent pair creation (IPC), and require computationally expensive simulations with dedicated Monte Carlo (MC) event generators. Reliable detector and machine-detector interface studies necessitate event samples that are several orders of magnitude larger than what is practically attainable with existing MC. To alleviate this bottleneck, we present D$e^+e^-$ffusion, a denoising diffusion probabilistic model that operates as a permutation-equivariant, set-valued surrogate for fast IPC simulation. Trained on a small GuineaPig++ sample, D$e^+e^-$ffusion faithfully reproduces the marginal and joint kinematic, angular, and positional distributions of all three IPC production processes. In addition, we assess the fidelity at the detector level by propagating both Geant4 and D$e^+e^-$ffusion events through a Geant4 simulation of the CLD vertex detector and by training a transformer-based two-sample classifier; the classifier achieves an area under the ROC curve of $0.553 \pm 0.016$. The trained model generates events nearly four orders of magnitude faster than Geant4, paving the way for a fast-simulation surrogate for FCC-ee design studies.
Here, this paper studies robust event classification using imperfect real-world phasor measurement unit (PMU) data. By analyzing the real-world PMU data, we find it is challenging to directly use this dataset for event classifiers due to the low data quality observed in PMU measurements and event logs. To address these challenges, we develop a novel machine learning framework for training robust event classifiers, which consists of three main steps: data preprocessing, fine-grained event data extraction, and feature engineering. Specifically, the data preprocessing step addresses the data quality issues of PMU measurements (e.g., bad data and missing data); in the fine-grained event data extraction step, a model-free event detection method is developed to accurately localize the events from the inaccurate event timestamps in the event logs; and the feature engineering step constructs the event features based on the patterns of different event types, in order to improve the performance and the interpretability of the event classifiers. Based on the proposed framework, we develop a workflow for event classification using the real-world PMU data streaming into the system in real time. Using the proposed framework, robust event classifiers can be efficiently trained based on many off-the-shelf lightweight machine learning models. Numerical experiments using the real-world dataset from the Western Interconnection of the U.S power transmission grid show that the event classifiers trained under the proposed framework can achieve high classification accuracy while being robust against low-quality data.
Atmospheric rivers (ARs), filaments of intense atmospheric moisture transport, play a significant role in delivering moisture poleward into the Arctic and triggering weather extremes. Although previous studies have focused on large‐scale circulations driving these events, this study investigates ARs through attributing their moisture sources using the Community Atmosphere Model version 5 (CAM5) with moisture‐tagging capability. Examining ARs in the Atlantic and Pacific sectors of the Arctic separately revealed distinct contributions from remote versus local, and ocean versus land, moisture sources. Unlike non‐AR events, Arctic ARs primarily draw moisture from their respective ocean basins in lower‐latitude regions during the cold season, and shift to land sources in the warm season. Cold‐season ARs in the Atlantic and Pacific sectors source 73.2% and 85.3% of their moisture from their respective ocean basins at lower latitudes, however warm‐season contributions decrease to 41.3% and 29.4%. In contrast, mid‐ and high‐latitude continents combined contribute 40.1% and 51.3% in the warm season. Trajectory clustering analysis shows that AR moisture sources depend on both their genesis regions and transport pathways. In recent decades, the Arctic has experienced a moistening trend in both the cold and warm seasons. Our results suggest that local and remote sources equally drive the observed cold‐season moistening, whereas remote sources predominantly drive the warm‐season moistening. A better understanding of Arctic AR moisture sources under current climate conditions provides valuable insights into their potential future changes amid the projected heterogeneous northern hemispheric warming.
The effects of space ionizing radiation on polymers is investigated in terms of operative physical and chemical processes. A useful model of charged particle impact with a polymer was designed. Principle paths of molecular relaxation were identified and energy handling processes were considered. The focus of the study was on energy absorption and the immediately following events. Further study of the radiation degradation of polymers is suggested.
The solar particle events of 18 November 1968, 25 February 1969, and 30 March 1969 were studied using data from the detector system aboard the lunar orbiting satellite Explorer 35. Protons, alpha particles, and Z or = 3 nuclei were registered in the solid state detector of the system. Interplanetary propagation, particle anisotropy, and the intensity ratios of protons to alpha particles and of alpha particles to C, N, and O nuclei above a common specific energy of 0.5 MeV/nucleon were studied. Diffusion coefficients and decay constants for the three events are given, as well as magnitudes and directions of anisotropies.
This paper considers two dynamic load models that are widely used in industry to account for induction motor behavior: CMLD and CLOD. These models must be parametrized for the specific utility system in a general way so that they can be used in planning studies and provide a conservative but realistic representation of load behavior. This study considers a measurement-based approach to tuning both models. The load modeling study compares the response of the tuned models to generic candidate models using historical events. This study considers one area-based subsystem to simplify the modeling approach and reduce the number of models required for simulations. Additionally, because dynamic load models often produce similar results for different sets of parameters, a sensitivity study was conducted to assess the parameter impacts on the voltage response. The sensitivity study covers the parameters that are tuned using event measurements. The process to estimate the parameters uses the particle-swarm optimization algorithm. Overall, the performance of the tuned model more accurately captures recovery voltage, delayed recovery, and settling voltage than its predecessor models while not being overly tuned so that it remains general for peak summer conditions.
The measured instrumental background of the XRS calorimeter spectrometer of Suzaku had several sources, including primary cosmic rays and secondary particles interacting with the pixels and with the silicon structure of the array. Prior to the launch of Suzaku, several data sets were taken without x-ray illumination to study the characteristics and timing of background signals produced in the array and anti-coincidence detector. Even though the source of the background in the laboratory was different from that in low-earth orbit (muons and environmental gamma-rays on the ground versus Galactic cosmic-ray (GCR) protons and alpha particles in space), the study of correlations and properties of populations of rare events was useful for establishing the preliminary screening parameters needed for selection of good science data. Sea-level muons are singly charged minimum-ionizing particles, like the GCR protons, and thus were good probes of the effectiveness of screening via the signals from the anti-coincidence detector. Here we present the first analysis of the on-ground background of the SXS calorimeter of Astro-H. On XRS, the background prior to screening was completely dominated by coincident events on many pixels resulting from the temperature pulse arising from each large energy deposition (greater than 200 keV) into the silicon frame around the array. The improved heat-sinking of the SXS array compared with XRS eliminated these thermal disturbances, greatly reducing the measured count rate in the absence of illumination. The removal of these events has made it easier to study the nature of the residual background and to look for additional event populations. We compare the SXS residual background to that measured in equivalent ground data for XRS and discuss these preliminary results.
NASA's climate reanalysis datasets from the Modern Era Retrospective-analysis for Research and Applications, Version 2 (MERRA-2) contains numerous long-term atmosphere, land, and ocean data products from 1980-present. MERRA-2 datasets, such as precipitation, soil moisture, and temperature, have been used widely to study extreme events. The native archived MERRA-2 data files are day-file (hourly time interval) and month-file, containing up to 125 parameters in one file. Due to the large number of data files and volumes, it is challenging for users, especially the applications research community, to handle the original hourly data files for long time periods to analyze extreme events. In this presentation, we review MERRA-2 data for studies of extreme conditions, and demonstrate analytic services at the NASA Goddard Earth Sciences Data and Information Services Center (GES DISC). One of the current operational services, 'subsetter', allows users to download only specific data of interest, i.e. data selected by parameter, region, and time period. New services are under development that will provide more 'on-the-fly' statistical calculations when downloading data; improve efficiency when accessing long time-series data. We will provide additional "How-to" resources that include step-by-step instructions on data access and usage. We have tested restructuring of day-files in an optimized data cube, which has significantly improved system performance for accessing long time-series. Overall performance is associated with cube size and structure, data compression method, and how the data are accessed. The optimized data cube structure will enable better online analytic services for statistical analysis and extreme events mining. To demonstrate the service, we use an extreme drought associated with the anomalous 2016 monsoon over southern Asia. This prototype time-series service may be augmented in the cloud infrastructure in the future.
The current shift in generation mix from fossil fuel plants towards variable and intermittent renewable energy sources is poised to create a future grid with reduced physical inertia and mismatch between generation and demand. Embedded storage, which is a concept of a coordinated network of storage units sited at the interface between the transmission and distribution system, is proposed as a mechanism to provide a buffer between generation and demand. This paper proposes an automated framework to model and integrate embedded storage in large-scale power systems with industry-grade grid-following (GFL) and grid-forming (GFM) control technologies. More importantly, the developed framework is used to explore the impacts of embedded storage control, penetration, location, and capacity in providing fast frequency response to the grid under contingency events such as generator trips and faults. The framework and study are conducted using the transient-stability simulation tool PSS/E and a realistic model of the Puerto Rico grid as a chosen test system. The simulation results show that GFL and GFM embedded storage, distributed throughout the system, with sufficient penetration and capacity, can effectively improve primary frequency response of the system under the studied contingency events.
Research development in the Charged Particle Lunar Environment Experiment (CPLEE) is reported. The CPLEE is ion-electron spectrometer placed on the lunar surface for the purpose of measuring charged particle fluxes impacting the moon from a variety of regions and to study the interactions between space plasmas and the lunar surface. The principal accomplishments reported include: (1) furnishing design specifications for construction of the CPLEE instruments; (2) development of an advanced computer-controlled facility for automated instrument calibration; (3) active participation in the deployment and past-deployment operational phases with regard to data verification and operational mode selection; and (4) publication of research papers, including a study of lunar photoelectrons, a study of plasmas resulting from man-made lunar impart events, a study of magnetotail and magnetosheath particle populations, and a study of solar-flare interplanetary particles.
Impulsive solar energetic particle (SEP) events are studied to: (1) describe a distinct class of SEP ion events observed in interplanetary space, and (2) test models of focused transport through detailed comparisons of numerical model prediction with the data. An attempt will also be made to describe the transport and scattering properties of the interplanetary medium during the times these events are observed and to derive source injection profiles in these events. ISEE 3 and Helios 1 magnetic field and plasma data are used to locate the approximate coronal connection points of the spacecraft to organize the particle anisotropy data and to constrain some free parameters in the modeling of flare events.
The author has identified the following significant results. The program to study short-lived events with the ERTS-1 satellite has evaluated 97 events reported by the Center for Short-Lived Phenomena. Forty-eight of these events were listed as candidates for ERTS-1 coverage and 8 of these were considered significant enough to immediately alert the ERTS operation staff by telephone. Studies of the images received from six events indicate that useful data on short-lived events can be obtained from ERTS-1 that would be difficult or impossible to obtain by other methods.
The short-term (about 1 min) events during two consecutive substorms on March 23 1979 have been studied using high time resolution measurements of magnetic and electric fields and of the kiloelectronvolt electron flux at X about -21 R(e). Data obtained make it possible to describe the localized magnetic structures transported or propagated within the plasma sheet and to identify these events as plasma sheet nightside magnetic flux transfer events (NFTEs). The best examples of the NFTEs found so far are all observed in a thin portion of plasma sheet where the contraction of the reconnected field lines dominates over the oppositely directed pressure gradient force. Systematic differences in the magnetic variations observed at ISEE-1 and 2 indicate current concentration at the outer plasma sheet boundary during the passage of a NFTE.