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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 163 records · Page 9
All sourcesNASA NTRSDOE OSTI
NASA NTRS1990

Size, duration, and rate of growth of nocturnal lightning events appearing on space shuttle video tapes

An analysis of video tapes of nocturnal lightning events, taken aboard space shuttle flights STS-8, STS-9, STS-41D, and STS-51J, shows flashes with dimensions ranging from approximately 1 km by 1 km to 440 km by 110 km. Of particular interest are the flashes whose dimensions exceeded 100 km, as flashes of this size are seldom reported. In general, larger flashes were found to have longer durations, take longer to reach their maximum extent, and reach their maximum extent at a smaller percent of their total duration than smaller flashes. Sixty four percent of the flashes occurred with one to five other events appearing in the same video frame. These simultaneous events were an average of 60 km apart from each other. If a breakdown process is propagating between the simultaneous flashes, it would be travelling at a rate of 10(exp 5)m/sec. Plots of the area of an event over its duration show peaks in the area curve which may be indicative if lightning strokes. There was an average of 3.6 peaks per flash. In general, the longer the flash duration, the more peaks there were in the area curve. The area curves of the lightning events fall into one of five shape categories. It is suggested that the shape of the area curve may indicate whether an event is an intracloud or cloud to ground lightning flash. Some of the lightning events had a persistent bright spot. These events had an average duration which was greater than that of events without the bright spot. On average, the bright spot events had a maximum area which was larger than that of the flashes without the bright spot.

Breslawski, Christine↗
NASA NTRS1990

Energetic particle abundances in solar electron events

The results of a comprehensive search of the ISEE 3 energetic particle data for solar electron events with associated increases in elements with atomic number Z = 6 or greater are reported. A sample of 90 such events was obtained. The events support earlier evidence of a bimodal distribution in Fe/O or, more clearly, in Fe/C. Most of the electron events belong to the group that is Fe-rich in comparison with the coronal abundance. The Fe-rich events are frequently also He-3-rich and are associated with type III and type V radio bursts and impulsive solar flares. Fe-poor events are associated with type IV bursts and with interplanetary shocks. With some exceptions, event-to-event enhancements in the heavier elements vary smoothly with Z and with Fe/C. In fact, these variations extend across the full range of events despite inferred differences in acceleration mechanism. The origin of source material in all events appears to be coronal and not photospheric.

Reames, D. V.↗
NASA NTRS2005

Solar Type II Radio Bursts and IP Type II Events

We have examined radio data from the WAVES experiment on the Wind spacecraft in conjunction with ground-based data in order to investigate the relationship between the shocks responsible for metric type II radio bursts and the shocks in front of coronal mass ejections (CMEs). The bow shocks of fast, large CMEs are strong interplanetary (IP) shocks, and the associated radio emissions often consist of single broad bands starting below approx. 4 MHz; such emissions were previously called IP type II events. In contrast, metric type II bursts are usually narrowbanded and display two harmonically related bands. In addition to displaying complete dynamic spectra for a number of events, we also analyze the 135 WAVES 1 - 14 MHz slow-drift time periods in 2001-2003. We find that most of the periods contain multiple phenomena, which we divide into three groups: metric type II extensions, IP type II events, and blobs and bands. About half of the WAVES listings include probable extensions of metric type II radio bursts, but in more than half of these events, there were also other slow-drift features. In the 3 yr study period, there were 31 IP type II events; these were associated with the very fastest CMEs. The most common form of activity in the WAVES events, blobs and bands in the frequency range between 1 and 8 MHz, fall below an envelope consistent with the early signatures of an IP type II event. However, most of this activity lasts only a few tens of minutes, whereas IP type II events last for many hours. In this study we find many examples in the radio data of two shock-like phenomena with different characteristics that occur simultaneously in the metric and decametric/hectometric bands, and no clear example of a metric type II burst that extends continuously down in frequency to become an IP type II event. The simplest interpretation is that metric type II bursts, unlike IP type II events, are not caused by shocks driven in front of CMEs.

Cane, H. V.↗
NASA NTRS2011

A Summary of the Flux-Rope CDAW events

In this paper, I summarize some of the results obtained during previous CDAW on the events selected for analysis. The events were selected based on the following criteria: 1. The events must be well observed in the interplanetary medium as shock-driving interplanetary coronal mass ejections (ICMEs), 2. The ICMEs should have corresponding CMEs near the Sun, observed in white-light coronal images, and 3. The heliographic coordinates of the solar sources must be within 15 degrees from the Sun Center. In all, 24 magnetic cloud (MC) events and 35 non-MC evens were analyzed. Of the 35 non-MC events selected for analysis, it was possible to fit flux ropes to 31/35 events if different boundaries and multiple flux ropes are used. The four events without flux rope structure seem to be poor events (short duration, poor magnetic and plasma signatures). Coronal flux rope fitting suggests (at least for a subset) that non-MC events become non-central during propagation. It was also found that MCs have high charge states; half of the non-MC events also have high charge states. The direction parameter of CMEs seems to be high for MCs. All these results are consistent with the idea that alll CMEs may be flux ropes.

Gopalswamy, Natchimuthuk↗
NASA NTRS2012

On the Probability of Occurrence of Extreme Space Weather Events

By virtue of their rarity, extreme space weather events, such as the Carrington event of 1859, are difficult to study, their rates of occurrence are difficult to estimate, and prediction of a specific future event is virtually impossible. Additionally, events may be extreme relative to one parameter but normal relative to others. In this study, we analyze several measures of the severity of space weather events (flare intensity, coronal mass ejection speeds, Dst, and greater than 30 MeV proton fluences as inferred from nitrate records) to estimate the probability of occurrence of extreme events. By showing that the frequency of occurrence scales as an inverse power of the severity of the event, and assuming that this relationship holds at higher magnitudes, we are able to estimate the probability that an event larger than some criteria will occur within a certain interval of time in the future. For example, the probability of another Carrington event (based on Dst less than - 850 nT) occurring within the next decade is approximately 12%. We also identify and address several limitations with this approach. In particular, we assume time stationarity, and thus, the effects of long-term space climate change are not considered. While this technique cannot be used to predict specific events, it may ultimately be useful for probabilistic forecasting.

Riley, Pete↗
NASA NTRS2015

NASA Space Science Day Events-Engaging Students in Science

The NASA Space Science Day Event follows the same format of planning and execution at all host universities and colleges. These institutions realized the importance of such an event and sought funding to continue hosting NSSD events. In 2014, NASA Johnson Space Center ARES team has supported the following universities and colleges that have hosted a NSSD event; the University of Texas at Brownsville, San Jacinto College, Georgia Tech University and Huston-Tillotson University. Other universities and colleges are continuing to conduct their own NSSD events. NASA Space Science Day Events are supported through continued funding through NASA Discovery Program. Community Night begins with a NASA speaker and Astromaterials display. The entire community surrounding the host university or college is invited to the Community Night. This year at the Huston-Tillotson (HTU) NSSD, we had Dr. Laurie Carrillo, a NASA Engineer, speak to the public and students. She answered questions, shared her experiences and career path. The speaker sets a tone of adventure and discovery for the NSSD event. After the speaker, the public is able to view Lunar and Meteorite samples and ask questions from the ARES team. The students and teachers from nearby schools attended the NSSD Event the following day. Students are able to see the university or college campus and the university or college mentors are available for questions. Students rotate through hour long Science Technology Engineering and Mathematics (STEM) sessions and a display area. These activities are from the Discovery Program activities that tie in directly with k- 12 instruction. The sessions highlight the STEM in exploration and discovery. The Lunar and Meteorite display is again available for students to view and ask questions. In the display area, there are also other interactive displays. Angela Green, from San Jacinto College, brought the Starlab for students to watch a planetarium exhibit for the NSSD at Huston-Tillotson University. Many HTU mentors were leading activities in the display room such as build a comet, volcano layering and robotics manipulation. Students were exposed to a variety STEM career possibilities and information. The students could relate the displays and sessions to what they were learning in school. The HTU mentors made the connection clear for the students. The students ended the event with a mission design presentation. They were able to take what they had learned during the day and were able to create a mission. Students presented their Mission Design and gained confidence in STEM. Conclusion: NASA Space Science Day Events provides an out of school experiential learning environment for students to enhance their STEM curriculum and let students see a college campus. The experiences students gain from attending NSSD gives them the confidence to see themselves on a college campus, possibly majoring in a STEM degree, and understand the importance of completing school.

Foxworth, S.↗
NASA NTRSDate not supplied

A Comparison of Stratospheric Smoke Events Seen by SAGE II (1984-2005) and SAGE III (2017-2021)

The ongoing Stratospheric Aerosol and Gas Experiment aboard the International Space Station (SAGE III/ISS) has mostly occurred during a period of relatively low aerosol loading. At the same time, it has almost observed a number of small to moderate injections of volcanic material in the stratosphere from the Aoba/Ambae eruption of 2018 to that of Karymsky in 2022. In addition, two of the largest known smoke intrusions into the stratosphere have occurred during the SAGE III/ISS mission (the British Columbia fire of August 2017 and the Australian Wildfire Event of 2019/2020). At least two other much smaller smoke events have also been observed in the SAGE III data (California Creek in September 2020 and McKay Creek in June 2021). Particularly with the two large events, it is tempting to speculate that these events are increasing in intensity and frequency possibly due to ongoing climate change. Realistically, change is difficult to assess since instrument data sets that can be used for quantifying historical events can be quite different in what and where they provide measurements. This complicates comparing one event to another potentially separated by many years. An exception to this issues are the measurements by SAGE III/ISS and those of its predecessor SAGE II (1984-2005). Both use the same measurement strategy, measure aerosol extinction coefficient at 1020 nm, and have similar spatial/temporal coverage. Both instruments are known to observe smoke events in the stratosphere. However, both have the same low observation density characteristic of solar occultation such that near-global coverage takes almost a month and characterizing effectively instant events like smoke and volcanic events take a matter of weeks depending on the vagaries of where the observations are being made at a critical juncture unlike instruments with high temporal/spatial resolution like limb-scatter instruments such as OMPS and OSIRIS. The goal of this work will be to use the same analysis approach to both the SAGE II and SAGE III data and compare both the frequency and intensity of smoke events observed by these instruments. While we do not expect to be able to make conclusions about change between the periods, the analysis is a first step in interpreting changes in the contribution of smoke to the stratospheric aerosol budget between the time frames encompassed by these instruments.

L. W. Thomason↗
DOE OSTI2020

A semi-supervised machine learning detector for physics events in tokamak discharges

Databases of physics events have been used in various fusion research applications, including the development of scaling laws and disruption avoidance algorithms, yet they can be time-consuming and tedious to construct. This paper presents a novel application of the label spreading semi-supervised learning algorithm to accelerate this process by detecting distinct events in a large dataset of discharges, given few manually labeled examples. A high detection accuracy (> 85%) for H-L back transitions and initially rotating locked modes is demonstrated on a dataset of hundreds of discharges from DIII-D with manually identified events for which only 3 discharges are initially labeled by the user. Lower yet reasonable performance (~75%) is also demonstrated for the core radiative collapse, an event with a much lower prevalence in the dataset. Additionally, analysis of the performance sensitivity indicates that the same set of algorithmic parameters is optimal for each event. Furthermore, this suggests that the method can be applied to detect a variety of other events not included in this paper, given that the event is well described by a set of 0D signals robustly available on many discharges. Procedures for analysis of new events are demonstrated, showing automatic event detection with increasing fidelity as the user strategically adds manually labeled examples. Detections on Alcator C-Mod and EAST are also shown, demonstrating the potential for this to be used on a multi-tokamak dataset.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2020

Gravitational Microlensing Event Statistics for the Zwicky Transient Facility

Microlensing surveys have discovered thousands of events, with almost all events discovered within the Galactic bulge or toward the Magellanic Clouds. The Zwicky Transient Facility (ZTF), while not designed to be a microlensing campaign, is an optical time-domain survey that observes the entire northern sky, including the Galactic plane, every few nights. The ZTF observes ~10 9 stars in the g and r bands and can significantly contribute to the observed microlensing population. In this paper, we predict that the ZTF will observe ~1100 microlensing events in 3 yr of observing within 10° latitude of the Galactic plane, with ~500 events in the outer Galaxy (ℓ ≥ 10°). This yield increases to ~1400 (~800) events by combining every three ZTF exposures, ~1800 (~900) events if the ZTF observes for a total of 5 yr, and ~2400 (~1300) events for a 5 yr survey with postprocessing image stacking. Using the microlensing modeling software PopSyCLE, we compare the microlensing populations in the Galactic bulge and the outer Galaxy. We also present an analysis of the microlensing event ZTF18abhxjmj to demonstrate how to leverage these population statistics in event modeling. The ZTF will constrain Galactic structure, stellar populations, and primordial black holes through photometric microlensing.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

Projected increase in compound dry and hot events over global land areas

Abstract Under global warming, dry and hot events have been increasing in recent decades and are projected to increase in the future across global land areas. The impacts of compound dry and hot events may lead to increased stress to the natural and human systems than separate dry or hot events. Thus, quantitative assessments of global land areas affected by these compound events are needed to understand their risks. This study focuses on the variation in global land and cropland areas affected by compound dry and hot events for both historical and future periods using observations from Climatic Research Unit (CRU) and simulations from Coupled Model Intercomparison Project Phase 5 (CMIP5) climate models. Based on historical observations and simulations, a substantial increase in the spatial extent of these compound events was detected, especially since the 1980s. Climate model projections under the Representative Concentration Pathway (RCP) 8.5 scenario reveal that both global land and cropland areas affected by compound dry and hot events will increase to approximately 1.7–1.8 times by the end of the 21st century. Based on different thresholds of compound events, the spatial extent of global land areas during the June–July–August (December–January–February) season will increase by 12.38–17.20% (7.83–11.19%) in 2050–2099 relative to that in 1950–1999, and the spatial extent of global cropland areas will increase by 14.69–19.63% (9.60–14.48%). The increase in areas affected by compound dry and hot events may lead to more losses in different sectors in the future and more efforts are needed to cope with their potential impacts.

Wu, Xinying↗
DOE OSTI2020

A robust measure of event isotropy at colliders

We introduce a new event shape observable — event isotropy — that quantifies how close the radiation pattern of a collider event is to a uniform distribution. This observable is based on a normalized version of the energy mover’s distance, which is the minimum “work” needed to rearrange one radiation pattern into another of equal energy. We investigate the utility of event isotropy both at electron-positron colliders, where events are compared to a perfectly spherical radiation pattern, as well as at proton-proton colliders, where the natural comparison is to either cylindrical or ring-like patterns. Compared to traditional event shape observables like sphericity and thrust, event isotropy exhibits a larger dynamic range for high-multiplicity events. This enables event isotropy to not only distinguish between dijet and multijet processes but also separate uniform N-body phase space configurations for different values of N. As a key application of this new observable, we study its performance to characterize strongly-coupled new physics scenarios with isotropic collider signatures.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2023

River Geomorphology Affects Biogeochemical Responses to Hydrologic Events in a Large River Ecosystem

Shifts in the frequency and intensity of high discharge events due to climate change may have important consequences for the hydrology and biogeochemistry of rivers. However, our understanding of event-scale biogeochemical dynamics in large rivers lags that of small streams. To fill this gap, we used high-frequency sensor data collected during four consecutive summers from a main channel and backwater site of the Upper Mississippi River. We identified high discharge events and calculated event concentration-discharge responses for both physical-chemical (nitrate, turbidity, and fluorescent dissolved organic matter) and biological (chlorophyll-a and cyanobacteria) constituents using metrics of hysteresis and slope. We found a range of responses across events, particularly for nitrate. Although fluorescent dissolved organic matter (FDOM) and turbidity exhibited more consistent responses across events, contrasting hysteresis metrics indicated that FDOM was flushed to the river from more distant sources than turbidity. Biological responses (chlorophyll a and cyanobacteria) differed more between sites than physical and chemical constituents. Lastly, we found that the event characteristics best explaining concentration responses differed between sites, with event magnitude more frequently related to responses in the main channel, and antecedent wetness conditions associated with response variation in the backwater. Furthermore, our results indicate that event responses in large rivers are distinct across the diverse habitats and biogeochemical components of a large floodplain river, which has implications for local and downstream ecosystems as the climate shifts.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Identification of Important Phenomena for Light Water Reactors During Heat Transport System Failure Events in Integrated Energy Systems

This work adapts historical literature and existing phenomena identification and ranking tables (PIRT) to be applicable to a novel nuclear power plant (NPP) and chemical or thermal process integrated energy system (IES), particularly focusing on the process heat and heat transport system failure events that are not a concern during normal NPP operation but become vital when an IES is considered. Nuclear energy has been suggested to go beyond base-load applications and be used for hydrogen co-generation systems, amongst other IESs. Prior to the implementation of nuclear IESs, sufficient analysis must be performed on accident events to ensure public safety. The events considered were deemed important because of their potential to damage systems, structures, and components (SSCs). Process thermal events of concern include loss of heat load and temperature transient events. Loss of heat load events were characterized as having high importance and being well understood. Temperature transient events may be further categorized by the cyclic loading and harmonics phenomena. Cyclic loading issues were classified as medium to high importance with knowledge gaps existing regarding fatigue and low power operation, while harmonics phenomena were classified as low importance and are well understood. Heat transport system failure events of concern include intermediate and process heat exchanger failures, mass addition to reactor coolant, ingress of material from thermal manifold/energy storage, and loss of intermediate fluid. Furthermore, these events tended to be of high or medium importance, with some knowledge gaps needing to be filled for individual reactor systems due to unique designs.

Integrated Energy System (IES)↗
DOE OSTI2022

Graph Neural Networks for low-energy event classification & reconstruction in IceCube

IceCube, a cubic-kilometer array of optical sensors built to detect atmospheric and astrophysical neutrinos between 1 GeV and 1 PeV, is deployed 1.45 km to 2.45 km below the surface of the ice sheet at the South Pole. The classification and reconstruction of events from the in-ice detectors play a central role in the analysis of data from IceCube. Reconstructing and classifying events is a challenge due to the irregular detector geometry, inhomogeneous scattering and absorption of light in the ice and, below 100 GeV, the relatively low number of signal photons produced per event. To address this challenge, it is possible to represent IceCube events as point cloud graphs and use a Graph Neural Network (GNN) as the classification and reconstruction method. The GNN is capable of distinguishing neutrino events from cosmic-ray backgrounds, classifying different neutrino event types, and reconstructing the deposited energy, direction and interaction vertex. Based on simulation, we provide a comparison in the 1 GeV–100 GeV energy range to the current state-of-the-art maximum likelihood techniques used in current IceCube analyses, including the effects of known systematic uncertainties. For neutrino event classification, the GNN increases the signal efficiency by 18% at a fixed background rate, compared to current IceCube methods. Alternatively, the GNN offers a reduction of the background (i.e. false positive) rate by over a factor 8 (to below half a percent) at a fixed signal efficiency. For the reconstruction of energy, direction, and interaction vertex, the resolution improves by an average of 13%–20% compared to current maximum likelihood techniques in the energy range of 1 GeV–30 GeV. The GNN, when run on a GPU, is capable of processing IceCube events at a rate nearly double of the median IceCube trigger rate of 2.7 kHz, which opens the possibility of using low energy neutrinos in online searches for transient events.

47 OTHER INSTRUMENTATION↗
DOE OSTI2020

The geometry of signal space: a case study of direct mapping between seismic signals and event distribution

SUMMARY Under favourable circumstances, seismic waveforms corresponding to an ensemble of events related by a common, spatially distributed process collectively exhibit a regular, signal-space geometry. When events in the ensemble have a common, or nearly common, source mechanism, this geometry is a distorted image of the distribution of events in the source region. The signal-space image can be visualized using a relatively simple waveform alignment and projection operation. Ensemble waveform correlation measurements can be inverted to estimate the distribution of the events in the source region, up to an arbitrary rotation, reflection and scaling, with residual distortion. We demonstrate these concepts with synthetic waveforms and with observations of long-wall mining induced seismicity for which substantial ground truth information is available. Our experience with these data has implications for location, correlation detection and machine learning and possible application to studies of repeating events in induced, volcanic and glacial seismicity. Our results place limits on the widely held assumption that waveform correlation is a useful measure of event separation. We suggest that the constraints on event separation need to be evaluated in the context of a population of related events, whose waveforms sample the signal space image of the source region. A better indicator of event separation is the length of the shortest path in signal space along the image.

58 GEOSCIENCES↗
DOE OSTI2025

Bayesian event categorization matrix approach for explosion monitoring

Current efforts to correctly categorize natural events from suspected explosion sources with data that is collected by ground- or space-based sensors presents historical challenges that remain unaddressed by the Event Categorization Matrix (ECM) model. Smaller historical events (lower yield explosions) may have data available from fewer measurement techniques than are available today, and therefore, a historical event record can lack a complete set of discriminants. The covariance structures can also differ between such observations of event (source-type) categories. Both obstacles are problematic for the classic ECM model. Our work addresses this gap and presents a Bayesian update to the previous ECM model, termed the Bayesian Event Categorization Matrix model, which can be trained on partial observations and does not rely on a pooled covariance structure. We further augment the ECM model with Bayesian Decision Theory so that false negative or false positive rates of an event categorization can be reduced in an intuitive manner. To demonstrate improved categorization rates for the Bayesian Event Categorization Matrix model, we compare an array of Bayesian and classic models with multiple performance metrics using Monte Carlo experiments. We use both synthetic and real data. Our Bayesian models show consistent gains in overall accuracy and lower false negative rates relative to the classic ECM model. Here, we propose future avenues to improve Bayesian Event Categorization Matrix models’ decision making and predictive capability.

58 GEOSCIENCES↗
DOE OSTI2023

Evaluation of Atmospheric Conditions Leading to a Fumigation Event

During the afternoon of 30 January 2022, the Savannah River Site experienced unusual temperature conditions leading to a fumigation event that triggered safety alarms and caused considerable confusion about the cause of the event. Normally, it is assumed that fumigation events occur early in the day once surface heating has begun. While most fumigation events are related to the breakup of a nocturnal inversion, this event was related to synoptic atmospheric conditions, which provided a more unique scenario that led to the fumigation event. The unusual synoptic atmospheric conditions led to the downwash and fumigation of the elevated plume, causing a pollutant to mix rapidly to the surface. These conditions could have potentially harmed workers within the facility, since the plume was directed toward a building air intake system. Here, we seek to outline the conditions that led to this unusual fumigation event and provide results of two-dimensional (2D) wind modeling of the event to characterize these conditions for future operational guidance of the facility air intake systems. This work sets the groundwork for future high-resolution modeling to explore the mechanisms and thresholds affecting fumigation on the facility-specific short distance scales and improve forecasting of non-standard fumigation events to protect human health.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Weakly Supervised Event Classification Using Imperfect Real-world PMU Data with Scarce Labels

This paper studies event classification using imperfect real-world phasor measurement unit (PMU) data with scarce event types (labels). By investigating the real-world PMU data, it is observed that most real-world PMU data's event type is unknown, which makes it challenging to directly use such dataset to build event classifiers as existing classification techniques require high-quality training data with known event type (i.e., label). To address this challenge, a weakly supervised learning based event classification approach is developed, which can use noisy and low-quality PMU data for the training. First, data quality issues are fixed using data preprocessing techniques and then event features are constructed from the PMU data. Using these features, a series of labeling functions are learnt to generate initial estimates of the labels of large amounts of unlabeled PMU data. As the labeling functions are learnt using the same data with scarce labels, the label estimates from the labeling functions can be correlated, noisy, and bias. To enhance these initial estimates, a generative model is developed to characterize the dependencies among the estimated labels, based on which better labels are obtained for training event classifiers. Numerical experiments using the real-world dataset from the Western Interconnection of the U.S. power transmission grid show that the proposed weakly supervised event classifier trained using the dataset with only 5% labeled data can achieve 78.4% classification accuracy.

Liu, Yunchuan↗